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Record W2034780961 · doi:10.1115/detc2007-34978

Experimental Validation of Nonlinear Compliant Contact Force Models

2007· article· en· W2034780961 on OpenAlexaff
Yuning Zhang, Inna Sharf

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdhesion, Friction, and Surface Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsCoefficient of restitutionContact forceNonlinear systemDissipationMechanicsStatistical physicsImpactRange (aeronautics)Contact dynamicsComputer sciencePhysicsEngineeringClassical mechanicsAerospace engineering

Abstract

fetched live from OpenAlex

Contact dynamics modeling continues to be an intensive research area with new applications of contact dynamics simulation arising in engineering practice. One approach to normal contact force modeling that has gained significant popularity is the compliant model in which the contact force between two objects is defined explicitly as a function of local deformation and its rate. Probably the most well-known model in this category is the Hunt and Crossley model, which employs a nonlinear damping term to model the energy dissipation during contact, with the damping coefficient related to the coefficient of restitution. This model prompted several investigations on how to evaluate the damping coefficient, in turn resulting in several variations on the original Hunt-Crossley model. In this paper, the authors aim to experimentally validate the Hunt-Crossley type of nonlinear contact force models and furthermore, to compare the experimental results to the model predictions obtained with different values of the damping coefficient. The paper reports our findings from the sphere to plate impact experiments, conducted for a range of initial impacting velocities, with measurements of impact forces and accelerations. The experimental forces are compared to those predicted from the contact dynamics simulation of the experimental scenario. The experiments, in addition to generating novel impact measurements, provide a number of insights into both the study of impact and the impact response.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.288

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 head0.028
GPT teacher head0.274
Teacher spread0.247 · 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 designBench or experimental
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

Citations1
Published2007
Admission routes1
Has abstractyes

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