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Record W2162317440 · doi:10.1139/l04-047

Parameter studies and verifications on three-dimensional finite element analysis of rigid pavements

2004· article· en· W2162317440 on OpenAlexvenueno aff
Ying-Haur Lee, Hsin-Ta Wu, Shao-Tang Yen

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
FundersNational Science Council
KeywordsFinite element methodStructural engineeringDimensionless quantityDeflection (physics)SlabEngineeringStress (linguistics)Applied mathematicsMathematicsMechanicsPhysics

Abstract

fetched live from OpenAlex

The main objective of this study was to conduct in-depth parameter studies and verifications on three-dimensional (3-D) finite element (FEM) analysis of rigid pavements. A systematic analytical approach was utilized and implemented in a Visual Basic software package to study the effects of mesh fineness and element selection. The deflection and stress convergence characteristics of various 3-D shell and solid elements were investigated. Several guidelines in mesh fineness and element selection were developed and recommended. Using the principles of dimensional analysis, an additional dimensionless variable (h/a, where h is the thickness of the slab and a is the radius of the applied load) was identified and verified to have a substantial influence on ABAQUS runs using either 3-D shell elements or 3-D solid elements. Separate 3-D FEM stress and deflection databases were developed using all dimensionless variables. An example critical stress predictive model was developed. Together with the existing two-dimensional FEM research findings, a tentative stress prediction equation was proposed to illustrate its possible applications.Key words: rigid pavement, finite element model, stress, deflection, design, evaluation.

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 score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.025
GPT teacher head0.245
Teacher spread0.220 · 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

Citations6
Published2004
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207