Bibliographic record
Abstract
Purpose The purpose of this paper is to advance the multiphysics analysis of helicopter rotors under icing conditions by coupling the iced rotor’s aerodynamics, analyzed by CFD, with the rotor’s structural characteristics, analyzed by CSD. Design/methodology/approach The current work introduces supercomputer-based computational approaches capable of assessing the impact of ice accretion on the aerodynamics, blade dynamics, vibrations and loading of a rotorcraft. The rigid and elastic motions of the blades are accounted for through a loose coupling of the flow solver to a multibody dynamics solver. The coupling framework allows for comprehensive aeroelastic simulations of iced rotors in hover and in forward flight. Findings The flow and structural modules were validated on a full helicopter configuration in forward flight using the ROBIN experimental model. The tip structural deflections were in very close agreement with the experimental measurements. Research limitations/implications The results of the CFD analyses are limited by the available experimental results they can be compared to. In dry air CFD, three-dimensional (3D) experiments occur first and CFD is then compared to them; in icing, the opposite is true: 3D experiments (if they are ever done, as they are very expensive) chase CFD and sometimes never occur. Practical implications This paper presents an outline of how CFD and computational stress dynamics (CSD) analyses can be linked and provides a toolbox for deeper investigation of the complex flows over helicopters operating under difficult in-flight icing conditions. Social implications More and more helicopters are designed to be able to operate in hostile environments such as rescuing and saving lives over the oceans or mountains, conditions under which icing encounters cannot be avoided. Originality/value A loosely coupled CFD/CSD framework that accounts for the rotor blades structural response to aerodynamic loading and ice accretion in hover and forward flight has been presented. This versatile and cost-effective framework provides a more accurate estimation of the helicopter rotor performance and its degradation due to icing encounters during the early design stages than traditional CFD tools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".