Thermal Conductivity of Fresh Lamb Meat, Offals and Fat in the Range ‐40 to +30oC: Measurements and Correlations
ABSTRACT The thermal conductivity of fresh lamb meat, offals and fat was measured over the temperature range -40°C to +30°C using a guarded hot plate apparatus. Simple empirical equations were presented for the conductivity of high-moisture (65 to 80%) meat and offals. With independently obtained values of physical parameters, several theoretical models were tested to sec if thermal conductivity could be calculated from composition and temperature. Over a wide range of compositions and temperatures, best predictions (in terms of mean, standard deviation and range of errors) were obtained with Levy's modification to the Maxwell-Eucken equation. Its accuracy was not unduly sensitive to the uncertainties in the values of the physical parameters, the prediction errors remaining in the range ± 10% for all reasonable values of the latter.
- [Show abstract] [Hide abstract]
ABSTRACT: In this paper influence of the water bolus temperature on the thermal distribution inside an homogeneous muscles phantom are analyzed for a microwave applicator for superficial hyperthermia on small subcutaneous tumors. Temperature simulations were used for the analysis considering two models with different thermal interfaces between the water bolus and the phantom. The results show dependence of the temperature peak deepness which position reduces increasing the bolus temperature with differences between the two models considered. These results can be used for a preliminary guideline for the choice of water bolus temperature to be used on hyperthermia treatment according to the tumor size and deepness.01/2009;
- Journal des Maladies Vasculaires 09/2010; 35(5):320-320. · 0.24 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: During processing of a food, its temperature, moisture and other compositions, structure, etc., can change, continuously changing its physical properties. Realistic simulation of food processes require dynamic estimation of the food physical properties as they continue to change during the process. Having a few data points for a few states of the material, as is true for the majority of food properties data, is not sufficient for realistic process simulations. The goal of this article is a practical one: it is to develop a concise resource for the equations that can estimate food properties as they change during processing. Such a resource should make computer-aided food product, process and equipment design one step closer to reality by making the necessary input parameters available in one location and in a format that can be readily used in a simulation software. Several equilibrium, transport and electrical properties are included. The estimation equations for any property are chosen from among the most successful and accurate, staying away from property estimators that have theoretical basis but have not been as successful for food materials. For each property, implementation of its prediction equations in a computer model has also been discussed. Accuracy of each property estimation process have been included from the literature, showing most properties can be estimated to within 10% accuracy, sufficient for modeling purposes. Having such reasonable prediction models has the important implication that unavailability of sufficient data, that is expected to be always true due to the variety and complexity of food materials and processes, is not a bottleneck for computer-aided food process engineering.Journal of Food Engineering 05/2013; 116(2):483–504. · 2.58 Impact Factor