卢泓方，男，1991年生，江苏宜兴人，博士，硕士生导师。2021年3月入职东南大学土木工程学院，从事管道非开挖修复及安全评估研究。在Nature子刊、ASCE会刊等期刊上发表SCI论文40余篇，Google Scholar被引3600余次（H指数为26），1篇论文入选ESI热点论文，5篇论文入选ESI高被引论文，2篇论文分别入选Journal of Pipeline Systems Engineering and Practice-ASCE期刊Editor’s Choice论文和Most Cited论文。出版英文专著《Pipeline Inspection and Health Monitoring Technology》并作为美国普渡大学的研究生教材。主持江苏省自然科学基金项目1项、重点实验室开放基金项目3项、企业委托横向3项。参与国家重点研发计划项目1项（项目骨干）、江苏省前沿引领技术基础研究重大项目1项（项目骨干）。担任Journal of Pipeline Science and Engineering期刊编委；Tunnelling and Underground Space Technology期刊客座编辑；Journal of Dynamic Disasters期刊副主编；中国石油学会石油储运专业委员会青年工作部委员；《天然气工业》和《油气储运》第一、二届青年编委；第十五届石油天然气管道安全(氢能储运)国际会议大会执行主席；江苏省复合材料学会青年工作委员会委员。连续入选全球前2%顶尖科学家“年度科学影响力排行榜”（2023年榜单全球77807名、中国能源领域378名、环境工程领域74名），获得2021年“科创江苏”创新创业大赛新材料领域一等奖，获得Journal of Zhejiang University-SCIENCE A年度最佳论文奖。

教育经历

2017.3-2020.5  美国路易斯安纳理工大学，土木工程，哲学博士（国家公派），导师：Dr. Tom Iseley

2013.9-2016.6  西南石油大学，油气储运工程（教育部A+学科），硕士

2009.9-2013.6  西南石油大学，油气储运工程（教育部A+学科），学士

Ÿ   Journal of Pipeline Science and Engineering编委

Ÿ   Tunnelling and Underground Space Technology客座编辑

Ÿ   Journal of Dynamic Disasters执行主编

Ÿ   Urban Lifeline客座编辑/青年编委

Ÿ   《天然气工业》和《油气储运》第一、二届青年编委

Ÿ   中国石油学会石油储运专业委员会青年工作部委员

Ÿ   国际地下资产管理研究所（BAMI-I）油气委员会主席

Ÿ   国际青年管道协会（YPI）中国区主席（2023年度）

Ÿ   江苏省复合材料学会青年工作委员会委员

Ÿ   第十五届石油天然气管道安全(氢能储运)国际会议大会执行主席

• 《房屋建筑学》（本科生课）

• 《专业写作（土木）》（本科生全英文课）

科研项目

Ÿ   江苏省自然科学基金青年基金项目，主持

Ÿ   重大基础设施智慧防灾“一带一路”联合实验室开放课题，主持

Ÿ   灾变力学与工程防灾四川省重点实验室开放课题，主持

Ÿ   城市基础设施智能化浙江省工程研究中心开放课题，主持

Ÿ   四川省特种设备检验研究院项目，主持

Ÿ   中海石油（中国）有限公司北京研究中心项目，主持

Ÿ   国家管网集团川气东送天然气管道有限公司项目，主持

Ÿ   核工业北京化工冶金研究院项目，主持

Ÿ   国家重点研发计划项目，项目骨干

Ÿ   江苏省前沿引领技术基础研究专项，项目骨干

科学技术成果鉴定

Ÿ   油气储运设施智能检测与预警系统关键技术研究及应用，第二单位，鉴定机构：中国特种设备检验协会

参编标准

GB/T 43852-2024 《冷热水用钢增强塑料复合压力管》（2024年10月1日实施）

代表性论文

1.       Peng, H., Lu, H.*, Xu, Z. D., Xi, D., & Qin, G. (2024). Failure mechanism of carbon dioxide transport infrastructure: A comprehensive review. International Journal of Greenhouse Gas Control, 135, 104144. (JCR Q2)

2.       Xi, D., Lu, H.*, Shi, K., Ni, H., & Iseley, T. (2024). Dual-Component Polyurethane Spray Technology for Repairing Concrete Pipes: A Case Study. Journal of Pipeline Systems Engineering and Practice-ASCE. DOI: 10.1061/JPSEA2/PSENG-1624 (ASCE期刊)

