Colloquiam: Documents published in 2022

Simulation and experimental investigation of tire tread block wear in three-body contact

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:36:54 +0100

On gravel roads, tires are not in direct contact with the surface. Particles of e.g. sand or stone contact directly with the tire and cause the tire to wear. During the sliding process, an interaction between particles and the tire occurs. On simplified conditions investigation of the movement of particles, friction and wear of a tire tread sample are done experimentally for different settings. Additionally, a finite element simulation is built up to simulate the wear of the tire tread sample under varying conditions. In this paper results from the experimental and numerical investigation of the wear of the tire tread sample are shown.

Microscale numerical simulation of yarn tensile behavior using a high-fidelity geometrical fiber model extracted from micro-CT imaging

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:36:36 +0100

Air jet weaving, where the weft yarn is transported through the machine using air as propelling medium, is a popular weaving method due to its superior productivity, however at the cost of a high energy demand. The interactions between the weft yarn and the air jets are complex and not yet fully understood. Moreover, state-of-the-art techniques to simulate these interactions, are far from mature since the yarn is often simplified as a smooth and solid cylinder. Therefore, a novel multi-scale and multi-physics approach is proposed to simulate the interaction between weft yarns and air jets. Starting from microcomputed tomography (µCT) scans of a yarn used in air jet weaving, a high-fidelity microscale geometrical model is constructed, representing the yarn by its fibers. This geometrical model is used as input for microstructural simulations and will be used for flow simulations on microscale, where the aim is to extract local coefficients and as such characterize the yarn. These coefficients are then used as input for computationally cheap macroscale models, where the yarn is represented by its centerline containing the microscale properties. In a final stage, the macroscale structural and flow models will be coupled as to obtain a full FSI simulation of a weft insertion in an air jet loom. Current paper highlights the microscale geometry extraction of a fine wool fiber yarn of 28.8 tex. Consecutively, a computational framework is proposed to simulate the tensile behavior of this yarn, using the previously obtained microscale geometrical model. The resulting stress-strain curve of the yarn is compared to experiments and shows good correspondence.

FEM analysis of FRCM strengthened RC columns exposed to fire

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:36:14 +0100

Reinforced concrete (RC) structures deteriorate over time and therefore, need to be strengthened. Despite the fact that RC structurtes have a decent fire rating, the performance of the strengthening system under fire exposure needs to be evaluated. One of the main restrictions associated with Fibre Reinforced Polymer (FRP) systems is their poor resistance to high temperatures, which originates from the combustible polymer matrix. Therefore, Fibre Reinforced Cementitious Matrix (FRCM) systems have been introduced due to their improved performance during fire exposure. The potential of Poly-paraphenylene-ben-zobisoxazole (PBO) FRCM to strengthen circular RC columns is evaluated using a nonlinear finite element analysis (FEA). The commericial software ABAQUS is used to develop 3D FE models to investigate the axial performance of the strengthening system. The modeling approach is performed by first conducting a thermal analysis to generate the nodal tempertaures. The second step of the model includes a displacement-controlled loading condition with imported nodal temperatures from the first model. The temperature dependent material properties are incorporated in both models. The modeling approach is validated against published literature and a parametric study is conducted on PBO FRCM strengthened and unstrengthened columns heated at durations of 1, 2, and 4 hours following the ASTM standard fire temperature-time curve. Results indicated a decrease in the axial capacity and stiffness of the strengthened and unstrengthened columns upon heating. Moreover, an increase in the columns' ductility due to the increase in temperature was observed. A decrease in ultimate strength of up to 78 and 68% was observed for the unstrengthened and strengthened columns respectively.

Theoretical procedure to predict the local buckling resistance of aluminium members in elastic-plastic range

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:27:59 +0100

In the present research work, a theoretical approach to evaluate the ultimate resistance of aluminium alloy members subjected to local buckling under uniform compression is provided.

A coupled multiphysics approach for modelling in-stent restenosis

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:27:40 +0100

Drug-eluting stents were developed to counteract the severe restenosis observed after bare-metal stent implantation. The risk of restenosis still prevailed due to the inhibitory effect of the drug on endothelial healing. The current work focuses on extending a multiphysics-based modeling framework to include the effect of anti-inflammatory drugs embedded in the drugeluting stents. An additional advection-reaction-diffusion equation governing the drug transport is introduced herein. Additionally, the effect of drugs, specifically rapamycin-based ones, on the proliferation of smooth muscle cells is captured. An optimal level of drug embedment is realized through the modeling framework.

Uncertainties of Parameters Quantification in SHM

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:27:23 +0100

The uncertainties of parameters quantification due to various known and unknown conditions are crucial to understand structural health monitoring (SHM) systems. For instance, the amplitudes and the variation of loading conditions play a vital rule how the structural parameters are going to be changed. Hence, the aforementioned issue leads to an additional challenge in the area of SHM that requires attention. This study observed the behaviour of a steel bridge experimentally by employing multi-sensors scenarios e.g. accelerometers and laser triangulation sensor. The dynamical properties such as the peak (e.g. maximum-minimum) accelerations and displacements are evaluated. Additionally, the frequencies and damping ratio from the measured data of the tested bridge has been estimated by utilizing the fast Fourier transform (FFT) estimation. The outcome shows that the variation of input excitations (i.e., random, free-decay, extra-loading) effects the investigated properties as well as on their magnitudes considerably. Therefore, the findings suggest that before making a final judgement based on the identified/estimated properties from measured data, the underlying uncertainties need to be considered to avoid sub-optimal assessment strategy.

Multi-objective optimization for understanding tree design rules with finite element modelling.

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:27:04 +0100

This research presents an optimization problem, which aims to understand the inherent design rules of the shape of a tree. It makes use of a classical optimization problem, the Nowacki beam, which consists of a cantilever beam with a point load at the end which seeks to obtain the lowest cross-sectional area and bending stress under a set of constraints [1]. Forrester et al. developed an algorithm to address this problem [2] by means of machine learning techniques. They began defining the beam properties and building a distributed random sampling plan and then computed the objective function and constraint functions. The process starts from an initially computed dataset that is used to train Kriging models, which are later used as a filling strategy, and genetic algorithms, as an optimization strategy. The result of each iteration is added to the dataset, and the process is repeated until convergence is found. In this way, the Pareto front with the optimal solutions is obtained.

Constitutive model for the analysis of the behavior and mechanics of wood damage

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:26:47 +0100

Wood is a heterogeneous material, whose morphology and topology make the prediction of its mechanical behavior complex under different boundary conditions [1-3]. In this way, different constitutive models with different scale lengths have been developed since the middle of the 20th century to predict the behavior and mechanics of wood damage [3-8]. However, there is still no agreement on which constitutive model or scale length allows for a more consistent representation of behavior and damage mechanics mentioned. This article seeks to contribute to the discussion a new constitutive model for the analysis of the behavior and mechanics of wood damage. To do this, we present the implementation in a user subroutine for Abaqus [9], of a viscoelastic constitutive model based on the generalized well criterion for the elastic regime with a macroscale model [10] [11]; the onset and the damage evolution law are analyzed under a mesoscale model based on the progressive degradation of cracking parallel and perpendicular to the fiber [12-14]

Taut domain analysis of transversely isotropic dielectric elastomer membranes

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:26:28 +0100

Actuation devices made of dielectric elastomers are prone to compression induced wrinkling instabilities, which can adversely affect their performance and may lead to device failure. On the other hand, wrinkles can be used constructively in certain applications demanding a controlled alternation of the surface morphology. The idea of taut states and the natural width under simple tension plays an important role in the analysis of compression generated instability (wrinkling). In case of electrically driven DE membranes, the domain of taut states in the plane of principal stretches is influenced substantially by the applied voltage and the film's constitutive properties. In the recent past, there has been an increasing interest in exploiting anisotropy in the material behavior of dielectric elastomers for improving their actuation performance. Spurred with these ongoing efforts, this paper presents a continuum mechanics based electromechanical model for predicting the thresholds on the domain of taut states of transversely isotropic planar dielectric elastomers. The developed analytical framework uses an amended energy function that accounts for the electromechanical coupling for a class of incompressible transversely isotropic dielectric membranes. The required expressions for the total Cauchy stress tensor and the associated principal stress components are evaluated utilizing the amended energy function. Finally, the concept of natural width under simple tension is implemented to obtained the nonlinear coupled electromechanical equation that evaluates the associated taut states domain of the transversely isotropic planar dielectric elastomers. Our results indicate that the extent of taut domain can be controlled by modifying the level and the principal direction of the transverse isotropy. The taut states domain for a particular level of applied electric field increases with increase in the anisotropy parameter, while the taut domains depleted with the increase in fiber orientations from 00to 900for an applied level of electrical loading. The fiber-reinforced wrinkle-tunable surfaces can be effectively designed and developed using the underlying analytical framework and the trends obtained in this study.

Energy-momentum conserving dynamic variational modeling of fiber-bending stiffness in composites

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:26:09 +0100

We propose a new variational formulation for large deformations in dynamical systems made of 3D-fiber-reinforced composites. The formulation emanates from the dynamic variational approach based on the principle of virtual power. The use of higher-order gradient theory along with multi-field mixed-finite element method enables us to model the fiber-bending stiffness in fiber reinforced composites for numerical simulations accurately. Our proposed model capture higher-order energy contributions exhibited by fibers that influence the fiber-bending curvature, and consequently the fiber-bending stiffness behaviour. For this, we introduce a higher-order gradient of the deformation mapping as an independent field in the internal energy functional formulation. Along with the energy-momentum scheme, our new time integrator makes possible to perform long-term dynamic simulations with larger time steps and efficient CPU-time. We demonstrate our model using transient dynamical simulations on thre geometrical examples that exhibit hyperelastic, transversely isotropic, polyconvex gradient material behaviour. In the first example, a cantilever beam is self-excited due to its body weight, in the second, a L-shaped block tumbles free in the ambient space after an initial loading phase and in the third a turbine rotor is rotated due to hydrodynamic pressure. It is observed that our model conserves total momenta and total energy and preserves their time evolution in all these examples along with spatial and temporal convergence.

From freezing-induced to injection-induced non-isothermal saturated porous media fracture

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:25:55 +0100

The focus of this contribution is laid on different aspects and instances related to porous media fracture under non-isothermal conditions. This includes the extreme case of fracturing due to pore-fluid freezing, where the micro-cryo-suction plays an important role in generating the required stresses for crack onset. This also includes studying the instances related to hydraulic fracturing and heat transfer under non-isothermal conditions. In all cases, the continuum mechanical modeling of the induced fractures is based on macroscopic porous media mechanics together with the phase-field method (PFM) for fracture modeling. For the micro-cryo-suction in saturated porous media, the water freezing is treated as a phase-change process. This is modeled using a different phase-field approach, in which the thermal energy derives the phase change and, thus, leads to the occurrence of micro-cryo-suction. Two numerical examples are presented to show the effectiveness of the proposed modeling frameworks.

Efficient dispersion curve computations for periodic vibro-acoustic structures using the (generalized) Bloch mode synthesis

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:25:34 +0100

Periodic structures such as metamaterials and phononic crystals hold potential as promising compact and lightweight solutions for noise and/or vibration attenuation in targeted frequency ranges. The performance of these structures is usually investigated by means of dispersion curves. The input for dispersion curve computations is often a finite element model of the corresponding unit cell. Nowadays, the vibration and noise attenuation of the periodic structures are generally tackled as separate problems and their performance is investigated with either structural or acoustic dispersion curves, respectively. Recently, vibro-acoustic unit cell models have come to the fore which can exhibit simultaneous structural and acoustic stopbands. However, the vibro-acoustic coupling inside the unit cell is usually not taken into account during the dispersion curve computations. To consider this coupling during their performance assessment, the computation of vibro-acoustic dispersion curves is required. Although these dispersion curves provide valuable information, the associated computational cost rapidly increases with unit cell model size. Model order reduction techniques are important enablers to overcome this high cost. In this work, the Bloch mode synthesis (BMS) and generalized BMS (GBMS) unit cell model order reduction techniques are extended to be applicable for 2D and 3D periodic vibro-acoustic systems. Through a verification case, the methodologies are shown to enable a strongly reduced dispersion curve calculation time while maintaining accurate predictions.

