The use of experimental data in association with simulation models has become an active research topic. Indeed, new experimental facilities (such as digital image/volume correlation (DIC/DVC)) now enable to collect a large and diversified amount of data, and these may be used to identify and validate complex models, or to enhance predictions made by simulations tools. Furthermore, data and models are more and more intertwined to improve knowledge in applications dealing with structural health monitoring and control for instance, with potential real-time dialogue between simulators and connected physical systems (e.g., the DDDAS concept). However, many challenges dealing with data filtering, computational cost, or numerical robustness need to be addressed in order to incorporate data efficiently.
The goal of this special issue is to present, in both deterministic and stochastic (Bayesian) contexts, recent fundamental advances in data assimilation and inverse methods with regards to innovative and powerful numerical approaches which emerged during the last years.
We anticipate contributions on the following topics:
- data assimilation and real-time model updating;
- use of model reduction or multiscale approaches;
- adaptive and multi-fidelity strategies;
- analysis of full-field measurements, data selection;
- representation and propagation of model and measurement errors;
- goal-oriented model updating;
- experimental design
Before submitting your manuscript, please ensure you have carefully read the submission guidelines for Advanced Modeling and Simulation in Engineering Sciences. The complete manuscript should be submitted through the Advanced Modeling and Simulation in Engineering Sciences submission system. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.
Lead Guest Editor
Ludovic Chamoin, ENS Paris-Saclay, France, firstname.lastname@example.org
Andrea Manzoni, Politecnio di Milano, Italy, email@example.com
Karen Veroy-Grepl, Aachen University, Germany, firstname.lastname@example.org
Open Access Publication
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- Authors retain copyright, licensing the article under a Creative Commons license: articles can be freely redistributed and reused as long as the article is correctly attributed.
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