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Record W4415692625 · doi:10.1061/9780784486504.004

Influence of Microplastic Contamination on Sand Liquefaction Initiation and Post-Liquefaction Behavior

2025· article· W4415692625 on OpenAlexaboutno aff
César Leal, L. A. Salgado, Wing Shun Kwan

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicGeotechnical Engineering and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsContaminationLiquefactionSoil waterMicroplasticsPolyethylene terephthalatePore water pressureSoil testShear (geology)

Abstract

fetched live from OpenAlex

Plastics have become an essential part of human life; however, the increased dependence on single-use disposable plastic items has led to the ubiquity of microplastics (MPs) in our environment. As plastics in the environment degrade into MPs, they can spread through various means, entering the ground and causing implications for the health and well-being of the surrounding environment as well as for the properties of the soil in which the contaminants can reside. A current gap exists in the geotechnical engineering community’s understanding of the effects of MPs on the dynamic properties of soils. The influence of MPs on soil behavior under dynamic loading is assessed through a series of constant volume strain-controlled cyclic simple shear tests in conjunction with bender elements (BE). This study examines the behavior of medium-dense specimens of clean Ottawa sand and Ottawa sand mixed with 10% MPs by dry mass. The MPs utilized in this investigation are composed of polyethylene terephthalate (PET) with a particle diameter range of 50 to 100 microns. Equivalent pore pressure ratio curves vs. increasing cyclic strain percentages were developed for both clean Ottawa sand and contaminated Ottawa sand. Monotonic simple shear tests are performed on the liquefied specimens following cyclic testing. The post-liquefaction stress-strain curves of clean and contaminated sand are also developed and compared. The results determined from this study improve the assessment of the liquefaction potential of highly contaminated soils in seismic-prone areas such as dense urban communities, which can reduce the potential loss of lives and resources.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.031

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 head0.005
GPT teacher head0.219
Teacher spread0.214 · 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 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

Citations1
Published2025
Admission routes1
Has abstractyes

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