Micro-CFD modelling of ultrafiltration bio-fouling

Petrosino, Francesco; Luca, Giorgio De; Curcio, Stefano; Wickramasinghe, S. Ranil; Chakraborty, Sudip

doi:10.1080/01496395.2022.2075759

Cited by 14 publications

(2 citation statements)

References 31 publications

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“…For example, in the field of bioscience, nanoscale material parameters can be coupled with macroscopic material models (Curcio et al, 2018; De Luca et al, 2014; Petrosino et al, 2019). The interactions and couplings between these scales are highly complex, and a single‐scale model often fails to fully describe the system behavior (Petrosino et al, 2020; Petrosino et al, 2023).…”

Section: Introductionmentioning

confidence: 99%

Numerical study of heat and mass transfer during drying process of barley grain piles based on the pore scale

Li,

Wang,

Yang

et al. 2023

J Food Process Engineering

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Drying conditions greatly affect the quality of grains, and efforts should be made to minimize the loss of grains during the drying process. In this study, numerical simulations were conducted to investigate the drying behavior of barley at both the particle and grain pile scales by solving the coupled heat and moisture equation. The model was validated using thin‐layer drying experimental results from the literature, and it was found that the simulated values of average moisture content of the grain had a maximum relative error of 7.73% compared to the experimental values. Furthermore, the impact of air temperature and relative humidity on drying was analyzed. The results showed that the heat and mass transfer coefficients of barley grains varied along the surface, the irregularity of the barley grains resulted in an asymmetric distribution of the surface heat transfer coefficient. Regions with lower porosity in the grain pile exhibited lower rates of heat and moisture transfer, particularly in the central area. Moisture transfer within the grain pile dominated the drying time compared to heat transfer. It was also observed that air temperature and relative humidity were the main variables influencing the drying rate of the grains. As the inlet air temperature increased from 45 to 70°C, the drying rate of the grain pile increased from 0.068% to 0.085%(d.b.)/min. Similarly, reducing the relative humidity from 40% to 18% resulted in an increase in the drying rate from 0.062% to 0.075%(d.b.)/min (within the first 10 min).Practical ApplicationsThis study employed numerical simulations to investigate the drying behavior of barley at both the particle scale and grain pile scale. The developed model was validated using experimental data from thin‐layer drying studies, confirming a significant agreement between the simulated and experimental values. Moreover, the study unveiled the impact of air temperature and relative humidity on the drying process. It was observed that regions with lower porosity within the grain pile experienced reduced rates of heat and moisture transfer. Notably, moisture transfer dominates the drying time. Additionally, the study emphasized the substantial influence of air temperature and relative humidity on the drying rates. These findings offer valuable insights for optimizing drying parameters, including air temperature and relative humidity, in order to enhance the efficiency and quality of the barley grain drying process.

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Section: Introductionmentioning

confidence: 99%

Numerical study of heat and mass transfer during drying process of barley grain piles based on the pore scale

Li,

Wang,

Yang

et al. 2023

J Food Process Engineering

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“…Several studies have been reported in the literature to address this discrepancy; however, no research has been conducted on scaling-up purposes within various Outotec GTK LabCell™ cells at the laboratory scale. The use of multiscale approaches in computational fluid dynamics also gained attention in understanding hydrodynamics to address these discrepancies in scaling up (Basavarajappa and Miskovic 2019;Hadane et al 2019;Petrosino et al 2022;Wang et al 2018). As a novel approach, this technical study will address these limitations and examine the effect of impeller speed, airflow rate, and cell volume together with their interactions on flotation responses (k, metallurgical response, and PSD) through the scaling process.…”

Section: Introductionmentioning

confidence: 99%

Influence of hydrodynamic variables on scaling up of mechanical flotation cells

et al. 2022

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Flotation performance is influenced by many hydrodynamic variables, such as impeller speed, airflow rate, and cell geometry. These variables’ effects and interactions remain unsatisfactorily explored, especially concerning scaling-up procedures. As an innovative approach, this study considered factorial-designed experiments to explore the effects of hydrodynamic factors (impeller tip speed and superficial gas velocity) on scaling up the Outotec GTK LabCell™ mechanical flotation machine cells, common equipment used as a benchmark for many industrial pre-feasibility studies. Therefore, the influence of hydrodynamic variables and their interactions on flotation performance was evaluated in two cells (2 L and 7.5 L). The evaluation was based on the flotation rate constant “k” calculated by first- and second-order equations. Analysis of the particle size distribution indicated that the performance of the two cells was different, as shown by the finer concentrate for the 2-L cell compared to the 7.5-L cell. The outcomes demonstrated that symmetrical design in the geometry of mechanical flotation cells would lead to an accurate scaling up based on the metallurgical responses. Otherwise, the scaling procedure could only be accurate under some specific conditions. As a criterion, the results showed that using k, the scaling-up process between these two GTK LabCell™ mechanical flotation machine cells (2 L and 7.5 L) would be possible only under a specific superficial gas velocity (0.14 cm/s) apart from the impeller tip speed (R2 = 1). These results could potentially be key for the future design and development of mechanical flotation cells.

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Microscale Modelling of Flow, Heat and Mass Transport During Vacuum Cooling of Porous Foods: Effective Property Computation

2023

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A microscale modelling framework to compute effective properties related to flow, heat and mass transfer during vacuum cooling (VC) of porous foods was developed. A heterogeneous computational domain reconstructed from steamed bread (SB) was used for modelling, while the cellular water transport in SB investigated using nuclear magnetic resonance was applied for model validation. The computed porosity (63.47 ± 1.05%), effective permeability (1.91 ± 0.39 × 10−11 m2), effective thermal conductivity, (0.33 ± 0.08 W m−1 K−1), and effective diffusivity (5.56 × ± 0.24 10−8 m2 s−1) were in the same range as those measured from the experiment/literature. Also, the analysis revealed that microstructural variability significantly affected the estimated effective properties. The microscale model yielded results similar to the lumped formulation but provided details not visible in the latter. Therefore, the developed model provides a framework for multiscale modelling, which could lead to a better understanding of the underlying moisture loss mechanisms during VC.

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Micro-CFD modelling of ultrafiltration bio-fouling

Cited by 14 publications

References 31 publications

Numerical study of heat and mass transfer during drying process of barley grain piles based on the pore scale

Numerical study of heat and mass transfer during drying process of barley grain piles based on the pore scale

Influence of hydrodynamic variables on scaling up of mechanical flotation cells

Microscale Modelling of Flow, Heat and Mass Transport During Vacuum Cooling of Porous Foods: Effective Property Computation

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