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 ca...
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Editorial Department of Bulletin of Geological Science and Technology
2024-11-01
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| Series: | 地质科技通报 |
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| Online Access: | https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20230720 |
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| author | Linggang ZHOU Yiting HU Xinwei CHEN Feng TU Zhaofeng WU Yang YU Yanbing WANG Yin MAN Weichao LI |
| author_facet | Linggang ZHOU Yiting HU Xinwei CHEN Feng TU Zhaofeng WU Yang YU Yanbing WANG Yin MAN Weichao LI |
| author_sort | Linggang ZHOU |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d95b8588ba29461f87a0624f4ce8e63a |
| institution | OA Journals |
| issn | 2096-8523 |
| language | zho |
| publishDate | 2024-11-01 |
| publisher | Editorial Department of Bulletin of Geological Science and Technology |
| record_format | Article |
| series | 地质科技通报 |
| spelling | doaj-art-d95b8588ba29461f87a0624f4ce8e63a2025-08-20T01:56:31ZzhoEditorial Department of Bulletin of Geological Science and Technology地质科技通报2096-85232024-11-0143610211310.19509/j.cnki.dzkq.tb20230720dzkjtb-43-6-102Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural networkLinggang ZHOU0Yiting HU1Xinwei CHEN2Feng TU3Zhaofeng WU4Yang YU5Yanbing WANG6Yin MAN7Weichao LI8State Grid Zhejiang Taizhou Power Supply Company, Taizhou Zhejiang 318001, ChinaState Grid Zhejiang Taizhou Power Supply Company, Taizhou Zhejiang 318001, ChinaOcean College, Zhejiang University, Zhoushan Zhejiang 316021, ChinaState Grid Zhejiang Electric Power Company, Hangzhou 310007, ChinaChina Engineering Group Zhejiang Power Design Institute Co., Ltd., Hangzhou 310014, ChinaOcean College, Zhejiang University, Zhoushan Zhejiang 316021, ChinaState Power Economic Research Institute Co. Ltd., Beijing 102200, ChinaChina Electric Power Research Institute, Beijing 100192, ChinaChina Institute of Water Resources and Hydropower Research, Beijing 100038, ChinaObjective 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.https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20230720soil solidification foundationneural networkbearing capacityrobust designsoft soil solidificationcomposite slab wall |
| spellingShingle | Linggang ZHOU Yiting HU Xinwei CHEN Feng TU Zhaofeng WU Yang YU Yanbing WANG Yin MAN Weichao LI Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network 地质科技通报 soil solidification foundation neural network bearing capacity robust design soft soil solidification composite slab wall |
| title | Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network |
| title_full | Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network |
| title_fullStr | Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network |
| title_full_unstemmed | Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network |
| title_short | Calculation of capacity and optimization design-composite slab wall soil solidification foundation based on neural network |
| title_sort | calculation of capacity and optimization design composite slab wall soil solidification foundation based on neural network |
| topic | soil solidification foundation neural network bearing capacity robust design soft soil solidification composite slab wall |
| url | https://dzkjqb.cug.edu.cn/en/article/doi/10.19509/j.cnki.dzkq.tb20230720 |
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