Machine learning-based seismic assessment of framed structures with soil-structure interaction

The objective of the current study is to propose an expert system framework based on a supervised machine learning technique (MLT) to predict the seismic performance of low- to mid-rise frame structures considering soil-structure interaction (SSI). The methodology of the framework is based on examining different MLTs to obtain the highest possible accuracy for prediction. Within the MLT, a sensitivity analysis was conducted on the main SSI parameters to select the most effective input parameters. Multiple limit state criteria were used for the seismic evaluation within the process. A new global seismic assessment ratio was introduced that considers both serviceability and strength aspects by utilizing three different engineering demand parameters (EDPs). The proposed framework is novel because it enables the designer to seismically assess the structure, while simultaneously considering different EDPs and multiple limit states. Moreover, the framework provides recommendations for building component design based on the newly introduced global seismic assessment ratio, which considers different levels of seismic hazards. The proposed framework was validated through comparison using non-linear time history (NLTH) analysis. The results show that the proposed framework provides more accurate results than conventional methods. Finally, the generalization potential of the proposed framework was tested by investigating two different types of structural irregularities, namely, stiffness and mass irregularities. The results from the framework were in good agreement with the NLTH analysis results for the selected case studies, and peak ground acceleration (PGA) was found to be the most influential input parameter in the assessment process for the case study models investigated. The proposed framework shows high generalization potential for low- to mid-rise structures.     

吉贾尔-帕坦喀喇昆仑公路沿线落石和边坡稳定性数值研究

在中巴经济走廊的重要通道喀喇昆仑公路（KKH）沿线，由于构造运动和降雨渗透对破碎岩石和边坡稳定性的不利作用，造成了大量落石和不稳定边坡。利用数值软件DIPS、GeoRock 2D和SLIDE对巴基斯坦北部吉贾尔-帕坦喀喇昆仑公路沿线的落石和边坡稳定性进行了数值研究；以喀喇昆仑公路沿线两个主要的易受落石影响的路段为例，研究落石和边坡的失稳机理。对4组节理进行的赤平投影分析表明：两处边坡断面均易发生平面破坏和楔形破坏。基于极限平衡理论，在静力条件下，边坡断面1的安全系数为0.917，处于不稳定状态，边坡断面2的安全系数为1.131，处于欠稳定状态；但在地震条件下，两处断面边坡的安全系数均小于1，处于不稳定状态。研究结果表明，边坡断面1和断面2的落石回弹高度分别为33 m和29 m。边坡断面1的落石速度在0.5~44 m/s，总动能达到1 135.099 kJ，而边坡断面2的落石具有0.5~40.901 m/s的速度和973.012 kJ的破坏能力。研究表明，KKH沿线的落石和滑坡具有极大的破坏潜力。