陆新征

职称:教授
电话:010-62795364
邮箱:luxz@tsinghua.edu.cn
通信地址:北京清华大学土木工程系(新土木馆)
邮编:100084

个人主页

www.luxinzheng.net

教育背景

2000.9-2005.1,清华大学土木工程系,博士学位

1996.9-2000.7,清华大学土木工程系,学士学位

工作履历

2012/12-现在,清华大学土木工程系防灾减灾工程研究所,教授

2011/07-2011/09,日本神户大学(Kobe University) 都市安全研究中心, Visiting Associate Professor

2010/10-现在,清华大学土木工程系防灾减灾工程研究所,所长

2008/10-2009/09,美国斯坦福大学(Stanford University) John A. Blume 地震研究中心, Visiting Scholar

2007/12-2012/12,清华大学土木工程系防灾减灾工程研究所,副教授

2005/03-2007/12,清华大学土木工程系防灾减灾工程研究所,讲师

开授课程

研究生课程《钢筋混凝土有限元》

研究生课程《灾害学》

本科生课程《土木工程与防灾减灾》

本科生课程《韧性城市与基础设施》

奖励与荣誉

科研奖励

[1] 2023年,日内瓦发明展主席团特别嘉许金奖(“金+”奖) (1/8)

[2] 2022年,北京市科技进步一等奖 (1/15)

[3] 2022年,香港建造业议会创新奖国际一等奖 (1/5)

[4] 2022年,施普林格-自然出版社“中国新发展奖” (1/2)

[5] 2021年,中国科技期刊卓越行动计划优秀编辑

[6] 2020年,教育部自然科学一等奖 (1/5)

[7] 2019年,腾讯“科学探索奖”

[8] 2018年,茅以升北京青年科技奖

[9] 2018年,国家科技进步一等奖(创新团队,9/14)

[10] 2014-2022年,Elsevier“中国高被引学者(Most Cited Chinese Researchers)-土木和结构工程学科”

[11] 2013年,国家自然科学二等奖 (2/4)


人才奖励

[1] 2020年,教育部“长江学者奖励计划”新冠疫情特设岗位

[2] 2019年,教育部“长江学者奖励计划”(特聘教授)

[3] 2016年,国家“万人计划”科技创新领军人才

[4] 2015年,教育部“长江学者奖励计划”(青年学者)

[5] 2012年,国家自然科学基金优秀青年科学基金

[6] 2011年,霍英东教育基金会第十三届高等院校青年教师基金

[7] 2010年,教育部新世纪优秀人才支持计划


教学奖励

[1] 2021年,“清华大学优质通识课程建设计划”

[2] 2019年,“清华大学精品课程”

[3] 2017年,“清华大学年度教学优秀奖”

[4] 2012年,清华大学教学成果一等奖(2/5)

[5] 2008年,“清华大学青年教师教学优秀奖”

研究领域

结构智能设计、城市综合防灾、结构数值模拟

学术及其他社会兼职

[1] 《工程力学》编委会主编

[2] Journal of Structural Engineering-ASCE, Associate Editor

[3] 中国土木工程学会理事

[4] 中国力学学会理事、结构工程专业委员会副主任委员

[5] 中国地震学会理事

[6] 中国建筑学会建筑结构分会理事

[7] The Editorial Board member for Journal of Earthquake Engineering

[8] The Advisory Editorial Board member of Earthquake Engineering & Structural Dynamics

[9] The Alternate Member of the Board of Directors for the International Society for Computing in Civil and Building Engineering

