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Record W2883708288 · doi:10.5185/amp.2017/027

Creep and thermal ratcheting characterization of polytetrafluoroethylene-based gasket materials

2018· article· en· W2883708288 on OpenAlexaff
Rahul Palaniappan Kanthabhabha Jeya, Abdel‐Hakim Bouzid

Bibliographic record

VenueAdvanced Materials Proceedings · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsGasketPolytetrafluoroethyleneCreepMaterials scienceComposite materialTemperature cyclingThermal expansionStress (linguistics)ThermalCompressive strengthForensic engineering

Abstract

fetched live from OpenAlex

Characterization of Teflon polymer based gaskets under expedited aging is the objective of this work. Teflon gaskets are exploited frequently as a replacement to asbestos fiber gaskets because of their excellent leak tightness and nonhazardous physical degradation properties. The research focuses profoundly on the adverse influence of temperature and thermal cycles on the creep and cumulative damage phenomenon under compressive load. Virgin and expanded PolyTetraFluoroEthylene (PTFE) are tested under 28 and 41 MPa of gasket stress at different temperatures. Intricate analysis of creep under coalesces of thermal ratcheting and principal stress is achieved through Universal Gasket Rig (UGR). The instigated cumulative damage is distinguishable into upper and lower bound temperature region indicating the escalation and decrease of thickness change during cycling which saturates after 12 thermal cycles for expanded PTFE while no saturation is reached for virgin PTFE in even after 20 thermal cycles. Percentage of thickness reduction at different applied stress is nearly the same for virgin PTFE whereas expanded PTFE shows largest reduction under lower stress. Compressive creep bespeaks the impact of temperature and load, thereby dictating the magnitude of ratcheting damage and contrariwise. Finally, the creep and thermal ratcheting has a proliferating effect on value of the coefficient of thermal expansion for all chosen gaskets. Copyright © 2017 VBRI Press.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.007
GPT teacher head0.228
Teacher spread0.221 · 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 teacher head, not a consensus.

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

Citations5
Published2018
Admission routes1
Has abstractyes

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