基于位移增量的高地应力下硐室群围岩蠕变参数的智能反分析
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摘要
深部高地应力下硐室围岩蠕变力学参数不准已成为制约岩体工程理论分析和数值计算发展的"瓶颈"问题,因而确定可靠的岩体蠕变参数服务于工程实际成为重点关注的课题,为此提出基于位移增量敏感性分析的高地应力下硐室群围岩蠕变参数的智能反分析方法。该方法基于描述深部高地应力条件下围岩蠕变随时间破坏特征的分数阶微积分的蠕变本构模型,取较为典型的主硐室顶拱位移、拱肩位移和边墙位移作为表征围岩的特性指标,从参数敏感性分析着手,确定模型中对位移较为敏感的5个蠕变参数(瞬时剪切模量、黏性系数、黏弹性剪切模量、黏弹性系数、分数阶系数β),并遵循"大值原则"和"敏感性原则"提取位移增量数据,输入主厂房和主变室等不同位置的现场位移增量监测信息建立多数据融合的适应度函数,采用均匀设计方法构造各参数不同水平组合的学习样本和训练样本,通过遗传算法与神经网络相结合的智能优化算法在解的全局空间进行搜索,确定反演蠕变参数值,最终通过灰色关联度和后验差法联合校核位移增量实测值与计算值。实例分析结果不仅表明智能优化算法获得的硐室围岩蠕变参数可靠性高,也验证了该法的有效性和合理性,同时为深部高地应力大型硐室长期稳定性评价时参数确定提供一个新手段。
The creep mechanical parameters inaccuracy of surrounding rock under high in-situ stress have become the"bottleneck" problem on the theoretical analysis and numerical calculation,therefore,determining the reliable rock mass creep parameters is urgently needed to be solved in practical engineering. An intelligent back analysis method of rock mass creep parameters based on the displacement increment sensitivity analysis for large underground caverns under high in-situ stress is put forward in this paper. This method is to use the fractional order calculus creep constitutive model which can describe the failure characteristics of surrounding rock creep over time under the high ground stress.Taking the displacements of arch roof,arch shoulder and sidewall as characteristic indices,five creep parameters(instantaneous shear modulus,viscosity coefficient,viscoelastic shear modulus,Viscoelastic coefficient,β) under inversion are confirmed by sensitivity analysis. Displacement increment data were extracted following the principle of "great value" and "sensitivity". Fitness function of displacement increment is established by determining the inversion creep parameters inputting the eight incremental displacement monitoring information from the main power house and main transformer chamber. The construction of different level combination of learning samples and training samples of each parameter by using uniform design method,parameters value is confirmed by adopting genetic algorithm-neural network searching in the global space. Finally the comparative analysis on displacement increment measured values and calculated values is conducted through grey correlation analysis method and posteriori difference method. The results from underground powerhouse of Jinping II hydropower station show that the surrounding rock mass creep parameters are accurate,validated and rational. It also provides a new method for parameters determination during the long-term stability evaluation of large cavern under high in-situ stress.
The creep mechanical parameters inaccuracy of surrounding rock under high in-situ stress have become the"bottleneck" problem on the theoretical analysis and numerical calculation,therefore,determining the reliable rock mass creep parameters is urgently needed to be solved in practical engineering. An intelligent back analysis method of rock mass creep parameters based on the displacement increment sensitivity analysis for large underground caverns under high in-situ stress is put forward in this paper. This method is to use the fractional order calculus creep constitutive model which can describe the failure characteristics of surrounding rock creep over time under the high ground stress.Taking the displacements of arch roof,arch shoulder and sidewall as characteristic indices,five creep parameters(instantaneous shear modulus,viscosity coefficient,viscoelastic shear modulus,Viscoelastic coefficient,β) under inversion are confirmed by sensitivity analysis. Displacement increment data were extracted following the principle of "great value" and "sensitivity". Fitness function of displacement increment is established by determining the inversion creep parameters inputting the eight incremental displacement monitoring information from the main power house and main transformer chamber. The construction of different level combination of learning samples and training samples of each parameter by using uniform design method,parameters value is confirmed by adopting genetic algorithm-neural network searching in the global space. Finally the comparative analysis on displacement increment measured values and calculated values is conducted through grey correlation analysis method and posteriori difference method. The results from underground powerhouse of Jinping II hydropower station show that the surrounding rock mass creep parameters are accurate,validated and rational. It also provides a new method for parameters determination during the long-term stability evaluation of large cavern under high in-situ stress.
