Modal analysis of twisted and curved blades using geometrically exact, intrinsic equations and general boundary conditions
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-1705.vid This paper presents a finite-difference method for structural dynamics analysis of initially twisted and curved beams with typical boundary conditions. The geometrically exact intrinsic formulation provides a set of nonlinear first-order partial differential equations that can be used for structural dynamic analysis of beams with initial twist or curvatures. These equations of motion are discretized in space domain using a central difference discretization scheme. Boundary conditions related to the displacements and rotations are introduced as intrinsic expressions in terms of the curvatures and strains. In this work, the general formulation is exemplified for a selected statically indeterminate case. An eigenfrequency analysis is done for a twisted blade under various boundary conditions and the results are verified against the corresponding modal analysis performed in ANSYS Workbench. However, the approach can deal with various combinations of typical rotating blades boundary conditions and can be used together with the geometrically exact, fully intrinsic equations in the structural analysis of statically indeterminate cases.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".