Estudo teórico e experimental da produção de biogás e do substrato bovino e humano em biodigestor: caracterização do escoamento em modelagem cilíndrica

Abstract

This thesis investigates experimentally and theoretically the production of biogas from bovine and human substrates in biodigesters, as well as the modeling of the flow of these substrates. The dual methodology combined the construction and operation of batch and continuous prototypes with the rheological characterization of the substrates, the quantification of biogas, and the analysis of its composition by gas chromatography. In parallel, a mathematical model based on conservation equations was developed and solved using the Generalized Integral Transform Technique to characterize the velocity, temperature, and concentration profiles. The results revealed the clear superiority of the human substrate, which generated 636.2 liters of biogas with 63.9% methane from 5 kg, surpassing the 506.9 liters and 51.5% methane of the bovine substrate. Standardizing the total solids content at 10.85% allowed for a fair comparison and the generation of a comprehensive set of dimensionless numbers from experimental data, including Reynolds, Prandtl, Schmidt, Sherwood, Biot, and Péclet. These parameters serve as a tool for analyzing real systems. Modeling via GITT, validated with the literature, predicts radial temperature and concentration gradients, revealing low-conversion zones that limit overall efficiency. Crucially, the distributed study for sizing and maximum rate operation defined that a continuous feed, after the substrate transformation period, allows for maximum operation of the biodigester, with the minimum reactor capacity. It is concluded that human substrate is more efficient for biogas production. The GITT methodology proved to be accurate in characterizing the transport specifications in the reactor. As its main contribution, the thesis provides an integrated methodological framework and a set of critical operational and dimensional parameters that enable the design, performance prediction, and improvement of biodigestion systems, with direct impacts on renewable energy generation and sustainability.