Fluidized Bed Dryers — Recent Advances

Optimization of air drying of foods

A drying model was developed for production scale fluid bed drying of granular baker's yeast. In the model, heat capacity of the dryer and the product entrained through cyclone and heat transfer from the dryer to environment were also taken into account to improve the predictive capacity of the model. Kinetic model based on the assumption that the resistances to mass transfer during drying lie not inside but liquid film around the granules was integrated into material and energy balances. Drying rate constant was determined from experimental results at constant air inlet flow rate and temperature but at varying dryer loadings. Its magnitude was found as function of amount of product loaded into the dryer. Simulations were performed for two different granule sizes and good correspondence was found between model predictions and experimental measurements for small granule sizes. For larger granules, deviations between simulations and measurements were observed and this was attributed to diffusive transport limitation of moisture inside granules, which requires mathematical description of spatial distribution of moisture and temperature inside the particles. The model can be used for design, optimization and control of drying processes for various applications.

Drying of baker's yeast in batch fluidized bed

A mathematical model of momentum, heat and mass transfer in the atomization zone was proposed. Uneven distribution of particles and entrainment effects were taken into account in the model. To verify the model an extensive experimental investigation was performed on water evaporation at different initial air temperatures, feed rates, flow rates of the drying agent and different parameters of atomization: spray cone angle and initial particle size distribution. Changes in air temperature inside the stream of sprayed material, material temperature, evaporation rate, and changes in Sauter diameter and distribution of particle diameters vs. their distance from the atomizer were determined experimentally. Damping screens allowed a flat profile of air flow rate in the tunnel to be obtained. Good agreement between experimental results and theoretical data was achieved. In the paper an attempt was made to apply the model to the calculation of spray drying in a pilot plant dryer. The air supplied to the dryer tangentially to the axis was characterized by a high swirl. The model of air flow in the dryer was determined theoretically using the Computational Fluid Dynamics CFX program. Results obtained in this way were used in our own model to determine particle trajectories in the dryer and to solve heat and mass balances for the continuous and dispersed phases. In order to consider swirl air flow pattern in the dryer, changes in heat and mass balance were made for the particle—drying agent system. The model was verified experimentally on the basis of results of investigations on drying of a 20% solution of sodium chloride. Additionally, our own results were compared with those obtained from the particle source in the cell type model for the drying system being studied. It was found that our model well described the process of drying in the analyzed system. Results obtained from our model were also very similar to the results obtained from the particle source in the cell type model. An extensive literature survey on spray drying, including unsteady state phenomena, is presented in the paper. Main sources of errors occurring in modelling of the spray drying process were discussed. A critical estimation of the existing mathematical models of the process was made and some of them were described in detail.

Development and experimental verification of momentum, heat and mass transfer model in spray drying

One-dimensional (1-D) simulation is a useful technique for the evaluation of dryer operating parameters and product properties before conducting real spray drying trials. The main advantage of a 1-D simulation tool is its ability to perform fast calculations with significant simplicity. Mathematical models can be formulated using heat, mass and momentum balances at the droplet level to estimate time-dependent gas and droplet parameters. One of the purposes of this paper is to summarize key mathematical models that may be used to perform 1-D simulation for spray drying processes, predict essential product-drying gas parameters, assess the accuracy of prediction using pilot-scale spray drying data and perhaps most importantly address the main benefits and limitations of the 1-D simulation technique in relation to industrial spray drying operations. The results of a recent international collaborative study on the development of spray drying process optimization software for skim milk manufacture are presented as an example of the application of 1-D simulation in milk processing.

/pdf/one-dimensional-simulation-of-co-current-dairy-spray-drying-1h5q2fhsps.pdf

One-dimensional simulation of co-current, dairy spray drying systems - pros and cons

On the basis of multiobjective optimization the analysis of process conditions of L-lysine drying in a fluidized-bed dryer was performed. Two methods of multiobjective optimization were used: a sequential one and the method of minimal losses. Results obtained were compared with those of one-objective optimization. The multiobjective optimization methods have been found useful in the selection of drying conditions in the dryer under consideration.

Multiobjective optimization of drying process

Mathematical modelling of spray drying

In the paper a procedure for the design of a fluidized bed dryer of biosynthesis products is presented. In this method a simplified mathematical model of heat and mass transfer in a fluidized bed dryer and deactivation kinetics of biosynthesis products during drying are utilized. The procedure is illustrated by the drying of yeast Saccharomyces cerevisiae. The effect of longitudinal dispersion on the process and results of fluidized bed drying in a continuous system are analysed.

Simulation of fluidized bed drying of biosynthesis products

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

S Grabowski

Author Tools

Chat about Author

Papers

Multiobjective optimization of drying process

Mathematical modelling of spray drying

Simulation of fluidized bed drying of biosynthesis products