Modelling of SiC-Matrix Composite Formation by Thermal Gradient Chemical Vapour Infiltration
Bibliographic record
Abstract
Abstract. Mechanical properties of ceramics can be dramatically improved by embedding a reinforcement phase (particles, whiskers, or fibres), i.e. producing a Ceramic-Matrix Composite (CMC). An advanced technique for manufacturing the CMC is Chemical Vapour Infiltration (CVI). In this paper, we developed a 1D model describing the Thermal Gradient Chemical Vapour Infiltration (TG CVI) for a formation of a composite with the silicon carbide (SiC) matrix from methyltrichlorsilane (MTS). Within the model, the fibrous substrate (preform) is considered as a complex porous medium with two systems of parallel non-uniformly scaled pores oriented along the preform thickness. Longitudinal convection in the process is governed by the phase transitions due to the matrix material deposition. To allow for the mass exchange between the pore systems, transverse diffusion and convection are accounted for in the model. We analysed the influence of the TG CVI operating conditions, namely the precursor (MTS) concentration in the ambient gas, the pressure in the reactor, the susceptor temperature, and the temperature gradient in the preform on the quality of the composite and the process duration.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".