A Model to Predict the Strength of Highway Culvert made from Cinchona industrial Waste and Pulverized Plastic as Partial Replacement of Cement and Sand in Concrete

Abstract: The increasing demand for sustainable and high-performance concrete necessitates accurate prediction of its mechanical and durability properties. This study developed Artificial Neural Network (ANN) models to estimate compressive, flexural, and tensile strength, as well as setting times and workability parameters, based on inputs of pulverized plastic waste (PPW) and cinchona industrial ash (Ci). The model was trained and validated using experimental datasets. Evaluation metrics such as RMSE, MAE, , and scatter index confirmed excellent model performance, especially for strength-related outputs ( ). These results were consistent with related ANN applications in literature, reinforcing its predictive robustness. The proposed model can aid in optimizing concrete mixes using industrial waste, contributing to circular economy and sustainable infrastructure. Further application in field-scale design is recommended. Keywords: ANN; Cinchona Industrial Waste (Ci); Mathematical Model; Pulverized Plastic Waste (PPW). Title: A Model to Predict the Strength of Highway Culvert made from Cinchona industrial Waste and Pulverized Plastic as Partial Replacement of Cement and Sand in Concrete Author: Omach Antony Owuonda, Fundi Isaac Sanewu, Nyongesa Daniel Wekesa International Journal of Recent Research in Civil and Mechanical Engineering (IJRRCME) ISSN 2393-8471 Vol. 12, Issue 1, April 2025 - September 2025 Page No: 75-86 Paper Publications Website: www.paperpublications.org Published date: 13-August-2025 DOI: https://doi.org/10.5281/zenodo.16839399 Paper Download Link (Source) https://www.paperpublications.org/upload/book/A%20Model%20to%20Predict%20the%20Strength-13082025-4.pdf