Documents published in Scipedia

• Material point method for large deformation seismic response analysis

  M. Kohler, A. Stöcklin, A. Puzrin

  eccomas2022.

  
  

  Abstract

  Landslides triggered by earthquakes are one of the major seismic hazards and can cause large damages and fatalities. The material point method (MPM) has become a popular technique to model such large mass movements. A limitation of existing MPM implementations is the lack of appropriate boundary conditions to perform seismic response analysis of slopes. To bridge this gap, an extension to the basic MPM framework is presented for simulating the seismic triggering and subsequent collapse of slopes within a single analysis step. The concepts of a compliant base boundary and free-field columns are applied within the MPM framework enabling the direct application of input ground motions and accounting for the absorption of outgoing waves.

  Abstract
  Landslides triggered by earthquakes are one of the major seismic hazards and can cause large damages and fatalities. The material point method (MPM) has become a popular technique [...]

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• Penalized direct-dorcing method and power-law-based wall model for immersed-boundary numerical simulations of obstacles in turbulent flow

  I. Hamadache, M. Belliard, P. Sagaut

  eccomas2022.

  
  

  Abstract

  In this paper, academic and industrial test cases have been conducted in order to validate the approach of using a Penalized Direct Forcing method coupled with an immersed turbulent wall model. Good results are obtained compared to a body fitted mesh with the Werner & Wengle wall model. In a shortcoming second step, we can project the coupling between the immersed wall law and a K-epsilon model, as well as obstacle shape optimization during the flow computation.

  Abstract
  In this paper, academic and industrial test cases have been conducted in order to validate the approach of using a Penalized Direct Forcing method coupled with an immersed [...]

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• A comparison between IBM with feedback forcing and a volume penalization method for compressible flows

  L. Ménez, E. Goncalves, P. Parnaudeau, D. Colombet

  eccomas2022.

  
  

  Abstract

  The aim of this work is to model compressible flows involving shock waves past a solid obstacle using a non-conformal mesh. An Immersed Boundary Method (IBM) with feedback forcing and a volume penalization method are considered and compared. Both methods are validated on various test-cases. Accuracy and computational cost are discussed.

  Abstract
  The aim of this work is to model compressible flows involving shock waves past a solid obstacle using a non-conformal mesh. An Immersed Boundary Method (IBM) with feedback [...]

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• Simulation of the flow-acoustic-structural interaction in flow ducts using a partitioned approach in the time domain

  J. Kersschot, H. Denayer, W. De Roeck, W. Desmet

  eccomas2022.

  
  

  Abstract

  Duct systems confining a subsonic air flow, such as ventilation ducts, often have a lightweight design. These lightweight constructions are easily excited by unsteady pressure fluctuations in the flow, causing structural vibrations and noise emissions. Designing effective solutions for this flow-acousticstructural problem requires a better understanding of the multi-physical interactions and efficient prediction tools. In this work, due to the confined configuration, the vibro-acoustic interaction is a strong two-way interaction and is modeled by coupling a flow-acoustic solver with a structural solver. The kinematic and dynamic continuity at the interface is ensured in this partitioned approach by a data exchange during runtime between the solvers. The data exchange is managed by the open-source coupling library preCICE [1]. The analysis of the flow-acoustic-structural interaction in a flexible flow duct with rectangular cross section was given in [2]. In this paper, the error resulting from the pressure mapping between both solvers is analyzed and an improved force mapping strategy is adopted.

  Abstract
  Duct systems confining a subsonic air flow, such as ventilation ducts, often have a lightweight design. These lightweight constructions are easily excited by unsteady pressure [...]

  • 28
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• Adaptive and flexible macro-micro coupling software

  I. Desai, B. Uekermann, C. Bringedal

  eccomas2022.

  
  

  Abstract

  Many multiscale simulation problems require a many-to-one coupling between different scales. For such coupled problems, researchers oftentimes focus on the coupling methodology, but largely ignore software engineering and high-performance computing aspects. This can lead to inefficient use of hardware resources, on the one hand, but also inefficient use of human resources as solutions to typical technical coupling problems are constantly reinvented. This work proposes a flexible and application-agnostic software framework to couple independent simulation codes in a many-to-one fashion. To this end, we introduce a prototype of a new lightweight software component called Micro Manager, which allows us to reuse the coupling library preCICE for two-scale coupled problems. We demonstrate the applicability of the framework by a two-scale coupled heat conduction problem.

  Abstract
  Many multiscale simulation problems require a many-to-one coupling between different scales. For such coupled problems, researchers oftentimes focus on the coupling methodology, [...]

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• Data-driven models for shrinkage porosity prediction in aluminium casting

  M. Nouri, J. Artozoul, A. Caillaud, A. Ammar, F. Chinesta, O. Köser

  eccomas2022.

