1. 国家自然科学基金面上项目(52471300)：2025/01-2028/12，主持

2. 国家重点研发计划子课题(2023YFC2809004)：2023/12-2027/11，主持

3. 国家自然科学基金青年项目(52004195)：2021/01-2023/12，主持

4. 陕西省重点研发计划项目(2024SF-YBXM-662)：202401-202512，主持

5. 中国博士后科学基金资助项目(2020M673355)：2020/04-2022/03，主持 

6. 陕西省社科界重大理论与现实问题研究项目(2020Z188)：2020/01-2021/05，主持

7. 陕西省教育厅专项科研计划项目(20JK0729)：2020/01- 2021/12，主持

8. 海岸和近海工程国家重点实验室开放基金(LP2021)：2020/08-2022/07，主持

9. 石油管材及装备材料服役行为与结构安全国家重点实验室开放基金(2020K-5)：2020/08-2020/12，主持

10. 石油管材及装备材料服役行为与结构安全国家重点实验室开放基金(2022K-6): 2022/09-2023/6，主持

11. 石油管材及装备材料服役行为与结构安全国家重点实验室开放基金(2023K-02): 2023/02-2023/09，主持

12. 海洋物探及勘探设备国家工程实验室开放基金(20CX02315A)：2020/05-2022/04，主持

13. 陕西省科学技术协会：西部能源、环境与安全青年学者论坛，2021/06-2021/12，主持

14. 陕西省高校科协青年人才托举计划项目(20220429)：2023/01-2024/12，主持

15. 西安市社会科学规划基金项目(23GL29)：2023/05-2024/04，主持

[1] Li Xinhong, Xue Long, Zhang Hao, et al. Estimating Erosion Degradation of Deep-Sea Mining Transportation Pipes Using a Discrete Phase Simulation Approach [J]. Journal of Pipeline Systems Engineering and Practice, 2025, 16(2): 4024078.

[2] Li Xinhong, Liu Yabei, Zhang Renren, et al. Probabilistic failure assessment of oil and gas gathering pipelines using machine learning approach [J]. Reliability Engineering & System Safety, 2025, 256: 110747.

[3] Li Xinhong, Wang Chenyu, Zhang Yuhang. Investigation of Characteristics of Acoustic Emission Signals Resulting from a Subsea Gas Pipeline Leak [J]. Journal of Pipeline Systems Engineering and Practice, 2025, 16(1): 4024065.

[4] Li Xinhong, Li Runquan, Han Ziyue, et al. An intelligent monitoring approach for urban natural gas pipeline leak using semi-supervised learning generative adversarial networks[J]. Journal of Loss Prevention in the Process Industries, 2024,92: 105476.

[5] Li Xinhong, Ning Xin, Ma Jie, et al. Investigating the evolution path of urban natural gas pipeline accidents using a complex network approach [J]. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2024, 10(4): 6024005.

[6] Li, Xinhong., Chi Shengyou, Han, Ziyue, Chen Guoming. Failure pressure assessment of subsea pipelines with multiple corrosion defects under combined loadings [J]. Journal of Pipeline Systems Engineering and Practice, 2025,16(1): 4024052.

[7] Li, Xinhong., Ning, Xin., Xu, Ziqiang., Liu, Peihua., & Han, Ziyue. Vulnerability assessment of buildings adjacent to natural gas pipelines under explosion accident [J]. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2024, 46(1): 12886-12900.

[8] Li Xinhong., Tian Fafu., Wang Jianjun., Chen Guoming. An ELM data-driven model for predicting erosion rate of string in underground compressed air storage [J]. Process Safety and Environmental Protection, 2024, 185: 761-771.

[9] Li Xinhong, Liu Yabei, Han Ziyue, et al. A risk-based maintenance decision model for subsea pipeline considering pitting corrosion growth[J]. Process Safety and Environmental Protection, 2024,184: 1306-1317.

[10] Li Xinhong, Wang Zhaoge, Chen Guoming. Modeling underwater plumes of gas released from seafloor soil: A comparison of different gases[J]. Process Safety and Environmental Protection, 2024,184: 950-960.

[11] Han, Ziyue., Li, Xinhong*., Abbassi Rouzbeh., & Chen, Guoming. A probabilistic modeling approach for life extension decision-making of aging subsea pipelines[J]. Ocean Engineering, 2024, 294: 116786.

