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Record W3123309701 · doi:10.1139/cgj-2020-0476

Protecting surface and buried structures from tunnelling using pile walls: a prediction model

2021· article· en· W3123309701 on OpenAlexvenueno aff
Andrea Franza, Nunzio Losacco, Alberto Ledesma, Giulia Viggiani, Rafael Jiménez

Bibliographic record

VenueCanadian Geotechnical Journal · 2021
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsnot available
FundersEuropean Commission
KeywordsPileGeotechnical engineeringQuantum tunnellingGround movementShieldStructural engineeringGeologyEngineeringMaterials science

Abstract

fetched live from OpenAlex

When tunnelling poses excessive risks for buildings and buried foundations, a pile row barrier may shield the existing structure from ground movements. This paper presents a three-dimensional linear elastic prediction method to evaluate the protective action of pile walls against surface and subsurface ground movements due to new tunnels, both directly behind the wall as well as within the entire ground. Analyses are carried out to evaluate the vertical and horizontal movements of the ground and the pile wall as the result of soil–pile row interaction. New factors that quantify the wall efficiency in reducing settlements and deflections behind the wall are proposed; the results indicate that the effectiveness of the pile wall at reducing horizontal displacements is limited. Subsequently, predictions are compared against field and numerical data to demonstrate that the elastic solution is applicable, particularly for small ground losses. Finally, the barrier efficiency in reducing settlements is discussed comparing pile walls and diaphragm walls.

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: none
Teacher disagreement score0.541
Threshold uncertainty score0.887

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 integrity0.0000.001
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 head0.014
GPT teacher head0.199
Teacher spread0.185 · 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

Citations16
Published2021
Admission routes1
Has abstractyes

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