article · International Journal of Engineering Research and Technology
Concrete production can incorporate wood ash as a partial replacement for conventional cement alongside Bida natural aggregates. A synthesis of existing studies and case analyses shows that artificial neural networks provide an effective tool for modelling the complex, non-linear relationships among cement quantity, aggregate ratios, curing duration, and the resulting compressive strength. The evidence indicates that concrete achieves optimal compressive strength with a water to cement ratio of 0.4 and a wood ash replacement level maintained between 5 and 15 percent. Utilizing these predictive computational techniques helps determine precise material proportions, demonstrating the viability of integrating supplementary materials into standard mixtures while maintaining structural performance. Further investigation remains necessary to fully standardise the combination of wood ash and Bida natural aggregates.
Substituting cement with by-products such as wood ash can lower material costs and reduce environmental burdens associated with conventional concrete manufacturing. Identifying clear replacement limits and employing predictive tools like artificial neural networks allows engineers and builders to design resource-efficient construction materials without sacrificing structural integrity.
The insights apply to concrete manufacturers, construction firms, and civil engineers exploring alternative binders and local aggregate sources. Because the underlying findings derive from a literature review and case study analyses rather than direct physical trials, the approach sits at an early research and modelling stage. Commercialisation would require formal laboratory validation, mix standardisation, and field testing.
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This paper aims to provide a comprehensive evaluation of current research on the Optimization of compressive strength of wood ash cement concrete with Bida natural aggregates using artificial neural network (ANN). The primary objectives are to assess the effectiveness of wood ash (WA) cement partial replacement, and Bida natural aggregates (BNA) in concrete production using ANN, and to ascertain the optimum replacement level of WA and future research directions. The methodology involves an extensive literature review, and analysis of case studies. Key findings highlight the optimum water cement ratio of 0.4, and WA replacement level of between 5-15% for optimum results of concrete involving WA. The study reveals that ANN can be used in the analysis of nonlinear relationship between cement quantity, aggregate ratio, curing duration and compressive strength of concrete. The review concludes with recommendations for future research, focusing on the use of WA to partially replace cement in concrete production using BNA.
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DOI: 10.70382/tijert.v13i5.029
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