Application of FWD and GPR for Performance Evaluation of In‐Service Roads.
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| Title: | Application of FWD and GPR for Performance Evaluation of In‐Service Roads. |
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| Authors: | Hu, Zhi1 (AUTHOR), Yu, Yiqiang1 (AUTHOR) yuyqfj@163.com, Cheng, Xingliang2 (AUTHOR), Wu, Jianjun1 (AUTHOR), Chen, Jiayu3 (AUTHOR), Tang, Chuxuan2 (AUTHOR), Wei, Jintao1 (AUTHOR), Wang, Long3 (AUTHOR), Wang, Jialei3 (AUTHOR), Wang, Xing (AUTHOR) wangxing@xhu.edu.cn |
| Source: | Advances in Civil Engineering. 2/15/2026, Vol. 2026, p1-13. 13p. |
| Subjects: | Ground penetrating radar, Pavement testing, Structural analysis (Engineering), Genetic algorithms, Elastic modulus |
| Abstract: | Road performance detection typically encompasses structural strength testing and damage assessment, with the resilient modulus serving as a key indicator of structural integrity. To enhance the assessment of road performance, this study explores the combined application of falling weight deflectometer (FWD) and ground penetrating radar (GPR) in practical road projects. First, by integrating genetic algorithm (GA) with layered elastic theory (LET), the issue of traditional iterative inversion methods getting stuck in local optima is addressed. Subsequently, a test section of approximately 200 m on the Taizhou section of the Zhejiang Yongtaiwen Expressway was selected as the experimental road. FWD and GPR were used for comprehensive road performance detection, and the results were verified using portable lightweight deflectometer (LWD) tests. Finally, a comparative analysis was conducted on the influence of design layer thickness and GPR detection layer thickness as input parameters on the inversion results. The study concludes that the combined FWD and GPR road performance detection method effectively identifies road damage types and their distribution, significantly improving the inversion accuracy of road structural strength (resilient modulus). It was found that although using design layer thickness for inversion of the resilient modulus offers some reliability, the inversion accuracy for the surface and base layers significantly declines, whereas the effect on the subgrade is minimal. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Road performance detection typically encompasses structural strength testing and damage assessment, with the resilient modulus serving as a key indicator of structural integrity. To enhance the assessment of road performance, this study explores the combined application of falling weight deflectometer (FWD) and ground penetrating radar (GPR) in practical road projects. First, by integrating genetic algorithm (GA) with layered elastic theory (LET), the issue of traditional iterative inversion methods getting stuck in local optima is addressed. Subsequently, a test section of approximately 200 m on the Taizhou section of the Zhejiang Yongtaiwen Expressway was selected as the experimental road. FWD and GPR were used for comprehensive road performance detection, and the results were verified using portable lightweight deflectometer (LWD) tests. Finally, a comparative analysis was conducted on the influence of design layer thickness and GPR detection layer thickness as input parameters on the inversion results. The study concludes that the combined FWD and GPR road performance detection method effectively identifies road damage types and their distribution, significantly improving the inversion accuracy of road structural strength (resilient modulus). It was found that although using design layer thickness for inversion of the resilient modulus offers some reliability, the inversion accuracy for the surface and base layers significantly declines, whereas the effect on the subgrade is minimal. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 16878086 |
| DOI: | 10.1155/adce/1658554 |
