Colloquiam: Documents published in 2022

Data-Driven Reduced Order Modeling for Aerodynamic Flow Predictions

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:06:48 +0100

During each aircraft program a vast amount of aerodynamics data has to be generated to judge performance, structural loads as well as handling qualities. Within the past years the usage of computational fluid dynamics has significantly increased providing accurate insights into aircraft behaviour at early design stages and therefore at least partially enabled the mitigation of costly design changes. However, fully relying on high fidelity aerodynamic data is still computational prohibitive. Hence, data-driven models have gained an increasing attention in recent years. These methods not only provide continuous models but also enable the inclusion of highly accurate aerodynamic results in time-critical environments. This paper aims at applying deep learning techniques to derive such models and compare them to state of the art reduced order modeling techniques. In particular, three deep learning methods, a Multilayer perceptron for distribution predictions, a Multi-layer perceptron for pointwise predictions and an Autoencoder coupled with an interpolation technique are compared to Proper Orthogonal Decomposition and Isomap with latent space interpolation. For all methods an efficient methodology to determine hyperparameters is outlined and applied. Results are presented for an Airbus provided XRF1 dataset which includes surface pressure distributions at various Mach numbers and angles of attack.

Transition of separated flow over a bump under unsteady inflow conditions

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:06:26 +0100

Laminar flow separation has detrimental effects on the aerodynamics and performance of low pressure turbines (LPT). Flow separation is caused by the presence of adverse pressure gradient condition on the upper side of the blade past the suction peak, and is followed by laminar-to-turbulent transition and the subsequent turbulent mean reattachment due to the enhanced mixing. These phenomena characterise the size and dynamics of the separated flow, which are primarily dominated by the laminar-turbulent process. This study examines the influence of periodically-varying inflow conditions on the separated flow over a bump geometry at low Reynolds numbers. The geometry and flow conditions represent the upper surface of small LPT during high-altitude of flight. Direct numerical simulations are performed, in which a harmonic variation of the inlet total pressure is imposed, as a rough approximation of the passage of the upstream blade's wake. Three different frequencies with identical amplitude of the total pressure are simulated. The dynamics of the separated shear layer and the transition process are studied by separating the flow components correlated and un-correlated to the inflow frequency. Even moderate frequencies are found to have a strong effect in reducing the averaged size of the separated flow region, thus reducing the losses.

A comparison of machine learning methods for pressure coefficient prediction of an aeronautical configuration

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:06:03 +0100

Machine learning entails powerful information processing algorithms that are relevant for modelling, optimization, and control of fluids. Currently, machine-learning capabilities are advancing at an incredible rate, and fluid mechanics is beginning to tap into the full potential of these powerful methods. Many tasks in fluid mechanics, such as reduced-order modelling, shape optimization and uncertainty quantification, may be posed as optimization and regression tasks. Machine learning can dramatically improve optimization performance and reduce convergence time. In this paper, the potential of tree-based machine learning techniques for the aerodynamic prediction of pressure coefficients of an AIRBUS XRF1 aircraft wing-body configuration has been assessed. For this purpose, a dataset including computational fluid dynamics (CFD) simulations has been employed to train the different models, with and without the use of proper orthogonal decomposition (POD) and having their hyperparameters values optimized to obtain the optimal subspace. A deep comparison of decision tree regressors and random forest algorithms has been performed, showing that the random forest regressor model performs better on all configurations.

Developing a DEM-Coupled OpenFOAM solver for multiphysics simulation of additive manufacturing process

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:24:43 +0100

Powder-based additive manufacturing technologies, specifically selective laser melting, are challenging to model due to the complex, interrelated physical phenomena that are present on multiple spatial scales, during the process. A key element of such models will be the detailed simulation of flow and heat transfer throughout the melt pool that is formed when the powder particles melt. Due to the high-temperature gradients that are generated inside the melt pool, the Marangoni force plays a key role in governing the flows inside the melt pool and deciding its shape and dimensions. On the other hand, the mass and heat transfer between the melt and the powder also has a significant role in shaping the melt pool at the edges. In this study, we modified an OpenFOAM solver (icoReactingMultiphaseInterFoam) coupled with an in-house developed DEM code known as eXtended Discrete Element Method or XDEM which models the dynamics and thermodynamics of the particles. By adding the Marangoni force to the momentum equation and also defining a laser model as a boundary condition for liquid-gas interface, the solver is capable of modeling the selective laser melting process from the moment of particle melting to the completion of the solidified track. The coupled solver was validated with an ice packed bed melting case and was used to simulate a multi-track selective laser melting process.

OpenFOAM model of fluid-structure interaction in dry wire drawing

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:23:42 +0100

A fluid-structure interaction model is employed to numerically investigate the interaction between the pressurized thin lubricant film and the radial, plastically deformed steel wire in a dry wire drawing process. A transient simulation is presented, with the implementation of a sliding fluid-structure interaction interface. Moreover, the fluid film has been calculated by the Navier-Stokes equations and the coupling with the wire model is performed by the IQN-ILS technique. This results on the one hand in the monitoring of the stresses and displacements of the structure and on the other hand in an observation of the hydrodynamic pressure build-up and wall shear stresses in the lubricant. Additionally, the evolution of the thickness of the fluid film is presented.

Investigation of the PANS Method for the Prediction of Aerodynamic Noise Around a Circular Cylinder

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:22:42 +0100

Aeroacoustics is the field of studying flow-induced sound, which results from the interaction of unsteady flow with solid structures, such as aircraft and automobiles. Different methods are available to achieve this, including theoretical, experimental, and computational methods. Due to the high costs of experiments, the concentration on computational methods has increased. Computational aeroacoustics (CAA), based on computational fluid dynamics (CFD), has received special attention from researchers because of its outstanding capability to get acceptable results with reasonable computational costs. The partially-Averaged Navier Stokes (PANS) method is a hybrid LES/RANS method based on dynamic resolution parameters. The SSVPANS method is a k---f based PANS method with an additional modeled equation for the resolved kinetic energy. This method has been implemented in FASTEST, an in-house finitevolume solver to compute the flows in complex applications. This study aims to investigate the aeroacoustic performance of the SSV-PANS method compared to a reference Large-eddy Simulation [1] regarding the computational accuracy and costs. To do this, hybrid method based on decomposing the fluid variables into incompressible hydrodynamics and compressible perturbation equations is used to study the aerodynamic noise. The aeroacoustic sources are computed from the incompressible flow field using the SSV-PANS method. In addition, the Kirchhoff wave extrapolation method is used to have an efficient evaluation of the far-field noise.

Development of a Framework for Internal Combustion Engine Simulations in OpenFOAM

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:21:40 +0100

High-accuracy simulations of internal combustion engines (ICE) allow deep insight into the physical processes of the different phases of the engine cycle: gas exchange, mixture formation, compression, combustion and emission formation. The commercial solvers for ICE simulations provide a full package which covers these areas. However, the user of such software is unable to look into the source code, making it impossible to implement new models or investigate possible implementation errors in the code, and costs arise due to licensing requirements for commercial solvers. Although the open source framework OpenFOAM already includes multiple classes and two solvers dedicated to internal combustion engine simulations, there is no way to move engine valves and piston simultaneously with its standard tools. Thus, this paper presents a new engine library for ICE simulations written for OpenFOAM. The new framework is capable of simulating a complete fired engine cycle. The piston and the valves are moved simultaneously. To address large deformations in the mesh, a methodology to avoid insufficient mesh quality was developed. Ignition and combustion is modeled with standard tools from OpenFOAM. To validate the method, the simulation results for the averaged in-cylinder quantities pressure, temperature and mass are compared with experimental data.

An energy-preserving unconditionally stable fractional step method on collocated grids

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:20:39 +0100

Preservation of energy is fundamental in order to avoid the introduction of unphysical energy that can lead to unstable simulations. In this work, an energy-preserving unconditionally stable fractional step method on collocated grids is presented as a method which guarantees both preservation of energy and stability of our simulation. Using an algebraic (matrix-vector) representation of the classical incompressible Navier-Stokes equations mimicking the continuous properties of the differential operators, conservation of energy is formally proven. Furthermore, the appearence of unphysical velocities in highly distorted meshes is also adressed. This problem comes from the interpolation of the pressure gradient from faces to cells in the velocity correction equation, and can be corrected by using a proper interpolation.

On the conservation of primary and secondary properties in the simulation of multiphase flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:20:19 +0100

The formulation of multiphase flows emanates from basic conservation laws: mass, momentum and energy. While these are embedded in the celebrated Navier-Stokes equations, none of these properties do necessarily hold when constructing a computational model, unless special care is taken in discretizing the different terms of the governing equations. The conservation of both primary (mass, momentum) and secondary (energy) quantities is not only relevant to mimic the dynamics of the system, but also computationally beneficial. Conservation of such quantities produce an enhanced physical reliability, removing most of the need for stabilization artifacts. In addition, discrete conservation implies numerical stability as well, producing inherently stable problems. Focusing on the capillary force, which is one of the most distinguishable features of multiphase flows, we present here our most recent developments in the quest for conservation. Departing from an inherently mass conservative method, in this work we sketch our previous developments to obtain an energy conservation and next we present our attempt at momentum. By carefully assessing the continuum formulation, we delve into the mathematical properties responsible for the conservation of linear momentum, which we then mimic in the regularized and discrete formulations.

An assessment of various discretizations of the energy equation in compressible flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:20:02 +0100

Nonlinear instabilities are one of the major problems in turbulence simulations. One reason behind this problem is the accumulation of aliasing errors produced by the discrete evaluation of the convective term. This can be improved by preserving the quadratic invariants in a discrete sense. However, another source of instabilities is the error due to an incorrect evolution of thermodynamic variables, such as entropy. An appropriate discretization of the energy equation is needed to address this issue. An analysis of the preservation properties of various discretizations of the compressible Euler equations is reported, which includes some of the most common approaches used in the literature, together with some new formulations. Two main factors have been identified and studied: one is the choice of the energy equation to be directly discretized; the other is the particular splitting of the convective terms, chosen among the Kinetic Energy Preserving (KEP) forms. The energy equations analyzed in this paper are total and internal energy, entropy, and speed of sound. All the cases examined are locally conservative and KEP, since this is considered an essential condition for a robust simulation. The differences among the formulations have been theoretically investigated through the study of the discrete evolution equations induced by the chosen energy variable, showing which quantities may be preserved. Both one-dimensional and two-dimensional tests have been performed to assess the advantages and disadvantages of the various options in different cases.

Development of a discontinuous Galerkin solver for the simulation of turbine stages

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:19:38 +0100

A high-order Discontinuous Galerkin (DG) solver is assessed in the computation of the flow through an Organic Rankine Cycle turbine nozzle and stage. The flow features are predicted with a RANS (Reynolds averaged NavierStoke) approach and the k-log() turbulence model in a multi reference frame, where interfaces between fixed and rotating zones are treated with a mixing plane approach, and non reflecting boundary conditions are used. Primitive variables based on pressure and temperature logarithms are adopted to ensure non-negative thermodynamic variables at a discrete level. The fluid can be modeled with the polytropic ideal gas law and the Peng-Robinson equation of state.

Modal analysis of a 3D gravitational liquid sheet

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:19:13 +0100

Modal analysis of three-dimensional gravitational thin liquid sheet flows, interacting with unconfined gaseous environments located on both sides of the liquid phase, is performed in the present work. Numerical data of this relevant two-phase flow configuration are obtained through the single-phase formulation and the Volume-of-Fluid (VOF) technique implemented in the flow solver Basilisk. This class of flows exhibits a variety of spatial and temporal relevant structures, both in free and forced configurations, that are investigated through the Spectral Proper Orthogonal Decomposition (SPOD). By means of such methodology, we explore the effect of two main governing parameters on the flow dynamics, namely the liquid sheet aspect ratio, AR = W/H, where H and W are the sheet inlet thickness and width, and the Weber number, We = lU2H/(2), in which U is the inlet liquid velocity, lthe liquid density, and the surface tension coefficient. Finally, for the highest aspect ratio value considered (AR = 40), we investigate the forced dynamics of the system excited by a harmonic perturbation in transverse velocity component applied at the inlet section, comparing results with ones arising from a purely two-dimensional analysis of the flow. The obtained results highlight the low rank behavior exhibited by the flow, suggesting that reduced order modeling could be particularly appealing to reduce complexity and computational effort in numerical simulation of this class of flows.

