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Record W2289412816 · doi:10.1680/jgrma.15.00027

Serviceability of foam core structural panels based on bond strength

2015· article· en· W2289412816 on OpenAlexaff
Farhoud Delijani, Kris J. Dick

Bibliographic record

VenueGreen Materials · 2015
Typearticle
Languageen
FieldEngineering
TopicStructural Analysis of Composite Materials
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsOriented strand boardServiceability (structure)Materials scienceComposite materialPolyurethaneDurabilitySandwich-structured compositeBond strengthStructural engineeringService lifeEngineeringCore (optical fiber)Adhesive

Abstract

fetched live from OpenAlex

Oriented strand board (OSB) face sheets adhered to polyurethane (PUR) foam have been used to make structural insulated panels (SIPs) for energy-efficient buildings for many years. One challenge for more widespread use is lack of a clear indication of service life and durability. Many regulatory agencies do not allow the use of SIPs without dimensional lumber framing, asserting OSB is typically not a principal structural member and citing a concern for service life. This paper presents the results of research focused on the evaluation of bond strength between the OSB skins and the PUR foam core as one measure of service life and fabrication quality. A total of 120 pull-off tests were conducted on panels subjected to various environments. A total of 120 tests were conducted on new to highly weathered, aged panels. Only 2·5% of these tests displayed partial debonding between the OSB and foam. Of the remaining specimens, 77·5% exhibited shear failure within the foam, indicating acceptable bond strength. The remaining 20% failed within the OSB skin. This paper discusses the findings and potential implications for service life of OSB skins and PUR foam core.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.243
Teacher spread0.214 · 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

Citations1
Published2015
Admission routes1
Has abstractyes

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