The formation of technical appearance of a helicopter-type unmanned aerial vehicle in part of take-off and landing devices that provide take-off and landing on the ship’s helicopter landing pad
Bibliographic record
Abstract
Due to the growing requirements to the fleet in terms of increasing the efficiency of solving assigned tasks, taking into account the ever-increasing operational situation, increased use of unmanned aerial vehicles is required, including small and medium-displacement ships. Thus, an important trend in the development of helicopter-type unmanned aerial vehicles (HT UAVs) is their adaptation to ship-based conditions. The key problem of adaptation is ensuring the take-off and landing on the ship’s landing pad (runway). This article discusses the influence of ship-based conditions, the most important of which is ship’s pitching, and requirements for performing takeoff and landing operations, including the need to adapt to forced landing systems, on the formation of the design of the landing gear of a HT UAV, and formulates the design specifications typical to the landing gear of a shore-based aircraft. At the same time, to study the dynamic and static compatibility of the HT UAV with the ship, deterministic or probabilistic characteristics of the ship’s pitching should be set in the form of pitching amplitudes and periods, pitching spectral densities, variances of displacements and velocities of the runway center, as well as displacements, velocities and accelerations in the runway center. Based on the specified parameters, the kinematics of the movement of the center of the runway and its spatially complex positions are calculated to solve the problem of dynamic compatibility of the VTOL UAV with the ship. Dynamic compatibility includes determining the stability and controllability of the HT UAV, unwinding and stopping the main rotor, take-off and landing, and transporting the HT UAV along the runway. The existing and prospective basic design schemes of the skid landing gear are divided into four main types and evaluated for compliance with the specifics of operation on the ship, special attention is paid to the possibility of adaptation to forced landing systems on deck. Based on the evaluation results, a design scheme of the landing gear for a promising HT parallelogram-lever type UAV with an external shock absorber is proposed. As a confirmation of the compliance of the proposed scheme with the formulated requirements, the results of the calculation of the dynamic landing gear model during landing and rolling, performed in the Simcenter Motion software package, are presented. The proposed scheme can be implemented for both HT UAVs and manned ship-based and shore-based helicopters.
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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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".