A fully-discrete entropy conserving/stable discretization for inviscid unsteady flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:18:53 +0100

The aim of this work is to contribute to the development of a high-order accurate discretization that is entropy conserving and entropy stable both in space and in time. To do this, the general framework is based on a high-order accurate discontinuous Galerkin (dG) method in space with entropy working variables, several entropy conservative and stable numerical fluxes and an entropy conserving modified Crank-Nicolson method. We present the first results, obtained with the discretizations here proposed, for two bi-dimensional unsteady viscous test-case: the Taylor-Green vortex and the double shear layer.

Influence of the turbulent wake downstream offshore wind turbines on larval dispersal: development of a new Lagrangian-Eulerian model

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:18:32 +0100

In the context of future offshore wind farms along the French coasts of the English Channel, the impacts of foundations on larval dispersal from bentho-pelagic species colonizing the hard substratum of artificial structures are studied in order to assess how the species connectivity could be modified by the farms. In particular, the effects of turbulent wake and horseshoe vortices are investigated. To this end, a new numerical approach is developed that combines the Eulerian model, OpenFoam, solving the 3D Navier-Stokes equations to compute the hydrodynamics, and the Lagrangian model, Ichthyop, based on an advection-diffusion equation to compute the larval trajectories. Firstly, some simple test cases are performed to validate the numerical coupling between OpenFoam and Ichthyop, such as the dispersion of larvae downstream a 2D cylinder in water. Secondly, the ability of OpenFoam turbulence models to simulate turbulent structures around monopile and gravity type foundations is evaluated. The RANS (Reynolds Averaged Navier-Stokes) k-omega SST turbulence model is chosen for the realistic application because it can reproduce the horseshoe vortices and turbulent wake with less computing time than the Smagorinsky LES (Large Eddy Simulation) model. Lastly, larval dispersal simulations for four benthic species and for a set of monopile and gravity foundations are performed.

Surrogate modeling of unsteady aerodynamic loads acting on a plunging airfoil

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:18:08 +0100

Cost-effective parameteric surrogate models of unsteady aerodynamic loads acting on a flapping wing are highly desirable. They would enable real time aerodynamic load prediction, multiobjective optimisation and optimal control of intelligent flapping wing flight devices. In the present work, a parametric surrogate modeling framework for unsteady aerodynamic loads based on a non-intrusive reduced order modeling approach is presented. The unsteady flow past a plunging 2D flat plate is considered where the aerodynamic load time histories are obtained for different plunging frequencies and amplitudes using a potential flow solver. The parametric non-intrusive reduced order model (p-NIROM) for the obtained loads is constructed using a combination of snapshot proper orthogonal decomposition (POD) for dimensionality reduction and a fully connected feed forward neural network (FCNN) for modeling the input parametric dependency. Both, linear and non-linear FCNN based p-NIROM are explored and compared on the basis of load time history reconstruction accuracy. The non-linear FCNN regression for the p-NIROM is observed to generalise well for unseen parametric instances as compared to the linear approach when a systematic data sampling strategy is adopted.

Linear and quadratic invariants preserving discretization of Euler equations

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:17:49 +0100

In the context of the numerical treatment of convective terms in compressible transport equations, general criteria for linear and quadratic invariants preservation, valid on uniform and non-uniform (Cartesian) meshes, have been recently derived by using a matrix-vector approach, for both finite-difference and finite-volume methods ([1, 2]). In this work, which constitutes a follow-up investigation of the analysis presented in [1, 2], this theory is applied to the spatial discretization of convective terms for the system of Euler equations. A classical formulation already presented in the literature is investigated and reformulated within the matrix-vector approach. The relations among the discrete versions of the various terms in the Euler equations are analyzed and the additional degrees of freedom identified by the proposed theory are investigated. Numerical simulations on a classical test case are used to validate the theory and to assess the effectiveness of the various formulations.

Validation on a new anisotropic four-parameter turbulence model for low Prandtl number fluids

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:17:27 +0100

This work aims to validate a new anisotropic four-parameter turbulence model for low-Prandtl number fluids in forced and mixed convection. Traditional models based on the gradient-diffusion hypothesis and Reynolds analogy are inadequate to simulate the turbulent heat transfer in low-Prandtl number fluids. Additional transport equations for thermal variables are required to predict the characteristic thermal time scale. In a four-parameter turbulence model, two additional transport equations are solved for the temperature variance and its dissipation rate. Thus, it is possible to formulate appropriate characteristic time scales to predict the near-wall and bulk behaviour of mean and turbulent variables. The isotropic version of the four-parameter model has been widely studied and validated in forced and mixed convection. We aim to extend the model validity by proposing explicit algebraic models for the closure of Reynolds stress tensor and turbulent heat flux. For the validation of the anisotropic four-parameter turbulence model, low-Prandtl number fluids are simulated in several flow configurations considering buoyancy effects and numerical results are compared with DNS data.

Numerical Testcases to Study Proudman Resonance Using Shallow Water Models

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:17:08 +0100

Proudman resonance is the dominant mechanism behind meteotsunamis. We develop a comprehensive set of testcases to validate numerical methods focusing on the performance with respect to represent mentioned resonance. With the test cases we assess the wave amplification in dependence of characteristics of the pressure perturbation, model parameters, model resolution, and bathymetry characteristics. We use the compilation of tests to validate an adaptive discontinuous Galerkin (DG) model for the two-dimensional non-linear shallow water equations. As the tests are highly sensitive to model resolution, we use the adaptive mesh capabilities of the model to locally refine the disturbance and thus gain considerable efficiency.

Correcting the discretization error of coarse grid CFD simulations with machine learning

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:16:49 +0100

Computational fluid dynamics is a cornerstone for the modern aerospace industry, providing important insights on aerodynamic analysis while reducing the need of expensive experiments and tests. Nevertheless, simulations of complex geometries are often performed on a discrete spatial domain too coarse to capture all relevant physical phenomena for the sake of lowering the computational cost. A consistent spatial discretization on so-called grids approximates the analytical solution of the partial differential equation with increasing number of discrete points. Such a grid refinement study is an expensive method to assess the general grid quality. This work shows that machine learning as a post-processing tool is capable of improving coarse grid simulations, even if not converged. The results show that three machine learning models varying in their complexity, namely the random forest, the neural network, and the graph neural network, are capable of finding patterns in coarse grid simulations. These patterns are used to predict the discretization error to approximate the field variables of interest of the corresponding fine grid simulation mapped onto the coarse grid. Initial training and testing is performed on the RAE2822 airfoil leading to corrected flow fields, improved surface integrals and coefficients, even when shocks are present. Additional tests are performed on the RAE5212 airfoil, showing the generalization limits of the trained models. The proposed method promises to reduce computational expenses while increasing the accuracy of the coarse grid results which works locally, e.g. it corrects the error for each cell individually and is therefore not restricted by the number of grid points. The presented results obtained by the machine learning models during post-processing are a promising baseline for more integrated developments, where the models will interact in a dynamic fashion with the flow solver to further improve coarse grid simulations.

SPDE-ConvNet: Predict stabilization parameter for Singularly Perturbed Partial Differential Equation

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:16:32 +0100

Singularly Perturbed Partial Differential Equations are challenging to solve with conventional numerical techniques such as Finite Element Methods due to the presence of boundary and interior layers. Often the standard numerical solution has spurious oscillations in the vicinity of these layers. Stabilization techniques are employed to eliminate these spurious oscillations in the numerical solution. The accuracy of the stabilization technique depends on a user-chosen stabilization parameter, where an optimal value is challenging to find. In this work, we focus on predicting an optimal value of the stabilization parameter for a stabilization technique called the Streamline Upwind Petrov Galerkin technique for solving singularly perturbed partial differential equations. This paper proposes SPDE-ConvNet, a convolutional neural network for predicting stabilization parameters by minimizing a loss based on the cross-wind derivative term. The proposed technique is compared with the state-of-the-art variational form-based neural network schemes.

Simulation of massively separated flows and rotating machine flows using hybrid models

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:16:06 +0100

RANS, DES, hybrid RANS/DVMS and DDES/DVMS models are introduced in low dissipation schemes. They are compared for the simulation of vortex shedding flows around a NACA0021 at high angle of attack and a Caradonna-Tung helix.

Matrix properties associated with discrete conservation in flow simulations

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:15:46 +0100

Supraconservative discretization methods are studied which conserve primary (mass, momentum and internal energy) as well as secondary (total energy) invariants. In particular, the coefficient matrices which are related to such conservation properties are analyzed. This analysis holds for any discretization method with a volume-consistent scaling.

Energy-preserving stable computations of high-pressure supercritical fluids turbulence

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:15:26 +0100

High-fidelity computations of turbulent flows at high-pressure supercritical fluid conditions present significant challenges. Besides the inherent broadband nature of the flow, the rapid variation of thermophysical properties across the pseudo-boiling region can result in additional complexities in terms of strong localized density gradients, spurious pressure oscillations, non-linear behaviour of fluids, and amplification of aliasing errors. Different research groups have utilized distinct approaches to achieve numerical stability, mostly resorting to upwindbiased schemes, artificial dissipation and/or high-order filtering. However, in these strategies, stability is achieved at the expense of artificially suppressing part of the turbulent energy spectrum. In this regard, this work aims to explore the suitability, in terms of stability and accuracy, of recently proposed energy-preserving schemes for scale-resolving simulations of supercritical turbulence. For ideal gases, such type of methods have been demonstrated to provide stable and accurate computations of turbulence by preserving kinetic energy and/or other quantities of physical relevance. However, their extension to real-gas thermodynamic frameworks is still in its infancy, and consequently requires to be carefully investigated. To this objective, this work analyzes the performance of different classical and energy-preserving discretizations under ideal-gas conditions, and carries out an initial assessment of their performance at high-pressure supercritical fluid regimes. The results obtained indicate that their extension to real-gas thermodynamics is not straightforward, and consequently motivate the necessity to develop new solutions able to satisfy the desired stability and accuracy requirements.

A three-dimensional FVC scheme on non-uniform tetrahedron meshes: application to the 3D Euler equation

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:00:51 +0100

This study is about the construction of a numerical scheme of the predictor-corrector type in conservative form for solving general systems of conservation laws in multiple space dimensions on unstructured meshes. The work is a generalization of the one-dimensional finite volume characteristics (FVC) scheme and is related to the work of Fayssal Benkhaldoun and Mohammed Sead. The construction of the intermediate state is based on the method of characteristics, while the corrective stage recovers the conservation equations. The scheme is accurate to first order, monotonic and entropic; it avoids Riemann solvers at each interface; it also allows for improved accuracy order in time and space on unstructured three-dimensional meshes in the framework of the finite volume method. The scheme's performance is evaluated through a series of test benchmarks for the three-dimensional version of the Euler equations..

CFD validation of a controllable pitch marine propeller using a truly autonomous mesh generation with adaptive mesh refinement

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:00:32 +0100

The design of propellers for maritime propulsion systems has a long history of using Computational Fluid Dynamics (CFD) as result of the constant desire to improve efficiency. The complex physics in addition to the motion of the propellers pose several challenges to CFD investigations, in particular with regards to mesh generation. In view of addressing these challenges, the present work proposes an alternative approach, which employs an autonomous mesh generation based on a modified Cartesian cut-cell methodology with Adaptive Mesh Refinement (AMR). In this work, this approach is validated against the extensive open measurement data of the Potsdam Propeller Test Case (PPTC) from SVA Potsdam, which contains both open water tests as well as detailed transient velocity field measurements. Additionally, benefits of both steady-state and fully-moving transient approaches for propeller numerical analyses are discussed, together with a future outlook on cavitation phenomena within the presented framework.

