Concrete Compressive Strength Prediction Using Neural Networks Based on Non-destructive Tests and a Self-calibrated Response Surface Methodology-Reference-Cited by-同舟云学术

Concrete Compressive Strength Prediction Using Neural Networks Based on Non-destructive Tests and a Self-calibrated Response Surface Methodology

Published:2020-10-07 Issue:4 Volume:39 Page:
ISSN:0195-9298
Container-title:Journal of Nondestructive Evaluation
language:en
Short-container-title:J Nondestruct Eval

Author:

Poorarbabi Ali,Ghasemi Mohammadreza,Azhdary Moghaddam Mehdi

Publisher

Springer Science and Business Media LLC

Subject

Mechanical Engineering,Mechanics of Materials

Link

http://link.springer.com/content/pdf/10.1007/s10921-020-00718-w.pdf

Reference34 articles.

1. Beshr, H., Almusallam, A., Maslehuddin, M.: Effect of coarse aggregate quality on the mechanical properties of high strength concrete. Constr. Build. Mater. 17(2), 97–103 (2003)

2. Neville, A.M.: Properties of Concrete. Wiley, New York (2005)

3. Ali-Benyahia, K., Sbartaï, Z.-M., Breysse, D., Ghrici, M., Kenai, S.: Improvement of nondestructive assessment of on-site concrete strength: influence of the selection process of cores location on the assessment quality for single and combined NDT techniques. Constr. Build. Mater. 195, 613–622 (2019)

4. In Place Methods for Determination of Strength of Concrete; ACI Manual of Concrete Practice, Part 2: Construction Practices and Inspection Pavements, ACI 228.1R-989, Detroit, MI, 1994, p. 25.

5. Jones, R.: Testing of concrete by ultrasonic-pulse technique. In: Highway Research Board Proceedings (1953).

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