基于改进粒子群算法的混凝土坝热学参数反演研究
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摘要
为实时获取真实浇筑环境下混凝土热学特性变化规律,基于温度观测数据,建立了材料参数识别的群体智能优化粒子群模型。针对传统粒子群算法易早熟陷入局部极值点这一问题,将粒子群算法与凹函数权值递减策略相结合,对粒子群算法进行改进,通过算法性能对比分析来说明其有效性。考虑冷却通水以及外界气温变化影响,将改进的粒子群算法用于某拱坝高温季节热学参数反演分析,通过实测温度与计算温度对比分析来说明反演参数的合理性。算例分析表明,改进的粒子群算法具有收敛速度快、识别精度高等优点。
A swarm intelligence optimization algorithm-particle swarm optimization(PSO) model was constructed for thermal parameter identification based on temperature observation data. Therefore, thermal characteristics of concrete in real pouring environment can be obtained in real time. In order to solve this problem that traditional PSO is easy to fall into the local extreme point prematurely, an improved particle swarm optimization(IPSO) was proposed, which combines particle swarm optimization and concave function weight decreasing strategy. Effectiveness of IPSO was illustrated by the algorithm performance comparison analysis. Considering the influence of cooling water and outside temperature change, IPSO was applied to inverse analysis of thermal parameters of an arch dam during hot season construction. The inversion parameters were validated by comparison of measured temperature and calculated temperature. The numerical example shows that IPSO has advantages of converging quickly and identifying accurately.
A swarm intelligence optimization algorithm-particle swarm optimization(PSO) model was constructed for thermal parameter identification based on temperature observation data. Therefore, thermal characteristics of concrete in real pouring environment can be obtained in real time. In order to solve this problem that traditional PSO is easy to fall into the local extreme point prematurely, an improved particle swarm optimization(IPSO) was proposed, which combines particle swarm optimization and concave function weight decreasing strategy. Effectiveness of IPSO was illustrated by the algorithm performance comparison analysis. Considering the influence of cooling water and outside temperature change, IPSO was applied to inverse analysis of thermal parameters of an arch dam during hot season construction. The inversion parameters were validated by comparison of measured temperature and calculated temperature. The numerical example shows that IPSO has advantages of converging quickly and identifying accurately.
引文
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[3] 李火坤,邓冰梅,魏博文,等.基于有限测点的高拱坝原型整体动位移场反演研究[J].振动与冲击,2016,35(10):1-8.LI Huokun,DENG Bingmei,WEI Bowen,et al.Inversion of the whole dynamic displacement field of a prototype high arch dam based on limited points measurement[J].Journal of Vibration and Shock,2016,35(10):1-8.
[4] 井向阳,常晓林,周伟,等.高拱坝施工期温控防裂时空动态控制措施及工程应用[J].天津大学学报(自然科学与工程技术版),2013,46(8):705-712.JING Xiangyang,CHANG Xiaolin,ZHOU Wei,et al.Spatial-temporal dynamic control framework of temperature control and crack prevention in construction of concrete arch dams and its engineering application[J].Journal of Tianjin University (Science and Technology),2013,46(8):705-712.
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[6] 蔡德所,戴会超,蔡顺德,等.分布式光纤传感监测三峡大坝混凝土温度场试验研究[J].水利学报,2003(5):88-91.CAI Desuo,DAI Huichao,CAI Shunde,et al.Monitoring the temperature in concrete structure of Three Gorges dam by using distributed opptical fiber sensor[J].Journal of Hydraulic Engineering,2003(5):88-91.
[7] 周宜红,宫经伟,黄耀英,等.泄洪洞衬砌混凝土施工期光纤测温现场试验[J].华中科技大学学报(自然科学版),2013,41(7):15-20.ZHOU Yihong,GONG Jingwei,HUANG Yaoying,et al.Site tests of temperature monitoring by DOF for lining concrete of spillway tunnel during construction period [J].Journal of Huazhong University of Science and Technology(Natural Science Edition),2013,41(7):15-20.
[8] 顾冲时,苏怀智,王少伟.高混凝土坝长期变形特性计算模型及监控方法研究进展[J].水力发电学报,2016,35(5):1-14.GU Chongshi,SU Huaizhi,WANG Shaowei.Advances in calculation models and monitoring methods for long-term deformation behavior of concrete dams [J].Journal of Hydroelectric Engineering,2016,35(5):1-14.
[9] TSENG A A,CHEN T C,ZHA F Z.Direct sensitivity coefficient method for solving two-dimensional inverse heat conduction problems by finite-element scheme[J].NumericalHeat Transfer,Part B:Fundamentals,1995,27(3):291-307.
