After casting steel slabs are reheated in a reheat furnace to temperatures in the range 1200-1250°C in order to be suitable for rolling. The high energy requirements and the importance of reheating for quality control are the motivation behind numerically modelling the furnace. Computational fluid dynamics allows us to understand the fundamental physics with great detail. It is however unclear how assumptions of such models influence the results of the simulations. In this work a steady-state model was analysed and it was found that the chosen slab temperature profile can underestimate the average heat flux on the slab surface by 30%. A slab model was employed to simulate the transient slab temperatures which results in an underestimation of the average slab temperatures by about 500°C for the case with reduced fluxes. The uniform slab temperature assumption also results in the overestimation of heat fluxes on its front and side face.

In this paper an advanced thermal lumped parameter model for a switched reluctance electric motor (SRM) is constructed, based on a 2D thermal finite element simulation of a radial cross section of the motor. When applying and combining advanced cooling methods such as direct coil cooling, end winding cooling (radial stretched) and spray cooling on an SRM, the conventional lumped parameter models can no longer be used due to the 3D and complex temperature gradients in the motor. In standard LP models, mostly one simple cooling method is implemented by which the thermal gradients are also quite simple (1D or 2D). When combining different cooling methods, the gradients become highly 3D and these LPM are no longer valid. To improve the accuracy of this problem, a fully 3D thermal finite element simulation could be performed, but this would unnecessarily increase effort, complexity and computational time. To avoid this an advanced lumped parameter model is constructed in this paper, such that the high thermal gradients are modeled in more detail. The results from one 2D finite element simulation of a radial cross section of half of a stator tooth are reduced to a simpler lumped parameter model with more nodes in the most crucial parts, i.e., where the highest thermal gradients are expected. The 2D thermal model is then expanded to a 3D lumped parameter model, including the gradients in axial direction. Using this model, various cooling configurations and geometry parameters can be varied easily such that the design of an SRM with advanced cooling can be optimized efficiently.

Thermal management of Li-ion batteries is critical for its performance and lifetime. Furthermore, when batteries are submitted to excessive temperatures by a bad thermal management system, thermal runaway can occur which can destroy the afflicted cell and the adjacent cells in a battery pack. Batteries are subject to cyclic behavior, charging and discharging, which is accompanied by a non-steady-state heat dissipation. Through thermal buffering, heat can be stored temporarily, which allows the heat transfer to the environment to be more evenly and thus reducing the maximal cooling load. Phase change materials or PCMs for thermal buffering are studied in this paper. By melting and solidifying, these substances take up and release a large amount of heat in a small volume and mass. To be able to design a thermal buffering system with PCMs, a one-dimensional transient model is developed to identify which influence design parameters have on the battery temperature. Simulations are performed for pure PCMs and for PCMs enhanced with three types of thermally conducting structures: metal foam, expanded graphite and carbon fibers. The results show that the effectiveness of thermal buffering is highly dependent on the cycle duration. For long cycles in the order of one day or more, thermal buffering can reduce peak temperature by around 4°C. For medium duration cycles in the order of several hours, peak temperatures can be reduced by around 13°C. For shorter cycles, heat buffering in the simulated cases was only slightly beneficial for the battery temperature. Furthermore, the simulations show that thermal buffering for battery packs requires a relatively small amount of PCM which results in short heat paths through the PCM. Enhancing the thermal conductivity by using thermally conductive structures slightly improves the thermal buffering performance, but might not be advisable due to the added complexity and cost.