4 papers
PIKFNO: An Interpretable Neural Operator Based on Physics Informed Kernel Function
Yuan Guo, Hanshu Chen, Zhuojia Fu
This work proposes a new interpretable neural operator framework, termed the Physics Informed Kernel Function Neural Operator (PIKFNO), which explicitly incorporates physics inform…
Mapping-based Hard-constrained Physics-Informed Neural Networks for unbounded wave problems
Tao Zhang, Hanshu Chen, Ilia Marchevsky +1
The aim of this paper is to introduce a Mapping-based Hard-constrained Physics-Informed Neural Network (MH-PINN) for efficiently and accurately solving unbounded wave problems. Fir…
Quantum AS-DeepOnet: Quantum Attentive Stacked DeepONet for Solving 2D Evolution Equations
Hongquan Wang, Hanshu Chen, Ilia Marchevsky +1
DeepONet enables retraining-free inference across varying initial conditions or source terms at the cost of high computational requirements. This paper proposes a hybrid quantum op…
Fatigue reliability analysis of offshore wind turbines under combined wind-wave excitation via DPIM
Jingyi Ding, Hanshu Chen, Xiaoting Liu +2
As offshore wind turbines develop into deepwater operations, accurately quantifying the impact of stochastic excitations in complex sea environments on offshore wind turbines and c…