Large Eddy Simulation of Primary Breakup Processes in Dual Fuel Internal Combustion Engines Using a Fully Compressible Multicomponent Approach

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 15:00:16 +0100

Direct numerical simulations of fully compressible multiphase flows in realistic dual fuel internal combustion engine (DFICE) components under realistic operating conditions requireenormous computational resources beyond the scope of current investigations. In order toreduce the computational complexity and computational costs, we come up with a simplifiedatomizing liquid sheet benchmark case. Our set-up is based on properties of the “SprayA-210675 model” with D=89.4μm of a DFICE. The reduced computational nozzle domainis 5D*0.5D*0.5D and the chamber domain is 15D*2.5D*0.5D in x, y, z direction. At the inlet ofthe reduced domain, liquid n-Dodecane and a mixture of Nitrogen and Methane formashearlayer, while the environment is initially filled with a gas mixture. Periodic boundaryconditions in spanwise directions and a symmetry boundary condition at the bottomsurfaceare prescribed. A viscous wall separates the two flows similar to the “SprayAnozzle”geometry and the corner between viscous wall and gas inlet is similar to the “SprayAnozzle”exit. The initial chamber and ambient pressure is 6MPa. Three computational grids (2.50million, 34.56 million, 67.50 million) are used to simulate the shear layer and toanalysethe predicted mixing processes depending on the grid resolution. The mesh resolutionisvaried between 1.788μm and 0.596μm. Velocity differences between the liquid n-Dodecaneand the gas mixture are 400m/s, 200m/s and 50m/s. We employ a numerical algorithm capable of handling fuel primary break-upandcompressibility of all involved phases. An Implicit Large Eddy Simulation approachforcompact stencils proposed by Egerer et al. [1] based on [2, 3] is used to model sub-gridstructures if the resolution is insufficient for DNS. A diffuse interface method is used, together with a barotropic

Effect of hydrogen addition to methane-air jet flame based on Sandia flame D

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:59:57 +0100

The present study investigates the effect of hydrogen addition to methane-air jet flame based on Sandia flame D.

A mixed midelity conceptual design process for Boundary Layer Ingestion concepts

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:59:38 +0100

Boundary Layer Ingestion (BLI) is a promising concept that helps improving aircraft aeropropulsive performance. However, it remains difficult to bring together OAD (Overall Aircraft Design) process and high-fidelity tools due to the time of response of complex disciplinary tools. ONERA has thus developed a mixed fidelity approach inside its in-house OAD platform. The purpose is to mix conventional and robust OAD methods with high levels of fidelity from disciplinary tools such as CFD (Computational Fluid Dynamics), FEM (Finite Element Model) or CAA (Computational Aero Acoustics). This paper focuses on the integration of rapid CFD tools inside the OAD process, in order to assess BLI benefits. The resulting process is validated against reference and experimental cases when available, or high-fidelity RANS data elsewhere. The paper intends to present the tools and their validation process. These modules are applied to the common inlet concept, which aims at ingesting00% of the fuselage boundary layer. The results demonstrate the potential gain on the Power Saving Coefficient (up to 3% obtained with the L2 BLI module without resizing loop) but with non-negligible fan losses (up to 1.5%).

Shape Optimisation of Turbomachinery Components

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:59:20 +0100

Low-order models are the first choice to find the initial design of turbomachinery components screening many configurations. The final optimisation of the three-dimensional geometry is crucial for the best performance. Because of the ability to accurately predict the performance of turbomachinery, fluid dynamic simulations became a powerful tool [10]. However, parameter studies for shape optimisation relying on fluid dynamic simulations are computationally expensive and might fail to reveal the optimal geometry. Gradient-based optimisation approaches allow a significant reduction of simulations and hence, determine the optimum efficiency. The adjoint method finds the optimisation gradient by calculating the derivatives of the state variables with respect to the design objective without the need for finite differences [6]. Thus, the adjoint optimisation is especially efficient for problems with many degrees of freedom and few design objectives, e.g. increasing efficiency. The application of the adjoint method for shape optimisation is demonstrated on the example of a centrifugal compressor impeller. The shape of the rotor blades is optimised, and the impact of different objection functions, i.e. reducing the required moment or increasing the achieved pressure ratio, and optimisation constraints, i.e. retaining the operating point or keeping an area ratio, is analysed. The results demonstrate that the compressor performance can be significantly improved using the adjoint method. However, the challenge is to obtain not only an optimised shape for operating points but also for the entire operating map. The final shapes, obtained for different operating points, are compared.

Hemodynamics in healthy and pathological thoracic aorta: integration of in-vivo data in CFD simulations and in in-vitro experiments

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:58:58 +0100

A comparison between the results of the CFD simulations and the in-vitro experiments carried out on a circulatory mock loop is presented. Both approaches integrate in-vivo measurements obtained from a patient-specific clinical data set. Three thoracic-aorta geometries are analyzed: a healthy aorta, an aneurysmatic aorta, and a coarctated aorta. The healthy geometry is obtained from Magnetic Resonance Imaging (MRI) acquisitions, together with the patient-specific flow-rate waveform, whereas the diseased ones are derived from the former geometry by locally morphing the vessel's wall. The open-source code Simvascular is used for simulations. The in-vitro results are measured in a fully controlled and sensorized circulatory mock loop for 3D-printed aortic models. Differently from in-vivo acquisitions, the experimental set-up eliminates some of the uncontrollable uncertainties that characterize MRI data. Indeed, perfect control of the flow rate and full knowledge of the wall model characteristics (rigid walls in the present case) is allowed in experiments and, thus, clear indications can be obtained to validate and improve the accuracy of numerical models. The numerical and experimental results are in good agreements for the three analyzed geometries and the flow-rate conditions. In-vivo data from the healthy case are in a satisfactory agreement with numerical/in-vitro results, and they can be ascribed to possible differences between MRI and numerical/in-vitro set-ups. The velocity fields obtained through CFD are consistent with the echographic results in in-vitro experiments, showing the same flow patterns in healthy and pathological cases.

Effect of Laser Beam Scattering in SPH-Simulation of Deep Penetration Laser Beam Welding

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:58:36 +0100

The effect of laser beam scattering on capillary stability and melt dynamics is investigated simulatively for deep penetration laser beam welding. The mesh-free Lagrangian Smoothed Particle Hydrodynamics (SPH) method is coupled with a ray-tracing scheme. The SPH model covers fluid and thermodynamics, including temperature-dependent surface tension, recoil pressure, heat conduction, and phase transitions. The ray tracer models the laser-material interaction by tracking the propagation of light rays within the capillary according to the laws of geometrical optics, and taking into account multiple reflections and scattering. Surface scattering due to surface roughness, and volume scattering due to condensed droplets or local changes of the complex refractive index in the vapor plume are evaluated separately. For surface scattering, the reflections at the material surface are divided into a specular part and a diffuse part with randomly reflected rays. For volume scattering, the Henyey-Greenstein model is used to specify the angular distribution of the scattered light ray. The effect of scattering is examined for laser beam welding of aluminum and titanium. The results show that volume scattering has a stabilizing effect on the capillary for the highly reflective material aluminum, while the effect of surface scattering is small for both materials.

Dirichlet boundary control of a steady multiscale fluid-structure interaction system

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:58:12 +0100

This work aims to extend the techniques used for the optimal control of the NavierStokes systems to control a steady multi-scale FSI system. In particular, we consider a multiscale fluid-structure interaction problem where the structure obeys a membrane model derived from the Koiter shell equations. With this approach, the thickness of the solid wall can be neglected, with a meaningful reduction of the computational cost of the numerical problem. The fluid-structure simulation is then reduced to the fluid equations on a moving mesh together with a Robin boundary condition imposed on the moving solid surface. The inverse problem is formulated to control the velocity on a boundary to obtain a desired displacement of the solid membrane. For this purpose, we use an optimization method that relies on the Lagrange multiplier formalism to obtain the first-order necessary conditions for optimality. The arising optimality system is discretized in a finite element framework and solved with an iterative steepest descent algorithm, used to reduce the computational cost of the numerical simulations.

A posteriori MOOD limiting approach for multicomponent flows on unstructured meshes

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:57:54 +0100

A relaxed, high-order, Multidimensional Optimal Order Detection (MOOD) framework is extended to the simulation of compressible multicomponent flows on unstructured meshes in the open-source unstructured compressible flow solver UCNS3D. The class of diffuse interface methods (DIM) is employed with a five-equation model. The high-order CWENO spatial discretisation is selected due to its low computational cost and improved non-oscillatory behaviour compared to the original WENO variants. The relaxed MOOD enhancement of the CWENO method has been necessary to further improve the robustness of the CWENO method. A series of challenging compressible multicomponent flow problems have been implemented in UCNS3D, including shock wave interaction with a water droplet and shock-induced collapse of bubbles arrays. Such problems are generally very stiff due to the strong gradients present, and it has been possible to tackle them using the extended MOOD-CWENO numerical framework.

Non-reflecting boundary condtions on unstructured grids

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:57:38 +0100

Non-reflecting boundary condition at interfaces for flow simulations in turbomachinery using the method laid out by Giles [1] and Saxer [2] require averages or Fourier decomposition of the flow solution using stations of constant radius at the interface. On structured grids the grid generation process can easily enforce grids having element centers with this property while on unstructured grids this is rarely achievable. We describe an approach which works on an auxiliary mesh with a band structure created from the surface mesh at interfaces and study the influence of the prescribed distribution of the bands on the solution. The effectiveness of the approach is demonstrated by applying it to the simulation of a compressor stage and comparing the results with results obtained by using the existing approach for creating bands and a simulation on a structured grid.

Numerical methods for diffuse interface multifluid models

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:57:22 +0100

We describe some numerical methods developed in ONERA's Cedre platform to solve diffuse interface multifluid models with a view to realistic industrial applications. These methods are illustrated on test cases such as a shock-droplet interaction case.

Numerical Investigation of Oleo-Pneumatic Shock Absorber: A Multifidelity Approach

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:56:59 +0100

A representative shock absorber geometry is developed based on the general guidelines available in the literature, and it is validated against experimental measurements from a drop test. Simulations are conducted using a multi-fidelity approach ranging from unsteady scale resolving three-dimensional simulations to dynamic system models. High fidelity simulations provide a detailed insight into the flow physics inside the shock absorber, as well as help calibrate and validate lower fidelity methods, under conditions for which no experimental measurements are available to achieve that purpose. On the other hand, lower fidelity methods are used to efficiently scan the design space and test the dependency of the shock absorber performance on the various design parameters, in addition to identifying parameter combinations that would be of interest to investigate using a high-fidelity approach.

High-order, high-fidelity simulation of unsteady shock-wave/boundary layer interaction using flux reconstruction

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:56:33 +0100

In this work, a high-order implicit large-eddy simulation of an oblique shockwave/boundary layer interaction at Mach 2.3 is performed. The high-order solver is based on the flux reconstruction method, allowing an arbitrary order of accuracy. A particular attention is paid to the shock-capturing technique which consists in a combination of a Laplacian artificial viscosity with the Ducros sensor. The ability of such a solver to accurately predict the flow features is assessed on both steady and unsteady fields. In particular, the typical lowfrequency motion of the reflected shock is reproduced. The shock-capturing methodology is proven to be efficient at resolving the shocks without damping the turbulence in the boundary layer. The results obtained give confidence in this solver to study in more details the shockwave/boundary layer interaction phenomenon and future work is focused on the analysis of the oscillatory turbulent field in the interaction region.

Implicit LES of the Transonic Flow Over A High-Pressure Turbine Cascade using DG Subcell Shock Capturing

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:55:37 +0100

Implicit large-eddy simulations of the high-pressure turbine cascade VKI-LS89 under transonic operating conditions using a high-order accurate discontinuous Galerkin spectral element method are presented. The subcell shock capturing method by Hennemann et al. [1] is investigated and compared against simulations with artificial viscosity. Additionally, the effect of laminar and turbulent inflow conditions are validated against numerical and experimental results from literature. This analysis shows that the subcell-shock-capturing method performs well by effectively reducing spurious oscillations across the shock front and acoustic waves while leaving the rest of the solution domain unaffected.

Functional implications of renal adaptations in gestational hypertension

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:55:17 +0100

During pregnancy, major adaptations in renal morphology, hemodynamics, and transport occur to achieve the volume and electrolyte retention required in pregnancy. These complex changes can appear counterintuitive when considered in isolation. Additionally, in pregnancies complicated by a disorder, such as gestational hypertension, kidney function may be altered from normal pregnancy. To analyze how renal function is altered during pregnancy, we developed epithelial cell-based computational models of solute and water transport in a nephron of the kidney for a rat in midand late-pregnancy. The model represents known pregnancy-induced changes in renal transporters, including reduction in proximal tubule and medullary loop transporters. The pregnant rat nephron models predicted urine output and excretion consistent with measured values. Additionally, we simulated the inhibition and knockout of the ENaC and H+-K+-ATPase transporters.

