Artificial Intelligence-Based Prediction of Permeable Pavement Surface Infiltration Rates

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dc.contributor.advisorKhan, Usman
dc.contributor.advisorButler, Liam
dc.contributor.authorMalik, Arham
dc.date.accessioned2022-03-03T14:07:51Z
dc.date.available2022-03-03T14:07:51Z
dc.date.copyright2021-12
dc.date.issued2022-03-03
dc.date.updated2022-03-03T14:07:51Z
dc.degree.disciplineCivil Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractPermeable pavements are a type of low impact development technology that is an alternative to conventional asphalt pavements. These pavements are used to address urban stormwater runoff concerns through infiltration and storage. Overtime, sediments carried by stormwater runoff degrade the performance of these pavements and can eventually diminish the infiltration capacity to the point where no infiltration takes place. The objective of this research is to develop a data-driven model to predict the infiltration rate of permeable pavements. Four permeable concrete lab specimens were constructed and subjected to clogging cycles while obtaining surface images and infiltration data. An artificial neural network was created to investigate the relationship between the images of the pavement surface and its associated surface infiltration rate. Results indicated that image parameters do change significantly as pavements clog and are suitable as inputs to predict surface infiltration rate, although model variability needs to be addressed.
dc.identifier.urihttp://hdl.handle.net/10315/39133
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectSustainability
dc.subject.keywordsPermeable pavements
dc.subject.keywordsPredicting
dc.subject.keywordsPermeable concrete
dc.subject.keywordsClogging
dc.subject.keywordsMaintenance
dc.subject.keywordsArtificial neural network
dc.subject.keywordsModelling
dc.subject.keywordsImage analysis
dc.subject.keywordsSurface infiltration rates
dc.subject.keywordsPerformance
dc.titleArtificial Intelligence-Based Prediction of Permeable Pavement Surface Infiltration Rates
dc.typeElectronic Thesis or Dissertation

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