Prediction and Optimization of Compressive Strength of Cement Concrete with Reclaimed Asphalt Pavement as Coarse Aggregates Using Scheffe’s Lattice Simplex Model
This study investigates the optimization of compressive strength in cement concrete incorporating Reclaimed Asphalt Pavement (RAP) as coarse aggregate, offering a sustainable alternative to natural materials in construction. RAP was manually processed and treated to reduce asphalt coating before use, and mix proportions were developed using a Scheffe’s second-degree polynomial model with 21 runs and three replicates, giving 63 samples in total. Regression analysis with backward elimination ensured precision in estimating model coefficients, while analysis of variance confirmed statistical significance with an adjusted R² of 74.18%. Findings revealed that RAP content and key interaction terms (e.g., X₁X₂ and X₃X₄) exerted notable influence on compressive strength, providing insight into mixture behavior and performance. The model generated predictive tools such as response surfaces and contour plots, which can guide material formulation; however, residual analysis showed a slight underestimation tendency, indicating the need for refinement, broader experimental validation, and possible model comparison. Overall, the study demonstrates both the promise and constraints of Scheffe’s model in optimizing sustainable concrete mixes with RAP, advancing resource conservation and supporting environmentally responsible construction practices.
Authors
- Michael Toryila Tıza (ORCID: https://orcid.org/0000-0003-3515-8951)
- Jonah Agunwamba (ORCID: https://orcid.org/0000-0002-0228-8250)
- Emmanuel OGUNLEYE (ORCID: https://orcid.org/0000-0001-7263-895X)
- Ebenezer Akande (ORCID: https://orcid.org/0000-0002-3201-6520)
- Collins Onuzulıke (ORCID: https://orcid.org/0000-0001-7264-9843)
Publication Details
- Journal
- Sakarya University Journal of Science
- Published
- 2026-06-26
- DOI
- https://doi.org/10.16984/saufenbilder.1703361
- Primary Topic
- Asphalt Pavement Performance Evaluation
- Type
- article
- Field-Weighted Citation Impact
- 0.00