A hybrid-Trefftz finite element for the postbuckling analysis of composite shell structures

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:25:15 +0100

A corotational mixed flat shell element for the geometrically nonlinear analysis of laminated composite structures is presented. The stress interpolation is derived from the linear elastic solution for symmetric composite materials.Displacement and rotation fields are only assumed along the contour of the element. As such, all the operators are efficiently obtained through analytical contour integration. The geometrical nonlinearity is introduced by means of a corotational formulation. The proposed finite element, named MISS-4c, proves to be locking free and shows no rank defectiveness. A multimodal Koiter's algorithm is used to obtain the initial postbuckling response. Results show good accuracy and high convergence rate in the geometrically nonlinear analysis of composite shell structures.

Two-scale asymptotic homogenization in a MEMS auxetic structure for over etch identification

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:24:55 +0100

The development and optimization of Micro electro-mechanical systems (MEMS) devices, due to their small size scale, require testing and precise characterization. As an example, over etch, which is the deviation between the designed masks and the effective dimensions of the suspended parts, strongly influences the performances of MEMS; therefore, to predict the correct functioning of the device its actual value must be carefully identified. In this work, we propose an efficient, time-saving tool to identify fabrication imperfections in MEMS devices. In particular, we replace the complex geometry of a MEMS mechanical filter with an equivalent homogeneous medium, whose linear-elastic effective properties are evaluated employing twoscale asymptotic homogenization and we identify the over etch by minimizing the relative error between experimental data and corresponding predictions obtained for different combinations of over etch.

Development of a 3D visco-elastic model for wood under large deformations

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:24:33 +0100

Some of the most frequently observed phenomena in structural materials are creep and relaxation. Both are associated with time-dependent behavior and dissipative rheological variables. In the case of wood, long-term creep can produce excessive deformation and instability problems by magnifying short-term deflections. Also, wood presents changes in its mechanical properties due to its hygroscopy, so that moisture appears as an important parameter to be considered. A priori, it is known that the moisture content in wood cells and the angle of microfibrils are parameters that directly affect the overall cell stiffness. With this information, material physics hypotheses can be elaborated to develop a constitutive model in large deformations to predict phenomena such as creep and relaxation in the medium and/or long term. The microstructure of the cell wall can be represented through a model of fiber-reinforced composite material originally developed for biomaterials such as arteries and fibrous tissues. Where the anisotropic character is conferred by the distribution of the fibers within the isotropic matrix of the material. This work aims to adapt these models to represent the mechanical behavior of the wood cell with faithful representation of its microstructure. FEniCS is used for the numerical implementation of the material. In this paper the validations, current status, conclusions, and perspectives of this research are presented.

Simulation of soft robots with nonlinear material behavior using the cosserat rod theory

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:24:15 +0100

For the simulation and model-based control of soft robots accurate models are required. In this contribution the simulation of a simple soft robot with the cosserat rod theory is examined for both linear and nonlinear material models. The soft robot is fabricated out of silicone. Thereby stiffness and damping properties are investigated. In addition to the achievable accuracy, the computation time is also examined.

Architectured and additively manufactured double-negative index metamaterials

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:23:52 +0100

Developing a new generation of multifunctional metamaterials with unusual thermoelastic properties enables a wide range of industrial applications, particularly in the aerospace industry. However, obtaining metamaterials with target properties by the systematic design of their microstructure and architecture remains a major challenge to this day. Topology Optimization (TO) is a powerful tool that can be used to develop the so-called anepectic metamaterials that combine both negative Poisson's Ratio (NPR) and negative thermal expansion (NTE). Here, an overview of the existing contributions in the literature regarding such metamaterials is presented. A Finite Element (FE) model for an anepectic microstructure is presented here for the purpose of simulating in silico the experimental results obtained in previous works. It is noted that scarce contributions resort to TO to design such metamaterials and even fewer present experimental validation. The present work presents a state of the art of anepectic metamaterials and emphasizes thus the importance of the engineering-cycle completion, i.e., starting with the systematic and optimal design of metamaterials and ending up in prototype fabrication and its verification.

A gradient-extended anisotropic damage-plasticity model in the logarithmic strain space

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:23:29 +0100

Within this contribution, we discuss additional theoretical as well as numerical aspects of the material model developed in [1, 2], where a `two-surface' damage-plasticity model is proposed accounting for induced damage anisotropy by means of a second order damage tensor. The constitutive framework is stated in terms of logarithmic strain measures, while the total strain is additively decomposed into elastic and plastic parts. Moreover, a novel gradientextension based on the damage tensor's invariants is presented using the micromorphic approach introduced in [3]. Finally, going beyond the numerical examples presented in [1, 2], we study the model's ability to cure mesh-dependency in a three-dimensional setup.

Dynamic Response of Offshore Wind Turbines under Nonlinear Irregular Ocean Waves

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:23:11 +0100

Offshore wind turbines (OWT) are exposed to different categories of ocean waves during their lifetime. Most ocean waves are categorized in the second-order nonlinear theory in normal and severe sea states, and their spectra combine different heights and frequencies. In the present study, a model for the dynamic response of OWTs to the wave load obtained irregular second-order nonlinear ocean waves is proposed. The foundation-wave-structure interaction and the effect of the nacelle-rotor assembly are simulated. Numerical results are provided and discussed.

Wave Based Method for 2D Unsaturated Elastodynamic Soil under Harmonic Loading

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:22:56 +0100

The Wave Based Method (WBM), which describes field variables of a boundary value problem with weighted wave functions, is used to model a layered halfspace under harmonic loading. This 2D soil structure is investigated for partially saturated layers. According to the Berryman-Thigpen-Chin model (BTC model) the capillary effects between the water and air phases enclosed by pores are negligibly small for elastic waves in the low frequency range. The mixture of water and air is treated as one fluid, for which the material parameters used in Biot's theory for fully saturated poroelastic structures have to be computed. Within this work, the BTC model is applied to describe soil layers within a halfspace, which are not perfectly dry or fully saturated. It is presented how the degree of saturation within a partially saturated soil layer affects the system's response.

S-N-based Fatigue Damage Modelling of Offshore Structures

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:22:38 +0100

Recently proposed damage models are presented and compared. In addition, a deterministic algorithm for nonlinear fatigue damage monitoring is presented and discussed. Furthermore, the commonly adopted functional forms for damage modelling is proposed and the adequacy of their functional form is directly investigated by the help of experimental data. Thereafter, the accuracy and whether the presented models give conservative estimates in comparison to Miner’s rule are checked with experimental data. It is found that the proposed models generally perform better for various materials commonly subjected to fatigue. Finally, it is discussed how both the theory and deterministic algorithms now exist for both adopting nonlinear functions in design if the expected loading sequence can be determined, whereas it can always be adopted for fatigue based structural health monitoring.

Influences of the geometrical nonlinearity on the complex band structures of periodic lattice frame structures

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:22:18 +0100

In this study, the complex band structures of geometrically nonlinear periodic frame structures are calculated by using the Spectral Element Method (SEM). For this purpose, the spectral element matrix for a geometrically nonlinear beam element is derived. By solving the inverse eigenvalue problem for computing the complex dispersion curves k() instead of the conventional eigenvalue problem for calculating the real dispersion curves (k), the complex wave vector can be obtained, whose imaginary parts describes the evanescent behavior of the Bloch waves. Subsequently, the geometrically nonlinear effects on the evanescent behavior of the Bloch waves are investigated by evaluating the dispersion curves and the transmission spectra.

A variational-based mixed finite element formulation for liquid crystal elastomers

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:22:00 +0100

Liquid crystal elastomers (LCEs) are soft materials, which are capable of large deformations induced by temperature changes and ultraviolet irradiation [1]. Since many years, these materials are under investigation in experimental researches as actuator materials. LCEs arise from a nematic polymer melt, consisting of long and flexible polymer chains as well as oriented and rigid rod-like molecules, the so-called mesogens, by crosslinking. In order to numerically simulate LCE materials by using the finite element method, a continuum model is necessary, including in a thermo-viscoelastic material formulation of the polymer chains the orientation effects of the mesogens. This can be performed by introducing a normalized direction vector as an independent field, and deriving from additional (orientational) balance laws independent differential equations [2]. These differential equations describe the independent rotation of the rigid mesogens connected with the flexible polymer chains. The orientation-dependent stress law of LCEs arises from an anisotropic free energy, comparable with fibre-reinforced materials. But, in contrast to fibre-reinforced materials, the direction vector of a LCE model has to be independent. In contrast to [2], we apply a variational principle for deriving a new mixed finite element formulation, which is based on drilling degrees of freedom for describing the mesogens rotation [3]. This principle leads to an extended set of balance laws.

Laminar Flow Control along the Attachment Line of a Swept Wing

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:09:16 +0100

Reducing aircraft fuel consumption by maximising the extent of laminar flow on wings assumes that the initial flow, along the wing's attachment line, is laminar. However, if the wing is attached to a solid wall, the wing's attachment line can be contaminated by the turbulent boundary layer developing over the solid wall for flow conditions summarised in a critical Reynolds number (R) greater than 250. Since typical R values encountered in flight can be well above 400, techniques, such as wall suction along the wing's leading edge were developed to further delay the threshold R at which contamination occurs. The present paper presents the results from an experimental investigation performed on the ONERA DTP-A model fitted with leading edge suction capabilities. The experiment was performed in the ONERA F2 wind tunnel in the framework of the EU-funded Clean Sky 2 HLFC-WIN project (LPA-IADP platform), while the suction panels were manufactured by Aernnova, an aero-component manufacturing company. Hot film measurements and infra-red thermography showed that attachment line contamination could effectively be delayed up to threshold R values of 1000 for large suction flow rates. Although panels from different manufacturing processes and with different geometric characteristics were tested, no significant difference from these parameters were observed.

Investigation of performance metrics in regression analysis and machine learning-based prediction models

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:08:43 +0100

Performance metrics (Evaluation metrics or error metrics) are crucial components of regression analysis and machine learning-based prediction models. A performance metric can be defined as a logical and mathematical construct designed to measure how close the predicted outcome is to the actual result. A variety of performance metrics have been described and proposed in the literature. Knowledge about the metrics' properties needs to be systematized to simplify their design and use. In this work, we examine various regression related metrics (14 in total) for continuous variables, including the most widely used ones, such as the (root) mean squared error, the mean absolute error, the Pearson correlation coefficient, and the coefficient of determination, among many others. We provide their mathematical formulations, as well as a discussion on their use, their characteristics, advantages, disadvantages, and limitations, through theoretical analysis and a detailed numerical example. The 10 unitless metrics are further investigated through a numerical analysis with Monte Carlo Simulation based on (i) random guessing and (ii) the addition of random noise with various noise ratios to the predicted values. Some of the metrics show a poor or inconsistent performance, while others exhibit good performance as evaluation measures of the 'goodness of fit'. We highlight the importance of the usage of the right metrics to obtain good predictions in machine learning and regression models in general.

ANN-based surrogate model for predicting the lateral load capacity of RC shear walls

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:07:45 +0100

Reinforced concrete (RC) shear walls are often used as the main lateral-resisting component in the seismic design of buildings. They provide a large percentage of the lateral stiffness of the structure, and therefore, they may experience large shear stresses at some point under earthquake loading. Consequentially, to accurately predict their behavior, it is recommended to use detailed finite element (FE) modeling with appropriate non-linear constitutive models for concrete and steel. However, such types of simulations are challenging and could significantly increase the computational time required to obtain the analysis results. In this paper, we study the viability of creating an artificial neural-network-based surrogate model of the RC shear wall that is able to capture its nonlinear behavior and predict the results obtained with a detailed FE model, offering a much lower computational effort. For this purpose, we develop a detailed parametric non-linear FE model based on well-established practices and validated studies using the OpenSees finite element software framework. The FE model consists of multi-layer shell elements with the vertical and transverse reinforcement included as smeared rebar layers. The concrete layers implement a damage mechanism with smeared crack constitutive model, whereas the rebar layers consider a uniaxial plasticity material law. The parametric FE model is used to build a large database of RC walls of different sizes and characteristics, with their corresponding lateral load capacity that is obtained through the detailed non-linear pushover analysis. Finally, the obtained database is used to train and validate the ANN-surrogate model. The developed model is able to accurately predict the lateral load capacity of RC shear walls without the need of detailed FE modeling, thus drastically reducing the complexity and the computational time required for the numerical solution and providing a reliable and robust analysis alternative, with only small compromise of accuracy.

