Mônica Ronobo Coutinho

Modelagem matemática e análise da hidratação de grãos de ervilha

A mathematical model for estimating the water concentration in pea grains during hydration was developed from a transient water mass balance inside a grain of pea considering a constant volume and spherical geometry. This model is represented by an ordinary first order differential equation and has two parameters: the mass transfer coefficient (Ks) and the equilibrium concentration (ρAeq). Both parameters have been numerically fitted using the minimization of the sum-of-squared residuals criterion and the hydration experimental data for pea grains at 20, 30, 40, 50, and 60 oC. At all temperatures, the model represented the major trends of the hydration process with standard deviations smaller than 5%. For the model fitted parameters, it was observed that the mass transfer coefficient behaved according to Arrheniuss equation in relation to the temperature variation, Ks = 182.8.exp(-3521/T) while the equilibrium concentration remained practically constant showing an average value of ρAeq = 0.533 g/cm3. Using the Ks Arrheniuss correlation and assuming the average value of ρAeq, a generalized model was obtained, which resulted in a standard deviation slightly greater than 7% for all the data values. Additionally, it was observed that the pea grains density remains practically constant along the hydration process and does not depend on the temperature.

Novo modelo de parâmetros concentrados aplicado à hidratação de grãos

A new first principle model with lumped parameters was developed for the hydration of soya beans. A transient mass balance was applied to the soya beans taking into consideration two basic hypotheses:1o) variation of the volume directly proportional to the variation of the mass of the grain during the process, 2o) Exponential variation of the apparent coefficient of mass transfer in function of water concentration in the soy. This model has got just two parameters, which were evaluated from adjustment of model to the measures of grain moisture along the time, at several temperatures. The results indicate that the proposed model was able to represent the hydration process, while the mass transfer coefficient depends on the temperature and it presents significant variations along the hydration.

Modelagem e validação da hidratação de grãos de soja

SUMMARY MODELING AND VALIDATION OF SOYA BEAN HYDRATION. A first principle model with lumped parameters was developed for the hydration of soya beans. A transient mass balance was applied to the soya beans taking into consideration the variation of the bean diameters during the process. Simulation results were compared to the empirical models available in the literature and with experimental data. Both the first principle and empirical models were validated by the experimental data that were obtained for the temperatures of 10, 15, 20, 30, 42 and 49°C. All models were able to represent the main data trends of the hydration process, after adjustment of their parameters for each temperature. However, the first principle model has the smallest deviations in relation to the experimental data. In addition, a generalized first principle model was proposed.

Application of the Hsu model to soybean grain hydration

Abstract A comparative analysis of the theoretical-experimental study, developed by Hsu on the hydration of Amsoy 71 soybean grain, was performed through several soaking experiments using CD 202 soybean at 10, 20, 30, 40, and 50 °C, measuring moisture content over time. The results showed that CD 202 soybean equilibrium moisture content, X eq , does not depend on temperature and is 21% higher than that found by Hsu, suggesting that soybean cultivar exerts great influence on X eq . The Hsu model was numerically solved and its parameters were adjusted by the least squares method, with maximum deviations of +/– 10% relative to the experimental values. The limiting step in the mass transfer process during hydration corresponds to water diffusion inside the grain, leading to radial moisture gradients that decrease over time and with an increase in temperature. Regardless of the soybean cultivar, diffusivity increases as temperature or moisture content increases. However, the values of this transport property for Amsoy 71 were superior to those of CD 202, very close at the beginning of hydration at 20 °C and almost three times higher at the end of hydration at 50 °C.

Evaluation of two mathematical models applied to soybean hydration.

The predictions of the Hsu model of soybean hydration are compared with simulation results of the distributed parameter phenomenological model (DPP) that was developed in this study. The models were developed based on the same mass balance with one volume differential element of the Hsu model; however, the Hsu model admits an exponential variation of concentration while the DPP model admits equal diffusion and convection fluxes at the solid-fluid interface. The models are represented by a partial second order differential equation in relation to the radial position and a first order equation in relation to time, which were solved and numerically fitted using MATLAB routines and experimental data obtained from the hydration assays in the temperature range from 10 to 50 °C. The Hsu model has a smaller quadratic deviation; however, it employs three fitting parameters while DPP uses only one.

Modeling of the soybean grains hydration by a distributed parameters approach.

A mathematical model with distributed parameters was proposed to describe the absorption of water by soybeans, in order to evaluate the moisture content variation with time inside the grains. This model was represented by a partial differential equation (second order relative to position and first order relative to time), whose parameters were numerically adjusted using a minimum squares method. For this purpose, available MATLAB® routines were used, together with experimental data obtained from hydration tests where soybeans were immersed in liquid water at temperatures of 10, 20, 30, 42 and 49°C. According to the results, the model was able to represent the main characteristics of the hydration process, with a maximum deviation of 10% in the whole set of experimental conditions.

Use of Scilab and Arduino for data acquisition environmental

The present work shows the construction of a data acquisition system using the Arduino and Scilab for integrating the sensors and the computer. The use of this system has enabled communication with some sensors, which are easily read by the computer and stored in a file. The application of this system was conducted in a commercial poultry, collecting input, output, internal and external parameters. The distribution of temperature and humidity inside was determined with this system through the construction sensor arrangement.

Computer-aided visual inspection

The quality control in industrial processes and production lines is increasingly rigorous due to governmental issues and the competition among other industries. These make new studies in this field even more important, especially on defects analysis and visual inspection. Among the methods of inspections commonly used the highlighted ones include the direct inspection that is performed without the aid of optical devices, and the remote inspection that makes use of optical instruments, both having an inspector responsible for a subjective evaluation. Such methods are usually the first used in quality control of products. In this paper we propose a remote and automatic computational image analysis to verify the presence of defects in products in a production line.