Engineering is evolving in the same way as society. Nowadays, data is earning a prominence never imagined before. In the past, in the domain of materials, processes and structures, testing machines allowed the extraction of data, which served in turn to calibrate state-of-the- art computational models.
Some calibration procedures were even integrated within testing machines. Thus, once the model was calibrated, computer simulation took place. However, data can offer much more than a simple state-of-the-art model calibration, and not only from its simple statistical analysis, but from the modeling and simulation viewpoints.
This gives rise to the family of so-called digital twins, also known as virtual and hybrid twins. Moreover, not only data can serve to enrich physically-based models. These could allow us to perform a tremendous leap forward, by replacing big-data-based habits by the incipient smart-data paradigm.
In this collection, we will cover recent advances in the field, with a particular emphasis on grey-box approaches, i.e., those in which the laws of physics are included in the approach.
Particular topics of interest include but are not limited to:
- Scientific machine learning
- Manifold learning
- Physics-informed machine learning
- Model reductionDigital
- Hybrid twins
Lead Guest Editor
Elías Cueto, Universidad de Zaragoza, Zaragoza, Spain
Guest Editors
Francisco Chinesta, PIMM Laboratory, Arts et Métiers Institute of Technology, HESAM Université, Paris, France
Charbel Farhat, Stanford University, California, USA
Pierre Ladeveze, ENS Paris Saclay, Gif-sur-Yvette, France
Francisco Javier Montans, Polytechnic University of Madrid, Madrid, Spain
Peer Review Process
Advanced Modeling and Simulation in Engineering Sciences operates a single-blind peer-review system, where the reviewers are aware of the names and affiliations of the authors, but the reviewer reports provided to authors are anonymous.
Submitted manuscripts will generally be reviewed by two to three experts who will be asked to evaluate whether the manuscript is scientifically sound and coherent, whether it duplicates already published work, and whether or not the manuscript is sufficiently clear for publication. The Editors will reach a decision based on these reports and, where necessary, they will consult with members of the Editorial Board.
Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies, including those pertaining to Collections. Articles will be added to the Collection as they are published.
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