Development and numerical modeling of composite structures
Bibliographic record
Abstract
This thesis deals with the development and numerical modeling of Fiber Reinforced Polymer (FRP) wind turbine towers and luminaires. More specifically, this project is designed to capitalize on the technologies developed at the University of Manitoba to design FRP composite structures for use in remote communities where the costs of transportation and erection make the use of steel towers prohibitive. The work presented includes the analysis of a 50 m tall 750 kW wind turbine tower according to International Electrotechnical Commission (IEC) and Canadian Standard Association (CSA) standards using Glass Fiber Reinforced Polymer (GFRP), Carbon Fiber Reinforced Polymer (CFRP) and conventional steel. Standard luminaires, 6 m and 12 m, were also designed according to American Association of State Highway and Transportation Officials (AASHTO) standards for highway luminaires. The results showed that FRP can be effectively used as an alternative material for wind turbine towers and luminaires. Fiber Reinforced Polymer (FRP) composite wind turbine towers and luminaires studied in this project are lighter than similar structures fabricated using steel. Furthermore, these structures also meet the structural performance requirements set by AASHTO, IEC and CSA standards.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".