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The Modeling Study on Kinematic Interface Joints Based on Accordant Displacement Method

2010· article· en· W1991391117 on OpenAlexaff
Xue Qian Chen, Qiang Du, Xiao Juan Chen

Bibliographic record

VenueApplied Mechanics and Materials · 2010
Typearticle
Languageen
FieldEngineering
TopicAdvanced Measurement and Metrology Techniques
Canadian institutionsCanadian Association of Emergency Physicians
Fundersnot available
KeywordsKinematicsDisplacement (psychology)Interface (matter)Structural engineeringReflector (photography)VibrationFinite element methodModalModal analysisEngineeringAcousticsMaterials sciencePhysicsOptics

Abstract

fetched live from OpenAlex

The kinematic interface joints are widely used in reflector systems of the high-power solid-state laser facilities. In order to get better finite element(FE) analysis results of reflector systems, it is important to model the joints exactly. The accordant displacement method is used for modeling the joints according to the contact form of joints. The FE model of the reflector system is built subjected to the assuming, the modal analysis and the ambient vibration calculations are carried out. The computing results of inherent frequencies, measure points’ root mean square(RMS) displacements and the transfer characteristics of four kinematic interface positions are accordant with that of the test results. The compared results show that the method modeling the kinematic interface joints is feasible in the paper.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.280
Teacher spread0.262 · 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 source (direct Gemma or distilled Codex), 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
Published2010
Admission routes1
Has abstractyes

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