基于GA-APSO混合罚模型的混凝土坝力学参数优化反演
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摘要
针对混凝土坝流变力学参数反分析中的多目标优化问题,利用混合罚函数法,构建一种新的无约束单目标优化函数,并就其函数求解中常规优化算法搜根收敛速率慢、局部最优等缺陷,通过向粒子群算法(PSO)中引入自适应因子,并融合遗传算法(GA)计算优势,提出一种基于自适应遗传粒子群算法(GA-APSO)的全局优化反演方法,并将ANSYS有限元程序作为子模块嵌套到该算法程序中,编制相应的有限元优化反演分析程序。同时,通过工程算例中的大坝正反分析结果,验证文中所建混合算法具有收敛速度快和全局搜索能力强的特点,进而可提高大坝优化反演效率。该方法亦可将其推广应用于其他坝型及岩质边坡的力学参数反分析。
Based on the method of mixed penalty function and considering the multi-objective optimization problem in the back analysis of rheological parameter of concrete dam, a new unconstrained single-objective optimization function was built. In order to offset the disadvantages of low searching efficiency in traditional optimization algorithm, the particle swarm optimization(PSO), which introducing self-adaptive factor and genetic algorithm(GA) were hybridized to construct a new global optimization inversion method according to their compatibility and algorithm complementary. This inversion method was established on a self-adaptive genetic particle swarm algorithm(GA-APSO), and the program of back analysis was coded, in which ANSYS finite element program was embedded as a module. The results of fore analysis and back analysis to the dam show that the optimization inversion method possesses good global search capability, a faster convergence rate and higher dam optimization inversion efficiency. This method can be applied to other dam types and the mechanical parameters of rock slope.
Based on the method of mixed penalty function and considering the multi-objective optimization problem in the back analysis of rheological parameter of concrete dam, a new unconstrained single-objective optimization function was built. In order to offset the disadvantages of low searching efficiency in traditional optimization algorithm, the particle swarm optimization(PSO), which introducing self-adaptive factor and genetic algorithm(GA) were hybridized to construct a new global optimization inversion method according to their compatibility and algorithm complementary. This inversion method was established on a self-adaptive genetic particle swarm algorithm(GA-APSO), and the program of back analysis was coded, in which ANSYS finite element program was embedded as a module. The results of fore analysis and back analysis to the dam show that the optimization inversion method possesses good global search capability, a faster convergence rate and higher dam optimization inversion efficiency. This method can be applied to other dam types and the mechanical parameters of rock slope.
引文
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[14]王伟,沈振中,李桃凡.遗传算法与自适应粒子群算法耦合的大坝安全预警评价模型[J].岩土工程学报,2009,31(8):1242-1247.WANG Wei,SHEN Zhenzhong,LI Taofan.Safety early warming evaluation model for dams based on coupled method of genetic algorithm and adapting particle swarm optimization algorithm[J].Chinese Journal of Geotechnical Engineering,2009,31(8):1242-1247.
[15]刘华伟,陈耀元,叶莹.多目标优化的新方法:幂加权和法及数值仿真[J].武汉理工大学学报(交通科学与工程版),2007,31(5):835-838.LIU Huawei,CHEN Yaoyuan,YE Ying.New method of multi objective optimization:Sum of weighted power and numerical emulator[J].Journal of Wuhan University of Technology(Transportation Science&Engineering),2007,31(5):835-838.
[16]吴中如.水工建筑物安全监控理论及其应用[M].北京:高等教育出版社,2003:282-291.WU Zhongru.Safety monitoring theories&its application of hydraulic structures[M].Beijing:Higher Education Press,2003:282-291.
[2]向衍,苏怀智,吴中如.基于大坝安全监测资料的物理力学参数反演[J].水利学报,2004(8):98-102.XIANG Yan,SU Huaizhi,WU Zhongru.Inverse analysis of mechanical parameters based on dam safety monitoring data[J].Journal of Hydraulic engineering,2004(8):98-102.
[3]ZHONG Dongjian,CHENG Lin,BAO Tengfei,et al.Integrated parameter inversion analysis method of a CFRD based on multi-output support vector machines and the clonal selection algorithm[J].Computers and Geotechnics,2013,47:68-77.
[4]CAO Ling,ZHAN Zhenbiao,HAN Yong.Deformation prediction and inversion of shuibuya project based on artificial neural network and genetic algorithm[J].Applied Mechanics and Materials,2012,170:2115-2118.
