3 papers
physics.flu-dyn2026
A New Paradigm for 3D Turbomachinery Design: Generative Diffusion Model Based Framework with Direct Geometry Encoding
Yingfan Geng, Jinhong Wang, Lazaros Papachristodoulou +2
The aerodynamic design of turbomachinery is critical to the performance of the overall energy system, yet it is challenging due to the complex non-linear flow physics and the prese…
physics.flu-dyn2026
Prediction of Steady-State Flow through Porous Media Using Machine Learning Models
Jinhong Wang, Matei C. Ignuta-Ciuncanu, Ricardo F. Martinez-Botas +1
Solving flow through porous media is a crucial step in the topology optimisation of cold plates, a key component in modern thermal management. Traditional computational fluid dynam…
physics.flu-dyn2026
Diffusion Model Driven Airfoil Design: From Geometry Encoding to Practical Applications
Yingfan Geng, Jinhong Wang, Teng Cao
Diffusion model, the state-of-the-art generative machine learning architecture, has shown promising results airfoil inverse designs. In this study, we implemented and trained a ser…