卢泓方

个人简介
卢泓方（1991-），男，江苏宜兴人。中国科学院人才计划（B类）入选者、宁波市领军人才、宁波市甬江人才工程入选者、江苏省青年科技人才托举工程入选者，美国路易斯安那理工大学博士，硕士生导师。2021-2025年任东南大学副教授，现任中国科学院宁波材料技术与工程研究所/中国科学院大学宁波材料工程学院研究员。主要从事能源储运技术研究，以第一/通讯在Nature、Nature Cities、Nature Sensors、Nexus（Cell Press）、Engineering、Cell Reports Sustainability及领域内的专业期刊发表SCI论文70余篇，Google Scholar被引5800余次（H指数33），1篇论文入选ESI热点论文，7篇论文入选ESI高被引论文。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。主持国家自然科学基金青年基金、国家自然科学基金企业创新发展联合基金集成项目课题、人力资源和社会保障部外国专家个人类项目（S类）、江苏省自然科学基金青年基金、企业委托横向多项。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（任务负责人）。担任中国腐蚀与防护学会缺陷评价与安全专业委员会秘书长；ASCE Journal of Pipeline Systems Engineering and Practice（SCI JCR Q3）、Natural Gas Industry B（ESCI JCR Q1）副主编；Journal of Pipeline Science and Engineering（SCI JCR Q1）等期刊编委；Tunnelling and Underground Space Technology（SCI JCR Q1）、交通运输工程学报（EI）等期刊客座编辑；《天然气工业》（EI）和《油气储运》（中文核心）等期刊青年编委；国家自然科学基金函评专家；中国石油学会石油储运专业委员会青年工作部委员；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。连续四年入选全球前2%顶尖科学家“年度科学影响力排行榜”（2025年榜单全球53598名、中国能源领域340名、环境工程领域60名）。获得2022年泰州市科技创新二等奖、Tunnelling and Underground Space Technology期刊2021年度最佳论文奖、ASCE Editor’s Choice Award（两次）、Journal of Zhejiang University-Science A期刊2022年度最佳论文奖。

教育经历
2017.3-2020.5  美国路易斯安那理工大学，结构工程，博士，导师：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

工作经历
2025.1至今         中国科学院宁波材料技术与工程研究所/中国科学院大学宁波材料工程学院，研究员
2021.1-2025.4    东南大学，副教授，系主任助理
2020.5-2020.12  美国普渡大学，博士后
2017.3-2020.5    美国路易斯安那理工大学，教学助理

人才项目

1. 中国科学院人才项目（B类）
2. 宁波市领军人才
3. 江苏省青年科技人才托举工程
4. 宁波市“甬江人才工程”

学术兼职

1. 中国腐蚀与防护学会缺陷评价与安全专业委员会秘书长
2. ASCE Journal of Pipeline Systems Engineering and Practice（JCR Q3）副主编
3. Natural Gas Industry B（JCR Q1）副主编
4. Journal of Pipeline Science and Engineering（JCR Q1）编委
5. Tunnelling and Underground Space Technology（JCR Q1）客座编辑
6. 交通运输工程学报（EI、CSCD）客座编辑/青年编委
7. Structural Durability & Health Monitoring（EI）客座编辑
8. Journal of Dynamic Disasters编委
9. Net Zero期刊编委
10. Urban Lifeline客座编辑/青年编委
11. Journal of Energy Infrastructure青年编委
12. 《天然气工业》（EI）和《油气储运》（中文核心）第一、二届青年编委
13. Petroleum期刊青年编委
14. 中国石油学会石油储运专业委员会青年工作部委员
15. 国际地下资产管理学会（BAMI-I）油气委员会主席
16. 国际青年管道协会（YPI）中国区主席（2023年度）
17. 国家自然科学基金函评专家
18. 江苏省复合材料学会青年工作委员会委员
19. 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
20. 全国大学生油气储运工程数值仿真大赛优秀方案集编辑委员会委员
21. 浙江省高层次人才协会会员
22. 江苏省市场监管重点实验室（油气管道检验评价与安全保障技术）学术委员会委员