Stochastic Simulation of the Head Impact on Windscreens

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:06:41 +0100

In accidents involving cars with pedestrians, the impact of the head on structural parts of the vehicle takes a significant risk of injury. If the head hits the windscreen, the injury is highly influenced by glass fracture. In pedestrian protection tests, a head impactor is shot on the windscreen while the resultant acceleration at the COG of the head is measured. To assess the risk of fatal or serious injury, a head injury criterion (HIC) as an explicit function of the measured acceleration can be determined. The braking strength of glass which has a major impact on the head acceleration, however, is not deterministic but depends on production-related micro-cracks on the glass surface as well as on the loading rate. The aim of the present paper is to show a pragmatic method, how to include the stochastic failure of glass in crash and impact simulations. The methodology includes a fracture mechanical model for the strain rate-dependent failure of glass, the experimental determination of the glass strength for the different areas of a windscreen (surface, edge, and screen-printing area), the statistical evaluation of the experimental data and the computation of a HIC probability distribution by stochastic simulation.

A material interpolation technique using the simplex polytope

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:06:20 +0100

The Discrete Material Optimization (DMO) and the Shape Function with Penalization (SFP) constitute the state-of-the-art material interpolation techniques for identifying from a list of pre-defined candidate materials the most suitable one(s) for the structural domain. The candidate materials are represented on this list through their mechanical properties, and are interpolated within the domain of interest (DOI), whether that is the finite element (FE) domain or groups of FEs, so-called patches. Depending on the technique preferred to interpolate the mechanical properties within the DOI, a different type of weights is selected. Goal of the discrete material optimization problem (MOP) is to solve for these weights and determine for each FE/patch a unique material from the list. The current work extends the concept of the SFP technique by employing as weights the shape functions of the hyper-tetrahedral FE, the dimension of which is dynamically adapted depending on the number of candidate materials considered for the structural domain. This generalized hyper-tetrahedral FE constitutes what is defined as a simplex, and similar to the SFP technique each of its nodes is tied to a specific candidate material. In the context of discrete optimization and utilizing the shape functions of an abstract high-dimensional FE as weights for the candidate materials, the proposed interpolation technique secures the continuity between the number of candidate materials that can be considered for the structure, a feature lacking in the SFP technique. Additionally, given that the number of nodes forming the simplex FE is always one unit greater than the dimension of the space it is defined within, the dimension of the resulting MOP drops by one per DOI. The developed material interpolation technique is combined with the topology optimization problem (TOP) to formulate the concurrent material and topology optimization problem for compliance minimization of the structure. Finally, the latter is examined on the academic case study of the 3D Messerchmitt-B¨olkow-Blohm (MBB) beam for the case of the concurrent topology and discrete fiber orientation optimization problem.

Analytical modeling of shock wave stresses and spall caused by laser plasma in a material interface – application to paint stripping on aluminum substrates

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:06:04 +0100

In the present work, analytical and numerical models have been developed to calculate shock wave stresses caused by laser plasma in a material interface. The input pressure causing the shock wave has been derived from a laser-matter interaction model. The material velocity, stresses, and strains versus time in the two materials and the interface have been computed by solving the jump equations for conservation of mass and balance of momentum. The material interface has been considered as an immovable boundary while the back free surface as an unrestrained boundary. Spall fracture strength of the interface was evaluated and was used as stripping criterion. The model has been used for the fast computation of interfacial stresses causing paint stripping on aluminium substrates and the subsequent fast assessment of stripping initiation. An explicit finite element model combined with the cohesive zone modelling method and a spall fracture model have been developed. These models have been compared to each other in terms of time, accuracy and input properties demand and to the experimental results.

Coupled thermomechanical analysis of thermoplastic composite pipe by FEM simulations

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:05:46 +0100

Spoolable thermoplastic composite pipe (TCP) is an ideal alternative to traditional, heavier metallic counterparts for deepwater riser applications. During operation the pipe is subjected to mechanical loads simultaneously with through-wall thermal gradients arising from the mismatch between temperatures of hot pipe contents and cool surrounding ocean. In this work, structural analysis of TCP under coupled thermomechanical loads is performed using the finite element method (FEM). Temperature-dependent material properties are considered. Material safety factors for different laminate stacking sequences are compared and multi-angle stacking is shown to be effective for both pressure- and tensiondominated scenarios. Safety factors are also generated for TCP bent at reduced and elevated temperatures illustrative of spooling in different environments. It is clear that optimising the laminate for operation will adversely affect spooling capacity and vice-versa, i.e. TCP intended for extreme in-service conditions will require large spools.

Parallelization of a finite element solver for chemo-mechanical coupled anode and cathode particles in lithium-ion batteries

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:05:24 +0100

Two chemo-mechanical coupled models for electrode particles of lithium-ion batteries are compared. On the one hand a CahnHilliard-type phase-field approach models lithium intercalation, phase separation and large deformations in phase transforming cathode materials like lithium iron phosphate. On the other hand a chemo-mechanical particle model for lithium intercalation and large deformations for an anode material such as silicon is studied. The comparison of two different ways to define the deformation gradient for the large deformation approach and the two different material properties lead to differences in the resulting quantities and equations for the coupling of the chemo-mechanical model. The usage of an adaptive solution algorithm as well as the parallelization of the finite element solver via the message passing interface concept results in a more reasonable computation time to perform two-dimensional simulations. Both materials are numerically investigated and the results are compared from a physical point of view. When fast charging a battery, higher stress values are reached, which can cause a shorter cycle life. A strong scalability analysis shows good performance for the assembling, however a saturation occurs in the performance of the solver used.

Closed - form expressions for the optimum winding angles of fibres in laminated pressure vessels subjected to internal pressure and axial force

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:05:09 +0100

The present paper aims at deriving closed-form expressions for the optimum winding angles of fibres in laminated cylindrical pressure vessels subjected to internal pressure, axial load and torque. To achieve this goal, the state of the stress on the surface of the vessel is represented by a composite layered element subjected to general in-plane loading. The symbolic software Mathematica is used to formulate, solve the optimization problem and to generate the data of optimum fibre angles for different loading combinations. The generated data is fitted with simple polynomial expressions capable of accurately predicting the optimum winding angles. The optimization is performed for three candidate composite materials: carbon/epoxy, glass/epoxy, and aramid/epoxy laminates.

Deep neural networks for unsupervised damage detection on the Z24 bridge

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:04:48 +0100

During their life-cycle, civil infrastructures are continuously prone to significant functionality losses, primarily due to material's degradation and exposure to several natural hazards. Following these concerns, many researchers have attempted to develop reliable monitoring strategies, as integration to visual inspections, to efficiently ensure bridge maintenance and early-stage damage detection. In this framework, recent improvements in sensor technologies and data science have stimulated the use of Machine Learning (ML) algorithms for Structural Health Monitoring (SHM). Among unsupervised learning techniques, the potential of autoencoder networks has been attracting notable interest in the context of anomaly detection. In this light, the present paper proposes two different autoencoder-based damage detection techniques, focused on the Multi-Layer Perceptron (MLP) and the Convolutional Autoencoder (CAE) networks, respectively. During the training, the selected ML models learn how reconstructing raw acceleration sequences acquired from sound conditions. Unknown data, including both healthy and damaged bridge responses, are afterwards used to test the implemented networks and to detect damage occurrence. To this aim, a specific index of reconstruction loss is selected as a damage sensitive feature with the aim to quantify the errors between the original and reconstructed sequences. The performance exhibited by the two approaches is compared and evaluated by application to the Z24 benchmark bridge. Results demonstrate the effectiveness of the proposed methodology to perform feature classification and real time damage detection at the level of macro-sequences as new sensor data is collected, resulting suitable for continuous assessment of full-scale monitored bridges.

Investigation of higher harmonic Lamb waves for facilitating delamination characterization

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:04:32 +0100

We advance this field by systematically exploring nonlinear interactions of A0 Lamb mode signals with delamination defects of various sizes and interlaminar locations, to facilitate the characterization of delaminations. The interrogation signal, in this regard, is a modulated sinusoid whose frequency varies in steps of 20 kHz between 40 kHz and 100 kHz. Commercial FEM software is used for modelling the contact at delamination interfaces and for simulating the Lamb wave propagation through the waveguide with delamination defect. It is demonstrated that the intermittently acting contact pressure between the two surfaces of delamination acts as a source of nonlinearity, resulting in generation of higher order harmonics of interrogation frequency. A metric for measuring nonlinearity, the nonlinearity index (NI), is used to quantify the strength of wave-damage interactions over a range of interrogation frequencies. The NI index is observed to vary with both the interlaminar location as well as the width of the delamination. The maximum value of NI is further influenced by the frequency of excitation signal. To infer the effect of delamination parameters on the NI, a concept of a concept of contact energy intensity is introduced, which is largely dependent on the size and the interlaminar position of the delamination. The nonlinearity index patterns are explained by combining the intensity of the contact energy with the phase difference between waves traveling through the sub-laminations and the flexural rigidity of the two sub-laminates at the delamination location. The inferences provided can potentially be used for determining the interlaminar location and width of delamination employing higher harmonic Lamb wave signals generated by the breathing delamination.

Forming effects on high-cycle fatigue in an aluminum sheet structure using the Ottosen-Stenström-Ristinmaa model

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:04:13 +0100

In this paper a multi-stage numerical analysis is presented with the aim to investigate effects of forming on the high-cycle fatigue performance of a deep-drawn aluminum sheet structure for use in a floating photovoltaic system. Forming simulations of a subsection of the full geometry are performed in a realistic two-step drawing-springback cycle. A simplified global analysis of service load response is performed to obtain displacements at the submodel boundary, that are used to generate boundary conditions for a local service load analysis. The local analysis is then performed on three different models of the subsection: (I) excluding forming effects, (II) including effects of thinning, and (III) including effects of thinning and residual stresses. The critical location with respect to the fatigue limit criterion in the Ottosen-Stenström-Ristinmaa high-cycle fatigue model was identified for case (I), and this location was used to compare the different models to assess effects of forming on high-cycle fatigue performance. Furthermore, the dynamic friction coefficient , and the isotropickinematic mixing coefficient were varied in order to investigate their respective effects.

Using artificial intelligence techniques for the accurate estimation of the ultimate pure bending of steel circular tubes

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:03:56 +0100

In this paper, the potential of building more accurate and robust models for the prediction of the ultimate pure bending capacity of steel circular tubes using artificial intelligence techniques is investigated. Therefore, a database consisting of 104 tests for fabricated and cold-formed steel circular tubes are collected from the open literature and used to train and validate the proposed data-driven approaches which include the Random Forest methodology in two variants: the original version in which the control parameters are manually updated, and an enhanced RF-PSO variant, where Particle Swarm Optimization is used for optimizing these parameters. The data set has four input parameters, namely the tube thickness, tube diameter, yield strength of steel and steel elasticity modulus, while the ultimate pure bending capacity is considered as the target output variable. The obtained results are compared to the real test values through various statistical indicators such as the root mean square error and the coefficient of determination. The results indicate that the proposed enhanced model can provide an accurate solution for modelling the complex behavior of steel circular tubes under pure bending conditions.

Multi-physical modelling and analysis of lubricated transmissions using a coupled finite element approach

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:03:36 +0100

Lubrication is vital to improve performance, efficiency and durability in transmissions; it serves to minimize wear, noise, vibration and friction. The proper functioning of lubricated transmissions relies on interactions amongst a wide range of physical phenomena (contact dynamics, fluid-structure interaction and heat transfer) operating at different spatial and temporal scales. A lubricated transmission model is proposed in this work to obtain accurate information regarding all physical domains and the coupling thereof to quantify performance, efficiency and durability. The model consists of a thermo-elastically coupled flexible multibody model for the gear pair and a Thermo-Elasto-Hydrodynamic Lubrication (TEHL) model for the lubricant, both based on first principle modelling to ensure high fidelity.