3.       Peng, H., Lu, H.*, Xu, Z. D., Xi, D., & Qin, G. (2024). Failure mechanism of carbon dioxide transport infrastructure: A comprehensive review. International Journal of Greenhouse Gas Control, 135, 104144. (JCR Q2)

4.       Xi, D., Lu, H.*, Zou, X., Fu, Y., Ni, H., & Li, B. (2024). Development of trenchless rehabilitation for underground pipelines from an academic perspective. Tunnelling and Underground Space Technology, 144, 105515. (JCR Q1)

5.       Lu, H., Xu, Z. D., Song, K., Frank Cheng, Y., Dong, S., Fang, H., Peng, H., Fu, Y., Xi, D., Han, Z., Jiang, X., Dong, Y., Gai, P. & Shan, Y. (2023). Greenhouse gas emissions from US crude oil pipeline accidents: 1968 to 2020. Scientific Data, 10(1), 563. (JCR Q1)

6.       Lu, H., Xu, Z. D., Cheng, Y. F., Peng, H., Xi, D., Jiang, X., ... & Shan, Y. (2023). An inventory of greenhouse gas emissions due to natural gas pipeline incidents in the United States and Canada from 1980s to 2021. Scientific Data, 10(1), 282. (JCR Q1)

7.       Xi, D., Lu, H.*, Fu, Y., Dong, S., Jiang, X., & Matthews, J. (2023). Carbon dioxide pipelines: A statistical analysis of historical accidents. Journal of Loss Prevention in the Process Industries, 105129. (JCR Q2)

8.       Lu, H., Xu, Z. D., Zang, X., Xi, D., Iseley, T., Matthews, J. C., & Wang, N. (2023). Leveraging Machine Learning for Pipeline Condition Assessment. Journal of Pipeline Systems Engineering and Practice-ASCE, 14(3), 04023024. (ASCE期刊, Editor’s Choice Award)

9.       Lu, H., Peng, H., Xu, Z., Qin, G., Azimi, M., Matthews, J. C., & Cao, L. (2023). Theory and machine learning modeling for burst pressure estimation of pipeline with multipoint corrosion. Journal of Pipeline Systems Engineering and Practice-ASCE, 14(3), 04023022. (ASCE期刊)

10.    Lu, H., Jiang, X., Xu, Z., Wang, N., & Iseley, D. T. (2023). Numerical study on mechanical properties of pipeline installed via horizontal directional drilling under static and dynamic traffic loads. Journal of Tunnelling and Underground Space Technology, 136, 105077. (JCR Q1)

11.    Lu, H., Jiang, X., Xu, Z., Ni, H., & Fu, L. (2023). Mechanical behavior of high-pressure pipeline installed through horizontal directional drilling under seismic loads. Journal of Tunnelling and Underground Space Technology, 136, 105073. (JCR Q1)

12.    Lu, H., Xi, D., & Qin, G. (2023). Environmental risk of oil pipeline accidents. Science of The Total Environment, 874, 162386. (JCR Q1)

13.    Lu, H., Peng, H., Xu, Z. D., Matthews, J. C., Wang, N., & Iseley, T. (2022). A Feature Selection–Based Intelligent Framework for Predicting Maximum Depth of Corroded Pipeline Defects. Journal of Performance of Constructed Facilities-ASCE, 36(5), 04022044. (ASCE期刊)

14.    Lu, H., Xi, D., Ma, X., Zheng, S., Huang, C., & Wei, N. (2022). Hybrid machine learning models for predicting short-term wave energy flux. Ocean Engineering, 264, 112258. (JCR Q1)

15.    Lu, H., Ma, X., & Ma, M. (2021). Impacts of the COVID-19 pandemic on the energy sector. Journal of Zhejiang University-SCIENCE A, 22(12), 941. (JCR Q2, Best Paper Award)

16.    Lu, H., Xu, Z. D., Azimi, M., Fu, L., & Wang, Y. (2022). An Effective Data-Driven Model for Predicting Energy Consumption of Long-Distance Oil Pipelines. Journal of Pipeline Systems Engineering and Practice-ASCE, 13(2), 04022005. (ASCE期刊)

17.    Lu, H., Xu, Z. D., Iseley, T., & Matthews, J. C. (2021). Novel data-driven framework for predicting residual strength of corroded pipelines. Journal of Pipeline Systems Engineering and Practice-ASCE, 12(4), 04021045. (ASCE期刊, Most Cited Paper)

