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Comparing Short-Term Performance of Corrugated HDPE Pipe Made with or without Recycled Resins for Transportation Infrastructure Applications

2021· article· en· W3214849714 on OpenAlexaff
Khanh Q. Nguyen, Patrice Cousin, Khaled A. Mohamed, Mathieu Robert, Brahim Benmokrane

Bibliographic record

VenueJournal of Materials in Civil Engineering · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsHigh-density polyethyleneDurabilityPolyethyleneEnvironmental scienceMaterials scienceWaste managementComposite materialEngineering

Abstract

fetched live from OpenAlex

In recent years, corrugated high-density polyethylene (HDPE) pipes manufactured from recycled resins have been on the rise for infrastructure sectors as a result of their numerous advantages. Compared to HDPE pipes made with virgin resins, these recycled pipes help solve the problem of plastic-waste management and the environmental impacts of waste. In addition, using recycled materials makes HDPE pipe more sustainable and cost effective. One question stands out: Will HDPE pipes made with recycled resins have the same performance and durability as virgin pipes under the impact of thermal stress during the burial process, environmental variations, and traffic load? This issue needs to be clarified because the demand for recycled pipes is increasing. The aim of this paper is to improve the knowledge to compare the short-term performance of these two types of pipes. The specimens came from four different North American manufacturers with their own production processes. This study provides more detailed data on physicochemical, mechanical, and thermal properties of HDPE pipes. These properties were tested on laboratory equipment according to ASTM standards. The test results can be used to estimate some aspects of the long-term characteristics of HDPE pipes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.525
Threshold uncertainty score0.718

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 communication0.0000.000
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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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.

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

Citations4
Published2021
Admission routes1
Has abstractyes

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