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Calculation of the stress-strain state of soil massifs with karst-suffusion cavities

2018· article· en· W2807838116 on OpenAlexaff
Airat Latypov, N. I. Zharkova, Armen Ter-Martirosyan

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsPolytechnique Montréal
FundersLomonosov Moscow State UniversityMinistry of Education and Science of the Russian Federation
KeywordsKarstMassifGeologyCarbonateGeotechnical engineeringCarbonate rockGeochemistryMaterials scienceMetallurgyPaleontology

Abstract

fetched live from OpenAlex

For the North-Eastern part of the Kazan the problem of karst-suffusion danger is rather actual that is associated with the presence and occurrence close to the surface of carbonate eluvium. Currently in this area of the city is an active construction of various facilities. This article is presented the results of calculation the parameters of the cavities and their spatial location on condition of that collapse of the soil massif is possible. The calculation model included the geometrical model of the engineering-geological section, supplemented by physical and mechanical properties as well as a cavity of cylindrical shape of different geometry. Earlier, the authors have completed and published studies to determine the critical diameter and critical depth of a cavity having the form of a simple cylinder. In reality the cavities have a more complex geometry so in this work the modelling was aimed at finding the critical parameters for different types of karst-suffusion cavities discovered in the study area. The simulation results have allowed establishing that the danger of collapse of the soil above the cavity largely depends on its diameter and position in space. Several typical calculation cases were identified. For each case was the effect of the cavity on the redistribution of stresses in the soil massifs. It is possible to develop recommendations for the design of buildings and structures in the study area. The research results showed good agreement with the results of field studies.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.008
GPT teacher head0.181
Teacher spread0.173 · 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".

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Citations1
Published2018
Admission routes1
Has abstractyes

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