18.    Lu, H., Iseley, T., Matthews, J., & Liao, W. (2021). Hybrid machine learning for pullback force forecasting during horizontal directional drilling. Automation in Construction, 129, 103810. (JCR Q1)

19.    Lu, H., Iseley, T., Matthews, J., Liao, W., & Azimi, M. (2021). An ensemble model based on relevance vector machine and multi-objective salp swarm algorithm for predicting burst pressure of corroded pipelines. Journal of Petroleum Science and Engineering, 203, 108585. (JCR Q1)

20.    Lu, H., Behbahani, S., Ma, X., & Iseley, T. (2021). A multi-objective optimizer-based model for predicting composite material properties. Construction and Building Materials, 284, 122746. (JCR Q1)

21.    Lu, H., Matthews, J., Azimi, M., Iseley, T. (2020). A Near Real-time HDD Pullback Force Prediction Model Based on Improved Radial Basis Function Neural Networks. Journal of Pipeline Systems Engineering and Practice-ASCE, 11(4), 04020042. (ASCE期刊)

22.    Lu, H., Iseley, T., Behbahani, S., & Fu, L. (2020). Leakage detection techniques for oil and gas pipelines: State-of-the-art. Tunnelling and Underground Space Technology, 98, 103249. (JCR Q1, Most Cited Paper)

23.    Lu, H., Wu, X., Ni, H., Yan, X., Azimi, M., Niu, Y. (2020). Stress analysis of urban gas pipeline repaired by inserted hose lining method. Composites Part B Engineering, 183, 107657. (JCR Q1)

24.    Lu, H., Behbahani, S., Azimi, M., Matthews, J. C., Han, S., & Iseley, T. (2020). Trenchless Construction Technologies for Oil and Gas Pipelines: State-of-the-Art Review. Journal of Construction Engineering and Management-ASCE, 146(6), 03120001. (JCR Q1)

25.    Lu, H., Cheng, F., Ma, X., & Hu, G. (2020). Short-term prediction of building energy consumption employing an improved extreme gradient boosting model: A case study of an intake tower. Energy, 203, 117756. (JCR Q1)

26.    Lu, H., Guo, L., Azimi, M., & Huang, K. (2019). Oil and Gas 4.0 era: A systematic review and outlook. Computers in Industry, 111, 68-90. (JCR Q1)

27.    Lu, H., Huang, K., Fu, L., Zhang, Z., Wu, S., Lyu, Y., & Zhang, X. (2018). Study on leakage and ventilation scheme of gas pipeline in tunnel. Journal of Natural Gas Science and Engineering, 53, 347-358. (JCR Q1)

28.    Lu, H., Wu, X. N., Iseley, T., Matthews, J. & Peng, S. B. (2018). Trenchless installation, rehabilitation and replacement technologies for natural gas pipelines abroad. Natural Gas Industry, 38(3), 110-120. (EI、卓越行动计划期刊)

29.    Lu, H., Wu, X. N., Iseley, T., Matthews, J. & Peng, S. B. (2018). The status quo of natural gas line pipe inspection technologies abroad and its implications for China. Natural Gas Industry, 38(2), 103-111. (EI、卓越行动计划期刊)

30.    Shang, B., Li, C., & Lu, H*. (2017). Stress analysis of suspended gas pipeline segment. Journal of Pipeline Systems Engineering and Practice-ASCE, 8(3), 04017003. (ASCE期刊)

31.    Lu, H., Huang, K., & Wu, S. (2016). Vibration and stress analyses of positive displacement pump pipeline systems in oil transportation stations. Journal of Pipeline Systems Engineering and Practice-ASCE, 7(1), 05015002. (ASCE期刊)

专著及章节

1.        Lu, H., Xu, Z. D., Iseley, T., Peng, H., & Fu, L. (2023). Pipeline Inspection and Health Monitoring Technology: The Key to Integrity Management. Springer Nature. (专著)

2.     Xi, D., Lu, H.*, Xu, Z. D., Jiang, X., Peng, H., & Fang, H. (2024). Prevention of natural gas pipeline cracking. Advances in Natural Gas: Formation, Processing, and Applications. Volume 6: Natural Gas Transportation and Storage, 293-313. (章节)