A time-staggered CFD scheme for variable density moist air Flow

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:55:01 +0100

We present a conservative second order staggered time scheme for dry and moist variable density air flow implemented in the open source CFD solver code saturne. The staggered time arrangement introduced by Pierce and Moin [1] is extended to finite volumes and discontinuous solutions. An Helmholtz equation is solved in order include the thermodynamical pressure variation and to remove the acoustic CFL restriction. The internal energy equation supplemented by a corrective source term based on the kinetic energy dissipation [2] is solved, allowing the scheme to be consistent with discontinuous solutions. The water phase change is treated by considering thermodynamical equilibrium. Dalton’s law is used to compute the density and the temperature is obtained from the internal energy equation, solving with Newton’s method in case of phase change. A numerical analysis is presented to insure the positivity of the thermodynamic variables, followed by the scheme verification and validation. First, dry air cases are presented: a natural convection and shock cases are used to verify its accuracy related to singularities and buoyancy effects. Moreover, a pressure cooker like system shows the scheme good reproduction of pressure variations and correct time error convergences rates. Finally, the moist air module is verified against analytical cases.

Mathematical and numerical analysis of a simplified model for boiling flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:54:45 +0100

We focus on a toy problem which corresponds to a simplification of a boiling twophase flow model. This model is a hyperbolic system of balance laws with a source term defined as a discontinuous function of the unknown. Several discretizations of this source terms are studied, and we illustrate their capacity to capture steady states.

Application of interface capturing schemes on multiphase/multicomponent compressible flow of underwater explosion

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:54:29 +0100

We present in this work shock-/interface-capturing numerical methods in the finitevolume central-weighted essentially non-oscillatory (CWENO) reconstruction scheme on unstructured grids for the simulation of multi-component or multiphase compressible flows. Using the five-equation interface capturing models of Allaire et al. and Kapila et al. in the open-source unstructured compressible flow solver UCNS3D, we will demonstrate the capabilities and robustness of the CWENO in capturing and resolving the material interface in multicomponent/multiphase flows in the presence of strong gradients and material discontinuities, with oscillation free solutions and reduced numerical diffusion. To test our numerical methods, a simple one-dimensional test case and a more sophisticated 2d underwater test case with cavitation are considered. The numerical results of our study are compared with results from existing high-order methods. The results show that the CWENO is less dissipative without the spurious oscillations that typically develop at material boundaries and also gives a high-resolution description of the moving material interface with less artificial smearing than other high other schemes.

Development lengths for non-newtonian flows in pipes and tubes based on the wall shear stress

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:54:11 +0100

The development length needed for tube flows to re-adjust from a uniform to the fully-developed velocity profile is usually defined as the length required for the centerline velocity to reach 99% of its fully-developed value. This definition, however, may be quite inaccurate in non-Newtonian flows with almost flat velocity distributions near the centerline, since the velocity far from the axis of symmetry develops more slowly. Shear-thinning and viscoplasticity may cause the flow close to the centerline to evolve faster than that closer to the walls. Thus, alternative definitions of the development length have been proposed for viscoplastic flows. Given that blood exhibits shear thinning, we numerically solve the flow development of power-law fluids in pipes and calculate the development length as a function of the radius, determining the global development length along with the standard centerline estimate. We also consider an alternative definition, based on the evolution of the wall shear stress. Results have been obtained for values of the power-law exponent ranging from 0.

On the effect of Prandtl number to subgrid-scale heat flux models

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:34:52 +0100

Estimations of the grid size and computational cost for direct numerical simulation (DNS) and large-eddy simulation (LES) of Rayleigh-Bénard convection (RBC) are presented in the {Ra, P r} phase space. Computational requirements to reach the so-called asymptotic Kraichnan or ultimate regime of turbulence using DNS are far too expensive. Therefore, we turn to LES to predict the large-scale behavior at very high Ra-numbers. However, a priori alignment studies clearly show why the modelization of the SGS heat flux is the main difficulty that (still) precludes reliable LES of buoyancy-driven flows at (very) high Ra-numbers. This inherent difficulty can be by-passed by carrying out simulations at low-P r numbers where no SGS heat flux activity is expected. This opens the possibility to reach the ultimate regime carrying out LES of RBC at low-P r using meshes of 10101011grid points. Nevertheless, to do so, we firstly need to combine proper numerical techniques for LES (also DNS) with an efficient use of modern hybrid supercomputers.

Towards proper subgrid-scale model for jet aerodynamics and aeroacoustics

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:34:31 +0100

This article presents the investigation of different grey-area mitigation (GAM) techniques towards achieving accurate subsonic turbulent round jet aerodynamics and aeroacoustics results. Combinations of new adapting subgrid length scales with 2D detecting LES models are used as the GAM technique. The numerical simulations are carried out on a set of refining meshes using two different scale-resolving codes: NOISEtte and OpenFOAM. The results show that all the considered techniques provide appropriate accuracy to predict the noise generated and the importance of both the numerical scheme and how subgrid eddy viscosity is modelled.

FEM analysis and monolithic Newton-multigrid solver for thixo-viscoplastic flow problems

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:34:12 +0100

In this contribution, we shall be concerned with the question of wellposedness of thixoviscoplastic flow problems in context of FEM approximations.We restrict our analysis to a quasiNewtonian modeling approach with the aim to set foundations for an efficient monolithic Newtonmultigrid solver. We present the wellposedness of viscoplastic subproblems and structure subproblems in parallel/independent fashion showing the possibility for a combined treatment. Then, we use the fixed point theorem for the coupled problem. For the numerical solutions, we choose 4:1 contraction configuration and use monolithic Newton-multigrid solver. We analyse the effect of taking into consideration thixotropic phenomena in viscoplastic material and opening up for more different coupling by inclusions of shear thickening and shear thinning behaviors for plastic viscosity and/or elastic behavior below the critical yield stress limit in more a general thixotropic models.

Computational micro-magneto-mechanics

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:33:56 +0100

We formulate a material model for micro-magneto-mechanics based on the generalized standard material approach. Our model includes exchange, elastic, anisotropy, demagnetizing and Zeeman energy. Furthermore we account for dissipative micro-magnetic behavior by means of a dissipation potential. For the constrained optimization problem w.r.t. magnetization we rely on the exponential map algorithm. We demonstrate our ideas with numerical examples. In particular we apply our model to a thin film composite. With this composite we represent the magneto-mechanical part of a magneto-electric composite sensor (resp. small sensor segment). Our numerical experiments focus on FeCoSiB as the magnetostrictive material. We discuss the coupling effects for the considered thin film composite in detail.

Unsteady Aerodynamic Sensitivity Analysis with FEniCS

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:33:42 +0100

Sensitivity analysis is considered a fundamental tool in aerospace engineering, allowing to evaluate the impact of parameters variations, and optimize the aerodynamic and structural design. There has been much effort in the development of both theoretical and numerical frameworks for sensitivity calculations through adjoint solutions. Regarding the implementation of these analyses into agile and versatile numerical tools, the use of scalable and transferable libraries has become of particular importance. In this work, FEniCS is used to calculate the sensitivity of aerodynamic observables in different flow condition. A comparison with different theoretical and benchmark cases is used to validate the methodology before applying it to further and more complex configurations, expanding the scope of the analyses to unsteady flows.

Incorporating effective transmission conditions between fluid and solid domains in transient wave propagation problems using the mortar element method

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:33:27 +0100

We derive an efficient numerical scheme for transient wave propagation in configurations where a fluid domain and a solid domain are separated by a thin coating material. These type of configurations are numerically challenging for multiple factors: managing fluid solid coupling, enabling non-conform space discretizations, and rendering robust time discrete algorithm w.r.t the thin layer thickness. By combining the mortar element method with effective transmission conditions we are able to address these challenges. We illustrate our approach by proposing relevant 2D numerical illustrations inspired from simple ultrasonic testing experiments.

Discretize first, filter next – a new closure model approach

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:33:13 +0100

Simulating multi-scale phenomena such as turbulent fluid flows is typically computationally very expensive. Filtering the smaller scales allows for using coarse discretizations, however, this requires closure models to account for the effects of the unresolved on the resolved scales. The common approach is to filter the continuous equations, but this gives rise to several commutator errors due to nonlinear terms, non-uniform filters, or boundary conditions. We propose a new approach to filtering, where the equations are discretized first and then filtered. For a non-uniform filter applied to the linear convection equation, we show that the discretely filtered convection operator can be inferred using three methods: intrusive (`explicit reconstruction') or non-intrusive operator inference, either via `derivative fitting' or `trajectory fitting' (embedded learning). We show that explicit reconstruction and derivative fitting identify a similar operator and produce small errors, but that trajectory fitting requires significant effort to train to achieve similar performance. However, the explicit reconstruction approach is more prone to instabilities.

Robust Topology Optimization of Static Systems with Unilateral Frictional Contact

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:32:55 +0100

In this paper a robust topology optimization algorithm for linear elastic structures in unilateral contact is presented. The deformation of the linear elastic structure is constrained by support structures that are modeled with the help of Signorini's contact conditions. The contact conditions in turn are enforced with the augmented Lagrangian approach. Doing so, the robust optimization considers uncertainties at the support such as manufacturing tolerances and its local friction behavior. Due to high numerical costs in robust optimization, the firstorder second-moment approach is used to approximate the mean and variance of the objective. This approximation results in minimal additional costs to approximate the mean, the variance and their gradients. Consequentially, a gradient-based optimization algorithm can be used to minimize a weighted sum of both. The results show that the presented approach indeed improves the robustness with respect to uncertain contact conditions compared to a deterministic optimization.

A fluid-structure interaction study of hemodynamics in arterial bypass-graft anastomoses

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:32:31 +0100

This paper reports on numerical experiments on arterial bypass-graft anastomoses. Bypass-grafts are oftentimes used in surgical procedures to divert blood around narrowed or occluded parts of an artery. The diverted blood flow is crucial to the success of the operation as it may lead to undesirable peculiarities that can result to a renewed occlusion in the distal connection of the graft. However, an a priori prediction of detrimental hemodynamic aspects due to undesirable flow properties is difficult to perform in vitro or in vivo conditions. To this end, this work targets to enhance our understanding of harming mechanisms through in silico experiments using computational fluid dynamics (CFD) and fluid-structure interaction (FSI) simulations. The latter are realized through a partitioned coupled approach which is verified for a 2D benchmark case against literature-reported results. Finally, we present numerical results on grafts with different cuff sizes. Wall shear stress (WSS), oscillatory shear index (OSI) and hemolysis are monitored and compared in the context of either rigid or elastic walls and cuff sizes. Special interest is given to the prediction of hemolysis induction which is often not considered in such studies. We show that wall elasticity is the key parameter in terms of WSS prediction while cuff size mainly affects the estimation of OSI.

Low Mach preconditioned non-reflecting boundary conditions for the harmonic balance solver

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:32:13 +0100

In computational fluid dynamics (CFD), unsteady computations are cost-intensive. The Harmonic Balance (HB) method [7] represents a cost-efficient alternative. Here, for timeperiodic flows, the governing equations are recasted in the Fourier domain. In the low Mach regime, the compressible governing equations are stiff. Therefore, densitybased solvers converge slowly. Low Mach preconditioning equalizes the eigenvalues of the system of equations, to improve the condition number and remove the stiffness of the system [14]. In this paper, low Mach preconditioning is applied to the HB method, with emphasis on the non-reflecting boundary conditions (NRBCs). These boundary conditions have a crucial impact on the flow inside the truncated computational domains used in CFD. Improper boundary conditions reflect waves exiting the computational domain and deteriorate the quality of the solution. However, NRBCs [6] avoid spurious reflections. We explain that to precondition the NRBC its formulation in terms of characteristics has to be adapted. An academic wave propagation test case is computed for different wave configurations to validate the preconditioned boundary conditions. The use of non-preconditioned NRBCs in a preconditioned computation leads to instabilities and reflections at the boundaries of the domain. A consistent setup with preconditioned NRBCs improves the stability and leads to good non-reflecting properties for all presented wave configurations.

High fidelity fluid-structure interaction simulation of a multi-megawatt airborne wind energy reference system in cross-wind flight

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:31:53 +0100

Airborne wind energy (AWE) is an emerging technology for the conversion of wind energy into electricity by flying crosswind patterns with a tethered aircraft connected to a generator either on board or on the ground. Having a proper understanding of the unsteady interaction of the air with the flexible and dynamic system during operation is key to developing viable AWE systems. The research goal is to simulate the time-varying fluid-structure interaction (FSI) of an AWE system in a crosswind flight maneuver using high fidelity simulation tools. In this work a framework is presented that serves as a proof of concept to perform high fidelity simulations of airborne wind energy systems. This is done using a partitioned and explicit approach in the open-source coupling tool CoCoNuT. An existing finite element method (FEM) model of the wing structure is coupled with a newly developed computational fluid dynamics (CFD) model of the wing aerodynamics including rigid body motion. It has been found that the mesh deformation is quite sensitive to dynamic mesh parameters. On the other hand, the overset/Chimera technique has been proven to be a robust approach to simulate the motion of an AWE system in CFD simulations.

