MétaCan
Menu
Back to cohort
Record W2167210879 · doi:10.1139/t2012-028

Intermittent freezing mode to reduce frost heave in freezing soils — experiments and mechanism analysis

2012· article· en· W2167210879 on OpenAlexvenueno aff
Yang Zhou, Guoqing Zhou

Bibliographic record

VenueCanadian Geotechnical Journal · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsnot available
FundersState Key Laboratory of Frozen Soil EngineeringChina University of Mining and TechnologyNational Natural Science Foundation of ChinaNational Science Foundation
KeywordsFrost heavingGeotechnical engineeringCongelationFrost (temperature)Frost weatheringGeologySoil waterMechanicsSoil scienceThermodynamicsGeomorphology

Abstract

fetched live from OpenAlex

Two types of freezing tests have been conducted on Xuzhou silty clay. The intermittent freezing test results show that the frost heave increases step by step after the initial freezing stage, and its total amount is only 48.8% that resulting from the continuous freezing test. A model describing the growth process of the active ice lens in saturated, rigid soils has been established, and the importance of the frozen fringe is investigated in the model. The growth processes of the final ice lenses in the two freezing tests have been used for laboratory validation of the model, and the calculated results are in general agreement with the experimental data. The mechanism of using an intermittent freezing mode to reduce frost heave has been revealed by analyzing the growth process of the final ice lens. We indicate that, during the noncooling stage, the backward movement of the freezing front, which causes the disappearance of the frozen fringe, stops the growth of the final ice lens. This effect results in a step-type frost heave curve in the intermittent freezing test and reduces the heave amount effectively. Finally, problems concerning the practical application of the intermittent freezing mode are discussed in a preliminary manner.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.278
Teacher spread0.233 · 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 designObservational
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

Citations68
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicClimate change and permafrostFrench-language works237,207