The Analysis of Sodalime Granule Size Distributions

2002 ◽  
Author(s):  
J. R. Clarke
Keyword(s):  
Granule Size ◽  
Size Distributions

Analysis and Specification of Starch Granule Size Distributions

10.3791/61586 ◽  
2021 ◽  
Author(s):  
Ming Gao ◽  
Mahta Moussavi ◽  
Deland Myers
Keyword(s):  
Starch Granule ◽  
Granule Size ◽  
Size Distributions

Foam granulation: Effects of formulation and process conditions on granule size distributions

2012 ◽  
Vol 218 ◽  
pp. 149-156 ◽  
Author(s):  
Melvin X.L. Tan ◽  
Karen P. Hapgood
Keyword(s):  
Granule Size ◽  
Process Conditions ◽  
Size Distributions

scholarly journals Granulometric investigations of snow avalanches

2009 ◽  
Vol 55 (193) ◽  
pp. 829-833 ◽  
Author(s):  
Perry Bartelt ◽  
Brian W. McArdell
Keyword(s):  
Granule Size ◽  
Depositional Environments ◽  
Vertical Shear ◽  
Size Distributions ◽  
Size Segregation ◽  
Surface Shear ◽  
Natural Sediment ◽  
Near Surface ◽  
Sediment Size ◽  
Log Normal

AbstractAvalanche deposits consist of rounded granules composed of aggregates of snow and ice particles. The size of the granules is related to vertical shear gradients within the flow; studying the granule-size distribution may be useful in understanding the flow and stopping of avalanches. We applied a sediment-size sampling method to measure snow granule-size distributions at different depositional environments on two dry and two wet avalanche deposits at three field sites. The granule-size distributions are approximately log-normal, similar to many natural sediment deposits. The median granule size in the wet and dry avalanches varies between 65 and 162 mm. Wet avalanches tend to produce more large granules than dry avalanches, indicating both smaller flow velocities and near-surface shear gradients. Granule size is similar in frontal lobes and levee deposits, suggesting that levee formation occurs independently of the size segregation at the avalanche front.

Rheology and granule size distributions of corn starch dispersions from two genotypes and grown in four regions

2001 ◽  
Vol 15 (4-6) ◽  
pp. 453-459 ◽  
Author(s):  
J.L Paterson ◽  
A Hardacre ◽  
P Li ◽  
M.A Rao
Keyword(s):  
Corn Starch ◽  
Granule Size ◽  
Size Distributions

Granule size distributions after twin-screw granulation – Do not forget the feeding systems

2016 ◽  
Vol 106 ◽  
pp. 59-69 ◽  
Author(s):  
R. Meier ◽  
M. Thommes ◽  
N. Rasenack ◽  
K.-P. Moll ◽  
M. Krumme ◽  
...  
Keyword(s):  
Granule Size ◽  
Size Distributions ◽  
Twin Screw ◽  
Twin Screw Granulation ◽  
Feeding Systems

On the modelling of granule size distributions in twin-screw wet granulation: Calibration of a novel compartmental population balance model

2019 ◽  
Vol 341 ◽  
pp. 116-125 ◽  
Author(s):  
Daan Van Hauwermeiren ◽  
Maxim Verstraeten ◽  
Pankaj Doshi ◽  
Mary T. am Ende ◽  
Neil Turnbull ◽  
...  
Keyword(s):  
Population Balance ◽  
Granule Size ◽  
Balance Model ◽  
Population Balance Model ◽  
Wet Granulation ◽  
Size Distributions ◽  
Twin Screw

scholarly journals Predicting Pharmaceutical Particle Size Distributions Using Kernel Mean Embedding

Pharmaceutics ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 271 ◽  
Author(s):  
Daan Van Hauwermeiren ◽  
Michiel Stock ◽  
Thomas De Beer ◽  
Ingmar Nopens
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Granule Size ◽  
Data Driven ◽  
Wet Granulation ◽  
Size Distributions ◽  
Unit Operation ◽  
Particle Size Distributions ◽  
Modeling Framework

In the pharmaceutical industry, the transition to continuous manufacturing of solid dosage forms is adopted by more and more companies. For these continuous processes, high-quality process models are needed. In pharmaceutical wet granulation, a unit operation in the ConsiGma TM -25 continuous powder-to-tablet system (GEA Pharma systems, Collette, Wommelgem, Belgium), the product under study presents itself as a collection of particles that differ in shape and size. The measurement of this collection results in a particle size distribution. However, the theoretical basis to describe the physical phenomena leading to changes in this particle size distribution is lacking. It is essential to understand how the particle size distribution changes as a function of the unit operation’s process settings, as it has a profound effect on the behavior of the fluid bed dryer. Therefore, we suggest a data-driven modeling framework that links the machine settings of the wet granulation unit operation and the output distribution of granules. We do this without making any assumptions on the nature of the distributions under study. A simulation of the granule size distribution could act as a soft sensor when in-line measurements are challenging to perform. The method of this work is a two-step procedure: first, the measured distributions are transformed into a high-dimensional feature space, where the relation between the machine settings and the distributions can be learnt. Second, the inverse transformation is performed, allowing an interpretation of the results in the original measurement space. Further, a comparison is made with previous work, which employs a more mechanistic framework for describing the granules. A reliable prediction of the granule size is vital in the assurance of quality in the production line, and is needed in the assessment of upstream (feeding) and downstream (drying, milling, and tableting) issues. Now that a validated data-driven framework for predicting pharmaceutical particle size distributions is available, it can be applied in settings such as model-based experimental design and, due to its fast computation, there is potential in real-time model predictive control.

scholarly journals Shear-induced mixing of granular materials featuring broad granule size distributions

2021 ◽  
Vol 104 (4) ◽  
Author(s):  
Joyjit Chattoraj ◽  
Nguyen Hoang Huy ◽  
Saurabh Aggarwal ◽  
Mohamed Salahuddin Habibullah ◽  
Farzam Farbiz
Keyword(s):  
Granular Materials ◽  
Granule Size ◽  
Size Distributions
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