Novel immersed boundary method for fluid-structure interaction of compressible flow

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:31:31 +0100

A 3D fluid-structure interaction (FSI) code is under development. The fluid domain (Navier-Stokes) solver will employ a sharp interface ghost node immersed boundary method (IBM) to apply the boundary conditions at fluid-solid interfaces. The Navier-Stokes (N-S) solver has been verified using a classic Poiseuille channel flow. The current version of the immersed boundary method is being tested by solving a heat conduction problem. The order of accuracy of the IBM was shown to be just above second order.

A semi-implicit method for thrombus formation in haemodynamic fluid-structure interaction

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:31:06 +0100

Aortic flows with thrombus formation represent a challenging application of fluidstructure interaction (FSI) in biomechanics where blood flow, thrombus, and vessel wall are strongly coupled. Considering patient-specific FSI and thrombus formation on identical time scales remains unfeasible. To resolve this issue, we propose incorporating the dynamics-based thrombus formation model of Menichini et al. [1] into our recently presented semi-implicit, splitstep partitioned FSI scheme for non-Newtonian fluids [2, 3]. Herein, we formulate the basic split-step scheme and present the first promising results, merely coupling the fluid pressure and structure displacement iteratively at each time step.

The iPGDZ+ technique for compressing primal solution time-series in unsteady adjoint - applications & assessment

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:30:46 +0100

Gradient-based optimization for large-scale problems governed by unsteady PDEs, in which gradients with respect to the design variables are computed using unsteady adjoint, are characterized by the backward in time integration of the adjoint equations, which require the instantaneous primal/flow fields to be available at each time-step. The most widely used technique to reduce storage requirements, at the expense of a controlled number of recomputations, is binomial check-pointing. Alternatively, one may profit of lossless and lossy compression techniques, such as iPGDZ+, this paper relies upon. iPGDZ+is a hybrid algorithm which consists of (a) an incremental variant of the Proper Generalized Decomposition (iPGD), (b) the ZFP and (c) the Zlib compression algorithms. Two different implementations of iPGDZ+are described: (a) the Compressed Full Storage (CFS ) strategy which stores the whole time-history of the flow solution using iPGDZ+and (b) the Compressed Coarse-grained Check-Pointing (3CP ) technique which combines iPGDZ+with check-pointing. Assessment in aerodynamic shape optimization problems in terms of storage saving, computational cost and representation accuracy are included along with comparisons with binomial check-pointing. The methods presented are implemented within the in-house version of the publicly available adjointOptimisation library of OpenFOAM, for solving the flow and adjoint equations and conducting the optimization.

Fluid-structure interaction tool for morphing blades

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:30:29 +0100

The design of aeronautical components commonly involves two highly coupled disciplines: aerodynamics and structural mechanics. The interaction between them becomes even more relevant when morphing aeronautical structures are studied. Considering the importance of morphing technology for the future of the aerospace industry, several tools have already been developed to couple these two disciplines together, but all of them deal with pure twodimensional or three-dimensional aero-structural problems. In some circumstances, the study of aeronautical components requires to couple a 2D computational fluid-dynamics (CFD) analysis with a 3D finite element analysis (FEA). This usually happens in the preliminary design phase of aeronautical engine blades (i.e. compressor blades) where the aerodynamic study of the original 3D geometry is replaced by the analysis of a 2D blade cascade in order to reduce the overall computational cost. However, such an approach requires a specific method to couple the 2D CFD geometry/mesh with the 3D FEA geometry/mesh in order to transfer the aerodynamic loads from the CFD analysis to the structural one. As mentioned before, the existing fluid-structure interaction (FSI) tools cannot be implemented to solve a 2D-3D problem; therefore, a novel 2D3D aero-structure coupling approach needs to be developed. This paper describes step-by-step the 2D-3D aero-structure coupling strategy applied to the performance analysis of a morphing blade cascade with the goal of enhancing its aerodynamic performance. The results show a relevant decrease in the total pressure losses of the morphing cascade thanks to the adapting blade leading-edge. In order to highlight the reliability of the FSI framework, the developed approach is applied to four different blade configurations which differ in size and location of the two morphing devices.

Unstructured high-order solutions of hovering rotors with and without ground effect

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:30:10 +0100

This work describes the computational cost and accuracy of high-order numerical schemes on a simplified concept of multiple reference frame (MRF) technique using mixedelement unstructured grid framework widely tested for aerospace applications. The Reynolds averaged Navier-Stokes equations are approximated with up to fourth spatial order using Spalart Allmaras turbulence model on two types of reconstruction scheme: monotonic upwind scheme for conservation laws (MUSCL) and weighted non-oscillatory (WENO). The calculations were made for both out-of-ground-effect (OGE) and in-ground-effect (IGE) cases and compared with experimental data in terms of pressure distribution, tip-vortex trajectory, vorticity contours and integrated thrust and torque. The predictions were obtained for several ground distances. Our findings suggest that the resolution of the vortex path and wake breakdown were considerably improved with increased scheme order. It is noticeable how low-order scheme struggles to deal with the large amount of diffusion. This numerical nature contributes to the vortex system settle down and achieve this stable ring state structure as seen on a couple radii downstream the rotor. As the wake is transported downwards, it can be clearly seen the interaction primary and secondary structures, which stretch between the tip vortices making an S-shaped path also seen experimentally. The presence of the vortex-ring close to the rotor blade contributes to a larger induced flow and under predictions of thrust coefficient . As we increase the scheme-order, it becomes more evident how the helical system convects down and breakdown toroidal vortex into smaller scales.

Large-eddy simulations of turbulent compressible supersonic jet flows using discontinuous Galerkin methods

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:29:47 +0100

In this work, a discontinuous Galerkin scheme is employed to perform large-eddy simulations of supersonic jet flows. A total of four simulations are performed with different meshes and order of accuracy to identify the resolution requirements to reproduce the physical characteristics from experiments. The number of degrees of freedom from the simulations varies from 50 × 106to 400 × 106. The results indicate that by increasing the resolution of simulation, in general, the results got closer to experimental data. The comparison of velocity distribution in the jet centerline and lipline from the simulation with 400 × 106with experimental shows that important characteristics of the flow are represented. The study investigated a procedure of using lower-order simulations to initialize high-order simulations to reduce the total computational cost of the calculation. This strategy is successful and allows the performance of high-order simulations with only 6% more computational effort than a second-order simulation with the same number of degrees of freedom.

Accelerating the simulation of elastohydrodynamic lubrication in a line contact using a surrogate model

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:29:28 +0100

Elastohydrodynamically lubricated contacts are an example of a strongly coupled fluid-structure interaction problem. Typically, these problems are solved in a partitioned way and require multiple flow-structure iterations per time step to reach convergence. The manner in which these iterations are performed is determined by the coupling algorithm. In the previous decade, several algorithms have been proposed, most of which are based on a quasi-Newton principle. These methods use an approximate Jacobian, which is constructed during the calculation itself. However, in many cases, a simpler model is available, which provides an approximate solution and Jacobian, and is denoted as surrogate model. For the elastohydrodynamically lubricated contact, this model is the coupled Reynolds-Boussinesq approach, which evaluates significantly faster than the CFD-CSM simulation. The incorporation of a surrogate model in a quasi-Newton method is realized with the IQN-ILSM algorithm. This work is a first step towards employing this coupling method for the elastohydrodynamically lubricated contact and, in this way, combining the speed of the Reynolds-Boussinesq approach with the accuracy and versatility of the CFD-CSM modelling. In the current work, only the surrogate solution will be used as initial solution. The use of the surrogate Jacobian is future work.

An extended discontinuous Galerkin method for high-order shock treatment

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:29:11 +0100

In this paper, we are going to present a high-order shock fitting approach based on a cut-cell method. We formulate a suitable Constraint Optimization Problem and develop an algorithm aiming to reconstruct the shock front represented by the zero iso-contour of a Level Set function.

Hybrid High-Order Finite Volume/Discontinuous Galerkin Methods for Turbulent Flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:28:54 +0100

In this paper we develop a family of arbitrarily high-order non-oscillatory hybrid Finite Volume/Discontinuous Galerkin schemes for turbulent flows on mixed-element unstructured meshes. The schemes are inherently compact in the sense that the central stencils employed are as compact as possible, and that the directional stencils are reduced in size, simplifying their implementation. Their key ingredient is the switch between a DG method and a FV method based on the CWENOZ scheme when a troubled cell is detected. Therefore, in smooth regions of the computational domain, the high order of accuracy offered by DG is preserved, while in regions with sharp gradients, the robustness of FV is utilized. This paper also presents the time evolution of troubled cells in unsteady test cases and the use of extended bounds for troubled cell detection. We assess the performance of these schemes in terms of accuracy, robustness and computational cost through a series of stringent 2D and 3D test problems. The results obtained demonstrate the accuracy and robustness that the schemes offer and highlight areas of future improvements that are considered.

Deep Neural Network-driven hp-adaptive Finite Element Method in three dimensions

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:07:46 +0100

Numerical solutions of Partial Differential Equations with Finite Element Method have multiple applications in science and engineering. Several challenging problems require special stabilization methods to deliver accurate results of the numerical simulations. The advection-dominated diffusion problem is an example of such problems. They are employed to model pollution propagation in the atmosphere. Unstable numerical methods generate unphysical oscillations, and they make no physical sense. Obtaining accurate and stable numerical simulations is difficult, and the method of stabilization depends on the parameters of the partial differential equations. They require a deep knowledge of an expert in the field of numerical analysis. We propose a method to construct and train an artificial expert in stabilizing numerical simulations based on partial differential equations. We create a neural network-driven artificial intelligence that makes decisions about the method of stabilizing computer simulations. It will automatically stabilize difficult numerical simulations in a linear computational cost by generating the optimal test functions. These test functions can be utilized for building an unconditionally stable system of linear equations. The optimal test functions proposed by artificial intelligence will not depend on the right-hand side, and thus they may be utilized in a large class of PDE-based simulations with different forcing and boundary conditions. We test our method on the model one-dimensional advection-dominated diffusion problem.

A numerical set-up for the simulation of infection probability from SARS- CoV-2 in public transport vehicles

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:07:25 +0100

In this work, a numerical framework aimed at simulating the transport of contaminants and infectious agents within a closed domain is presented. The method employs mature CFD algorithms to calculate air fields with reasonable computational costs. The main objective is to give fast response to stakeholders about air quality indicators in the design phase of HVAC systems. A discussion regarding the size and characteristics of different contaminants is proposed, highlighting the most appropriate methods and coefficients needed to simulate their transport. Next, the methodology employed to evaluate the risk of infection is presented. The numerical set-up, based on the buoyantBoussinesqPimpleFoam solver in OpenFOAM, was tuned by simulating the well-known case of the heated floor cavity, providing accurate results. Hence, the case study of a transport vehicle of generic shape is presented, in order to show possible results in terms of air-age distribution, PM2.5 distribution, and global infection risk matrix.

A CFD-based multi-fidelity surrogate model for prediction of flow parameters in a ventilated room

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:07:04 +0100

In this work, we present a multi-fidelity machine learning surrogate model, which predicts comfort-related flow parameters in a ventilated room with a heated floor. The model uses coarseand fine-grid CFD data obtained using LES turbulence models. The dataset is created by changing the width aspect ratio of the rooms, inlet flow velocity, and temperature of the hot floor. The surrogate model takes the values of temperature and velocity magnitude at four different cavity locations as inputs. These probes are located such that they could be replaced by actual sensor readings in a practical case. The model's output is a set of comfort-related flow parameters. We test two multi-fidelity approaches based on Gaussian process regression (GPR), among them GPR with linear correction (LC GPR), and multi-fidelity GPR (MF GPR) or cokriging. The computational cost and accuracy of these approaches are compared with GPRs based on single-fidelity data. All of the tested multi-fidelity approaches successfully reduce the computational cost of dataset generation compared to high-fidelity GPR while maintaining the required level of accuracy. The co-kriging approach demonstrates the best trade-off between computational cost and accuracy.

