Closed-form Solutions for the Overall Coefficient of Thermal Expansion of n-phase Fiber Composites with Arbitrary Fiber Orientation
Bibliographic record
Abstract
The coefficient of thermal expansion (CTE) is an important physical property of fiber composites. In the past, researchers have provided closed-form expressions for CTE for 2D and 3D random fiber composite structures. In this study, closed-form solutions for the overall CTE of n-phase fiber composites with arbitrary fiber orientation angles are derived based on the volume-weighted averaging equation. The overall unidirectional (fully aligned fibers) thermoelastic properties are developed using the transformation field analysis (TFA) method. In addition, the mechanical concentration factors are estimated using the Eshelby-Mori-Tanaka (EMT) theory. The proposed model allows for varying the fiber volume fraction, aspect ratio, geometry of the fibers, and fiber orientations while designing to meet different criteria. The results obtained using the derived equations are compared and validated with the results published in the literature. Also, a numerical study for an epoxy/graphite composite structure with a range of orientation angles is presented.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".