Modeling and Control of Batch Pulsed Top-spray Fluidized bed Granulation

In this thesis, a thorough study of the batch top-spray fluidized bed granulation was carried out including experimental study, population balance model (PBM), computational fluid dynamic (CFD) study and control strategy development. For the experimental study, the influence variables of pulsed frequency, binder spray rate and atomization pressure of a batch top-spray fluidized bed granulation process were studied using the Box-Behnken experimental design method. Different mathematical models were developed to predict the mean size of granules, yield, relative width of granule distribution, Hausner ratio and final granule moisture content. Validation experiments have shown the reliability and effectiveness of using the Box-Behnken experimental design method to study a fluidized bed granulation process. The one-dimensional population balance models (ODPBMs) have been developed to model a pulsed top-spray fluidized bed granulation, linking the operating factors of the pulsed frequency, the binder spray rate, and atomization air pressure with the granule properties to predict granule growth behavior at different operating conditions. A multi-stage open optimal control strategy based on the developed ODPBMs was proposed to reduce the model and process mismatch through adjusting the trajectory of the evolution of the granule size distribution at predefined sample intervals. The effectiveness of the proposed modeling and multi-stage open optimal control strategy has been validated by experimental and simulation tests. In addition, an Eulerian-Eulerian two-fluid model (EETFM) was developed to describe the gas-particle two-phase flow in the fluidized bed granulator. By computational fluid dynamic analysis, it has been proven that the fluidized bed granulation system is not homogeneous, based on which a two-compartmental population balance model (TCPBM) was developed to describe the particle growth in the fluidized bed granulation. Validation experiments have shown the effectiveness and superior accuracy of the TCPBM comparing with the ODPBM in predicting the final particle size distributio

The effect of binder concentration in fluidized-bed granulation: Transition between wet and melt granulation

According to the binder nature, fluidized-bed granulation (FBG) is usually classified as wet or melt granulation. In particular, the industrial urea granulation performed in fluidized beds, is often called “melt granulation” because a highly concentrated urea solution is used as binder (between 95–97 wt%) (Cotabarren et al., 2012). However, plant disturbances can cause changes in binder urea concentration and thus granulation can shift from melt to wet granulation and vice versa. In a previous investigation, the granulation system urea (seeds)–urea (binder) was extensively studied in a pilot-scale batch fluidized-bed granulator (Veliz Moraga et al., 2015). Besides, the effect of seed size, bed temperature, binder flowrate and fluidization and atomization air flowrates on process variables as well as on product properties were studied. The aim of this work is to analyze the effect of the binder urea concentration on the urea granulation performance and product properties. This concentration was varied from 87.5 wt% to 98 wt%, while the fluidization air velocity, urea melt flowrate, bed temperature set-point and atomization air flowrate were kept constant. The product properties (percentage of agglomerates and coated particles, crushing strength and moisture content) and granulation efficiency are discussed in terms of the transition from wet to melt granulation. The critical urea content was experimentally found; indeed, urea concentrations lower than the critical one dramatically affect the product quality. Finally, the criterion proposed by Villa et al. (2016) for predicting agglomerates formation is used to determine the minimum allowable binder urea concentration. The prediction is consistent with the trends experimentally observed, indicating the good capacity of the criterion to identify the boundary for agglomeration occurrence.Fil: Bertin, Diego Esteban. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Cotabarren, Ivana María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Veliz Moraga, Sussy Ximena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Piña, Juliana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; ArgentinaFil: Bucala, Veronica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Planta Piloto de Ingeniería Química. Universidad Nacional del Sur. Planta Piloto de Ingeniería Química; Argentin