Refinement techniques for spline spaces with cloud-based geomiso TNL software

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:06:43 +0100

Geomiso TNL is a new both on-premises and cloud-based software, which delivers isogeometric analysis (IGA) and 3D design with splines. It combines IGA and cloud computing, one of the fastest growing fields in IT industry. The combination of cloud computing and advanced refinement techniques constitutes a real game changer in CAD/CAE fields. Cloud-based IGA represents the future of product engineering, soon to become an industry standard. Automatic mesh refinement has not been widely adopted in industry, because it requires access to the exact geometry. This hybrid program achieves seamless and automatic communication with CAD, thus mesh refinement utilizes the exact geometry, while cloud computing enables users to execute large-scale simulation experiments without the need for dedicated hardware. The recently developed cloud-based platform www.geomiso.cloud is introduced to help engineers and industries make effective use of inelastic static isogeometric analysis and design with advanced spline techniques. It is argued that Geomiso TNL is a new, more efficient, alternative to FEA software packages. This is the first time ever such a cloud-based program has been developed.

PSYDAC: a high-performance IGA library in Python

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:06:23 +0100

Psydac is a Python 3 library for the solution of partial differential equations, which combines the convenience of a domain specific language with the speed of a high-performance parallel engine. Its main focus is on isogeometric analysis using tensor-product B-spline finite elements; to this end it uses an optimized sparse format called 'stencil matrix', which drastically reduces memory storage compared to the popular CSR/CSC formats. It supports multi-patch mapped geometries, and finite element exterior calculus. It can distribute each domain patch across many MPI processes, with multiple OpenMP threads operating in each block. The users of Psydac define a weak form of the model equations through SymPDE, an extension of Sympy that provides the mathematical expressions and checks their semantic validity. Simple mappings can be defined analytically, and multi-patch NURBS geometries can be imported from file. Once a finite element discretization is chosen, Psydac maps abstract concepts onto concrete objects, the basic building blocks being MPI-distributed vectors and matrices. Python code is automatically generated for the model-specific operations, namely matrix and vector assembly, and user-defined diagnostics. Finally, Psydac accelerates all computationally intensive operations using Pyccel, a transpiler which converts Python code to either C or Fortran. We present the library design, the typical usage workflow, the user interface for a simple 2D example, and the parallel scaling results in a large 3D simulation. In addition we show a few complex applications in fluid dynamics and electromagnetism, where the accuracy of the solver is verified against manufactured and reference solutions.

Advanced Experiments on Gaussian Process-based Multi-fidelity Methods over Diverse Mathematical Characteristics

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:06:02 +0100

Advanced applications of multi-fidelity surrogate modelling techniques provide significant improvements in optimization and uncertainty quantification studies in many engineering fields. Multi-fidelity surrogate modelling can efficiently save the design process from the computational time burden caused by the need for numerous computationally expensive simulations. However, no consensus exists about which multi-fidelity surrogate modelling technique usually exhibits superiority over the other methods given for certain conditions. Therefore, the present paper focuses on assessing the performances of the Gaussian Process-based multi-fidelity methods across selected benchmark problems, especially chosen to capture diverse mathematical characteristics, by experimenting with their learning processes concerning different performance criteria. In this study, a comparison of Linear-Autoregressive Gaussian Process and NonlinearAutoregressive Gaussian Process methods is presented by using benchmark problems that mimic the behaviour of real engineering problems such as localized behaviours, multi-modality, noise, discontinuous response, and different discrepancy types. Our results indicate that the considered methodologies were able to capture the behaviour of the actual function sufficiently within the limited amount of budget for 1-D cases. As the problem dimension increases, the required number of training data increases exponentially to construct an acceptable surrogate model. Especially in higher dimensions, i.e. more than 5-D, local error metrics reveal that more training data is needed to attain an efficient surrogate for Gaussian Process based strategies.

Simulation of wind induced excitation of a membrane structure with ponding water

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:05:42 +0100

This paper proposes a new partitioned coupling approach to simulate the wind induced excitation of a membrane structure with ponding water. This approach uses three different solvers to simulate wind, water and membrane structure. The main assumption here is that the interaction between the wind and water can be neglected due to the small depth and small fetch of the water, relative to the size of the membrane structure. This assumption results in a coupling strategy where the structural solver independently interacts with the wind and water solver. The results from this method is compared with a straightforward approach, where a two-phase solver, modeling the wind and water, is coupled to a structural solver. The obtained results agreed very well with the reference modeling approach, where all the interactions are taken into account. Furthermore, the proposed method was found to be computationally more efficient.

Isogeometric analysis of industry applications with Geomiso SEA: a new hybrid software for shell analysis

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:05:15 +0100

In this paper the new Geomiso SEA software (www.geomiso.com) is proposed for applications on inelastic static isogeometric analysis with shell elements. This hybrid program is applicable to real world structures, while it satisfies the rising need for technical software of dual CAD/CAA nature. It is based on the new isogeometric method, which has attracted a lot of attention for solving boundary value problems. T-spline-based isogeometric shell analysis efficiently handles multi-patch geometries. Geomiso SEA is not just a plug-in, but a complete software solution, used to simulate spline models of structures or machine components, for analyzing their strength and behavior. The utilization of the exact mesh for analysis vanishes geometric errors, while there is no need of repeating the geometry design for refinement purposes. Industry applications on both thick and thin shells are demonstrated with a comparison between Geomiso SEA and FEA programs. This unique solution for seamless integration of the industrial design of shell geometries with its computational realtime testing, appears to be preferable to FEA programs, representing major improvements, such as higher accuracy, and considerably reduced computational cost.

Efficient coarse correction for parallel time stepping in plaque growth simulations

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:04:55 +0100

In order to make the numerical simulation of atherosclerotic plaque growth feasible, a temporal homogenization approach is employed. The resulting macro-scale problem for the plaque growth can be further accelerated by using parallel time integration schemes, such as the parareal algorithm. However, the parallel scalability is dominated by the computational cost of the coarse propagator. Therefore, in this paper, an interpolation-based coarse propagator, which uses growth values from previously computed micro-scale problems, is introduced. For a simple model problem, it is shown that this approach reduces both the computational work for a single parareal iteration as well as the required number of parareal iterations.

Multi-fidelity active learning for shape optimization problems affected by noise

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:04:33 +0100

The efficiency of simulation-driven design optimization based on surrogate models, depends strongly on the suitability of the surrogate model for the simulation data on which it is based. We investigate adaptive surrogate modelling methods that maximize the efficiency and the robustness for any optimization problem. Specific techniques include: adaptive sampling, noise filtering by metamodel tuning, and small initial datasets to give maximum freedom to the adaptation. These methodological advancements are demonstrated for an analytical test problem, as well as the shape optimization of the DTMB 5415 ship model for calm-water resistance.

Reduced-order model for large amplitude vibrations of flexible structures coupled with a flow

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:04:07 +0100

This work concerns the numerical modeling of the vibrations of geometrically nonlinear structures coupled with a fluid flow. Firstly, a reduced-order model (ROM) for the geometrically nonlinear structure is proposed. Then, the aforementioned ROM is used to replace a Finite Element solver (FE) in the frame of a fluid-structure partitioned coupling on a two-dimensional example involving vortex induced vibrations.

Fluid-structure interaction simulation of a wire-wrapped tube array using overset grids

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:03:45 +0100

Axial flows in tube bundle geometries are omnipresent in nuclear power plants, including fuel assemblies and heat exchangers. The tubes are often long and slender which makes them susceptible to flow-induced vibrations. Current reactor research investigates the use of wires helicoidally wound around each rod, to preserve their mutual distance. This poses new challenges for numerical simulations. The wire-wrapped geometry is complex, among other things due to small gaps, making the meshing process complicated and cumbersome. This research explores the use of overset grids for such wire-wrapped tube bundles. This meshing method allows grids to overlap and the flow solution is interpolated between the different grids, providing more freedom for meshing. In this case the approach consists of making one grid for a single tube with a wire, termed the component mesh, and placing this grid in a so-called background mesh that takes into account other geometrical features (e.g. the bundle duct). In the case of bundles, the same tube mesh can be repeated several times without additional meshing effort, regardless of the bundle size. The approach is verified using 4 cases found in literature, using the same component mesh either one or multiple times for each case, thus reducing the meshing effort to a minimum thanks to the freedom and re-usability overset offers. The first two cases involve a fluid-structure interaction simulation of a single wire-wrapped tube in a cylindrical domain, the first one simulating a steady deformation and the second one a free vibration of the tube. Good agreement with results in literature was found. The latter two cases are Computational Fluid Dynamics simulations of a 7-pin and 19-pin bundle in a hexagonal duct, and excellent agreement with literature results was obtained. The overset approach was proven beneficial for simulating wire-wrapped bundle geometries: with largely reduced effort the same predictive capabilities can be obtained and potentially even extended.

Fuzzy logic based rapid visual screening methodology for structural damage state determination of URM buildings

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:03:31 +0100

Most of the Unreinforced Masonry (URM) buildings are quite old in Europe based on 'Building stock inventory to assess seismic vulnerability across Europe' [1] report. Following the earthquakes (Albania, Italy, etc.) that occurred in Europe, it was revealed that masonry buildings are extremely vulnerable. While probabilistic and deterministic approaches are important for examining a small number of buildings, they do not offer the opportunity to examine a large building stock in a short period of time. Rapid Visual Screening (RVS) methods are used to identify building preand post-earthquake vulnerability. Several RVS techniques have been presented in literature over last 30 years. Recent earthquakes have highlighted critical necessity of a rapid vulnerability assessment method for pre-earthquake warning, mitigation, preparedness, and post-earthquake damage state assessment of existing buildings. These findings demonstrate the importance of using an accurate RVS technique to inspect buildings. Due to the subjectivity of the screener, these RVS methods contain uncertainty and vagueness. Fuzzy Inference System (FIS) overcomes nonrandom uncertainty and vagueness by considering building characteristics in terms of their degree of truth. This paper introduces a FIS-based SRVS case implementation and compares FIS-based Soft-RVS (S-RVS) to traditional RVS methods for identifying building damage state taking into account rapid visual assessment reports about damage caused by the 2019 Albania earthquake. To determine the damage states of URM buildings, 40 buildings damaged in the 2019 Albania earthquake were analyzed and processed to use in the applied fuzzy logic mathematical model. Initial findings demonstrate that the site-specific FIS-based S-RVS method is capable of accurately determining the damage states of at least half of the buildings.

Space-time fluid-structure interaction: formulation and dG(0) time discretization

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:03:15 +0100

This contribution is related to the key-note lecture `Space-time fluid-structure interaction with adjoint-based methods for error estimation and optimization' given in the Minisymposium `Innovative Methods for Fluid-Structure Interaction'. The main objective is twofold. First, we design function spaces and a space-time variational-monolithic formulation of fluid-structure interaction in arbitrary Lagrangian-Eulerian coordinates. Second, we apply a Galerkin-time discretization using discontinuous finite elements of degree r = 0. Therein, the main emphasis is on the correct derivation of the jump terms and the integration of nonlinear time derivatives, as the latter arise due to the arbitrary Lagrangian-Eulerian transformation.

A Mixed Finite Element Formulation for Arbitrary Element Geometries and Nearly-Incompressible Finite Elasticity

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:02:58 +0100

In this contribution, the displacement-based scaled-boundary finite element method (SBFEM) is extended to a mixed displacement-pressure formulation for the geometrically and materially nonlinear analysis of nearly-incompressible solids. The displacements and pressures are both parameterized by a scaled-boundary approach, for which an interpolation in the scaling direction is used. Here, higher-order interpolation functions may be employed. It is shown that by introducing the pressure as a field variable, volumetric locking is no longer present. The approach is valid for arbitrary scaling center locations, which can be either inside or outside of the element domain. Other than that, the formulation is valid for non-star-convex element geometries. Numerical examples show that the method is capable of alleviating volumetric locking for arbitrary polygonal meshes and is beneficial in comparison to the displacement-based method when it comes to modeling nearly-incompressible materials.