Advanced deep learning comparisons for non-invasive tunnel lining assessment from ground penetrating radar profiles

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:03:07 +0100

Innovative, automated, and non-invasive techniques have been developed by scientific community to indirectly assess structural conditions and support the decision-making process for a worthwhile maintenance schedule. Nowadays, machine learning tools are in the spotlight because of their outstanding capabilities to deal with data coming from even heterogeneous sources and their ability to extract information from the structural systems, providing highly effective, reliable, and efficient damage classification tools. In the current study, a supervised multi-level damage classification strategy has been developed regarding Ground Penetrating Radar (GPR) profiles for the assessment of tunnel lining conditions. In previous research, the authors firstly considered a convolutional neural network (CNN), adopting the quite popular ResNet-50, initialized through transfer learning. In the present work, further enhancements have been attempted by adopting two configurations of the newest state-of-art advanced neural architectures: the neural transformers. The foremost is the original Vision Transformer (ViT), whose core is an encoder entirely based on the innovative self-attention mechanism and does not rely on convolution at all. The second is an improvement of ViT which merges convolution and self-attention, the Compact Convolution Transformer (CCT). In conclusion, a critical discussion of the different pros and cons of adopting the above-mentioned different architectures is finally provided, highlighting the actual powerfulness of these technologies in the future civil engineering paradigm nevertheless.

Thermal and structural modelling of thermoset composite repairs towards optimization of the cure cycle for minimum distortion

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:02:45 +0100

During manufacturing of composite materials residual stresses can result in distortion of the final part. This distortion is even more critical when building on existing parts, such as for a repair, as the added material has to conform to the original structure. To predict this distortion due to curing of thermoset carbon-matrix composite repairs, a numerical modelling method is employed. The temperature cycle applied for the cure of thermoset composites can significantly influence the amount of residual stress and resulting deformation after manufacturing. Therefore, a method is devised to parametrise and subsequently tune this temperature cycle for minimum distortion after manufacturing. Numerical tests with the optimised temperature cycle resulted in a 36% reduction in process induced strain for a repair of a flat laminate plate. The same methodology is applied to a wing box consisting of two composite skins connected by two C-spars where a scarf repair is applied in the skin. The repair patch is locally heated by a heating blanket to cure the repair patch. A subsequent thermalmechanical model is used to investigate the amount of residual stress and strain after cure and the influence of underlying structural elements on the repair. The developed framework can support the patch fabrication with accurate design and analysis for repairs with minimum distortion. Which in turn will result in development of cost-effective composite repairs.

A machine learning based approach to predict the stress intensity factors in 2D linear elastic fracture mechanics

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:02:32 +0100

Within the framework of linear elastic fracture mechanics, the stress intensity factors (SIFs) are the mostly applied crack-tip characterizing parameters. To obtain the SIFs, approximate formulae are widely used because exact analytical solutions are available only for very simple geometrical and loading configurations [1]. However, even approximate solutions for SIFs are also rather limited to very simple geometrical and loading conditions. In this work, an accurate and efficient SIF prediction model based on Physics-informed neural network (PINN) [4] is developed, where we incorporate the equilibrium equations and constitutive relations into the PINN. In order to capture the singular behavior of the stress and displacement fields around the crack tip, we extend the standard PINN structure by adding two more trainable parameters

Dynamic characterization of offshore wind turbines supported on a jacket using Artificial Neural Networks

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:02:13 +0100

The dynamic characterization of an offshore wind turbine (OWT) and its foundation is an important task within the design stage of the support structure. The system fundamental frequency should not coincide with that of the loads that affect it, otherwise resonance phenomena can conclude with the collapse of the structure or its deterioration due to fatigue. Assuming a linear behaviour, the system fundamental frequency can be computed by solving the eingenvalue problem after defining the stiffness and mass global matrices. This procedure can become computationally expensive if soil-structure interaction (SSI) phenomena is taken into account. For this reason, a surrogate model based on Artificial Neural Networks (ANN) is proposed for estimating the fundamental frequency of the wind turbine assembly, jacket support structure and pile foundation considering SSI effects. A dataset is generated to train the ANN. This synthetic data collects the characteristics of the OWT-jacket-foundation and its fundamental frequency, which is obtained by a finite element substructuring model. The SSI is reproduced through impedance functions computed through a previously developed continuum model. Comparing the predictions of the ANN with the results obtained by the structural model, it is observed that this type of regression allows to reproduce in a sufficiently precise way the dependence of the fundamental frequency with respect to the variables that define the system. Thus the use of Machine Learning techniques, such as ANNs, makes it possible to take into account the system behaviour obtained by rigorous models in large-scale calculations that it would be unfeasible otherwise.

Postbuckling failure mechanism of square aluminum plates under shear loading

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:01:55 +0100

Buckling is very important for structural design, especially when the structure is thin-walled. Slender plates are widely used as structural members in civil, naval and aerospace engineering and they are able to carry considerable additional loads in the postbuckling range. Engineers take advantage of this postbuckling reserve and design structures that are allowed to buckle and operate below their ultimate loads for further weight and cost reduction. Consequently, both buckling and postbuckling behavior of slender plates are of critical importance during the design of lightweight thin-walled engineering structures.

New predictive models for ballistic limit of spacecraft honeycomb-core sandwich panels subjected to hypervelocity impact

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 10:01:39 +0100

Parameters of the honeycomb core (such as cell size and foil thickness), as well as the material of the core, influence the ballistic performance of honeycomb-core sandwich panels in cases of hypervelocity impact (HVI) by orbital debris. Two predictive models capable of accounting for this influence have been developed in this study: one utilized a conventional approach based on a dedicated ballistic limit equation, while the other employed an artificial neural network trained to predict the outcomes of HVI on HCSP. BLE fitting and ANN training were conducted using a database composed of 46 numerical experiments, performed with a validated numerical model and ten physical tests derived from the literature. The new ballistic limit equation is based on the Whipple shield BLE, in which the standoff distance between the facesheets was replaced by a function of the honeycomb cell size, foil thickness, and yield strength of the HC material. The corresponding fit factors were determined by minimizing the sum of squared errors between the BLE predictions and the results of HVI tests listed in the database. The BLE was then tested against a new set of simulation data and demonstrated an excellent predictive accuracy, with the discrepancy ranging from 1.13% to 5.58% only. The artificial neural network was developed using MATLAB's Deep Learning Toolbox framework and was trained utilizing the same HCSP HVI database as was employed for the BLE fitting. The ANN demonstrated a very good predictive accuracy, when tested against a set of simulation data not previously used in the training of the network, with the discrepancy ranging from 0.67% to 7.27%. Both of the developed predictive models (the BLE and the ANN) are recommended for use in the design of orbital debris shielding for spacecraft, involving honeycomb-core sandwich panels.

Distinct element modelling of the seismic response of historical masonry constructions: insight on the out-of-plane collapse of façades

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:51:45 +0100

Façades belonging to historical masonry constructions typically fail by out-of-plane mechanisms. The estimate of their out-of-plane capacity is not a trivial task, due to the different possible collapse modes (overturning, bending, disaggregation, leaf separation, sliding) and to the discontinuous nature of masonry, influencing the non-linear seismic behaviour of walls. Simplified approaches, proposed by building codes, mainly based on the mechanics of the rigid block, may not always be suitable for the purpose. Indeed, they disregard the real morphology of masonry, which instead influences weaker failure mechanisms (such as disaggregation and leaf separation). Furthermore, they neglect the interaction of the façade with the rest of the building and its interlocking with transversal walls. These shortcomings can be overcome resorting to distinct element method (DEM), in which masonry is modelled as an aggregation of discrete units and no-thickness interfaces and the actual morphology of constructions is considered. In this paper, DEM is adopted to investigate the out-of-plane seismic behaviour of façades through non-linear analyses, by focusing on vertical bending and overturning failure mechanisms. The former is studied by comparing results of shake table tests on both single-leaf and double-leaf masonry walls to dynamic simulations in which real accelerograms are applied. The latter is analysed by performing non-linear static analyses on the Romanesque church of St. Maria Maggiore in Tuscania, Italy, by focusing on its façade. Distinct element method provided a realistic description of the behaviour of façades under earthquake loadings, in terms of both seismic capacity, crack pattern and failure mode.

Limit analysis of non-periodic masonry by means of Discontinuity Layout Optimization

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:51:22 +0100

Masonry structures forming part of our historical heritage were often constructed using nonperiodic textures. In this case, unlike the situation for masonry with periodic textures, few methods are available to estimate wall strength and, moreover, available methods are often difficult to apply. In this work, Discontinuity Layout Optimization (DLO) is proposed as a method of estimating the failure load and associated mechanism of masonry walls constructed with non-periodic textures. In the first part three different textures are considered (periodic, quasi-periodic and chaotic) with a simplified scheme and a parametric analysis is undertaken, considering the variation of the height of the panel. A further classification for quasi-periodic textures is then provided and a DLO rigid block analysis is carried for square panels to show the influence of such textures. The results highlight the importance of the parameters considered in the analysis, and that DLO is a suitable method to investigate their influence.

Nonlinear macroelement based on Bouc-Wen formulation with degradation for the equivalent frame modelling of masonry walls

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:51:03 +0100

The equivalent frame model takes into account the shear and bending mechanisms that take place in piers and spandrels through plastic hinges. It represents a good compromise between accuracy and computational burden in the analysis of complex masonry walls. For the purposes of dynamic analysis, in addition to the hysteretic behaviour of the plastic hinges, it is also necessary to introduce their degradation of strength and stiffness. This study presents a macroelement model for piers and spandrels in which the bending mechanism is described by two hinges at the ends of the macroelement, and the shear mechanism by a shear link. They are characterized by a hysteretic behaviour with progressive plasticity, described by the Bouc-Wen model, and by degradation of strength and stiffness. Degradation is described through a damage parameter, which governs both strength and stiffness decay, and a flexibility increase parameter, which only governs stiffness reduction. In this way it is possible to independently control both strength and stiffness degradation. The model is applied to simulate experimental tests on panels, highlighting a good agreement with the experimental results.

Mesh adaptation of ablating hypersonic vehicles

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:50:46 +0100

The ablation of a vehicle during atmospheric reentry leads to a degradation of its surface state. Ablated wall interacts with the boundary layer that develops around the object. The deformation can be seen as a ripple or a roughness pattern with different characteristic amplitudes and wavelengths. The effect on the flow is taken into account either by means of modelizations or by direct simulation by applying the deformation to the mesh. Mesh regularization techniques can be used in order to take into account wall deformations during a simulation. In this work we apply our regularization directly to a mesh which has been already deformed. The meshes will be adapted for use in a parallel CFD Navier-Stokes code. A refinement of the mesh close to the wall is required to correctly capture the boundary layer, but also to accuratly represent the geometry of the wall deformation. For the numerical methods used, a constraint of orthogonality is added to the mesh impining on the wall.

Rocking Analysis for the bell tower of Sant’anna in Cervino

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:50:33 +0100

In seismic prone areas ecclesiastical masonry complexes have shown a very high vulnerability, as detected after the last Italian earthquakes, such as those occurred in L'Aquila (2009), Emilia-Romagna (2012), Central Italy (2016), and Ischia (2017). These are particular types of aggregate buildings subjected often to partial collapses, due to the presence of highly vulnerable elements, like the bell towers. Preliminary analyses should including straightforward and quick methods are necessary. In this paper the bell tower vulnerability is analyzed taking into account the rocking behaviour of the tower only and considering the contribute of the entire ecclesiastical complex as a rigid body sliding with a fixed friction coefficient with respect to the foundations. It is shown that suitable values of maximum oscillations and horizontal displacements are obtained. The case study is the ecclesiastical complex of S. Anna in Cervino (Caserta, Italy).

Data-led Mechanical and Thermal Analysis of Layered Structures Based on Parametric Finite Element Analysis and Neural Network

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:50:18 +0100

The mechanical and thermal behaviours of layered structures is of great importance for many advanced material systems and loading conditions. The responses of layered structures are controlled by the constitutive properties of each layer as well as the thicknesses. A comprehensive data-based approach is essential for both material analysis and design in direct or inverse problems. In this work parametric numerical modelling and Artificial Neural Network (ANN) are jointly used to develop data for layered structures. Mechanical and thermal finite element (FE) models are used to produce data for different material property and thickness domains. The use of ANN program is established and evaluated for different loading conditions. Using indentation as a typical case for mechanical loading and localized heating as typical example for thermal loading, ANN program was used to predict the behaviour of layered structures with different properties and layer thicknesses. Use of the data system in establishing dominating factors, synergetic effect on mechanical-thermal performance in advanced materials design is discussed.

