4 citations · 6 across the 11 of their papers we have counts for
11 papers
ArtisanCAD: An Industrial-Level CAD Agent with Expert-Grounded Knowledge Distillation
Yunhan Xu, Qifeng Wu, Xunjin Li +10
Computer-aided design (CAD) for industrial components requires long-horizon procedural modeling, robust feature dependencies, editable parametric geometry, and production-grade B-R…
Knowledge-Constrained Shape Optimization with a Mixture-of-Experts Neural Operator for High-Confidence Design
Wenhao Fan, Yuanwei Bin, Jianghan Gu +4
Engineering shape optimization faces challenges in both expert-dependent problem setup and surrogate-model reliability. In practical aerodynamic design, optimization settings such…
Least-Action-Guided Diffusion for Physical Extrapolation
Zhongxin Yang, Yuanwei Bin, Xiang I. A. Yang +1
Reliable extrapolation remains a central challenge for generative models in computational physics, because models trained over finite ranges of time, parameters, or geometries may…
A Geometry-Aware Triplane Field Network for Vehicle Aerodynamic Prediction
Kangkang Qi, Huiyu Yang, Keqi Ding +5
High-fidelity computational fluid dynamics (CFD) is crucial to vehicle aerodynamic analysis, but its cost still constrains early-stage design exploration. Machine-learning-based su…
RETO: A Rotary-Enhanced Transformer Operator for High-Fidelity Prediction of Automotive Aerodynamics
Bojun Zhang, Huiyu Yang, Yunpeng Wang +4
Rapid aerodynamic evaluation is crucial for modern vehicle design, yet existing neural operators struggle to capture intricate spatial correlations. We propose the rotary-enhanced…
Turbulence-like 5/3 spectral scaling in contextual representations of language as a complex system
Zhongxin Yang, Chun Bao, Yuanwei Bin +2
Natural language is a complex system that exhibits robust statistical regularities. Here, we represent text as a trajectory in a high-dimensional embedding space generated by trans…
Large Language Model Driven Development of Turbulence Models
Zhongxin Yang, Yuanwei Bin, Yipeng Shi +1
Artificial intelligence (AI) has achieved human-level performance in specialized tasks such as Go, image recognition, and protein folding, raising the prospect of an AI singularity…
Incorporating basic calibrations in existing machine-learned turbulence modeling
Jiaqi J. L. Li, Yuanwei Bin, George P. Huang +1
This work aims to incorporate basic calibrations of Reynolds-averaged Navier-Stokes (RANS) models as part of machine learning (ML) frameworks. The ML frameworks considered are tens…
Constrained re-calibration of Reynolds-averaged Navier-Stokes models
Yuanwei Bin, George Huang, Robert Kunz +1
The constants and functions in Reynolds-averaged Navier Stokes (RANS) turbulence models are coupled. Consequently, modifications of a RANS model often negatively impact its basic c…
Large-eddy simulation of separated flows on unconventionally coarse grids
Yuanwei Bin, George I. Park, Yu Lv +1
We examine and benchmark the emerging idea of applying the large-eddy simulation (LES) formalism to unconventionally coarse grids where RANS would be considered more appropriate at…
A priori screening of data-enabled turbulence models
Peng E S Chen, Yuanwei Bin, Xiang I A Yang +3
Assessing the compliance of a white-box turbulence model with known turbulent knowledge is straightforward. It enables users to screen conventional turbulence models and identify a…