Multiscale kinetic transport models for the spread of epidemics with uncertain data

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:02:43 +0100

Most epidemiological models are rooted in the pioneering work proposed by Kermack and McKendrick and are based on systems of deterministic ODEs, which describe the temporal evolution of the spread of an infectious disease assuming population and territorial homogeneity. Generally, the concept of the average behavior of a population is sufficient to have a first reliable description of an epidemic development, but the inclusion of the spatial component becomes crucial when it is necessary to consider spatially heterogeneous interventions, as in the case of the COVID-19 pandemic. Moreover, any realistic data-driven model must take into account the large uncertainty in the values reported by official sources such as the amount of infectious individuals. In this work, drawing inspiration from kinetic theory, recent advances on the development of stochastic multiscale kinetic transport models for the spread of epidemics under uncertain data are presented. The propagation of the infectious disease is described by the spatial movement and interactions of individuals divided into commuters moving in the territory on a wide scale and non-commuters acting only on urban scales. The resulting models are solved numerically through a suitable stochastic Asymptotic-Preserving IMEX Runge-Kutta Finite Volume Collocation Method, which ensures a consistent treatment of the system of equations, without loss of accuracy when entering in the stiff, diffusive regime. Application studies concerning the spread of the COVID-19 pandemic in Italy assess the validity of the proposed methodology.

Modelling the COVID-19 pandemic: variants and vaccines

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:02:21 +0100

In December 2019, a new coronavirus, the SARS-CoV-2, was detected in the Chinese city of Wuhan. Since then, many mathematical models have been developed to study the possible evolution of the COVID-19 disease and shed some light on the different biological processes of concern. On 14 December 2020, the United Kingdom reported a potentially more contagious and lethal variant of the virus, at the same time that different vaccines were being tested in order to prevent severe forms of the disease. In the following lines, we revisit a model proposed by our team, which took into account these two determining facts, showing its performance with real Italian data.

Extended virtual element method for two-dimensional fracture modeling in linear elasticity

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:01:58 +0100

The virtual element method (VEM), is a stabilized Galerkin scheme deriving from mimetic finite differences, which allows for very general polygonal meshes, and does not require the explicit knowledge of the shape functions within the problem domain. In the VEM, the discrete counterpart of the continuum formulation of the problem is defined by means of a suitable projection of the virtual shape functions onto a polynomial space, which allows the decomposition of the bilinear form into a consistent part, reproducing the polynomial space, and a correction term ensuring stability. In the present contribution, we outline an extended virtual element method (X-VEM) for two-dimensional elastic fracture problems where, drawing inspiration from the extended finite element method (X-FEM), we extend the standard virtual element space with the product of vector-valued virtual nodal shape functions and suitable enrichment fields, which reproduce the singularities of the exact solution. We define an extended projection operator that maps functions in the extended virtual element space onto a set spanned by the space of linear polynomials augmented with the enrichment fields. Numerical examples in 2D elastic fracture are worked out to assess convergence and accuracy of the proposed method for both quadrilateral and general polygonal meshes.

Numerical treatment of the vectorial equations of solar oscillations

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:01:35 +0100

Driven by the challenging task of finding robust discretization methods for Galbrun's equation, we investigate conditions for stability and different aspects of robustness for different finite element schemes on a simplified version of the equations. The considered PDE is a second order indefinite vector-PDE which remains if only the highest order terms of Galbrun's equation are taken into account. A key property for stability is a Helmholtz-type decomposition which results in a strong connection between stable discretizations for Galbrun's equation and Stokes and nearly incompressible linear elasticity problems.

Hybrid Finite-Volume/Discontinuous Galerkin framework for the solution of Multiphysics problems using unstructured meshes

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 14:01:15 +0100

A hybrid FV/DG framework is developed for the simulation of compressible multispecies flows on unstructured meshes with a five-equation Diffuse-Interface Model [1]. The high order DG method is employed for the purpose of limiting the material interface smearing typical of the diffuse-interface models resulting from excessive numerical dissipation [2, 3]. In order to ensure high-order accuracy in smooth flow regions and non-oscillatory behaviour near shocks or material interfaces, the hybrid scheme resorts to the underlying FV method when invalid cells are detected by a troubled cell indicator checking the unlimited DG solution, and enables a highorder non-linear CWENOZ reconstruction [4,5] if the solution present oscillations. The CWENO and CWENOZ type reconstruction uses a high-order polynomial for the central stencil and a lower-order polynomial for the directional stencils enhancing robustness and efficiency of classic WENO schemes. To achieve consistency in advecting material interfaces at constant pressure and velocity, the source term from the non-conservative equation is discretised compatibly with the Riemann solver, following the work of Johnsen and Colonius [6].

Under-resolved Direct Numerical Simulation of NACA0012 at Stall

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:27:16 +0100

In this work a high-order spectral-h/p element solver is employed to efficiently but accurately resolve the flow field around the NACA0012 aerofoil.

A PINN computational study for a scalar 2D inviscid Burgers model with Riemann data

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:27:00 +0100

In this work, we present an application of modern deep learning methodologies to the numerical solution of two dimensional hyperbolic partial differential equations in transport models. More specifically, we employ a supervised deep neural network that takes into account of initial-boundary value problems for a scalar, 2D inviscid Burgers model including the case with Riemann data, whose solutions develop discontinuity, containing both shock wave and rarefaction wave. We also apply the proposed PINN approach to the linear advection equation with periodic sinusoidal initial condition. Our results suggest that a relatively simple deep learning model was capable of achieving promising results in the linear advection and inviscid Burgers equation with rarefaction, providing numerical evidence of good approximation of weakentropy solutions to the case of nonlinear 2D inviscid Burgers model. For the Riemann problems, the neural network performed better when rarefaction wave is predominant. The premises underlying these preliminary results as an integrated physics-informed deep learning approach are promising. However, there are hints of evidence suggesting specific fine tuning on the PINN methodology for solving hyperbolic-transport problems in the presence of shock formation in the solutions.

Using Graph Neural Network for gas-liquid interface reconstruction in Volume Of Fluid methods

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:26:40 +0100

The volume of fluid (VoF) method is widely used in multi-phase flow simulations to track and locate the interface between two immiscible fluids. A major bottleneck of the VoF method is the interface reconstruction step due to its high computational cost and low accuracy on unstructured grids. We propose a machine learning enhanced VoF method based on Graph Neural Networks (GNN) to accelerate the interface reconstruction on general unstructured meshes. We first develop a methodology to generate a synthetic dataset based on paraboloid surfaces discretized on unstructured meshes. We then train a GNN based model and perform generalization tests. Our results demonstrate the efficiency of a GNN based approach for interface reconstruction in multi-phase flow simulations in the industrial context.

Parametric Compressible Flow Predictions using Physics-Informed Neural Networks

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:26:18 +0100

The numerical approximation of solutions to the compressible Euler and Navierstokes equations is a crucial but challenging task with relevance in various fields of science and engineering. Recently, methods from deep learning have been successfully employed for solving partial differential equations by incorporating the equations into a loss function that is minimized during the training of a neural network. This approach yields a so-called physics-informed neural network which does not rely on a classical discretization and can address parametric problems in a straightforward manner. Therefore, it avoids characteristic difficulties of traditional approaches, such as finite volume methods. This has raised the question, whether physics-informed neural networks may be a viable alternative to conventional methods for computational fluid dynamics. Here, we show a new physics-informed neural network training procedure to approximately solve the two-dimensional compressible Euler equations, which makes use of artificial dissipation during the training process. We demonstrate how additional dissipative terms help to avoid unphysical results and how the additional numerical viscosity can be reduced during training while iterating towards a solution. Furthermore, we showcase how this approach can be combined with parametric boundary conditions. Our results highlight the appearance of unphysical results when solving compressible flows with physics-informed neural networks and offer a new approach to overcome this problem. We therefore expect that the presented methods enable the application of physics-informed neural networks for previously difficult to solve problems.

Feedback reconstruction techniques for optimal control problems on a tree structure

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:25:59 +0100

The computation of feedback control using Dynamic Programming equation is a difficult task due the curse of dimensionality. The tree structure algorithm is one the methods introduced recently that mitigate this problem. The method computes the value function avoiding the construction of a space grid and the need for interpolation techniques using a discrete set of controls. However, the computation of the control is strictly linked to control set chosen in the computation of the tree. Here, we extend and complete the method selecting a finer control set in the computation of the feedback. This requires to use an interpolation method for scattered data which allows us to reconstruct the value function for nodes not belonging to the tree. The effectiveness of the method is shown via a numerical example.

Structure-Preserving Neural Networks for the N-body Problem

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:25:42 +0100

In order to understand when it is useful to build physics constraints into neural networks, we investigate different neural network topologies to solve the N -body problem. Solving the chaotic N -body problem with high accuracy is a challenging task, requiring special numerical integrators that are able to approximate the trajectories with extreme precision. In [1] it is shown that a neural network can be a viable alternative, offering solutions many orders of magnitude faster. Specialized neural network topologies for applications in scientific computing are still rare compared to specialized neural networks for more classical machine learning applications. However, the number of specialized neural networks for Hamiltonian systems has been growing significantly during the last years [3, 5]. We analyze the performance of SympNets introduced in [5], preserving the symplectic structure of the phase space flow map, for the prediction of trajectories in N -body systems. In particular, we compare the accuracy of SympNets against standard multilayer perceptrons, both inside and outside the range of training data. We analyze our findings using a novel view on the topology of SympNets. Additionally, we also compare SympNets against classical symplectic numerical integrators. While the benefits of symplectic integrators for Hamiltonian systems are well understood, this is not the case for SympNets.

An accelerated deflation preconditioner for parametric systems based on subspace recycling

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:25:27 +0100

Krylov subspace recycling [1] is often deployed to accelerate the iterative solution of sequences of linear systems. Such approaches reuse a continuously updated deflation subspace to reach a converged solution within a low number of iterations. This procedure is justified for problems that describe gradually evolving phenomena, such as crack propagation, and thus involve a sequence of systems that are not simultaneously available. However considering parametric systems, these techniques might induce an unnecessary overhead cost. Specifically, by constantly updating the recycled subspace a new projection on the newly constructed subspace needs to be operated for each new system, inducing a cost that scales with O( × N2) for dense systems, where N is the size of the system and is the size of the employed recycled basis. In that context, this work proposes an accelerated recycling procedure for parametric systems that is inspired by the Galerkin Model Order Reduction strategy and employs an offline online operation splitting. In the offline part, the subspace to be recycled is constructed via an Automatic Krylov subspaces Recycling algorithm (AKR) [2] and the parametric system is projected on the subspace to yield a Reduced Order Model (ROM). Then, in the online part the construction of the deflation preconditioner only requires employing the ROM and as a result the cost of constructing the preconditioner is reduced to O(2). The proposed procedure is tested on a randomly parametrized linear system and is compared the non-deflated GMRES algorithm and a conventional recycling strategy presented in [11].

Mixed finite element formulations and energy-momentum time integrators for thermo-viscoelastic gradient-based fiber-reinforced continua

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:25:11 +0100

Nowadays, fibre-reinforced materials and their accurate dynamic simulation play a significant role in the construction of lightweight structures. On the one hand, we are dealing with locking of the matrix material as well as the fibres, thermal expansion, the directed heat conduction through the fibres and viscoelastic behaviour in such materials. The material reinforcement is performed by fiber rovings with a separate bending stiffness, which can be modelled by second order gradients. On the other hand, we also want to perform accurate long-term simulations. In this presentation, we focus on numerically stable dynamic long-time simulations with locking free meshes, and thus use higherorder accurate energy-momentum schemes emanating from mixed finite element methods. We adapt the variational-based space-time finite element method in Reference [1] to the material formulation, and additionally include independent fields to obtain well-known mixed finite elements [2, 3].

A tensor-product finite element cochain complex with arbitrary continuity

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:24:59 +0100

We develop tensor product finite element cochain complexes of arbitrary smoothness on Cartesian meshes of arbitrary dimension. The first step is the construction of a onedimensional Cm-conforming finite element cochain complex based on a modified Hermite interpolation operator, which is proved to commute with the exterior derivative by means of a general commutation lemma. Adhering to a strict tensor product construction we then derive finite element complexes in higher dimensions.

Least-Squares and DPG approximation of eigenvalue associated to coupled problems

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 13:24:48 +0100

The Arts and Science Contest of the ECCOMAS Young Investigators Committee (EYIC) aims to show science in all its beauty and elegance, by visualizing scientific works with an artistic point of view. The competition was open to every participant with an accepted the visuals were uploaded in 4 groups on the ECCOMAS Facebook page, one group per week. The visual with the most likes of each group was put in the finalists short-list, and a jury chose the final winners of the contest. The starry night of reaction diffusion won this competition and the present contribution presents the numerical method behind the picture.

