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Record W2906933029 · doi:10.1109/access.2018.2889991

Passive Earth Pressures on Retaining Walls for Pit-in-Pit Excavations

2018· article· en· W2906933029 on OpenAlexaff
Hu Hui, Mengqi Yang, Peiyuan Lin, Xingli Lin

Bibliographic record

VenueIEEE Access · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsToronto Metropolitan University
FundersNational Natural Science Foundation of China
KeywordsLateral earth pressureDegree RankineArchExcavationGeotechnical engineeringRetaining wallWedge (geometry)Soil waterGeologyParametric statisticsStructural engineeringEngineeringGeometryMathematics

Abstract

fetched live from OpenAlex

The technique of pit-in-pit excavations is increasingly used in China to provide an efficient solution of maximizing the utilization of underground space while minimizing the amount of solid waste due to excavations. One of the critical steps toward the successful implementation of the pit-in-pit excavation technique is to rationally estimate the passive earth pressure, which is typically done using approaches such as numerical modeling, field monitoring, or traditional Coulomb or Rankine earth pressure theories. This paper presents a simplified approach for computing passive earth pressures for pit-in-pit excavations. A trapezoidal-shaped failure wedge is formed between two levels of retaining walls. A complete symmetric soil arch is used to describe the stress field of soils in the rectangular zone, whereas a half arch with one base acting on the wall and another base acting on the inclined shear surface is proposed for soils in the triangular zone. The soil arching effect is explicitly considered to derive the earth pressure for both cohesionless and cohesive soils at any intermediate passive state. A parametric study is conducted to demonstrate that the mobilized passive earth pressure increases nonlinearly with the magnitude of wall movement and soil shear strength parameters. The allowable spacing between two walls is also defined to produce a design chart. In the end, the proposed model is assessed against experimental measurements from model-scale tests.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score0.452

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)0.0000.000

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 head0.026
GPT teacher head0.281
Teacher spread0.255 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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