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Detalle de: Optimal dynamic heat generation profiles for simultaneous estimation of thermal food properties using a hotwire probe: Computation, implementation and validation

Title Optimal dynamic heat generation profiles for simultaneous estimation of thermal food properties using a hotwire probe: Computation, implementation and validation
Abstract

The methodology of dynamic optimal experimental design was applied to estimate the thermal conductivity and the volumetric heat capacity of conduction heated foods simultaneously. For this purpose, a hotwire probe was used to generate heat in the thermal center of a food product. The temperature response was measured at a specified location inside the food. In order to minimize the effect of experimental input errors on the estimates, the information content of the measured temperature profiles was maximized. Optimal (dynamic) heat generation profiles as well as an optimal location to measure the temperature response in the food product were computed based on modern global optimization algorithms. These heating profiles were implemented and it was shown that the methodology guarantees an optimal regime for simultaneous parameter estimation. Pulse heating with two peaks - one at the beginning and one at the end of the experiment - was found to be an optimal heating profile. The optimal measurement position was located at some distance from, and close to, the heating probe. The mathematical and numerical outcomes of the applied methodology were interpreted in a physical context.

Apa Reference Scheerlinck, N., Berhane, N. H., Moles, C. G., Banga, J. R., & Nicolaï, B. M. (2008). Optimal dynamic heat generation profiles for simultaneous estimation of thermal food properties using a hotwire probe: Computation, implementation and validation. Journal of Food Engineering, 84(2), 297–306. 10.1016/j.jfoodeng.2007.05.019
Doi 10.1016/j.jfoodeng.2007.05.019
Publication Date Jan 2008
Publication Type Article
Researcher Julio Rodriguez Banga
Ontology Biosystems Modeling, Experimental design
Research Groups Computational Biology Lab at MBG
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