Learning a hyperelastic constitutive model from 3D experimental data

Authors

Institutions

Publication Details

Journal
Computer Methods in Applied Mechanics and Engineering
Published
2025-12-12
DOI
https://doi.org/10.1016/j.cma.2025.118592
Citations
1
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.67
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Learning a hyperelastic constitutive model from 3D experimental data

Clément Jailin, Richard N. Langlois, Emmanuel Baranger, Benjamin Smaniotto et al.
1 citations
Computer Methods in Applied Mechanics and Engineering
Elasticity and Material Modeling
0.67
article

Learning a hyperelastic constitutive model from 3D experimental data

Clément Jailin, Richard N. Langlois, Emmanuel Baranger, Benjamin Smaniotto, Mathys Bourdyot, Marius Compans
article en
1 citations

Abstract

No abstract available for this paper.
Computer Methods in Applied Mechanics and EngineeringVol. 450
École Normale Supérieure Paris-Saclay (FR), Université de Lyon (FR), École Normale Supérieure - PSL (FR), Laboratoire de Biologie et Pharmacologie Appliquée (FR), Laboratoire de Mécanique des Contacts et des Structures (FR), Laboratoire de Mécanique Paris-Saclay (FR), Institut National des Sciences Appliquées de Lyon (FR)
Openalex Percentile: Top 24%
Elasticity and Material Modeling
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.