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Record W2587063384 · doi:10.1115/imece2016-67296

Piecewise Fifth Order Spline Interpolation for Line Heating Forming Process

2016· article· en· W2587063384 on OpenAlexafffund
Henri Champliaud, Zhengkun Feng, David Provencher, Danick Tousignant, Javad Gholipour

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicLaser and Thermal Forming Techniques
Canadian institutionsNational Research Council CanadaÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPiecewiseSpline (mechanical)Interpolation (computer graphics)Spline interpolationLine (geometry)Finite element methodGeometryThermalMathematicsMathematical analysisAlgorithmComputer scienceMechanical engineeringEngineeringStructural engineeringComputer graphics (images)PhysicsBilinear interpolation

Abstract

fetched live from OpenAlex

A fifth order piecewise spline interpolation model has been developed for computing the evolving geometry of a plate deformed by line heating thermal gradients. 3D formulations are presented and applied to continuously derivable geometries to demonstrate the capability of the methodology. Then the developed formulation is used to form gradually, with a sequence of heating lines, a 3D shape from an initially flat plate. The geometric results obtained from finite element simulations with three heating lines are used to illustrate where heating lines should be applied on a flat plate to achieve the intended geometry of a workpiece. Furthermore, it is shown that applying the developed piecewise fifth order spline interpolation model to the same flat plate produces results very close to the ones obtained from the thermal structural FE simulations.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.260

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 head0.012
GPT teacher head0.265
Teacher spread0.253 · 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 designOther design
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
Published2016
Admission routes2
Has abstractyes

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