Heat Enhancement of Ethylene Glycol/Water Mixture in the Presence of Gyroid TPMS Structure: Experimental and Numerical Comparison
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Bibliographic record
Abstract
Cooling small components is becoming an attractive topic for researchers. In this paper, an attempt is made to use an ethylene glycol/water mixture as a cooling liquid. This liquid is a helpful application for when the fluid is in a harsh environment and should not freeze. The experiment uses an ethylene glycol/water mixture circulating through a triply periodic minimal surface structure (TPMS) made of aluminum and silver. A constant heat flux equal to 38,000 W/m2 is applied, and three different flow rates, 11.8 cm3/s, 15.5 cm3/s, and 19.6 cm3/s, are studied. The experimental setup is complemented with numerical modelling by solving the Navier–Stokes equation and the energy equation using the finite element technique. The flow is Newtonian, and a laminar regime is implemented. Results reveal that the performance of the ethylene glycol/water mixture did not enhance heat removal when compared to water. The average Nusselt number is similar regardless of the concentration of ethylene glycol in the mixture. This average Nusselt number, Nuaverage, in the presence of aluminum TPMS ranges between 60 and 80 (60 < Nuaverage < 80) and between 65 and 85 (65 < Nuaverage < 85) using silver TPMS. The increase in the mixture’s viscosity due to ethylene glycol increased the pressure drop. The performance evaluation criteria reach the maximum value of 90 when the mixture is composed of 5%vol ethylene glycol in water with aluminum TPMS. In the presence of silver TPMS, the maximum performance evaluation criterion is around 95 with a 5% ethylene glycol/water mixture. Finally, it is proven experimentally and confirmed numerically that the TPMS structure secures uniform heat extraction from the hot surface.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it