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Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography

Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this wor...

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Autores principales: Chen, Wei, Wei, Kesen, Wei, Jincheng, Han, Wenyang, Zhang, Xiaomeng, Hu, Guiling, Wei, Shuaishuai, Niu, Lei, Chen, Kai, Fu, Zhi, Xu, Xizhong, Xu, Baogui, Cui, Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227256/
https://www.ncbi.nlm.nih.gov/pubmed/35744369
http://dx.doi.org/10.3390/ma15124309
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author Chen, Wei
Wei, Kesen
Wei, Jincheng
Han, Wenyang
Zhang, Xiaomeng
Hu, Guiling
Wei, Shuaishuai
Niu, Lei
Chen, Kai
Fu, Zhi
Xu, Xizhong
Xu, Baogui
Cui, Ting
author_facet Chen, Wei
Wei, Kesen
Wei, Jincheng
Han, Wenyang
Zhang, Xiaomeng
Hu, Guiling
Wei, Shuaishuai
Niu, Lei
Chen, Kai
Fu, Zhi
Xu, Xizhong
Xu, Baogui
Cui, Ting
author_sort Chen, Wei
collection PubMed
description Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this work, we used unmanned aerial vehicle infrared thermal imaging technology to monitor the construction work. By analyzing the temperature distribution at the paving site, and conducting laboratory tests, the relationship between the melt temperature, high-temperature stability, and water stability of the asphalt mix was assessed. The results showed that the optimal temperature measurement height for an unmanned aerial vehicle (UAV) with an infrared thermal imager was 7–8 m. By coring the representative temperature points on the construction site and then conducting a Hamburg wheel tracking (HWT) test, the test results were verified through the laboratory test results in order to establish a prediction model for the melt temperature and high-temperature stability of y = 10.73e(0.03x) + 1415.78, where the predictive model for the melt temperature and water was y = −19.18e(−0.02x) + 98.03. The results showed that using laboratory tests combined with UAV infrared thermography could quickly and accurately predict the road performance of asphalt mixtures during paving. We hope that more extensive evaluations of the roadworthiness of asphalt mixtures using paving temperatures will provide reference recommendations in the future.
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spelling pubmed-92272562022-06-25 Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography Chen, Wei Wei, Kesen Wei, Jincheng Han, Wenyang Zhang, Xiaomeng Hu, Guiling Wei, Shuaishuai Niu, Lei Chen, Kai Fu, Zhi Xu, Xizhong Xu, Baogui Cui, Ting Materials (Basel) Article Temperature segregation during the paving of asphalt pavements is one of the causes of asphalt pavement distress. Therefore, controlling the paving temperature is crucial in the construction of asphalt pavements. To quickly evaluate the road performance of asphalt mixtures during paving, in this work, we used unmanned aerial vehicle infrared thermal imaging technology to monitor the construction work. By analyzing the temperature distribution at the paving site, and conducting laboratory tests, the relationship between the melt temperature, high-temperature stability, and water stability of the asphalt mix was assessed. The results showed that the optimal temperature measurement height for an unmanned aerial vehicle (UAV) with an infrared thermal imager was 7–8 m. By coring the representative temperature points on the construction site and then conducting a Hamburg wheel tracking (HWT) test, the test results were verified through the laboratory test results in order to establish a prediction model for the melt temperature and high-temperature stability of y = 10.73e(0.03x) + 1415.78, where the predictive model for the melt temperature and water was y = −19.18e(−0.02x) + 98.03. The results showed that using laboratory tests combined with UAV infrared thermography could quickly and accurately predict the road performance of asphalt mixtures during paving. We hope that more extensive evaluations of the roadworthiness of asphalt mixtures using paving temperatures will provide reference recommendations in the future. MDPI 2022-06-17 /pmc/articles/PMC9227256/ /pubmed/35744369 http://dx.doi.org/10.3390/ma15124309 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Wei
Wei, Kesen
Wei, Jincheng
Han, Wenyang
Zhang, Xiaomeng
Hu, Guiling
Wei, Shuaishuai
Niu, Lei
Chen, Kai
Fu, Zhi
Xu, Xizhong
Xu, Baogui
Cui, Ting
Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
title Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
title_full Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
title_fullStr Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
title_full_unstemmed Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
title_short Research on the Road Performance of Asphalt Mixtures Based on Infrared Thermography
title_sort research on the road performance of asphalt mixtures based on infrared thermography
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227256/
https://www.ncbi.nlm.nih.gov/pubmed/35744369
http://dx.doi.org/10.3390/ma15124309
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