科研项目

科技部重点研发计划

[1] 国家十四五重点研发计划项目、建筑(群)数字孪生模型推演与虚实交互关键技术研究、2023/12-2026/11

[2] 国家十三五重点研发计划课题、城市地震巨灾情景构建技术、2018/12-2021/12


国家自然科学基金委

[1] 国家自然科学基金重点项目、城市密集建筑群地震灾害链效应与抗灾韧性研究、2023/1-2027/12

[2] 国家自然科学基金-浙江两化融合联合基金重点项目、韧性视角下智慧城市基础设施系统安全与防护基础理论与关键技术,2018/01-2021/12


北京市、住建部等省部级课题

[1] 中华人民共和国住房和城乡建设部科学技术计划项目、基于深度对抗学习的智能生成式建筑结构设计方法研究、2023/1-2025/12

[2] 北京市自然科学基金面上项目、面向“韧性防灾”的地震与连续倒塌综合防御钢框架研究、2018/01-2020/12

代表性学术成果

专著

[1] Lu XZ, Guan H, Earthquake Disaster Simulation of Civil Infrastructures: From Tall Buildings to Urban Areas (second edition), Singapore: Springer, 2021. ISBN 978-981-15-9531-8. DOI: 10.1007/978-981-15-9532-5.

[2] 陆新征, 田源, 许镇, 熊琛, 城市抗震弹塑性分析, 北京: 清华大学出版社, 2021. ISBN 978-7-302-57958-8.

[3] 陆新征, 工程地震灾变模拟:从高层建筑到城市区域 (第2版), 科学出版社, 2020. ISBN 978-7-030-65920-0

[4] 陆新征, 许镇, 黄盛楠, 基于计算机辅助的桥梁倒塌事故分析, 北京: 清华大学出版社,2015. ISBN 978-7-302-38725-1

[5] 陆新征, 李易, 叶列平, 混凝土结构防连续倒塌理论与设计方法研究, 北京: 中国建筑工业出版社,2011. ISBN 978-7-112-13657-5

[6] 陆新征, 何水涛, 黄盛楠, 超高车辆撞击桥梁上部结构研究:破坏机理、设计方法和防护对策,北京: 中国建筑工业出版社,2011. ISBN 978-7-112-13586-8


教材

[1] 陆新征, 蒋庆, 缪志伟, 潘鹏, 建筑抗震弹塑性分析(第二版), 中国建筑工业出版社, 2015.

[2] 任爱珠, 许镇, 纪晓东, 陆新征, 防灾减灾工程与技术, 清华大学出版社, 2014.

[3] 江见鲸, 陆新征, 混凝土结构有限元分析(第二版), 北京: 清华大学出版社, 2013.


学术刊物

[1] Fei YF, Liao WJ, Lu XZ*, Guan H*, Knowledge-enhanced graph neural networks for construction material quantity estimation of reinforced concrete buildings, Computer-Aided Civil and Infrastructure Engineering, 2023, DOI: 10.1111/mice.13094

[2] Fei YF, Liao WJ, Lu XZ*, Taciroglu E, Guan H, Semi-supervised learning method incorporating structural optimization for shear-wall structure design using small and long-tailed datasets, Journal of Building Engineering, 2023, 79: 107873. DOI: 10.1016/j.jobe.2023.107873

[3] Xu YJ, Lu XZ*, Fei YF, Huang YL, Hysteretic behavior simulation based on pyramid neural network: Principle, network architecture, case study and explanation, Advances in Structural Engineering, 2023, 26(13):2359-2374. DOI:10.1177/13694332231184322

[4] Zhao PJ, Fei YF, Huang YL, Feng YT, Liao WJ, Lu XZ*, Design-condition-informed shear wall layout design based on graph neural networks, Advanced Engineering Informatics, 2023, 58: 102190. DOI: 10.1016/j.aei.2023.102190

[5] Jin XL, Liao WJ, Tian Y, Xie LL, Lu XZ*, Numerical simulation and seismic performance analysis of sacrificial-energy dissipation beam-column joint, Engineering Structures, 2023, 296: 116979. DOI: 10.1016/j.engstruct.2023.116979

[6] Liao WJ, Wang XY, Fei YF, Huang YL, Xie LL, Lu XZ*, Base-isolation design of shear wall structures using physics-rule-co-guided self-supervised generative adversarial networks, Earthquake Engineering & Structural Dynamics, 2023, 52(11): 3281-3303. DOI:10.1002/eqe.3862

[7] Tian Y, Huang YL, Qu Z, Fei YF, Lu XZ*, High-performance uniform damping model for response history analysis in OpenSees, Journal of Earthquake Engineering, 2023, 27(11): 3136-3152. DOI: 10.1080/13632469.2022.2124557

