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

Sen, Maitraye; Dubey, Aditi; Singh, Ravendra; Ramachandran, Rohit

doi:10.1155/2013/843784

Cited by 40 publications

(24 citation statements)

References 53 publications

(59 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Such a PBM-DEM coupled model for particle aggregation has been reported [12]. A one way coupling consisting of PBM-DEM hybrid model has been reported [13,14] in case of continuous mixing, in which the PBM consists of spatial discretization only (as there is no size change taking place during mixing).…”

Section: Introductionmentioning

confidence: 99%

A Multi-Scale Hybrid CFD-DEM-PBM Description of a Fluid-Bed Granulation Process

et al. 2014

Self Cite

View full text Add to dashboard Cite

In this study, a hybrid multi-scale model has been developed for a continuous fluid bed wet granulation process by dynamically coupling computational fluid dynamics (CFD) with a discrete element model (DEM) and population balance model (PBM). In this process, the granules are formed by spraying the liquid binder on the fluidized powder bed. The fluid flow field has been solved implementing CFD principles and the behavior of the solid particles has been modeled using DEM techniques whereas the change in particle size has been quantified with the help of PBM. The liquid binder droplets have been modeled implicitly in DEM. A detailed understanding of the process aids in the development of better design, optimization and control strategies. The model predicts the evolution of important process variables (i.e., average particle diameter, particle size distribution (PSD) and particle liquid content) over time, which have qualitative similarity with experimentally observed trends. The advantage of incorporating the multi-scale approach is that the model can be used to study the distributions of collision frequencies, particle velocity and particle liquid content in different sections of the fluid bed granulator (FBG), in a more mechanistic manner.

show abstract

Section: Introductionmentioning

confidence: 99%

A Multi-Scale Hybrid CFD-DEM-PBM Description of a Fluid-Bed Granulation Process

et al. 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…The meaning of 'Layer 4 and wall hotspots RSD' will be explained later in this section. The oscillations present are an inherent property of DEM simulation and have been observed previously in the literature [15]. As the powder particles can interact with each other and the geometry wall and move around the space in several different ways, based on the interaction parameters, contact angle, etc., oscillations in the output variables are often observed.…”

Section: Layer2mentioning

confidence: 65%

“…DEM is considered as an explicit particle level model because it treats the particles as discrete entities and is able to capture the effect of equipment geometry, material properties and different particle-particle and particle-geometry interactions on the basis of the forces acting due to different contacts. It is an excellent tool to obtain fundamental particle level information, which is not possible based on other modeling techniques which have been used to model powder systems (i.e., population balance models (PBM) [15], continuum models [16], Markov chain models [17], etc.). DEM can be effectively used for performing qualitative process analysis, process design and optimization, equipment design studies (e.g., determining if any dead zones are present based on the flow pattern), scale-up studies, troubleshooting practical processing issues, etc.…”

Section: Introductionmentioning

confidence: 99%

“…DEM has been used widely to study different kinds of batch and continuous blenders with different mixing mechanisms for both free-flowing and cohesive particles. For example, previous works present extensive studies on the mixing dynamics of the V-blender [18], conical blender [19], slant conical blender [20], rotating drums [21] and other continuous processing blenders [15,22]. Chaudhuri et al studied the mixing of cohesive particles in a tumbling blender [7].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analyzing the Mixing Dynamics of an Industrial Batch Bin Blender via Discrete Element Modeling Method

et al. 2017

Self Cite

View full text Add to dashboard Cite

A discrete element model (DEM) has been developed for an industrial batch bin blender in which three different types of materials are mixed. The mixing dynamics have been evaluated from a model-based study with respect to the blend critical quality attributes (CQAs) which are relative standard deviation (RSD) and segregation intensity. In the actual industrial setup, a sensor mounted on the blender lid is used to determine the blend composition in this region. A model-based analysis has been used to understand the mixing efficiency in the other zones inside the blender and to determine if the data obtained near the blender-lid region are able to provide a good representation of the overall blend quality. Sub-optimal mixing zones have been identified and other potential sampling locations have been investigated in order to obtain a good approximation of the blend variability. The model has been used to study how the mixing efficiency can be improved by varying the key processing parameters, i.e., blender RPM/speed, fill level/volume and loading order. Both segregation intensity and RSD reduce at a lower fill level and higher blender RPM and are a function of the mixing time. This work demonstrates the use of a model-based approach to improve process knowledge regarding a pharmaceutical mixing process. The model can be used to acquire qualitative information about the influence of different critical process parameters and equipment geometry on the mixing dynamics.

show abstract

“…Each simulation has been run for 50 seconds. More details on the DEM simulation can be obtained from Sen et al [46]. The DEM simulations have been post-processed to obtain the mean residence time of the particles within the mixer.…”

Section: Selection Of the Control Variables And Pairing With Suitablementioning

confidence: 99%

A Hybrid MPC-PID Control System Design for the Continuous Purification and Processing of Active Pharmaceutical Ingredients

2014

Self Cite

View full text Add to dashboard Cite

Abstract:In this work, a hybrid MPC (model predictive control)-PID (proportional-integral-derivative) control system has been designed for the continuous purification and processing framework of active pharmaceutical ingredients (APIs). The specific unit operations associated with the purification and processing of API have been developed from first-principles and connected in a continuous framework in the form of a flowsheet model. These integrated unit operations are highly interactive along with the presence of process delays.Therefore, a hybrid MPC-PID is a promising alternative to achieve the desired control loop performance as mandated by the regulatory authorities. The integrated flowsheet model has been simulated in gPROMS TM (Process System Enterprise, London, UK). This flowsheet model has been linearized in order to design the control scheme. The ability to track the set point and reject disturbances has been evaluated. A comparative study between the performance of the hybrid MPC-PID and a PID-only control scheme has been presented. The results show that an enhanced control loop performance can be obtained under the hybrid control scheme and demonstrate that such a scheme has high potential in improving the efficiency of pharmaceutical manufacturing operations.

show abstract

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

Cited by 40 publications

References 53 publications

A Multi-Scale Hybrid CFD-DEM-PBM Description of a Fluid-Bed Granulation Process

A Multi-Scale Hybrid CFD-DEM-PBM Description of a Fluid-Bed Granulation Process

Analyzing the Mixing Dynamics of an Industrial Batch Bin Blender via Discrete Element Modeling Method

A Hybrid MPC-PID Control System Design for the Continuous Purification and Processing of Active Pharmaceutical Ingredients

Contact Info

Product

Resources

About