[12] Li Xinhong, Liu Yazhou, Chen Guoming, Abbassi Rouzbeh. Dynamic risk-based methodology for economic life assessment of aging subsea pipelines[J]. Ocean Engineering, 2024, 294: 116687.

[13] Li Xinhong, Ma Jie. Investigation of urban natural gas pipeline leak and resulting dispersion in a semi-closed space: A case of accident in Shiyan, China [J]. Process Safety and Environmental Protection, 2024, 183: 459-475.

[14] Li, Xinhong., Zhao, Han., Zhang, Renren., & Wang, Jianjun. Risk area classification for flammable gas dispersion in natural gas distribution station [J]. Journal of Loss Prevention in the Process Industries, 2023, 86, 105202.

[15] Li, Xinhong., Zhang, Yuhang., Zhang, Luyao., & Han, Ziyue. A probabilistic assessment methodology for pitting corrosion condition of offshore crude oil pipelines[J]. Ocean Engineering, 2023, 288: 116112.

[16] Li Xinhong., Ma, Jie., Pasman, Hans., & Zhang, Renren. (2023). Dynamic risk investigation of urban natural gas pipeline accidents using Stochastic Petri net approach. Process Safety and Environmental Protection, 178, 933-946.

[17] Li Xinhong., Guo, Mengmeng., & Chen, Guoming. (2023). A hybrid algorithm for inspection planning of subsea pipelines subject to corrosion-fatigue degradation. Process Safety and Environmental Protection, 178, 685-694.

[18] Han, Ziyue., Li, Xinhong*., & Chen, Guoming. (2023). A stochastic model for RUL prediction of subsea pipeline subject to corrosion-fatigue degradation. Process Safety and Environmental Protection, 178, 739-747.

[19] Han, Ziyue., Li, Xinhong*., Zhang, Renren., Yang, Ming., & Seghier, M. E. A. B. (2023). A dynamic condition assessment model of aging subsea pipelines subject to corrosion-fatigue degradation. Applied Ocean Research, 139, 103717.

[20] Li Xinhong, Hu, Yaping., & Han, Ziyue. (2023). Fatigue condition assessment of subsea pipelines under vortex induced vibration and cyclical lateral displacement. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 45(4), 9941-9957.

[21] Li Xinhong, Jia Ruichao, Zhang Renren. A data-driven methodology for predicting residual strength of subsea pipeline with double corrosion defects[J]. Ocean Engineering, 2023, 279: 114530.

[22] Li Xinhong, Ma Jie, Han Ziyue, et al. Application of game theory in risk management of urban natural gas pipelines[J]. Journal of Loss Prevention in the Process Industries, 2023, 83: 105037.

[23] Li Xinhong, Zhu Yujiao, Wang Jingwen, Zhang Renren, & Chen Guoming. Dispersion modeling of underwater oil released from buried subsea pipeline considering current and wave. Ocean Engineering, 2023, 272, 113924.

[24] Li Xinhong, Wang Jingwen. Modelling underwater dispersion of gas released from seabed soil considering current and wave[J]. Process Safety and Environmental Protection, 2023,171: 260-271.

[25] Li Xinhong, Jia Mingrui, Zhang Renren, et al. Dispersion modeling and assessment of natural gas containing hydrogen released from a damaged gas transmission pipeline[J]. International Journal of Hydrogen Energy, 2022,47(83): 35365-35385.

[26] Li Xinhong, Liu Yazhou, Abbassi Rouzbeh, et al. A Copula-Bayesian approach for risk assessment of decommissioning operation of aging subsea pipelines [J]. Process Safety and Environmental Protection, 2022, 167: 412-422.

[27] Li Xinhong, Abbassi Rouzbeh, Meng Huixing. Safety and risk analysis in digitalized process operations[J]. Process Safety and Environmental Protection, 2022,166: 212-213.

[28] Li Xinhong, Jingwen Wang, Chen Guoming. A machine learning methodology for probabilistic risk assessment of process operations: A case of subsea gas pipeline leak accidents[J]. Process Safety and Environmental Protection, 2022, 165: 959-968.