[8] Tian Y, Lu XZ*, Huang DR, Wang T, SCI effects under complex terrains: shaking table tests and numerical simulation, Journal of Earthquake Engineering, 2023, 27(5): 1237-1260. DOI: 10.1080/13632469.2022.2074921

[9] Gu DL, Kareem A, Lu XZ*, Cheng QL, A computational framework for the simulation of wind effects on buildings in a cityscape, Journal of Wind Engineering and Industrial Aerodynamics, 2023, 234:105347. DOI: 10.1016/j.jweia.2023.105347

[10] Sun CJ, Gu DL, Lu XZ*, Three-dimensional structural displacement measurement using monocular vision and deep learning based pose estimation, Mechanical Systems and Signal Processing, 2023, 190: 110141. DOI: 10.1016/j.ymssp.2023.110141

[11] Zhao PJ, Liao WJ, Huang YL, Lu XZ*, Intelligent design of shear wall layout based on graph neural networks, Advanced Engineering Informatics, 2023, 55, 101886, DOI: 10.1016/j.aei.2023.101886

[12] Liao WJ, Fei YF, Ghahari F, Zhang WY, Chen PY, Kurtulus A, Yen CH, Cheng QL, Lu XZ*, Taciroglu E, Influence of accelerometer type on uncertainties in recorded ground motions and seismic damage assessment, Bulletin of Earthquake Engineering, 2022, 20: 4419-4439. DOI: 10.1007/s10518-022-01461-5

[13] Xu YJ, Lu XZ*, Fei YF, Huang YL, Iterative self-transfer learning: A general methodology for response time-history prediction based on small dataset, Journal of Computational Design and Engineering, 2022, 9(5): 2089–2102. DOI:10.1093/jcde/qwac098

[14] Zhao PJ, Liao WJ, Huang YL, Lu XZ*, Intelligent beam layout design for frame structure based on graph neural networks, Journal of Building Engineering, 2023, 63, Part A: 105499. DOI: 10.1016/j.jobe.2022.105499

[15] Zhao PJ, Liao WJ, Huang YL, Lu XZ*, Intelligent design of shear wall layout based on attention-enhanced generative adversarial network, Engineering Structures, 2023, 274, 115170. DOI: 10.1016/j.engstruct.2022.115170

[16] Fei YF, Liao WJ, Huang YL, Lu XZ*, Knowledge-enhanced generative adversarial networks for schematic design of framed tube structures, Automation in Construction, 2022, 144: 104619. DOI: 10.1016/j.autcon.2022.104619

[17] Sun CJ, Gu DL, Zhang Y, Lu XZ*, Vision-based displacement measurement enhanced by super-resolution using generative adversarial networks, Structural Control and Health Monitoring, 2022, 29(10): e3048. DOI: 10.1002/stc.3048

[18] Liao WJ, Huang YL, Zheng Z, Lu XZ*, Intelligent generative structural design method for shear-wall building based on “fused-text-image-to-image” generative adversarial networks, Expert Systems with Applications, 2022, 118530, DOI: 10.1016/j.eswa.2022.118530

[19] Tian Y, Sun CJ, Lu XZ*, Huang YL, Quantitative analysis of site-city interaction effects on regional seismic damage of buildings. Journal of Earthquake Engineering. 2022, 26(8): 4365-4385. DOI: 10.1080/13632469.2020.1828199

[20] Xu YJ, Lu XZ*, Tian Y, Huang YL, Real-Time seismic damage prediction and comparison of various ground motion intensity measures based on machine learning. Journal of Earthquake Engineering. 2022, 26(8): 4259-4279. DOI: 10.1080/13632469.2020.1826371

[21] Zhao PJ, Liao WJ, Xue HJ, Lu XZ*, Intelligent design method for beam and slab of shear wall structure based on deep learning, Journal of Building Engineering, 2022, 57: 104838. DOI: 10.1016/j.jobe.2022.104838

[22] Xu YJ, Fei YF, Huang YL, Tian Y, Lu XZ*, Advanced corrective training strategy for surrogating complex hysteretic behavior, Structures, 2022, 41: 1792-1803, DOI: 10.1016/j.istruc.2022.05.097

