3 citations · 5 across the 9 of their papers we have counts for
9 papers
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…
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…
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…
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…
Enhancing deep learning of ammonia/natural gas combustion kinetics via physics-aware data augmentation and scale separation
Ke Xiao, Yangchen Xu, Han Li +1
Accurate and efficient numerical simulation of ammonia combustion is critical for advancing ammonia-based energy systems, where turbulent flame dynamics and pollutant formation str…
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…
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…
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.…
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…