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Record W3023499682 · doi:10.1520/jte20180533

Cement-Improved Wetting Resistance of Coarse Saline Soils in Northwest China

2019· article· en· W3023499682 on OpenAlexaff
Jian Xu, Yanfeng Li, Songhe Wang, Jianwei Ren, Jiulong Ding, Qinze Wang, Cheng Dongxing, Fan Yu

Bibliographic record

VenueJournal of Testing and Evaluation · 2019
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsMcMaster University
Fundersnot available
KeywordsWettingCementCuring (chemistry)Geotechnical engineeringMaterials scienceComposite materialSaturation (graph theory)SilicateGeologyChemistryMathematics

Abstract

fetched live from OpenAlex

Abstract Wetting-induced collapse of coarse saline soil foundations is a frequently encountered problem in the inland basin of Northwest China, but this particular behavior and relevant treatment have not been given adequate attention. Specimens treated by silicate cement were used in wetting collapse testing at conventional foundation loads, with five cement contents and four curing durations considered. The results indicate that in the case of no curing, the collapsible deformation during wetting declines at higher cement contents, and a stepwise development of deformation was noticed over the wetting duration. Specimens treated by cement after curing exhibit a decrease in the compressive deformation during wetting, and part of them show volume expansion instead. The complex hydrolysis and hydration reaction of cement in the process of curing primarily accounts for this. Moreover, the collapsibility coefficient varies within a narrow range in the noncuring case, proving the limited influence of cement inclusion; however, a gentle range, from 2.0 to 4.0 %, can be found after curing, beyond which it slightly varies. An elastoplastic model was established, incorporating a variable boundary seepage equation, and was then used for modeling a field immersion test. The rationality of the model was verified by comparing the measured and simulated results, including the degree of saturation and vertical displacement. The optimal depth and width for cement treatment was discussed in view of the practical engineering.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.231

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.019
GPT teacher head0.248
Teacher spread0.229 · 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 designSimulation or modeling
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

Citations3
Published2019
Admission routes1
Has abstractyes

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