基于CNN闸泵站共体式结构变形预测的全局敏感性分析
Global Sensitivity Analysis for CNN Based Deformation Prediction of A Cohesive Structure of A Sluice and Pumping Station
周兰庭 1闫占宇 1顾晓峰 2孙永明 2张旭2
作者信息
- 1. 河海大学水利水电学院,江苏 南京 210098
- 2. 江苏省太湖水利规划设计研究院有限公司,江苏 苏州 215103
- 折叠
摘要
针对设计阶段传统的结构变形敏感性分析计算成本较大的问题,引入了CNN模型,预测在不同材料参数和水位条件下闸泵站共体式结构的变形,并对所建模型进行全局敏感性分析,从而大幅降低计算成本.首先通过ANSYS的PDS模块计算出200组结构变形数据,并基于这些数据构建和训练CNN结构变形预测模型,随后运用Sobol法分析设计参数对结构变形的敏感性.结果表明,闸泵站共体式结构的变形以沉降为主,在竖直方向上的位移受复合地基弹性模量的影响较大,在顺河向和横河向上的位移受上下水位影响较大,结构的最大应力受上下游水深和混凝土弹性模量影响较大.研究结果可为相关设计提供参考依据.
Abstract
Aiming at the problem of large computational cost of traditional structural deformation sensitivity analysis in the design stage,this paper constructed a CNN model to predict the structural deformation of the sluice and pumping station cohesive structure under different material parameters and water levels,and conducted global sensitivity analysis based on the proposed model,which greatly saved the computational cost.Firstly,200 sets of structural deformation data were calculated by the PDS module of ANSYS,and the CNN structural deformation prediction model was constructed and trained on the basis of these data.Then,the sensitivity relationship of the design parameters to the structural deformation was analysed by using the Sobol method.The results show that the structural deformation of the sluice and pumping sta-tion co-composite structure is dominated by settlement,and the displacements in vertical direction are greatly affected by the elasticity modulus of composite foundation;The displacement in the upstream and downstream directions is affected by the upstream and downstream water levels;The maximum stress of the structure is affected by the upstream and downstream water depths and the modulus of elasticity of the concrete.The results of this analysis provide a reference ba-sis for the related design work.
关键词
闸泵站共体/CNN/敏感性分析/Sobol序列抽样/有限元分析Key words
cohesive structure of sluice pumping station/CNN/sensitivity analysis/Sobol sequence sampling/finite element analysis引用本文复制引用
基金项目
国家自然科学基金项目(51739003)
江苏省水利科技项目(2022085)
出版年
2024
NETL
NSTL
万方数据