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[11] TERVOLA P.A method to determine the thermal conductivity from measured temperature profile[J].International Journal of Heat and Mass Transfer,1989,32(8):1425-1430.
[12] AMIRFAKHRIAN M,ARGHAND M,KANSA E J.A new approximate method for an inverse time-dependent heat source problem using fundamental solutions and RBFs[J].Engineering Analysis with Boundary Elements,2016,64:278-289.
[13] 黄达海,刘广义,刘光廷.大体积混凝土热学参数反分析新方法[J].计算力学学报,2003,20(5):574-578.HUANG Dahai,LIU Guangyi,LIU Guangting.A new method for back analysis on thermal parameters of mass concrete needs[J].Chinese Journal of Computational Mechanics,2003,20(5):574-578.
[14] 朱岳明,刘勇军,谢先坤.确定混凝土温度特性多参数的试验与反演分析[J].岩土工程学报,2002,24(2):175-177.ZHU Yueming,LIU Yongjun,XIE Xiankun.Determination of thermal parameters of concrete by reverse analysis of test results[J].Chinese Journal of Geotechnical Engineering,2002,24(2):175-177.
[15] 刘宁,张剑,赵新铭.大体积混凝土结构热学参数随机反演方法初探[J].工程力学,2003,20(5):114-120.LIU Ning,ZHANG Jian,ZHAO Xinming.Stochastic back analysis of thermal parameters of mass concrete structures[J].Engineering Mechanics,2003,20(5):114-120.
[16] 江凯,黄耀英,周宜红,等.基于光纤测温的大体积混凝土热学参数反演分析[J].人民长江,2012,43(2):50-53.JIANG Kai,HUANG Yaoying,ZHOU Yihong,et al.Inverse analysis for thermal parameters of mass concrete based on fiber temperature monitoring[J].Yangtze River,2012,43(2):50-53.
[17] 强晟,娄二召,侯光普,等.一种基于实测混凝土温度梯度获取表面散热系数的新方法[J].水利学报,2015,46(10):1240-1246.QIANG Sheng,LOU Erzhao,HOU Guangpu,et al.A new method for concrete surface coefficient of heat transfer based on the measured temperature gradient[J].Journal of Hydraulic Engineering,2015,46(10):1240-1246.
[18] EBERHART R C,KENNEDY J.A new optimizer using particle swarm theory[C]// Proceedings of the Sixth International Symposium on Micro Machine and Human Science.Piscataway,USA:IEEE,1995:39-43.
[19] KENNEDY J,EBERHART R C.Particle swarm optimization[C]// Proceedings of the 1995 IEEE International Conference on Neural Networks.Piscataway,USA:IEEE,1995:1942-1948.
[20] SHI Y,EBERHART R C.A modified particle swarmoptimizer [C]// IEEE World Congress on Computational Intelligence.Piscataway,USA:IEEE,1998:69-73.
[21] SHI Y,EBERHART R C.Parameter selection in particle swarm optimization[C]// International Conference on Evolutionary Programming.Berlin:Springer,1998:591-600.
[22] 陈贵敏,贾建援,韩琪.粒子群优化算法的惯性权值递减策略研究[J].西安交通大学学报,2006,40(1):53-56.CHEN Guimin,JIA Jianyuan,HAN Qi.Study on the strategy of decreasing inertia weight in particle swarm optimization algorithm[J].Journal of Xi’an Jiaotong University,2006,40(1):53-56.
[23] ROBINSON J,SINTON S,RAHMAT-SAMII Y.Particle swarm,genetic algorithm,and their hybrids:optimization of a profiled corrugated horn antenna [C]// IEEE Antennas and Propagation Society International Symposium.Piscataway,USA:IEEE,2002:314-317.
[24] 田明俊,周晶.岩土工程参数反演的一种新方法[J].岩石力学与工程学报,2005,24(9):1492-1496.TIAN Mingjun,ZHOU Jing.New algorithm for parameter inversion in geotechnical engineering[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(9):1492-1496.
[25] 徐中明,谢耀仪,贺岩松,等.基于粒子群-向量机的汽车加速噪声评价[J].振动与冲击,2015,34(2):25-29.XU Zhongming,XIE Yaoyi,HE Yansong,et al.Evaluation of car interior sound quality based on PSO-SVM[J].Journal of Vibration and Shock,2015,34(2):25-29.
[26] 李春祥,丁晓达,叶继红.基于混合蚁群和粒子群优化 LSSVM的脉动风速预测[J].振动与冲击,2016,35(21):131-136.LI Chunxiang,DING Xiaoda,YE Jihong.Fluctuating wind velocity forecasting based on LSSVM with hybrid ACO & PSO[J].Journal of Vibration and Shock,2016,35(21):131-136.
