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    Development of Discharge-Based Thresholding Algorithm for Pervious Concrete Pavement Mixtures

    Source: Journal of Materials in Civil Engineering:;2019:;Volume ( 031 ):;issue: 009
    Author:
    Ajayshankar Jagadeesh
    ,
    Ghim Ping Ong
    ,
    Yu-Min Su
    DOI: 10.1061/(ASCE)MT.1943-5533.0002807
    Publisher: American Society of Civil Engineers
    Abstract: The functional performance of pervious concrete pavement surfaces (such as hydraulic, acoustic, and frictional performances) is greatly influenced by the properties of its internal pore structure (such as effective porosity, intrinsic permeability, tortuosity, and pore size distribution). Nondestructive evaluation (NDE) using X-ray computed tomography (CT) and digital image processing (DIP) involves the crucial step of image segmentation of grayscale histograms, which can significantly affect subsequent pore structure analysis and fluid flow simulations. This paper presents a new discharge-based segmentation algorithm capable of predicting non-Darcy permeability of pervious concrete mixtures. The algorithm uses X-ray CT image–based finite-volume permeability simulations to determine the specific discharge at various hydraulic gradients. Experimental results of a falling-head permeability test were used to calibrate and validate the developed finite-volume models. The permeability simulation results from the developed thresholding algorithm were compared against simulation results obtained from 10 different global thresholding algorithms. It was found from the analyses that the developed discharge-based thresholding algorithm predicts non-Darcy permeability characteristics and the effective porosity of the pervious concrete mixtures more accurately than other global thresholding algorithms.
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      Development of Discharge-Based Thresholding Algorithm for Pervious Concrete Pavement Mixtures

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4259441
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    contributor authorAjayshankar Jagadeesh
    contributor authorGhim Ping Ong
    contributor authorYu-Min Su
    date accessioned2019-09-18T10:37:04Z
    date available2019-09-18T10:37:04Z
    date issued2019
    identifier other%28ASCE%29MT.1943-5533.0002807.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4259441
    description abstractThe functional performance of pervious concrete pavement surfaces (such as hydraulic, acoustic, and frictional performances) is greatly influenced by the properties of its internal pore structure (such as effective porosity, intrinsic permeability, tortuosity, and pore size distribution). Nondestructive evaluation (NDE) using X-ray computed tomography (CT) and digital image processing (DIP) involves the crucial step of image segmentation of grayscale histograms, which can significantly affect subsequent pore structure analysis and fluid flow simulations. This paper presents a new discharge-based segmentation algorithm capable of predicting non-Darcy permeability of pervious concrete mixtures. The algorithm uses X-ray CT image–based finite-volume permeability simulations to determine the specific discharge at various hydraulic gradients. Experimental results of a falling-head permeability test were used to calibrate and validate the developed finite-volume models. The permeability simulation results from the developed thresholding algorithm were compared against simulation results obtained from 10 different global thresholding algorithms. It was found from the analyses that the developed discharge-based thresholding algorithm predicts non-Darcy permeability characteristics and the effective porosity of the pervious concrete mixtures more accurately than other global thresholding algorithms.
    publisherAmerican Society of Civil Engineers
    titleDevelopment of Discharge-Based Thresholding Algorithm for Pervious Concrete Pavement Mixtures
    typeJournal Paper
    journal volume31
    journal issue9
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/(ASCE)MT.1943-5533.0002807
    page04019179
    treeJournal of Materials in Civil Engineering:;2019:;Volume ( 031 ):;issue: 009
    contenttypeFulltext
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