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Record W7015659819

Temperature induced stresses on modified bituminous low-slope roofing systems

2011· article· en· W7015659819 on OpenAlexvenueaboutno aff

Bibliographic record

VenueNPARC · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltRoofFailure mode and effects analysisScale (ratio)ThermalMembraneResearch council
DOInot available

Abstract

fetched live from OpenAlex

In Canada, where the design temperatures are above freezing, the SBS modified bitumen roofing membrane are the most commonly used and are in practice since 1950?s. The modified bituminous roof membrane system is a two-ply system comprising of a base sheet and a cap sheet. Existing literatures on the thermal stresses induced in the modified bitumen systems indicate that these systems have a history of problems such as blistering, rupturing, splitting and slippage, however, with the improvement in the manufacturing process and better system designs, these issues subsided with time. In the recent past, the issue of membrane ridging on low sloped modified bitumen systems was brought to the attention of National Research Council of Canada. Membrane ridging sometimes referred to wrinkling was a common failure mode observed on BUR systems over the past decade, however this seems to be emerging on the two-ply mod-bit systems. However, the question is whether the ridging is the effect of any material or whole system performance. The present paper presents two case studies showing the membrane ridging on two roofs and also discusses a small scale experimental study that was conducted at the National research Council of Canada to understand the thermal induced stresses in modified bituminous roofing systems.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.205
Teacher spread0.182 · 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 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

Citations0
Published2011
Admission routes2
Has abstractyes

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