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

Abstract

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.

Obtaining the percentages of ductility and brittleness of AISI/SAE 1020 and 304 steels, using digital image processing.

“…Digital image processing has been used in multiple applications [1], [2], [3], [4]. The applications refer to topics such as fruit selection [5], classification of medical images [6], [7], structural analysis [8], [9], [10] and materials classification [11], [12]. Secondly, the Charpy test , has been used to determinate toughness [13], behavior analysis in thermic variation [14], and identification of different properties of materials [15].…”