With the wide application of unmanned aerial vehicles, interest in multirotor conifgurations has increased. The unique features of multirotor con guration have been intensely investigated, including aerodynamic interference, which is particularly important because it in uences the vibration, noise, and handling quality of rotorcraft. Most previous studies have used high-fidelity approaches, such as computational fluid dynamics to identify such interference. However, such an approach is inappropriate for real-time flight simulations. In this study, an improved aerodynamic interference analysis based on a dynamic vortex tube was established for performance prediction in real-time ight simulation. A simple and effective formulation is proposed for integration with rotor aerodynamics to evaluate the interference of multirotor con gurations. The present analysis is validated on various multirotor configurations. An investigation of interference in a multirotor unmanned aerial vehicle (UAV) is then presented. The analysis results exhibit good agreement with experimental results and high-fidelity predictions. Although the accuracy of the proposed analysis is lower than that of experimental studies and high-fidelity analyses, it is suf cient for capturing interference trends. The proposed analysis can account for aerodynamic interference in the flight simulation of a multirotor UAV.

Aviation statistics identify collision with terrain and obstacles as a leading cause of helicopter accidents. Assisting helicopter pilots in detecting the presence of obstacles can greatly mitigate the risk of collisions. However, only a limited number of helicopters in operation have an installed helicopter terrain awareness and warning system (HTAWS), while the cost of active obstacle warning systems remains prohibitive for many civil operators. In this work, we apply machine learning to automate obstacle detection and classification in combination with commercially available airborne optical sensors. While numerous techniques for learning-based object detection have been published in the literature, many of them are data and computation intensive. Our approach seeks to balance the detection and classification accuracy of the method with the size of the training data required and the runtime. Specifically, our approach combines the invariant feature extraction ability of pretrained deep convolutional neural networks (CNNs) and the high-speed training and classification ability of a novel, proprietary frequency-domain support vector machine (SVM) method. We describe our experimental setup comprising the CNN + SVM model and datasets of predefined classes of obstacles—pylons, chimneys, antennas, TV towers, wind turbines, helicopters—synthesized from prerecorded airborne video sequences of low-altitude helicopter flight. We analyze the detection performance using average precision, average recall, and runtime performance metrics on representative test data. Finally, we present a simple architecture for real-time, onboard implementation and discuss the obstacle detection performance of recently concluded flight tests.

Recent advances in urban air mobility have driven the development of many new vertical take-off and landing (VTOL) concepts. These vehicles often feature original designs departing from the conventional helicopter configuration. Due to their novelty, the characteristics of the supervortices forming in the wake of such aircraft are unknown. However, these vortices may endanger any other vehicle evolving in their close proximity, owing to potentially large induced velocities. Therefore, improved knowledge about the wakes of VTOL vehicles is needed to guarantee safe urban air mobility operations. In this work, we study the wake of three VTOL aircraft in cruise by means of large eddy simulation. We present a two-stage numerical procedure that enables the simulation of long wake ages at a limited computational cost. Our simulations reveal that the wakes of rotary vehicles (quadcopter and side-by-side helicopter) feature larger wake vortex cores than an isolated wing. Their decay is also accelerated due to self-induced turbulence generated during the wake roll-up. A tilt-wing wake, on the other hand, is moderately turbulent and has smaller vortex cores than the wing. Finally, we introduce an empirical model of the vortex circulation distribution that enables fast prediction of wake-induced velocities, within a 2% error of the simulation results on average.

The high fatality rate of autogyros in the 1990s sparked academic research into autogyro performance, stability and control, and handling qualities. This has included limited study on the inverse simulation of autogyros. The conducted research relied on the use of a modified version of the Generic Inverse Simulation Algorithm (GENISA), which used an iteratively recalculated inverse simulation time step to account for the variability in rotor speed throughout maneuvers. This does not allow for prediction of maneuver completion time, though, significantly increasing computational workload when developing ADS-33E mission task element maneuver models. The research conducted in this article presents a further modified inverse simulation algorithm, based on GENISA, which allows a constant inverse simulation time step to be utilized. Robustness analysis of the inverse simulation algorithm, using a mathematical model of the longitudinal dynamics of a twoseat Montgomerie–Parsons autogyro, showed it is robust enough to analyze realistic moderate (60 mph) and high speed (80 mph) longitudinal pop-up and pop-down maneuvers. More importantly, the constant time step in the algorithm allows for prediction of maneuver completion time, significantly reducing workload when conducting handling qualities assessment.

The structural design of rotor blades with ultra-thin, unconventional airfoils is conducted in support of the NASA Rotor Optimization for the Advancement of Mars eXploration (ROAMX) project. The outer mold line was provided by NASA, and the internal structural design was developed at the University of Maryland using a CAD-based three-dimensional (3D) aeromechanical analysis. The main objectives of this paper are to document the unique aeroelastic behavior encountered due to the low Reynolds number (down to 15K) and high subsonic Mach number (up to 0.95). Four different blade designs are considered, with the pitch axis varied from quarter-chord to midchord to determine the effect of center of gravity (C. G.) offset on natural frequencies, blade deformations, root loads, and 3D stresses. Torsional stability is emphasized for each of the designs - especially important due to the low Lock number on Mars. The designs are first studied in vacuum, and significant reductions in root loads and 3D stresses are achieved by moving the pitch axis closer to midchord to reduce the C. G. offset. Next, the design with the pitch axis at 40% chord is selected for a lifting-line aeromechanical analysis. The blade control load, airloads, deformations, and 3D stresses are studied for steady hover. Dynamic control load and dynamic 3D stresses are studied for unsteady hover. Interesting elastic twist is observed due to the trapeze effect and propeller moment, in turn affecting the spanwise distribution of aerodynamic loads. The dynamic control load is found to increase significantly due to inertial coupling from the C. G. offset. The dynamic stresses also increase but still have factors of safety greater than two for both tensile and compressive stress.

