scholarly journals Multi-zone & multi-compartment model for dynamic simulation of horizontal fluidized bed granulator

2018 ◽  
Author(s):  
Lisa Mielke ◽  
Andreas Bück ◽  
Evangelos Tsotsas
Keyword(s):  
Fluidized Bed ◽  
Solid Phase ◽  
Compartment Model ◽  
Population Balance Modeling ◽  
Surface Moisture ◽  
Model Based ◽  
System A ◽  
Preliminary Model ◽  
Ongoing Development ◽  
Drying Model

Due to the ongoing development and implementation of process control and observation techniques in production processes of particulate products, the research on complexly designed process apparatuses has become of great interest. The work presented in this paper is focused on a model-based study on a multi-chamber horizontal fluidized bed apparatus for fluidized bed layering granulation. The model for the solid phase is extended by a new drying model. Because of the great variety of parameters that influence this complex system a preliminary model-based study on a simplified setup shall show which construction or process parameters influence the product quality. Keywords: fluidized bed granulation; population balance modeling; surface moisture content; drying  

scholarly journals Variability in Estimated Modelled Insulin Secretion

2021 ◽  
pp. 193229682199112
Author(s):  
Jennifer J. Ormsbee ◽  
Hannah J. Burden ◽  
Jennifer L. Knopp ◽  
J. Geoffrey Chase ◽  
Rinki Murphy ◽  
...  
Keyword(s):  
Insulin Secretion ◽  
Kinetic Parameters ◽  
Pancreatic Beta Cells ◽  
Compartment Model ◽  
Interquartile Range ◽  
Cumulative Distribution ◽  
Model Framework ◽  
Intravenous Glucose ◽  
C Peptide ◽  
Model Based

Background: The ability to measure insulin secretion from pancreatic beta cells and monitor glucose-insulin physiology is vital to current health needs. C-peptide has been used successfully as a surrogate for plasma insulin concentration. Quantifying the expected variability of modelled insulin secretion will improve confidence in model estimates. Methods: Forty-three healthy adult males of Māori or Pacific peoples ancestry living in New Zealand participated in an frequently sampled, intravenous glucose tolerance test (FS-IVGTT) with an average age of 29 years and a BMI of 33 kg/m2. A 2-compartment model framework and standardized kinetic parameters were used to estimate endogenous pancreatic insulin secretion from plasma C-peptide measurements. Monte Carlo analysis (N = 10 000) was then used to independently vary parameters within ±2 standard deviations of the mean of each variable and the 5th and 95th percentiles determined the bounds of the expected range of insulin secretion. Cumulative distribution functions (CDFs) were calculated for each subject for area under the curve (AUC) total, AUC Phase 1, and AUC Phase 2. Normalizing each AUC by the participant’s median value over all N = 10 000 iterations quantifies the expected model-based variability in AUC. Results: Larger variation is found in subjects with a BMI > 30 kg/m2, where the interquartile range is 34.3% compared to subjects with a BMI ≤ 30 kg/m2 where the interquartile range is 24.7%. Conclusions: Use of C-peptide measurements using a 2-compartment model and standardized kinetic parameters, one can expect ~±15% variation in modelled insulin secretion estimates. The variation should be considered when applying this insulin secretion estimation method to clinical diagnostic thresholds and interpretation of model-based analyses such as insulin sensitivity.

scholarly journals Neuro-fuzzy model-based simulation of a laboratory scale clean-in-place system: A study of the rinsing process

2021 ◽  
Vol 4 ◽  
pp. 100098
Author(s):  
Rodrigo Sislian ◽  
Flávio V. da Silva ◽  
Marco A. Coghi ◽  
Rubens Gedraite
Keyword(s):  
Fuzzy Model ◽  
Laboratory Scale ◽  
Model Based ◽  
System A ◽  
Neuro Fuzzy

3D Numerical Simulation of Polydisperse Pressurized Gas-Solid Fluidized Bed

2011 ◽  
Author(s):  
P. Fede ◽  
O. Simonin ◽  
I. Ghouila
Keyword(s):  
Numerical Simulation ◽  
Fluidized Bed ◽  
Ethylene Polymerization ◽  
Solid Phase ◽  
Three Dimensional ◽  
Gas Velocity ◽  
Particle Segregation ◽  
3D Numerical Simulation ◽  
Model Predictions ◽  
The Mean

