Bin Xu
Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates
Academic Titles:Director and Founder, Key Laboratory for Intelligent Infrastructure and Monitoring of Fujian Province
Gender:Male
Date of Birth:1972-03-04
Alma Mater:Ibaraki University
Education Level:博士研究生
Degree:Doctoral Degree in Engineering
Date of Employment:2016-08-01
School/Department:College of Civil Engineering, Huaqiao University
Business Address:College of Civil Engineering, Huaqiao University, Jimei Avenue 668, Xiamen, China
E-Mail:
Status:在岗
Other Post:Director and Founder, International Research Center for Safety and Sustainability of Civil Engineering
Administrative Position:Director, Key Laboratory
Discipline:Civil Engineering
Academic Honor:
2008 教育部新世纪优秀人才支持计划
2016 桐江学者
2017 福建省“闽江学者奖励计划”特聘教授
2017 厦门市双百计划
2018 福建省引进高层次人才
Honors and Titles:
2024-09-10 华侨大学师德模范
福建省引进高层次人才（海外B类）
Excellent Teacher, Xiamen City Government, China，2019
Best Paper Award, The 4th International Conference on Structural Health Monitoring and Integrity Management, Hangzhou, China，2018
The Second Level Technical Invention Award, Fujian Province Government, China，2018
Overseas High-level Innovative Talents Award, Xiamen City Government, China，2017
Minjiang Scholar Professor Award, Fujian Provincial Government, China，2017
Tongjiang Scholar Professor Award, Quanzhou City Government, China，2016
The First Level Best Paper Award, The 15th Best Paper Award in Natural Science, Hunan Province Government, China，2014
Ethics Role Model Award, Hunan University, China，2014
Hits:
Journal:DEStech Transactions on Environment, Energy and Earth Science
Abstract:It is hard to develop wind farms in mountain areas when traditional conical steel towers are used. Prestressed concrete-steel hybrid (PCSH) tower has advantages and is an alternative for wind turbine due to weak requirement in transportation. In this paper, an optimization approach for PCSH wind turbine tower using particle swarm optimization (PSO) approach is proposed and employed to find an optimal design for a 2MW wind turbine with a height of 77.5m. The physical dimensions of the PCSH tower are adopted as variables and the total cost is treated as the optimal object function. Compared with that of the original design using traditional conical steel towers, the cost of the PCSH tower is reduced significantly by the use of the PSO algorithm.
Indexed by:Essay collection
Document Type:J
Volume:331
Translation or Not:no
Date of Publication:2019-06-14
First Author:李泽宇
Co-author:陈洪兵
Correspondence Author:许斌
