Papers

2026

  1. A Differentiable Framework for Inverse Identification of Heterogeneous Cohesive Laws
    A Differentiable Framework for Inverse Identification of Heterogeneous Cohesive Laws
    S. Hao, J. Han, and B. Bahmani
    Preprint, 2026
    Details Paper
  2. Data-Driven Cohesive Zone Modeling within the Generalized Standard Materials Framework
    Data-Driven Cohesive Zone Modeling within the Generalized Standard Materials Framework
    S. Hao, J. Han, and B. Bahmani
    arXiv preprint, 2026
    Details Paper
  3. Constitutive Priors for Inverse Design
    Constitutive Priors for Inverse Design
    J. Han and B. Bahmani
    Computer Methods in Applied Mechanics and Engineering, 2027
    Details Paper arXiv
  4. Conformal Quantile Regression for Neural Probabilistic Constitutive Modeling
    Conformal Quantile Regression for Neural Probabilistic Constitutive Modeling
    B. Bahmani
    Computer Methods in Applied Mechanics and Engineering, 2026
    Details Paper arXiv
  5. A Multimodal Conditional Mixture Model with Distribution-Level Physics Priors
    A Multimodal Conditional Mixture Model with Distribution-Level Physics Priors
    J. Han and B. Bahmani
    International Journal for Numerical Methods in Engineering, 2026
    Details Paper arXiv
  6. A Multi-Fidelity Bayesian Neural Operator for Mechanics of Spinodal Metamaterial
    A Multi-Fidelity Bayesian Neural Operator for Mechanics of Spinodal Metamaterial
    P. You, H. Chen, B. Bahmani, and H. D. Espinosa
    npj Computational Materials, 2026
    Details Paper arXiv
  7. Neural Operator Representation of Granular Micromechanics-based Failure Envelope
    Neural Operator Representation of Granular Micromechanics-based Failure Envelope
    J. Han, P. Poorsolhjouy, and B. Bahmani
    arXiv preprint, 2026
    Details Paper
  8. AIChE
    Discretizations from Hell: Different Representations of the Same Dynamics
    R. Chandar, H. Arbabi, B. Bahmani, et al.
    AIChE Annual Meeting, 2026

2025

  1. Neural Chaos: A Spectral Stochastic Neural Operator
    Neural Chaos: A Spectral Stochastic Neural Operator
    B. Bahmani, et al.
    Journal of Computational Physics, 2025
    Paper arXiv
  2. A Resolution Independent Neural Operator
    A Resolution Independent Neural Operator
    B. Bahmani, et al.
    Computer Methods in Applied Mechanics and Engineering, 2025
    Paper arXiv
  3. A Physics-informed Multi-resolution Neural Operator
    A Physics-informed Multi-resolution Neural Operator
    S. Roy, B. Bahmani, et al.
    arXiv preprint, 2025
    Paper

2024

  1. Physics-constrained Symbolic Model Discovery for Polyconvex Incompressible Hyperelastic Material
    Physics-constrained Symbolic Model Discovery for Polyconvex Incompressible Hyperelastic Material
    B. Bahmani and W. Sun
    International Journal for Numerical Methods in Engineering, 2024
    Paper arXiv
  2. Discovering Interpretable Elastoplasticity Models via the Neural Polynomial Method enabled Symbolic Regression
    Discovering Interpretable Elastoplasticity Models via the Neural Polynomial Method enabled Symbolic Regression
    B. Bahmani, et al.
    Computer Methods in Applied Mechanics and Engineering, 2024
    Paper arXiv
  3. A Review on Data-Driven Constitutive Laws for Solids
    A Review on Data-Driven Constitutive Laws for Solids
    J. Fuhg, G. Padmanabha, N. Bouklas, B. Bahmani, et al.
    Archives of Computational Methods in Engineering, 2024
    Paper arXiv

2023

  1. Manifold embedding data-driven mechanics
    Manifold embedding data-driven mechanics
    B. Bahmani and W. Sun
    Journal of Mechanics and Physics of Solids, 2023
    Paper arXiv
  2. Distance-preserving manifold de-noising for data-driven mechanics
    Distance-preserving manifold de-noising for data-driven mechanics
    B. Bahmani and W. Sun
    Computer Methods in Applied Mechanics and Engineering, 2023
    Paper
  3. Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
    Equivariant geometric learning for digital rock physics: estimating formation factor and effective permeability tensors from Morse graph
    C. Cai, N. Vlassis, L. Magee, R. Ma, Z. Xiong, B. Bahmani, et al.
    International Journal for Multiscale Computational Engineering, 2023
    Paper arXiv

2022

  1. Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty quantification
    Data-driven discovery of interpretable causal relations for deep learning material laws with uncertainty quantification
    X. Sun, B. Bahmani, et al.
    Granular Matter, 2022
    Paper arXiv
  2. Synthesizing controlled microstructures of porous media using generative adversarial networks and reinforcement learning
    Synthesizing controlled microstructures of porous media using generative adversarial networks and reinforcement learning
    P. Nguyen, N. Vlassis, B. Bahmani, et al.
    Scientific Reports, 2022
    Paper

2021

  1. A kd-tree-accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data
    A kd-tree-accelerated hybrid data-driven/model-based approach for poroelasticity problems with multi-fidelity multi-physics data
    B. Bahmani and W. Sun
    Computer Methods in Applied Mechanics and Engineering, 2021
    Paper arXiv
  2. Training multi-objective/multi-task collocation physics-informed neural network with student-teachers transfer learnings
    Training multi-objective/multi-task collocation physics-informed neural network with student-teachers transfer learnings
    B. Bahmani and W. Sun
    arXiv preprint, 2021
    Paper

2019

  1. CMAME
    Automated homogenization-based fracture analysis: Effects of SVE size and boundary condition
    B. Bahmani, et al.
    Computer Methods in Applied Mechanics and Engineering, 2019
    Paper
  2. JEM
    Asynchronous spacetime discontinuous Galerkin formulation for a hyperbolic time-delay bulk damage model
    B. Bahmani and R. Abedi
    Journal of Engineering Mechanics, 2019
    Paper
  3. A stochastic bulk damage model based on Mohr-Coulomb failure criterion for dynamic rock fracture
    A stochastic bulk damage model based on Mohr-Coulomb failure criterion for dynamic rock fracture
    B. Bahmani, et al.
    Applied Sciences, 2019
    Paper
  4. ASCE-ASME
    Effect of volume element geometry on convergence to a representative volume
    K. Acton, C. Sherod, B. Bahmani, and R. Abedi
    ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 2019
    Paper

2018

  1. CMAME
    Voronoi tessellation based statistical volume element characterization for use in fracture modeling
    K. Acton, S. Baxter, B. Bahmani, P. Clarke, and R. Abedi
    Computer Methods in Applied Mechanics and Engineering, 2018
    Paper
  2. Application of an enriched FEM technique in thermo-mechanical contact problems
    Application of an enriched FEM technique in thermo-mechanical contact problems
    A. Khoei and B. Bahmani
    Computational Mechanics, 2018
    Paper

You can also find my articles on my Google Scholar profile.