Numerical Simulation of the Heat Transfer in a Refrigerated Trailer Equipped with Eutectic Plates for Frozen Food Delivery

The present work reports the Computational Fluid Dynamics simulation and analysis of the heat transfer inside a refrigerated truck trailer equipped with three eutectic plates and fans. The numerical model solves the conjugated heat transfer inside the trailer in 2D using the �� −�� Shear Stress Transport (SST) turbulence model. It has been already favorably validated against the numerical and experimental data of Lafaye de Micheaux el al. (2015) by Croquer et al. (2019). These simulations are used to improve the configuration of the refrigeration system with the eutectic plates as well as to investigate the feasibility of the eutectic plates for the transport of frozen food products under different operating loads and transport temperature requirements. Three eutectic plates having an optimal inter-plate distance of 6 cm to maximize the air flow between the plates (Croquer et al., 2019) are either placed in series on the roof of the trailer or vertically at its back. For both configurations, fans are blowing the air from the eutectic plates to the inside of the trailer and modeled by adding a source term into the momentum equations. During the door opening period, the configuration with the plates placed on the roof of the trailer without the cargo has noticeably lower area-averaged temperature inside the trailer than the configuration with the plates placed on the back of the trailer due to the presence of the circulation zones and the cold plates located near the doorway. However, introduction of the cargo into the simulations eliminates the formation of the circulation zones that prevents the infiltration of the atmospheric air. Also, the configuration with the plates placed on the roof of the trailer allows the atmospheric air to infiltrate earlier, therefore resulting in an overall higher temperature observed in the cargo

Design and Optimization of a Double-intake and Rotor Squirrel Cage Fan Using OpenFoam and Metamodels

The range hood is crucial in kitchens during cooking activities. Inside the residential houses, cooking activities are one of the main sources of particle emission, which decreases the air quality level. Furthermore, multiple studies found a strong correlation between the particles emitted from cooking activity and chronic obstructive pulmonary disease (COPD), lung cancer and diabetes. The use of an efficient range hood is essential to maintain a healthy air quality level inside the house. The fan is the main component inside a range hood. Most of the range hoods are equipped with an axial fan or a one rotor squirrel cage fan. In the present study, a powerful double-intake and rotor squirrel cage fan is designed and optimized by using a developed optimization process loop based only on open source libraries. Dakota is used to achieve the sampling and build the surrogate surfaces, Salome to generate the geometry and the mesh grid and OpenFoam for the calculations. More than eleven design parameters are selected in the impellers, blades and volute regions. The two objective functions: total efficiency and the generated noise are improved by maximizing and minimizing their values, respectively. The Latin Hypercube Sampling (LHS) method is selected to achieve sampling over more than 363 design parameters set. In order to model the turbulent flow, a 3D incompressible simpleFoam solver is used and coupled to the Multiple Reference Frame (MRF) approach. The Kriging and the quadratic polynomial response surface are used to expand the design space and improve the objective functions. The total efficiency is improved by 12 % and the noise is reduced by 2 sones compared to the initial design. The Kriging Metamodel predicts with less than 2 % the total efficiency and 1% the generated noise compared to the OpenFoam calculation. A large 3D coherent structure is observed in the volute region with a scattered turbulent region near the outlet. The optimal design is validated at the design point against the produced prototype, with an error of 2.8 % and 1.3 % on the total efficiency and generated noise, respectively