Cold chain in catering : experimental data in a french hospital and thermal modelling

International audienceThis study presents the results of an experimental measurement campaign on the food cold chain in a Parisian hospital. It focuses on two main steps of this cold chain: rapid cooling after cooking and warming up before consumption. Despite French regulations requirements, it is observed that around 70% of the products do not reach the target temperature of +10°C within 2 hours after cooking. It is also observed that only 30% of the products reach the target temperature of +63°C before being served to the patient. The experimental results are compared to the results of modelling. The proposed modelling takes into account the technical parameters of the used equipments and the heat transfer between the air inside the equipment and the product. This heat transfer is calibrated on the experimental data. The results of the modelling correctly fit the observed values

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

International audienceBeef-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

Modélisation et renouvellement d'une chaîne du froid dans le secteur de la restauration en milieu hospitalier

International audienceReengineering process is intended both for users and equipment designers. It may redefine the process management such as thermal constraints applied to food product in order to enhance their safety. The objective of this study is to develop models able to predict the thermal history of food products all along its processing chain and to study the influence of process parameters on the microbial growth. In this purpose, these models are coupled with microbial models in order to assess the impact of process control parameters on the final concentration of micro-organisms. The studied case corresponds to the processing of meals (beef in sauce) prepared for differed consumption in a central kitchen at a French Parisian hospital. Each step of the process is modelled by using a deterministic thermal approach. However, the input parameters of the model are often random variables. The input parameters of the models include technical features (e.g. cooling and heating capacity, airflow, thermal inertia effects of the equipment, thermal capacities of the products) as well as other process parameters set by the operators (e.g. duration of cooling down and of warming up, thermostat setup, charge of the equipment). According to the operator's influence on these last parameters, they could be considered as random. A sensitivity analysis showed that the reheating step is one of the important key points to achieve targeted food safety objectives. It also showed that the cooling rate in the cooling cell is another key parameter to be accounted for