Thermo-Mechanical Processing of Dual-Phase Steels and Its Effects on the Work Hardening Behaviour
Bibliographic record
Abstract
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, θ, 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 θ ǫp=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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".