Numerical study on geocell reinforced poor sand-based ground improvement using jellyfish optimisation algorithm
by S. Jeyanthi; R. Venkatakrishnaiah; K.V.B. Raju
International Journal of Applied Nonlinear Science (IJANS), Vol. 4, No. 2, 2024

Abstract: Due to the lack of widely accessible, ideal development sites in city centres, problematic areas with low load-bearing deposits are more widespread. Granular fill layers are widely employed as a solution to difficult soils. Coating poor soil with compacted solid replacement improves its behaviour. Despite geosynthetics' evident reinforcing potential, most investigations have focused on its permanent deformation. Jellyfish search algorithm (JSA) optimisation and geocell reinforced soil foundation assessed unstable sand bearing capability. Compressed granular infill over clay soil supported the sand. Data for the optimisation models was acquired in the field through techniques like in-situ soil testing. An insufficient foundation of sand-based geocell-reinforced soil serves as an input to a JSA algorithm that controls the pressure in the base isolator. Pressure, stiffness, and bearing capacity of a geocell-reinforced soil structure were calculated numerically. The proposed method uses MATLAB. According to numerical data, decreasing negative soil effects considerably affects geocell-reinforced soil foundation performance. Determine the optimal geocell foundation properties to reduce settlement and pressure.

Online publication date: Mon, 04-Mar-2024

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