Heat transfer coefficients measurement in industrial freezing equipment by using heat flux sensors Alvaro Amarante * , Jean-Louis Lanoisell  e Universit e de Technologie de Compi egne, Laboratoire G enie de Proc ed es Industriels––UMR CNRS 6067, 60205 Compi egne, France Received 8 December 2003; accepted 5 April 2004 Abstract Heat transfer coefficients, either for convection or conduction mechanisms were determined by using heat flux sensors coupled to temperature measurement devices. Three distinct pieces of equipment were assessed with respect to their heat transfer capabilities. The dynamic variability of heat transfer coefficients was determined along the processing length of a conduction–convection SuperContact â tunnel and a fluidized bed freezer. The main sources of heat transfer inefficiency were uneven air speed profiles for convection and high thermal contact resistance for conduction mechanisms. Fluctuation of coolant temperature was determined to be the limiting factor in a plate freezer. Simulations either with Tylose â gel (SuperContact â tunnel) or with mashed carrot (plate freezer) were carried out to predict improvement in heat transfer coefficients. Ó 2004 Elsevier Ltd. All rights reserved. Keywords: Heat flux; Heat transfer coefficient; Heat flux sensor; Freezing 1. Introduction The simulation of the performance of a freezing sys- tem is required for its design, adaptation and operation. For this, the accurate knowledge of the heat transfer coefficients is essential in order to obtain a reliable prediction. Heat transfer coefficients and refrigeration loads, however, are often complex to be estimated in industrial processing conditions. Uncertainty in the order of 10–30% is commonly reported in the literature (Becker & Fricke, 2003; Cleland & € Ozilgen, 1998). It is still common practice to collect product tem- perature–time data and apply regression analysis using different models to derive the heat transfer coefficients. Analytical modeling is difficult due to the discontinu- ity inherent to phase change and to unsteady condi- tions (Heldman & Taylor, 1997). Numerical modeling, although accurate, is strongly dependent on the ther- mophysical properties of the product undergoing freez- ing, and results in an average value for the heat transfer coefficient during the entire processing cycle (Cleland, 1990). The dynamic variation of coefficients in function of time and in different locations in the equipment can be modeled by using CFD techniques (Verboven, Nicola € ı, Scheerlinck, & De Baerdemaeker, 1997), but again the complexity of realistic problem formulation and the intensive calculation required still keep this method of little use for practitioners. Experimentally calculated heat transfer coefficients for food products were systematically collected in the form of dimension- less correlations by different authors (Arce & Sweat, 1980; Fricke & Becker, 2002; Stewart, Becker, Greer, & Stickler, 1990), frequently in the form of Nu ¼ f ðRe; PrÞ. These correlations are useful for a first approach, but their use in real engineering problems finds limitations due to the specific configuration used in the experiments or partially available information. Moreover, informa- tion about heat transfer coefficients in industrial scale equipment is scarce in the literature. Recentresearchwork(Harris,Lovatt,&Willix,1999; Harris, Willix, & Lovatt, 2003) has presented a cus- tomized sensor for local heat transfer coefficient deter- mination.Agoodaccuracywasachieved,butthesystem needs further development for other applications, par- ticularly for reduced geometries and unsteady process- ing conditions. Theaimofthisworkistopresenttheuseofheatflux sensorscoupledtoaplasticsupportinordertomapheat Journal of Food Engineering 66 (2005) 377–386 www.elsevier.com/locate/jfoodeng * Corresponding author. Tel.: +33-3-44-23-44-49; fax: +33-3-44-23- 19-80. E-mail address: alvaro.amarante@utc.fr (A. Amarante). 0260-8774/$ - see front matter Ó 2004 Elsevier Ltd. All rights reserved. doi:10.1016/j.jfoodeng.2004.04.004