An experimental study on intensifying osmotic dehydration was carried out in a state of nature and with acoustic cavitation of different cavitating intensity (0.5A, 0.TA and 0.9A) respectively, in which the material i...An experimental study on intensifying osmotic dehydration was carried out in a state of nature and with acoustic cavitation of different cavitating intensity (0.5A, 0.TA and 0.9A) respectively, in which the material is apple slice of 5 mm thickness. The result showed that acoustic cavitation remarkably enhanced the osmotic dehydration, and the water loss was accelerated with the increase of cavitating intensity. The water diffusivity coefficients ranged from 1.8 × 10^-10 m^2.s^-1 at 0.5A to 2.6 × 10^-10 m^2.s^-1 at 0.9A, and solute diffusivity coefficients ranged from 3.5×10^-11 m^2.s^-1 at 0.5A to 4.6×10^-11 m^2.s^-1 at 0.9A. On the basis of experiments, a mathematical model was established about mass transfer during osmotic dehydration, and the numerical simulation was carried out. The calculated results agree well with experimental data, and represent the rule of mass transfer during osmotic dehydration intensified by acoustic cavitation.展开更多
An evolutionary nature-inspired Firefly Algorithm (FA) is employed to set the optimal osmotic dehydration parameters in a case study of papaya. In the case, the functional form of the dehydration model is established ...An evolutionary nature-inspired Firefly Algorithm (FA) is employed to set the optimal osmotic dehydration parameters in a case study of papaya. In the case, the functional form of the dehydration model is established via a response surface technique with the resulting optimization formulation being a non-linear goal programming model. For optimization, a computationally efficient, FA-driven method is employed and the resulting solution is shown to be superior to those from previous approaches for determining the osmotic process parameters. The final component of this study provides a computational experimentation performed on the FA to illustrate the relative sensitivity of this evolutionary metaheuristic approach over a range of the two key parameters that most influence its running time-the number of iterations and the number of fireflies. This sensitivity analysis revealed that for intermediate-to-high values of either of these two key parameters, the FA would always determine overall optimal solutions, while lower values of either parameter would generate greater variability in solution quality. Since the running time complexity of the FA is polynomial in the number of fireflies but linear in the number of iterations, this experimentation shows that it is more computationally practical to run the FA using a “reasonably small” number of fireflies together with a relatively larger number of iterations than the converse.展开更多
Response surface methodology was used to investigate the effect of brine concentration (10% - 20%) solution temperature (35℃ - 55℃), and duration of osmosis (30 - 60 min) with respect to water loss (WL) and salt gai...Response surface methodology was used to investigate the effect of brine concentration (10% - 20%) solution temperature (35℃ - 55℃), and duration of osmosis (30 - 60 min) with respect to water loss (WL) and salt gain (SG). The solu- tion to sample ratio of 5/1 (w/w) was used. The Box-Behnken design of three variables and three levels including seventeen experiments formed by five central points were used for optimizing input parameters. Linear, quadratic and interaction effects of three variables were analyzed with respect to water loss and solid gain. For each response, second order polynomial models were developed using multiple regression analysis. Analysis of variance (ANOVA) was per- formed to check the adequacy and accuracy of the fitted models. The response surfaces and contour maps showing the interaction of process variables were constructed. The optimum operating conditions were: solution temperature 44.89℃, brine concentration of 16.53 per cent and duration of osmosis of 47.59 min. At this optimum point, water loss and salt gain were predicted to be 44.55 per cent and 2.98 percent respectively.展开更多
文摘An experimental study on intensifying osmotic dehydration was carried out in a state of nature and with acoustic cavitation of different cavitating intensity (0.5A, 0.TA and 0.9A) respectively, in which the material is apple slice of 5 mm thickness. The result showed that acoustic cavitation remarkably enhanced the osmotic dehydration, and the water loss was accelerated with the increase of cavitating intensity. The water diffusivity coefficients ranged from 1.8 × 10^-10 m^2.s^-1 at 0.5A to 2.6 × 10^-10 m^2.s^-1 at 0.9A, and solute diffusivity coefficients ranged from 3.5×10^-11 m^2.s^-1 at 0.5A to 4.6×10^-11 m^2.s^-1 at 0.9A. On the basis of experiments, a mathematical model was established about mass transfer during osmotic dehydration, and the numerical simulation was carried out. The calculated results agree well with experimental data, and represent the rule of mass transfer during osmotic dehydration intensified by acoustic cavitation.
文摘An evolutionary nature-inspired Firefly Algorithm (FA) is employed to set the optimal osmotic dehydration parameters in a case study of papaya. In the case, the functional form of the dehydration model is established via a response surface technique with the resulting optimization formulation being a non-linear goal programming model. For optimization, a computationally efficient, FA-driven method is employed and the resulting solution is shown to be superior to those from previous approaches for determining the osmotic process parameters. The final component of this study provides a computational experimentation performed on the FA to illustrate the relative sensitivity of this evolutionary metaheuristic approach over a range of the two key parameters that most influence its running time-the number of iterations and the number of fireflies. This sensitivity analysis revealed that for intermediate-to-high values of either of these two key parameters, the FA would always determine overall optimal solutions, while lower values of either parameter would generate greater variability in solution quality. Since the running time complexity of the FA is polynomial in the number of fireflies but linear in the number of iterations, this experimentation shows that it is more computationally practical to run the FA using a “reasonably small” number of fireflies together with a relatively larger number of iterations than the converse.
文摘Response surface methodology was used to investigate the effect of brine concentration (10% - 20%) solution temperature (35℃ - 55℃), and duration of osmosis (30 - 60 min) with respect to water loss (WL) and salt gain (SG). The solu- tion to sample ratio of 5/1 (w/w) was used. The Box-Behnken design of three variables and three levels including seventeen experiments formed by five central points were used for optimizing input parameters. Linear, quadratic and interaction effects of three variables were analyzed with respect to water loss and solid gain. For each response, second order polynomial models were developed using multiple regression analysis. Analysis of variance (ANOVA) was per- formed to check the adequacy and accuracy of the fitted models. The response surfaces and contour maps showing the interaction of process variables were constructed. The optimum operating conditions were: solution temperature 44.89℃, brine concentration of 16.53 per cent and duration of osmosis of 47.59 min. At this optimum point, water loss and salt gain were predicted to be 44.55 per cent and 2.98 percent respectively.