Three dimensional unsteady numerical simulations of dense pressurized polydisperse fluidized bed have been carried out. The geometry is a medium-scale industrial pilot for ethylene polymerization. The numerical simulation have been performed with a polydisperse collision model. The consistency of the polydisperse model predictions with the monodisperse ones is shown. The results show that the pressure distribution and the mean vertical gas velocity are not modified by polydispersion of the solid phase. In contrast, the solid particle species are not identically distributed in the fluidized bed indicating the presence of particle segregation.

scholarly journals Comparison of solid phase closure models in Eulerian-Eulerian simulations of a circulating fluidized bed riser

2019 ◽  
Vol 195 ◽  
pp. 39-50 ◽  
Author(s):  
Markku Nikku ◽  
Alexander Daikeler ◽  
Alexander Stroh ◽  
Kari Myöhänen
Keyword(s):  
Fluidized Bed ◽  
Circulating Fluidized Bed ◽  
Solid Phase ◽  
Closure Models

scholarly journals Experimental and Theoretical Study of the Axial Distribution of Solid Phase Particles in a Fluidized Bed

2021 ◽  
Vol 64 (4) ◽  
pp. 349-362
Author(s):  
A. V. Mitrofanov ◽  
V. E. Mizonov ◽  
N. S. Shpeynova ◽  
S. V. Vasilevich ◽  
N. K. Kasatkina
Keyword(s):  
Fluidized Bed ◽  
Field Experiments ◽  
Solid Phase ◽  
Cell Model ◽  
Experimental Studies ◽  
Parametric Identification ◽  
Resistance Coefficient ◽  
Model Material ◽  
Spherical Particles ◽  
Axial Distribution

The article presents the results of computational and experimental studies of the distribution of a model material (plastic spherical particles with a size of 6 mm) along the height of a laboratory two-dimensional apparatus of the fluidized bed of the periodic principle of action. To experimentally determine the distribution of the solid phase over the height of the apparatus, digital photographs of the fluidized bed were taken, which were then analyzed using an algorithm that had been specially developed for this purpose. The algorithm involved splitting the image by height into separate rectangular areas, identifying the particles and counting their number in each of these areas. Numerical experiments were performed using the previously proposed one-dimensional cell model of the fluidization process, constructed on the basis of the mathematical apparatus of the theory of Markov chains with discrete space and time. The design scheme of the model assumes the spatial decomposition of the layer in height into individual elements of small finite sizes. Thus, the numerically obtained results qualitatively corresponded to the full-scale field experiment that had been set up. To ensure the quantitative reliability of the calculated forecasts, a parametric identification of the model was performed using known empirical dependencies to calculate the particle resistance coefficient and estimate the coefficient of their macrodiffusion. A comparison of the results of numerical and field experiments made us possible to identify the most productive empirical dependencies that correspond to the cellular scheme of modeling the process. The resulting physical and mathematical model has a high predictive efficiency and can be used for engineering calculations of devices with a fluidized bed, as well as for setting and solving problems of optimal control of technological processes in these devices for various target functions.

Dynamical modelling of an anaerobic digestion fluidized bed reactor

1997 ◽  
Vol 36 (5) ◽  
pp. 285-292 ◽  
Author(s):  
Benjamin Bonnet ◽  
Denis Dochain ◽  
Jean-Philippe Steyer
Keyword(s):  
Fluidized Bed ◽  
Solid Phase ◽  
Biofilm Reactor ◽  
Momentum Balance ◽  
Balance Equations ◽  
Biological Variables ◽  
Dynamical Simulation ◽  
Model Derivation ◽  
The Stability ◽  
Bed Expansion

One of the main difficulties in modelling a Fluidized Bed Biofilm Reactor (FBBR) is to take into account hydraulic phenomena (such as bed expansion) and its interactions with the biological variables. In this paper, we shall present a dynamical model of the process, analyse the stability of the hydrodynamics and illustrate its performances in simulation. A key feature of the model is that it combines mass balance of the process components with momentum balance equations in order to emphasise the different hydrodynamics of the liquid phase and of the solid phase, and the interactions between both phases. The model derivation finally leads to a set of partial differential equations (PDE). This model is intended to be used as a basis for the derivation of controllers and for dynamical simulation.

Sign in / Sign up

Export Citation Format

Share Document