STATISTICAL OPTIMIZATION AND SENSITIVITY ANALYSIS OF RHEOLOGICAL MODELS USING CASSAVA STARCH
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IAEME
Abstract
Description
Models are sometimes employed to determine some parameters that can be used to
distinguish between different types of food samples. Rheological models can be used to
predict flow for severe conditions where it is difficult to determine the nature of the
fluid flow, consequently it is essential to select the appropriate rheological models. This
study aims to propose a rheological model that describes an ideal cassava starch
rheological behavior and its influence on state variables such as concentration and
temperature in order to validate the rheological models. In this study, five rheological
models (namely; Power-law model, Robertson-stiff model, Herschel-Bulkey model,
Prandtl-Eyring model and Bigham plastic model) were amended into various statistical
model by adding the error variance (e). This study concludes that Herschel-Bulkley
model and Robertson-stiff model closely explain the rheological patterns occurring
during the production of cassava starch. The sensitivity evaluation of other rheological
models demonstrate that the validity of Power-law model, Herschel-Bulkley model and
Robertson stiff model is not notably influenced by changes in concentration and
temperature of the cassava starch. Nevertheless, the Prandtl-Eyring and Bingham
plastic models are noted to have less reliable prediction at lower temperature and
higher concentration respectively.
Keywords
AC Collections. Series. Collected works, TP Chemical technology