Energy-maneuverability diagrams are an important tool that operational pilots use to understand helicopter maneuver performance across a wide range of conditions, however these representations are based upon a number of assumptions that have not been rigorously investigated. The present work reports the results of an investigation into the theory and application of helicopter maneuverability through simulation and flight test. The computational portion of the work focused on a systematic investigation into some of the key simplifying assumptions that are commonly applied in the creation of energy-maneuverability representations. This investigation included aerodynamic simulations of steady maneuvers using a dynamic inflow model as well as a free vortex method. The flight test portion of the work provided important operational context for understanding the practical application of the simulation results. The study illustrated that the fundamental assumption employed in estimating maneuver power requirements for energy-maneuverability representations appears to be reasonable in conditions of the greatest practical relevance, however another key assumption that is invoked to convert excess power into climb performance would likely lead to overestimating the vehicle capability in important operational conditions. Additionally, the flight test data demonstrated that energy-maneuverability results for high angles of bank should be considered for trending information rather than for detailed climb performance values.

A data-driven clustering algorithm based on proper orthogonal decomposition was applied to assess the scatter found in the UH-60A wind tunnel airloads measurements. Upon verifying the capability of the algorithm, pushrod loads, blade surface pressure, sectional loads, and torsional moments were analyzed. Spatial eigenmodes resulting from the decomposition provided the optimal basis; projection of the individual cycles on to the high singular value modes allowed visualizing the statistical distribution of data over the entire azimuth. While not all cases showed furcation in the data, bimodal distribution was found in the high thrust cases, where statistically normal distribution is generally assumed. Consequent clustering of the measured cycles produced excellent correlation among clusters found in the pushrod loads, blade surface pressure, and torsional moment that suggest a common source for furcation in the data. The cycles assigned to one group repeatedly showed distinguishable variations from the other group in terms of the presence/absence of a dynamic stall vortex, azimuthal occurrence of stall, chordwise location of separation and reattachment etc. When one of the cluster is smaller in size compared to the other, the conventional phase-average obscured all the intricate features even when the loads are substantially higher than the larger cluster. In general, clustering the data set when warranted showed not only higher peak loads but also lower variance for both the clusters across the entire azimuth compared to the conventional simple phase-average results. Computational simulations were conducted using CREATETM-AV Helios towards understanding the underlying flow field. Misjudged earlier as under/over-predictive when compared with the simple phase-average data, Helios results consistently showed significantly improved correlation with the smaller of the two clusters. Combining the clustered results and the flow visualization provided by Helios, aperiodicity in the spatial location and the strength of both the trim tab vortices and tip vortices have also been hypothesized as potential sources of furcation.

The development lifecycle of software for aircraft systems is dominated by safety and cybersecurity considerations. Software development processes and tools are being continually updated to improve and optimize these critical considerations. While the processes and tools have received continuous updates, changes to the programming languages employed for developing safe and secure software for aircraft systems have evolved at a much slower pace. As of 2017, 63% of Department of Defense (DoD) systems were developed with the C/C++ programming languages (Ref. 1). This is representative of the dominant position that software developed with the C/C++ programming language has in existing aircraft avionics and mission systems. The C language has been around since the 1970s and C++ was first introduced in the late 1980s. These languages are very stable and their extensive supporting ecosystems have helped grow and maintain their expansive use in aerospace and many other domains. The longevity of C/C++ has enabled language, usage, process, and tool tailoring so that the software built with C/C++ can be certified for use in both safety-critical and security-critical environments. The C/C++ ecosystems are stable and mature but have properties that make writing software embedded in aircraft avionics very challenging.

Corotating coaxial rotors are seeing renewed interest in distributed electric propulsion systems and electric Vertical Take-Off and Landing (eVTOL) aircraft. The recent literature reports many interesting investigations, using prescribed rotor blades, into the flow phenomena as well as aerodynamic and aeroacoustic benefits of corotating rotors. However, the subject of the design of blade geometries, optimized to a design goal, for corotating rotors is currently lacking in the literature. This paper is written from such a design perspective, by extending a previous generalized approach to the aerodynamic optimization of counterrotating rotors to corotating rotors. The previous requirement for upper and lower counterrotating rotor torques to be equal can now be lifted in the case of corotating rotors, enabling improved versatility in the optimization of corotating blade designs. The optimization is demonstrated on an application example to address the conflicting conditions that index angles (high) for low noise benefits are at odds with those (low) for aerodynamic efficiency. The approach demonstrated in this paper is to set the index angle for low noise, and then recover back the aerodynamic efficiency by using the newly developed aerodynamic optimization technique.

The U.S. Army Concept Design and Assessment (CD&A) Technology Area has been following leading companies’ eVTOL development. Based on the Tech Area’s extensive aircraft design and analysis experience questions arose regarding current eVTOLs designs meeting potential military performance and attributes requirements. Similar concerns were seen for Urban Air Mobility (UAM) applications. This document summarizes performance and attribute analyses of leading UAM configurations and compares to helicopters as an alternative configuration. The overall conclusion is that multirotor configurations’ speed and range are inherently inadequate for military applications. High Speed eVTOL (HS-eVTOL) configurations (i.e. winged VTOLs) are point designs for high speed, medium range, and very short hover duration missions. They are also inadequate for an important spectrum of military missions. The work concludes the Department of Defense (DoD) needs to invest in more traditional low disk loading eVTOL configurations if it is to gain the most operational benefit from electric propulsion VTOL aircraft.

