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讲师
宋明明
发布时间：2020-07-17        浏览次数：5228

职称：特聘研究员、助理教授、硕导

电子邮件：mingmingsong@tongji.edu.cn

研究领域：结构健康监测、数字孪生、深度学习、混合驱动建模、贝叶斯推理

所属研究室：桥梁健康监测与振动控制研究室





个人简介

宋明明，浙江大学本科，同济大学硕士，美国Tufts University博士。2019年8月博士毕业后，留校先后任职博后和研究助理教授。2022年入职同济大学土木工程学院桥梁系，加入长江学者孙利民教授的桥梁健康监测与振动控制研究室，任特聘研究员、助理教授、硕导。研究方向为结构健康监测、数字孪生、贝叶斯推理、深度学习、混合驱动建模等。研究工作发表16篇SCI检索论文，包含6篇Mechanical Systems and Signal Processing期刊论文。主持国家自然科学基金青年项目1项，参与面上项目2项，参与多项美国国家科学基金（NSF）等项目， 2021年获得上海市领军人才（海外）青年人才项目资助。任土木工程防灾减灾全国重点实验室固定成员、美国土木工程师协会结构健康监测与控制委员会委员、国际桥梁与结构工程协会中国团组秘书处秘书、中国振动工程学会结构抗振控制与健康监测专业委员会委员等。担任Buildings期刊客座编辑，是Mechanical Systems and Signal Processing，Structural Health Monitoring，Journal of Sound and Vibration，Engineering Structures，Soil Dynamics and Earthquake Engineering，Journal of Bridge Engineering等多本SCI期刊审稿人。

       每年招收硕士生1-2名，欢迎推免生、考研生报名！

 

主要学历

  • 2014.9 – 2019.8美国塔夫茨大学 （Tufts University），结构工程，博士学位

  • 2010.9 – 2013.5同济大学，桥梁工程，硕士学位

  • 2006.9 – 2010.7浙江大学，土木工程，学士学位

 

任职经历

  • 2022.3 – 至今同济大学，桥梁工程系，助理教授

  • 2020.8 – 2022.2美国塔夫茨大学，土木与环境工程系，研究助理教授

  • 2019.9 – 2020.7美国塔夫茨大学，土木与环境工程系，博后


研究项目

  1. 国家自然科学基金青年项目，基于层次贝叶斯理论和人工智能的桥梁结构混合数字孪生方法（编号52208199），2023.1 - 2025.12，主持

  2. 上海市海外高层次人才项目，2022.3 – 2024.12，主持

  3. 国家自然科学基金面上项目，基于混合监测的桥梁数字化建模（编号52378187），2024.1 - 2027.12，参与

  4. 国家自然科学基金面上项目，基于多源残错数据的桥梁网级评估方法（编号52278313），2023.1 - 2026.12，参与

  5. National Offshore Wind Research & Development Consortium, Physics Based Digital Twins for Optimal Asset Management (154719), 2021.1 - 2022.12, 80万美元, 参与

  6. National Science Foundation (NSF), An Adaptive System Identification Approach Using Mobile Sensors (1903972), 2019.6 - 2022.5, 52万美元, 参与

  7. Bureau of Safety and Environmental Enforcement (BSEE), The Block Island Structural Monitoring Joint Project (140E0119C0003), 2020.5 - 2021.12, 60万美元, 参与

  8. United States Geological Survey (USGS), A Hierarchical Bayes Inversion Approach for Site Characterization Using Surface Wave Measurements (G18AP00034), 2018.6 - 2020.5, 8万美元, 参与

  9. National Science Foundation (NSF), CAREER: Probabilistic Nonlinear Structural Identification for Health Monitoring of Civil Structures (1254338), 2013.6 - 2019.5, 40万美元, 参与


荣誉奖励

  • 获2021年上海市海外高层次人才项目资助

  • 塔夫茨大学2019年度Littleton奖

  • 塔夫茨大学2016年度Kentaro Tsutsum奖学金


社会服务

  1. 土木工程防灾减灾全国重点实验室固定成员

  2. 美国土木工程师协会 结构健康监测与控制委员会委员ASCE EMI Structural Health Monitoring and Control (SHMC) technical committee

  3. 国际桥梁与结构工程协会（IABSE）中国团组秘书处秘书

  4. 中国振动工程学会结构抗振控制与健康监测专业委员会委员 Chinese Society for Vibration Engineering

  5. 2022年国际桥梁及结构工程协会（IABSE）大会（南京）组织委员

  6. 第三届IABSE东亚青年论坛中国团组秘书

  7. 担任Buildings期刊客座编辑

  8. 担任以下期刊审稿人：
    Mechanical Systems and Signal Processing
    Structural Health Monitoring
    Journal of Sound and Vibration
    Engineering Structures
    Structural Control and Health Monitoring
    Soil Dynamics and Earthquake Engineering
    Journal of Bridge Engineering

 

期刊论文

  1. Song M, Mehr NP, Moaveni B, Hines E, Ebrahimian H, Bajric A. One year monitoring of an offshore wind turbine: Variability of modal parameters to ambient and operational conditions. Engineering Structures. 2023 Dec 15;297:117022.

