Intimate contact development for automated fiber placement of thermoplastic composites
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The consolidation step in the automated fiber Placement (AFP) of thermoplastic composites is crucial for development of interlaminar bonding strength. Two mechanisms contribute to the interlaminar bond strength development in the interface between the incoming tow and the substrate: (a) the development of intimate contact between the two surfaces and (b) the formation of a fusion bond across those contacting surfaces known as healing. So far, a number of different theoretical intimate contact models have been proposed in the literature to study intimate contact development for different manufacturing processes. However, very limited experimental methods are available to measure degree of intimate contact. To fill this gap, a new experimental approach based on topology of the tape surface is introduced to quantify the degree of intimate contact for the AFP process. The new approach is based on the Bearing Area Curve (BAC) of the surface profile of the tape. To implement the new procedure, an unidirectional strips of carbon fiber/PEEK were laid down on the polished steel tool with different placement rates, compaction forces, hot gas torch (HGT) temperatures, and tool temperatures. The degree of intimate contact is calculated based on the proposed experimental approach and compared with prediction models from the literature. Furthermore, the effect of AFP process parameters on the degree of intimate contact is studied using BAC method and the effective intimate contact model. The results showed that the development of intimate contact is significantly governed by the torch and tool temperature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 it