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A platform for research: civil engineering, architecture and urbanism
Nonlinear Equation for Predicting the Settlement of Reinforced Soil Foundations
A reinforced soil foundation (RSF) consists of layers of geosynthetic reinforcement and compacted granular fill material. The RSF approach is a fast, sustainable, and economical alternative to shallow foundation design. This paper presents the development of a prediction equation for estimating the settlement of footings placed on reinforced soil. The parameters that are considered in the prediction equation include footing geometry (width and length), soil friction angle and cohesion, reinforcement characteristics (stiffness, spacing, length, and number of reinforcement layers), and applied static loads from 50 to 600 kPa. For the prediction equation development, 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 prediction equation for estimating the maximum settlement of RSF. The equation was validated using three case studies. The developed prediction equation will be useful for practitioners in preliminary RSF design.
Nonlinear Equation for Predicting the Settlement of Reinforced Soil Foundations
A reinforced soil foundation (RSF) consists of layers of geosynthetic reinforcement and compacted granular fill material. The RSF approach is a fast, sustainable, and economical alternative to shallow foundation design. This paper presents the development of a prediction equation for estimating the settlement of footings placed on reinforced soil. The parameters that are considered in the prediction equation include footing geometry (width and length), soil friction angle and cohesion, reinforcement characteristics (stiffness, spacing, length, and number of reinforcement layers), and applied static loads from 50 to 600 kPa. For the prediction equation development, 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 prediction equation for estimating the maximum settlement of RSF. The equation was validated using three case studies. The developed prediction equation will be useful for practitioners in preliminary RSF design.
Nonlinear Equation for Predicting the Settlement of Reinforced Soil Foundations
Khosrojerdi, Mahsa (author) / Xiao, Ming (author) / Qiu, Tong (author) / Nicks, Jennifer (author)
2019-02-18
Article (Journal)
Electronic Resource
Unknown
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