A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads
The passage of superloads over the jointed plain concrete pavements (JPCPs) causes signification fatigue damage to the JPCPs. This mainly happens because of their non-standardized loading configurations and high gross vehicle and axle weights. Developing a high-accuracy prediction model for JPCP fat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/36/1/2 |
| _version_ | 1827306370596077568 |
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| author | Yongsung Koh Halil Ceylan Sunghwan Kim In Ho Cho |
| author_facet | Yongsung Koh Halil Ceylan Sunghwan Kim In Ho Cho |
| author_sort | Yongsung Koh |
| collection | DOAJ |
| description | The passage of superloads over the jointed plain concrete pavements (JPCPs) causes signification fatigue damage to the JPCPs. This mainly happens because of their non-standardized loading configurations and high gross vehicle and axle weights. Developing a high-accuracy prediction model for JPCP fatigue damage under superloads is strongly required to complement the mechanistic–empirical (ME) pavement design in aspects of its wide range of dimensions, including number, spacing, and loading of tires and axles. In this study, various data-driven models based on different theoretical approaches, including artificial neural network-based models, generalized additive models, and multiple linear regression models, were constructed using a well-established database derived from finite-element analysis results in order to predict the target response for JPCP fatigue damage when subjected to superloads. The prediction accuracies of these data-driven models were then evaluated to confirm their further applicability to the existing ME pavement design software. |
| first_indexed | 2024-04-24T18:20:26Z |
| format | Article |
| id | doaj.art-926b5973e58b4403ba43db9a39651aa5 |
| institution | Directory Open Access Journal |
| issn | 2673-4591 |
| language | English |
| last_indexed | 2024-04-24T18:20:26Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj.art-926b5973e58b4403ba43db9a39651aa52024-03-27T13:36:25ZengMDPI AGEngineering Proceedings2673-45912023-06-01361210.3390/engproc2023036002A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to SuperloadsYongsung Koh0Halil Ceylan1Sunghwan Kim2In Ho Cho3Department of Civil, Construction and Environmental Engineering (CCEE), Iowa State University, Ames, IA 50011, USADepartment of Civil, Construction and Environmental Engineering (CCEE), Iowa State University, Ames, IA 50011, USAInstitute for Transportation, Iowa State University, Ames, IA 50011, USADepartment of Civil, Construction and Environmental Engineering (CCEE), Iowa State University, Ames, IA 50011, USAThe passage of superloads over the jointed plain concrete pavements (JPCPs) causes signification fatigue damage to the JPCPs. This mainly happens because of their non-standardized loading configurations and high gross vehicle and axle weights. Developing a high-accuracy prediction model for JPCP fatigue damage under superloads is strongly required to complement the mechanistic–empirical (ME) pavement design in aspects of its wide range of dimensions, including number, spacing, and loading of tires and axles. In this study, various data-driven models based on different theoretical approaches, including artificial neural network-based models, generalized additive models, and multiple linear regression models, were constructed using a well-established database derived from finite-element analysis results in order to predict the target response for JPCP fatigue damage when subjected to superloads. The prediction accuracies of these data-driven models were then evaluated to confirm their further applicability to the existing ME pavement design software.https://www.mdpi.com/2673-4591/36/1/2superloadjointed plain concrete pavementfatigue crackingfinite element analysisdata-driven model |
| spellingShingle | Yongsung Koh Halil Ceylan Sunghwan Kim In Ho Cho A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads Engineering Proceedings superload jointed plain concrete pavement fatigue cracking finite element analysis data-driven model |
| title | A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads |
| title_full | A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads |
| title_fullStr | A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads |
| title_full_unstemmed | A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads |
| title_short | A Data-Driven Approach for Fatigue Damage Prediction in Jointed Plain Concrete Pavement Subjected to Superloads |
| title_sort | data driven approach for fatigue damage prediction in jointed plain concrete pavement subjected to superloads |
| topic | superload jointed plain concrete pavement fatigue cracking finite element analysis data-driven model |
| url | https://www.mdpi.com/2673-4591/36/1/2 |
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