引文
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[23]曹树刚,边金,李鹏.岩石蠕变本构关系及改进的西原正夫模型[J].岩石力学与工程学报,2002,21(5):632-634.CAO Shugang,BIAN Jin,LI Peng.Rheologic consititutive relationship of rocks and a modifical model[J].Chinese Journal of Rock Mechanics and Engineering,2002,21(5):632-634.
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[2]杨林德,颜建平,王悦照,等.围岩变形的时效特征与预测的研究[J].岩石力学与工程学报,2005,24(2):212-216.YANG Linde,YAN Jianping,WANG Yuezhao,et al.Study on tiem-dependent properties and deformation prediction of surrounding rock[J].Chinese Journal of Rock Mechanics and Engineering,2005,24(2):212-216.
[3]梁正召,张永彬,唐世斌,等.岩体尺寸效应及其特征参数计算[J].岩石力学与工程学报,2013,32(6):1157-1166.LIANG Zhengzhao,ZHANG Yongbin,TANG Shibin,et al.Size effect of rock messes and associated representative element properties[J].Chinese Journal of Rock Mechanics and Engineering,2013,32(6):1157-1166.
[4]邢猛,李连崇.隧洞围岩损伤演化与时效破坏过程的模拟分析[J].地下空间与工程学报,2017,13(3):703-710.XING Meng,LI Lianchong.Numerical analysis on damage evolution and time-dependent failureof rock surrounding underground tunnel[J].Chinese Journal of Underground Space and Engineering,2017,13(3):703-710.
[5]MISHRA Vivek,SINGH K N.Microstructural relation of macerals with mineral matter in coals from Ib valley and Umaria,Son-Mahanadi basin,India[J].International Journal of Coal Science&Technology,2017,4(2):191-197.
[6]KAVANAGH K T,CLOUGH R W.Finite element applications in the characterization of elastic solids[J].International Journal of Solids and Structures,1971,7(1):11-23.
[7]曹文贵,颜荣贵.各向异性岩体的绝对应力量测之反分析法研究[J].煤炭学报,1994,19(2):122-130.CAO Wengui,YAN Ronggui.Back analysis of stress measurement anisotropic rock mass[J].Journal of China Coal Society,1994,19(2):122-130.
[8]高延法.岩移“四带”模型与动态位移反分析[J].煤炭学报,1996,21(1):51-56.GAO Yanfa.“Four zone”model of rockmass movement and back analysis of dynamic displacement[J].Journal of China Coal Society,1996,21(1):51-56.
[9]高玮,郑颖人.一种新的岩土工程进化反分析算法[J].岩石力学与工程学报,2003,22(2):192-196.GAO Wei,ZHENG Yingren.New evolutionary back analysis algorithm in geotechnical engineering[J].Chinese Journal of Rock Mechanics and Engineering,2003,22(2):192-196.
[10]葛宏伟,梁艳春,刘玮,等.人工神经网络与遗传算法在岩石力学中的应用[J].岩石力学与工程学报,2004,23(9):1542-1550.GE Hongwei,LIANG Yanchun,LIU Wei,et al.Applications of artificial neural networks and genetic algorithms to rock mechanics[J].Chinese Journal of Rock Mechanics and Engineering,2004,23(9):1542-1550.
[11]高玮.基于粒子群优化的岩土工程反分析研究[J].岩土力学,2006,27(5):795-798.GAO Wei.Back analysis algorithm in geotechnical engineeringbased on particle swarm optimization[J].Rock and Soil Mechanics,2006,27(5):795-798.
[12]王金安,李飞.复杂地应力场反演优化算法及研究新进展[J].中国矿业大学学报,2015,44(2):189-205.WANG Jin’an,LI Fei.Review of inverse optimal algorithm of in-situ stress field and new achievement[J].Journal of China University of Mining&Technology,2015,44(2):189-205.
[13]冯夏庭,张治强,杨成祥,等.位移反分析的进化神经网络方法研究[J].岩石力学与工程学报,1999,18(5):529-633.FENG Xiating,ZHANG Zhiqiang,YANG Chengxiang,et al.Study on genetic-neural net work method of displacement back analysis[J].Chinese Journal of Rock Mechanics and Engineering,1999,18(5):529-633.
