Thermal Analysis and Modification of C/C Ablative Composites for High-Temperature Insulation Applications
Bibliographic record
Abstract
This study focuses on the modification and thermal analysis of eight distinct carboncarbon (C/C) composite types, designed as advanced thermal insulators.The investigation proceeded along two primary pathways.Firstly, an examination was conducted on the impact of phenolic resin modification, aimed at diminishing the erosion rate of these composites when exposed to an oxyacetylene flame.This involved integrating ammonia molecules with nickel ions in a complex, facilitating hydrogenoxygen bonding, as evidenced by the pronounced broad band of hydroxyl (OH) groups in Fourier-transform infrared spectroscopy (FTIR) results.The presence of this nickel complex was observed to accelerate the graphitization level (GL).Secondly, a comprehensive thermo-mathematical analysis was undertaken on C/C models subjected to oxy-acetylene flames, utilizing the Finite Element Method (FEM) as simulated via the ANSYS software package.X-ray diffraction analysis conducted at 1650℃ revealed the presence of both graphite and turbostratic structures, designated as T&G.This signifies an enhanced GL in resins modified with 10 wt.% of the nickel complex Ni(CH2COCH2COCH3)2.2NH3,compared to those with 3 and 5 wt.% modifications.The effectiveness of modified C/C composites was found to be contingent on the specific type of additive and reinforcement used.Furthermore, a notable convergence between practical and mathematical analysis results was observed, establishing a reliable database for optimizing the selection of insulation type and thickness in practical applications.This investigation underscores the significance of chemical modifications in enhancing the thermal insulation properties of C/C composites.The findings hold substantial implications for the development of high-performance insulation materials, particularly in contexts demanding resistance to extreme temperatures and erosive environments.
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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 | 0.001 |
| 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".