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Record W1971373348 · doi:10.1115/detc2006-99616

Determination of the Interference Geometry Between Two Convex Objects

2006· article· en· W1971373348 on OpenAlexaff
Lianzhen Luo, Meyer Nahon

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsMcGill University
Fundersnot available
KeywordsInterference (communication)Regular polygonGeometryPoint (geometry)Computer scienceContact geometryBasis (linear algebra)Function (biology)Geometric modelingMathematics

Abstract

fetched live from OpenAlex

The determination of the interference geometry between two arbitrary objects is an essential problem encountered in the simulation of continuous contact dynamics and haptic interactions. In these applications, with known material properties, the interbody contact force is only a function of the interference geometry between two objects. Here a theoretical basis and algorithms for the calculation of the interference geometry, such as overlap region, contact area and normal, and interference volume, are presented. Two methods to obtain the contact area and normal are analyzed: an area-weighted method and a best-fitting method. The geometric properties of the area-weighted method are presented and the degenerate cases related to both methods are discussed. Methods to calculate the application point of an interbody contact force are discussed. Some numerical simulation results are presented based on the implementation of the geometric algorithms, which are verified by comparison with hand calculation. The continuity of contact normal and its application point are demonstrated for a case in which the contacting objects smoothly move with respect to each other in the simulation.

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 score0.886
Threshold uncertainty score0.139

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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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