[29] Li Xinhong, Guo Mengmeng, Zhang Renren, et al. A data-driven prediction model for maximum pitting corrosion depth of subsea oil pipelines using SSA-LSTM approach[J]. Ocean Engineering, 2022, 261: 112062.

[30] Li Xinhong, Zhao Han, Zhang Renren. Data-driven dynamic failure assessment of subsea gas pipeline using process monitoring data[J]. Process Safety and Environmental Protection, 2022,166: 1-10.

[31] Li Xinhong, Han Ziyue, Yazdi Mohamed, et al. A CRITIC-VIKOR based robust approach to support risk management of subsea pipelines[J]. Applied Ocean Research, 2022,124: 103187.

[32] Li Xinhong, Zhu Yujiao, Abbassi Rouzbeh, et al. A probabilistic framework for risk management and emergency decision-making of marine oil spill accidents [J]. Process Safety and Environmental Protection, 2022, 162: 932-943.

[33] Li Xinhong, Jingwen Wang, Abbassi Rouzbeh, et al. A risk assessment framework considering uncertainty for corrosion-induced natural gas pipeline accidents[J]. Journal of Loss Prevention in the Process Industries, 2022, 75: 104718.

[34] Li Xinhong, Jia Ruichao, Zhang Renren, et al. A KPCA-BRANN based data-driven approach to model corrosion degradation of subsea oil pipelines[J]. Reliability Engineering & System Safety, 2022,219: 108231.

[35] Li Xinhong, Khan Faisal, Yang Ming, et al. Risk assessment of offshore fire accidents caused by subsea gas release[J]. Applied Ocean Research, 2021,115:102828.

[36] Li Xinhong, Zhang Luyao, Khan Faisal, et al. A data-driven corrosion prediction model to support digitization of subsea operations[J]. Process Safety and Environmental Protection, 2021,153:413-421.

[37] Li Xinhong, Zhang Yi, Abbassi Rouzbeh, et al. Probabilistic fatigue failure assessment of free spanning subsea pipeline using dynamic Bayesian network[J]. Ocean Engineering, 2021,234:109323.

[38] Li Xinhong, Zhang Luyao, Zhang Renren, et al. A semi-quantitative methodology for risk assessment of university chemical laboratory[J]. Journal of Loss Prevention in the Process Industries, 2021,72:104553.

[39] Li Xinhong, Zhang Yi, Abbassi Rouzbeh, et al. Dynamic probability assessment of urban natural gas pipeline accidents considering integrated external activities[J]. Journal of Loss Prevention in the Process Industries, 2021,69:104388.

[40] Li Xinhong, Han Ziyue, Zhang Renren, et al. Risk assessment of hydrogen generation unit considering dependencies using integrated DEMATEL and TOPSIS approach [J]. International Journal of Hydrogen Energy, 2020, 45(53): 29630-29642.

[41] Li Xinhong, Han Ziyue, Zhang Renren, et al. An integrated methodology to manage risk factors of aging urban oil and gas pipelines [J]. Journal of Loss Prevention in the Process Industries, 2020, 66, 104154.

[42] Li Xinhong, Abbassi Rouzbeh, Chen Guoming, Wang Qingsheng. Modeling and analysis of flammable gas dispersion and deflagration from offshore platform blowout [J]. Ocean Engineering, 2020, 201: 107146.

[43] Li Xinhong, Han Ziyue, Yang Shangyu, Chen Guoming. Underwater gas release modeling and verification analysis[J]. Process Safety and Environmental Protection, 2020, 137: 8-14.

[44] Li Xinhong, Chen Guoming, Khan Faisal, et al. Dynamic risk assessment of subsea pipelines leak using precursor data[J]. Ocean Engineering, 2019, 178: 156-169.

[45] Li Xinhong, Yang Ming, Chen Guoming. An integrated framework for subsea pipelines safety analysis considering causation dependencies[J]. Ocean Engineering, 2019, 183: 175-186.

[46] Li Xinhong, Chen Guoming, Faisal Khan. Analysis of underwater gas release and dispersion behavior to assess subsea safety risk[J]. Journal of hazardous materials, 2019,367:676-685.

[47] Li Xinhong, Chen Guoming, Chang Yuanjiang. Risk-based operation safety analysis during maintenance activities of subsea pipelines[J]. Process Safety and Environmental Protection, 2019,122:247-262. 

