Combinatory Models for Predicting the Effective Thermal Conductivity of Frozen and Unfrozen Food Materials

Joint Authors

Karthikeyan P
Reddy, Kalvala Srinivas

Source

Advances in Mechanical Engineering

Issue

Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-14, 14 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2010-06-07

Country of Publication

Egypt

No. of Pages

14

Main Subjects

Mechanical Engineering

Abstract EN

A model to predict the effective thermal conductivity of heterogeneous materials is proposed based on unit cell approach.

The model is combined with four fundamental effective thermal conductivity models (Parallel, Series, Maxwell-Eucken-I, and Maxwell-Eucken-II) to evolve a unifying equation for the estimation of effective thermal conductivity of porous and nonporous food materials.

The effect of volume fraction (υ) on the structure composition factor (ψ) of the food materials is studied.

The models are compared with the experimental data of various foods at the initial freezing temperature.

The effective thermal conductivity estimated by the Maxwell-Eucken-I + Present model shows good agreement with the experimental data with a minimum average deviation of ±8.66% and maximum deviation of ±42.76% of Series + Present Model.

The combined models have advantages over other empirical and semiempirical models.

American Psychological Association (APA)

Reddy, Kalvala Srinivas& Karthikeyan P. 2010. Combinatory Models for Predicting the Effective Thermal Conductivity of Frozen and Unfrozen Food Materials. Advances in Mechanical Engineering،Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-506539

Modern Language Association (MLA)

Reddy, Kalvala Srinivas& Karthikeyan P. Combinatory Models for Predicting the Effective Thermal Conductivity of Frozen and Unfrozen Food Materials. Advances in Mechanical Engineering No. 2010 (2010), pp.1-14.
https://search.emarefa.net/detail/BIM-506539

American Medical Association (AMA)

Reddy, Kalvala Srinivas& Karthikeyan P. Combinatory Models for Predicting the Effective Thermal Conductivity of Frozen and Unfrozen Food Materials. Advances in Mechanical Engineering. 2010. Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-506539

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-506539