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Comparison of Compressive Strength of M30 Grade Concrete with Destructive and Nondestructive Procedures Using Digital Image Processing as a Technique

Autor(en): ORCID

Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Advances in Civil Engineering, , v. 2022
Seite(n): 1-12
DOI: 10.1155/2022/4649660
Abstrakt:

Destructive, semidestructive, and nondestructive methods are used to assess the compressive strength of concrete and its substantial mechanical property. In the destructive method, samples of concrete are crushed and treated under compression to determine its compressive strength. As such, the impact is seen on test results like the method of casting and compaction. The tests on concrete become limited in the destructive method and are confined to predict compressive strength, flexural strength, etc. To overcome its limitations and to study concrete matrix, semidestructive and nondestructive test methods came into limelight. Among nondestructive methods, strength prediction can be carried out using Schmidt’s rebound hammer test, ultrasonic pulse velocity test, image analysis techniques, radioactive tests, etc. Consequently, an advanced technique to predict the strength of the structural element using digital image processing technique has been introduced, and one can have a glimpse of the enlarged image, which quantifies and is used to assess the strength. The various characteristic features associated with the image help to calculate the strength of the structural element. A high-pixel camera is used to take images of concrete cube samples, and they are analyzed with digital image processing techniques and a tool in MATLab or directly by making use of ImageJ software. In addition, digital image processing techniques are being implemented in various fields such as medical, industrial, remote sensing, and engineering. The present paper proposes to cast 150 × 150 × 150 mm-sized M30 grade concrete cube samples and to study their strength after a period of 7 days and subsequently after 28 days. Destructive and nondestructive methods are used, and the samples are analyzed with digital image processing techniques using ImageJ software. The observed findings are discussed in the paper.

Copyright: © 2022 Sreenath Mahankali and Giridhar Valikala et al.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10687269
  • Veröffentlicht am:
    13.08.2022
  • Geändert am:
    10.11.2022
 
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