陶俊 - 复旦大学 - 航空航天系

个人简介

教育经历 2009-9至2014-7, 复旦大学, 流体力学, 博士 2005-9至2009-7, 复旦大学, 飞行器设计与工程, 学士工作经历 2020-5至今, 复旦大学, 航空航天系, 青年副研究员 2017-10至2019-10, 加州大学欧文分校, Associate Specialist 2014-6至2017-1, 复旦大学, 博士后

研究领域

主要集中在飞行器设计和空气动力学两方面。参与了国产大型客机C919、CR929和商用航空发动机CJ-1000、CJ-2000的多项国家重大专项的气动设计研制工作，研究方向包括：复杂流动机理、计算空气动力学、飞行器总体设计、飞机/发动机空气动力学优化和设计，飞机/发动机气动噪声计算与降噪设计、基于人工智能的优化设计方法等

近期论文

查看导师新发文章（温馨提示：请注意重名现象，建议点开原文通过作者单位确认）

Jun Tao, Gang Sun. A Novel Optimization Method for Maintaining Aerodynamic Performances in Noise Reduction Design [J]. Aerospace Science and Technology, 2015, 43: 415-422.(SCI Q1区，航空航天Top 2期刊) Jun Tao, Gang Sun. An Artificial Neural Network Approach for Aerodynamic Performance Retention in Airframe Noise Reduction Design of a 3D Swept Wing Model [J]. Chinese Journal of Aeronautics, 2016, 29(5): 1213-1225. (SCI Q1区) Jun Tao, Gang Sun, Jingzhe Si, Zhibo Wang. A Robust Design for a Winglet Based on NURBS-FFD Method and PSO Algorithm [J]. Aerospace Science and Technology, 2017, 70: 568-577. (SCI Q1区，航空航天Top 2期刊) Jun Tao, Gang Sun, Gang Wu, Liqiang Guo, et al. An Innovative Study on Low Surface Energy Micro-nano Coatings with Multilevel Structures for Laminar Flow Design [J]. Chinese Journal of Aeronautics, 2019, 32(3): 577-584. (SCI Q1区) Jun Tao, Gang Sun, Xinyu Wang, Liqiang Guo. Robust Optimization for a Wing at Drag Divergence Mach Number Based on an Improved PSO Algorithm [J]. Aerospace Science and Technology, 2019, 92: 653-667. (SCI Q1区，航空航天Top 2期刊) Jun Tao, Gang Sun. Application of Deep Learning Based Multi-Fidelity Surrogate Model to Robust Aerodynamic Design Optimization [J]. Aerospace Science and Technology, 2019, 92: 722-737. (SCI Q1区，航空航天Top 2期刊) Jun Tao, Gang Sun, Liqiang Guo, Xinyu Wang. Application of a PCA-DBN-based Surrogate Model to Robust Aerodynamic Design Optimization [J]. Chinese Journal of Aeronautics, 2020, 33(6): 1573-1588. (SCI Q1区) Liqiang Guo, Jun Tao*, Cong Wang, Miao Zhang, Gang Sun*. Fuel efficiency optimization of high-aspect-ratio aircraft via variable camber technology considering aeroelasticity [J]. Proceedings of the Institution of Mechanical Engineers Part G-Journal of Aerospace Engineering, 2020. DOI: 10.1177/ 0954410020959964 (SCI检索)