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MODELING HEAT EXCHANGER PERFORMANCE FOR NON‐NEWTONIAN FLUIDS
Author(s) -
ASTERIADOU KONSTANTIA,
HASTING A.P.M.,
BIRD M.R.,
MELROSE JOHN
Publication year - 2010
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/j.1745-4530.2008.00321.x
Subject(s) - computational fluid dynamics , mechanics , fluent , heat exchanger , inlet , work (physics) , shear stress , flow (mathematics) , tube (container) , materials science , thermodynamics , mechanical engineering , physics , engineering , composite material
The flow of a shear‐thinning food product in a tube‐in‐tube‐in‐tube (TnTnT) heat exchanger (HE ) is modeled with a CFD (computational fluid dynamics) commercial code, FLUENT 6.1. Results are compared with in‐line industrial measurements. The heating medium was pressurized hot water in counter current flow and constant wall temperature. The equipment was modeled in five meshed sections: three TnTnT heat exchange domains and two 180 ° bends that connect them. Good agreement was obtained between measured and predicted values of the product outlet temperature at the end of the process. Agreement on temperature profiles in the different sections of the heater, in the center of the flow, was generally poor. Modeled temperature was higher at the outlet of the bend compared with the inlet indicating that mixing took place. Path lines of massless particles that follow the flow show a racetrack effect; with the closer the stream to the inner wall, the sooner it reaches the outlet. Predicted values of shear stress show higher levels on the internal wall, which may have an impact on potential product damage, especially for heat sensitive products.Understanding of the flow regime and temperature distribution profile in a complicated geometry such as a TnTnT HE, with the use of CFD, can lead to more efficient processes and more confidence in validating them.PRACTICAL APPLICATIONS This work describes the difficulties of validation of computational fluid dynamics (CFD) models based on in‐line measurements. It also indicates the importance of accurate monitoring methods in the food processing in order to ensure efficiency. CFD can contribute in understanding food flows and processes such as heat transfer in an enclosed domain and determine a better equipment design and selection of control points. Product and process quality can be improved with minimum cost and time investment. Physical and engineering phenomena that take place can be identified and used in favor of the process and the factory.