Prediction of compressive strength of papercrete mixed with rice husk ash as partial replacement of fine aggregates in concrete mortar using back propagation algorithm

Abstract About 8.7% of total solid municipal waste in the Philippines consists of wastepaper. As such, this study aims to investigate the feasibility of papercrete mortar to introduce alternative means of adequately disposing of wastepaper. In addition, the study aims to integrate rice husk ash into papercrete as an additional variable for the partial replacement of fine aggregates in concrete mortar. The researchers hypothesized that this addition would sustainably benefit its structural properties, similar to traditional concrete. Using 40 curated mixtures, compressive tests were conducted to validate this assumption. Additionally, an Artificial Neural Network (ANN) model was developed in conjunction with the experiment to help assess future curated mixtures without the need for excessive laboratory testing. Findings from the compressive tests depict that papercrete mortar infused with rice husk ash is viable for both Type N and Type O mortar. Regarding the performance of the ANN model, it demonstrates excellent capabilities with a regression score above 99% and a mean squared error performance lower than 1%, making it feasible to assess the viability of curated mortar mixtures that replace fine aggregates with wastepaper and rice husk ash before performing an actual experiment.