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Record W3007732396 · doi:10.1520/stp162120190024

Energy Resistance of Commercial Roofs

2020· book-chapter· en· W3007732396 on OpenAlexaffabout
Sudhakar Molleti, Bas A. Baskaran

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsResistance (ecology)Architectural engineeringEnergy (signal processing)EngineeringPhysicsEcologyBiology

Abstract

fetched live from OpenAlex

A consortium study, Energy Resistance of Commercial Roofs, was developed by the National Research Council Canada (NRC) with support from roofing contractor associations, roofing and accessories manufacturers, insulation manufacturers, and roofing consultants to develop scientifically supported performance data on energy resistance of roofing systems that are constructed according to field practices. This study has two major tasks. This paper presents and discusses the results from Task 1, in which 36 roofing assemblies representing seven climatic zones in North America were designed and tested to evaluate their effective thermal resistance and to validate their performance relative to the code requirements. The test matrix comprised mechanically attached roofing system, partially adhered roofing system, and adhesive applied roofing system designed with three different insulation types—polyisocyanurate, expanded polystyrene, and stone wool. The test protocol involved measurement of the thermal resistance of the insulation component and effective thermal resistance of the roofing assemblies at four different mean temperatures representing a very cold climate to solar-heated climatic conditions. All the testing was conducted at NRC's Dynamic Roofing Facility–Energy. The experimental research highlighted two influencing parameters that are currently not considered in the energy design of the roof. One is the temperature dependency performance of insulation and its impact on the effective R-value, and the second is the thermal bridging of fasteners. The measured data showed a decreasing trend of the effective R-value with increasing fastener density. The combined effect of insulation performance and thermal bridging lowered the effective R-value of some of the tested assemblies by 2% to 20% below the target design values. The current design practice needs to acknowledge the thermal bridging effects of fasteners and plates and accommodate them appropriately at the design stage of the roofs. Excluding this could lead to repercussions on the overall energy performance of the roof.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.010
GPT teacher head0.167
Teacher spread0.158 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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
Published2020
Admission routes2
Has abstractyes

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