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Record W1982676505 · doi:10.1061/40889(201)96

A Worldwide Survey of Environmental Reduction Factors for Fiber Reinforced Polymers (FRP)

2006· article· en· W1982676505 on OpenAlexaboutno aff
John J. Myers, Thara Viswanath

Bibliographic record

VenueStructures Congress 2006 · 2006
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsnot available
FundersUniversity of MissouriNational Science Foundation
KeywordsFibre-reinforced plasticAramidDurabilityReduction (mathematics)Materials scienceForensic engineeringEnvironmental scienceComposite materialFiberEngineeringMathematics

Abstract

fetched live from OpenAlex

In this study, the reduction factors for FRP (Fiber Reinforced Polymers) proposed by various guidelines from countries including the USA, Japan, Canada, Great Britain, Norway and Europe were obtained to assemble a database of current environmental reduction factors and review their appropriateness. A literature review was also conducted that summarizes recent durability investigations conducted worldwide on various FRP materials under different exposure conditions. These FRP materials include carbon, aramid, glass, and hybrid FRP's. The reduction factors obtained from the results of the recent laboratory studies are compared with those provided by various codes on FRPs around the world. Some of the values obtained from reported experimental work were similar to the values proposed by various guidelines; however, none of the experimental results obtained provided the strength degradation due to the synergistic effect for the different exposures presented.

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)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.006
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.221
Teacher spread0.211 · 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 designObservational
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

Citations6
Published2006
Admission routes1
Has abstractyes

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Same venueStructures Congress 2006Same topicMechanical Behavior of CompositesFrench-language works237,207