L11
Heat Transfer

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10:40
conference time (CEST, Berlin)
Predictive Model for Transient Thermal Analysis of Domestic Oven
27/10/2021 10:40 conference time (CEST, Berlin)
Room: L
J. Chhatre (Whirlpool India, IND)
J. Chhatre (Whirlpool India, IND)
Cooking process involves changes in the chemical composition and structure of food by controlled heat addition and an oven is one of the devices widely used for it. A cooking cycle consists of a sequence of phases ( e.g. preheat, cooking mode). The process is very sensitive to temperatures, both in steady and transient phases. So it is very critical to maintain the desired temperature and heating rate inside the oven cavity to achieve the right quality of food. Energy norms are becoming stringent which trigger the need for energy efficient designs and operations. Opportunities in design include exploring and evaluating ideas in structural and material domains. And various possible control strategies are to be studied for improving efficiency during operation. Owing to these needs, using predictive methodology and systems engineering approach has become very crucial. Most conventional ovens have resistive heating elements as heat sources and a fan ( optional) inside the cavity. In the present study a mathematical model is developed for thermal behavior of the oven using a lumped modeling approach. The model is developed using Dymola. It can predict transient temperature profiles at different locations of the oven (like walls, air, door) and energy consumption including decomposition of energy. The results produced by the model are compared with a set of experimental data generated in the lab. The model can support the design phase to analyze effects of different design factors like insulation thicknesses, different wall emissivities, cavity dimensions, heater areas, door structure, material selections etc. on transient thermal behavior of the oven and to generate tradeoffs between them. It can also support design of control algorithms to tune control factors and to compare different control strategies. Development of control algorithms focus on achieving desired temperature profile inside the cavity using minimum energy. So the design ( structure) and control need to interact starting from the initial phase to achieve optimum temperature and energy performance. The existing model can act as a plant (virtual design prototype) in control algorithm development process providing futuristic data to control algorithms.
Transient and steady analysis, Cooking modes, mathematical modeling, lumped modeling approach, controller tuning
11:00
conference time (CEST, Berlin)
Reduced Order Models for Thermal Management in Batteries
27/10/2021 11:00 conference time (CEST, Berlin)
Room: L
T. Szpartaluk-Kozak, M. Kurzynka (QuickerSim Sp. z o.o., POL)
T. Szpartaluk-Kozak, M. Kurzynka (QuickerSim Sp. z o.o., POL)
The efficient design of battery cooling systems requires extensive testing and simulation. Current software possibilities allow for advanced CFD simulations or low fidelity, thermal mass-based models. In high fidelity simulations, the preparation of computational models requires a vast amount of time. Execution times are long. Obtained results often require time-consuming post-processing. Models created using this approach are not suited for the software-in-the-loop and system-level simulations. On the other end of the spectrum, low fidelity thermal lumped models are available. They offer fast execution but require the identification of parameters based on the experiment or CFD simulations. Low-fidelity models do not capture the spatial distribution of temperatures. They are significant for safety precautions, cell aging, and cooling systems design. In both cases, complete design iteration can span up to multiple days on the initial stage. To accelerate this design process, we suggest a reduced-order modeling approach. We present an efficient framework for the creation of reduced-order models for nonlinear thermal problems. Our key feature is the efficient management of ROMs of thermal components. We can assemble, run and post-process models with hundreds of components on a regular desktop computer. Equivalent full order meshes would reach a size of over 5 million degrees of freedom. We handle nonlinear material properties and fluid components. Our framework is capable of handling industrial-scale applications. We can generate digital twins with real-time execution. We present the methodology of assembling ROM of thermal systems out of ROMs generated for each unique component. We describe the assembly process of the ROM on component and system levels. Next, we present a methodology to handle nonlinear data, retaining low memory consumption. In the last part, we present Q-Bat- - the simulation environment based on our methodology. The framework is based on the MATLAB- scripting language. We show how to streamline and automate the ROM creation and analysis. The model can be compiled to the Simulink- environment, enabling system-level simulations. We present computational results and compare them, in terms of accuracy and performance, against high fidelity CFD analysis.
Reduced Order Modelling, Digital Twin, Thermal Management
11:20
conference time (CEST, Berlin)
Transfer of Heat Transfer Simulation Results to a Mixed Reality Platform for Industry 4.0
27/10/2021 11:20 conference time (CEST, Berlin)
Room: L
R. Stauch, M. Sonntag, C. Polak, D. Mayer, A. Saramet, M. Schnierle (Hochschule Esslingen, DEU)
R. Stauch, M. Sonntag, C. Polak, D. Mayer, A. Saramet, M. Schnierle (Hochschule Esslingen, DEU)
Thermal design of plastic injection mold is important because it not only affects the part quality and the cycle time, but also ensures the manufacturability of the part. The thermal management of the injection molding process is especially important for molding of multi-component parts. The temporal and the spatial temperature evolution in a bi-injection mold has been computed as a transient 3D heat transfer simulation using the multi region CHT solver of the CFD simulation software OpenFOAM. Beside the molded parts the simulation model comprises several cooling channels, electric heating elements and insulating elements, which are modeled using several regions and boundary conditions. Applying an automated modification of boundary conditions and volumetric field sources during the simulation run, the temperature controlling of the cooling channels and the heating elements have been also included in the simulation model. A variation of the injection molding process with extended heating elements incorporating an increase of the heating power and a scenario of a complete failure of the cooling system are simulated and the resulting temperature distributions are compared with the reference case. All the temperature distributions are post-processed with ParaView. Subsequently, the post-processed simulation results are exported via Blender to the mixed reality software VAL HoloDesk, which has been developed in the Virtual Automation Lab (VAL) at the UAS Esslingen. The complete post-processing workflow from OpenFOAM to VAL HoloDesk has been explicitly derived. The resulting digital twin of the injection mold extends common digital twins by the implementation of the spatial temperature fields. This extension enables an interactive post-processing and the study of the temperature distribution inside the injection mold. The mixed reality environment enables immersive visualization of the simulation model and offers a detailed analysis of temperatures of selected spatial locations on the surfaces of the molded parts and of the injection mold. Thus, the thermal management of the injection mold can be incorporated in the digital development process.
OpenFOAM, Heat Transfer, Industry 4.0, Augmented Reality, Mixed Reality, Digital Twin
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