Thermal Protection and Microclimate of SOLAS Approved Lifeboats
Bibliographic record
Abstract
Lifeboats are used as an evacuation system on a wide variety of offshore structures and marine vehicles. Currently, International Maritime Organization (IMO) Lifesaving Appliances (LSA) Code does not specify thermal protection and ventilation criteria for lifeboats. A test program was conducted to assess the system thermal protection and microclimate of SOLAS approved lifeboats for the Arctic environment. Some of the research findings of the first phase experiments are reported in this paper. In conducting experiments with a 72-person SOLAS approved lifeboat, the study found that the lifeboat only had a ventilation rate of 2 litres per second with vents open only, which may not be adequate. Inadequate ventilation will result in high concentration of carbon dioxide, causing headache, dizziness, restlessness, breathing difficulty, sweating, and increased heat rate, cardiac output and blood pressure. All of these may adversely affect lifeboat occupants in performing survival tasks. Using a thermal manikin, only slight decrease in thermal resistance (less than 10%) was observed in many test cases, when active ventilation was implemented (ventilation rate of 31 and 42 litres per second) and when side hatches were opened (ventilation rate of 95 litres per second). This suggests that reasonable increase in ventilation rate may be implemented without trading off much in thermal protection. However, a more noticeable decreases in thermal resistance (15% to over 30%) were observed when clothing was wet. This suggests it is critical to stay dry. A mathematical model was also developed to assess heat and cold stress of lifeboat occupants under different environment, lifeboat, occupant and ventilation conditions.
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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 | 0.001 | 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) | 0.002 | 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".