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Record W2293577027 · doi:10.14288/1.0078539

Modelling power transfer in electron beam heating of cylinders

2009· article· en· W2293577027 on OpenAlexaff
David W. Tripp

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHeat transferBeam (structure)Cathode rayMaterials sciencePower (physics)MechanicsPhysicsElectronOpticsThermodynamicsNuclear physics

Abstract

fetched live from OpenAlex

The electron beam remelting process is used extensively for the refining and recycling of titanium and its alloys. The success of the process relies on its ability to provide a thermal environment capable of removing impurities and deleterious particles while allowing control of chemical composition and solidification. These aspects of the process hinge on the accurate control of power input to the melt stock. Over the years, the effects of various parameters (such as chamber pressure) on the power delivery to the melt stock have largely been ignored. In this work, a series of laboratory scale experiments using instrumented cylinders was conducted. In parallel, a finite element model of the electron beam heating process was developed to analyze the experimental results. The experimental results show that the temperature regime within a target cylinder is affected by variations in chamber pressure. The magnitude of the temperature changes measured as a result of pressure changes was on the order of two to three times the intrinsic error in the thermocouples. Thus these perceived temperature changes were close to the limit of our ability to measure them. The experimental results are self consistent in that a pressure variation produced a similar trend at each thermocouple location. Analysis with the model has shown that the effect of pressure is to alter the power distribution within the beam and not the efficiency of power transfer. The model can be made to reproduce both qualitatively and quantitatively the measured temperature response by varying the beam spreading parameter with chamber pressure. Such a claim cannot be made when varying the power transfer efficiency with chamber pressure. By fitting the model to the experimental thermocouple results it has been shown that that the beam power distribution is adequately represented by a Gaussian or normal distribution. Additional analysis has led to empirical relationships for the effect of chamber pressure on beam focusing characteristics under the conditions used in the laboratory. - The indirect link between chamber pressure and beam power distribution is reinforced using careful and self-consistent experiments, a mathematical model that can reproduce both quantitatively and qualitatively the results of the experiments and the physics of beam - gas particle interactions.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.985

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 head0.009
GPT teacher head0.190
Teacher spread0.181 · 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 designObservational
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
Published2009
Admission routes1
Has abstractyes

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