CFD modeling of the heat and mass transfer in a refrigerated truck trailer equipped with eutectic plates
Bibliographic record
Abstract
An eutectic refrigeration system is proposed to replace conventional refrigeration systems powered by fossil fuel consumption for transporting frozen food products via refrigerated truck trailers. To study the feasibility of the eutectic system, numerical models have been first developed and favorably validated against published numerical and experimental results. The consolidated model has then been used to accurately predict the performance of the eutectic plates, while being compared to new measurements on a lab scale system. Initially, an infiltration model was developed using a k-w SST turbulence model to predict the thermoaerolic behavior of air during door-opening periods. Two fan modes and different configurations of eutectic plates were analyzed. Without any cargo, plates placed in series along the truck trailer's roof had a higher renewal time than those placed in parallel at the rear due to recirculation zones created by the pre-existing flow. However, as cargo is introduced into the system, both configurations behaved similarly as recirculation zones couldn't form. Furthermore, a granular multiphase Eulerian-Eulerian model was developed to predict frost formation on top of a cold plate. The k-w SST turbulence model was incorporated into the frost model to extend its applicability to a wider range of inlet velocities. Finally, the solidification and melting models were consolidated into the model as a user-defined function (UDF). With the consolidated model, the performance of a eutectic system was studied for typical summer conditions in Montreal, Canada. The analysis showed that approximately 2.3 % of the phase change material undergoes a phase change within the first 120 seconds. Overall, the performance of the eutectic system can be considered a viable replacement for the conventional system. Moreover, the system will be greatly enhanced through infiltration prevention and frost removal mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".