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Record W1513444374

Estimation of the pressing force in blade forming application

2007· article· en· W1513444374 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venueinternational conference on Modelling and simulation · 2007
Typearticle
Languageen
FieldEngineering
TopicBladed Disk Vibration Dynamics
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsPressingIsothermal processBlade (archaeology)Turbine bladeMaterials scienceMechanicsComputer simulationHot pressingMechanical engineeringTurbineComposite materialPhysicsEngineeringThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

We develop a 3-D FE model to simulate the hot forming process for the turbine blades based on elastic-plastic theory and unilateral contact friction theory under isothermal assumption. Due to the quasi-static assumption, an explicit dynamic formulation is used with a scale mass matrix. A method is proposed to estimate from experimental data the temperature of the forming simulation. The evolution of the material properties versus the temperature is selected combining experimental results and bibliographic sources. The numerical model is validated using experimental data. A numerical analysis of the influence of blade size (thickness, width, length, depth) on the pressing force is described. Finally a fast model to estimate the required pressing force is proposed. A multi-input single-output model is used where the input are only defined by the geometrical parameters, the material and the temperature of the blade and the output is the pressing force. The model is approximated with a least square method based on FE simulation results. Comparisons are made between the fast and FE models.

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.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.587
Threshold uncertainty score0.249

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 head0.029
GPT teacher head0.283
Teacher spread0.254 · 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