Experimental Modal Analysis of a Half-Scale Model Rear Twin-Engine Mounted Aircraft Fuselage Section
Bibliographic record
Abstract
Experimental modal testing using an impact hammer is a commonly used method for obtaining the modal parameters of any structure for which the vibrational behavior is of interest. Natural frequencies and associated mode shapes of the structure can be extracted directly from measured FRFs (Frequency Response Functions) through various curve fitting procedures. This thesis provides an overview of the modal testing conducted on various scaled aerospace components. These components are part of a half-scale model rear twin-engine mounted aircraft fuselage tail section which is being constructed in order to provide relevant vibrational and dynamic trends to a leading Canadian aerospace manufacturer. The experimental modal results were used to validate the associated computational modal data. It is this initial validation step which forms the foundation of the research project presented herein and which will allow for future modal testing work to be conducted on the half-scale assembly once completed. Testing set-up, experimental equipment and the methodology employed are all described in detail. Furthermore, a series of validity checks were done by ensuring that the experimental results satisfy the requirements inherent to linear modal analysis including repeatability, reciprocity and linearity. This provided confidence in the employed testing procedure. Recorded natural frequencies (eigenvalues), mode shapes (eigenvectors), coherence plots and other important experimental data are presented along with notable trends. Finally, key literature has been referenced where appropriate and important concepts to modal analysis are expanded upon. This thesis, then, demonstrates that experimental modal analysis can be successfully implemented into a testing methodology that helps establish vibrational trends and, thus, better understand and help resolve vibro-acoustic issues on aircraft.
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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 | 0.001 |
| 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) | 0.006 | 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".