Explorative In-situ Analysis of Turbulent Flow Data Based on a Data-Driven Approach

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:50:03 +0100

The Proper Orthogonal Decomposition (POD) has been used for several years in the post-processing of highly-resolved Computational Fluid Dynamics (CFD) simulations. While the POD can provide valuable insights into the spatial-temporal behaviour of single transient flows, it can be challenging to evaluate and compare results when applied to multiple simulations. Therefore, we propose a workflow based on data-driven techniques, namely dimensionality reduction and clustering to extract knowledge from large simulation bundles from transient CFD simulations. We apply this workflow to investigate the flow around two cylinders that contain complex modal structures in the wake region. A special emphasis lies on the formulation of in-situ algorithms to compute the data-driven representations during run-time of the simulation. This can reduce the amount of data inand output and enables a simulation monitoring to reduce computational efforts. Finally, a classifier is trained to predict characteristic physical behaviour in the flow only based on the input parameters.

Fluid-Structure Interaction Analyses of Amniotic Fluid with a Comprehensive Fetus Model Exposed to External Loading

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:49:43 +0100

A history of trauma during gestation is a risk factor for poor pregnancy outcomes. A multidisciplinary approach is vital to protect the mother's and the fetus' safety. Even though pregnancy-related trauma is uncommon, it is one of the leading causes of morbidity and mortality in pregnant women and fetuses. Hence, it is axiomatic to study the mechanism of the traumatic injuries to the fetus. The development of next-generation protective devices depends on our understanding of these mechanisms. Computational fluid-structure interaction simulations are used to study the effect of external loading on the fetus submerged in the amniotic fluid inside the uterus. A multitude of resulting variables is utilized to understand the cushioning function of the amniotic fluid on the fetus.

Single-edge notched tension testing for assessing hydrogen embrittlement: a numerical study of test parameter influences

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:49:19 +0100

To evaluate the feasibility of the safe use of existing gas grids for the transport and storage of hydrogen gas, the phenomenon of hydrogen assisted degradation of steel used in the pipeline grid has to be examined. A finite element based framework developed for describing this phenomenon at the continuum scale is used to assist in the design and analysis of experimental characterisation of the tearing resistance. The framework is based on the complete Gurson model for ductile damage and takes into account damage acceleration due to the local hydrogen concentration, and the diffusion of hydrogen. Simulations representing single edge notched tension (SENT) fracture toughness tests of an API 5L X70 grade steel are performed and results are discussed in terms of crack growth resistance curves. Side grooves are included in the geometry of the SENT model to promote uniform crack growth. Different boundary conditions are employed, simulating ex-situ and in-situ hydrogen charging of specimens. Moreover, the effect of the applied deformation rate on the dynamics of hydrogen diffusion and the resulting toughness values is investigated. Accordingly, guidance regarding experimental SENT testing for the hydrogen assisted tearing resistance degradation is provided, in terms of test conditions (in-situ/ex-situ) and deformation rate.

Design of integrated fluidic actuators for muti-axial loaded structural elements

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:48:53 +0100

The construction sector is responsible for high grey energy consumption and high greenhouse gas emissions. Adaptive structures can be a suitable solution to counteract this. Actuation of a beam to reduce the mass by counteracting the deflection with integrated fluidic actuators has been proven in previous studies. New challenges are brought about with the actuation of slabs due to the multi-axial load transfer. Many actuator principles are conceivable for this application. A combination of uniaxially acting actuators and complex designs that generate forces in different spatial directions in a targeted manner are possible. This paper presents various principles for the development of actuators integrated into the cross-section of a slab. These are able to manipulate the multi-axial load transfer behaviour directly. For this purpose, the actuator principles are classified according to various aspects. In a second step, numerical investigations are used to prove the effectiveness of the actuator principles.

ARCHITECTURAL AND ENVIRONMENTAL IMPACT OF RETROFITTING TECHNIQUES TO PREVENT IN-PLANE ≪DOMINO≫ FAILURE MODES OF UNREINFORCED MASONRY BUILDINGS

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:48:30 +0100

The preservation of heritage buildings is not just about the structural safety, but it is necessarily related to the central themes of restoration, fruition and reuse of ancient buildings. Such topic requires an interdisciplinary design approach that involves, among the others, structural engineering, numerical modelling and architecture to address the challenges of contemporaneity in heritage management also in terms of interests of the stakeholders. In this regard, the opportunities offered by natural F.R.C.M. (Fibre Reinforced Cementitious Matrix) composites, made of basaltic fibres and lime mortar, are analysed.

Effects of uncertainties of image-based material properties of great vessels on vascular deformation

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:48:07 +0100

Patient-specific computational models represent a powerful tool for the planning of cardiovascular interventions. In this context, the patient-specific material properties are considered as one of the biggest source of uncertainty. In this work, we investigated the effect of the uncertainty of the elastic module (E), as computed from a recent image-based methodology, on a fluid-structure interaction (FSI) model of a patientspecific aorta. The Uncertainty Quantification (UQ) was carried out using the generalized Polynomial Chaos (gPC) method. Four deterministic simulations were run based on the four quadrature points, computed considering a deviation of ±20% on the estimation of the E value of the vessel wall from patient's imaging. The UQ of the E parameter was evaluated on the area and flow variations among cardiac cycle extracted from five cross-sections of the aortic FSI model. Results from gPC analysis showed a not significant variation of the area and flow quantities during the whole cardiac period, thus demonstrating the effectiveness of the used image-based methodology in the inferring of the E parameter, despite its intrinsic errors due to model definition. This study highlights the importance of imaging to retrieve useful data in an indirect and noninvasive way, to enhance the reliability of in-silico models in the clinical practice.

Quantification of time-averaging uncertainties in turbulence simulations

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:47:45 +0100

An automatic method is proposed for the removal of the initialization bias that is intrinsic to the output of any statistically stationary simulation. The general techniques based on optimization approaches such as Beyhaghi et al. [1] following the Marginal Standard Error Rules (MSER) method of White et al. [16] were observed to be highly sensitive to the fluctuations in a time series and resulted in frequent overprediction of the length of the initial truncation. As fluctuations are an innate part of turbulence data, these techniques performed poorly on turbulence quantities, meaning that the local minima was often wrongly interpreted as the minimum variance in the time series and resulted in different transient point predictions for any increments to the sample size. This limitation was overcome by considering the finite difference of the slope of the variance computed in the optimization algorithm. The start of the zero slope region was considered as the initial transient truncation point. This modification to the standard approach eliminated the sensitivity of the scheme, and led to consistent estimates of the transient truncation point, provided that the finite difference time interval was chosen large enough to cover the fluctuations in the time series. Therefore, the step size for the finite difference slope was computed using both visual inspection of the time series and trial and error. We propose the Augmented DickeyFuller test as an automatic and reliable method to determine the truncation point, from which the time series is considered stationary and without an initialization bias.

Classification of compromised DOFS data with LSTM neural networks

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:47:28 +0100

Distributed optical fiber sensors (DOFS) are gaining momentum for in-situ condition monitoring and damage detection purposes. Although DOFS are a versatile sensing method enabling high-resolution strain and temperature mapping, they are also sensitive to mechanical vibrations. Vibrations are typically created by the ambient environment (e.g acoustic background, rotating equipment) which can produce high levels of measurement noise. With physical access to DOFS installations, the principle of acoustic or mechanical vibrations can also be utilized for malicious sensor tampering. The current lack of anomaly-detection systems suggests that practical DOFS applications would benefit from an automated analysis to detect and classify compromised measurements. Noise classification makes it possible to identify its source and potentially remove its effects from the measurement in the future. This would expand the commercial applications of DOFS systems significantly. Neural networks have been used for error detection in cyber-physical applications in numerous studies with high-accuracy results. Specifically, long short-term memory (LSTM) neural network models have become popular in recent years to classify anomalies in sequential e.g time-series data. Our investigation conducted a series of physical experiments using magnitude-controlled mechanical disturbances on bare free-hanging DOFS. Both random low-frequency vibrations at large displacement amplitudes and a constant high-frequency acoustic source at a low amplitude were employed. Experiments revealed that strain patterns are visually different with varying types and levels of disturbances. For the numerical analysis, statistics and machine learningbased approaches were applied for DOFS vibration noise classification, and their accuracy is discussed in detail. Results from the post-processing of compromised DOFS data suggest that it is possible to develop a vibration detection or classification system based on off-the-shelf DOFS interrogation equipment coupled with LSTM numerical tools.

Multiscale finite element modeling linking shell elements to 3D continuum

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:47:10 +0100

The present paper investigates the response of masonry structural elements with periodic texture adopting an advanced multiscale finite element model, coupling different formulations at the two selected scales of analysis. At the macroscopic structural level, a homogeneous thick shell is considered and its constitutive response is derived by the detailed analysis of the masonry repetitive Unit Cell (UC), analyzed at the microlevel in the framework of the threedimensional (3D) Cauchy continuum. The UC is formed by the assembly of elastic bricks and nonlinear mortar joints, modeled as zero-thickness interfaces. The Transformation Field Analysis procedure is invoked to address the nonlinear homogenization problem of the regular masonry. The performance of the model in reproducing various masonry textures is explored by referring to an experimentally tested pointed vault under different profiles of prescribed differential settlements. The structural behavior of the vault is studied in terms of global load-displacement curves and damaging patterns and the numerical results are compared with those recovered by detailed micromechanical analyses and experimental evidences.

Validation of the temperature history during extrusion based additive manufacturing

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:46:52 +0100

Additive manufacturing (AM) is considered as a key technology for the efficient production of individualized components. The technique enables the tool-less production of complex geometries and designs that could not be realized cost-effectively with conventional manufacturing methods. The focus of this work is on the Fused Filament Fabrication (FFF), where a thermoplastic filament is extruded trough a nozzle. The material is deposited layer by layer until the final part is build. Thereby, high temperature gradients occur within the part when the hot material is deposited on the lower layers. During the printing process the lower layers are reheated several times so that the material properties are influenced even after the deposition has been made. The thermal history has major effects on crucial material properties such as the degree of crystallization or thermal and mechanical properties. An inadequate degree of crystallization influences both the structural properties such as the stiffness or the degree of bonding and the dimensional accuracy due to subsequent shrinkage effects. Additionally, the temperature gradients cause residual stresses which are partly relaxed to varying part deformations. The remaining stresses can lead to premature failures. To achieve a high and repeatable part quality as well as a low scatter in the final part dimension an in-depth process understanding is required considering the underlying material-process-partinteractions. In order to analyse these complex multiphysical processes, manufacturing process simulations are a suitable method. A main requirement for the numerical analysis of AM processes is the calculation of the thermal history as accurately as possible. The objective of this work is, therefore, to evaluate the prediction accuracy of currently available AM process simulation tools. For this purpose, a gcode-based AM process simulation of a cuboid is performed in order to calculate the transient temperature fields using the Abaqus AM plug-in from Dassault Syst`emes. The cuboid made of PETG is printed with a Prusa i3 MK3.

Voxel-based density registration of trabecular bone: a longitudinal HR-pQCT study of postmenopausal women

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:46:33 +0100

Bone mineral density (BMD) is one of the important parameters used to characterise bone quality. Clinically, the only recommended method - dual X-ray absorptiometry - can only evaluate a two-dimensional areal BMD. Currently, three-dimensional localised BMD information is absent. HR-pQCT enables the assessments of 3D microstructure down to trabecular bone. Therefore, in this study, a voxel-based density registration (VDR) method is proposed to analyse the longitudinal changes of trabecular-bone density distribution. The VDR techniques were evaluated based on a six-month longitudinal study of five postmenopausal women. The time effect on localised changes of trabecular-bone mineral density was visualized and variations between different anatomical regions were quantified for the first time. Different distributions between anatomical regions were found in bone mineral density of trabecular bone (vBMDtrab), with a change of vBMDtrab at medial region (-0.56%) significantly higher than anterior (-1.58%) (p = 0.032). This study indicates that localised density changes might be used as a prior indicator for the effect of aging or other interventions.

Tangential differential calculus for curved, linear Kirchhoff beams with systematic convergence studies

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:46:15 +0100

We propose a reformulation of linear Kirchhoff beams in two dimensions based on the tangential differential calculus (TDC). The rotation-free formulation of the Kirchhoff beam is classically based on curvilinear coordinates. However, for general applications in engineering and sciences that take place on curved geometries embedded in a higher-dimensional space, the tangential differential calculus enables a formulation independent of curvilinear coordinates and, hence, is suitable also for implicitly defined geometries. The geometry and differential operators are formulated in global Cartesian coordinates related to the embedding space.

