Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics

Autor: Saurabh Deshpande, Raúl I. Sosa, Stéphane P. A. Bordas, Jakub Lengiewicz

Publikováno v: Frontiers in Materials, Vol 10 (2023)

Deep learning surrogate models are being increasingly used in accelerating scientific simulations as a replacement for costly conventional numerical techniques. However, their use remains a significant challenge when dealing with real-world complex e

Externí odkaz: https://doaj.org/article/55ee0b2ad62845e4bca1effb76cf083f

From quantum to continuum mechanics in the delamination of atomically-thin layers from substrates

Autor: Paul Hauseux, Thanh-Tung Nguyen, Alberto Ambrosetti, Katerine Saleme Ruiz, Stéphane P. A. Bordas, Alexandre Tkatchenko

Publikováno v: Nature Communications, Vol 11, Iss 1, Pp 1-8 (2020)

The unexpectedly long-ranged interface stress observed in recent delamination experiments is yet to be clarified. Here, the authors develop an analytical approach to show the wavelike atomic deformation as the origin for the observed ultra long-range

Externí odkaz: https://doaj.org/article/5ba7529f34eb44cfa819409a71c40881

Seismic Performance of Kiewitt-Sunflower Single Layer Spherical Reticulated Shells

Autor: Sheng He, Siliu Yu, Weijing Yun, Stéphane P. A. Bordas, Peng Yu

Publikováno v: KSCE Journal of Civil Engineering. 26:2354-2368

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::571e364eca2fbe473c9c92d7e4e94fa9
https://doi.org/10.1007/s12205-022-1286-8

Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences

Autor: Anja K. Leist, Matthias Klee, Jung Hyun Kim, David H. Rehkopf, Stéphane P. A. Bordas, Graciela Muniz-Terrera, Sara Wade

Publikováno v: Leist, A K, Klee, M, Kim, J H, Rehkopf, D H, Bordas, S P A, Muniz-Terrera, G & Wade, S 2022, ' Mapping of machine learning approaches for description, prediction, and causal inference in the social and health sciences ', Science Advances, vol. 8, no. 42, pp. eabk1942 . https://doi.org/10.1126/sciadv.abk1942

Machine learning (ML) methodology used in the social and health sciences needs to fit the intended research purposes of description, prediction, or causal inference. This paper provides a comprehensive, systematic meta-mapping of research questions i

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::436148ef9e3f1e223e8aa3af60147caf
https://doi.org/10.1126/sciadv.abk1942

Geometrically Unfitted Finite Element Methods and Applications : Proceedings of the UCL Workshop 2016

Autor: Stéphane P. A. Bordas, Erik Burman, Mats G. Larson, Maxim A. Olshanskii

This book provides a snapshot of the state of the art of the rapidly evolving field of integration of geometric data in finite element computations. The contributions to this volume, based on research presented at the UCL workshop on the topic in Jan