Pseudo-Homogeneous Sinusoidal Infill Using Non-Planar FFF Techniques for Use in RPAS Structures
Bibliographic record
Abstract
This thesis investigates the development and testing of pseudo-homogeneous sinusoidal infill (PHSI) using non-planar fused filament fabrication (FFF) techniques for application in aerospace components, focusing on remotely piloted aircraft systems (RPAS).The objective is to enhance the mechanical properties of FFF-produced components through non-planar techniques while quantifying strength and modulus as bulk properties.A systematic methodology was employed, referencing industry standards.Statistical analysis confirmed the reliability and consistency of the mechanical performance improvement of PHSI parts, highlighting their potential for use in RPAS structural applications.This research builds upon previous studies at Carleton University, advancing the understanding of non-planar 3D printing methods and their impact on mechanical properties.The findings contribute to the ongoing discussion on certification standards for 3D printed RPAS components.The insights gained from this study are applicable to a wide range of components, encouraging further exploration of non-planar designs in aerospace applications.I want to start by expressing my gratitude to
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".