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Call for Papers: Data-Based Engineering and Computation

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

Guest Editors
Francisco Chinesta, ENSAM ParisTech
Charbel Farhat, Stanford University
Pierre Ladeveze, ENS Paris Saclay
Francisco Javier Montans, Polytechnic University of Madrid


Submission Instructions

Before submitting your manuscript, please ensure you have carefully read the submission guidelines for Advanced Modeling and Simulation in Engineering Sciences. Your complete manuscript should be submitted through the Advanced Modeling and Simulation in Engineering Sciences submission system, selecting inclusion with the thematic series, “Data-based Engineering and Computations” when prompted. All submissions will undergo rigorous peer review and accepted articles will be published within the journal as a collection.


Open Access Publication

Submissions will also benefit from the usual advantages of open access publication:

Rapid publication: Online submission, electronic peer review and production make the process of publishing your article simple and efficient.
High visibility and international readership in your field: Open access publication ensures high visibility and maximum exposure for your work - anyone with online access can read your article.
No space constraints: Publishing online means unlimited space for figures, extensive data and video footage.
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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