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Record W4246840005 · doi:10.11159/icesdp17.109

Simulation Analysis of Thermal Insulation Performance of PCM for Mitigating Urban Heat Island Effect

2017· article· en· W4246840005 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the World Congress on Civil, Structural, and Environmental Engineering · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEnergy and Environmental Systems
Canadian institutionsnot available
Fundersnot available
KeywordsUrban heat islandThermal analysisThermalEnvironmental scienceThermal insulationMaterials scienceMeteorologyComposite materialPhysics

Abstract

fetched live from OpenAlex

This study aimed to analyze the Thermal Insulation Performance of the PCM Cool Roof System, which is being developed for mitigating the Urban Heat Island Effect. We compared the performance of general insulation material versus that of PCM, both applied on a standard roof model. General insulation material contained 50mm Expanded Poly Styrene, 135mm Expanded Poly Styrene, and 135mm cellulose. We found that PCM had less cooling energy consumption compared to general insulation, whereas general insulation had less heating energy consumption. The annual total energy consumption was found to be lower when using PCM. Therefore, we conclude that the PCM Cool Roof System has insulating capacity comparable to that of general insulation. And its thermal insulation performance is similar or better compared with general insulation, although thermal conductivity of PCM in solid status is generally 0.24 W/mK which almost eight times higher than general insulation.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.356

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)0.0000.000

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 head0.006
GPT teacher head0.224
Teacher spread0.218 · 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