Miguel A. Bessa
Mechanics of Materials · 2013–2019
A researcher in the Science corpus: 4 papers; trusts 23 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Mechanics of Materials — 57 citations into it; #2,624 of 6,291 by trust here, #1,992 by citations
- Computational Theory and Mathematics — 27 citations into it; #6,867 of 12,182 by trust here, #8,294 by citations
- Materials Chemistry — 17 citations into it
- Statistics and Probability — 14 citations into it
- Artificial Intelligence — 13 citations into it
- Biomedical Engineering — 12 citations into it
- Molecular Biology — 7 citations into it
- Statistical and Nonlinear Physics — 6 citations into it
Whom Miguel A. Bessa trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Julien Yvonnet
- J. Michel
- Ilya M. Sobol
- Paul J. Werbos
- Eric R. Ziegel
- V. Kouznetsova
- G. Berkooz
- Pierre Ladevèze
- Qi-Chang He
- J. Chaboche
Who trusts Miguel A. Bessa overall
- Qizhi He
- Zeliang Liu
- Kun Wang
- Jiun-Shyan Chen
- Ramin Bostanabad
- WaiChing Sun
- Mark Fleming
- Wing Kam Liu
Papers from Miguel A. Bessa's perspective
Ordered by how strongly the researchers Miguel A. Bessa trusts endorse each paper. Same corpus, a different order for every researcher.
- Numerically explicit potentials for the homogenization of nonlinear elastic heterogeneous materials
- A new family of solvers for some classes of multidimensional partial differential equations encountered in kinetic theory modeling of complex fluids
- Design and Modeling for Computer Experiments
- The Proper Orthogonal Decomposition in the Analysis of Turbulent Flows
- On the distribution of points in a cube and the approximate evaluation of integrals
- A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code
- Dimensional model reduction in non‐linear finite element dynamics of solids and structures
- Multi‐scale constitutive modelling of heterogeneous materials with a gradient‐enhanced computational homogenization scheme
- Simulation of the multi-scale convergence in computational homogenization approaches
- Generation of random distribution of fibres in long-fibre reinforced composites
Their papers
- A framework for data-driven analysis of materials under uncertainty: Countering the curse of dimensionality (2017) — 525 citations
- Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials (2016) — 441 citations
- Deep learning predicts path-dependent plasticity (2019) — 569 citations
- Modeling the inelastic deformation and fracture of polymer composites – Part II: Smeared crack model (2013) — 152 citations