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<p>Waste materials like flyash, bottom ash, slag and construction and demolition (C&amp;D) debris are generated at a rapid rate creating problems of disposal and environmental degradation. Reuse of these materials as foundation medium or as backfilling reduces disposal problems which paves way for sustainable construction. Soil reinforcement with the use of geosynthetics is a method globally practiced for earth reinforcement in geotechnical engineering applications. This study is aimed at exploring the performance of natural and synthetic reinforcements on Waste Foundry Sand (WFS). This waste being generated from foundry industries would otherwise lead to land disposal problems. Natural Bamboo material in the form of reinforcement is gaining attention. This has been used recently as the tensile strength of the material is higher than the commercial geogrid material. This helps in the lateral restraint and stability of the reinforced foundation system thereby enhancing the bearing capacity. This research focuses on the identification of ideal geometric parameters of reinforcements with the objective of enhancing the load bearing capacity. The laboratory model test results have identified depths of reinforcement, diameters of the reinforcing layers and the spacing between the reinforcement layers as the key elements for the increased Bearing capacity ratio (BCR). The optimal geometric parameters are determined as u/B = 0.25, D/B = 3, h/B = 0.25 &amp; 0.5, and l/B = 0.6. Bamboo grids offered higher bearing capacity which is 16–23% more than geogrid reinforced sand. PLAXIS 3D numerical modeling was also performed in addition to the experimental program to study the stress distribution and deformation behaviour of reinforced system and the BCR was obtained. The results of BCR in the case of bamboo grid and for the optimal parameters u/B = 0.25, D/B = 3, h/B = 0.25 &amp; 0.5 are respectively 4.53, 4.50 and 6.24 which are slightly higher than that of geogrid. A hybrid Finite Basis Physics-Informed Neural Networks (FBPINN) and Seahorse Optimization (SHO) framework were used to estimate the BCR for the optimized reinforcement parameters and the predicted model showed R<sup>2</sup> of 0.98.</p>

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Evaluation of geogrid and bamboo grid reinforcements on the performance of circular footing on waste foundry sand

  • 期刊论文

  • 发表日期：

    2026年5月13日

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  • V. Jayanthi,
  • S. P. Jeyapriya,
  • J. S. Sudarsan,
  • S. Nithiyanantham

摘要

Waste materials like flyash, bottom ash, slag and construction and demolition (C&D) debris are generated at a rapid rate creating problems of disposal and environmental degradation. Reuse of these materials as foundation medium or as backfilling reduces disposal problems which paves way for sustainable construction. Soil reinforcement with the use of geosynthetics is a method globally practiced for earth reinforcement in geotechnical engineering applications. This study is aimed at exploring the performance of natural and synthetic reinforcements on Waste Foundry Sand (WFS). This waste being generated from foundry industries would otherwise lead to land disposal problems. Natural Bamboo material in the form of reinforcement is gaining attention. This has been used recently as the tensile strength of the material is higher than the commercial geogrid material. This helps in the lateral restraint and stability of the reinforced foundation system thereby enhancing the bearing capacity. This research focuses on the identification of ideal geometric parameters of reinforcements with the objective of enhancing the load bearing capacity. The laboratory model test results have identified depths of reinforcement, diameters of the reinforcing layers and the spacing between the reinforcement layers as the key elements for the increased Bearing capacity ratio (BCR). The optimal geometric parameters are determined as u/B = 0.25, D/B = 3, h/B = 0.25 & 0.5, and l/B = 0.6. Bamboo grids offered higher bearing capacity which is 16–23% more than geogrid reinforced sand. PLAXIS 3D numerical modeling was also performed in addition to the experimental program to study the stress distribution and deformation behaviour of reinforced system and the BCR was obtained. The results of BCR in the case of bamboo grid and for the optimal parameters u/B = 0.25, D/B = 3, h/B = 0.25 & 0.5 are respectively 4.53, 4.50 and 6.24 which are slightly higher than that of geogrid. A hybrid Finite Basis Physics-Informed Neural Networks (FBPINN) and Seahorse Optimization (SHO) framework were used to estimate the BCR for the optimized reinforcement parameters and the predicted model showed R2 of 0.98.