荣誉和奖励

1. 2025年斯坦福全球前2%顶尖科学家“年度科学影响力排行榜”（全球53598名）
2. ASCE Journal of Pipeline Systems Engineering and Practice期刊Editor’s Choice Award（2024年）
3. 第六届“中国特种设备检验协会科学技术奖”三等奖（4/5）（2024年）
4. 国际先进材料协会（IAAM）科学家奖章（Scientist Medal）（2024年）
5. 2024年斯坦福全球前2%顶尖科学家“年度科学影响力排行榜”（全球67983名）
6. 2023年斯坦福全球前2%顶尖科学家“年度科学影响力排行榜”（全球77807名）
7. 2022年斯坦福全球前2%顶尖科学家“年度科学影响力排行榜”（全球162852名）
8. ASCE Journal of Pipeline Systems Engineering and Practice期刊Editor’s Choice Award（2023年）
9. Journal of Zhejiang University-SCIENCE A期刊年度最佳论文奖（2022年）
10. 2022年度泰州市科技创新二等奖（2/7）（2022年）
11. 2021年“科创江苏”创新创业大赛新材料领域一等奖（3/8）（2021年）
12. Tunnelling and Underground Space Technology期刊年度最佳论文奖（2021年）
13. 中国地质学会非开挖技术委员会“青年之星”奖（2020年）

