Experimental investigation and performance evaluation of thermal energy management arrangements for robots
Bibliographic record
Abstract
Abstract In this study, thermal energy management systems with the choices of three different thermal insulating materials are experimentally investigated for robotic applications. These insulating materials are stone wool, fiberglass and extruded polyurethane with air cooling and heating system which are evaluated in the low and high temperature environments to really assess the thermal behavior and performance in such extreme ambient conditions. In this regard, thermodynamic and heat transfer modeling studies are undertaken to investigate various performance parameters, including energy and exergy efficiencies. The experimental results showed that energy efficiencies of the thermal management methods are obtained 46.34% for stone wool, 31.15% for fiberglass, and 44.3% for air cooling system at 40°C. Moreover, the exergy efficiencies are 12.6% for stone wool, 15.08% for fiberglass, 18.91% for extruded polyurethane, and 3.86% for air cooling system.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".