Evaluation of the Mass Diffusion Coefficient and Mass Biot Number Using a Nondominated Sorting Genetic Algorithm

A precise determination of the mass diffusion coefficient and the mass Biot number is indispensable for deeper mass transfer analysis that can enable finding optimum conditions for conducting a considered process. The aim of the article is to estimate the mass diffusion coefficient and the mass Biot number by applying nondominated sorting genetic algorithm (NSGA) II genetic algorithms. The method is used in drying. The maximization of coefficient of correlation (R) and simultaneous minimization of mean absolute error (MAE) and root mean square error (RMSE) between the model and experimental data were taken into account. The Biot number and moisture diffusion coefficient can be determined using the following equations: Bi = 0.7647141 + 10.1689977s − 0.003400086T + 948.715758s2 + 0.000024316T2 − 0.12478256sT, D = 1.27547936∙10−7 − 2.3808∙10−5s − 5.08365633∙10−9T + 0.0030005179s2 + 4.266495∙10−11T2 + 8.33633∙10−7sT or Bi = 0.764714 + 10.1689091s − 0.003400089T + 948.715738s2 + 0.000024316T2 − 0.12478252sT, D = 1.27547948∙10−7 − 2.3806∙10−5s − 5.08365753∙10−9T + 0.0030005175s2 + 4.266493∙10−11T2 + 8.336334∙10−7sT. The results of statistical analysis for the Biot number and moisture diffusion coefficient equations were as follows: R = 0.9905672, MAE = 0.0406375, RMSE = 0.050252 and R = 0.9905611, MAE = 0.0406403 and RMSE = 0.050273, respectively.

Moisture diffusion coefficient estimation in peas drying by means of a modified Hawlader and Uddin method

The aim of the present work is to determine the moisture diffusion coefficient in peas applying, in a first step, a methodology previously published in the literature by Uddin et al.[1] for determining constant diffusion coefficients taking in account the volume reduction associated to the drying process. Then, in a second step, refine it by means of an optimization step. The optimization step is justified because the methodology of Uddin et al. is based in a solution of the diffusion equation that is not mathematically valid for the drying-shrinking problem. Keywords: : moisture diffusivity; drying-shrinking; peas drying

Effect of Suction Cycles and Suction Gradients on the Water Retention Properties of a Hard Clay

The effect of suction cycles and suction gradients on a hard clay is investigated. The cylindrical samples of the hard clay are prepared to carry out the hydration and dehydration tests with different suction gradient and suction cycles. The results show that the suction gradient has little effect on the suction-water content relation, while the suction cycle has great effect on it, particularly the first cycle of hydration and dehydration. The apparent moisture diffusion coefficient of the hard clay has been identified by the use of a two-dimensional diffusion model. The moisture diffusion coefficient varies between 4.10−11 m2/s and 2.10−10 m2/s and it decreases during dehydration while the relative humidity is less than 85%. The results also show that the suction cycles play little effect on the moisture diffusion coefficient.

Modeling of mass transfer performance of hot-air drying of sweet potato (Ipomoea Batatas L.) slices

In order to investigate the transfer characteristics of the sweet potato drying process, a laboratory convective hot air dryer was applied to study the influences of drying temperature, hot air velocity and thickness of sweet potato slice on the drying process. The experimental data of moisture ratio of sweet potato slices were used to fit the mathematical models, and the effective diffusion coefficients were calculated. The result showed that temperature, velocity and thickness influenced the drying process significantly. The Logarithmic model showed the best fit to experimental drying data for temperature and the Wang and Singh model were found to be the most satisfactory for velocity and thickness. It was also found that, with the increase of temperature from 60 to 80?C, the effective moisture diffusion coefficient varied from 2.962?10-10 to 4.694?10-10 m2?s-1, and it fitted the Arrhenius equation, the activation energy was 23.29 kJ?mol-1; with the increase of hot air velocity from 0.423 to 1.120 m?s-1, the values of effective moisture diffusion coefficient varied from 2.877?10-10 to 3.760?10-10 m2?s-1; with the increase of thickness of sweet potato slice from 0.002 m to 0.004 m, the values of effective moisture diffusion coefficient varied from 3.887?10-10 to 1.225?10-9 m2?s-1.