  
  

  Abstract

  Casting is one of the most used processes to form metals like aluminium. A casting part can contain several defects that threaten its resistance. Shrinkage porosity is one of the major anomalies that designers try to avoid. For this purpose, rounds of numerical simulations should be performed with operating on a selection of parameters in order to minimize the presence of porosity in the casting part. In general, these approaches are time-cost with dependence on the complexity of the study case and the needed accuracy. In this paper, a methodology of data-driven porosity prediction for 3D parts is proposed in order to minimize the time-cost. A supervised learning algorithm is implemented to learn nodal porosity prediction using decision trees based method. A dataset is generated from a casting simulation software with operating on a selection of parameters. The training is realised on critical features vector extracted from nodal thermal history. Model order reduction method is used to interpolate thermal fields allover the parameter space. This interpolation is sufficiently accurate with minor errors. Promising results of shrinkage porosity prediction on a 3D study case are obtained. An evaluation of these results is performed with reference to the simulations results. This solution can contribute to open perspectives for more data-driven solutions that optimize the time-cost in the design stage.

  Abstract
  Casting is one of the most used processes to form metals like aluminium. A casting part can contain several defects that threaten its resistance. Shrinkage porosity is one [...]

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• Model order reduction of solidification problems

  F. Arbes, Ø. Jensen, K. Mardal, J. Dokken

  eccomas2022.

  
  

  Abstract

  Advection driven problems are known to be difficult to model with a reduced basis because of a slow decay of the Kolmogorov N -width. This paper investigates how this challenge transfers to the context of solidification problems and tries to answer when and to what extend reduced order models (ROMs) work for solidification problems. In solidification problems, the challenge is not the advection per se, but rather a moving solidification front. This paper studies reduced spaces for 1D step functions that move in time, which can either be seen as advection of a quantity or as a moving solidification front. Furthermore, the reduced space of a 2D solidification test case is compared with the reduced space of an alloy solidification featuring a mushy zone. The results show that not only the PDE itself, but the smoothness of the solution is crucial for the decay of the singular values and thus the quality of a reduced space representation.

  Abstract
  Advection driven problems are known to be difficult to model with a reduced basis because of a slow decay of the Kolmogorov N -width. This paper investigates how this challenge [...]

  • 50
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• Data-driven enhanced model reduction for bifurcating models in computational fluid dynamics

  M. Hess, A. Quaini, G. Rozza

  eccomas2022.

  
  

  Abstract

  We investigate various data-driven methods to enhance projection-based model reduction techniques with the aim of capturing bifurcating solutions. To show the effectiveness of the data-driven enhancements, we focus on the incompressible Navier-Stokes equations and different types of bifurcations. To recover solutions past a Hopf bifurcation, we propose an approach that combines proper orthogonal decomposition with Hankel dynamic mode decomposition. To approximate solutions close to a pitchfork bifurcation, we combine localized reduced models with artificial neural networks. Several numerical examples are shown to demonstrate the feasibility of the presented approaches.

  Abstract
  We investigate various data-driven methods to enhance projection-based model reduction techniques with the aim of capturing bifurcating solutions. To show the effectiveness [...]

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• Accelerated nonlinear PDE-constrained optimization by reduced order modelling

  B. Gibson, M. Yano

  eccomas2022.

  
  

  Abstract

  We present a framework to accelerate optimization of problems where the objective function is governed by a nonlinear partial differential equation (PDE) using projection-based reduced-order models (ROMs) and a trust-region (TR) method. To reduce the cost of objective function evaluations by several orders of magnitude, we replace the underlying full-order model (FOM) with a series of hyperreduced ROMs (HROMs) constructed on-the-fly. Each HROM is equipped with an online-efficient a posteriori error estimator, which is used to define a TR. Hyperreduction is performed following a goal-oriented empirical quadrature procedure, which guarantees first-order consistency of the HROM with the FOM at the TR center. This ensures the optimizer converges to a local minimum of the underlying FOM problem. We demonstrate the framework through optimization of a nonlinear thermal fin and pressure-matching inverse design of an airfoil under Euler flow and Reynolds-averaged Navier-Stokes flow.

  Abstract
  We present a framework to accelerate optimization of problems where the objective function is governed by a nonlinear partial differential equation (PDE) using projection-based [...]

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• On the matching of eigensolutions to parametric partial differential equations

  M. Alghamdi, F. Bertrand, D. Boffi, F. Bonizzoni, A. Halim, G. Priyadarshi

  eccomas2022.

  
  

  Abstract

  In this paper a novel numerical approximation of parametric eigenvalue problems is presented. We motivate our study with the analysis of a POD reduced order model for a simple one dimensional example. In particular, we introduce a new algorithm capable to track the matching of eigenvalues when the parameters vary.

  Abstract
  In this paper a novel numerical approximation of parametric eigenvalue problems is presented. We motivate our study with the analysis of a POD reduced order model for a simple [...]

  • 190
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