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Record W6910468294 · doi:10.4224/17210698

Thermal protection measurement of immersion suit comparison of two manikins with humans pilot study report

2010· report· en· W6910468294 on OpenAlexfundvenueno aff

Bibliographic record

VenueNPARC · 2010
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
FundersTransport Canada
KeywordsImmersion (mathematics)Thermal manikinHeat flowThermal insulationCore temperatureHeat transferTemperature measurement

Abstract

fetched live from OpenAlex

The use of manikins to evaluate the thermal protection characteristics of cold water protective suits such as marine abandonment or helicopter passenger suits is not widely accepted in international standards. A full demonstration of the validity of such use requires that two questions be answered. 1. Is the heat loss from a manikin representative of the heat loss from a human under identical conditions? 2. Can the measured heat loss be related to the fall in core temperature of a human subject by appropriate models or correlations? As part of a study of the first question, the heat losses, expressed as local heat transfer coefficients or local insulation values, were compared for two thermal submersible manikins and two human subjects wearing immersion suits with three different levels of closed cell foam insulation in two floatation positions in stirred water. Both the manikins and the human subjects were instrumented with heat flow sensors, skin temperature sensors, and outer suit surface temperature sensors at 13 sites over the body. Measurements were taken over the last 30 minutes of a 60 minute exposure in a water temperature of about 12 °C and an air temperature which was in the range 15 to 19 °C. In addition to the heat flow sensor readings, the heat loss from the manikins was determined by their sectional power consumption with their skin temperatures set to a uniform 30 °C. Floatation positions were vertical with immersion to the neck, and a natural position determined by the buoyancy characteristics of the suits. This latter position was determined by measuring the height of several body points relative to the water surface on the human subjects and then arranging the manikins to the same position. The human subjects were selected to have a similar fit with the suits as the manikins. The local heat transfer coefficients showed some scatter, but no systematic variation from manikin to human or from heat flow sensor to manikin power measurement could be discerned. When the local values were used to calculate an overall resistance by the parallel method, the scatter was greatly reduced, and again no systematic variations could be discerned. The final spread in the values of overall resistance was about +/- 18%. The differences between manikin and human (+/- 12%), between humans (+/- 13%), and between manikins (+/- 6%), were all of comparable magnitude. The trend of resistance as a function of suit thickness was similar to that shown by measurements of the insulation of the suit materials on a hot plate. It is likely that the variation in local heat transfer coefficients was due to the effects of differences in fit, folds or wrinkles in the suit materials, and was essentially random. These random differences then tended to average out in the calculation of the overall resistance. It is concluded that within the scatter due to fit, folds and wrinkles, the heat loss from the manikins was a good representation of the heat loss from humans for the vertical and natural floating positions in water for suits insulated with closed cell foam.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.161
GPT teacher head0.354
Teacher spread0.193 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2010
Admission routes2
Has abstractyes

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