Linear regression of concrete mix design components for strengths between 250 and 280 kg/cm² by applying the ACI Method and the Porrero Method
DOI:
https://doi.org/10.51372/gacetatecnica272.3Keywords:
linear regression, ACI Method, Porrero Method, concrete mix designAbstract
This research is an exploratory correlational study that aims to determine the linear regression of the components of concrete mix designs—water, cement, fine aggregate, and coarse aggregate—in undergraduate theses from the Civil Engineering program at the University Centroccidental Lisandro Alvarado in Barquisimeto, Venezuela. These theses employed the ACI Method and the Porrero Method for compressive strengths between 24,517 and 27,459 MPa (250 and 280 kg/cm2), with a nominal maximum aggregate size of 1 inch, slumps up to 6 inches, Portland cement type I or CPCA1, and natural sand. A total of 276 theses were reviewed, of which 74 met the established scope. The descriptive statistical analysis showed low to intermediate dispersions with a downward trend, leading to the conclusion that the regressions of both methods are linear. The ACI Method model has an explanatory power of 84,8%, and the Porrero Method 55,1%; however, neither model met the assumption of normality
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ACI, “Requisitos de Reglamento para Concreto Estructural (ACI 318S-14) y Comentario (ACI 318SR-14)” American Concrete Institute, EUA, 2015
J. Porrero, C. Ramos, J. Graces y G. Velazco, “Manual del Concreto Estructural”, Caracas, Venezuela, 2014
F. Peña, “Determinación de la distribución de probabilidades de los componentes de diseños de mezclas de concreto para resistencias entre 250 – 280 kg/cm²”, Trabajo de Grado, Decanato de Ingeniería Civil, Universidad Centroccidental Lisandro Alvarado, Barquisimeto, Venezuela, 2018
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