(414f) Characterizing Rheological Properties of Newtonian and Non-Newtonian Fluid Food Products with A Statistical Method | AIChE

(414f) Characterizing Rheological Properties of Newtonian and Non-Newtonian Fluid Food Products with A Statistical Method

Authors 

Burnell, C. - Presenter, Tuskegee University
Allen, T. - Presenter, Tuskegee University
Dautenhahn, P. C. - Presenter, Tuskegee University


A tank-tube viscometer and its novel Newtonian and non-Newtonian viscosity equations were developed to determine flow characteristics of Newtonian and non-Newtonian fluids. Rheological behaviors of fluid food products are characterized with the novel viscosity equations of the tank-tube viscometer.

Experimental data of accumulated amounts of a test fluid drained from the reservoir of a tank-tue viscometer at various drain durations are obtained, using an electronic balance, a data acquisition software, and EXCEL spreadsheet. The viscometer is kept at a desired temperature with a circulator. A series of experimental data for the test fluid were obtained under controlled experimental conditions such as the test fluid composition and temperatures of the test fluid.

Several series of experimental data of amounts of Newtonian fluids drained from the reservoir at various drain durations are applied to the Newtonian viscosity equation to obtain dynamic viscosity values with the linear least squares method. Several series of experimental data of amounts of shear-thinning fluids drained from the reservoir at various drain durations are applied to the non-Newtonian viscosity equation to characterize rheological behavior of non-Newtonian fluids through the linear least squares method.

The objectives of this presentation are for our students to be familiar with statistical analysis of experimental data, to understand accuracies of experimental data with correlation coefficients obtained from statistical analysis of experimental data, to be able to recognize and omit some bad experimental data deviated noticeably from the rest of experimental data set, and to identify possible experimental error sources.

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