代表性论文（一作及通讯）

1. Lu, H. & Cheng, Y. F.* (2025). Include climate impacts when protecting infrastructure. Nature, 645, 41.
2. Lu, H., Liu, C., Wang, B. & Cheng, Y. F.* (2026). Lagging hydrogen detection standardization threatens energy transition. Nature Sensors, 1, 101-104.
3. Lu, H., Song, K., Shan, Y., & Cheng, Y. F.* (2025). Quantifying greenhouse gas emission risks from natural gas pipeline incidents. Nexus (Cell Press), 2(4), 100097.
4. Lu, H. & Cheng, Y. F.* (2025). Artificial Intelligence in Energy Pipelines: Opportunities and Risks. Engineering. (JCR Q1)
5. Lu, H., Xie, D., & Cheng, Y. F.* (2025). Methane emissions from the oil and gas supply chain: Characteristics and mitigation. Nexus (Cell Press), 2(3), 100087.
6. Lu, H., Xi, D., Guo, T.*, & Cheng, Y. F.* (2025). Environmental impacts of methane emissions from the oil and gas industry. Cell Reports Sustainability, 3, 100587.
7. Lu, H. (2025). Urban gas infrastructure meets hydrogen ambitions. Nature Cities, 2, 773-774.
8. Lu, H. & Cheng, Y. F.* (2025). Detecting urban gas pipeline leaks using a vehicle–canine collaboration strategy. Nature Cities, 2, 281-282.
9. Lu, H., Xi, D., Xiang, Y., Su, Z. & Cheng, Y. F.* (2025). Vehicle-canine collaboration for urban pipeline methane leak detection. Nature Cities, 2, 336-343. (期刊主页横幅展出)
10. Men, J., Lu, H.*, & Cheng, Y. F.* (2025). Continuous Time-dependent System Resilience Evolution Behaviors of Hazardous Energy Systems subjected to Cascading Disaster Chains. Reliability Engineering & System Safety, 267(B), 111918. (JCR Q1)
11. Jiang, X., Lu, H.*, Xia, Z., Shan, Z. W., Xiang, Y., & Cheng, Y. F. (2025). Above-ground natural gas riser leak dispersion and leakage rate prediction based on CFD and BPNN approaches. Process Safety and Environmental Protection, 203(A), 107854. (JCR Q1)
12. Wang, Q., Lu, H.*, Li, F., & Cheng, Y. F. (2025). Advancing LightGBM with data augmentation for predicting the residual strength of corroded pipelines. npj Materials Degradation, 9, 128. (JCR Q1)
13. Zhu, C., Xu, Y., & Lu, H.* (2025). Pipeline Unidirectional Guided Wave Generation Based on a Hybrid Piezoelectric Transducer Ring and Wave-Packet Modification. Journal of Pipeline Science and Engineering, 100416. (JCR Q1)
14. Wang, Q., Lu, H.*, Li, F., & Cheng, Y. F. (2025). Intelligent prediction of residual strength in blended hydrogen–natural gas pipelines with crack-in-dent defects. npj Materials Degradation, 9, 161. (JCR Q1)
15. Xi, D., Lu, H.*, & Cheng, Y. F. (2025). Characteristics of liquefied natural gas facility incidents and associated greenhouse gas emissions: A statistical analysis. Journal of Pipeline Science and Engineering, 100357. (JCR Q1)
16. Peng, H., Xu, Z. D., Lu, H.*, Xia, Z., & Wang, X. (2025). Risk Assessment Framework for Closed Wellbore Sealing Integrity Failure under Corrosion Environment in CO2 Geological Sequestration. Geoenergy Science and Engineering, 254, 214064.
17. Xia, Z., Xu, Z. D., Xie, Z., Peng, H., Zang, X., Liu, X., ... & Lu, H.* (2025). Hazard evolution of different orifice shapes leakage in buried hydrogen-blended natural gas pipelines. Journal of Pipeline Science and Engineering, 100315. (JCR Q1)
18. Shan, Z. W., Li, W. J, Guo, T., Lu, H.*, Chen, W., Su, R.K.L. (2025). Strengthening design method of randomly corroded steel tubes subjected to axial compressive loading. Structures, 79, 109436. (JCR Q1)
19. Wang, Q. & Lu, H.* (2025). Machine learning methods for predicting residual strength in corroded oil and gas steel pipes. npj Materials Degradation, 9, 30. (Nature旗下期刊, JCR Q1)
20. Lu, H., Xi, D. & Cheng, Y. F.* (2025). Hydrogen production in integration with CCUS: A realistic strategy towards net zero. Energy, 315, 134398. (JCR Q1)
21. Lu, H.*, Liu, C., Zou, X., Peng, H., Ni, H., & Iseley, T. (2025). Prediction of construction traction force for corroded pipeline rehabilitation using multilayer composite liners. ASCE Journal of Pipeline Systems Engineering and Practice, 16(2), 04024080. (ASCE期刊)
22. Lu, H.*, Matthews, J., Chae, A., Shou, K. J., Ariaratnam, S., Fang, H., Ma, B., & Iseley, T. (2024). Advancing underground infrastructure: trenchless technologies and smart asset management in the digital age. Tunnelling and Underground Space Technology, 154, 106130. (JCR Q1)
23. Xia, Z., Xu, Z. D., Lu, H.*, Peng, H., Zang, X., Liu, X., & Wang, X. (2024) Modeling and assessment of hydrogen-blended natural gas releases from buried pipeline. International Journal of Hydrogen Energy, 90, 230-245. (JCR Q1)
24. Wang, Q. & Lu, H.* (2024). A novel stacking ensemble learner for predicting residual strength of corroded pipelines. npj Materials Degradation, 8, 87. (Nature旗下期刊, JCR Q1)
