APPLICATION OF DEEP LEARNING FRAMEWORK (ARTIFICIAL INTELLIGENCE) FOR CONCRETE GRADATION

Authors

  • Mohammad Sakib Perwez Khan Assistant Professor, Civil Engineering, Chandigarh College of Engg. & Tech.-Degree Wing, Sector 26, Chandigarh
  • Harmeet Sngh B. E. student, Civil Engineering, Chandigarh College of Engg. & Tech.-Degree Wing, Sector 26, Chandigarh, 3
  • Aadev Mann B. E. student, Civil Engineering, Chandigarh College of Engg. & Tech.-Degree Wing, Sector 26, Chandigarh,
  • Harmandeep Singh B. E. student, Civil Engineering, Chandigarh College of Engg. & Tech.-Degree Wing, Sector 26, Chandigarh,

Keywords:

Deep Learning, Artificial Intelligence, Characteristic Strength, Gradation, 28 days strength.

Abstract

Concrete gradation or calculating the strength that a given mix of concrete will give is one of the major concerns of a civil engineering/construction engineering. To find the grade of concrete different destructive and nondestructive method are employed. This calculation of grade of concrete helps in the verification and confirmation of the overall stability and safety of the given structure.
In this study, an attempt has made to apply the deep learning framework of artificial intelligence to predict the grade of hardened concrete mix of life 28 days. A deep learning framework was made to predict the grade of concrete by analysing the photograph of a hardened concrete mix. At a small scale few grades of concrete were designed and casted in the laboratory and the pictorial data was collected under specific conditions. Then this data was used to train the framework and then the framework was used to predict the grade of a random data of concrete.

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Published

2019-04-15

How to Cite

Khan, M. S. P. ., Sngh, H. ., Mann, . A., & Singh, H. . (2019). APPLICATION OF DEEP LEARNING FRAMEWORK (ARTIFICIAL INTELLIGENCE) FOR CONCRETE GRADATION. International Journal of Technical Innovation in Modern Engineering & Science, 5(4), 826–829. Retrieved from https://ijtimes.com/IJTIMES/index.php/ijtimes/article/view/2856