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Computers and Concrete Volume 21, Number 1, January 2018 , pages 47-54 DOI: https://doi.org/10.12989/cac.2018.21.1.047 |
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Predicting residual compressive strength of self-compacted concrete under various temperatures and relative humidity conditions by artificial neural networks |
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Ahmed M. Ashteyat and Muhannad Ismeik
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| Abstract | ||
| Artificial neural network models can be successfully used to simulate the complex behavior of many problems in civil engineering. As compared to conventional computational methods, this popular modeling technique is powerful when the relationship between system parameters is intrinsically nonlinear, or cannot be explicitly identified, as in the case of concrete behavior. In this investigation, an artificial neural network model was developed to assess the residual compressive strength of self-compacted concrete at elevated temperatures (20-900oC) and various relative humidity conditions (28-99%). A total of 332 experimental datasets, collected from available literature, were used for model calibration and verification. Data used in model development incorporated concrete ingredients, filler and fiber types, and environmental conditions. Based on the feed-forward back propagation algorithm, systematic analyses were performed to improve the accuracy of prediction and determine the most appropriate network topology. Training, testing, and validation results indicated that residual compressive strength of selfcompacted concrete, exposed to high temperatures and relative humidity levels, could be estimated precisely with the suggested model. As illustrated by statistical indices, the reliability between experimental and predicted results was excellent. With new ingredients and different environmental conditions, the proposed model is an efficient approach to estimate the residual compressive strength of self-compacted concrete as a substitute for sophisticated laboratory procedures. | ||
| Key Words | ||
| modeling; artificial neural network; residual compressive strength; self-compacted concrete; temperature; relative humidity | ||
| Address | ||
| Ahmed M. Ashteyat: Department of Civil Engineering, The University of Jordan, Amman 11942, Jordan Muhannad Ismeik: Department of Civil Engineering, The University of Jordan, Amman 11942, Jordan; Department of Civil Engineering, Australian College of Kuwait, Safat 13015, Kuwait | ||