11 papers
RealPDEBench: A Benchmark for Complex Physical Systems with Real-World Data
Peiyan Hu, Haodong Feng, Hongyuan Liu +13
Predicting the evolution of complex physical systems remains a central problem in science and engineering. Despite rapid progress in scientific Machine Learning (ML) models, a crit…
GenCP: Towards Generative Modeling Paradigm of Coupled Physics
Tianrun Gao, Haoren Zheng, Wenhao Deng +5
Real-world physical systems are inherently complex, often involving the coupling of multiple physics, making their simulation both highly valuable and challenging. Many mainstream…
Towards an AI Fluid Scientist: LLM-Powered Scientific Discovery in Experimental Fluid Mechanics
Haodong Feng, Lugang Ye, Dixia Fan
The integration of artificial intelligence into experimental fluid mechanics promises to accelerate discovery, yet most AI applications remain narrowly focused on numerical studies…
Model-Based Closed-Loop Control Algorithm for Stochastic Partial Differential Equation Control
Peiyan Hu, Haodong Feng, Yue Wang +1
Neural operators have demonstrated promise in modeling and controlling systems governed by Partial Differential Equations (PDEs). Beyond PDEs, Stochastic Partial Differential Equat…
From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control
Peiyan Hu, Xiaowei Qian, Wenhao Deng +8
The application of deep learning for partial differential equation (PDE)-constrained control is gaining increasing attention. However, existing methods rarely consider safety requi…
How to Re-enable PDE Loss for Physical Systems Modeling Under Partial Observation
Haodong Feng, Yue Wang, Dixia Fan
In science and engineering, machine learning techniques are increasingly successful in physical systems modeling (predicting future states of physical systems). Effectively integra…
Wavelet Diffusion Neural Operator
Peiyan Hu, Rui Wang, Xiang Zheng +7
Simulating and controlling physical systems described by partial differential equations (PDEs) are crucial tasks across science and engineering. Recently, diffusion generative mode…
Multi-modal Policies with Physics-informed Representations in Complex Fluid Environments
Haodong Feng, Peiyan Hu, Yue Wang +1
Control in fluid environments is an important research area with numerous applications across various domains, including underwater robotics, aerospace engineering, and biomedical…
CL-DiffPhyCon: Closed-loop Diffusion Control of Complex Physical Systems
Long Wei, Haodong Feng, Yuchen Yang +6
The control problems of complex physical systems have broad applications in science and engineering. Previous studies have shown that generative control methods based on diffusion…
DiffPhyCon: A Generative Approach to Control Complex Physical Systems
Long Wei, Peiyan Hu, Ruiqi Feng +7
Controlling the evolution of complex physical systems is a fundamental task across science and engineering. Classical techniques suffer from limited applicability or huge computati…
Efficient Navigation of a Robotic Fish Swimming Across the Vortical Flow Field
Haodong Feng, Dehan Yuan, Jiale Miao +4
Navigating efficiently across vortical flow fields presents a significant challenge in various robotic applications. The dynamic and unsteady nature of vortical flows often disturb…