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Verification and validation for and with reduced order modeling

Guest Editors:

  • Ludovic Chamoin (LMT (ENS Cachan/CNRS/Université Paris Saclay, Cachan, France)
  • Pedro Diez (Laboratori de Calcul Numeric (LaCaN), Universitat Politecnica de Catalunya, Barcelona, Spain)

Reduced Order Models (ROM) are essential tools to address the current challenges in Modeling and Simulation. However, the reduction of the computational complexity is accompanied by a loss of accuracy of the solution. The idea of ROM is to drastically reduce the complexity keeping the quality standards of the numerical solution (error within some prescribed tolerance).

In a more general context, in silico experiments that consist in building a virtual reality with numerical models are growing faster than the classical in vivo, in vitro or in situ versions. However, the numerical result is frequently suspicious of lack of realism. The inception of this suspicion is twofold because one may presume that 1) the underlying mathematical model is exaggeratedly simplifying reality (modeling error, related to validation) and 2) the numerical solver providing an approximate solution is questionable (numerical error, related to verification), for instance using a too coarse discretization. The use of a ROM is introducing a further approximation that could increase the numerical error and aggravate the effect of the second item.

Thus, reducing the order of the model is important, but the reduction has to be kept under control.

A growing synergy has emerged during the last decade between Verification & Validation (V&V) tools and ROM. On the one hand, predictive ROM cannot go without effective V&V procedures; this is currently a fundamental and active research topic. On the other hand, V&V can take great advantage of the flexibility and simplicity brought by reduced-order models.

The objective of the current special issue is therefore to present recent advances on this synergy, state-of-the-art techniques allowing quantifying the accuracy of the ROM solution and illustrative applications of coupled V&V and ROM in engineering activities.
 

  1. In this work a pancreatic surgery simulator is developed that provides the user with haptic feedback. The simulator is based on the use of model order reduction techniques, particularly Proper Generalized Deco...

    Authors: Andrés Mena, David Bel, Icíar Alfaro, David González, Elías Cueto and Francisco Chinesta
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:31
  2. Model order reduction is one of the most appealing choices for real-time simulation of non-linear solids. In this work a method is presented in which real time performance is achieved by means of the off-line ...

    Authors: Icíar Alfaro, David González, Sergio Zlotnik, Pedro Díez, Elías Cueto and Francisco Chinesta
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:30
  3. The proper generalized decomposition (PGD) requires separability of the input data (e.g. physical properties, source term, boundary conditions, initial state). In many cases the input data is not expressed in ...

    Authors: Sergio Zlotnik, Pedro Díez, David Gonzalez, Elías Cueto and Antonio Huerta
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:28
  4. Surrogate solutions and surrogate models for complex problems in many fields of science and engineering represent an important recent research line towards the construction of the best trade-off between modeli...

    Authors: Simona Perotto and Alessandro Zilio
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:25
  5. First, the effectivity of classical Proper Generalized Decomposition (PGD) computational methods is analyzed on a one dimensional transient diffusion benchmark problem, with a moving load. Classical PGD method...

    Authors: Pierre-Eric Allier, Ludovic Chamoin and Pierre Ladevèze
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:17
  6. The aim of this paper is to study two-time-scale nonlinear transient models and their associated parameter identification. When it is possible to consider two well-separated time scales, and when the fast comp...

    Authors: Guillaume Puel and Denis Aubry
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:8
  7. We propose an a posteriori estimator of the error of hyper-reduced predictions for elastoviscoplastic problems. For a given fixed mesh, this error estimator aims to forecast the validity domain in the paramete...

    Authors: David Ryckelynck, Laurent Gallimard and Samuel Jules
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:6
  8. The use of coarse-grained approximations of atomic systems is the most common methods of constructing reduced-order models in computational science. However, the issue of central importance in developing these...

    Authors: John Tinsley Oden, Kathryn Farrell and Danial Faghihi
    Citation: Advanced Modeling and Simulation in Engineering Sciences 2015 2:5