Mechanical dispersion of semi-solid binders in high-shear granulation

Granulation is an important industrial process used to produce many foods, medicines, consumer products, and industrial intermediate products. This thesis focuses on high shear wet granulation with the specific case study of detergent manufacture using a high shear pin mixer. The key rate process in detergent manufacturing was determined to be the mechanical dispersion of the semi-solid surfactant binder. The pin mixer and mechanical dispersion utilized experiments, population balance models, and discrete element method (DEM) models. The mechanical dispersion of the surfactant binder was studied using a lab scale 6 liter pin mixer. An experimental method was developed to isolate mechanical dispersion from the other rate processes of granulation. Experiments were conducted over a range of impeller speeds, mixing times, and surfactant injection temperatures. Two surfactants where used each with different yield stresses. The yield stresses of both surfactants were characterized using uniaxial compression tests and extrapolated to the impact speeds observed in the pin mixer. Using the yield stress to calculate the Stokes deformation number revealed that the breakage of surfactant would occur at all impact conditions in the pin mixer. The mechanical dispersion results demonstrated that the rate process could be modeled as a breakage process. The results determined that the key parameter governing the mechanical dispersion of paste was the number of revolutions of the impeller. This implies that impaction or sudden stress from the impeller is the mechanism that causes nuclei breakage. The results of the mechanical dispersion experiments were then used to develop a mechanistic semi-empirical model. Because the results indicated that breakage should occur for every impact with the impeller, the model was based on particle impact efficiency between the impeller and nuclei. The impact efficiency was described in a way similar to particle gas filtration where the Stokes number is the characteristic dimensionless group. The population balance model was breakage only and was able to accurately predict the full size distributions of the surfactant nuclei. The results showed that the model was able to accurately account for the effect of tip speed and number of revolutions. This was found by fitting the simulation to a single impeller speed and then predicting the size distributions by varying only the velocity input. Finally, a DEM unit shear cell was developed to understand the transmission of stress from a bulk material to a single large particle of interest similar to surfactant nuclei. The simulation examined the effect of both shear rate, placement of the large particle, and the material properties. The results determined that the material properties used in the simulation had a much greater effect on the shear profile and stress in the shear cell than the effect of the macroscopic shear rate. Using the von Mises yield criteria, the results demonstrated that the shear cell transmitted more stress to the large particle than the yield stress characterized experimentally from the surfactant. The results indicate that the surfactant should break in shear within the pin mixer. Mechanical dispersion has been successfully modeled for the case of detergent granulation in the pin mixer. The combined results demonstrate that mechanical dispersion of surfactant can be modeled as a breakage process. The number of impeller orations and the Stokes number are key parameters to accurately describe and model the simulation. The surfactant should break apart due to both impact and shear within the granulator

Computer-aided modeling for efficient and innovative product-process engineering

Model baserede computer understøttet produkt process engineering har opnået øget betydning i forskelligste industrielle brancher som for eksampel farmaceutisk produktion, petrokemi, finkemikalier, polymerer, bioteknologi, fødevarer, energi og vand. Denne trend er forventet at fortsætte på grund af substantielle fordele, hvilke computer understøttede metoder medfører. Den primære forudsætning af computer understøttet produkt process engineering erselvfølgelig den tilgængelighed af modeller af forskellige typer, former og anvendelser. Udviklingen af den påkrævet modellen for de undersøgte systemer er normalt en tidskrævende udfordring og derfor mest også dyrt. Den involverer forskelligste trin, fagekspert viden og dygtighed og forskellige modellerings værktøjer. Formålet af dette projekt er at systematisere den model udviklings proces og anvendelse og dermed øge effektiviteten af modeller såvel somkvaliteten. Den væsentlige bidrag af denne PhD afhandling er en generisk metodologi for proces model udviklingen og anvendelse i kombination med grundige algoritmiske arbejdes diagrammer for de forskellige involverede modeller opgaver og udviklingen af computer understøttede modeller rammer hvilke er strukturbaseret på den generiske metodologi, delvis automatiseret i de forskellige arbejdstrin og kombinerer alle påkrævet værktøjer, understøttelseog vejledning for de forskellige arbejdstrin. Understøttede modelleringsopgaver er etableringen af modeller mål, indsamling af de nødvendige informationer, model formulering inklusive numeriske analyser, etablering af løsningsstrategier og forbinding med den passende løsningsmodul, model identificering og sondering såvel som model anvendelse for simulation og optimering. Den computer understøttede modeller ramme blev implementeret i en brugervenlig software. En række forskellige demonstrationseksempler fra forskellige områder i kemisk ogbiokemiske engineering blev løst for udvikling og validering af den generiske modellerings metodologi og den computer understøttet modeller ramme anvendt på den udviklet software værktøj.Model-based computer aided product-process engineering has attained increased importance in a number of industries, including pharmaceuticals, petrochemicals, fine chemicals, polymers, biotechnology, food, energy and water. This trend is set to continue due to the substantial benefits computer-aided methods provide. The key prerequisite of computer-aided productprocess engineering is however the availability of models of different types, forms andapplication modes. The development of the models required for the systems under investigation tends to be a challenging, time-consuming and therefore cost-intensive task involving numerous steps, expert skills and different modelling tools. The objective of this project is to systematize the process of model development and application thereby increasing the efficiency of the modeller as well as model quality.The main contributions of this thesis are a generic methodology for the process of model development and application, combining in-depth algorithmic work-flows for the different modelling tasks involved and the development of a computer-aided modelling framework. This framework is structured, is based on the generic modelling methodology, partially automates the involved work-flows by integrating the required tools and, supports and guides the userthrough the different work-flow steps. Supported modelling tasks are the establishment of the modelling objective, the collection of the required system information, model construction including numerical analysis, derivation of solution strategy and connection to appropriate solvers, model identification/ discrimination as well as model application for simulation and optimization. The computer-aided modelling framework has been implemented into an userfriendlysoftware.A variety of case studies from different areas in chemical and biochemical engineering have been solved to illustrate the application of the generic modelling methodology, the computeraided modelling framework and the developed software tool

