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Nonlinear Time-Dependent Mechanical Behavior of Medium-Density Polyethylene Pipe Material

2021· article· en· W3133418414 on OpenAlexaffabout
Suprio Das, Ashutosh Sutra Dhar

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMaterials scienceCreepUltimate tensile strengthStress relaxationStrain rateComposite materialPolyethyleneStress (linguistics)Stress–strain curveDeformation (meteorology)Tensile testingNonlinear systemMaterial propertiesFinite element methodStructural engineeringEngineering

Abstract

fetched live from OpenAlex

Medium-density polyethylene (MDPE) pipes are extensively used for gas distribution systems in Canada and worldwide. MDPE pipe material possesses time-dependent mechanical properties that govern the performance of the pipes in service. In this research, an extensive laboratory investigation is carried out to investigate the time-dependent behavior of MDPE pipe material. Uniaxial tensile tests are conducted with samples (coupons) cut from the wall of a 60-mm diameter MDPE pipe. A tensile test with a sample of the full cross section of the pipe is also conducted to investigate the influence of sample type on the test results. The test program includes uniaxial testing at various strain rates ranging from 10−6/s to 10−2/s to capture the effects of loading rates, creep testing, and relaxation testing. The program revealed that the stress-strain responses of MDPE pipe material are highly nonlinear and strain rate-dependent. However, the strain rate effect is negligible below 10−6/s, which is termed herein as the “reference strain rate.” A numerical technique for modeling time-dependent behavior is proposed using the features available in a commercially available finite element software, Abaqus. In this technique, strain rate-dependent stress-strain models are used to simulate loading and unloading responses, and a power-law type creep-law model is used to simulate the creep/relaxation behavior. The proposed modeling approach successfully simulated the test results.

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)0.001
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 score0.111
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.202
Teacher spread0.196 · 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

Citations11
Published2021
Admission routes2
Has abstractyes

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