Additive Manufacturing and Composite Materials for Marine Energy: Case of Tidal Turbine
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 global trend in additive manufacturing is the technology of three-dimensional (3D) printing with a high potential to avoid some of the weaknesses of conventional fabrication techniques. This new technology has been used to manufacture small tidal and wind turbines. In isolated areas, small turbines can be manufactured and assembled on-site for green energy production. The purpose of this document is to evaluate the thermomechanical behavior of a printed tidal turbine using Digimat-AM (Additive Manufacturing) with fused filament fabrication method. The finite element computes the mechanical deflection, temperature, residual stresses, and warpage fields of the printed part. The composites used during printing are thermoplastic polymers (acrylonitrile butadiene styrene, polyamide 6 [PA6], polyamide 12 [PA12], and polyetherimide [PEI]) reinforced with carbon and glass fillers in the form of fibers and beads (CF/GF and CB/GB). Through the simulation, one could show that the blade printed with PEI-CB/CF has excellent mechanical performance of low mechanical deflection and warpage, compared to PA6-CB/CF. In addition, the fiber-shaped fillers are better than the bead-shaped ones for the 3D printing process. In general, this study has shown the potential and feasibility of 3D printing as an excellent opportunity in the fabrication of small blades in the future, but more studies are required to understand this potential.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 it