| Prediction and optimization of airfoil aerodynamic performance using deep neural network coupled Bayesian method RL Liu, Y Hua, ZF Zhou, Y Li, WT Wu, N Aubry Physics of Fluids 34 (11), 2022 | 27 | 2022 |
| Surrogate modeling of heat transfers of nanofluids in absorbent tubes with fins based on deep convolutional neural network Y Hua, CH Yu, Q Zhao, MG Li, WT Wu, P Wu International Journal of Heat and Mass Transfer 202, 123736, 2023 | 20 | 2023 |
| Accelerating and improving deep reinforcement learning-based active flow control: Transfer training of policy network YZ Wang, Y Hua, N Aubry, ZH Chen, WT Wu, J Cui Physics of Fluids 34 (7), 2022 | 18 | 2022 |
| Fast optimization of multichip modules using deep learning coupled with Bayesian method ZQ Wang, Y Hua, N Aubry, ZF Zhou, F Feng, WT Wu International Communications in Heat and Mass Transfer 141, 106592, 2023 | 16 | 2023 |
| Physics-informed graph convolutional neural network for modeling fluid flow and heat convection JZ Peng, Y Hua, YB Li, ZH Chen, WT Wu, N Aubry Physics of Fluids 35 (8), 2023 | 13 | 2023 |
| Prediction of internal and external flow with sparse convolution neural network: A computationally effective reduced-order model JZ Peng, N Aubry, Y Hua, ZH Chen, WT Wu, S Chen Physics of Fluids 35 (2), 2023 | 13 | 2023 |
| Closed-loop forced heat convection control using deep reinforcement learning YZ Wang, XJ He, Y Hua, ZH Chen, WT Wu, ZF Zhou International Journal of Heat and Mass Transfer 202, 123655, 2023 | 12 | 2023 |
| Airfoil shape optimization using genetic algorithm coupled deep neural networks MY Wu, XY Yuan, ZH Chen, WT Wu, Y Hua, N Aubry Physics of Fluids 35 (8), 2023 | 10 | 2023 |
| Reduced order modelling of natural convection of nanofluids in horizontal annular pipes based on deep learning XJ He, CH Yu, Q Zhao, JZ Peng, ZH Chen, Y Hua International Communications in Heat and Mass Transfer 138, 106361, 2022 | 10 | 2022 |
| Thermal performance in convection flow of nanofluids using a deep convolutional neural network Y Hua, JZ Peng, ZF Zhou, WT Wu, Y He, M Massoudi Energies 15 (21), 8195, 2022 | 9 | 2022 |
| Active control for the flow around various geometries through deep reinforcement learning YF Mei, C Zheng, Y Hua, Q Zhao, P Wu, WT Wu Fluid Dynamics Research 54 (1), 015510, 2022 | 8 | 2022 |
| Real-time prediction of transarterial drug delivery based on a deep convolutional neural network XY Yuan, Y Hua, N Aubry, M Zhussupbekov, JF Antaki, ZF Zhou, JZ Peng Applied Sciences 12 (20), 10554, 2022 | 6 | 2022 |
| Policy transfer of reinforcement learning-based flow control: From two-to three-dimensional environment XJ He, YZ Wang, Y Hua, ZH Chen, YB Li, WT Wu Physics of Fluids 35 (5), 2023 | 5 | 2023 |
| Estimation of steady-state temperature field in Multichip Modules using deep convolutional neural network Y Hua, ZQ Wang, XY Yuan, YB Li, WT Wu, N Aubry Thermal Science and Engineering Progress 40, 101755, 2023 | 4 | 2023 |
| Thermal performance estimation of nanofluid-filled finned absorber tube using deep convolutional neural network Y Hua, CH Yu, JZ Peng, WT Wu, Y He, ZF Zhou Applied Sciences 12 (21), 10883, 2022 | 4 | 2022 |
| An Enhanced Multi-Sensor Simultaneous Localization and Mapping (SLAM) Framework with Coarse-to-Fine Loop Closure Detection Based on a Tightly Coupled Error State Iterative … C Yu, Z Chao, H Xie, Y Hua, W Wu Robotics 13 (1), 2, 2023 | 1 | 2023 |
| Reconstruction of temperature field in nanofluid-filled annular receiver with fins using deep hybrid transformer-convolutional neural network CH Yu, YB Li, N Aubry, P Wu, WT Wu, Y Hua, ZF Zhou Powder Technology 429, 118960, 2023 | 1 | 2023 |
| Performance analysis of reinforcement learning algorithms on intelligent closed-loop control on fluid flow and convective heat transfer YZ Wang, YB Li, N Aubry, Y Hua, ZF Zhou, ZH Chen, WT Wu Physics of Fluids 35 (7), 2023 | 1 | 2023 |
| Transfer learning of convolutional neural network model for thermal estimation of multichip modules ZQ Wang, Y Hua, HR Xie, ZF Zhou, YB Li, WT Wu Case Studies in Thermal Engineering 59, 104576, 2024 | | 2024 |
| Data and physics-driven modeling for fluid flow with a physics-informed graph convolutional neural network JZ Peng, Y Hua, N Aubry, ZH Chen, M Mei, WT Wu Ocean Engineering 301, 117551, 2024 | | 2024 |