[27] 孙林燕.一种新的改进粒子群算法[D].大连:大连海事大学,2008.
[28] 郁磊,史峰,王辉,等.MATLAB智能算法30个案例分析[M].北京:北京航空航天大学出版社,2015.
[29] 周建兵,黄耀英,何小鹏,等.向家坝导流底孔回填混凝土温度动态预测[J].长江科学院院报,2015,32(2):119-122.ZHOU Jianbing,HUANG Yaoying,HE Xiaopeng,et al.Dynamic prediction of concrete temperature for the plugging of bottom diversion outlet of xiangjiaba hydropower project[J].Journal of Yangtze River Scientific Research Institute,2015,32(2):119-122.
[2] 张国新,刘有志,刘毅.特高拱坝温度控制与防裂研究进展[J].水利学报,2016,47(3):382-389.ZHANG Guoxin,LIU Youzhi,LIU Yi.Temperature control and crack prevention of super-high arch dam[J].Journal of Hydraulic Engineering,2016,47(3):382-389.
[3] 李火坤,邓冰梅,魏博文,等.基于有限测点的高拱坝原型整体动位移场反演研究[J].振动与冲击,2016,35(10):1-8.LI Huokun,DENG Bingmei,WEI Bowen,et al.Inversion of the whole dynamic displacement field of a prototype high arch dam based on limited points measurement[J].Journal of Vibration and Shock,2016,35(10):1-8.
[4] 井向阳,常晓林,周伟,等.高拱坝施工期温控防裂时空动态控制措施及工程应用[J].天津大学学报(自然科学与工程技术版),2013,46(8):705-712.JING Xiangyang,CHANG Xiaolin,ZHOU Wei,et al.Spatial-temporal dynamic control framework of temperature control and crack prevention in construction of concrete arch dams and its engineering application[J].Journal of Tianjin University (Science and Technology),2013,46(8):705-712.
[5] 周彪,孙国强,朱信华,等.混凝土温度监测中温度计的应用研究[J].大坝与安全,2017(3):21-25.ZHOU Biao,SUN Guoqiang,ZHU Xinhua,et al.Application of thermometer in concrete temperature monitoring [J].Dam & Safety,2017(3):21-25.
[6] 蔡德所,戴会超,蔡顺德,等.分布式光纤传感监测三峡大坝混凝土温度场试验研究[J].水利学报,2003(5):88-91.CAI Desuo,DAI Huichao,CAI Shunde,et al.Monitoring the temperature in concrete structure of Three Gorges dam by using distributed opptical fiber sensor[J].Journal of Hydraulic Engineering,2003(5):88-91.
[7] 周宜红,宫经伟,黄耀英,等.泄洪洞衬砌混凝土施工期光纤测温现场试验[J].华中科技大学学报(自然科学版),2013,41(7):15-20.ZHOU Yihong,GONG Jingwei,HUANG Yaoying,et al.Site tests of temperature monitoring by DOF for lining concrete of spillway tunnel during construction period [J].Journal of Huazhong University of Science and Technology(Natural Science Edition),2013,41(7):15-20.
[8] 顾冲时,苏怀智,王少伟.高混凝土坝长期变形特性计算模型及监控方法研究进展[J].水力发电学报,2016,35(5):1-14.GU Chongshi,SU Huaizhi,WANG Shaowei.Advances in calculation models and monitoring methods for long-term deformation behavior of concrete dams [J].Journal of Hydroelectric Engineering,2016,35(5):1-14.
[9] TSENG A A,CHEN T C,ZHA F Z.Direct sensitivity coefficient method for solving two-dimensional inverse heat conduction problems by finite-element scheme[J].NumericalHeat Transfer,Part B:Fundamentals,1995,27(3):291-307.
[10] MARTIN T J,DULIKRAVICH G S.Inverse determination of boundary conditions and sources in steady heat condition with heat generation[J].Journal of Heat Transfer-ASME,1996,118(3):546-554.
[11] TERVOLA P.A method to determine the thermal conductivity from measured temperature profile[J].International Journal of Heat and Mass Transfer,1989,32(8):1425-1430.
[12] AMIRFAKHRIAN M,ARGHAND M,KANSA E J.A new approximate method for an inverse time-dependent heat source problem using fundamental solutions and RBFs[J].Engineering Analysis with Boundary Elements,2016,64:278-289.
[13] 黄达海,刘广义,刘光廷.大体积混凝土热学参数反分析新方法[J].计算力学学报,2003,20(5):574-578.HUANG Dahai,LIU Guangyi,LIU Guangting.A new method for back analysis on thermal parameters of mass concrete needs[J].Chinese Journal of Computational Mechanics,2003,20(5):574-578.
