Determination of the morphological texture of the fibres in a composite material made from a textile of AISI 316L fibres using a mixed deconvolution/positivity method
Bibliographic record
Abstract
The orientation distribution or `morphological texture function' (MTF) of the fibres is determined from measurements of the crystallographic texture of the fibres themselves. From neutron diffraction pole-figure measurements of the fibres in the composite and X-ray diffraction pole figures of the individual fibres, the MTF is determined by a deconvolution. To account for errors in the expansion coefficients due to measurement uncertainties, the deconvolution is performed simultaneously with a positivity criterion in the form of a set of linear equations which may be solved by a least-squares method. This approach is validated using a model system of AISI 316L stainless-steel fibres in an Al–13 wt% Si eutectic casting alloy. The fibres had been spun into yarns and subsequently woven to form a textile. The composite was made by infiltrating a `brick' containing several layers of the textile with the Al alloy. The results of the deconvolution procedure show that the method indeed yields the expected morphological texture. The so-determined MTF is resolved to an angular resolution not attainable by other methods. It also provides a very good estimate of the volume fractions of the different texture components.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".