[14]冯夏庭,习心宏.智能岩石力学(1)-导论[J].岩石力学与工程学报,1999,18(2):222-226.FENG Xiating,XI Xinhong.Intelligent rock mechanics(1)-introduction[J].Chinese Journal of Rock Mechanics and Engineering,1999,18(2):222-226.
[15]冯夏庭,杨成祥.智能岩石力学(2)-参数与模型的智能辨识[J].岩石力学与工程学报,1999,18(3):350-353.FENG Xiating,YANG Chengxiang.Intelligent rock mechanics(2)-intelligent recognition of input parameters and constitutive models[J].Chinese Journal of Rock Mechanics and Engineering,1999,18(3):350-353.
[16]邓建辉,李焯芬,葛修润.BP网络和遗传算法在岩石边坡位移反分析中的应用[J].岩石力学与工程学报,2001,20(1):1-5.DENG Jianhui,LI Chaofen,GE Xiurun.Application of BP network and genetic algorithm to displacement back analysis of rock slopes[J].Chinese Journal of Rock Mechanics and Engineering,2001,20(1):1-5.
[17]董志宏,丁秀丽,卢波,等.大型地下硐室考虑开挖卸荷效应的位移反分析[J].岩土力学,2008,29(6):1563-1565.DONG Zhihong,DING Xiuli,LU Bo,et al.Displacement back analysis of rock mechanical parameters of large-scaleunderground powerhouse with unloading surrouding rockmass[J].Rock and Soil Mechanics,2008,29(6):1563-1565.
[18]向文,张强勇,张建国.坝区岩体蠕变参数解析-智能反演方法及其工程应用[J].岩土力学,2015,36(5):1505-1511.XIANG Wen,ZHANG Qiangyong,ZHANG Jianguo.Analytical intelligence inversion method of rheological parametersfor dam zone rock mass and its application to engineering[J].Rock and Soil Mechanics,2015,36(5):1505-1511.
[19]王祥秋,杨林德,高文华.软弱围岩蠕变损伤机理及合理支护时间的反演分析[J].岩石力学与工程学报,2004,23(5):793-796.WANG Xiangqiu,YANG Linde,GAO Wenhua.Creep damage mechanism and back analysis of optimum support time for soften rockmass[J].Chinese Journal of Rock Mechanics and Engineering,2004,23(5):793-796.
[20]程丽娟,李仲奎,郭凯.锦屏一级水电站地下厂房洞室群围岩时效变形研究[J].岩石力学与工程学报,2011,30(S1):3081-3088.CHENG Lijuan,LI Zhongkui,GUO Kai.Time-dependent deformation study of underground powerhouse of Jinping hydropower station[J].Chinese Journal of Rock Mechanics and Engineering,2011,30(S1):3081-3088.
[21]DU Wenfeng,PENG Suping,ZHU Guowei,et al.Time-lapse geophysical technology-based study on overburden strata changes induced by modern coal mining[J].International Journal of Coal Science&Technology,2014,1(2):184-191.
[22]蔡燕燕,张建智,俞缙,等.考虑围岩蠕变全过程与扩容的深埋隧洞非线性位移解[J].岩土力学,2015,36(7):1831-1839.CAI Yanyan,ZHANG Jianzhi,YU Jin,et al.Nonlinear displacement solutions for deep tunnels considering whole process ofcreep and dilatation of surrounding rock[J].Rock and Soil Mechanics,2015,36(7):1831-1839.
[23]曹树刚,边金,李鹏.岩石蠕变本构关系及改进的西原正夫模型[J].岩石力学与工程学报,2002,21(5):632-634.CAO Shugang,BIAN Jin,LI Peng.Rheologic consititutive relationship of rocks and a modifical model[J].Chinese Journal of Rock Mechanics and Engineering,2002,21(5):632-634.
[24]徐鹏,杨圣奇,陈国飞.改进的岩石Burgers流变模型及其试验验证[J].煤炭学报,2004,39(10):1993-2000.XU Peng,YANG Shengqi,CHEN Guofei.Modified Burgers model of rocks and its experimental verification[J].Journal of China Coal Society,2004,39(10):1993-2000.
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