Author

Muhammad Umar Khan

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Oct 2026

ASSESSMENT OF FATIGUE CRACK PROPAGATION LIFE BASED ON PHYSICS-INFORMED NEURAL NETWORKS UNDER ENSEMBLE LEARNING IN HYDROGEN ENVIRONMENTS

This paper offers a physics-informed neural network (PINN) and ensemble learning framework that integrates physical and data-driven modeling using Bayesian model averaging (BMA) with a probabilistic neural network (PNN).

De-Biao Meng, Muhammad Umar Khan, Hua-Xi Wu et al. · Surface review and letters · 0 citations

Open access Jul 2026

Time-Variant Reliability Analysis via Copula Failure Correlation and Advanced Kriging

In practical engineering, mechanical structures are affected by time-dependent uncertainties and by correlated failure modes. This study proposes an enhanced time-variant reliability analysis framework by coupling a mixed Archimedean Copula model with an adaptive Kriging model driven by the maximum expected prediction...

Debiao Meng, Huaxi Wu, Muhammad Umar Khan et al. · Mathematics · 0 citations