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Record W3153479252

Methods for evaluating long-term changes in thermal resistance of vacuum insulation panels

2005· article· en· W3153479252 on OpenAlexvenueaboutno aff
Phalguni Mukhopadhyaya, K. Kumaran, John Lackey, Nicole Normandin, David van Reenen

Bibliographic record

VenueNPARC · 2005
Typearticle
Languageen
FieldChemistry
TopicAerogels and thermal insulation
Canadian institutionsnot available
Fundersnot available
KeywordsRelative humidityBuilding envelopeHumidityVacuum insulated panelThermal insulationMaterials scienceThermal resistanceDynamic insulationComposite materialWater vaporEnvironmental scienceThermal bridgeThermal comfortThermal massFOIL methodApparent temperaturePermeanceThermalForensic engineeringLayer (electronics)PermeationEngineeringMeteorology
DOInot available

Abstract

fetched live from OpenAlex

Efficient insulating systems are the key to the energy efficiency of a building envelope. Vacuum Insulation Panels (VIPs) offer excellent thermal resistance properties that can enhance the energy efficiency of insulating systems, use less space, and provide savings in energy consumption. However, from a Canadian perspective, VIP systems are little known and indeed unused in the building industry. There is a need to investigate the prospect of using VIPs in various components of building envelope. The long-term thermal insulating efficiency of the VIPs depends on its ability to maintain an adequate level of vacuum inside the panel. For design purpose the long-term thermal insulating characteristics of the VIPs needs to be understood and defined. This paper addresses some of the test methods that could accelerate the long term changes in thermal resistance and presents selected results from tests using elevated pressure, relative humidity and temperature on three types of VIPs.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.134
Threshold uncertainty score0.587

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.076
GPT teacher head0.392
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2005
Admission routes2
Has abstractyes

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