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Prediction equations for estimating maximum lateral displacement and settlement of geosynthetic reinforced soil abutments
Computers and Geotechnics ( IF 5.3 ) Pub Date : 2020-09-01 , DOI: 10.1016/j.compgeo.2020.103622
Mahsa Khosrojerdi , Ming Xiao , Tong Qiu , Jennifer Nicks

Abstract The Geosynthetic Reinforced Soil Integrated Bridge System (GRS-IBS), which consists of closely-spaced layers of geosynthetic reinforcement and compacted granular fill material, is a fast, sustainable and cost-effective method for bridge support. The in-service performance of this innovative bridge support system is largely evaluated through the vertical and horizontal deformations of the GRS abutments. This paper presents the development of nonlinear equations for estimating the maximum lateral displacement and settlement of GRS abutments. The parameters that are considered in the prediction equations include abutment geometry (height, facing batter and foundation width), backfill friction angle, reinforcement characteristics (stiffness, spacing, and length), and applied static loads from 50 to 400 kPa. In the development of the prediction equations, a parametric study was first conducted using a validated finite difference numerical model. The results of the parametric study were then used to conduct a regression analysis to develop the equations for estimating the maximum lateral displacement and settlement of GRS abutments under service loads. The equations were validated using three case studies. The developed prediction equations can contribute to a better understanding and enable simple calculations in designing these structures.

中文翻译:

估计土工合成材料加筋土台肩最大横向位移和沉降的预测方程

摘要 土工合成材料加筋土综合桥系统 (GRS-IBS) 由紧密排列的土工合成材料加筋层和压实的粒状填充材料组成,是一种快速、可持续和具有成本效益的桥梁支撑方法。这种创新的桥梁支撑系统的使用性能主要通过 GRS 桥台的垂直和水平变形进行评估。本文介绍了用于估计 GRS 桥台最大横向位移和沉降的非线性方程的发展。预测方程中考虑的参数包括桥台几何形状(高度、面糊和基础宽度)、回填摩擦角、钢筋特性(刚度、间距和长度)以及 50 到 400 kPa 的施加静载荷。在预测方程的开发过程中,首先使用经过验证的有限差分数值模型进行了参数研究。然后使用参数研究的结果进行回归分析,以开发用于估计 GRS 桥台在使用载荷下的最大侧向位移和沉降的方程。这些方程使用三个案例研究进行了验证。开发的预测方程有助于更好地理解并在设计这些结构时进行简单的计算。这些方程使用三个案例研究进行了验证。开发的预测方程有助于更好地理解并在设计这些结构时进行简单的计算。这些方程使用三个案例研究进行了验证。开发的预测方程有助于更好地理解并在设计这些结构时进行简单的计算。
更新日期:2020-09-01
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