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Ant Colony Optimization Analysis on Overall Stability of High Arch Dam Basis of Field Monitoring

机译:基于现场监测的高拱坝整体稳定性蚁群优化分析。

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摘要

A dam ant colony optimization (D-ACO) analysis of the overall stability of high arch dams on complicated foundations is presented in this paper. A modified ant colony optimization (ACO) model is proposed for obtaining dam concrete and rock mechanical parameters. A typical dam parameter feedback problem is proposed for nonlinear back-analysis numerical model based on field monitoring deformation and ACO. The basic principle of the proposed model is the establishment of the objective function of optimizing real concrete and rock mechanical parameter. The feedback analysis is then implemented with a modified ant colony algorithm. The algorithm performance is satisfactory, and the accuracy is verified. The m groups of feedback parameters, used to run a nonlinear FEM code, and the displacement and stress distribution are discussed. A feedback analysis of the deformation of the Lijiaxia arch dam and based on the modified ant colony optimization method is also conducted. By considering various material parameters obtained using different analysis methods, comparative analyses were conducted on dam displacements, stress distribution characteristics, and overall dam stability. The comparison results show that the proposal model can effectively solve for feedback multiple parameters of dam concrete and rock material and basically satisfy assessment requirements for geotechnical structural engineering discipline.
机译:本文对复杂基础上的高拱坝总体稳定性进行了蚁群优化(D-ACO)分析。为获得大坝混凝土和岩石力学参数,提出了一种改进的蚁群优化模型。针对基于现场监测变形和ACO的非线性反分析数值模型,提出了典型的大坝参数反馈问题。该模型的基本原理是建立优化实际混凝土和岩石力学参数的目标函数。然后使用改进的蚁群算法实施反馈分析。算法性能令人满意,验证了准确性。讨论了用于运行非线性FEM代码的m组反馈参数以及位移和应力分布。还基于改进的蚁群优化方法对李家峡拱坝的变形进行了反馈分析。通过考虑使用不同分析方法获得的各种材料参数,对大坝位移,应力分布特征和大坝整体稳定性进行了比较分析。对比结果表明,该建议模型可以有效地解决大坝混凝土和岩石材料的多个参数反馈问题,基本满足岩土结构工程学科的评估要求。

著录项

  • 期刊名称 other
  • 作者单位
  • 年(卷),期 -1(2014),-1
  • 年度 -1
  • 页码 483243
  • 总页数 14
  • 原文格式 PDF
  • 正文语种
  • 中图分类
  • 关键词

  • 入库时间 2022-08-21 11:18:30

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