25. Peng, H., Xu, Z. D., Lu, H.*, Xi, D., Xia, Z., Yang, C., & Wang, B. A review of underground transport infrastructure monitoring in CCS: Technology and Engineering Practice. Process Safety and Environmental Protection, 190(B), 726-745. (JCR Q1)
26. Peng, H., Xu, Z. D., Xia, Z., Zang, X., Xi, D., Jiang, X., ... & Lu, H.* (2024). Closed Wellbore Integrity Failure Induced by Casing Corrosion Based on Solid-Chemical Coupling Model in CO2 Sequestration. Geoenergy Science and Engineering, 241, 213140. (JCR Q1)
27. Xi, D., Lu, H.*, Shi, K., Ni, H., & Iseley, T. (2024). Dual-Component Polyurethane Spray Technology for Repairing Concrete Pipes: A Case Study. ASCE Journal of Pipeline Systems Engineering and Practice, 15(4), 05024002. (ASCE期刊, Editor’s Choice Award)
28. 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)
29. 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)
30. Lu, H., Xu, Z. D., Song, K., Cheng, Y. F., 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. (Nature旗下期刊, JCR Q1)
31. 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. (Nature旗下期刊, JCR Q1)
32. 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, 84, 105129. (JCR Q2)
33. Lu, H., Xu, Z. D., Zang, X., Xi, D., Iseley, T., Matthews, J. C., & Wang, N. (2023). Leveraging Machine Learning for Pipeline Condition Assessment. ASCE Journal of Pipeline Systems Engineering and Practice, 14(3), 04023024. (ASCE期刊, Editor’s Choice Award)
34. 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. ASCE Journal of Pipeline Systems Engineering and Practice, 14(3), 04023022. (ASCE期刊)
35. 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. Tunnelling and Underground Space Technology, 136, 105077. (JCR Q1)
36. 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. Tunnelling and Underground Space Technology, 136, 105073. (JCR Q1)
37. Lu, H.*, Xi, D., & Qin, G. (2023). Environmental risk of oil pipeline accidents. Science of The Total Environment, 874, 162386. (JCR Q1)
38. 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. ASCE Journal of Performance of Constructed Facilities, 36(5), 04022044. (ASCE期刊)
39. 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)
40. 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)
41. 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. ASCE Journal of Pipeline Systems Engineering and Practice, 13(2), 04022005. (ASCE期刊)
42. Lu, H., Xu, Z. D., Iseley, T., & Matthews, J. C. (2021). Novel data-driven framework for predicting residual strength of corroded pipelines. ASCE Journal of Pipeline Systems Engineering and Practice, 12(4), 04021045. (ASCE期刊, Most Cited Paper)
43. 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)
44. 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)
45. 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)
46. Lu, H., Ma, X., Ma, M., & Zhu, S. (2021). Energy price prediction using data-driven models: A decade review. Computer Science Review, 39, 100356. (JCR Q1)
47. 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. ASCE Journal of Pipeline Systems Engineering and Practice, 11(4), 04020042. (ASCE期刊)
48. 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)
49. 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)
50. 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. ASCE Journal of Construction Engineering and Management, 146(6), 03120001. (JCR Q1, ASCE期刊)
51. 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)
52. Lu, H., Ma, X., & Azimi, M. (2020). US natural gas consumption prediction using an improved kernel-based nonlinear extension of the Arps decline model. Energy, 194, 116905. (JCR Q1)
53. Lu, H., & Ma, X. (2020). Hybrid decision tree-based machine learning models for short-term water quality prediction. Chemosphere, 249, 126169. (JCR Q1)
54. Lu, H., Ma, X., Huang, K., & Azimi, M. (2020). Prediction of offshore wind farm power using a novel two-stage model combining kernel-based nonlinear extension of the Arps decline model with a multi-objective grey wolf optimizer. Renewable and Sustainable Energy Reviews, 127, 109856. (JCR Q1)
55. 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)
56. 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)
57. 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)
58. 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)
59. Shang, B., Li, C., & Lu, H*. (2017). Stress analysis of suspended gas pipeline segment. ASCE Journal of Pipeline Systems Engineering and Practice, 8(3), 04017003. (ASCE期刊)
60. Lu, H., Huang, K., & Wu, S. (2016). Vibration and stress analyses of positive displacement pump pipeline systems in oil transportation stations. ASCE Journal of Pipeline Systems Engineering and Practice, 7(1), 05015002. (ASCE期刊)