A well-defined reference set of data for CFD and comprehensive code validation for a scaled helicopter main rotor with boundary layer transition in forward flight is presented. The boundary layer transition was measured using Differential Infrared Thermography (DIT) on the top (suction) side of the NASA/Army “PSP rotor” in the NASA Langley 14- by 22-Foot Subsonic Tunnel. The tests used a FLIR X8500 SLS long-wave infrared camera to observe the three-bladed rotor. The boundary layer transition was detected for forward flight at an advance ratio of 0.3 (115kt). The measured boundary layer transition positions are consistent with previous measurements and predicted boundary layer transition locations. A method for the analysis of DIT images for a rotor in forward flight is shown and validated based on computational analysis of a pitching airfoil with varying inflow, showing both qualitative and quantitative similarity to experimental data.

Legacy gunner seats in the H-60 family of helicopters have long been known for their poor crash performance(i) and poor ergonomics(ii). The seat occupant is poorly restrained in a crash and can move significantly away from the seat to impact other interior hard structure, causing injury and death. The poor seating and posture induced by the seat's design can lead to lost work days and reduced operational readiness due to chronic back pain. Recently, a NAVAIR program designed and developed a new gunner's seat to address the legacy seat's shortcomings. A critical component of the seat is the restraint system, which must protect the occupant in the event of a crash, yet provide a significant level of mobility away from the seat, while still buckled into the restraint, during flight to allow the aircrew to perform their mission duties. This paper discusses the symbiotic relationship between aircrew, maintainers, and engineers used to develop the completely redesigned restraint system as part of a rapid gunner seat upgrade program.

This paper evaluates the state-of-the-art Viscous Vortex Particle Method (VVPM) and its application for mutual aerodynamic interaction of multiple rotors with fuselage and download predictions as well. For this effort, the VVPM is coupled with structural dynamics and lifting line airloads from the Rotorcraft Comprehensive Analysis System (RCAS), as well as a panel method for fuselage blockage effects. The coupled RCAS/VVPM/Panel solution is applied to several test cases including 1) performance prediction of the NASA’s Multirotor Test Bed which is a new test capability for advanced eVTOL multirotor air vehicle configurations, 2) aerodynamic interactions between a rotor and ROBIN fuselage in a wind tunnel and 3) download evaluation with Cassarino’s compound helicopter configuration. Results demonstrate the capability to predict induced velocity field, pressure distributions on the fuselage, and downloads using the coupled RCAS/VVPM/Panel solver.

In this paper, the effects of Rossby number and Reynolds number on the evolution of forces and the flow field over a rotating wing has been studied. Force measurements were conducted for five Reynolds number (Re = 8000, 10000, 12000, 14000 & 15000) and three Rossby number cases (Ro = 4.7, 5.4 & 5.9). Quantitative flow field measurements were conducted using the rotating three-dimensional velocimetry technique for all three Rossby numbers at Re = 8000 & 15000. For the majority of the cases considered, the lift coefficient plots showed an initial steep increase, a peak and then a drop down to reach a steady state value. A steep rise and a strong peak in lift coefficient can be attributed to the formation and growth of a strong LEV. The steady state value of lift coefficient can be attributed to the continuous shedding of secondary LEVs as the wing continues to rotate. However, at select Re cases for Ro = 5.4 and Ro = 5.9, the initial steep rise in lift coefficient was not observed. Furthermore, the steady state lift coefficient at all Reynolds numbers for a given Ro was observed to be constant, and marginally higher at higher Ro. Hence, a new method was implemented to normalize the steady state lift coefficient; by normalizing the steady state lift coefficient by the corresponding Rossby number, and it was observed that the steady state lift coefficient values for all the cases collapsed onto a single value. Dye flow visualization qualitatively showed the onset, growth and shedding of both the LEV and TEV. The quantitative flow field analysis yielded a uniform LEV formation in the measurement domain considered. The circulation was determined by integrating the spanwise vorticity in the vortex core and it was observed to agree well with the lift coefficient trends for the cases considered.

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 partly 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 any commercially-available airborne optical sensor. While numerous techniques for learning-based object detection have appeared in the literature, many of them are data- and computation-intensive. Our approach seeks to balance the performance in regards to the detection and classification accuracy on the one hand, and the amount of training data and runtime performance on the other hand. Specifically, our approach combines the invariant feature extraction ability of pre-trained deep Convolutional Neural Networks (CNNs) and the high-speed training and classification ability of a novel, proprietary frequency-domain Support Vector Machine (SVM) method. In this paper, we present the CNN+SVM method for efficient obstacle detection and classification. We describe the experimental setup comprising datasets of pre-defined classes of obstacles – pylons, chimneys, antennas, towers, wind turbines, flying aircraft – from airborne video sequences of low-altitude helicopter flight. We analyze the performance results using average precision, average recall, and runtime performance metrics on representative test data. Finally, we present a simple architecture for a real-time, on-board evaluation of automatic vision-based obstacle detection.