长江科学院院报 ›› 2017, Vol. 34 ›› Issue (6): 81-87.DOI: 10.11988/ckyyb.20160259

• 岩土工程 • 上一篇    下一篇

基于IDE-OSVR-ABAQUS的岩土力学参数反演方法

卢远富a，b，c，包腾飞a，b，c，李涧鸣a，b，c，王甜a，b，c   

  1. 河海大学 a.水利水电学院; b.水资源高效利用与工程安全国家工程研究中心;
    c.水文水资源与水利工程科学国家重点实验室，南京 210098
  • 收稿日期:2016-03-21 修回日期:2016-04-21 出版日期:2017-06-01 发布日期:2017-06-19
  • 作者简介:卢远富(1991-)，男，湖北麻城人，硕士研究生，研究方向为水工建筑物安全监控，(电话)15295514300(电子信箱)yuanfulu@163.com。

Inversion of Geotechnical Mechanical Parameters Based on Improved Differential Evolution Algorithm, Online Support Vector Regression and ABAQUS

LU Yuan-fu1,2,3, BAO Teng-fei1,2,3, LI Jian-ming1,2,3, WANG Tian1,2,3   

  1. 1.College of Water Conservancy and Hydropower, Hohai University, Nanjing 210098, China;
    2.National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety,
    Hohai University, Nanjing 210098, China;
    3.State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China
  • Received:2016-03-21 Revised:2016-04-21 Published:2017-06-01 Online:2017-06-19

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摘要： 提出引入自适应因子的改进型差分进化算法(IDE)，并应用于优化在线支持回归机(OSVR)的核参数和惩罚参数，建立岩土体位移和岩土力学参数之间复杂非线性关系的动态最优IDE-OSVR模型，输入岩土体位移值直接输出岩土力学参数实现参数反演。通过均匀设计方法与ABAQUS正计算构建初始训练集，然后逐次反演并进行验算误差，将误差未达到预定阈值前的验算样本增添至训练集，使得IDE-OSVR模型不断在线学习，提高参数反演精度。将IDE-OSVR-ABAQUS反演方法应用于工程算例，并同几种典型方法对比。结果表明该方法的岩土力学参数反演速度很快，反演精度很高，是一种合理的岩土力学参数反演方法。

关键词: 改进型差分进化算法, 在线支持回归机, ABAQUS , 参数反演, 岩土体位移

Abstract: An improved differential evolution algorithm (IDE) is proposed by introducing adaptive factor and is applied to optimizing the kernel parameter and penalty parameter of online support vector regression (OSVR). A dynamic optimal IDE-OSVR model which reflects the complex nonlinear relationship between rock and soil mass displacements and geotechnical parameters is established. The inversion of parameters can be accomplished by inputting the soil mass displacements in the IDE-OSVR model. The initial training set is designed with uniform design method and ABAQUS calculation, then the errors of successive inversed parameters are checked, and the checked sample will be added to training set if the error is greater than the predetermined threshold. Through the continuous online learning process, the precision of parameters inversion by IDE-OSVR model can be enhanced. The inversion method based on IDE-OSVR-ABAQUS is applied to an engineering example and the result is compared with those of typical methods. The comparison result shows that the IDE-OSVR-ABAQUS inversion method is very fast with high accuracy, hence is a reasonable method for the inversion of geotechnical mechanics parameters.

Key words: IDE, OSVR, ABAQUS, parameters inversion, soil mass displacement

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