# A Validated Thermal Computational Fluid Dynamics Model of Wine Warming in a Glass
## 6 Conclusions  
This study investigated the warming of wine since the temperature significantly affects the wine's sensory attributes. It provides the physical knowledge to obtain the desired drinking temperature. The presented simulation approach accurately represents the physical process of wine warming in a glass, as validated by experiments with excellent agreement. The simulation must account for heat conduction, convection, and even thermal radiation to model the heat transfer appropriately. Leaving out thermal radiation or natural air convection leads to highly inaccurate results with relative errors of up to 66.3%. The most convective and radiative heat is introduced into the wine at a narrow horizontal  
Figure 15: Temperature increase over time of 150 mL of wine in a wine glass depending on the room temperature \(T_{\rm R}\) and initial wine temperature \(T_{0}\).  
band at the outer wall, where the glass diameter is maximal. Accelerated initial heating is governed by natural convection in wine due to the uptake of the sensible heat of the glass. Simulations and experiments suggest that the influence of the alcohol content can be neglected concerning wine warming. Therefore, the results apply to all non-sparkling wines with moderate sugar content for the investigated configuration.  
For 150 mL of wine in a medium-sized red wine glass, the temperature increase over time was determined for various combinations of initial wine (storage) and surrounding (room) temperatures. The results can give insight into how to prepare wine in varying ambient climates. The parameter study for arbitrary storage and room temperature configurations should be extended to different filling quantities, glass shapes, and wall thicknesses to obtain broader information on the temperature increase. Future studies could also consider warming wine in a decanter, which is commonly used to aerate wines for a relatively long period. In the future, a framework recently published by the authors [39; 40] will be used to derive fast and accurate metamodels, so-called digital twins, from the CFD data. The predicted warming time to reach the optimal drinking temperature could then be provided in the form of a lean app that is easily accessible to sommeliers, restaurateurs, and wine lovers.  
Conceptualization, M.K. and F.K.; data curation, M.K. and F.K.; formal analysis, M.K. and F.K.; investigation, M.K. and F.K.; methodology, M.K. and F.K.; project administration, M.S.; resources, M.S.; software, M.K. and F.K.; supervision, M.S.; validation, M.K. and F.K.; visualization, M.K. and F.K.; writing--original draft, M.K. and F.K.; writing--review and editing, M.K. and F.K. All authors have read and agreed to the published version of the manuscript.  
The APC was funded by the Open Access Publishing Fund of Technical University of Darmstadt.  
Not applicable.  
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.  
The authors would like to thank Stolzle Lausitz GmbH (WeiSWasser/Oberlausitz, Germany) for providing the dimensions and material properties of their wine glass. Moreover, the authors would like to acknowledge [PERSON] for giving valuable insights into the serving of wine from a sommelier's perspective. The work of [PERSON] is supported by the Graduate School CE within the Centre for Computational Engineering at Technical University of Darmstadt.  
The authors declare no conflicts of interest.  
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