IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2023i1p112-d1305104.html
   My bibliography  Save this article

Innovative Imaging and Analysis Techniques for Quantifying Spalling Repair Materials in Concrete Pavements

Author

Listed:
  • Junhwi Cho

    (Department of Regional Infrastructure Engineering, Kangwon National University, Chuncheon-si 24341, Republic of Korea)

  • Julian Kang

    (Department of Construction Science, Texas A&M University, College Station, TX 77843, USA)

  • Yooseob Song

    (Department of Civil and Environmental Engineering, University of Alabama in Huntsville, Huntsville, AL 35899, USA)

  • Seungjoo Lee

    (Department of Korean Peninsula Infrastructure Special Committee, Korea Institute of Civil Engineering and Building Technology, Ilsanseo-gu, Goyang-si 10223, Republic of Korea)

  • Jaeheum Yeon

    (Department of Regional Infrastructure Engineering, Kangwon National University, Chuncheon-si 24341, Republic of Korea)

Abstract

Traditional spalling repair on concrete pavement roads is labor-intensive. It involves traffic blockages and the manual calculation of repair areas, leading to time-consuming processes with potential discrepancies. This study used a line scan camera to photograph road surface conditions to analyze spalling without causing traffic blockage in an indoor setting. By using deep learning algorithms, specifically a region-based convolutional neural network (R-CNN) in the form of the Mask R-CNN algorithm, the system detects spalling and calculates its area. The program processes data based on the Federal Highway Administration (FHWA) spalling repair standards. Accuracy was assessed using root mean square error (RMSE) and Pearson correlation coefficient (PCC) via comparisons with actual field calculations. The RMSE values were 0.0137 and 0.0167 for the minimum and maximum repair areas, respectively, showing high accuracy. The PCC values were 0.987 and 0.992, indicating a strong correlation between the actual and calculated repair areas, confirming the high calculation accuracy of the method.

Suggested Citation

  • Junhwi Cho & Julian Kang & Yooseob Song & Seungjoo Lee & Jaeheum Yeon, 2023. "Innovative Imaging and Analysis Techniques for Quantifying Spalling Repair Materials in Concrete Pavements," Sustainability, MDPI, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:112-:d:1305104
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/1/112/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/1/112/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Angus Eugene Retallack & Bertram Ostendorf, 2019. "Current Understanding of the Effects of Congestion on Traffic Accidents," IJERPH, MDPI, vol. 16(18), pages 1-13, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Duc C. Phan & Long T. Truong, 2024. "Traffic Congestion and Safety: Mixed Effects on Total and Fatal Crashes," Sustainability, MDPI, vol. 16(20), pages 1-11, October.
    2. Angus Eugene Retallack & Bertram Ostendorf, 2020. "Relationship Between Traffic Volume and Accident Frequency at Intersections," IJERPH, MDPI, vol. 17(4), pages 1-22, February.
    3. Mladen Jardas & Ana Perić Hadžić & Edvard Tijan, 2021. "Defining and Measuring the Relevance of Criteria for the Evaluation of the Inflow of Goods in City Centers," Logistics, MDPI, vol. 5(3), pages 1-15, July.
    4. Bong Gu Kang & Byeong Soo Kim, 2023. "A Study on Cognitive Error Validation for LED In-Ground Traffic Lights Using a Digital Twin and Virtual Environment," Mathematics, MDPI, vol. 11(17), pages 1-16, September.
    5. Abdelrahman M. Farouk & Afiqah R. Radzi & Noor Suraya Romali & Mohamed Farouk & Mohamed Elgamal & Raouf Hassan & Mazen M. Omer & Rahimi A. Rahman, 2024. "Performance Indicators for Assessing Environmental Management Plan Implementation in Water Projects," Sustainability, MDPI, vol. 16(8), pages 1-19, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2023:i:1:p:112-:d:1305104. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.