Computational Structural Mechanics Association

AMSES

The CSMA has been providing financial and scientific support since 2012 to the OpenAccess journal Advanced Modeling and Simulation in Engineering Sciences. The journal, previously led by editor-in-chief Pierre Ladevèze until may 2024, is published by Springer. Francisco Chinesta has taken over as editor-in-chief since that date, ensuring continuity.
The process of indexing a new journal is particularly lengthy. The success of the journal led to its indexing in 2023.
SCImago Journal & Country Rank

HAL list of articles published in AMSES journal


280 documents

  • Yinghan Wu, Kaixuan Shao, Francesco Piccialli, Gang Mei. Numerical modeling of the propagation process of landslide surge using physics-informed deep learning. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-15. ⟨10.1186/s40323-022-00228-6⟩. ⟨hal-04456076⟩
  • Terrin Stachiw, Alexander Crain, Joseph Ricciardi. A physics-based neural network for flight dynamics modelling and simulation. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-20. ⟨10.1186/s40323-022-00227-7⟩. ⟨hal-04456077⟩
  • E. Rajasekhar Nicodemus. A methodology to assess and improve the physics consistency of an artificial neural network regression model for engineering applications. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-29. ⟨10.1186/s40323-022-00224-w⟩. ⟨hal-04456078⟩
  • Valerie A. Martin, Reuben H. Kraft, Thomas H. Hannah, Stephen Ellis. An energy-based study of the embedded element method for explicit dynamics. Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-18. ⟨10.1186/s40323-022-00223-x⟩. ⟨hal-04513972⟩
  • Sebastián Cedillo, Ana Gabriela Núñez, Esteban Sánchez-Cordero, Luis Timbe, Esteban Samaniego, et al.. Physics-Informed Neural Network water surface predictability for 1D steady-state open channel cases with different flow types and complex bed profile shapes. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning, 9 (1), pp.1-23. ⟨10.1186/s40323-022-00226-8⟩. ⟨hal-04458286⟩
  • Nora Hagmeyer, Matthias Mayr, Ivo Steinbrecher, Alexander Popp. One-way coupled fluid–beam interaction: capturing the effect of embedded slender bodies on global fluid flow and vice versa. Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-30. ⟨10.1186/s40323-022-00222-y⟩. ⟨hal-04513974⟩
  • Jan Oldenburg, Finja Borowski, Alper Öner, Klaus Peter Schmitz, Michael Stiehm. Geometry aware physics informed neural network surrogate for solving Navier–Stokes equation (GAPINN). Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-15. ⟨10.1186/s40323-022-00221-z⟩. ⟨hal-04513973⟩
  • Harald Willmann, Wolfgang A. Wall. Inverse analysis of material parameters in coupled multi-physics biofilm models. Advanced Modeling and Simulation in Engineering Sciences, 2022, 9 (1), pp.1-32. ⟨10.1186/s40323-022-00220-0⟩. ⟨hal-04513976⟩
  • Fabio Giampaolo, Mariapia de Rosa, Pian Qi, Stefano Izzo, Salvatore Cuomo. Physics-informed neural networks approach for 1D and 2D Gray-Scott systems. Advanced Modeling and Simulation in Engineering Sciences, 2022, Physics-Informed and Scientific Machine Learning Francesco Piccialli, 9 (1), pp.1-17. ⟨10.1186/s40323-022-00219-7⟩. ⟨hal-04456081⟩
  • Hanane Khatouri, Tariq Benamara, Piotr Breitkopf, Jean Demange. Metamodeling techniques for CPU-intensive simulation-based design optimization: a survey. Advanced Modeling and Simulation in Engineering Sciences, 2022, Efficient strategies for surrogate-based optimization including multifidelity and reduced-order models, 9 (1), pp.1-31. ⟨10.1186/s40323-022-00214-y⟩. ⟨hal-04458288⟩

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