Linear regression of concrete mix design components for strengths between 250 and 280 kg/cm² by applying the ACI Method and the Porrero Method (Gaceta Técnica, 2026)
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
Keywords: linear regression; ACI Method; Porrero Method; concrete mix design