[48] Li Xinhong, Chen Guoming, Zhu Hongwei, et al. Gas dispersion and deflagration above sea from subsea release and its impact on offshore platform[J]. Ocean Engineering, 2018, 163:157-168.

[49] Li Xinhong, Chen Guoming, Zhu Hongwei, et al. Modelling and assessment of accidental oil release from damaged subsea pipelines [J]. Marine Pollution Bulletin,2017,123(1-2),133-141. 

[50] Li Xinhong, Chen Guoming, Zhu Hongwei. Quantitative risk analysis on leakage failure of submarine oil and gas pipelines using Bayesian network[J]. Process Safety & Environmental Protection, 2016, 103:163-173.

[51] Li Xinhong, Zhu Hongwei, Chen Guoming, et al. Optimal maintenance strategy for corroded subsea pipelines[J]. Journal of Loss Prevention in the Process Industries, 2017, 49:145-154. 

[52] Li Xinhong, Chen Guoming, Zhu Hongwei, et al. Quantitative risk assessment of submarine pipeline instability[J]. Journal of Loss Prevention in the Process Industries, 2017, 45:108-115. 

[53] Li Xinhong, Chen Guoming, Zhang Renren, et al. Simulation and assessment of underwater gas release and dispersion from subsea gas pipelines leak[J]. Process Safety and Environmental Protection, 2018, 119: 46-57.

[54] Li Xinhong, Chen Guoming, Jiang Shengyu, et al. Developing a dynamic model for risk analysis under uncertainty: Case of third-party damage on subsea pipelines[J]. Journal of Loss Prevention in the Process Industries, 2018, 54: 289-302.

[55] Li Xinhong, Chen Guoming, Zhu Hongwei, et al. Simulation and assessment of gas dispersion above sea from a subsea release: A CFD-based approach [J]. International Journal of Naval Architecture and Ocean Engineering, 2019,11(1):353-363.

[56] He Rui, Li Xinhong, Chen Guoming, et al. A quantitative risk analysis model considering uncertain information[J]. Process Safety and Environmental Protection, 2018, 118: 361-370.

[57] He, Rui., Li, Xinhong., Chen, Guoming., et al. (2020). Generative adversarial network-based semi-supervised learning for real-time risk warning of process industries. Expert Systems with Applications, 150, 113244.

[58] Shi, Jihao., Li, Xinhong., Khan, Faisal., et al. (2019). Artificial bee colony based bayesian regularization artificial neural network approach to model transient flammable cloud dispersion in congested area. Process Safety and Environmental Protection, 128, 121-127.

[59] Gu Qinghua, Chang Yinxin, Li Xinhong*, Chang Zhaozhao, Feng Zhidong. A novel F-SVM based on FOA for improving SVM performance [J]. Expert Systems with Applications, 2020, 113713.

[60] Geng Zhiyuan, Li Xinhong*, Chen Guoming, et al. Experimental and numerical study on gas release and dispersion from underwater soil [J]. Process Safety and Environmental Protection, 2021,149:11-21.

[61] 李新宏, 付雅倩, 刘亚洲, 等. 基于Copula-BN的海上船舶碰撞风险评估方法[J]. 中国安全科学学报, 2023, 33(09): 204-213.

[62] 胡亚平, 张认认, 李新宏, 等. 基于贝叶斯参数学习的海底原油管道腐蚀状态评估[J]. 中国安全生产科学技术, 2023,19(11): 93-99.

[63] 贾明汭, 张认认, 李新宏, 等. 氢气输送管道微观失效的分子动力学仿真研究[J]. 中国安全生产科学技术, 2023,19(09): 123-128.

[64] 李新宏, 贾明汭, 韩子月, 等. 穿越城市生活区的天然气管道泄漏连锁爆燃后果评估研究[J]. 中国安全生产科学技术, 2022,18(08): 183-188.

[65] 李新宏, 陈国明, 李秉军. 海洋油气管道泄漏事故应急管理体系构建研究[J]. 油气田地面工程, 2022, 41(05): 1-5.

[66] 李新宏, 朱玉娇, 李成成, 等. 贫数据条件下海底电缆故障概率评估方法[J]. 中国安全生产科学技术, 2022, 18(06): 224-229.