A hybrid gear concept that combines a metallic outer rim of gear teeth with a composite web to reduce drivetrain weight was evaluated for impact of tooth microgeometry modifications on transmission error. Control of transmission error through tooth microgeometry modification is important for control of noise and vibrations generated by a drivetrain. The added flexibility of hybrid gears over steel gears brings to question the performance of hybrid over conventional gears relative to their dynamic transmission error and resulting noise levels. Previously developed drivetrain models featuring hybrid spur gears were used to determine optimal tooth microgeometry modifications that minimized peak-to-peak transmission error. Static and dynamic transmission errors were then calculated using the optimal microgeometries and compared to results for a similarly optimized all-steel drivetrain. From the results, it appears that the use of hybrid gears will not negatively affect vibration performance for low- and medium-speed applications, as hybrid gear models predicted similar transmission errors to their all-steel counterparts. At higher speeds, drivetrains featuring hybrid gears were predicted to have significantly different transmission errors, but whether this difference was an improvement or detriment is design and speed-dependent. Therefore, careful design is necessary for high-speed hybrid gears.

Time-dependent Navier–Stokes simulations have been carried out for a V22 rotor in hover using an improved, lowdissipation, HLLE ++ upwind algorithm in the OVERFLOW code. Emphasis is placed on lessons learned over the past decade regarding the effects of high-order spatial accuracy, grid resolution, and the use of detached eddy simulation in predicting the figure-of-merit, the rotor's chief performance parameter. A general quick-start procedure is described together with a statistical measure of FM convergence that reduces hover computations by fourfold, similar to computational work for forward flight. Cartesian adaptive mesh refinement is used to resolve the tip–vortex to its correct physical size. This adaptive mesh refinement in the rotor wake also revealed a complex turbulent flow with worm-like structures of various scales. These structures were numerically found a decade ago and recently observed in experiment.

Performance of ball bearings in the motion converter subassembly of an internally driven, single-speed, torque-split, twin configuration pericyclic transmission prototype is evaluated to extend the analytical knowledge base on this innovative transmission concept. A dynamic model of the transmission is developed with high-fidelity models of the installed rolling element bearings to determine their reactions. Attention is focused on the pair of ball bearings supporting the motion converter subassembly which are subjected to a complex combination of loads, including radial and axial forces, moments, carrier motion, and possibly internal preload. Then the influence of internal axial clearance and preload on the behavior of the rolling elements is analyzed with a fully dynamic ball bearing model. Provisions to consider the carrier motion and a robust integration algorithm for component orientations are presented. Finally, a microstructure-based fatigue life simulation of the critical bearing component is performed to demonstrate the effect of clearance/preload on bearing reliability.

This article describes the implementation and linearization of free-vortex wake models in state-variable form as applied to rotary- and flapping-wing vehicles. More specifically, the wake models are implemented and tested for a UH-60 rotor in forward flight and for a hovering insect representative of a hawk moth. A periodic solution to each wake model is found by time marching the coupled rotor/wing and vortex wake dynamics. Next, linearized harmonic decomposition models are obtained and validated against nonlinear simulations. Order reduction methods are explored to guide the development of linearized wake models that provide increased runtime performance compared to the nonlinear and linearized harmonic decomposition wake models while guaranteeing satisfactory prediction of the periodic response of the wake. This constitutes a first attempt to extend free-vortex wake methods in state-variable form, originally developed for rotary-wing applications, to flapping-wing flight.

The flow fields of a 2-m diameter two-bladed single rotor, a 2× 2-bladed coaxial corotating (stacked) rotor, and a 2× 2-bladed coaxial counterrotating (CCR) rotor in hover were measured using particle image velocimetry and computed using a finitevolume unsteady Reynolds-averaged Navier–Stokes (URANS) CFD model. Phase-resolved measurements were performed on the stacked rotor at nine azimuthal locations, and time-resolved measurements were performed on the CCR rotor at 64/rev with at least 500 flow realizations per azimuth for each operating condition. The goal of this study was to compare the flow features of these rotor configurations and explore the interactions between the rotors. Overall, there was good correlation between the measurements and simulations. In particular, the effect of index angle on the upper and lower rotor thrust sharing for the stacked rotor was predicted well by the simulation. The slipstream boundary for the stacked rotor was found to vary with the index angle. The slipstream boundary and vortex trajectories for the CCR rotor were found to vary with azimuthal location, indicating the effect of blade passage on the wake geometry. Simulations indicated a stronger dependence of the tip vortex trajectory on the index angle and thrust for the stacked rotor compared to the CCR rotor. The radial thrust distribution along the upper blades was found to depend on the index angle for the stacked rotor and showed small variation due to blade passage for the CCR rotor. A larger azimuthal dependence was seen for the radial thrust distribution on the lower rotor blades, primarily due to the proximity of the upper rotor tip vortices. The lower rotor radial thrust distribution was biased towards the blade tip, outside the upper rotor slipstream.