Accurate aeroelastic flutter predictions using a harmonic method
Bibliographic record
Abstract
The numerical results from fundamental research on the aeroelastic stability analysis of airfoils are presented. The long-term goal is to improve flutter predictions of fixed- and rotary-wings by replacing low- to medium-fidelity aerodynamic load calculations made via linearized unsteady aerodynamic theories with Navier-Stokes- or Euler-based flow solutions. Linear aerodynamic theories, such as Theodorsen’s thin-airfoil theory, and doublet-lattice method, which form the backbone of most classical aeroelastic models, provide fast solutions but ignore or fail to capture nonlinearities in the flow which are critical in many situations. On the other hand, computations with, for example, Unsteady Reynolds Averaged Navier-Stokes equations can potentially provide with more accurate results over the entire flight envelope of an aircraft. Today, high-fidelity aeroelastic simulations using computational fluid dynamic (CFD) methods are considered indispensable given that other analysis approaches, such as wind tunnel testing and flight testing are very expensive, time consuming and risky. Despite great advancements in computational resources and algorithms, still the cost of fully coupled, time-integration aeroelastic analysis over the entire flight envelope is prohibitive. In the present study, the harmonic method is proposed to supply CFD solutions to a frequency-domain aeroelastic stability analysis framework. This way, flow nonlinearities caused by the lifting surface thickness, shock waves or by flow separation are, to some extend included in the aeroelastic stability analysis. This also removes the need for expensive fully coupled time-integration simulations. The unsteady aerodynamic lift and pitching moment resulting from simple harmonic motion of airfoils are obtained using an in-house compressible Euler flow solver for a range of reduced frequencies. Then, using the Fourier transform, the time-dependent aerodynamic loads are transformed to the frequency domain and are combined with the structural dynamic loads. Both pitching and pitching-plunging airfoil configurations are studied, and the p-k method is used for aeroelastic stability analysis. Using this computational framework, the effects of airfoil thickness, flow compressibility, and amplitude of oscillations on the aerodynamic loads as well as the flutter speed are studied. The numerical results are compared with those obtained from an analytical framework based on Theodorsen’s unsteady thin-airfoil theory. The sensitivity of the flutter speed to deviations from Theodorsen’s assumptions is particularly examined.
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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 | 0.001 | 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 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".