[67] 李新宏, 王靖雯, 朱玉娇, 等. 海洋水合物开采分解气体泄漏运移后果评估[J]. 中国安全科学学报, 2021,31(11): 114-119.

[68] 李新宏, 张毅, 韩子月, 等. 基于风险与成本的海洋溢油事故应急控制决策[J]. 中国安全科学学报, 2021,31(04):184-190.

[69] 李新宏, 张毅, 韩子月, 等. 天然气管道失效致因与事故链模型研究[J]. 油气田地面工程, 2021,40(04): 1-7.

[70] 李新宏, 韩子月, 卢才武, 等. 老龄城镇油气管道失效风险评价方法[J].中国安全科学学报, 2020, 30(2): 93-98．

[71] 李新宏, 韩子月, 耿志远, 等. 基于实验与仿真的三维水下气体泄漏预测与安全评估研究[J]. 中国安全生产科学技术, 2020,16(1):1-5.

[72] 李新宏, 韩子月，陈国明. 水下气体泄漏海面火灾后果预测及评估[J]. 中国安全科学学报，2019, 29(12):61-66.

[73] 李新宏, 陈国明, 朱红卫, 等. 基于欧拉-拉格朗日方法的水下气体泄漏扩散行为研究[J]. 中国石油大学学报(自然科学版), 2019,43(01):131-137.  

[74] 李新宏, 朱红卫, 陈国明,等. 海底油气管道泄漏事故风险分析的贝叶斯动态模型[J]. 中国安全科学学报, 2015, 25(4):75-80.

[75] 李新宏, 陈国明, 朱红卫, 等. 海底输气管道泄漏天然气扩散风险研究[J]. 石油科学通报, 2016, 1(3): 390-400.

[76] 李新宏, 朱红卫, 陈国明,等. 海底管道泄漏天然气扩散规律数值模拟[J]. 油气储运, 2016, 35(2):215-220.

[77] 李新宏, 李秀美, 陈国明,等. 2000m超深水水下分离器泄漏油气扩散特性研究[J]. 中国安全生产科学技术, 2016, 12(1):38-43.

[78] 李新宏, 朱红卫, 陈国明,等. 海底管道泄漏油气扩散规律数值仿真与对比分析[J]. 安全与环境学报, 2017, 17(2):608-614.

[79] 李新宏, 陈国明, 徐长航,等. 水深对海底管道泄漏水下气体扩散行为的影响研究[J]. 中国安全生产科学技术, 2018, 14(5), 17-22.

[80] 李新宏, 陈国明, 朱红卫. 海底油气管道腐蚀失效风险预警方法研究[J]. 中国安全科学学报, 2017(7):163-168.

[81] 李新宏, 朱红卫, 陈国明,等. 公路隧道内CNG管束气瓶车泄漏天然气扩散CFD仿真[J]. 中国安全生产科学技术, 2016, 12(12):138-143.

1. 全球前2％顶尖科学家榜单，2023/2024；

2. 中国职业安全健康协会第一届安全科学与工程学科优秀博士学位论文，2020；

3. 山东省优秀毕业生，2019；

4. 中国石油大学(华东)“学术十杰”，2018；

5. 研究生国家奖学金，2015/2017/2018；

6. 西安建筑科技大学首届校优秀青年科研团队育苗学者，2020；

7. 西安建筑科技大学第四届校优秀青年学者(青蓝青年学者)，2021；

8. 西安建筑科技大学优秀共产党员，2023；

1. 李新宏(1/9)，中国职业安全健康协会科技进步二等奖，2023

2. 李新宏(1/8), 西安建筑科技大学科技进步二等奖,  2023

3. 李新宏(4/9)，陕西省科技进步二等奖，2023

4. 李新宏(1/7)，陕西高等学校科学技术研究优秀成果二等奖，2024

1. 李新宏. 海洋油气管道泄漏风险演化与管控方法[M]. 西安交通大学出版社, 2024. ISBN: 978-7-5693-2235-4.

2. Li Xinhong, Zhang Luyao, Khan Faisal, et al. Dynamic operational risk assessment in process safety management[M]//Methods in Chemical Process Safety. Elsevier, 2022.