地质灾害段管道结构安全数字孪生机理模型  

Digital Twin mechanism model for the structural safety of pipelines in geohazards area

作　　者：张宏[1] 季蓓蕾 刘燊 吴锴[1] 张东 施宁 刘啸奔 ZHANG Hong;JI Beilei;LIU Shen;WU Kai;ZHANG Dong;SHI Ning;LIU Xiaoben(College of Mechanical and Transportation Engineering,China University of Petroleum(Beijing)//National Engineering Laboratory for Pipeline Safety//MOE Key Laboratory of Petroleum Engineering//Beijing Key Laboratory of Urban Oil and Gas Distribution Technology;Pipeline R&D Center,PipeChina North Pipeline Company)

机构地区：[1]中国石油大学(北京)机械与储运工程学院·油气管道输送安全国家工程实验室·石油工程教育部重点实验室·城市油气输配技术北京市重点实验室 [2]国家管网集团北方管道公司管道科技研究中心

出　　处：《油气储运》2021年第10期1099-1104,1130,共7页Oil & Gas Storage and Transportation

基　　金：国家自然科学基金资助项目“逆断层作用下X80管道屈曲演化与韧性破损机理研究”,52004314;中国石油大学(北京)青年拔尖人才科研基金资助项目“断层作用下高强钢管道失效机理与可靠性评价”,2462018YJRC019;中国石油大学(北京)科研基金资助项目“基于大数据的天然气管网智能运行与控制研究”,2462020YXZZ045。

摘　　要：地质灾害是危害油气管道运行安全的主要因素之一,但受设备检测精度及检测数据离散性等因素限制,仅通过单一的监测检测技术无法定量分析管道的安全情况,亟需融合多源监测检测技术开展管道结构安全数字孪生机理模型研究,实现地质灾害段管道安全状态的智能感知与预测。提出地质灾害段管道结构安全数字孪生机理模型的构建流程,通过建立参数化的地质灾害段管道有限元模型,结合影响管道应力应变分布的可变参数范围,建立了管道应力应变数据库,利用BP神经网络拟合了可变参数与管道应力应变状态的高度非线性关系。结合管道真实应力应变监测数据,采用粒子群优化算法,建立了准确反演管道沿线真实应力应变分布的机理模型,并通过实例应用,验证了模型的准确性。研究成果可用于地质灾害段管道的定量安全评价,并可为管道数字孪生体的构建提供内核支撑。(图8,表1,参20)Geohazard is one of the major factors threating the safe operation of oil and gas pipelines.However,due to the inspection accuracy of equipment and the discreteness of inspection data,the pipeline safety cannot be analyzed quantitatively with a single monitoring and inspection technology.Thus,it is urgent to study the Digital Twin mechanism model for the structural safety of pipelines in combination with the multi-source monitoring and inspection data,so as to realize the intelligent perception and prediction of pipeline safety in geohazard areas.Herein,the process to establish a Digital Twin mechanism model for the structural safety of pipelines in geohazard areas was put forward.Meanwhile,by building a parameterized finite element model of pipelines in geohazard areas,a stress-strain database of the pipeline was established with consideration to the range of the variable parameters affecting the stress-strain distribution of pipelines,and then the highly nonlinear relationship between the variable parameters and the stress-strain state of the pipelines was fitted by BP neural network.In addition,combined with the real monitoring data of pipeline stress and strain,a mechanism model capable of accurately inverting the real stress and strain distribution along the pipeline was constructed with the particle swarm optimization algorithm.Moreover,the accuracy of the model was verified by an application case.Therefore,the research results could be applied to the quantitative safety assessment of the pipelines in geohazard areas,and core support could be provided for the construction of Digital Twin of pipelines.(8 Figures,1 Table,20 References)

关 键 词：多源监测检测数据 数值反演 优化 数字孪生 定量安全评价 

分 类 号：X937[环境科学与工程—安全科学]