DEVELOPMENT OF METHODOLOGICAL APPROACHES TO LONG-TERM BUDGET FORECAST IN THE REGIONS OF THE RUSSIAN FEDERATION

Евгений Семенов — Tue, 22 Nov 2022 12:21:03 +0100

The subject of this research is the analysis of long-term budget forecasts of the constituent units of the Russian Federation. The relevance of the study is determined by the need to update the Methodological Recommendations of the Ministry of Finance of Russia on the preparation of long-term regional budget forecasts, which have not been updated since 2015. The goal of the study is to develop recommendations for the constituent units of the Russian Federation to improve the long-term budget forecasting. The scientific novelty of the study lies in identifying, based on the examination of subnational experience of foreign countries, “the best practices” that can be used in Russia for long-term budget forecasting, and analyzing the quality of existing long-term budget forecasts of the constituent units of the Russian Federation. The research method is the analysis of international and domestic experience of building budget forecasts, methods of grouping, system analysis and synthesis. This study used data from official websites of the foreign authorities responsible for long-term budget forecasting, as well as approved long-term budget forecasts of the constituent units of the Russian Federation, presented in the ConsultantPlus: Regions legal reference system and on the official Internet sites of the executive authorities of the constituent units of the Russian Federation. Based on the results of the study, recommendations were formulated for the regions of the Russian Federation to improve the quality of budget forecasting: increase of the forecasting horizon to at least 30 years, which includes short-term, medium-term and long-term components, with a description of each component’s features, modification of the composition and structure of long-term budget forecasts, determination of the relationship with the regional budget, medium-term budget forecasts, specifying the practical role of the forecast in political and budgeting processes. The authors conclude that a forecast should be used not only in its conventional form of a document approved by the regional regulatory documents, but also as a calculator with parameters (a set of formulas) for internal use by the regional financial authorities, used to assess the budgetary implications of the proposed measures and decisions and to calculate the limitations of budget parameters in the process of drafting the budget. Research prospects are to analyze the results of pilot implementation of the proposed approach to long-term budget forecasting in Russian regions

THEORETICAL AND EMPIRICAL ASPECTS OF DETERMINING THE EXPECTATIONS OF ECONOMIC AGENTS BASED ON TEXT ANALYSIS

Евгений Семенов — Tue, 22 Nov 2022 11:57:02 +0100

The Internet is a public source of information, where information can be found at minimum search cost. Social media are becoming increasingly popular among web users trying to find and analyze information about the current economic situation. Web users get the opportunity to exchange views or discuss various issues in the news communities of social networks. This information can be used by economic agents to make decisions. Thus, the study of user behavior in social networks makes it possible to identify the expectations and preferences of economic agents.

The goal of this study is to assess the expectations and sentiments of economic agents based on textual analysis of social media data.

The study addresses the following objectives:

Analysis of the mechanisms of influence of the information dissemination and networking effects on the behavior of economic agents;

Systematization of the results of theoretical and empirical analysis of the economic agents’ expectations;

An overview of machine learning methods used in text processing;

Development of an algorithm for identifying sources of information for web scraping and rules for selecting text information to create a body of posts and comments;

Collecting a database and preparing posts and comments for text analysis;

Application of topic modeling to the identification of topics and keywords in social media data;

Assessment of high-frequency indicators of the public sentiment.

The subject of the research is a quantitative assessment of the sentiment of web users based on Russian data.

The novelty of the study is the assessment of inflation expectations, sentiments in the foreign exchange market and indices of economic conditions using structured and unstructured internet data. Methods: topic modeling; machine learning methods and econometric methods of time series analysis.

The study is based on data for Russia in 2014-2021. The study shows that social media posts, search queries and online news articles can be good proxy variables for the economic agents’ expectations. We construct three types of public confidence indicators based on internet data: inflation expectations; sentiment in the foreign exchange market and index of economic conditions. The results of econometric analysis indicate that the quality of macroeconomic performance models with sentiment indicators is higher than without these indicators. Additionally, indicators based on VK posts, RBC news articles and Google Trends search queries are more informative compared to comments. The main conclusion of the study is that internet data can improve the quality of macroeconomic performance models. In a further study, we plan to expand the list of indicators of the sentiment of economic agents and to evaluate advanced time series models

MODELLING THE EFFECTS OF BANK OF RUSSIA’S MONETARY POLICY ON EAEU COUNTRIES

Евгений Семенов — Tue, 22 Nov 2022 11:25:03 +0100

In this paper we estimate the effects of the Bank of Russia’s monetary policy on the Eurasian Economic Union members. The relevance of the study arises from two points: first, economic integration implies coordination in macroeconomic policy; second, fluctuations of Russian economy as the biggest economy in the region cause fluctuations in the whole EAEU, changing the flows of goods and resources. The purpose of this paper is to identify key effects and channels of cross-border transmission of Bank of Russia’s monetary policy under changing monetary regimes of the EAEU countries. For the empirical model we use quarterly data on EAEU key macroeconomic indicators from 2000 to 2021, the basic method is block-exogenous structural vector autoregression. Our results show that interest rate channel plays the key role in cross-border transmission of monetary policy effects in the region. The exception is the case when the recipient’s country central bank employs fixed exchange rate regime, rendering international interest rate channel ineffective. Another important channel is international trade: monetary policy tightening leads to the contraction of demand for the imported goods, so the exports of the recipient countries decrease. We conclude that despite heterogenous response among the EAEU countries to monetary shocks occurring in Russia, monetary policy tightening decreases economic activity in the whole economic union. The study can be extended in several ways like the analysis of the synchronization in systematic monetary policy decisions in EAEU or detailed estimations of financial channels of international transmission using banking statistics

THEORETICAL BASIS OF STATE DECENTRALIZATION

Евгений Семенов — Tue, 22 Nov 2022 11:19:03 +0100

The issue of decentralization in the public administration system in Russia has acquired new urgency in the context of the 2020 crisis. Other countries of the world have faced similar new challenges. The object of the research is the system of separation of powers between regions and the center in a federal state. The purpose of the study is to determine the principles and limitations of authority delegation from higher to lower tiers (i.e. decentralization), potential benefits and prerequisites of delegation. This research provides an extensive review of the literature on decentralization around the world. Based on the analysis of findings and their synthesis, theoretical ideas are formed as to how to distribute powers within the budgetary system, as well as how decentralization and economic growth are connected. Scientific novelty of the paper lies in revealing the prospective areas of research on the problems of authority delegation and economic growth. It is established that decentralization and close interdependence of revenues and expenditures of territorial budgets promotes private sector development. At the same time, the risks of inefficiency of

ESEARCH OF THE PHENOMENON OF STUDENT BULLING

Евгений Семенов — Tue, 22 Nov 2022 11:08:03 +0100

Relevance. The Russian schooling system fails to effectively counteract bullying, a phenomenon common in educational organizations around the world, including the Russian Federation. According to the 2019 PISA report for OECD countries, 12% of all children in Russia were identified as victims of school bullying. More and more parents are transferring their children to homeschooling, having lost confidence in the school as an organization capable of ensuring safety: today, bullying experience is linked to child suicides and school shootings. Traditional disciplinary methods do not work in the case of bullying, due to the specificity of this socio-psychological phenomenon. Research object: the phenomenon of bullying in the student environment. Subject: scientifically grounded methodological basis for anti-bullying activities of an educational organization (EO), taking into account the specifics of bullying. Study goal: based on the analysis of international and domestic studies of the phenomenon of school bullying, to create a clear and scientifically grounded basis of anti-bullying activities for educational organizations (EO). Study objectives: to analyze international and domestic research of bullying; to create theoretical basis for the model of anti-bullying activities for schools; to develop guidelines for the organization of anti-bullying activities in schools. Results. Analysis of studies in Russian, English, German languages enabled us to answer key questions about the nature of bullying, patterns and mechanisms of its development, and to give a theoretical basis for the model of anti-bullying activities of EOs, to propose guidelines for organizing anti-bullying activities of EOs. Conclusions: Bullying as a socio-psychological phenomenon, due to its complexity, is immune to the traditional administrative pedagogical methods of influence: special knowledge and skills are required from all involved persons - adults and children. The global experience offers a number of models of anti-bullying activities of educational organizations that have empirically proven to be efficient. They are consistent, with a clear division of goals into levels (school-wide, intra-class, individual psychological: working with victims, working with initiators, working with witnesses, working with parents), assuming leadership and full responsibility by the principal. Recommendations: 1) practical recommendations for organizing anti-bullying activities of EOs – an organizational model, an “emergency response protocol”, and methodological support for the work of employees of an educational organization, – enable developing anti-bullying action programs, but the task of adapting them to the Russian environment, conditions of individual regions and EOs remains urgent, as well as the creation of advanced training programs for school principals and class teachers, educational psychologists and social educators by regional Advanced Training Institutes (ATI). 2) This research requires further development in particular, in relation to the figure of the teacher, who often acts both as a victim of bullying and as its initiator

THE RELEVANT SCIENTIFIC AND METHODOLOGICAL APPROACHES TO ENSURING FUNDAMENTAL HUMAN RIGHTS IN DATA PROCESSING IN PUBLIC ADMINISTRATION

Евгений Семенов — Tue, 22 Nov 2022 10:58:02 +0100

Enforcing fundamental human rights is a constitutional obligation of the Russian Federation. In the digital age, the risks of human rights violations are increasing, making it increasingly relevant to implement a consistent state policy related specifically to data processing in public administration. The objective of this paper is to analyze the scientific and methodological approaches to enforcing fundamental human rights in data processing in public administration and the possibilities for consideration of human rights in the Russian public administration. The subject of the study includes scientific publications, court cases, international and national laws and regulations, including foreign countries. The study uses formal legal and historical legal methods, comparative legal method, method of legal interpretation, logical analysis, general scientific methods of classification and modeling. The results of the study are an analytical review of foreign and Russian scientific and methodological approaches to enforcing fundamental human rights in data processing in digital public administration; systematization of the basic legal grounds for enforcing fundamental human rights in data processing in public administration; the proposals for legal enforcement of fundamental human rights in data processing in the Russian public administration. The study allows drawing conclusions about the lack of attention in the Russian doctrine and practice to the issue of fundamental rights. Since Russian legislation in this area is based on the European model, the implementation of European approaches to data protection is recommended. It is necessary to create special legislation on data processing in public administration, to define the criteria for proper data processing and data storage, to differentiate the types of data collection and data processing, to ensure transparency. Based on advanced digital technologies, data processing rules in the public sector should be stricter and more transparent than in the private sector. The scientific novelty of the research is determined by insufficient regulation of data processing in public administration, where the constitutional function of enforcement and protection of fundamental human rights is not sufficiently regulated. Based on the results of the study, recommendations are to use the findings in the formation of an appropriate state policy to enforce fundamental human rights in data processing in the Russian public administration

DEVELOPMENT TOOLS FOR THE FAR EAST AND THE ARCTIC OF RUSSIA

Евгений Семенов — Tue, 22 Nov 2022 10:51:03 +0100

Studying the development problems of the Arctic and the Far East has always been relevant due to the specific nature of these territories. At the same time, the existing support tools do not always consider this specificity, which is why the effects of their use are minimal.

In this regard, the purpose of this study is to develop recommendations for improving the social and economic development policy tools for the Far Eastern and Arctic regions. This goal will be addressed within the framework of solving the following tasks:

systematization of existing development tools,

assessment of the economic and social effects of the measures applied,

producing recommendations for the development or exclusion of existing tools.

The study was conducted using the methods of content analysis, retrospective analysis, and classification. The sources of information included regulatory documents and strategic planning documents, scientific publications, analytical data, and official statistics.

As a result, a list of measures for the development of the regions of the Far East and the Arctic was produced, and areas that required improvement were identified. The key findings are as follows.

Most of the development tools are focused on stimulating economic growth and increasing investment appeal, rather than improving the demographic situation.

The measures taken fail to translate into the expected economic and social effects. The number of specific and individual instruments for stimulating the socio-economic development of the Far East and the Arctic is insignificant. Some of the instruments duplicate each other, which entails uncertainty when considering opportunities for capital investments, disorienting potential investors.

As recommendations, it is proposed to review the list of instruments towards greater social support, development of individual mechanisms, and unification of territorial development instruments with overlapping scopes.