Photoelasticity of YVO4 through first-principle calculation

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:46:01 +0100

The laser host materials undergo relatively small changes in their intrinsic properties due to various sources during an experiment. These sources are often related to temperature change and vibrations due to crystal mounting, which may cause stress-induced birefringence in laser host materials[1]. Birefringence is a phenomenon that causes optical anisotropy due to external load or residual stress. As a result, the final outcome of the experiments can be affected. One way to reduce probable noises is to predict the change in optical properties with respect to load. In the case of laser host materials, refractive index is one of the most prominent properties that undergoes change. The change in refractive index due to external load in the linear response regime is known as photoelasticity. Therefore, to predict the change pattern of refractive index in a crystal, one needs to know the elastic and photoelastic constants of the material.

Effect of graphite-particle morphology on thermomechanical performance of compacted graphite iron: Numerical modelling

Jesús Sánchez Pinedo — Wed, 23 Nov 2022 09:45:43 +0100

Compacted graphite iron (CGI) is used in numerous applications, e.g., in the automotive industry, in tools and pipes, thanks to its excellent thermomechanical properties. Despite its extensive industrial use, its fracture at the microscale was not thoroughly investigated. Interfacial debonding is the main mechanism of fracture of CGI at the microscale and is based on the deformational incompatibility between graphite and the surrounding matrix. To study this decohesion, a two-dimensional micromechanical model of elliptical inclusions embedded in a metallic matrix is generated. An elastoplastic response is assumed for both constituents, and cohesive finite elements are applied to the graphite-matrix interface to simulate decohesion. A parametric analysis of interfacial features such as thickness and stiffness is performed to identify the effect of these parameters on debonding. The obtained results provide insights into the thermomechanical behaviour of CGI at the microscale and enable more effective modelling of this engineering alloy.

An efficient strategy of parcel modeling for polydispersed multiphase turbulent flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:31:08 +0100

A three-dimensional particle-laden two-phase turbulent flow by employing the Eulerian-Lagrangian method using multiphase Particle-In-Cell model is implemented to analyze the effects of parcel modeling. In order to achieve an optimal trade-off between accuracy and computational cost, a hybrid approach is proposed. This approach is a combination of two typical models: the volume fixed model, in which each parcel has the same volume, and the number fixed model, in which each parcel has the same number of particles. This approach is studied for the particle-laden turbulent flow benchmark case of Boreé et al. [1], with a mass loading of 22%, by using large eddy simulation through a two-way coupling between continuous and polydispersed phases.

A numerical analysis of CO2 storage by adsorption using ZIF-8

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:30:43 +0100

In 21st century, the reduction of CO2 concentration in the atmosphere is one of the most challenges of the humanity, specifically in the engineering. To start a possibility solution proposal, this work consisted in an analysis of carbon dioxide storage, using adsorption by ZIF8, a material that belongs to a class called Zeolitic Imidazolate Frameworks, which have high porosity, high thermal resistance and chemical stability. The main contribution of this work is to verify which parameters are relevant in the CO2 storage capacity by adsorption. To archive this goal, the study was made through computational simulations using the open source FreeFem++ software, inputting a specified quantity of pure CO2, entering in an 1,82 liter tank filled by the adsorbent until its internal pressure reached 1,0 MPa. First, the isothermal curve was validated with the literature, and after adjusting the parameters of adsorption model, called Dubinin Astakov (D-A). The simulations were performed, varying CO2 inlet flow, the tank’s aspect ratio with the values of 1; 1,9; 3; 5 and 7, and the external wall’s heat transfer coefficient with values of 5, 700 and 1000 W/m²K. Each simulation generated at each step the tank’s average and maximum temperatures, internal pressure, and the carbon dioxide adsorption density. All the simulations started with a standard temperature of 300 K and pressure of 100 kPa. Temperature and adsorption density distributions were generated to analyze in which part of the tank the adsorption is higher. The results showed that the regions where the temperatures are higher, the adsorption is lower, and in the end of the simulation, the simulations with the lower average temperatures had the higher adsorption density. The highest values of adsorption density were obtained with higher surface areas under the influence of forced convection, rather than natural convection, and with lower CO2 inlet flow. The highest adsorption density reached was 15,67 %, in a simulation with 50% of the tank’s volume per minute as CO2 inlet flow rate, aspect ratio of 7,0; and 700 W/m²K heat transfer coefficient. The average temperature obtained in the end of this simulation was 326,20 K and it took 3644 seconds for the tank to achieve the internal pressure of 1,0 MPa.

A multigrid immersed boundary method for the CFD solver Horses3D

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:30:20 +0100

This work describes the implementation of the Immersed Boundary Method (IBM) in a high order discontinuous Galerkin framework for the CFD solver Horses3D [1]. High order schemes are very attractive due to their low numerical dissipation, their capability of providing high-accurate solutions and higher efficiency for a given level of accuracy with respect to low order schemes. However, the generation of high order meshes needed by these schemes is still a bottleneck since it requires a large amount of time. IBM tries to tackle the problem by preserving the high order beneficial properties while avoiding the generation of complex meshes.

On highly scalable 2-level-parallel unstructured CFD

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:29:53 +0100

Exascale HPC systems are just about to become available. Such enormous simulation capabilities from the hardware perspective, however, require software that can effectively make efficient use of this massively parallel hardware. For the domain-decomposition based algorithms generally used for CFD, it has become apparent that running one MPI process, i.e. one domain, per CPU core is no longer apt when there are hundreds of cores available per cluster node. There are just too many processes per node that need to communicate with other remote processes. Message aggregation is thus a key aspect of highly scalable parallel codes. A 2-level parallelization featuring a shared-memory level in addition to the MPI process level seems a promising solution. The CODA (CFD for ONERA, DLR, Airbus) software for high-fidelity compressible-flow simulations of industrial configurations implements such a 2-level domaindecomposition hybrid-parallel approach. The processing of unstructured meshes is particularly challenging with respect to load balancing and non-linear data access. For maximum parallel scalability, CODA's parallelization not only features overlapping communication with computation on the process level, but also a dedicated Single Program (on) Multiple Data (SPMD) programming model for the shared-memory level. Here, the design principles of this parallelization concept are outlined, followed by details concerning its implementation in the Flucs infrastructure (FLIS), which has become part of CODA. Moreover, results of scalability studies with CODA are presented, which impressively demonstrate the extreme scalability realized with this parallelization approach. The studies were performed on two distinct HPC clusters, one based on Intel's Xeon Scalable Processor, the other one based on AMD's EPYC.

EXPLICIT AND IMPLICIT LARGE EDDY SIMULATION FOR A NACA0012 USING A HIGH ORDER DISCONTINUOUS GALERKIN SOLVER

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:28:54 +0100

We perform Large Eddy Simulation on a 3D NACA0012 airfoil using a high order discontiuous Galerkin spectral element solver at moderate Reynolds numbers, Re = 1.0 · 105. The aim is to compare the results of classic explicit Sub Grid Scale models, e.g. the WALE and VREMAN models, with the ones get by using implicit LES, where no explicit SGS is used, but we use stabilising split-form energy-stable formulations, with two-point Pirozzoli and KennedyGruber fluxes. We compare general qualitative variables such as the Q-criteria as well as local quantitative variables, as boundary layer velocity profiles. We show that both methods achive similar predictions for the integrated global variables, but differences can be appreciated in the local velocity profiles.

Free response of a gravitational liquid sheet by means of three-dimensional Volume-of-Fluid simulations

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:27:56 +0100

The volume-of-fluid (VOF) method is employed to simulate the dynamics of gravitational liquid sheets (curtains) issuing into an initially quiescent gaseous environment.

A level-set model for two-phase flow with variable surface tension: Thermocapillary and surfactants

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:27:39 +0100

An unstructured conservative level-set method for two-phase flow with variable surface tension is introduced. Surface tension is a function of temperature or surfactant concentration on the interface. Consequently, the called Marangoni stresses induced by temperature gradients or surfactant concentration gradients on the interface lead to a coupling of momentum transport equation with thermal energy transport equation or interface surfactant transport equation. The finite-volume method discretizes transport equations on 3D collocated unstructured meshes. The unstructured conservative level-set method is employed for interface capturing, whereas the multiple marker approach avoids the numerical coalescence of fluid particles. The fractional-step projection method solves the pressure-velocity coupling. Unstructured flux-limiters are proposed to discretize the convective term of transport equations. A central difference scheme discretizes diffusive terms. Gradients are evaluated by the weighted least-squares method. Verifications and validations are reported.

Comparison of different entropy stabilization techniques for discontinuous Galerkin spectral element methods

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:27:21 +0100

We review and compare two techniques to get entropy stability for nodal Discontinuous Galerkin Spectral Element Methods (DG) in compressible flows. One technique is based on entropy split-forms, e.g., [8, 15, 5] and one is based on a direct algebraic correction [1]. We have implemented the Flux Differencing methodology for both, Legendre-Gauss-Lobatto (Lobatto) and Legendre-Gauss (Gauss) based spectral element basis functions. While the Lobatto operators belong to the class of diagonal norm summation-by-parts (SBP) operators, the Gauss operators belong to the generalized class of SBP operators, where it is not necessary that the boundary nodes are included. To reach entropy stability, respectively guaranteed entropy dissipation, a key ingredient is an entropy conserving numerical flux function. With this ingredient, only the volume integral term of the DG method has to be modified accordingly. We have also implemented an alternative technique, which is in general applicable for a wide range of discretizations. Abgrall [R. Abgrall, A general framework to construct schemes satisfying additional conservation relations. Application to entropy conservative and entropy dissipative schemes. Journal of Computational Physics, vol 372, 2018] introduced an algebraic correction term that retains conservation of the primary quantities and is furthermore constructed such, that an entropy (in-) equality can be shown. The second technique is at first sight a simpler alternative to the split-form based approach. Hence, questions regarding its advantages and disadvantages naturally come up.

A Machine Learning based Expert System for Optimizing CFD Solver Parameters

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:26:57 +0100

Computational Fluid Dynamics is a viable tool in the field of aerodynamics enabling to reduce time, effort and budget required for experimental testing. Although powerful and established for various years, it remains a complex tool calling for experienced users to ensure consistent high-quality results. This complexity primarily stems from the underlying model, namely the Navier-Stokes equations typically combined with a set of equations resolving the effects of turbulence. Additionally, to obtain accurate high-fidelity result appropriate meshes are required. As a consequence, a substantial number of parameters needs to be selected carefully and the quality of a result often highly depends on individual knowledge and experience of a user. Hence, a strong desire exists to reduce the number of input parameters without causing a loss of accuracy and efficiency. Such reduction of parameters might be viewed as a prerequisite to CFD as a tool in process chains for multidisciplinary applications where typically no user interaction is possible. In this article we propose a machine-learned Expert System for CFD to provide guidance for users in selecting optimal or at least near optimal parameter combinations. The proposed Expert System is divided into two macro steps, the surrogate model and a genetic algorithm to determine from the surrogate model the parameters. Numerical examples are presented to demonstrate the approach.

A new projection method for Navier-stokes equations by using Raviart-thomas finite element

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:26:32 +0100

Computational Fluid Dynamics codes usually adopt velocity-pressure splitting to reduce the computational effort in the solution of the Navier-Stokes equations. In standard projection methods, the finite element approximations show difficulties to find a solution with discrete free-divergence velocity field in all space points. In this work, a new velocity-pressure method for Navier-Stokes equations that projects the velocity field inside the discrete free-divergence velocity space is presented. This algorithm computes the velocity field on the discrete free-divergence space by using Raviart-Thomas finite elements. The projection is obtained by the minimization of the distance, over the discrete free-divergence space, between the auxiliary field and the desired Raviart-Thomas interpolation space. The Raviart-Thomas discretization is based on the quadrilateral and hexahedral finite element space and therefore the divergence mimetic computational approach is used to avoid the well-known degradation of the divergence term convergence. The auxiliary velocity field is obtained by solving the velocity-pressure split system used in the classical ChorinTemam algorithm. The pressure is recovered by the orthogonal space to the projection on the Raviart-Thomas interpolation space. The method is investigated with an explicit and semi-implicit treatment of the pressure terms. The issues on boundary conditions and the errors in the reproducibility of the tangential components are investigated. Several numerical examples are reported to support this new projection method.