  2. Partovi-Mehr N, Branlard E, Song M, Moaveni B, Hines EM, Robertson A. Sensitivity Analysis of Modal Parameters of a Jacket Offshore Wind Turbine to Operational Conditions. Journal of Marine Science and Engineering. 2023 Jul 30;11(8):1524.

  3. Song M, Moaveni B, Ebrahimian H, Hines E, Bajric A. Joint parameter-input estimation for digital twinning of the Block Island wind turbine using output-only measurements. Mechanical Systems and Signal Processing. 2023 Sep 1;198:110425.

  4. Hines EM, Baxter CD, Ciochetto D, Song M, Sparrevik P, Meland HJ, Strout JM, Bradshaw A, Hu SL, Basurto JR, Moaveni B. Structural instrumentation and monitoring of the Block Island Offshore Wind Farm. Renewable Energy. 2023 Jan 1;202:1032-45.

  5. Song M, Christensen S, Moaveni B, Brandt A, Hines E. Joint parameter-input estimation for virtual sensing on an offshore platform using output-only measurements. Mechanical Systems and Signal Processing. 2022 May 1;170:108814.

  6. Mehrjoo A, Song M, Moaveni B, Papadimitriou C, Hines E. Optimal sensor placement for parameter estimation and virtual sensing of strains on an offshore wind turbine considering sensor installation cost. Mechanical Systems and Signal Processing. 2022 Apr 15;169:108787.

  7. Song M, Renson L, Moaveni B, Kerschen G. Bayesian model updating and class selection of a wing-engine structure with nonlinear connections using nonlinear normal modes. Mechanical Systems and Signal Processing. 2022 Feb 15;165:108337.

  8. Zhang Y, Lian J, Zhang G, Liu Y, Song M*, Li S. Ground vibration characteristics induced by flood discharge of a high dam: An experimental investigation. Journal of Renewable and Sustainable Energy. 2021 Jan 4;13(1):014502.

  9. Liu P, Huang S, Song M, Yang W. Bayesian Model Updating of a Twin-Tower Masonry Structure through Subset Simulation Optimization Using Ambient Vibration Data. Journal of Civil Structural Health Monitoring. 2020 Oct 23:1-20.

  10. Song M, Behmanesh I, Moaveni B, Papadimitriou C. Accounting for Modeling Errors and Inherent Structural Variability through a Hierarchical Bayesian Model Updating Approach: An Overview. Sensors. 2020 Jan;20(14):3874.

  11. Song M, Astroza R, Ebrahimian H, Moaveni B, Papadimitriou C. Adaptive Kalman filters for nonlinear finite element model updating. Mechanical Systems and Signal Processing. 2020 Sep 1;143:106837.

  12. Yousefianmoghadam S, Song M, Mohammadi M, Packard B, Stavridis A, Moaveni B, Wood RL, Packard B. Nonlinear dynamic tests of a reinforced concrete frame building at different damage levels. Earthquake Engineering & Structural Dynamics. 2020 May 11.

  13. Song M, Behmanesh I, Moaveni B, Papadimitriou C. Modeling error Estimation and response prediction of a 10-Story building model through a hierarchical Bayesian model updating framework. Frontiers in Built Environment. 2019;5:7.

  14. Song M, Moaveni B, Papadimitriou C, Stavridis A. Accounting for amplitude of excitation in model updating through a hierarchical Bayesian approach: Application to a two-story reinforced concrete building. Mechanical Systems and Signal Processing. 2019 May 15;123:68-83.

  15. Song M, Renson L, Noël JP, et al. Bayesian model updating of nonlinear systems using nonlinear normal modes. Structural Control and Health Monitoring. 2018 Dec;25(12):e2258.   

  16. Song M, Yousefianmoghadam S, Mohammadi ME, Moaveni B, Stavridis A, Wood RL. An application of finite element model updating for damage assessment of a two-story reinforced concrete building and comparison with lidar. Structural Health Monitoring. 2018 Sep;17(5):1129-50.

 

会议论文

  1. Akhlaghi MM, Song M, Pontrelli M, Moaveni B, Baise LG. Site Characterization Through Hierarchical Bayesian Model Updating Using Dispersion and H/V Data. In Model Validation and Uncertainty Quantification, Volume 3 2020 (pp. 333-335). Springer, Cham.

  2. Song, M., Astroza, R., Ebrahimian, H., Moaveni, B., Papadimitriou, C. (2020). Nonlinear Model Updating Using Recursive and Batch Bayesian Methods. Proc. of 38th International Modal Analysis Conference (IMAC-XXXVIII), Houston, Texas, USA.

  3. Song, M., Behmanesh, I., Moaveni, B., Papadimitriou, C. (2018). Hierarchical Bayesian calibration and response prediction of a 10-Story building model. Proc. of 36th International Modal Analysis Conference (IMAC-XXXVI), Orlando, Florida, USA.

  4. Yousefianmoghadam S, Song M, Stavridis A, Moaveni B. System identification of a two-story infilled RC building in different damage states. In Improving the Seismic Performance of Existing Buildings and Other Structures 2015 (pp. 607-618).

  5. Song M, Shen Z, Tang P. Data quality-oriented 3D laser scan planning. In Construction Research Congress 2014: Construction in a Global Network 2014 (pp. 984-993).            

 

研究网站

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