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Record W4400330789 · doi:10.1051/e3sconf/202454502005

Comparative Analysis of Thermal Performance of Painted, Finned, and Plain Roofs in Arid and Temperate Climates: Insights from Kuwait City and Vancouver

2024· article· en· W4400330789 on OpenAlexaboutno aff
Hayder Salem, Ahmad Sedaghat

Bibliographic record

VenueE3S Web of Conferences · 2024
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
FundersKuwait Foundation for the Advancement of SciencesCentral Queensland University
KeywordsASHRAE 90.1RoofTemperate climateEnvironmental scienceThermal comfortAridEnergy performanceReflective surfacesAtticArchitectural engineeringCivil engineeringEfficient energy useMeteorologyGeographyEngineeringEcology

Abstract

fetched live from OpenAlex

This paper presents a comparative analysis of the thermal performance of three common roofing types - painted, finned, and plain for buildings with customary materials without insulationin- two contrasting climatic contexts: Kuwait City and Vancouver. Experimental data were collected on hourly basis for the surface temperatures for 4 months in winter of Kuwait. Utilizing ASHRAE methods, we simulated the dynamic thermal behaviour of these roofing materials to assess their suitability for mitigating energy demands and enhancing indoor thermal comfort of a building with 127 m 2 rooftop surface area. Our findings reveal distinct thermal characteristics associated with each roofing type in the respective climates. In Kuwait City’s arid environment, the painted roof emerges as the optimal choice, demonstrating superior performance in reducing thermal loads during hot months while posing challenges related to increased heating demand in cooler seasons with 4.5°C reduction by painted roof. Conversely, in Vancouver’s temperate climate, the painted roof exhibits continuous outward conduction of heat, contributing to elevated heating demands throughout the year despite its effectiveness in maintaining lower temperatures compared to the indoor environment. This study highlights the importance of considering climatic factors and seasonal variations in selecting roofing materials to achieve optimal energy efficiency and indoor comfort. These findings can assist decision-making processes for architects, engineers, and policymakers aiming to enhance building performance and sustainability across diverse climatic regions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.277

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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 designSimulation or modeling
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

Citations0
Published2024
Admission routes1
Has abstractyes

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