TY - JOUR
T1 - Predicting the performance of direct contact membrane distillation (DCMD)
T2 - Mathematical determination of appropriate tortuosity based on porosity
AU - Kim, Woo Ju
AU - Campanella, Osvaldo
AU - Heldman, Dennis R.
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2021/4
Y1 - 2021/4
N2 - Direct contact membrane distillation (DCMD) is a promising novel membrane technology for management of waste streams from food manufacturing operations, and for concentration of value-added components from the waste streams. Due to the complexity of technology, the development of prediction models to describe mass transfer during DCMD presents a significant contribution. The overall objective of this investigation was to propose models for prediction of membrane tortuosity based on measured porosity, and to confirm the models by experimental measurements of water flux for DCMD applications. Three types of commercial membranes with porosities ranging from 69.8% to 87.9% were investigated. Eleven (11) different models for prediction of tortuosity from porosity were identified from published literature and evaluated. Statistical comparisons of predicted and experimental water flux were conducted using root-mean-square-error, accuracy factor, and bias factor to identify the models providing the closest agreement between predicted and experiment outcomes. The statistical comparisons indicated that models based on the fractal theory provide the closest agreement between predicted and experimental water flux for DCMD applications. In addition, the proposed model provided best agreement between predicted and experimental temperatures. The simulations of water flux were used to evaluate the influence of membrane surface area on water flux, and capabilities of the tortuosity models. As the width and length of membrane were increased, the differences in water flux predicted by proposed model, as compared to the traditional model, increased significantly. These outcomes confirm the importance using appropriate models for prediction of tortuosity for DCMD applications.
AB - Direct contact membrane distillation (DCMD) is a promising novel membrane technology for management of waste streams from food manufacturing operations, and for concentration of value-added components from the waste streams. Due to the complexity of technology, the development of prediction models to describe mass transfer during DCMD presents a significant contribution. The overall objective of this investigation was to propose models for prediction of membrane tortuosity based on measured porosity, and to confirm the models by experimental measurements of water flux for DCMD applications. Three types of commercial membranes with porosities ranging from 69.8% to 87.9% were investigated. Eleven (11) different models for prediction of tortuosity from porosity were identified from published literature and evaluated. Statistical comparisons of predicted and experimental water flux were conducted using root-mean-square-error, accuracy factor, and bias factor to identify the models providing the closest agreement between predicted and experiment outcomes. The statistical comparisons indicated that models based on the fractal theory provide the closest agreement between predicted and experimental water flux for DCMD applications. In addition, the proposed model provided best agreement between predicted and experimental temperatures. The simulations of water flux were used to evaluate the influence of membrane surface area on water flux, and capabilities of the tortuosity models. As the width and length of membrane were increased, the differences in water flux predicted by proposed model, as compared to the traditional model, increased significantly. These outcomes confirm the importance using appropriate models for prediction of tortuosity for DCMD applications.
KW - DCMD membrane Intrinsic parameter
KW - Direct contact membrane distillation
KW - Porosity
KW - Tortuosity
KW - Water flux prediction
UR - http://www.scopus.com/inward/record.url?scp=85096519013&partnerID=8YFLogxK
U2 - 10.1016/j.jfoodeng.2020.110400
DO - 10.1016/j.jfoodeng.2020.110400
M3 - Article
AN - SCOPUS:85096519013
SN - 0260-8774
VL - 294
JO - Journal of Food Engineering
JF - Journal of Food Engineering
M1 - 110400
ER -