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Record W4396883650 · doi:10.1139/cgj-2023-0620

Experimental comparison of foam flow and gas flow in municipal solid waste

2024· article· en· W4396883650 on OpenAlexvenueno aff
Jie Hu, Xiaobing Xu, Meng Meng, Wenjie Xu

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldMaterials Science
TopicPickering emulsions and particle stabilization
Canadian institutionsnot available
FundersKey Research and Development Program of Zhejiang ProvinceNational Natural Science Foundation of China
KeywordsFlow (mathematics)Municipal solid wasteWaste managementPetroleum engineeringGeotechnical engineeringEnvironmental scienceFlow propertiesMaterials scienceGeologyEngineeringMechanics

Abstract

fetched live from OpenAlex

Foam is found to be a special fluid (i.e., gas divided by liquid film) that exists in municipal solid waste (MSW) landfills. As a disconnected phase, the unsaturated flow behavior of foam is significantly different from that of gas in connected phase. In this study, the difference between foam flow and gas flow was characterized through displacement tests in the MSW columns. Resistance factor, which is defined as the ratio of steady pressure drop between foam displacement and gas displacement, is employed to characterize this difference. The effects of foam quality, void ratio, and particle size on resistance factor were studied. The unsaturated permeability curves of foams generated by leachate samples at different depths were measured. The leachate at the middle layer has low surface tension to produce strong foam, while the leachate at the top and bottom layers has high surface tension to produce weak foam. The unsaturated permeabilities of weak foam and strong foam were about 1 and 2 orders of magnitude smaller than that of gas, respectively. The reduction in waste void ratio decreased the resistance factor as the excessive shearing effect in small pores would cause the foam to collapse.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.027
GPT teacher head0.307
Teacher spread0.280 · 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
Published2024
Admission routes1
Has abstractyes

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