SHPB-driven framework for inverse identification of constitutive parameters of atypical concrete based on Bayesian optimization and neural networks

Zhijian Cai

doi:10.1016/j.ijimpeng.2026.105862

SHPB-driven framework for inverse identification of constitutive parameters of atypical concrete based on Bayesian optimization and neural networks

2026-07-29

0

PRE

AI

Z

Zhijian Cai *

H

Hao Lu *

H

Hao Chen

Z

Ziming Xiong

M

Mingyang Wang

C

Chao Zhang

R

Renpeng Chen

DOI：10.1016/j.ijimpeng.2026.105862

Original

Original request for help

Save

Abstract

En 中文

• Proposed an SHPB-driven BO–NN framework for constitutive parameter inversion. • Achieved accurate identification with only 15 additional simulations. • Outperformed GA, PSO, DE, and random search under the same budget. • Revealed key parameters and multi-solution behavior via SHAP analysis.

SHPB-driven framework for inverse identification of constitutive parameters of atypical concrete based on Bayesian optimization and neural networks

Abstract

Journal

Organization

Cited Papers

Citing Papers