Tailoring particle shape for enhancing the homogeneity of powder mixtures: Experimental study and DEM modelling

Asachi, Maryam; Behjani, Mohammadreza Alizadeh; Nourafkan, Ehsan; Hassanpour, Ali

doi:10.1016/j.partic.2020.03.006

Cited by 5 publications

(2 citation statements)

References 44 publications

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“…Offers comprehensive data on the development and enlargement of granules at the particle level [70]. Capable of simulating intricate particle geometries and interactions [71].…”

Section: Discrete Element Methods (Dem)mentioning

confidence: 99%

Process Simulation of Twin-Screw Granulation: A Review

Arthur,

Rahmanian

2024

Pharmaceutics

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Twin-screw granulation has emerged as a key process in powder processing industries and in the pharmaceutical sector to produce granules with controlled properties. This comprehensive review provides an overview of the simulation techniques and approaches that have been employed in the study of twin-screw granulation processes. This review discusses the major aspects of the twin-screw granulation process which include the fundamental principles of twin-screw granulation, equipment design, process parameters, and simulation methodologies. It highlights the importance of operating conditions and formulation designs in powder flow dynamics, mixing behaviour, and particle interactions within the twin-screw granulator for enhancing product quality and process efficiency. Simulation techniques such as the population balance model (PBM), computational fluid dynamics (CFD), the discrete element method (DEM), process modelling software (PMS), and other coupled techniques are critically discussed with a focus on simulating twin-screw granulation processes. This paper examines the challenges and limitations associated with each simulation approach and provides insights into future research directions. Overall, this article serves as a valuable resource for researchers who intend to develop their understanding of twin-screw granulation and provides insights into the various techniques and approaches available for simulating the twin-screw granulation process.

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“…Offers comprehensive data on the development and enlargement of granules at the particle level [70]. Capable of simulating intricate particle geometries and interactions [71].…”

Section: Discrete Element Methods (Dem)mentioning

confidence: 99%

Process Simulation of Twin-Screw Granulation: A Review

Arthur,

Rahmanian

2024

Pharmaceutics

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“…Parameters from literature. Many DEM studies on segregation have taken either all or merely a selection of the parameters from the literature (Asachi et al, 2021;Chibwe et al, 2020;Cliff et al, 2021;Hong et al, 2021;Ketterhagen et al, 2007Ketterhagen et al, , 2009Ketterhagen and Hancock, 2010;Kou et al, 2013Kou et al, , 2015Kou et al, , 2018Kou et al, , 2019Liao et al, 2023;Mandal and Khakhar, 2019;Tian et al, 2022;Wu et al, 2013;Xu et al, 2018bXu et al, , 2021You et al, 2016;Yu et al, 2018;Yu and Saxén, 2010, 2012Zhang et al, 2021;Zhao and Chew, 2020a). This approach has the same shortcoming as the previous group, since the parameters are obtained from resources that have not conducted calibration.…”

Section: Determination Of Dem Parameters For Segregationmentioning

confidence: 99%

DEM Modelling of Segregation in Granular Materials: A Review

Hadi,

Roeplal,

Pang

et al. 2024

KONA

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Segregation control is a challenging yet crucial aspect of bulk material handling processes. The discrete element method (DEM) can offer useful insights into segregation phenomena, provided that reliable models are developed. The main challenge in this regard is finding a good balance between including particle-level details and managing the computational load. This is especially true for industrial applications, where multi-component flows consisting of particles with various irregular shapes and wide size distributions are encountered in huge amounts. In this work, we review the state of the art in DEM modelling of segregation in industrial applications involving the gravity-driven flow of dry, cohesionless granular materials. We start by introducing a novel scientific notation to distinguish between different types of mixtures. Next, we review how parameters for mixture models are determined in the current literature, and how segregation is affected by material, geometric and operational parameters based on these models. Finally, we review existing segregation indices and their applicability to multi-component segregation. We conclude that systematic calibration procedures for segregation models are currently missing in the literature, and realistic models representing multicomponent mixtures have not yet been developed. Filling these gaps will pave the way for optimising industrial processes dealing with segregation.

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