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Artificial Life for Pavement Distress Survey
Key Engineering Materials, 2005Automatic recognition of road distresses is of considerable interest since it facilitates road maintenance. We propose the use of artificial life for pavement distress survey. All artificial organisms in the artificial life algorithm exhibit the principle of cooperation which can be found in computer virtues and the hunting process of predators ...
Qi Wang, Hui Zhang
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Contracting for Pavement Distress Data Collection
Transportation Research Record: Journal of the Transportation Research Board, 1998Many agencies responsible for managing pavements have adopted pavement management systems (PMS) to help manage their pavement networks more cost-effectively. One of the most costly parts of operating a PMS is collecting condition information, especially pavement distress information.
Roger E. Smith +2 more
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A Framework for Premature Pavement Distress Evaluation
IFCEE 2015, 2015As part of a major rehabilitation program in 2001, several pavement sections of the Arkansas Interstate system was rubblized and overlayed. Recently, some of these sections west of Little Rock on Interstate-40 (I-40) experienced severe distresses (cracking, potholes, and roughness).
Nazmul Chowdhury +3 more
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Airport Pavement Distress Analysis
Iranian Journal of Science and Technology, Transactions of Civil Engineering, 2023Hamid Noori, Raju Sarkar
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Solution for Distressed Pavements and Crack Reflection
Transportation Research Record: Journal of the Transportation Research Board, 2003It is commonly accepted that cracks in aged asphalt pavements will reflect through seal coat and overlay applications. Pavement fabric placed under asphalt concrete overlays will slow this crack reflection, but not stop it. Nineteen years of experience working with the same fabric under a double chip seal has shown that using a modified technique ...
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Pavement Distress Under Accelerated Trafficking
Transportation Research Record: Journal of the Transportation Research Board, 1998A test pad was closely monitored for a 6-month period, with 640,000 axle load repetitions applied to the test pavement. The load was applied by the Texas Mobile Load Simulator, a full-scale accelerated loading device. Pavement performance data, such as rutting and cracking, were collected at intervals of 0; 2,500; 5,000; 10,000; 20,000; 40,000; 80,000;
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Pavement distress detection using convolutional neural networks with images captured via UAV
Automation in Construction, 2022, Tao Ma, Junqing Zhu
exaly
Pavement distress detection and classification based on YOLO network
International Journal of Pavement Engineering, 2021Yu Shen, Yuchuan Du
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