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Record W2037827961 · doi:10.1139/t00-007

Shakedown analysis of anisotropic asphalt concrete pavements with clay subgrade

2000· article· en· W2037827961 on OpenAlexvenueno aff
M. Boulbibane, I.F. Collins, Dieter Weichert, Lutfi Raad

Bibliographic record

VenueCanadian Geotechnical Journal · 2000
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsShakedownSubgradeGeotechnical engineeringStiffnessAnisotropyAsphaltStructural engineeringGeologyEngineeringMaterials scienceFinite element methodComposite material

Abstract

fetched live from OpenAlex

The essence of a shakedown analysis is to determine the critical shakedown load for a given pavement. Pavements operating above this load are predicted to exhibit increased accumulation of plastic strains under long-term repeated loading conditions that eventually lead to incremental collapse (e.g., deep ruts). Those pavements operating at loads below this critical level may exhibit some initial distress, but will eventually settle down to a steady state in which no further mechanical deterioration occurs. Conventional pavement design procedures assume that the pavement deteriorates indefinitely. However, there is now ample field evidence that this is not always true and that steady-state conditions are frequently achieved. The materials in the various layers of the pavement are modeled as elastic-plastic Mohr-Coulomb materials. Anisotropic strength effects are studied as well as the influences of variable temperature, stiffness, strength, and thickness of the asphalt concrete layer. A lower bound approach is used to provide safe estimates of the critical shakedown load.Key words: shakedown theory, multilayered pavements, anisotropy.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0180.000

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 head0.011
GPT teacher head0.221
Teacher spread0.211 · 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
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

Citations18
Published2000
Admission routes1
Has abstractyes

Explore more

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