A compilation of correlation parameters for predicting the enthalpy and thermal conductivity of solid foods within the temperature range of −40°C to +40°C

Amos, Nissim; Willix, J.; Chadderton, T.; North, Mike F.

doi:10.1016/j.ijrefrig.2008.01.011

Cited by 12 publications

(5 citation statements)

References 38 publications

(51 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…In TM-0, meals are assumed to have uniform specific heat capacity c f ood , thermal conductivity λ f ood and density ρ f ood , which are assessed from meat and sauce values via a weighted-average procedure (Sepúlveda & Barbosa-Cánovas, 2003). As discussed in Rabi et al (2012), thermophysical properties directly or indirectly invoked in TM-0 were either taken from the literature (CEN, 1993;Zhang, Lyng, Brunton, Morgan, & McKenna, 2004;Amos, Willix, Chadderton, & North, 2008;Marcotte, Taherian, & Karimi, 2008), estimated in situ or measured by means of CT-Metre (CSTB Grenoble). Table 1 shows thermophysical parameters for the numerical solution of governing equations.…”

Section: Thermophysical Parameters and Numerical Solution Methodsmentioning

confidence: 99%

Blast-cooling of beef-in-sauce catering meals: numerical results based on a dynamic zero-order model

et al. 2014

View full text Add to dashboard Cite

Beef-in-sauce catering meals under blast-cooling have been investigated in a research project which aims at quantitative HACCP (hazard analysis critical control point). In view of its prospective coupling to a predictive microbiology model proposed in the project, zero-order spatial dependence has proved to suitably predict meal temperatures in response to temperature variations in the cooling air. This approach has modelled heat transfer rates via the a priori unknown convective coefficient hc which is allowed to vary due to uncertainty and variability in the actual modus operandi of the chosen case study hospital kitchen. Implemented in MS Excel®, the numerical procedure has successfully combined the 4th order Runge-Kutta method, to solve the governing equation, with non-linear optimization, via the built-in Solver, to determine the coefficient hc. In this work, the coefficient hc was assessed for 119 distinct recently-cooked meal samples whose temperature-time profiles were recorded in situ after 17 technical visits to the hospital kitchen over a year. The average value and standard deviation results were hc = 12.0 ± 4.1 W m-2 K-1, whilst the lowest values (associated with the worst cooling scenarios) were about hc » 6.0 W m-2 K-1.

show abstract

Section: Thermophysical Parameters and Numerical Solution Methodsmentioning

confidence: 99%

Blast-cooling of beef-in-sauce catering meals: numerical results based on a dynamic zero-order model

et al. 2014

View full text Add to dashboard Cite

show abstract

“…As discussed in Rabi et al (2012), thermophysical properties directly or indirectly invoked in TM-0 were either taken from the literature (CEN, 1993;Zhang, Lyng, Brunton, Morgan, & McKenna, 2004;Amos, Willix, Chadderton, & North, 2008;Marcotte, Taherian, & Karimi, 2008), estimated in situ or measured by means of CT-Metre (CSTB Grenoble). Table 1 shows thermophysical parameters for the numerical solution of governing equations.…”

Section: Thermophysical Parameters and Numerical Solution Methodsmentioning

confidence: 99%

Blast-cooling of beef-in-sauce catering meals: numerical results based on a dynamic zero-order model

2014

IJFS

View full text Add to dashboard Cite

Beef-in-sauce catering meals under blast-cooling have been investigated in a research project which aims at quantitative HACCP (hazard analysis critical control point). In view of its prospective coupling to a predictive microbiology model proposed in the project, zero-order spatial dependence has proved to suitably predict meal temperatures in response to temperature variations in the cooling air. This approach has modelled heat transfer rates via the a priori unknown convective coefficient hc which is allowed to vary due to uncertainty and variability in the actual modus operandi of the chosen case study hospital kitchen. Implemented in MS Excel ® , the numerical procedure has successfully combined the 4 th order Runge-Kutta method, to solve the governing equation, with non-linear optimization, via the built-in Solver, to determine the coefficient hc. In this work, the coefficient hc was assessed for 119 distinct recently-cooked meal samples whose temperature-time profiles were recorded in situ after 17 technical visits to the hospital kitchen over a year. The average value and standard deviation results were hc = 12.0 ± 4.1 W m −2 K −1 , whilst the lowest values (associated with the worst cooling scenarios) were about hc ≈ 6.0 W m −2 K −1 .

show abstract

“…Currently, two methods for determining the thermophysical properties of food products are the most common: calculation based on the nutrient composition [11][12][13] and the use of experimental data [14][15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…Researchers [12] were among the first to obtain and arrange the thermophysical characteristics of individual components in food products (proteins, fats, carbohydrates) in a wide temperature range and developed the corresponding calculation models. In [13], an extensive collection of empirical data from various researches on the nutritional composition of food products and polynomial relationships for calculating their thermophysical properties in the temperature range of minus 40 °C to plus 40 °C are presented. Experimental data [14] on the thermal conductivity of beef meat, fat and bones are of special interest.…”

Section: Introductionmentioning

confidence: 99%

Thermal conductivity factor for beef of NOR and DFD grades at the subcryoscopic temperatures

Berezovsky

Королев

Sarantsev

2021

Teor. prakt. pererab. mâsa (Print)

View full text Add to dashboard Cite

Thermal conductivity factor and specific isobaric heat capacity of food products are currently the most important parameters in the development of mathematical models for food freezing and thawing and in improving production technology. There is significant variance among the existing experimental data for the thermal conductivity factor in meat. Most of the modern calculated relationships are based on the nutritional approach, which favorably differs by the ability to calculate the thermophysical characteristics of any food products. However, the calculation error at the subcryoscopic temperatures may be 15% to 20%. The development of superchilling as a way of storing meat requires high accuracy of freezing time calculation, including vacuumpacked boneless meat. In the presented article, the authors investigated hydrogen index, cryoscopic temperature, frozen moisture proportion and thermal conductivity factor for beef M. longissimus dorsi samples of NOR and DFD grades. It was found that DFD beef is characterized by 10% to 12% higher values of thermal conductivity factor in comparison with NOR grade. Using the method of regression analysis, the authors developed empirical relationships for calculating the thermal conductivity factor of meat depending on its temperature and pH level. Unlike cryoscopic temperature and frozen moisture proportion, pH is easy to measure and may be easily used on a conveyor belt for more accurate assessment of meat thermophysical properties. With an increase in pH from 5.3 to 7, an increase in cryoscopic temperature is observed from minus 0.94 °C to minus 0.72 °C. It has been shown that one of the factors for the higher cryoscopic temperature and higher pH level of DFD beef is higher water-holding capacity with less strongly bound moisture.

show abstract

A compilation of correlation parameters for predicting the enthalpy and thermal conductivity of solid foods within the temperature range of −40°C to +40°C

Cited by 12 publications

References 38 publications

Blast-cooling of beef-in-sauce catering meals: numerical results based on a dynamic zero-order model

Blast-cooling of beef-in-sauce catering meals: numerical results based on a dynamic zero-order model

Blast-cooling of beef-in-sauce catering meals: numerical results based on a dynamic zero-order model

Thermal conductivity factor for beef of NOR and DFD grades at the subcryoscopic temperatures

Contact Info

Product

Resources

About