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Record W2069921416 · doi:10.1139/l08-118

Dynamic simulation of falling weight deflectometer tests on flexible pavements using the spectral element method: forward calculations

2009· article· en· W2069921416 on OpenAlexafffundvenueabout
Simon Grenier, Jean‐Marie Konrad, Denis LeBœuf

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFalling weight deflectometerDeflection (physics)Structural engineeringParametric statisticsDynamic loadingGeotechnical engineeringEngineeringFinite element methodDynamic load testingSubgradeMathematicsPhysics

Abstract

fetched live from OpenAlex

A dynamic analysis based on the spectral element method is described for the interpretation of falling weight deflectometer (FWD) tests on flexible pavements. This dynamic approach was implemented in the computer code Dynamic Analysis of Pavement - Université Laval (DYNAPAV-UL) that includes both frequency-independent hysteretic damping and frequency-dependent viscous damping material models. A parametric study was conducted on a four-layer flexible pavement to evaluate the influence of different layer moduli on deflection basins and deflection histories. The viscous behaviour of the asphalt concrete layer was also investigated. While the deflection basin currently used in static methods gives some details of the pavement response under transient loading, the simulations of FWD tests using the dynamic model suggest that the time histories should be included as well for the interpretation of FWD deflection measurements. In fact, important dynamic phenomena due to inertial effects and viscous effects are only revealed by deflection histories.

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)0.001
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 score0.630
Threshold uncertainty score0.630

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.024
GPT teacher head0.296
Teacher spread0.273 · 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

Citations27
Published2009
Admission routes4
Has abstractyes

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