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Record W3015411666

Thermo-Mechanical Processing of Dual-Phase Steels and Its Effects on the Work Hardening Behaviour

2014· dissertation· en· W3015411666 on OpenAlex
Hossein Seyedrezai

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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueQSpace (Queen's University Library) · 2014
Typedissertation
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWork hardeningMaterials scienceDual (grammatical number)Work (physics)Hardening (computing)MetallurgyMechanical engineeringComposite materialEngineeringMicrostructureArt
DOInot available

Abstract

fetched live from OpenAlex

This thesis focuses on understanding the relationship between the microstructure and the different work hardening mechanisms of DP steels.Through the application of various thermo-mechanical processing schedules prior to inter-critical (IC) annealing, five distinctly different microstructural variants were produced.The work hardening behaviour of the five microstructural variants was examined in terms of the true work hardening rate, , the instantaneous work hardening exponent, n, and the dislocation annihilation factor, h.Additionally, back stresses were measured in selected microstructural variants having similar martensite volume fraction of 15%, using a custom-made in-plane forward-reverse shear testing fixture.At small strains (<2%), the work hardening behaviour was found to be dominated by the introduction of back stresses and the generation of GNDs in the ferrite matrix.The work hardening response at this stage was characterized by p=0.5% and a minimum value in the instantaneous work hardening exponent, n min .Both of these parameters were determined to be functions of f /d (f is the volume fraction and d is the size of martensite particles), the mean ferrite grain size as well as the morphology and spatial distribution of martensite particles.At higher strains (2-3%), a maximum value in the instantaneous work hardening exponent is reached (n max ).This parameter, which can be considered as the work hardening capacity of the material, was found to be a function of mean ferrite grain size but is independent of f /d.The relative contribution of back stresses was also found to reach a constant value at a similar von Mises equivalent strain.This observation suggests that at strains above those associated with n max , other work ii hardening mechanisms become more important.At strains over 4%, dislocation annihilation by dynamic recovery becomes the controlling factor for the rate of work hardening.This phenomenon is described by the dislocation annihilation factor, h, and is a function of f /d, the mean ferrite grain size as well as the morphology and spatial distribution of martensite particles.Finally, it was concluded that the ideal DP microstructure will contain a uniform distribution of fine, equiaxed martensite particles in a fine, equiaxed ferrite matrix.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.832
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)0.0000.000

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 head0.006
GPT teacher head0.191
Teacher spread0.184 · 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