[23] Lu XZ*, Liao WJ, Zhang Y, Huang YL, Intelligent structural design of shear wall residence using physics-enhanced generative adversarial networks, Earthquake Engineering & Structural Dynamics, 2022, 51(7): 1657-1676. DOI: 10.1002/eqe.3632

[24] Gu DL, Chen W, Lu XZ*, Automated assessment of wind damage to windows of buildings at a city scale based on oblique photography, deep learning and CFD, Journal of Building Engineering, 2022, 52: 104355. DOI: 10.1016/j.jobe.2022.104355

[25] Xu YJ, Lu XZ*, Cetiner B, Taciroglu E, Real-time regional seismic damage assessment framework based on long short-term memory neural network. Computer-Aided Civil and Infrastructure Engineering, 2021. 36(4): p. 504-521.

[26] Xiong C, Li QS, Lu XZ*, Automated regional seismic damage assessment of buildings using an unmanned aerial vehicle and a convolutional neural network. Automation in Construction, 2020. 109.

[27] Lu XZ*, Lin KQ, Li CF, Li Y, New analytical calculation models for compressive arch action in reinforced concrete structures. Engineering Structures, 2018. 168: p. 721-735.

[28] Lu XZ, Lin KQ, Li Y, Guan H, Ren PQ, Zhou YL, Experimental investigation of RC beam-slab substructures against progressive collapse subject to an edge-column-removal scenario. Engineering Structures, 2017. 149: p. 91-103.

[29] Lu XZ*, Xie LL, Guan H, Huang YL, Lu X, A shear wall element for nonlinear seismic analysis of super-tall buildings using OpenSees. Finite Elements in Analysis and Design, 2015. 98: p. 14-25.

[30] Lu XZ*, Han B, Hori M, Xiong C, Xu Z, A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing. Advances in Engineering Software, 2014, 70: 90-103. DOI: 10.1016/j.advengsoft.2014.01.010

[31] Xu Z, Lu XZ*, Guan H, Chen C, Ren AZ, A virtual reality based fire training simulator with smoke hazard assessment capacity. Advances in Engineering Software, 2014. 68: p. 1-8.

[32] Xu LJ, Lu XZ*, Guan H, Zhang YS. Finite-element and simplified models for collision simulation between over-height trucks and bridge superstructures. Journal of Bridge Engineering, ASCE. 2013, 18(11): 1140–1151. DOI:10.1061/(ASCE)BE.1943-5592.0000472

[33] Lu X, Lu XZ*, Guan H, Ye LP, Collapse simulation of reinforced concrete high-rise building induced by extreme earthquakes. Earthquake Engineering & Structural Dynamics, 2013, 42(5): 705-723. DOI:10.1002/eqe.2240

[34] Xu Z, Lu XZ*, Guan H, Lu X, Ren AZ, Progressive-collapse simulation and critical region identification of a stone arch bridge. Journal of Performance of Constructed Facilities-ASCE, 2013, 27(1): 43–52. DOI:10.1061/(ASCE)CF.1943-5509.0000329.

[35] Lu XZ*, Lu X, Guan H, Zhang WK, Ye LP, Earthquake-induced collapse simulation of a super-tall mega-braced frame-core tube building. Journal of Constructional Steel Research, 2013. 82: p. 59-71.

[36] Li Y, Lu XZ*, Guan H, Ye LP, An improved tie force method for progressive collapse resistance design of reinforced concrete frame structures. Engineering Structures, 2011. 33(10): p. 2931-2942.

[37] Lu X, Lu XZ*, Zhang WK, Ye LP, Collapse simulation of a super high-rise building subjected to extremely strong earthquakes. Science China-Technological Sciences, 2011. 54(10): p. 2549-2560.

[38] Lu XZ, Teng JG, Ye LP, Jiang JJ, Bond-slip models for FRP sheets/plates bonded to concrete. Engineering Structures, 2005. 27(6): p. 920-937.

[39] Lu XZ, Ye LP, Teng JG, Jiang JJ, Meso-scale finite element model for FRP sheets/plates bonded to concrete. Engineering Structures, 2005. 27(4): p. 564-575.