Inside the Phenomenological Aspects of Wet Granulation: Role of Process Parameters

Granulation is a size-enlargement process by which small particles are bonded, by means of various techniques, in coherent and stable masses (granules), in which the original particles are still identifiable. In wet granulation processes, the powder particles are aggregated through the use of a liquid phase called binder. The main purposes of size-enlargement process of a powder or mixture of powders are to improve technological properties and/or to realize suitable forms of commercial products. A modern and rational approach in the production of granular structures with tailored features (in terms of size and size distribution, flowability, mechanical and release properties, etc.) requires a deep understanding of phenomena involved during granules formation. By this knowledge, suitable predictive tools can be developed with the aim to choose right process conditions to be used in developing new formulations by avoiding or reducing costs for new tests. In this chapter, after introductive notes on granulation process, the phenomenological aspects involved in the formation of the granules with respect to the main process parameters are presented by experimental demonstration. Possible mathematical approaches in the granulation process description are also presented and the one involving the population mass balances equations is detailed

Multi-scale modeling and optimization for industries with formulated products

[ES] La tesis titulada "Multi-scale Modeling and optimization for Industries with Formulated Products" se centra en el desarrollo de modelos matemáticos y técnicas de optimización para este tipo de productos. Por un lado la tesis se focaliza en modelado de secadores con diferentes metodologías. Primero, se desarrolla un modelo cinético de secado de una una única gota. Luego, se desarrolla un modelo basado en mecánica de fluidos computacional (CFD) para los secadores y el cuál se ha validado a escala industrial. Finalmente, se desarrollan modelos basados en "data-driven" y modelos subrogados para reducir el coste computacional del modelo en CFD sin perder su nivel de detalle. Por otro lado, la tesis tiene una segunda parte donde se focaliza en el desarrollo de modelos de optimización matemática para el tratamiento de residuos y la revalorización del biogás

Control of detergent properties in a spray dryer process

EngDThis research details the building, implementation and validation of models designed for the control of specific powder detergent properties in a spray dryer process. Findings are reported in two sections; the control of moisture content, particle size distribution (PSD) and bulk density properties; the development of a process model for the online estimation and simulation of the process. The project was completed at Procter & Gamble’s Newcastle Innovation Centre, using a mixed flow spray dryer for the case study. Moisture content can be controlled using a soft sensor to enable estimation of this parameter at a higher sampling frequency than manual measurements of the powder. The proposed empirical model proved to be the most successful approach compared to heat and mass balances. Each model required adjustment of a parameter following the first manual measurement of moisture in a batch run. Control of PSD can be achieved through analysis of droplet size distribution. The dominant influence on the final PSD is the atomization of the slurry, which can be manipulated through changes to the ratio of air and slurry flow to the nozzle. However, numerous sources of variability necessitate continuous amendments to the atomizing air flow rate to maintain the PSD at the required target value. The use of an automatic cascade loop control strategy facilitated manipulation of the air flow to the nozzle, improving control of PSD considerably, halving the response time and reducing variability of mean particle size. Control of bulk density is dependent on an understanding of the key factors that determine the final density of the powder. The density model proposed incorporates statistics for the impact of packing, air entrapment and drying. The model details the limits of the rate of air injection into the slurry, its influence on density control and provides explanations for density changes during the process. viii Separate studies demonstrate the influence of each property on process conditions in each compartment of the mixed flow spray dryer. A model linking these properties to the process conditions has been formulated to provide optimal control strategies for the process. The spray drier involves 3 compartments; a spray chamber, an inner fluid bed and an outer fluid bed. Computational fluid dynamics are used to estimate flow properties and residence times of the chamber and a CSTR model is used to model the fluid beds. The constant drying rate curve (CDRC) and reactor engineering approach (REA) drying models have been implemented and fitted using historical data. A sigmoidal model approach to the CDRC has been included to enable a smoother transition between the constant and falling rate periods. Simulation of the process and online estimations of the powder’s properties were assessed. In each batch, the CDRC model provided the most accurate representation of the process. The CDRC model is recommended for control of the spray drying process and in simulation studies

A compartmental CFD-PBM model of high shear wet granulation

The conventional, geometrically lumped description of the physical processes inside a high shear granulator is not reliable for process design and scale-up. In this study, a compartmental Population Balance Model (PBM) with spatial dependence is developed and validated in two lab-scale high shear granulation processes using a 1.9L MiPro granulator and 4L DIOSNA granulator. The compartmental structure is built using a heuristic approach based on computational fluid dynamics (CFD) analysis, which includes the overall flow pattern, velocity and solids concentration. The constant volume Monte Carlo approach is implemented to solve the multi-compartment population balance equations. Different spatial dependent mechanisms are included in the compartmental PBM to describe granule growth. It is concluded that for both cases (low and high liquid content), the adjustment of parameters (e.g. layering, coalescence and breakage rate) can provide a quantitative prediction of the granulation process