Abstract Among the steps for the conversion of biomass into bioenergy, there is enzymatic hydrolysis. However, factors such as composition, formation of inhibitors, inhibition and enzymatic deactivation can affect the yield and productivity of this process. Lignocellulosic biomass is composed of cellulose, hemicellulose and lignin. However, lignin is organized in a complex and non-uniform way, promotes biomass recalcitrance, which repress the enzymatic attack on cellulose to be converted into glucose, and, consequently, the production of biofuel. Thus, a challenge in enzymatic hydrolysis is to model the reaction behavior. In this context, this study aims to evaluate the performance in enzymatic hydrolysis for the conversion of cellulose present in sugarcane bagasse into glucose. Therefore, modeling and optimization will be proposed to produce high glucose concentration rates. Therefore, a previously developed study will be used, in which the authors proposed a kinetic model for the hydrolysis step. However, as a differential to what has been proposed, the calculation will be carried out evaluating the evaporation, in order to maximize the response to the glucose concentration. Thus, considering evaporation and optimized kinetic parameters, it was possible to obtain high rates of glucose concentration at 204.23 $g.L^{-1

ABSTRACT This work aims to develop and validate a model based on chemical equilibrium to predict the composition of syngas produced by gasification of woody biomass (sawdust). The model uses Gibbs Energy minimization to evaluate the composition of the system in chemical equilibrium. The results are validated by comparison between experimental data from a gasification experiment and those of other similar models in the literature. The study shows good agreement among experimental results and elucidates the role of solid unburned carbon in such systems, which is present in considerable amount. It can be concluded that equilibrium models can be used to predict carbon conversion in gasification systems.

Abstract Proper simulation of processes of the natural gas industry such as dehydration, liquefaction and regasification require accurate prediction of thermodynamic properties of the working fluids. For such processes, cubic equations of state are the calculation methods most frequently employed. Among them, the Peng-Robinson equation is usually the one recommended for gas, refinery and petrochemical applications in many simulators. Numerous works have been proposed in order to improve the temperature dependence relation of the attraction parameter of the equation – the so called alpha function. In this work, five currently available alpha functions are evaluated for the prediction of molar volumes and enthalpies of natural gas samples. Additionally, parameters of one of the models are readjusted to volumetric data of methane, in order to represent its supercritical behavior more accurately. Experimental data of 44 mixtures are compared with calculated results. Van der Waals mixing rules are used, with binary interaction parameters set as zero. In the case of the original alpha function, it is also tested how the inclusion of non-zero binary parameters affects the predictions. The extended Saffari-Zahedi model presents the smallest average deviation for the molar volumes (1.35%). For the enthalpy calculation, the inclusion of the binary parameters results in deviation values of 2.62% for gas-gas transitions and 4.44% for gas-liquid transitions.

Abstract: In this study, several linear regression models were tested to predict the cumulative 30-day methane yield produced in mesophilic solid-state anaerobic digestion, employing diverse lignocellulosic biomass sources. Data collected from 13 studies were utilized, totalizing 86 experimental points, divided into regression and validation. Models containing higher order terms, the inverse of variables and interactions among all eleven input variables were tested. Simple linear models utilizing a single variable were unable to describe the methane production, giving an R² lower than 0.37. However, combinations of multiple variables and its inverses as only independent variable permitted an increase in simple linear models predictive capacity up to 63% of experimental variability. Higher order models presented an improvement in predictive quality: for a fourth-order multiple linear model, a validation R² of 0.8329 was achieved. In view of the obtained results, the proposed linear regression models consist in an attractive tool to propose experimental routines and to investigate new biomass sources for methane production using solid-state anaerobic digestion, significantly reducing time and cost requirements to experiments’ execution.

ABSTRACT Cement is one of the most used building materials in the world. The process of cement production involves numerous and complex reactions that occur under different temperatures. Thus, there is great interest in the optimization of cement manufacturing. Clinker production is one of the main steps of cement production and it occurs inside the kiln. In this paper, the dry process of clinker production is analysed in a rotary kiln that operates in counter flow. The main phenomena involved in clinker production is as follows: free residual water evaporation of raw material, decomposition of magnesium carbonate, decarbonation, formation of C3A and C4AF, formation of dicalcium silicate, and formation of tricalcium silicate. The main objective of this study was to propose a mathematical model that realistically describes the temperature profile and the concentration of clinker components in a real rotary kiln. In addition, the influence of different speeds of inlet gas and solids in the system was analysed. The mathematical model is composed of partial differential equations. The model was implemented in Mathcad (available at CCA/UFES) and solved using industrial input data. The proposal model is satisfactory to describe the temperature and concentration profiles of a real rotary kiln.

ABSTRACT: Essential oils are complex mixtures of volatile compounds found at low levels in aromatic plant specific parts. Soluble in organic solvents, these oils are characterized by their fragrance and antimicrobial activity, being widely used in industries. The mathematical modeling of essential oil extraction is a relevant step in the project of industrial plants because it is about achieving optimized operational conditions. A model is available in the literature describing the extraction process of basil essential oil, based on diffusion within the leaf. Parametric equations were tested for the variable diffusion coefficient with the concentration, resulting in a significant improvement in the description process, when compared to papers presented in the literature.

No processo de resfriamento de frutas por ar forçado, ocorre, além da transferência convectiva de calor, a transferência de massa por evaporação. A energia necessária para a evaporação é retirada da fruta que tem sua temperatura diminuída. Neste trabalho, propõe-se o uso de correlações empíricas para o cômputo do coeficiente convectivo de transferência de calor em função da temperatura da superfície do morango durante este processo de resfriamento. O objetivo desta variação do coeficiente convectivo é compensar o efeito da evaporação no processo de transferência de calor. São testadas correlações lineares e exponenciais, ambas com dois parâmetros ajustáveis. As simulações são realizadas, utilizando-se de condições experimentais reportadas na literatura para o resfriamento de morango. Os resultados encontrados confirmam a adequação da metodologia proposta.

In the forced-air cooling process of fruits occurs, besides the convective heat transfer, the mass transfer by evaporation. The energy need in the evaporation is taken from fruit that has its temperature lowered. In this study it has been proposed the use of empirical correlations for calculating the convective heat transfer coefficient as a function of surface temperature of the strawberry during the cooling process. The aim of this variation of the convective coefficient is to compensate the effect of evaporation in the heat transfer process. Linear and exponential correlations are tested, both with two adjustable parameters. The simulations are performed using experimental conditions reported in the literature for the cooling of strawberries. The results confirm the suitability of the proposed methodology.