Algorithmic Differentiation for an effcient CFD solver

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:25:57 +0100

We illustrate the benefits of Algorithmic Differentiation (AD) for the development of aerodynamic flow simulation software. In refining the architecture of the elsA CFD solver, developed jointly by ONERA and Safran, we consider AD as a key technology to cut development costs of some derivatives of interest, namely the tangent, adjoint, and Jacobian. We first recall the mathematical background of CFD applications which involve these derivatives. Then, we briefly present the software architecture of elsA (Cambier et al. [12]) and the design choices which give it its HPC capability while highlighting how these choices strongly constrain the applicability of AD. To meet our efficiency requirements, we select the Source-Transformation approach to AD through the Tapenade tool which is justified by a series of experiments and benchmarks. Finally, we present results on large scale configurations.

A runtime-based dynamic mesh partitioning approach

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:25:34 +0100

Large-scale parallel numerical simulations are fundamental for the understanding of a wide variety of aeronautical problems. Mesh decomposition is applied to make use of parallel hardware. In particular, when using a massively parallel architecture, not only the final quality of the mesh subdivision is relevant. Also the partitioning algorithm itself needs to be robust as well as efficient. A strategy for dynamic mesh partitioning based on runtime measurements is presented. We integrate the 'Geometric Mesh Partitioner' (GeMPa), which is a partitioning library based on Hilbert Space-Filling Curve (HSFC), in the FlowSimulator (FS) software. FS is a platform designed to run multi-disciplinary simulations on massively parallel cluster architectures. The algorithm performance is evaluated on an unstructured mesh representing the ONERA M6 wing. In particular, the load imbalance among processes is evaluated and compared with a well-known graph-based partitioning approach. Finally, we analyze how the number of processes influences the load imbalance.

Numerical simulation of multiphase flows with incompressible viscoelastic flows and elastic solids

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:25:17 +0100

A numerical model for the simulation of multiphase flows with free surfaces is presented. The model allows to incorporate in a unified manner several phases ranging from incompressible Newtonian flows, Oldroyd-B viscoelastic flows and neo-Hookean elastic solids deformations. We advocate a Eulerian modeling of the multiphase flows, relying on the volume fraction of liquid, describing multiple phases with those different rheologies.One advantage of the Eulerian approach is to allow for large deformations of elastic solids, and changes of topologies. The numerical framework relies on an operator splitting strategy and a two-grid method. The numerical model is validated with a numerical experiment based on the collision between two elastic bodies with free surfaces.

D2Q9 model of upwind lattice Boltzmann scheme for hyperbolic scalar conservation laws

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:25:02 +0100

D2Q9 model of upwind lattice Boltzmann scheme for hyperbolic scalar conservation laws.

A practical algorithm to build geometric models of cardiac muscle tissue

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:24:44 +0100

Cardiac muscle tissue has a unique, network-like structure. Three-dimensional models of this structure are needed for simulations of cardiac electrophysiology and mechanics. We developed an algorithm to produce such models artificially, using an implicit surface expressed on a tailored unstructured multi-domain mesh to define the cell membranes. The algorithm first creates a random network of cell centers, observing angle and distance criteria inferred from real tissue. The space around the network edges is assigned to the cellular domains based on the nearest half-edge. The network is then immersed in a regular tetrahedral mesh which is refined to fit the domain boundaries and to offer sufficient density around the cell membrane. The refinements are alternated with mesh improvement operations to maintain an acceptable mesh quality. On the refined mesh a level-set function is expressed that defines the cell membrane. The remeshing code Mmg3d is then used to discretize the level set while retaining the domains, and to improve the quality of the final mesh. A serial implementation of the algorithm was able to produce meshes of a few hundreds of cardiac cells in 15 minutes, but we are still facing difficulties in the remesher, likely resulting from the unusual complexity of these meshes. It was still possible, however, to correctly mesh a small network of cells that was designed to be replicated by successive mirroring. This allowed us to build models of upto 1 cm3of tissue (10 million cells and 370 billion tetrahedra) that now serve in performance tests of a large-scale simulation code.

Efficient implementation of a high-order compressible Navier-Stokes equations solver running on Graphics Processing Units

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:24:24 +0100

This paper presents the implementation of a compressible Navier-Stokes equations solver that runs on multiple GPUs.

FEATURE DETECTION ALGORITHMS AND MODAL DECOMPOSITION METHODS

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:24:05 +0100

Various modal decomposition techniques have been developed in the last decade [111]. We focus on data-driven approches, and since data flow volume is increasing day by day, it is important to study the performance of order reduction and feature detection algorithms. In this work we compare the performance and feature detection behaviour of energy and frequency based algorithms (Proper Orthogonal Decomposition [13] and Dynamic Mode Decomposition [46, 811]) on two data set testcases taken from fluid dynamics.

Lattice-Boltzmann simulations of traffic-related atmospheric pollutant dispersion in urban areas

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:23:44 +0100

The developing field of urban physics includes computational fluid dynamics (CFD) as a tool to model wind comfort, heat management and pollutant dispersion in cities. In particular, road traffic emissions significantly contribute to air pollution and should be considered in atmospheric dispersion simulations. To this end, the lattice-Boltzmann method (LBM) offers a promising alternative to traditional finite-volume CFD solvers in terms of computational cost and accuracy. At IFP Energies Nouvelles (IFPEN), a recent emission model relying on real-life driving data recorded with a mobile application was used to construct urban emission maps. However, it has not been coupled yet with a precise unsteady CFD solver, which could provide local unsteady and accurate information about local concentration fields. We propose to combine the LBM open-source code OpenLB with the emission model designed at IFPEN to simulate traffic-induced pollutant dispersion in an urban-like environment. The LBM code is used to solve the Navier-Stokes equations as well as the passive scalar transport with a double distribution function (DDF) approach. The solver is successfully validated on the well-known CODASC test case and a first evaluation of the impact of a representative urban setting on pollutant dispersion with non-uniform sources is proposed.

An Immersed Boundary Method for the CFD Solver Airbus-CODA

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:23:22 +0100

This work implements and analyses an Immersed Boundary Method based on Volume Pezalization for the flow simulator Airbus-CODA (CFD for ONERA, DLR, and AIRBUS). The Immersed Boundary Volume Penalization has unique advantages, e.g. easy to implement, straightforward formulation for moving geometries, and numerical errors can be controlled apriori [1, 2], showing the potential for aeronautical applications. Numerical experiments will assess the accuracy of the Immersed Boundary Volume Penalization in CODA.

Momentum-conserving ROMs for the incompressible Navier-Stokes equations

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:23:04 +0100

Projection-based model order reduction of an ordinary differential equation (ODE) results in a projected ODE. Based on this ODE, an existing reduced-order model (ROM) for finite volume discretizations satisfies the underlying conservation law over arbitrarily chosen subdomains. However, this ROM does not satisfy the projected ODE exactly but introduces an additional perturbation term. In this work, we propose a novel ROM with the same subdomain conservation properties which also satisfies the perturbed ODE exactly. We apply this ROM to the incompressible Navier-Stokes equations and show with regard to the mass equation how the novel ROM can be constructed to satisfy algebraic constraints. Furthermore, we show that the resulting mass-conserving ROM allows us to derive kinetic energy conservation and consequently nonlinear stability, which was not possible for the existing ROM due to the presence of the perturbation term.

Numerical simulation of the micro-extrusion process of printable biomaterials

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:12:35 +0100

This work aims to gain a better understanding of how the rheological properties of printable materials affect their processability, as well as the quality of the final product, which at the end can lead to reducing time and costs of the process and increase product development. As the first step, the proper rheological non-Newtonian models are extracted from experimental studies. Later, three-dimensional numerical simulation of extrusion process is performed in the context of Direct Numerical Simulation (DNS) of governing equations, where the whole physics of fluid motion is taken into account. A finite-volume fractional step approach is used to solve the Navier-Stocks equations on collocated arbitrary meshes. Geometrical volume-of-fluid (GVOF) interface capturing approach is used to resolve the topological changes of the moving interface. The governing equations are solved using High-Performance Computing (HPC) parallel approaches. Besides the contribution of this work to the advancement of numerical techniques applied to multiphase complex flows, obtained results will shed light on the nature of non-Newtonian extrusion process with vast applications in the 3D printer industrial sectors.

The X-Mesh method applied to Multiphase Flows

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:12:11 +0100

The accurate modeling of moving boundaries and interfaces is a difficulty present in many situations in computational mechanics. In this paper we use a new approach, X-Mesh, to simulate with the finite element method the interaction between two immiscible fluids while keeping an accurate description of the interface without mesh regeneration. The method is validated with complex problems such as Rayleigh-Taylor instabilities, sloshing and dambreak. The quality of the results and the efficiency of the method show the potential of this approach to simulate such physical phenomena.

DNS and LES on unstructured grids: playing with matrices to preserve symmetries using a minimal set of algebraic kernels

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:11:47 +0100

The essence of turbulence are the smallest scales of motion. They result from a subtle balance between two differential operators differing in symmetry: the convective operator is skew-symmetric, whereas the diffusive is symmetric and negative-definite. On the other hand, accuracy and stability need to be reconciled for numerical simulations of turbulent flows in complex configurations. With this in mind, a fully-conservative discretization method for collocated unstructured grids was proposed [Trias et al., J.Comp.Phys. 258, 246-267, 2014]: it preserves the symmetries of the differential operators and it has shown to be a very suitable approach for DNS and LES. On the other hand, an efficient cross-platform portability is nowadays one of the greatest challenges for CFD codes. In this regard, our leitmotiv reads: relying on a minimal set of (algebraic) kernels is crucial for code portability and maintenance! In this context, this work focuses on the computation of eigenbounds for the above-mentioned convection and diffusion matrices which are needed to determine the time-step `a la CFL. A new inexpensive method that allows this, without explicitly constructing these time-dependent matrices is proposed and tested. It only requires a sparse-matrix vector product where only the vector changes on time. Hence, apart from being significantly more efficient than the standard CFL condition, cross-platform portability is straightforward.

The interaction between an isolated roughness element and free-stream turbulence

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:11:19 +0100

Control and delay of the laminar-turbulent transition is a key parameter in reducing skin friction and drag. The flow characteristics, surface roughness, and environmental noise can affect the onset of transition. The present work investigates, numerically and experimentally, the interaction of the free-stream turbulence (FST) and an isolated cylindrical roughness element, and the resulting impact on the transition onset in a flat-plate boundary layer. High-fidelity direct numerical simulations (DNS) are performed for a roughness element immersed in the boundary layer over a flat plate with an asymmetrical leading edge, with and without FST. The numerical results are compared to hot-wire anemometry measurements performed in the Minimum Turbulence Level wind tunnel at KTH. The initial numerical and experimental results show that in the absence of FST, for the chosen flow parameters, highand low-speed streaks are generated downstream of the roughness element while the flow remains laminar and globally stable. When FST is added, the spanwise spacing of the streaky structures changes and the transition location of the boundary layer moves upstream. It was found that the aspect ratio of the streaky structures does not vary significantly.

