Research Seminar Series
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Audrey Luiz, Room 413,
Modeling and Scale-up of Agitated Drying of Particles
About the Speaker
Benjamin Glasser received his BS (1989) and MS (1991) in Chemical Engineering from Wits University, Johannesburg, South Africa. He obtained his PhD, also in Chemical Engineering, from Princeton University (1996), USA. He then spent a year as a postdoctoral fellow at Cambridge Hydrodynamics Inc. In 1997 he joined the Department of Chemical and Biochemical Engineering at Rutgers University where he is currently a Professor. His honors include the Merck Excellence Faculty Development Award the Bristol-Myers Squibb Young Faculty Award, and the Rutgers University Scholar-Teacher Award for excellence in research and teaching. Professor Glasser serves as Director of the Pharmaceutical Engineering Program and Director of the Catalyst Manufacturing Center at Rutgers. His research interests include flow and segregation of granular materials, drying of particulates, the mechanics of fluidized beds, multiphase flows and reactors, and nonlinear dynamics of transport processes.
Drying of particles is important in a number of industries ranging from ceramic processing to pharmaceutical manufacturing. Particles are often agitated during drying in order to improve heat and mass transfer. This can lead to particle agglomeration or attrition problems as the drying process proceeds. Unwanted particle agglomeration or attrition due to agitated drying is often discovered upon scale-up from the lab to the plant. Traditional laboratory drying equipment has not successfully reproduced the degree of agglomeration or attrition observed at scale. This discrepancy may be attributed to the fact that as batch size increases during scale-up, the compressive and shearing forces experienced by the particles increase. Such behavior can be extremely troublesome in the pharmaceutical industry, for example, where drying of drug crystals can lead to unacceptable levels of attrition. This situation can potentially lead to millions of dollars lost to down time in an industry where drug compounds can be worth millions of dollars per kilogram. In this talk we will discuss work we have done on developing an understanding of granular flow, mixing, and scale-up in bladed mixers during agitated drying. We make use of the Discrete Element Method (DEM) to model the flow of particles in bladed mixers. We compare the simulations to experimental measurements in laboratory and pilot scale equipment. We discuss scale-up of granular flow in bladed mixers and contrast wet and dry flows. Finally, we will discuss the application of these results to improving the operation of industrial drying processes.
Design and operation optimization of LNG mixed refrigerant processes
About the Speaker
Mengyu Wang is a PhD candidate working under supervision of Associate Professor Ali Abbas in the School of Chemical and Biomolecular Engineering.
Natural gas is widely recognized as a clean and economical energy source, due to its low carbon intensity and relatively lower price compared to other fossil fuels. It is predicted that by 2030, natural gas will grow to a 37% share of fossil fuels in power generation from 30% today. Transporting natural gas over long distances to far markets has been made possible via liquefied natural gas (LNG) process technologies. The LNG industry using proven technologies has expanded from small capacities of around one million tonne per annum (MTPA) in 1970s to the current so-called “mega trains” with capacity above 7.8 MTPA.
This seminar will discuss the role of natural gas in serving the growing global energy demand and will introduce gas liquefaction process technologies used in the LNG industry. The seminar will then focus on the development of an optimization framework that considers a combination of critical techno-economic variables. A comprehensive design and operation optimization analysis of the LNG process will then be presented highlighting the energy and cost savings possible though model-based optimisation. Finally, the optimisation framework is shown to be a significant tool for the LNG plant in developing effective responses to upstream upsets (gas concentration and pressure from upstream gas well), and therefore possible life extensions of semi-depleted gas wells.