[5]漆祖芳,姜清辉,周创兵,等.基于v-SVR和MVPSO算法的边坡位移反分析方法及其应用[J].岩石力学与工程学报,2013,32(6):1185-1196.QI Zufang,JIANG Qinghui,ZHOU Chuangbing,et al.A new slope displacement back analysis method based on v-SVR and MVPSO algorithm and its application[J].Chinese Journal of Rock Mechanics and Engineering,2013,32(6):1185-1196.
[6]赵迪,张宗亮,陈建生.粒子群算法和ADINA在土石坝参数反演中的联合应用[J].水利水电科技进展,2012,32(3):43-47.ZHAO Di,ZHANG Zongliang,CHEN Jiansheng.A combined application of particle swarm optimization algorithm and ADINA for parametric inversion of earth-rock[J].Advances in Science and Technology of Water Resources,2012,32(3):43-47.
[7]魏博文,徐镇凯,徐宝松.碾压混凝土坝层面影响带黏弹塑性流变模型[J].水利学报,2012,43(9):1097-1102.WEI Bowen,XU Zhenkai,XU Baosong.Viscoelasto—plastic rheological model of effect zone for RCCD[J].Journal of Hydraulic Engineering,2012,43(9):1097-1102.
[8]顾冲时,李波,虞鸿,等.碾压混凝土坝力学参数的反分析[J].中国科学:技术科学,2010,40(6):651-656.GU Chongshi,LI Bo,YU Hong,et al.Back analysis of mechanical parameters of roller compacted concrete dam[J].Sci China:Tech Sci,2010,40(6):651-656.
[9]龚晓雯,顾冲时.基于改进粒子群算法的水口重力坝坝体参数反演[J].水电能源科学,2010,28(2):72-74.GONG Xiaowen,GU Chongshi.Parameter inversion analysis of Shuikou Dam Body based on improved particle swarm optimization algorithm[J].Water Resources and Power,2010,28(2):72-74.
[10]陈益峰,周创兵.隔河岩坝基岩体在运行期的弹塑性力学参数反演[J].岩石力学与工程学报,2002,21(7):968-975.CHEN Yifeng,ZHOU Chuangbing.Back analysis on elasto-plastic mechanic parameters of rock foundation of Geheyan Dam during running period[J].Chinese Journal of Rock Mechanics and engineering,2002,21(7):968-975.
[11]贾善坡,伍国军,陈卫忠.基于粒子群算法与混合罚函数法的有限元优化反演模型及应用[J].岩土力学,2011,32(增2):598-603.JIA Shanpo,WU Guojun,CHEN Weizhong.Application of finite element inverse model based on improved particle swarm optimization and mixed penalty function[J].Rock and Soil Mechanics,2011,32(Suppl 2):598-603.
[12]张志增,李仲奎,程丽娟.基于主从式并行遗传算法的岩土力学参数反分析方法[J].工程力学,2010,27(10):21-26.ZHANG Zhizeng,LI Zhongkui,CHENG Lijuan.Back analysis on geomechanical parameters based on a master-slave parallel genetic algorithm[J].Engineering Mechanics,2010,27(10):21-26.
[13]施荣华,朱炫滋,董健,等.基于粒子群-遗传混合算法的MIMO雷达布阵优化[J].中南大学学报(自然科学版),2013,44(11):4499-4505.SHI Ronghua,ZHU Xuanzi,DONG Jian,et al.A hybrid approach based on PSO and GA for array optimization in MIMO radar[J].Journal of Central South University(Science and Technology),2013,44(11):4499-4505.
[14]王伟,沈振中,李桃凡.遗传算法与自适应粒子群算法耦合的大坝安全预警评价模型[J].岩土工程学报,2009,31(8):1242-1247.WANG Wei,SHEN Zhenzhong,LI Taofan.Safety early warming evaluation model for dams based on coupled method of genetic algorithm and adapting particle swarm optimization algorithm[J].Chinese Journal of Geotechnical Engineering,2009,31(8):1242-1247.
[15]刘华伟,陈耀元,叶莹.多目标优化的新方法:幂加权和法及数值仿真[J].武汉理工大学学报(交通科学与工程版),2007,31(5):835-838.LIU Huawei,CHEN Yaoyuan,YE Ying.New method of multi objective optimization:Sum of weighted power and numerical emulator[J].Journal of Wuhan University of Technology(Transportation Science&Engineering),2007,31(5):835-838.
[16]吴中如.水工建筑物安全监控理论及其应用[M].北京:高等教育出版社,2003:282-291.WU Zhongru.Safety monitoring theories&its application of hydraulic structures[M].Beijing:Higher Education Press,2003:282-291.