Non-newtonian viscous elongation and shear fluid model based on optimal triple tensor decomposition

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:11:01 +0100

The modeling of the distinct non-Newtonian fluid properties is an essential prerequisite for the computational simulation of associated flow fields. In particular, some non-Newtonian fluids reveal strong diverse viscosity response behaviours to pure elongational and simple shearing flows. Therefore, it is necessary to be able to distinguish between these flow types even in complex flow configuration. Unfortunately flow types are naturally mixed and this distinction becomes quite difficult. Only in a Lagrangian framework the tracking of the Lagrangian fluid element deformation allows an accurate strain related deformation type assignment. However, most CFD approaches prefer the Eulerian framework accepting the loss of the natural flow path alignment of the moving fluid particles. Consequently shear and elongation rates are barely separable without particular assignment methods. In this work a tensor decomposition method from vortex dynamics is discussed which allows to distinguish between these flow types. In vortex dynamics the problem occurred to separate shearing from purely rotational flows because different hydro- and aerodynamic flow phenomena are caused by shear and vortex related flow types. Thereto, various methods were proposed, among others the optimal triple tensor decomposition method which is able to separate vortical from shearing flows but also, after some modification, elongational from shearing flows. This tensor decomposition is now used to calculate elongation and shearing rates as input variables into non-Newtonian fluid models for the calculation of the local elongational and shear viscosity. The application case is a cross slot channel flow often used as reference. In this numerical simulation study the impact of the elongation rate modeling on the contraction flow topology is shown and discussed. It is shown that the modeling of different viscous elongational and shear-thinning affects the resulting flow significantly

Neural network prediction of the flow field in a periodic domain with hyper-neural network parametrization

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:10:48 +0100

This paper is concerned with fast flow field prediction in a blade cascade for variable blade shapes as well as variable Reynolds number using the machine-learning architecture called convolutional neural network. To generate flow field for a specific Reynolds number, an encoder-decoder convolutional neural network, also called U-Net, is used. The values 500, 1000 and 1500 of the Reynolds number are chosen as the training set. Three U-Nets were trained on CFD results for 100 blade profiles, each U-Net for a different Reynolds number. In order to get a prediction for variable Reynolds number, a so-called hypernetwork in employed. The hypernetwork essentially interpolates between the two trained U-Nets. The architecture of the hypernetwork is fully-connected feedforward neural network with one input neuron corresponding to the Reynolds number, one hidden layer and the output layer corresponds to the weights for the interpolated U-Net. The concept of the hypernetwork-based parametrization is tested on a problem of compressible fluid flow through a blade cascade with three unseen blade profiles and unseen Reynolds number.

Symmetry-preserving discretisation methods for magnetohydrodynamics

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:10:24 +0100

In this work, the symmetry-preserving method [1, 2, 3] is extended to include magnetohydrodynamic effects, using the collocated grid arrangement of Ni et al. [4, 5]. The electromagnetic part is solved explicitly using the induction-less approximation and an electric potential Poisson equation. The proposed solver is implemented in OpenFOAM and tested for accuracy and stability, and compared to the method of Ni et al. [4, 5]. A new benchmark case using a Taylor-Green vortex in a transverse magnetic field is used, for which kinetic energy budget terms are compared to the analytical solutions. Finally, Hunt's case is used to compare flow profiles to the analytical solutions. Influence of the spatial discretisation on accuracy and stability is also examined by solving both cases on meshes with variable degrees of distortion. The symmetry-preserving method showed accuracy on Cartesian meshes and stability even on extremely distorted meshes, whereas the method of Ni et al. [4, 5] showed less accurate conservation of current density and was not able to produce stable solutions on the extremely distorted meshes.

Fluidization by gas pore pressure of dense granular flows: numerical simulations versus experiments

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:10:03 +0100

A model accounting for fluidisation by pore gas pressure in dense granular flows is presented. A viscoplastic rheology, based on the Drucker-Prager criterium, is used to describe the granular medium which is a mixture of air and glass beads. The pore gas pressure, which satisfies an advection-diffusion equation, reduces the friction between the particles and thus the value of the apparent viscosity. As a consequence, dense fluidised granular flows can travel longer distances. In laboratory experiments, the run-out distance reached by dense granular columns when collapsing is almost doubled when fluidisation is applied. This fundamental result, in the context of pyroclastic density currents, is reproduced by numerical simulations performed with the fluidised model.

Computational modelling and characterization of non-Newtonian visco-plastic cementitious building materials

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:09:42 +0100

Cementitious building materials like Ultra High Performance Concrete (UHPC), Self-Compacting Concrete (SCC) or concrete with low clinker content possess complex rheological properties. Due to high packing densities and the use of various additives and chemical admixtures, a huge range of non-Newtonian flow characteristics from shear-thinning to shear-thickening, visco-elastic material behaviour and structural build-up can appear. For these concretes, transient computational modelling using Computational Fluid Dynamics (CFD) requires a meaningful choice of rheological parameters and the associated boundary conditions. The authors present the rheological analysis of five cementitious pastes with low ( = 0.45) to high ( = 0.58) solid volume fraction . Rheological parameters from rheometric flow protocols are compared with empirical stoppage test results for short and steady (slump flow) and transient flow (L-Box) conditions. Following, numerical simulation with the measured rheological parameters as input parameters is compared to the experimental flow results. CFD analysis using OpenFOAM is performed for the flow in empirical stoppage tests. We found that with increasing non-Newtonian behaviour, deviations between real and simulated flow appear due to insufficient transient flow descriptions and unknown secondary effects. The results provide new insight into computational modelling of complex cementitious building materials and serve as basis for further advanced CFD based modelling and characterization of time-dependent non-Newtonian concrete flow.

Preparing a Fortran legacy code for the upcoming exascale architectures

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:09:25 +0100

Preparing legacy codes for the upcoming exascale systems is a timely topic since the unveiling of the Frontier system in June 2022. In this work we describe the steps taken to prepare the AVBP code for this new step in computing ressources. AVBP [6] is a parallel CFD code that solves the three-dimensional compressible Navier-Stokes equations on unstructured and hybrid grids. AVBP is a cutting-edge software when it comes to distributed memory CPUs, scaling efficiently up to 200.000's of cores on Bluegene or AMD Epyc2 systems. However, other types of architectures such as ARM processors and accelerators are gaining popularity and play a significant role in the exascale era. We first explore the usage of ARM processors, then GPU accelerators through OpenACC[2] directives. This work highlights the difficulties of porting a legacy code to those architectures and solutions implememented so far for performance.

On the algebraic modifications of traditional turbulence models to predict by-pass and separation induced transition

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:09:05 +0100

Many reliable and robust turbulence models are nowadays available for the ReynoldsAveraged Navier-Stokes (RANS) equations to accurately simulate a wide range of engineering flows. However, turbulence models are not able to correctly predict flow phenomena with low to moderate Reynolds numbers, which are characterized by strong transitions. Laminar to turbulent transition is common in aerospace, turbomachinery, maritime, and automotive. Therefore, numerical models able to accurately predict transitional flows are mandatory to overcome the limits of turbulence models for the efficient design of many industrial applications. A modified version of the k-~ and Spalart-Allmaras turbulence models is proposed in order to predict transition due to the bypass and separation-induced modes. The modifications here proposed are based on the kand the SA-BCM transition models. Both the models are correlation-based algebraic transition models that relies on local flow information and include an intermittency function instead of an intermittency equation. The basic idea behind the models is that, instead of writing a transport equation for intermittency, an intermittency function multiplies the production terms of the turbulent working variables of the formulation of the turbulence models. In particular, the turbulence production is damped until it satisfies some transition onset requirements. The proposed models are implemented in a high-order discontinuous Galerkin (dG) solver and validated on different transitional benchmark cases from the ERCOFTAC T3 suite, with bypass (T3A, T3Aand T3B) and separation-induced (T3L1 and T3L3) transition.

Fully integrated mesh generation in fluid-structure interaction

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:08:43 +0100

In fluid-structure interaction (FSI), the fluid and solid domains are permantently changing, coupled along a time-dependent, moving fluid-structure interface. The update of the fluid domain, i.e., in the numerical context, the mesh update is critical for robust and efficient simulations. Herein, we propose to inherently embed the mesh generation into the simulation.The FSI domain is defined based on structured building blocks that imply all the relevant information needed for the automatic mesh generation: Topology, geometry, and grading information. Transfinite maps play a crucial role for the definition of sub-meshes with any desired order and resolution in each building block. In every time step, a new mesh is generated, taking into account the deforming FSI interface. This generation is fast compared to the overall work load in each time step which is still dominated by the (iterative) solutions of the systems of equations. It is also very robust and removes any mesh entanglement by construction provided that suitable building blocks are selected once initially. Numerical results confirm the success of the proposed FSI strategy with integrated mesh generation.

Reynolds stress correction by machine learning methods with physical constraints

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:08:21 +0100

For the past three decade, Reynolds Average Navier-Stokes models have been widely used in the industry to simulate complex flows. However, these models suffer from limitations. Indeed there are still large discrepancies in the Reynolds stresses between the RANS model and high-fidelity data provided by DNS or experiments. This paper presents a strategy to correct the Menter SST model using an explicit algebraic model and two different neural networks: an multilayer perceptron (MLP) and a generative adversarial network (GAN). Moreover, in order to preserve the physical properties of the Reynolds stress tensor, we introduce a penalisation term in the loss of the GAN.

Comparison of uncertainty quantification methods for mathematical problems in intermediate dimensions

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:08:02 +0100

The efficiency of multidimensional quadrature methods is compared for seven test functions in intermediate dimensions. Following this goal, the numerical evaluations of the mean and variance of the test functions, for two probability density functions, are assessed with respect to (wrt) their known exact values. The retained dimensions (3 to 6) correspond to the number of operational and geometrical uncertain parameters we plan to consider in a near future for realistic sensitivity analysis or robust designs. Most of the numerical quadrature methods rely on a generalized Polynomial Chaos (gPC) defined either by quadrature or by collocation. Two of the gPC collocation techniques, Basis Poursuit Denoise (BPdn) and Least Angle Regression (LAR), search for a sparse gPC while satisfying the collocation equations. Finally, the efficiency of the quadrature methods is discussed in relation with the regularity, the input dimension and the ANOVA decomposition of the test functions.

Cell-centered Lagrangian scheme for multi-material flows with equal pressure assumption

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:07:43 +0100

The present document is motivated by the development and the study of diffuse interface strategies which does not require the use of geometric interface reconstructions. A simple diffuse interface strategy is proposed for the multimaterial diffusion equation. While it is possible to consider only one average temperature per mixed cell, it is known [7] that standard harmonic or arithmetic homogeneous methods are not accurate on the simple 'sandwich' problem when working with coarse meshes. This has direct consequences for radiation-hydrodynamics applications. The numerical strategy presented here may be seen as a natural extension of standard homogeneous model and understood as if the diffusion operator is integrated on the global cell (not the materials) taking into account several temperature (one per material). Obviously, the accuracy of the presented method, compared to exact geometric reconstruction based ones, is expected to be lower in the general case. However, we believe that the simplicity of the methodology introduced in the present document, its robustness and practicality for real physical applications makes it interesting for a large audience.

The effect of the tracer staggering on sea ice deformation fields

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:07:24 +0100

Sea ice models can simulate linear deformation characteristics (linear kinematic features) that are observed from satellite imagery. A recent study based on the viscous-plastic sea ice model highlights the role of the velocity placement on the simulation of linear kinematic features (LKFs) and concluded that the tracer staggering has a minor influence on the amount simulated LKFs. In this work we consider the same finite element discretization and show that on triangular meshes the placement of the sea ice tracers and the associated degrees of freedom (DoFs) have a strong influence on the amount of simulated LKFs. This behaivor can be explained by the change of the total number of DoFs associated with the tracer field. We analyze the effect on a benchmark problem and compare P1-P1, P0-P1, CR-P0 and CR-P1 finite element discretizations for the velocity and the tracers, respectively. The influence of the tracer placement is less strong on quadrilateral meshes as a change of the tracer staggering does not modify the total number of DoFs. Among the low order finite element approximations compared in this study, the CR-P0 finite element discretization resolves the deformation structure in the best way. The CR finite element for velocity in combination with the P0 discretization for tracer produces more LKFs than the P1-P1 finite element pair even on grids with fewer DoFs. This can not be achieved with the CR-P1 setup and therefore highlights the importance of the tracer discretization for the simulation of LKFs on triangular meshes.

Parameterising ocean-induced melt of an idealised Antarctic ice shelf using deep learning

Jesús Sánchez Pinedo — Tue, 22 Nov 2022 16:07:06 +0100

The largest uncertainty when projecting the Antarctic contribution to sea-level rise comes from the ocean-induced melt at the base of Antarctic ice shelves. Current parameterisations used to link the hydrographic properties in front of ice shelves to the melt at their base struggle to accurately simulate basal melt patterns. We suggest that deep learning can be used to tackle this issue. We train a deep feed-forward neural network to emulate basal melt rates simulated by highly-resolved ocean simulations in an idealised geometry. We explore the advantages and limitations of this new approach through sensitivity studies varying hyperparameters, input variables and training choices. We show that large neural networks perform better, that the input format of the temperature and salinity matters most, and that the neural network can be applied to conditions outside of its training range if trained appropriately. The results are promising and we make recommendations for further work with this approach.