Linear Stability Analysis and Dynamic Response of Shimmy Dampers for Main Landing Gears
Bibliographic record
Abstract
This paper presents the analysis and study of common shimmy dampers used today for main landing gears with the use of analytical and numerical tools. The shimmy phenomenon is studied by using the tire stretched string theory model and by developing linear approximations of the dynamics of a single tire landing gear. The dynamics of commonly used shimmy dampers are then incorporated into the model. The objectives of this paper are to study already developed shimmy damper designs and to develop tools to design a new innovative and better shimmy damper for main landing gears, those which have nonsteerable wheels. Two shimmy damper designs are studied in this paper, one developed by Boeing and another by UTC Aerospace Systems (UTAS). A linear approximation of the dynamics of these dampers is obtained, omitting the freeplay, saturation, and nonlinear dynamics. Stability plots are then created by changing the system's parameters, such as the velocity, caster length, and the shimmy damper stiffness and damping coefficients. These plots show the comparison of using a UTC two-arm design against the Boeing damper, for which the former spans larger zones of stability but requires higher damping coefficients due to the UTC damper's geometry which is very impractical. In addition, a multibody model is developed in MSC adams (from MSC Software Corporation) to study the dynamic response of these systems and to create a modeling tool that can be used to design a new and improved shimmy damper for main landing gears. The simulation results from the model show the disadvantages of using the UTC two-arm damper, which include an asymmetrical vibration response. Further recommendations are given to design an improved shimmy damper.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".