Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network

Objective The soil solidification technique is widely used in soft foundation treatment. To exploit spatial plasticity of this technique, composite slab wall soil solidification foundations have gradually been applied in engineering projects. However, a reliable method for calculating the bearing capacity of composite slab wall soil solidification foundations is lack, and the mechanical parameters of both solidified and soft soil remain uncertain. These factors complicate the optimization of the composite slab wall soil solidification foundation designs. Therefore, it is crucial to propose a method for calculating the bearing capacity and optimizing the design of such foundations. Methods This study focuses on the 110 kV Jingwei coastal substation in Taizhou, Zhejiang Province. A numerical model is established based on the mechanical parameters of solidified and soft soil to calculate the bearing capacity of composite slab wall soil solidification foundations. The results of these calculations are used to train a neural network, enabling predictions of the bearing capacity for various design parameters, thus facilitating engineering applications. Uncertainties of the mechanical parameters are addressed through Monte Carlo simulations, and their impact on design is estimated using the robustness evaluation index standard deviation. The design cost is approximately estimated by the cross-sectional area of the foundation. Robust design theory is introduced to optimize the design while balancing cost-effectiveness and robustness. Results This method is implemented in an engineering project, resulting in an optimal design with solidified plate thickness P=2 m, solidified wall depth W=3 m, solidified wall thickness D=1.5 m, solidified wall net spacing S=1 m, and upper foundation width B=4 m, providing a reference for engineering designs. Conclusion The proposed methods for calculating bearing capacity and optimizing the design of composite slab wall soil solidification foundations offer new concepts and approaches for similar projects.

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-11-01
DOI
https://doi.org/10.19509/j.cnki.dzkq.tb20230720
Primary Topic
Geotechnical Engineering and Soil Stabilization
Type
article
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article

Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network

SHILAP Revista de lepidopterología
Geotechnical Engineering and Soil Stabilization
article

Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network

article en

Abstract

Objective The soil solidification technique is widely used in soft foundation treatment. To exploit spatial plasticity of this technique, composite slab wall soil solidification foundations have gradually been applied in engineering projects. However, a reliable method for calculating the bearing capacity of composite slab wall soil solidification foundations is lack, and the mechanical parameters of both solidified and soft soil remain uncertain. These factors complicate the optimization of the composite slab wall soil solidification foundation designs. Therefore, it is crucial to propose a method for calculating the bearing capacity and optimizing the design of such foundations. Methods This study focuses on the 110 kV Jingwei coastal substation in Taizhou, Zhejiang Province. A numerical model is established based on the mechanical parameters of solidified and soft soil to calculate the bearing capacity of composite slab wall soil solidification foundations. The results of these calculations are used to train a neural network, enabling predictions of the bearing capacity for various design parameters, thus facilitating engineering applications. Uncertainties of the mechanical parameters are addressed through Monte Carlo simulations, and their impact on design is estimated using the robustness evaluation index standard deviation. The design cost is approximately estimated by the cross-sectional area of the foundation. Robust design theory is introduced to optimize the design while balancing cost-effectiveness and robustness. Results This method is implemented in an engineering project, resulting in an optimal design with solidified plate thickness P=2 m, solidified wall depth W=3 m, solidified wall thickness D=1.5 m, solidified wall net spacing S=1 m, and upper foundation width B=4 m, providing a reference for engineering designs. Conclusion The proposed methods for calculating bearing capacity and optimizing the design of composite slab wall soil solidification foundations offer new concepts and approaches for similar projects.

SHILAP Revista de lepidopterología
Openalex Percentile: Top 65%
Geotechnical Engineering and Soil Stabilization
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