5 papers
Equation Recast for Canonical Operator Learning Across Parametric PDEs
Qiyun Cheng, Valentin Duruisseaux, Cesar F. Clauser +7
Learning solution operators across broad parameter ranges can require substantial coverage of both input functions and physical parameters, particularly for purely data-driven para…
Surrogate Modeling for Neutron Transport: A Neural Operator Approach
Md Hossain Sahadath, Qiyun Cheng, Shaowu Pan +1
This work introduces a neural operator based surrogate modeling framework for neutron transport computation. Two architectures, the Deep Operator Network (DeepONet) and the Fourier…
MD-PNOP: Equation-Recast Neural Operators for Minimal-Data Extrapolation and PDE Solver Acceleration
Qiyun Cheng, Md Hossain Sahadath, Huihua Yang +2
The computational overhead of traditional numerical solvers for partial differential equations (PDEs) remains a critical bottleneck for large-scale parametric studies and design op…
An Adaptive Real-Time Forecasting Framework for Cryogenic Fluid Management in Space Systems
Qiyun Cheng, Huihua Yang, Wei Ji
Accurate real-time forecasting of cryogenic tank behavior is essential for the safe and efficient operation of propulsion and storage systems in future deep-space missions. While c…
A Data-Driven Based Concurrent Coupling Approach for Cryogenic Propellant Tank Long-term Pressure Control Predictions
Qiyun Cheng, Huihua Yang, Shanbin Shi +1
The design and optimization of cryogenic propellant storage tanks for NASA's future space missions require fast and accurate predictions of long-term fluid behaviors. Computational…