Turbulence & Drag Reduction湍流与减阻
Resolving near-wall turbulence over riblets and translating flow physics into practical drag-reduction strategies.
解析微肋条表面的近壁湍流机理，并将流动物理转化为可应用的减阻策略。
- DNS / LES
- Riblets
- Wall-bounded flows
Fluid mechanics · Flow control · Data-driven modeling 流体力学 · 流动控制 · 数据驱动建模
Yue Zhang张悦
Research Assistant at City University of Hong Kong 香港城市大学研究助理
I investigate how turbulence can be understood, predicted, and controlled—from drag-reducing surfaces to wind flow in the built environment—using high-fidelity simulation and physics-informed, data-driven models.
我的研究聚焦于湍流的机理认知、快速预测与有效控制，涵盖减阻表面、建筑环境风场，以及高保真数值模拟与物理信息数据驱动模型。
10Publications篇学术成果
PhDFluid Mechanics流体力学
CFD + MLResearch toolkit交叉研究方法
Currently at CityUHK
Department of Architecture and Civil Engineering
现任职于香港城市大学
建筑学及土木工程学系
01
Research agenda研究方向
Understanding flow.
Designing better environments.理解流动机理，
创造更优环境。
Urban & Building Aerodynamics城市与建筑空气动力学
Quantifying how façade geometry reshapes street-canyon ventilation, turbulence, and pedestrian-level wind environments.
量化建筑立面几何对街谷通风、湍流结构及行人高度风环境的影响。
- Street canyons
- Façade design
- Built environment
Data-Driven Flow Modeling数据驱动流动建模
Combining reduced-order models, surrogate modeling, and machine learning for fast, physically meaningful prediction.
融合降阶模型、代理模型与机器学习，实现快速且具有物理意义的流场预测。
- POD–Kriging
- Surrogate models
- Physics-informed ML
02
Selected work代表性工作
From flow physics
to predictive tools.从流动物理
到预测工具。
POD–Kriging surrogate modeling for urban canyon wind flow
A rapid surrogate framework connecting façade-rib geometry to the complete urban-canyon flow field.
建立建筑立面肋条几何与完整街谷流场之间的快速代理预测框架。
Façade protruding ribs and turbulent flow in street canyons
Large-eddy simulations reveal how façade details alter mean flow, turbulence statistics, and canyon-scale vortices.
通过大涡模拟揭示建筑立面细节对平均流、湍流统计量及街谷尺度涡结构的影响。
Machine-learning-enhanced pressure-field prediction for airfoils
A compressive-sensing framework for reconstructing surface pressure fields and predicting lift from sparse observations.
构建机器学习增强的压缩感知框架，以稀疏观测重建翼型表面压力场并预测升力。
Drag degradation in channel flow over trapezoidal riblets
Direct numerical simulations clarify how oversized riblets reorganize near-wall turbulence and lose drag-reduction performance.
利用直接数值模拟阐明过大微肋条如何重组近壁湍流并导致减阻性能退化。
03
Publications学术成果
Full publication list完整论文列表
-
2026
Yue Zhang, Xing Zheng*. Influence of geometric parameters of façade protruding ribs on turbulent flow statistics in street canyons: A large-eddy simulation study.
Building and Environment, 287, 113845.
-
2026
Yue Zhang, Xing Zheng*. POD–Kriging surrogate modeling for rapid prediction of the impact of façade protruding rib geometries on urban canyon wind flow.
Building and Environment, 292, 114198.
-
2025
Yue Zhang, Shaohui Zhang, Fei Jiang, Zhaoqian Wu, Weihua Li. Predicting surface pressure fields and lift coefficients of subsonic airfoils by machine-learning-enhanced compressive sensing framework.
Physics of Fluids, 37, 095103.
-
2026
Yue Zhang, Jinsheng Cai, Wenfeng Li*. A framework of the effective simulation of high-Reynolds-number turbulent flows over ribbed surfaces using a data-driven boundary surrogate model.
AIAA Journal, 64(2), 808–822.
-
2024
Yue Zhang, Jinsheng Cai, Wenfeng Li*. Direct numerical simulations of the drag degradation mechanism in channel flow over trapezoidal riblets.
Aerospace Science and Technology, 144, 108821.
-
2026
Yue Zhang, Fei Jiang, Zhaoqian Wu, Zhi Zhong, Shaohui Zhang, Weihua Li. Direct numerical simulations of streamwise-aligned riblets: Investigations of the blockage ratio.
Physics of Fluids, 38(7), 075184.
-
2022
Yue Zhang, Jinsheng Cai, Wenfeng Li*. Turbulent channel flow with riblets in drag-reducing and drag-increasing regimes.
AIAA AVIATION 2022, AIAA 2022-3851. EI.
-
2019
Yue Zhang*, Chenjiang Guo. An UWB dual-polarized low-profile tight-coupled dipole array.
2019 International Applied Computational Electromagnetics Society Symposium – China. EI.
-
2026
许德辰, 张悦, 钱战森, 等. 飞艇微肋条减阻模化方法研究.
气动研究与试验, 4(1), 33–41.
-
2022
许德辰, 张悦, 刘欣乐, 李文丰. 基于粒子追踪测速的壁面摩擦应力测量.
实验流体力学, 36(2), 131–138.
04
Experience个人经历
Academic journey学术经历
Appointments & education工作与教育
Research Associate研究助理
Department of Architecture and Civil Engineering, City University of Hong Kong香港城市大学，建筑学及土木工程学系
PhD in Fluid Mechanics流体力学博士
School of Aeronautics, Northwestern Polytechnical University
Advisor: Prof. Jinsheng Cai西北工业大学航空学院
导师：蔡晋生教授
MEng in Electromagnetic Field & Microwave Technology电磁场与微波技术硕士
School of Electronics and Information, Northwestern Polytechnical University西北工业大学电子信息学院
Visiting Student访问学生
Novosibirsk State University, Russia俄罗斯新西伯利亚国立大学
BEng in Electromagnetic Field & Microwave Technology电磁场与微波技术学士
School of Electronics and Information, Northwestern Polytechnical University西北工业大学电子信息学院
05
Toolkit研究工具
Methods & software方法与软件
OpenFOAMANSYS FluentPythonMATLABParaViewTecplotPointwiseICEMANSYS HFSSDNSLESMachine Learning
Let’s connect保持联系
Interested in turbulence,
cities, or smarter flow models?期待围绕湍流、城市风环境
与智能流动模型展开交流。
I welcome conversations about research collaboration, academic opportunities, and shared questions in fluid mechanics.
欢迎就科研合作、学术机会及流体力学相关问题与我联系。
yzhan64@cityu.edu.hk ↗