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Record W2794038000 · doi:10.4271/2024-01-3635

Simple Terramechanics Models and their Demonstration in the Next Generation NATO Reference Mobility Model

2017· article· en· W2794038000 on OpenAlexaff
Michael McCullough, J. Preston–Thomas, Sally Shoop, Paramsothy Jayakumar, Henry Hodges

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2017
Typearticle
Languageen
FieldEngineering
TopicTransportation Safety and Impact Analysis
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsSimple (philosophy)Computer scienceMobility modelDistributed computing

Abstract

fetched live from OpenAlex

<title>ABSTRACT</title> <p>In 2014, a NATO Applied Vehicle Technology (AVT) Exploratory Team 148 (ET-148) was formed to explore the development of an improved Next-Generation NATO Reference Mobility Model (NG-NRMM)[<xref rid="R1" ref-type="bibr">1</xref>]. A development path forward was identified and initiated in a subsequent NATO research task group (AVT-248) to implement ET-148 recommendations. One key area for improvement was the vehicle-terrain interaction (Terramechanics) models defining important performance metrics for off-road performance in differing soils, and environmental conditions. The near term implementation focuses on existing “Simple” Terramechanics models as a practical improvement to the incumbent NRMM Cone Index (CI) empirically based method, without requiring the computational power of the large scale complex discrete element model (DEM) methods that are the targeted long term solution. Practical approaches and limitations to the implementation of these existing Simple Terramechanics models in 3D vehicle models are described along with parameter identification approaches and their limitations.</p>

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.060
GPT teacher head0.273
Teacher spread0.213 · 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 designObservational
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

Citations4
Published2017
Admission routes1
Has abstractyes

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