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李 泽, 杨元浩, 刘文连, 许汉华, 张小艳.基于溶蚀速率的灰岩边坡服役寿命研究水资源与水工程学报[J].,2023,34(4):183-190
基于溶蚀速率的灰岩边坡服役寿命研究
Service life of limestone slopes based on dissolution rate
  
DOI:10.11705/j.issn.1672-643X.2023.04.22
中文关键词:  灰岩边坡  服役寿命  溶蚀速率  边坡稳定性  非线性数学规划模型
英文关键词:limestone slope  service life  dissolution rate  slope stability  nonlinear mathematical programming model
基金项目:国家自然科学基金项目(12162018、12262016)
作者单位
李 泽1, 杨元浩1, 刘文连2, 许汉华2, 张小艳3 (1.昆明理工大学 建筑工程学院 云南 昆明 650500 2.中国有色金属工业昆明勘察设计研究院有限公司云南 昆明 650051 3.昆明理工大学 电力工程学院 云南 昆明 650500) 
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中文摘要:
      边坡服役寿命的预测能够定量、精确地评价灰岩边坡的长期安全性,但其预测模型尚未成熟。因此,为解决计算灰岩边坡服役寿命这一难题,提出基于溶蚀速率的灰岩边坡服役寿命优化计算方法。将灰岩边坡服役寿命作为目标函数,根据溶蚀速率和抗剪参数衰减速率计算灰岩边坡服役若干年后结构面贯通段和非贯通段的有效长度以及结构面的抗剪参数;结合滑体的平衡方程以及结构面贯通段和非贯通段的屈服条件,建立灰岩边坡长期服役的稳定性非线性数学规划模型,使用“序列二次规划法”求解数学规划模型,获得边坡的服役寿命。经验证,本文算法得出的边坡安全系数与有限元法数值模拟计算结果的平均相对误差为2.47%,表明本文算法能较为精确地预测灰岩边坡的服役寿命。
英文摘要:
      The prediction of slope service life can quantitatively and accurately evaluate the long-term safety of limestone slopes, but its prediction model is not yet fully developed. Therefore, in order to solve the problem of service life calculation of limestone slopes, an optimization method based on dissolution rate is proposed. Taking the service life of limestone slope as the objective function, the effective length of the penetrated section and non-penetrated section and the shear parameters of the structural surface after several years of service were calculated according to the dissolution rate and the attenuation rate of the shear parameters. Combined with the equilibrium equation of the sliding body and the yield conditions of the penetrated and non-penetrated section of the structural surface, the stable nonlinear mathematical programming model of the limestone slope for long-term service was established, and then the model was solved by the “sequential quadratic programming method” to obtain the service life of the slope. According to the comparison, the mean relative error between the numerical simulation results of the finite element method and the proposed algorithm is 2.47%, indicating that the algorithm can accurately predict the service life of limestone slopes.
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