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From the 1 of 7 linked papers with an AI index.

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7 papers

stat.AP2026

Process-fracture mapping of a DLP-printed photopolymer using Bayesian active learning and surrogate-based sensitivity analysis

Ethan Blackwell, Yogesh C. Chandrashekar, Guoqiang Li +1

Digital light processing (DLP) enables rapid fabrication of polymer structures, but fracture performance depends on multiple interacting processing variables, making exhaustive exp…

q-bio.TO2026

History Matters: Damage-Mediated Amplification of Brain Deformation and Injury Risk under Repeated Head Impacts

Carson Cooper, Anu Tripathi, Genevieve Palardy +1

Computational head models are typically applied to isolated impacts, leaving repeated head loading largely unexplored. An Ogden-Roxburgh Mullins damage formulation was implemented…

stat.ML2026

Operator-Informed Gaussian Processes for Complex Helmholtz Wavefields: From Synthetic Benchmarks to In Vivo Brain Elastography

Boyuan Deng, Kshitiz Upadhyay, Michael Shields

The paper extends physics‑informed Gaussian‑process regression to complex‑valued Helmholtz wavefields by converting the complex operator into a coupled real system, allowing uncert…

cond-mat.soft2026

A constitutive framework for distortional-mode-dependent failure in soft materials: Tension-compression asymmetry and beyond

Yogesh C. Chandrashekar, Kshitiz Upadhyay

Soft materials exhibit pronounced tension-compression asymmetry (TCA) in their softening and failure, a feature that conventional hyperelastic and continuum-damage formulations fai…

cs.CE2026

A physics-informed data-driven framework for modeling hyperelastic materials with progressive damage and failure

Kshitiz Upadhyay

This work presents a two-stage physics-informed, data-driven constitutive modeling framework for hyperelastic soft materials undergoing progressive damage and failure. The framewor…

cond-mat.soft2025

Stress Softening Damage in Strongly Nonlinear Viscoelastic Soft Materials A Physics Informed Data Driven Constitutive Model with Time Temperature Coupling

Alireza Ostadrahimi, Amir Teimouri, Kshitiz Upadhyay +1

This study presents a novel physics informed, data-driven modeling framework for capturing the strongly nonlinear thermo-viscoelastic behavior of soft materials exhibiting stress s…