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

Winiczenko, Radosław; Górnicki, Krzysztof; Kaleta, Agnieszka

doi:10.3390/sym12020260

Cited by 4 publications

(1 citation statement)

References 62 publications

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“…17 Ferrández et al 17 also successfully replaced constrained mono-objective problems with MOO for highpressure thermal processes in food treatment, as the latter gave a better, adequate set of parameters with less computation time. Several studies have been dedicated to MOO through GA 16,18,19 and hybrid ANN-MOGA. [20][21][22][23][24] The utilization of ANN and GA can be efficient for multivariate modeling and optimization in the case of non-linear variables.…”

Section: Introductionmentioning

confidence: 99%

Ascorbic acid nanoencapsulation using polyelectrolyte complex formation and optimization using hybrid artificial neural network‐genetic algorithm

Khuntia,

Mitra

2023

JSFA Reports

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BackgroundsThe polyelectrolyte complex (PEC) formation using chitosan (Cs) and alginate (Alg) has been employed to carry out Vitamin C (VC) nanoencapsulation because of its instability in adverse conditions. This method includes VC nanoencapsulation using physical cross‐linking. The effect of the mixing order as well as the different mass ratios of both the polymer and the VC content, were investigated on the size, pdi, zeta potential, encapsulation efficiency (EE%), and yield%. Hence, considering different mass ratios of both polymer (4:1–1:4) and VC content (10%–30% w/w of Cs) as independent variables, PECs were formed using 0.1% (w/v) of Cs and Alg solution.ResultThe result showed that, for equal mass ratio (1:1) of Cs and Alg, the addition of Alg solution to Cs solution led to lower particle size, while higher particle size was observed with reverse order of addition. However, no significant effect of polymer mass ratios was observed on particle size and NPs stability, while EE varied with VC concentration. Artificial neural network (ANN) was applied to train the experimental parameters Cs: Alg ratios (X1:X2) and VC content (X3) for the output variables. Moreover, process optimization was carried out using multi‐objective genetic algorithm (MOGA) with the goal of lowering particle size and increasing EE while increasing nanoparticle yield.ConclusionThe PEC method effectively encapsulated VC as obtained from higher EE. The Cs: Alg ratio of 4:2.1 and 18% VC content (w/w of Cs) was found optimum for nanoencapsulation. The final ANN‐GA model showed an acceptable agreement with experimental data.

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Section: Introductionmentioning

confidence: 99%

Ascorbic acid nanoencapsulation using polyelectrolyte complex formation and optimization using hybrid artificial neural network‐genetic algorithm

Khuntia,

Mitra

2023

JSFA Reports

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Identification of the potato moisture diffusion coefficient considering shrinkage: a nonlinear estimator approach to an inverse problem

Vera,

Mendoza

2024

Braz. J. Chem. Eng.

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This study aimed to determine the moisture diffusion coefficients of potatoes by taking into account the shrinkage that occurs during the drying process. In addition, the study also considered the scenario where shrinkage was neglected for comparison purposes. The main objective of this study is to establish the importance of considering shrinking phenomena for proper modeling of the drying process and to highlight the advantages of a recently published methodology for estimating parameters. The potato samples, which were dried in a moisture balance, were prepared such that the moisture diffusion was unidimensional. The determination of the moisture diffusivity when shrinkage is neglected is based on the analytical solution of the diffusion equation when constant diffusivity is assumed. When shrinkage is considered, the diffusion coefficient is identified via a nonlinear estimator constructed based on a numerical solution to the diffusion equation. The shrinking rate and the drying kinetics are the information fed to the algorithm. Arrhenius-type expressions for the dependency of the diffusivity on temperature were obtained, and from them, activation energies were determined for both cases: considering and neglecting shrinkage. From the comparison of the effective diffusion coefficients obtained, we conclude that when shrinkage is neglected, the diffusion coefficients are underestimated. A model for the diffusion coefficient as a function of temperature and concentration is provided.

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Potential of drying carrot using ozone pre-treatment: Mass transfer modelling and techno-functional properties

Santos,

Almeida,

Monteiro

et al. 2024

Food and Bioproducts Processing

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

Cited by 4 publications

References 62 publications

Ascorbic acid nanoencapsulation using polyelectrolyte complex formation and optimization using hybrid artificial neural network‐genetic algorithm

Ascorbic acid nanoencapsulation using polyelectrolyte complex formation and optimization using hybrid artificial neural network‐genetic algorithm

Identification of the potato moisture diffusion coefficient considering shrinkage: a nonlinear estimator approach to an inverse problem

Potential of drying carrot using ozone pre-treatment: Mass transfer modelling and techno-functional properties

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