Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration
Before the construction of the bridge bored pile in the karst area, geological conditions of the excavation area should be investigated. In order to avoid the karst caves in underground space making adverse impacts on the construction, bearing capacity, and stability of pile foundation, in this pape...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2022/1555877 |
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| author | Xue Liu Chunwei Pan Fangkun Zheng Ying Sun Qingsong Gou |
| author_facet | Xue Liu Chunwei Pan Fangkun Zheng Ying Sun Qingsong Gou |
| author_sort | Xue Liu |
| collection | DOAJ |
| description | Before the construction of the bridge bored pile in the karst area, geological conditions of the excavation area should be investigated. In order to avoid the karst caves in underground space making adverse impacts on the construction, bearing capacity, and stability of pile foundation, in this paper, we use the transient electromagnetic method to detect the karst development in the bearing layer of the pile foundation, which is different from the traditional karst survey method. To improve the interpretation accuracy of transient electromagnetic detection for karst caves, the quantum particle swarm optimization (QPSO) algorithm was combined with the smooth constrained least squares (CLS) algorithm, and the transient electromagnetic inversion based on the QPSO-CLS joint algorithm was generated. Better inversion results were achieved by the proposed method in this study. Based on the inversion calculation results of simulation data and field test data, it is further demonstrated that the QPSO-CLS joint algorithm has high optimization efficiency without manually setting the initial model. The interpretation results are consistent with the theoretical model and drilling logging results, which proves the adaptability of the proposed algorithm. |
| format | Article |
| id | doaj-art-489d527f14ca468b85ddadd837b6cb26 |
| institution | Kabale University |
| issn | 1687-8094 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-489d527f14ca468b85ddadd837b6cb262025-02-03T06:05:03ZengWileyAdvances in Civil Engineering1687-80942022-01-01202210.1155/2022/1555877Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst ExplorationXue Liu0Chunwei Pan1Fangkun Zheng2Ying Sun3Qingsong Gou4CCCC Fourth Harbor Engineering Institute Co., Ltd.Guangdong Transportation Industrial Investment Co., Ltd.CCCC Fourth Harbor Engineering Institute Co., Ltd.CCCC Fourth Harbor Engineering Institute Co., Ltd.Chongqing Institute of Geology and Mineral ResourcesBefore the construction of the bridge bored pile in the karst area, geological conditions of the excavation area should be investigated. In order to avoid the karst caves in underground space making adverse impacts on the construction, bearing capacity, and stability of pile foundation, in this paper, we use the transient electromagnetic method to detect the karst development in the bearing layer of the pile foundation, which is different from the traditional karst survey method. To improve the interpretation accuracy of transient electromagnetic detection for karst caves, the quantum particle swarm optimization (QPSO) algorithm was combined with the smooth constrained least squares (CLS) algorithm, and the transient electromagnetic inversion based on the QPSO-CLS joint algorithm was generated. Better inversion results were achieved by the proposed method in this study. Based on the inversion calculation results of simulation data and field test data, it is further demonstrated that the QPSO-CLS joint algorithm has high optimization efficiency without manually setting the initial model. The interpretation results are consistent with the theoretical model and drilling logging results, which proves the adaptability of the proposed algorithm.http://dx.doi.org/10.1155/2022/1555877 |
| spellingShingle | Xue Liu Chunwei Pan Fangkun Zheng Ying Sun Qingsong Gou Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration Advances in Civil Engineering |
| title | Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration |
| title_full | Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration |
| title_fullStr | Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration |
| title_full_unstemmed | Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration |
| title_short | Transient Electromagnetic 1-Dimensional Inversion Based on the Quantum Particle Swarms Optimization-Smooth Constrained Least Squares Joint Algorithm and Its Application in Karst Exploration |
| title_sort | transient electromagnetic 1 dimensional inversion based on the quantum particle swarms optimization smooth constrained least squares joint algorithm and its application in karst exploration |
| url | http://dx.doi.org/10.1155/2022/1555877 |
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