Impact of Idling on Engine Temperatures in Winter Conditions
Bibliographic record
Abstract
This study aimed to evaluate the impact of the duration of idling on engine warm-up and engine cool-down, and to assess the effectiveness of an energy recovery system. The results confirmed that there is no need to idle an engine for extended periods after a cold start to warm it up. It is more efficient to idle the engine for a short period, and then drive the vehicle or operate the machinery at moderate loads until the engine warms up to normal operating temperatures. The tests also confirmed that the engine retains enough heat for easy starting even after being shut down for a few hours and there is no need to idle an engine for fear of having cold start problems. The tests with an energy recovery system, which circulates engine coolant to the heater after the engine is shut down, showed that the system can maintain cab temperatures at comfortable levels even after the engine has been shut down for a few hours. This product would be ideal for day cab applications where idle periods rarely exceed one or two hours, or on heavy equipment that currently do not employ anti-idle technologies. The series of tests were performed were on a truck engine, yet the results can be applied to most diesel engines in trucks and heavy machinery.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".