Model-free data-driven inference in computational mechanics

DOI10.1016/J.CMA.2022.115704OpenAlexW4307905418MaRDI QIDQ2679455

Yanyan Li

Publication date: 20 January 2023

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2207.06419

zbMATH Keywords

Monte Carlocomputational mechanicsuncertainty quantificationdata-drivenmechanics of materials

Mathematics Subject Classification ID

Statistics (62-XX) Mechanics of deformable solids (74-XX)

Related Items (4)

Advanced discretization techniques for hyperelastic physics-augmented neural networks ⋮ Convolution finite element based digital image correlation for displacement and strain measurements ⋮ Convergence rates for ansatz‐free data‐driven inference in physically constrained problems ⋮ Data-driven games in computational mechanics

Uses Software

• FLANN
• GitHub
• PAIsing
• pybind11

Cites Work

• Unnamed Item
• Bayes procedures for adaptive inference in inverse problems for the white noise model
• Bayesian inverse problems with Gaussian priors
• GPU accelerated population annealing algorithm
• Efficient data structures for model-free data-driven computational mechanics
• Data driven computing with noisy material data sets
• Mixed-integer programming formulation of a data-driven solver in computational elasticity
• Data-driven computational mechanics
• On the Brittleness of Bayesian Inference
• Kullback--Leibler Approximation for Probability Measures on Infinite Dimensional Spaces
• A Branch and Bound Algorithm for Computing k-Nearest Neighbors
• Equation of State Calculations by Fast Computing Machines
• On Information and Sufficiency

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