activity
20232026
most citedA comprehensive study on the accuracy and generalization of deep learning-generated chemical ODE integrators

3 citations · 5 across the 14 of their papers we have counts for

collaborators

16 papers

cs.AI2026

RocketAgent: A Long-Horizon Engineering Agent for Multidisciplinary Design of Liquid-Rocket Thrust Chambers

Junxiang He, Runze Mao, Kun He +4

Liquid-rocket thrust-chamber design involves interdependent analyses in which downstream constraints can require earlier design decisions to be revisited. Managing these dependenci…

cs.SE2026

A Case-Bundle Operating Model for Coding Agents in OpenFOAM-Based CFD

Ke Xiao, Han Li, Teng Zhang +3

General-purpose coding agents can set up computational fluid dynamics (CFD) cases, execute solvers, and manage remote jobs. Reviewable and reusable work additionally depends on per…

cs.LG2026

Physics Transformer: Tailoring Transformer for General PDE Prediction

Guoze Sun, Rui Zhang, Jiankai Tang +4

Transformer architectures have attracted increasing attention for solving partial differential equations (PDEs), owing to their flexibility in handling irregular discretizations an…

cs.LG2026

Thermodynamics-Informed Input Reparameterization for Neural Prediction of Real-Fluid Thermodynamic Properties in Supercritical Combustion

Haoze Zhang, Han Li, Ke Xiao +3

Real-fluid thermodynamic property evaluation is a major computational cost in supercritical combustion simulations. In the enthalpy-based pressure-correction formulation, the closu…

cs.LG2026

NPSolver: Neural Poisson Solver with Iterative Physics Supervision

Bocheng Zeng, Rui Zhang, Runze Mao +5

Efficiently solving Poisson equations on complex, irregular domains remains a fundamental challenge in scientific computing, as classical iterative solvers often suffer from prohib…

cs.CL2026

Full-Stack Domain Enhancement for Combustion LLMs: Construction and Optimization

Quanjia Xiao, Weimin Ouyang, Zonglin Yang +4

Large language models (LLMs) in the direction of task adaptation and capability enhancement for professional fields demonstrate significant application potential. Nevertheless, for…

cs.CL2026

A unified foundational framework for knowledge injection and evaluation of Large Language Models in Combustion Science

Zonglin Yang, Runze Mao, Tianhao Wu +3

To advance foundation Large Language Models (LLMs) for combustion science, this study presents the first end-to-end framework for developing domain-specialized models for the combu…

physics.flu-dyn2026

A Preliminary Assessment of Coding Agents for CFD Workflows

Ke Xiao, Haoze Zhang, Yangchen Xu +3

We investigate the use of tool-using coding agents to automate end-to-end workflows in the open-source CFD package OpenFOAM. Building on general-purpose coding agent interfaces, we…

cs.LG2026★ 1 cited

Towards LLM-enabled autonomous combustion research: A literature-aware agent for self-corrective modeling workflows

Ke Xiao, Haoze Zhang, Runze Mao +2

The rapid evolution of large language models (LLMs) is transforming artificial intelligence into autonomous research partners, yet a critical gap persists in complex scientific dom…

cs.LG2025

Benchmarking neural surrogates on realistic spatiotemporal multiphysics flows

Runze Mao, Rui Zhang, Xuan Bai +21

Predicting multiphysics dynamics is computationally expensive and challenging due to the severe coupling of multi-scale, heterogeneous physical processes. While neural surrogates p…

cs.DC2025★ 1 cited

Deep Learning-Enabled Supercritical Flame Simulation at Detailed Chemistry and Real-Fluid Accuracy Towards Trillion-Cell Scale

Zhuoqiang Guo, Runze Mao, Lijun Liu +3

For decades, supercritical flame simulations incorporating detailed chemistry and real-fluid transport have been limited to millions of cells, constraining the resolved spatial and…

physics.flu-dyn2024

Graphics Processing Unit/Artificial Neural Network-accelerated large-eddy simulation of turbulent combustion: Application to swirling premixed flames

Min Zhang, Runze Mao, Han Li +2

Within the scope of reacting flow simulations, the real-time direct integration (DI) of stiff ordinary differential equations (ODE) for the computation of chemical kinetics stands…

physics.flu-dyn2023★ 3 cited

A comprehensive study on the accuracy and generalization of deep learning-generated chemical ODE integrators

Han Li, Ruixin Yang, Min Zhang +2

The application of deep neural networks (DNNs) holds considerable promise as a substitute for the direct integration of chemical source terms in combustion simulations. However, ch…

cs.CE2023

An integrated framework for accelerating reactive flow simulation using GPU and machine learning models

Runze Mao, Yingrui Wang, Min Zhang +5

Recent progress in artificial intelligence (AI) and high-performance computing (HPC) have brought potentially game-changing opportunities in accelerating reactive flow simulations.…

physics.flu-dyn2023

GPU-accelerated Large Eddy Simulation of turbulent stratified flames with machine learning chemistry

Min Zhang, Runze Mao, Han Li +2

Stratified premixed combustion, known for its capability to expand flammability limits and reduce overall-lean combustion instability, has been widely adopted to comply with increa…

physics.flu-dyn2023

Detailed simulation of LOX/GCH4 flame-vortex interaction in supercritical Taylor-Green flows with machine learning

Jiayang Xu, Yifan Xu, Zifeng Weng +4

Accurate and affordable simulation of supercritical reacting flow is of practical importance for developing advanced engine systems for liquid rockets, heavy-duty powertrains, and…