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Record W3082259970 · doi:10.1061/9780784483176.010

Hertzian Contact Stiffness under Eisenmann Assumptions

2020· article· en· W3082259970 on OpenAlexaff
Nazmul Hasan

Bibliographic record

VenueInternational Conference on Transportation and Development 2020 · 2020
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsSNC-Lavalin (Canada)
Fundersnot available
KeywordsContact mechanicsStiffnessContact forceMechanicsDeformation (meteorology)Contact theoryBending stiffnessContact regionPhysicsClassical mechanicsMathematical analysisMathematicsStructural engineeringEngineeringMaterials scienceFinite element method

Abstract

fetched live from OpenAlex

In dynamic wheel/rail models, the Hertzian contact stiffness is an important parameter. A track structure and wheel set connected by means of a Hertzian spring is used to describe high frequency vertical vibrations. Unfortunately the Hertzian contact stiffness has been a subject of some dispute by various authors and the suggested values of Hertzian contact stiffness by different authors spread over a wide range between 1,400 and 2,300 kN/mm. In an earlier paper the author used Bousinesque equation for vertical deformation of rail under the center of a circular loaded surface to derive a linearized Hertzian contact stiffness formula. Eisenmann has devised a simplified calculation method for the wheel-rail contact problem with the assumption that all curve radii in the mathematical formulation of the contact problem are infinitely large except the radius of the wheel. Measurements have proven that a simplified two-dimensional calculation under Eisenmann assumptions suffices for wheel diameters between 600 and 1,200 mm. In this paper, a formula for the contact length under Eisenmann assumptions is derived first before deriving a formula for the contact stiffness. The formulation is validated by application on data taking from literature and by comparing Hertzian contact stiffness values with the earlier formula.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.561

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.033
GPT teacher head0.242
Teacher spread0.208 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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