参编标准

1. 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）
2. T/CMEA 72-2025 《城镇排水管道缺陷和病害智能判识与评估规程》（2025年12月22日实施）
3. T/CI 1242-2025《氢气及天然气管道风险监测预警技术导则》
4. 《超临界CO2输送管道风险分布式光纤监测预警技术规范》（团体标准）

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)
3. Xi, D., Lu, H.*, Dong, S., Xu, Z. D., & Wang, B. (2024). Engineering Properties of Hydrogen Storage Materials. Hydrogen Transportation and Storage. Section I: An Overview of Hydrogen Storage and Transportation Technologies. (章节)
4. Jiang, X., Lu, H.*, Dong, S., Xu, Z. D., & Wang, B. (2024). Prevention of Hydrogen Pipeline Cracking and Leakage. Hydrogen Transportation and Storage. Section I: An Overview of Hydrogen Storage and Transportation Technologies. (章节)

科研项目

1. 采用软管内衬修复的埋地多点腐蚀缺陷管道抗震性能研究，国家自然科学基金青年基金项目，主持，30万元，在研
2. 深地油气钻井关键构建服役行为与性能调控方法研究，国家自然科学基金企业创新发展联合基金集成项目，任务负责人，100万元，在研
3. 多点非一致地震激励下内衬软管修复腐蚀缺陷埋地钢管抗震性能研究，江苏省自然科学基金青年基金项目，主持，20万元，已结题
4. 掺氢天然气管道在受限空间的泄漏特征研究，江苏省特种设备安全监督检验研究院项目，主持，22.4万元，在研
5. 基于软管内衬修复的多点腐蚀缺陷钢管力学性能研究，江苏省特种设备安全监督检验研究院项目，主持，20万元，已结题
6. 压电式超声导波检测方法研究，江苏省特种设备安全监督检验研究院项目，主持，19.8万元，在研
7. 长距离海底管道穿插内衬软管修复关键技术研究，中海石油（中国）有限公司北京研究中心项目，主持，123万元，已结题
8. 基于大数据分析下的长输管道腐蚀缺陷剩余寿命预测技术研究，国家管网集团川气东送天然气管道有限公司项目，主持，87万元，已结题
9. 光纤水位传感器设计与制作，核工业北京化工冶金研究院项目，主持，30万元，已结题
10. 中央高校基本科研业务费专项资金项目，主持，20万元，已结题
11. 城市地下重大基础设施智能态势感知与健康评估，江苏省前沿引领技术基础研究专项，项目骨干，500万元，已结题
12. KP计划顶尖人才项目，浙江省政府，项目骨干，2800万元，在研
13. 国家建设高水平大学公派研究生项目，主持，已结题

科学技术成果鉴定

1. 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

发明专利

1. 一种防沉积的固液混合流体输送管道系统和方法，发明公开
2. 基于多层复合内衬修复长距离腐蚀管道施工牵引力的预测方法、装置、介质及设备，发明公开
3. 一种沙漠和盐碱地治理的系统和方法，发明公开
4. 一种海底管道穿插内衬软管修复模型试验平台及方法，发明公开
5. 一种用于海底管道穿插内衬软管修复技术的数值模拟系统，发明公开
6. 一种页岩气田弯头处冲蚀速率预测方法，发明公开
7. 钻井过滤器段轴向流量测量系统和方法，发明公开
8. 一种拉压式网格增强粘弹性阻尼器，发明授权
9. 一种基于超声导波的含附属结构管道的损伤检测方法，发明授权
10. 一种有效半径机械可调的光纤F-P压力传感器，发明公开
11. 钻井过滤器段轴向流量测量系统和方法，发明公开
12. 一种适用于球形节点在轴力及弯曲往复荷载作用下的力学性能测试装置，发明公开
13. 一种考虑物理约束损失函数的腐蚀油气管道剩余强度预测方法，发明公开

luhongfang@nimte.ac.cn

18782992609