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

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

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

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…

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.LG20261 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…

physics.flu-dyn2025

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…