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Using crack width for shear, stiffness, and stirrup strain history predictions for reinforced concrete beams.

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Title: Using crack width for shear, stiffness, and stirrup strain history predictions for reinforced concrete beams.
Authors: Castillo, Rodrigo1 (AUTHOR) rodrigon@buffalo.edu, Elhami-Khorasani, Negar1 (AUTHOR), Okumus, Pinar1 (AUTHOR), Chandola, Varun2 (AUTHOR)
Source: Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance. Jul2026, Vol. 22 Issue 7, p1159-1171. 13p.
Subjects: Reinforced concrete, Machine learning, Crack propagation, Gaussian processes, Shearing force, Structural analysis (Engineering), Shear strain, Stiffness (Engineering)
Abstract: Shear failures in reinforced concrete structures occur with little or no warning. Reinforced concrete members with shear cracks should be evaluated to ensure safety. Existing evaluation methods have large variability, require time-consuming modeling or expert opinion. This study uses machine learning to investigate correlations of crack width with shear loading, stiffness, and stirrup strain histories. Experimental literature enables the assembly of a database of rectangular reinforced concrete slender beams with crack width measurements for beams with shear reinforcement amounts smaller and larger than the minimum required by ACI 318-19. Measured data include crack widths from 122 beams, load–displacement relationship from 100 beams, and stirrup strains from 46 beams. Gaussian Process Regression is used to correlate crack width and geometric, material and design properties to shear loading, stiffness, and stirrup strain histories. Ten-fold cross validation training shows mean absolute percent errors of 18, 33 and 77% for shear, stiffness, and stirrup strain history predictions. The proposed algorithms can be used to accelerate the evaluation of in-service structures and can be updated upon availability of additional data. [ABSTRACT FROM AUTHOR]
Copyright of Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 194972696
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Using crack width for shear, stiffness, and stirrup strain history predictions for reinforced concrete beams.
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  Data: <searchLink fieldCode="DE" term="%22Reinforced+concrete%22">Reinforced concrete</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22Crack+propagation%22">Crack propagation</searchLink><br /><searchLink fieldCode="DE" term="%22Gaussian+processes%22">Gaussian processes</searchLink><br /><searchLink fieldCode="DE" term="%22Shearing+force%22">Shearing force</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+analysis+%28Engineering%29%22">Structural analysis (Engineering)</searchLink><br /><searchLink fieldCode="DE" term="%22Shear+strain%22">Shear strain</searchLink><br /><searchLink fieldCode="DE" term="%22Stiffness+%28Engineering%29%22">Stiffness (Engineering)</searchLink>
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  Data: Shear failures in reinforced concrete structures occur with little or no warning. Reinforced concrete members with shear cracks should be evaluated to ensure safety. Existing evaluation methods have large variability, require time-consuming modeling or expert opinion. This study uses machine learning to investigate correlations of crack width with shear loading, stiffness, and stirrup strain histories. Experimental literature enables the assembly of a database of rectangular reinforced concrete slender beams with crack width measurements for beams with shear reinforcement amounts smaller and larger than the minimum required by ACI 318-19. Measured data include crack widths from 122 beams, load–displacement relationship from 100 beams, and stirrup strains from 46 beams. Gaussian Process Regression is used to correlate crack width and geometric, material and design properties to shear loading, stiffness, and stirrup strain histories. Ten-fold cross validation training shows mean absolute percent errors of 18, 33 and 77% for shear, stiffness, and stirrup strain history predictions. The proposed algorithms can be used to accelerate the evaluation of in-service structures and can be updated upon availability of additional data. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1080/15732479.2024.2359488
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 13
        StartPage: 1159
    Subjects:
      – SubjectFull: Reinforced concrete
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Crack propagation
        Type: general
      – SubjectFull: Gaussian processes
        Type: general
      – SubjectFull: Shearing force
        Type: general
      – SubjectFull: Structural analysis (Engineering)
        Type: general
      – SubjectFull: Shear strain
        Type: general
      – SubjectFull: Stiffness (Engineering)
        Type: general
    Titles:
      – TitleFull: Using crack width for shear, stiffness, and stirrup strain history predictions for reinforced concrete beams.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Castillo, Rodrigo
      – PersonEntity:
          Name:
            NameFull: Elhami-Khorasani, Negar
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            NameFull: Okumus, Pinar
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            NameFull: Chandola, Varun
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          Dates:
            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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            – TitleFull: Structure & Infrastructure Engineering: Maintenance, Management, Life-Cycle Design & Performance
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