Novel Approach to Strength Modeling of Concrete under Triaxial Compression

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{Gandomi:2012:JMCE,

• author = "Amir Hossein Gandomi and Saeed Karim Babanajad and Amir Hossein Alavi and Yaghoob Farnam",
• title = "Novel Approach to Strength Modeling of Concrete under Triaxial Compression",
• journal = "Journal of Materials in Civil Engineering",
• year = "2012",
• volume = "24",
• number = "9",
• pages = "1132--1143",
• month = sep,
• keywords = "genetic algorithms, genetic programming, Gene expression programming, Compressive strength, Triaxial compression, Ultimate strength",
• publisher = "American Society of Civil Engineers",
• ISSN = "0899-1561",
• DOI = "doi:10.1061/(ASCE)MT.1943-5533.0000494",
• size = "12 pages",
• abstract = "In this study, a robust variant of genetic programming, namely gene expression programming (GEP) was used to build a prediction model for the strength of concrete under triaxial compression loading. The proposed model relates the concrete triaxial strength to mix design parameters. A comprehensive database used for building the model was established on the basis of the results of 330 tests on concrete specimens under triaxial compression. To verify the predictability of the GEP model, it was employed to estimate the concrete strength of the specimens that were not included in the modelling process. Further, the model was externally validated using several statistical criteria recommended by researchers. A sensitivity analysis was carried out to determine the contributions of the parameters affecting the concrete strength. The proposed model is effectively capable of evaluating the ultimate strength of concrete under triaxial compression loading. The derived model performs superior when compared with other empirical models found in the literature. The GEP-based design equation can readily be used for predesign purposes or may be used as a fast check on solutions developed by more in-depth deterministic analyses.",

}

Genetic Programming entries for A H Gandomi Saeed K Babanajad A H Alavi Yaghoob Farnam

Citations