Characterizing continuous powder mixing using residence time distribution

Gao, Yijie; Vanarase, Aditya U.; Muzzio, Fernando J.; Ierapetritou, Marianthi G.

doi:10.1016/j.ces.2010.10.045

Cited by 175 publications

(54 citation statements)

References 29 publications

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“…The effect of operating parameters and powder properties on mixing performance within continuous convective blenders has been studied extensively [35][36][37][38][39]41,45]. Marikh et al [36,45] have studied the influence of mass flow rate, impeller speed and bulk powder properties on the hold up within a pilot-scale continuous mixer for different agitator types.…”

Section: Continuous Mixersmentioning

confidence: 99%

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Modeling of Particulate Processes for the Continuous Manufacture of Solid-Based Pharmaceutical Dosage Forms

2013

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Abstract:The objective of this work is to present a review of computational tools and models for pharmaceutical processes, specifically those for the continuous manufacture of solid dosage forms. Relevant mathematical methods and simulation techniques are discussed, as is the development of process models for solids-handling unit operations. Continuous processing is of particular interest in the current study because it has the potential to improve the efficiency and robustness of pharmaceutical manufacturing processes.

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Section: Continuous Mixersmentioning

confidence: 99%

“…These characteristics can be calculated from experimental data such as concentration measured at the outlet of the mixer. Composition can be assessed using near infrared spectroscopy (NIR) [34,35,[41][42][43][44]. In addition, flow trajectories within the mixer can be studied using positron emission particle tracking (PEPT) [39].…”

Section: Continuous Mixersmentioning

confidence: 99%

Modeling of Particulate Processes for the Continuous Manufacture of Solid-Based Pharmaceutical Dosage Forms

2013

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“…Investigations were realised with the temperature of the working liquid (tap water) variation between 20 and 25 o C. The volumetric fl ow rate of liquid were varied from 0.0084 to 0.0167 dm 3 • s -1 . The working volume (volume of TRMF generator) was equal to 5 • 10 -3 m 3 .…”

Section: Experimental Apparatusmentioning

confidence: 99%

Experimental study and mathematical modeling of the residence time distribution in magnetic mixer

Rakoczy¹,

Kordas²,

Grądzik³

et al. 2013

Polish Journal of Chemical Technology

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This study reports on research results in the fi eld of a mixing process under the action of a transverse rotating magnetic fi eld (TRMF). The main objective of this paper is to present the effect of this type of a magnetic fi eld on residence time distribution (RTD) measurements. This paper evaluates the performance of a magnetic mixer by comparing the results of an experimental investigations in a pilot set-up and theoretical values obtained from mathematical model. This model consisting of the set of ideal continuous stirred tank reactors (CSTR) fi tted well the experimental data.

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“…Among the several other modeling approaches which exist in literature, for example, Monte-Carlo methods [12], continuum and constitutive models [13], statistical models [14,15], compartment models [16,17], RTD models [18,19] and hybrid models [20,21], discrete element modeling (DEM) is one of the fundamental modeling approaches that is able to capture the particle level physics. In DEM, each particle is treated as a discrete entity where the trajectory of the particles is tracked and the collision between particles is modeled.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Development and Comparison of a Hybrid PBM-DEM Description of a Continuous Powder Mixing Process

Sen

Dubey

Singh

et al. 2013

Journal of Powder Technology

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is paper describes the development of a multidimensional population balance model (PBM) which can account for the dynamics of a continuous powder mixing/blending process. e PBM can incorporate the important design and process conditions and determine their effects on the various critical quality attributes (CQAs) accordingly. e important parameters considered in this study are blender dimensions and presence of noise in the inlet streams. e blender dynamics have been captured in terms of composition of the ingredients, (relative standard deviation) RSD, and (residence time distribution) RTD. PBM interacts with discrete element modeling (DEM) via one-way coupling which forms a basic framework for hybrid modeling. e results thus obtained have been compared against a full DEM simulation which is a more fundamental particle-level model that elucidates the dynamics of the mixing process. Results show good qualitative agreement which lends credence to the use of coupled PBM as an effective tool in control and optimization of mixing process due to its relatively fewer computational requirements compared to DEM.

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Characterizing continuous powder mixing using residence time distribution

Cited by 175 publications

References 29 publications

Modeling of Particulate Processes for the Continuous Manufacture of Solid-Based Pharmaceutical Dosage Forms

Modeling of Particulate Processes for the Continuous Manufacture of Solid-Based Pharmaceutical Dosage Forms

Experimental study and mathematical modeling of the residence time distribution in magnetic mixer

Mathematical Development and Comparison of a Hybrid PBM-DEM Description of a Continuous Powder Mixing Process

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