文章摘要
任秋兵,李明超,杜胜利,刘承照.筑坝堆石料抗剪强度间接测定模型与实用计算公式研究[J].水利学报,2019,50(10):1200-1213
筑坝堆石料抗剪强度间接测定模型与实用计算公式研究
Mathematical model and practical formula for indirect determination of shear strength of dam rockfill materials
投稿时间:2019-07-16  
DOI:10.13243/j.cnki.slxb.20190501
中文关键词: 筑坝堆石料  抗剪强度  间接测定  数学模型  实用公式  进化神经网络
英文关键词: dam rockfill materials  shear strength  indirect determination  mathematical model  practical formula  evolutionary neural networks
基金项目:国家重点研发计划项目(2018YFC0406905);国家优秀青年科学基金项目(51622904);国家自然科学基金面上项目(51879185)
作者单位E-mail
任秋兵 水利工程仿真与安全国家重点实验室, 天津大学, 天津 300354  
李明超 水利工程仿真与安全国家重点实验室, 天津大学, 天津 300354 LMC@tju.edu.cn 
杜胜利 水利工程仿真与安全国家重点实验室, 天津大学, 天津 300354  
刘承照 水利工程仿真与安全国家重点实验室, 天津大学, 天津 300354  
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中文摘要:
      筑坝堆石料的质量是堆石坝快速施工和安全运行的基础,坝料分区填筑前须进行大量堆石料物理力学性能基础试验,抗剪强度便是其中的一个关键指标。为提高积累数据利用率和节约试验成本,本文依托室内大型试验数据库和数据驱动方法,提出一种筑坝堆石料抗剪强度间接测定数学模型及其实用计算公式。首先收集源自世界各地的典型堆石料剪切试验资料,通过相关性分析和综合性成本型指标选取公式自变量;进而利用进化算法优化神经网络连接权重和阈值,结合hold-out泛化验证,构建最优多元非线性回归模型;最后根据神经网络理论提取回归模型关键参数,经推导得到堆石料抗剪强度计算公式,同时考虑工程应用特性,结合Garson算法建立一种兼具准确性和鲁棒性的公式简化应用方法。将上述模型方法应用于实际工程,结果表明所提公式对堆石料抗剪强度的推算准确率达到90%以上,可为筑坝堆石料抗剪强度测定提供一种有效辅助手段,从而减少部分重复性测试工作。
英文摘要:
      The quality of dam rockfill materials is the basis of the rapid construction and safe operation of rockfill dams. A large number of basic tests of physical and mechanical properties of rockfill must be carried out before district filling, and the determination of shear strength is one of the important test items. In order to improve the utilization rate of accumulated data and save the test cost,this paper presents the mathematical model and practical calculation formula for indirect determination of shear strength of dam rockfill materials based on the global database and data-driven method. Firstly,the shear test data of rockfill materials from all over the world are collected,and formula independent variables are selected with correlation analysis and comprehensive cost-type index. Secondly, the optimal multivariate nonlinear regression model is constructed by using the evolutionary algorithm to optimize the connection weights and threshold levels of neural networks and combining with hold-out generalization verification. Eventually,the key parameters of the regression model are extracted and the shear strength formula is derived based on the neural network theory. Considering the characteristics of engineering application, a formula simplification method with both accuracy and robustness is established by using Garson algorithm. The above method is applied to practical engineering,and the simulation results show that the accuracy of the proposed formula in calculating the shear strength of rockfill is more than 90%. The formula provides an effective auxiliary means for the determination of shear strength of rockfill,thereby reducing some repetitive test work.
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