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Record W4211005701 · doi:10.1201/9781003188339-78

On the use of Extended Finite Element Method (XFEM) for jointed rock slope problems

2021· book-chapter· en· W4211005701 on OpenAlexaff
S. Moallemi, T. W. Yee, Dongfeng Qi, Thamer Yacoub, Brent Corkum, J.H. Curran

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsRocscience (Canada)
Fundersnot available
KeywordsClassification of discontinuitiesExtended finite element methodDiscretizationFinite element methodRock mass classificationInstabilityDomain (mathematical analysis)GeologyJoint (building)Structural engineeringGeometryGeotechnical engineeringMathematicsMathematical analysisEngineeringMechanicsPhysics

Abstract

fetched live from OpenAlex

Finite element method as an advanced numerical technique has been used widely for modeling jointed rock mass, where both joint and intact rock would be modeled explicitly. One of the major challenges that is associated with this approach is conforming the mesh with the joints in complex geometries. As a solution, extended finite element method (XFEM) is introduced to trace the discontinuities implicitly where the discretization of the domain is independent of joints. In this paper, we expanded the application of XFEM in jointed rock slopes for any number of discontinuities in the domain and discussed the factors that can affect numerical instability in analysis.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.896
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.047
GPT teacher head0.235
Teacher spread0.188 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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

Citations1
Published2021
Admission routes1
Has abstractyes

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