A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Optimized Analysis of Airport Flexible Pavement Instrumentation Response
The National Airport Pavement Test Facility is a state-of-the-art, full-scale testing facility for airport pavements operated by the Federal Aviation Administration. The primary purpose of this program is to advance airfield pavement design methodologies by understanding pavement behavior under aircraft loading. This chapter presents the findings of an exploratory data analysis, visualization, and summary of flexible pavements tested in construction cycles 1 and 3. Each construction cycle serves a specific objective and is split into multiple test sections. Both dynamic data (i.e., stress, strain, and deflection) and static data (i.e., temperature and moisture) were analyzed. Data visualization was performed for single- and multiple-pass responses to compare different testing conditions. Determining critical track locations for each sensor (the track on top of or the closest to the top of the sensor) allowed the researchers to summarize the dataset for each construction cycle into an organized, clean, and smaller size dataset. The summarized database could be used for developing machine learning prediction models for efficient pavement analysis.
Optimized Analysis of Airport Flexible Pavement Instrumentation Response
The National Airport Pavement Test Facility is a state-of-the-art, full-scale testing facility for airport pavements operated by the Federal Aviation Administration. The primary purpose of this program is to advance airfield pavement design methodologies by understanding pavement behavior under aircraft loading. This chapter presents the findings of an exploratory data analysis, visualization, and summary of flexible pavements tested in construction cycles 1 and 3. Each construction cycle serves a specific objective and is split into multiple test sections. Both dynamic data (i.e., stress, strain, and deflection) and static data (i.e., temperature and moisture) were analyzed. Data visualization was performed for single- and multiple-pass responses to compare different testing conditions. Determining critical track locations for each sensor (the track on top of or the closest to the top of the sensor) allowed the researchers to summarize the dataset for each construction cycle into an organized, clean, and smaller size dataset. The summarized database could be used for developing machine learning prediction models for efficient pavement analysis.
Optimized Analysis of Airport Flexible Pavement Instrumentation Response
Carter, Alan (editor) / Vasconcelos, Kamilla (editor) / Dave, Eshan (editor) / Diab, Lara (author) / Okte, Egemen (author) / Zhou, Qingwen (author) / Al-Qadi, Imad L. (author) / Garg, Navneet (author)
International Symposium on Asphalt Pavement & Environment ; 2024 ; Montreal, QC, Canada
14th International Conference on Asphalt Pavements ISAP2024 Montreal ; Chapter: 50 ; 297-303
2024-12-24
7 pages
Article/Chapter (Book)
Electronic Resource
English
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