Neuro-fuzzy model for the prediction of CO₂ emissions of concrete mixes for biodigestors in swine production systems

Abstract

Due to the importance of swine production in Brazil, there is a need to understand the environmental impact generated by the construction materials used in the production of rural facilities, especially in the construction of biodigesters, as these facilities play an important role in the sustainability of production systems. Considering the relevance of the volume of concrete used in the construction of biodigesters for the management and treatment of swine waste, this research study sought to evaluate the emissions of carbon dioxide equivalent (CO ₂ Eq.) in different concrete mix scenarios. For that purpose, a computational ANFIS (Adaptive Neuro-Fuzzy Inference System) model was developed to predict and analyse CO ₂ Eq. emissions during the life cycle of materials adopted in conventional concrete. The results indicate that the proper choice of dosage can lead to a reduction of 31.41% in CO ₂ Eq. emissions, for concrete from 30 to 40 MPa. This represents a promising proposal for reducing the environmental impact of the production of concrete constructions, which has the potential to stimulate further research in this area.

Keywords:
Carbon dioxide emissions; ANFIS system; Sustainable concrete; Rural buildings; Swine constructions