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Record W4247016240 · doi:10.32920/ryerson.14654481.v1

Experimental analysis and numerical modeling of particle embedment and fracture in the solid particle erosion of ductile materials

2021· preprint· en· W4247016240 on OpenAlexafffund
Vahid Hadavi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsEmbedmentMaterials scienceShadowgraphyParticle (ecology)MechanicsRoundness (object)Fracture (geology)AbrasiveDiscrete element methodParticle sizeComposite materialOpticsPhysicsLaserEngineeringGeology

Abstract

fetched live from OpenAlex

Embedment and fracture of abrasives are two often neglected important phenomena that can affect material removal occurring in industrial processes that involve high speed impact of particles on relatively ductile targets. This thesis proposes new methodologies to predict the likelihood of particle embedment and fracture for a typical solid particle erosion application. Double-pulsed laser shadowgraphy was used to measure the instantaneous orientation of angular 89-363 μm SiC particles within a micro-abrasive jet, in order to assess whether their orientation affected the propensity for particle embedment. A tendency for particles to orient with the jet axis was measured and successfully modelled (<9% error), with larger abrasives more likely to orient. The measured instantaneous orientation of particles was used to generate a three-dimensional coupled finite element and smoothed particle hydrodynamics model capable of simulating the particle embedment. Use of various combinations of process parameters yielded embedment predictions that agreed with measured ones with, at most, a 16% error. Increases in particle size, orientation angle, and velocity were found to enhance the propensity for embedment. Double-pulsed laser shadowgraphy was used to record the impact and fracture of abrasives upon impact. A numerical model that utilized an Element Free Galerkin (EFG) technique with a novel scheme for generating realistic three-dimensional particle geometries was used to simulate the particle fracture. For a wide variety of process parameters, the numerical predictions of particle average size, roundness and rebound velocity agreed with the corresponding measurements to within 10%, at most. The propensity for particle fracture was found to depend on the magnitude of particle kinetic energy perpendicular to the target. It was confirmed that at the same incident velocity, larger particles were more likely to fracture. However, for the same kinetic energy, smaller particles were more likely to fracture. To the best knowledge of the author, this thesis is the first to report measurements of particle orientation and particle fracture in abrasive jets, and the first to develop numerical modeling of particle fracture and embedment. The results have important implications for erosion testing and abrasive jet machining operations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.122
Threshold uncertainty score1.000

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)0.0010.000

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 head0.021
GPT teacher head0.294
Teacher spread0.273 · 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.

Study designBench or experimental
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
Published2021
Admission routes2
Has abstractyes

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