[14] 朱岳明,刘勇军,谢先坤.确定混凝土温度特性多参数的试验与反演分析[J].岩土工程学报,2002,24(2):175-177.ZHU Yueming,LIU Yongjun,XIE Xiankun.Determination of thermal parameters of concrete by reverse analysis of test results[J].Chinese Journal of Geotechnical Engineering,2002,24(2):175-177.
[15] 刘宁,张剑,赵新铭.大体积混凝土结构热学参数随机反演方法初探[J].工程力学,2003,20(5):114-120.LIU Ning,ZHANG Jian,ZHAO Xinming.Stochastic back analysis of thermal parameters of mass concrete structures[J].Engineering Mechanics,2003,20(5):114-120.
[16] 江凯,黄耀英,周宜红,等.基于光纤测温的大体积混凝土热学参数反演分析[J].人民长江,2012,43(2):50-53.JIANG Kai,HUANG Yaoying,ZHOU Yihong,et al.Inverse analysis for thermal parameters of mass concrete based on fiber temperature monitoring[J].Yangtze River,2012,43(2):50-53.
[17] 强晟,娄二召,侯光普,等.一种基于实测混凝土温度梯度获取表面散热系数的新方法[J].水利学报,2015,46(10):1240-1246.QIANG Sheng,LOU Erzhao,HOU Guangpu,et al.A new method for concrete surface coefficient of heat transfer based on the measured temperature gradient[J].Journal of Hydraulic Engineering,2015,46(10):1240-1246.
[18] EBERHART R C,KENNEDY J.A new optimizer using particle swarm theory[C]// Proceedings of the Sixth International Symposium on Micro Machine and Human Science.Piscataway,USA:IEEE,1995:39-43.
[19] KENNEDY J,EBERHART R C.Particle swarm optimization[C]// Proceedings of the 1995 IEEE International Conference on Neural Networks.Piscataway,USA:IEEE,1995:1942-1948.
[20] SHI Y,EBERHART R C.A modified particle swarmoptimizer [C]// IEEE World Congress on Computational Intelligence.Piscataway,USA:IEEE,1998:69-73.
[21] SHI Y,EBERHART R C.Parameter selection in particle swarm optimization[C]// International Conference on Evolutionary Programming.Berlin:Springer,1998:591-600.
[22] 陈贵敏,贾建援,韩琪.粒子群优化算法的惯性权值递减策略研究[J].西安交通大学学报,2006,40(1):53-56.CHEN Guimin,JIA Jianyuan,HAN Qi.Study on the strategy of decreasing inertia weight in particle swarm optimization algorithm[J].Journal of Xi’an Jiaotong University,2006,40(1):53-56.
[23] ROBINSON J,SINTON S,RAHMAT-SAMII Y.Particle swarm,genetic algorithm,and their hybrids:optimization of a profiled corrugated horn antenna [C]// IEEE Antennas and Propagation Society International Symposium.Piscataway,USA:IEEE,2002:314-317.
[24] 田明俊,周晶.岩土工程参数反演的一种新方法[J].岩石力学与工程学报,2005,24(9):1492-1496.TIAN Mingjun,ZHOU Jing.New algorithm for parameter inversion in geotechnical engineering[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(9):1492-1496.
[25] 徐中明,谢耀仪,贺岩松,等.基于粒子群-向量机的汽车加速噪声评价[J].振动与冲击,2015,34(2):25-29.XU Zhongming,XIE Yaoyi,HE Yansong,et al.Evaluation of car interior sound quality based on PSO-SVM[J].Journal of Vibration and Shock,2015,34(2):25-29.
[26] 李春祥,丁晓达,叶继红.基于混合蚁群和粒子群优化 LSSVM的脉动风速预测[J].振动与冲击,2016,35(21):131-136.LI Chunxiang,DING Xiaoda,YE Jihong.Fluctuating wind velocity forecasting based on LSSVM with hybrid ACO & PSO[J].Journal of Vibration and Shock,2016,35(21):131-136.
[27] 孙林燕.一种新的改进粒子群算法[D].大连:大连海事大学,2008.
[28] 郁磊,史峰,王辉,等.MATLAB智能算法30个案例分析[M].北京:北京航空航天大学出版社,2015.
[29] 周建兵,黄耀英,何小鹏,等.向家坝导流底孔回填混凝土温度动态预测[J].长江科学院院报,2015,32(2):119-122.ZHOU Jianbing,HUANG Yaoying,HE Xiaopeng,et al.Dynamic prediction of concrete temperature for the plugging of bottom diversion outlet of xiangjiaba hydropower project[J].Journal of Yangtze River Scientific Research Institute,2015,32(2):119-122.