MétaCan
Menu
Back to cohort
Record W4309040695 · doi:10.1115/1.4056260

Long-Term Performance of Semimetallic Gaskets

2022· article· en· W4309040695 on OpenAlexaff
Abdel‐Hakim Bouzid, Shubhra Kanti Das

Bibliographic record

VenueJournal of Nuclear Engineering and Radiation Science · 2022
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsÉcole de Technologie Supérieure
FundersWelding Research Council
KeywordsGasketGraphiteMaterials scienceComposite materialLeakage (economics)CreepUltimate tensile strengthForensic engineering

Abstract

fetched live from OpenAlex

Abstract Flexible graphite-based gaskets are used extensively in high-temperature applications as a replacement for asbestos-based gaskets. The effects of aging and temperature exposure on flexible graphite sheet gaskets were the subject of a previous work (Derenne et al., 1997, “Elevated Temperature Characterization of Flexible Graphite Sheet Materials for Bolted Flanged Joints,” Welding Research Council Bulletin, Issue 419, pp. 1–87.). In this paper, the effects of aging on flexible graphite under a confined-gasket configuration will be examined as they are yet unknown. This study outlines the performance evaluation of the elevated temperature behavior of flexible graphite-based gaskets under a confined configuration and long-term exposure employing a high-temperature aged leakage relaxation (HALR) fixture. This aged relaxation leakage adhesion test (ARLA)-like fixture retains the mechanical features of the aged tensile relaxation screening (ATRS)/high-temperature aged tensile relaxation (HATR) while enabling cold leakage rate and weight loss measurements. Four distinct semimetallic gaskets with different graphite-confined configurations, namely, corrugated metal, spiral wound, kammprofile, and double jacketed, were evaluated within a temperature range of 800–1200 °F (430–650 °C) for an exposure time of 2500 h. Graphite weight loss, gasket thickness change, leakage and tightness parameters, and creep and relaxation measurements were taken at regular intervals for each gasket style. To better assess the aging process, these critical mechanical and leakage properties were scrutinized; the influence of the degradation process, related mainly to graphite oxidation, was emphasized.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.194
Teacher spread0.188 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Nuclear Engineering and Radiation ScienceSame topicFatigue and fracture mechanicsFrench-language works237,207