Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams
Joint grouting simulation is an important aspect of arch dam construction simulation. However, the current construction simulation model simplifies the temperature factors in joint grouting simulation, which leads to the difference between the simulation results and the actual construction schedule....
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-08-01
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| Series: | Energies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1996-1073/13/17/4487 |
| _version_ | 1797555008328171520 |
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| author | Wenshuai Song Tao Guan Bingyu Ren Jia Yu Jiajun Wang Binping Wu |
| author_facet | Wenshuai Song Tao Guan Bingyu Ren Jia Yu Jiajun Wang Binping Wu |
| author_sort | Wenshuai Song |
| collection | DOAJ |
| description | Joint grouting simulation is an important aspect of arch dam construction simulation. However, the current construction simulation model simplifies the temperature factors in joint grouting simulation, which leads to the difference between the simulation results and the actual construction schedule. Furthermore, the majority of existing temperature prediction research is based on deterministic point predictions, which cannot quantify the uncertainties of the prediction values. Thus, this study presents a real-time construction simulation method coupling a concrete temperature field interval prediction model to address these problems. First, a real-time construction simulation model is established. Secondly, this paper proposes a concrete temperature interval prediction method based on the hybrid-kernel relevance vector machine (HK-RVM) with the improved grasshopper optimization algorithm (IGOA). The hybrid-kernel method is adopted to ensure the prediction accuracy and generalization ability of the model. Additionally, the improved grasshopper optimization algorithm (IGOA), which utilizes the tent chaotic map and cosine adaptive method to improve the algorithm performance, is developed for the parameter optimization of HK-RVM. Thirdly, concept drift detection based on variable window technology is proposed to update the prediction model. Finally, an arch dam project in China is used as a case study, by which the superiority and applicability of the proposed method are proven. |
| first_indexed | 2024-03-10T16:41:11Z |
| format | Article |
| id | doaj.art-cfdf4466186b481685a60ae6917c14da |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-03-10T16:41:11Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-cfdf4466186b481685a60ae6917c14da2023-11-20T12:04:08ZengMDPI AGEnergies1996-10732020-08-011317448710.3390/en13174487Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch DamsWenshuai Song0Tao Guan1Bingyu Ren2Jia Yu3Jiajun Wang4Binping Wu5State Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, ChinaState Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, ChinaState Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, ChinaState Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, ChinaState Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, ChinaState Key Laboratory of Hydraulic Engineering Simulation and Safety, Tianjin University, Tianjin 300350, ChinaJoint grouting simulation is an important aspect of arch dam construction simulation. However, the current construction simulation model simplifies the temperature factors in joint grouting simulation, which leads to the difference between the simulation results and the actual construction schedule. Furthermore, the majority of existing temperature prediction research is based on deterministic point predictions, which cannot quantify the uncertainties of the prediction values. Thus, this study presents a real-time construction simulation method coupling a concrete temperature field interval prediction model to address these problems. First, a real-time construction simulation model is established. Secondly, this paper proposes a concrete temperature interval prediction method based on the hybrid-kernel relevance vector machine (HK-RVM) with the improved grasshopper optimization algorithm (IGOA). The hybrid-kernel method is adopted to ensure the prediction accuracy and generalization ability of the model. Additionally, the improved grasshopper optimization algorithm (IGOA), which utilizes the tent chaotic map and cosine adaptive method to improve the algorithm performance, is developed for the parameter optimization of HK-RVM. Thirdly, concept drift detection based on variable window technology is proposed to update the prediction model. Finally, an arch dam project in China is used as a case study, by which the superiority and applicability of the proposed method are proven.https://www.mdpi.com/1996-1073/13/17/4487arch damconstruction simulationconcrete temperature fieldinterval predictionrelevance vector machinegrasshopper optimization algorithm |
| spellingShingle | Wenshuai Song Tao Guan Bingyu Ren Jia Yu Jiajun Wang Binping Wu Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams Energies arch dam construction simulation concrete temperature field interval prediction relevance vector machine grasshopper optimization algorithm |
| title | Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams |
| title_full | Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams |
| title_fullStr | Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams |
| title_full_unstemmed | Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams |
| title_short | Real-Time Construction Simulation Coupling a Concrete Temperature Field Interval Prediction Model with Optimized Hybrid-Kernel RVM for Arch Dams |
| title_sort | real time construction simulation coupling a concrete temperature field interval prediction model with optimized hybrid kernel rvm for arch dams |
| topic | arch dam construction simulation concrete temperature field interval prediction relevance vector machine grasshopper optimization algorithm |
| url | https://www.mdpi.com/1996-1073/13/17/4487 |
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