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Model Tests on Additional Stress Transmission between Different Granular Materials in Foundation Soils

2014· article· en· W2043867989 on OpenAlexaff
Chang Dan Wang, Shunhua Zhou, Hui Su

Bibliographic record

VenueAdvanced materials research · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGeotechnical engineeringStress (linguistics)Soil waterAttenuationOverburden pressureGranular materialFoundation (evidence)Materials scienceModulusCompression (physics)GeologySoil scienceComposite materialOptics

Abstract

fetched live from OpenAlex

To research and analyze the additional stress distribution and change of granular materials, the model tests are used to observe vertical additional stress in different position and depth in different foundations. And the comparison between observed values both in different soils and single soils is conducted to analyze the transmission and attenuation of additional stress in granular materials. The research results show that the existing of boundary surface can lead to different vertical additional stress transmit obviously. And with the increasing of loading, the vertical additional stress differences between that of different soils get larger, meanwhile, the ratio of stress differences to smaller additional stress increases slightly. With the increasing of depth, the attenuation rate of vertical additional stress of silty soil changes much fast than that of fine sand. Wherever in horizontal direction or vertical direction, the vertical additional stress of fine sand which has higher compression modulus in different soils is slightly larger than that in single soil and transfers additional stress (loading) more under the same loading. To granular materials, inner friction structure effect is evident influence to additional stress transfer.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.324
Threshold uncertainty score0.812

Codex and Gemma teacher scores by category

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 head0.031
GPT teacher head0.304
Teacher spread0.273 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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