Treatment and bioenergy recovery from livestock wastewater in UASB reactor: novel approaches for engineering projects

Henrique Vieira de Mendonça, Mônica Silva dos Santos — Tue, 13 May 2025 00:00:00 +0000

This study presents an innovative approach for energy recovery and treatment of cattle wastewater, exploring the performance of a UASB reactor operated at 40°C, a condition that has received scant attention in the extant literature. The experiment was conducted using a semi-continuous feeding regime, with hydraulic retention times of 6, 5, 3, and 2 days, and organic loading rates of 4, 5, 7, and 11 kg COD m^-3 d^-1. The range of organic matter removal for total COD was 60% to 80%, and for soluble COD, it was 50% to 75%. These values resulted in methane yields ranging from 0.20 to 0.34 m³ CH₄ per kilogram of total COD removed and from 0.4 to 0.5 m³ CH₄ per kilogram of soluble COD removed. The findings underscore the efficacy of operating the reactor under these conditions, not only in achieving substantial biogas production but also in ensuring the efficient removal of organic matter. This reinforces the potential of the processes as a sustainable and effective alternative for treating effluents with high pollutant loads, thereby combining environmental mitigation and clean energy generation.

Kinetic modeling and neuro-fuzzy application in ethanol production

Tue, 13 May 2025 00:00:00 +0000

This study presents the application of kinetic modeling and Neuro-Fuzzy techniques in ethanol production. The research aims to optimize the fermentation process by employing the Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict ethanol yield under different conditions. Initially, sugarcane juice was used as a raw material and subjected to fractional distillation to obtain ethanol. The experimental data were analyzed using artificial neural networks and fuzzy logic to develop a predictive model. The ANFIS hybrid model demonstrated high accuracy in forecasting ethanol production, allowing for process optimization and cost reduction. Additionally, the kinetic analysis of fermentation provided insights into substrate consumption and ethanol yield efficiency. The results indicate that the Neuro-Fuzzy approach is a powerful tool for improving bioethanol production processes, enhancing both efficiency and sustainability.

Brazilian Journal of Biosystems Engineering

Treatment and bioenergy recovery from livestock wastewater in UASB reactor: novel approaches for engineering projects

Kinetic modeling and neuro-fuzzy application in ethanol production