基于深部位移的蠕滑型滑坡预警指标及预警预报研究

基于边坡监测数据建立数学模型,是边坡变形和稳定性分析的重要方法。但是单一预测模型的形式和应用范围具有一定的确定性,不同模型对数据的利用程度也有所差别,往往不能充分运用已知信息,导致模型精度不高,适用性不强。针对单一预测模型存在的问题,提出一种基于熵权法的PSO-SVR-NGM优化组合模型。该模型结合高精度变权缓冲NGM(1,1,k,c)模型和PSO-SVR模型,能够减小单一预测模型的误差,大幅度提高预测精度。首先通过引入变权缓冲算子λ和背景值权重系数η、κ改进无偏NGM(1,1,k,c)模型,构建新的3参数变权缓冲NGM(1,1,k,c)模型。结合最大灰色关联度和最小平均相对拟合误差重新构造粒子群算法的适应度函数,利用改进的粒子群算法对提出的变权缓冲模型进行搜索寻优,确定最佳的参数组合。然后通过熵权法对改进的变权缓冲NGM(1,1,k,c)模型和PSO-SVR模型进行赋权建立优化组合模型。最后,将该组合模型应用于3个不同变形特征的边坡工程中,并与其他单一模型进行对比分析。结果表明,相对于单一模型,本文所提出的组合模型的拟合和预测误差较小,与原始位移数据的相关性较好,能够更真实地反映边坡变形规律,具有较强的工程适应性。同时组合模型的提出与发展也促进了单一模型的优化改进,为解决实际工程问题提供了良好的思路。     

Stress relaxation of grouted entirely large diameter B-GFRP soil nail

One of the potential solutions to steel-corrosion-related problems is the usage of fiber reinforced polymer (FRP) as a replacement of steel bars. In the past few decades, researchers have conducted a large number of experimental and theoretical studies on the behavior of small size glass fiber reinforce polymer (GFRP) bars (diameter smaller than 20 mm). However, the behavior of large size GFRP bar is still not well understood. Particularly, few studies were conducted on the stress relaxation of grouted entirely large diameter GFRP soil nail. This paper investigates the effect of stress levels on the relaxation behavior of GFRP soil nail under sustained deformation ranging from 30% to 60% of its ultimate strain. In order to study the behavior of stress relaxation, two B-GFRP soil nail element specimens were developed and instrumented with fiber Bragg grating (FBG) strain sensors which were used to measure strains along the B-GFRP bars. The test results reveal that the behavior of stress relaxation of B-GFRP soil nail element subjected to pre-stress is significantly related to the elapsed time and the initial stress of relaxation procedure. The newly proposed model for evaluating stress relaxation ratio can substantially reflect the influences of the nature of B-GFRP bar and the property of grip body. The strain on the nail body can be redistributed automatically. Modulus reduction is not the single reason for the stress degradation.     

基于随机有限元法的波致海床响应概率分析

波浪荷载作用下的海床响应是岩土工程领域的研究热点,波致海床液化是导致海床及结构物失稳的主要原因。针对海床响应分析中涉及的诸多不确定性因素,如沉积物参数的空间变异性以及荷载的随机性,建立了基于随机有限元方法的概率分析框架,将在MATLAB中实现的空间异质土体的模拟与在COMSOL中实现的孔隙弹性有限元分析通过LiveLink程序进行耦合。提出了一种分解的Karhunen-Loève（简称K-L）展开方法,该方法占用较少的计算时间和内存空间,使得高分辨率、大尺寸的三维随机场的模拟更加高效。应用上述概率框架分别对规则波浪荷载作用下的二维倾斜海床以及随机波浪荷载下的三维海床响应进行了研究,揭示了海床土体渗透系数K与剪切模量G的空间变异性以及波浪荷载随机性对孔隙水压力分布和海床液化深度的影响规律,表明了传统确定性分析方法将导致不安全的工程设计。