Documents published in Scipedia

• Preparing a Fortran legacy code for the upcoming exascale architectures

  J. Legaux, G. Staffelbach

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  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 [...]

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

  A. Colombo, A. Crivellini, A. Ghidoni, A. Nigro, G. Noventa

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  Many reliable and robust turbulence models are nowadays available for the ReynoldsAveraged Navier-Stokes (RANS) equations to accurately simulate a wide range of engineering [...]

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• Fully integrated mesh generation in fluid-structure interaction

  T. Fries, D. Bošnjak, R. Schussnig

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  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 [...]

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• Reynolds stress correction by machine learning methods with physical constraints

  T. Philibert, A. Ferrero, A. Iollo, F. Larocca

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  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. [...]

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• Comparison of uncertainty quantification methods for mathematical problems in intermediate dimensions

  J. Peter, Q. Bennehard

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  The efficiency of multidimensional quadrature methods is compared for seven test functions in intermediate dimensions. Following this goal, the numerical evaluations of the [...]

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

  R. Chauvin, G. Sébastien, M. Bastien, L. Antoine

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  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 [...]

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• The effect of the tracer staggering on sea ice deformation fields

  C. Mehlmann

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  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 [...]

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

  B. Bouissou, C. Burgard, N. Jourdain

  eccomas2022.

  
  

  Abstract

  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.

  Abstract
  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 [...]

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• Data-Driven Reduced Order Modeling for Aerodynamic Flow Predictions

  D. Hines Chaves, P. Bekemeyer

  eccomas2022.

  
  

  Abstract

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

  Abstract
  During each aircraft program a vast amount of aerodynamics data has to be generated to judge performance, structural loads as well as handling qualities. Within the past years [...]

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• Transition of separated flow over a bump under unsteady inflow conditions

  H. Marbona, A. Martínez-Cava, D. Rodríguez, E. Valero

  eccomas2022.

  
  

  Abstract

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

  Abstract
  Laminar flow separation has detrimental effects on the aerodynamics and performance of low pressure turbines (LPT). Flow separation is caused by the presence of adverse pressure [...]

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