Browse Topic: Vehicles, Equipment, and Performance
ABSTRACT Over time, the National Institute of Standards and Technology (NIST) has refined the 4Dimension / Real-time Control System (4D/RCS) architecture for use in Unmanned Ground Vehicles (UGVs). This architecture, when applied to a fully autonomous vehicle designed for missions in urban environments, can greatly assist in the process of saving time and lives by creating a more intelligent vehicle that acts in a safer and more efficient manner. Southwest Research Institute (SwRI®) has undertaken the Southwest Safe Transport Initiative (SSTI) aimed at investigating the development and commercialization of vehicle autonomy as well as vehicle-based telemetry systems to improve active safety systems and autonomy. This paper will discuss the implementation of the 4D/RCS architecture to the SSTI autonomous vehicle, a 2006 Ford Explorer.
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This SAE Information Report contains definitions for hydrogen fuel cell powered vehicle terminology. It is intended that this document be a resource for those writing other hydrogen fuel cell vehicle documents, specifically, Standards or Recommended Practices.
The Sikorsky S-92® helicopter fleet, representing more than 300 aircraft and 2.6 million flight hours, is relied upon to support a large range of important missions across the globe. In previous efforts, a high-fidelity CFD-CSD based full-aircraft simulation methodology, co-simulated with production FCS, was developed and applied to model both coaxial aircraft and single main/tail rotor configurations (Refs. 1-5). The CFD solver is based on the CREATE™-AV HELIOS toolset (Ref. 6) and the CSD solver is based on Rotorcraft Comprehensive Analysis System (RCAS) (Ref. 7). The current paper further correlated the CoSim methodology (Ref. 1) with the S-92® helicopter flight-test database at both hover, cruise and edge-of-envelope maneuver flight conditions. The consistent correlations for flight dynamics, static and fatigue component loads at conditions across the flight envelope demonstrate the reliable predictive capability of the high-fidelity CoSim methodology to be-used as a virtual digital flight test and to support advanced design at early stage.
This study evaluates the operational impact of multiple concurrent spatialized auditory cues during high-workload rotorcraft missions. A controlled, within-subject flight simulation experiment was conducted in which military-qualified rotorcraft pilots completed continuous multi-objective missions including formation flying, visual asset detection, collision avoidance, and emergency landing tasks. Each mission was flown under spatialized (3D) and non-spatialized (2D) audio rendering conditions while cue composition remained constant. Preliminary results indicate that under complex, formation-dominant workload conditions, pilots consistently prioritized visually anchored tasks and largely deprioritized auditory cue information regardless of spatial rendering. Collision avoidance cues did not produce observable evasive responses, and reported cue trust remained low without prior training. Although limited performance improvements were observed in isolated conditions, participants reported consciously suppressing audio cues. These findings suggest that effective integration of spatial audio requires structured training, procedural embedding, and deliberate workload redistribution rather than perceptual enhancement alone.
In this study, a multifidelity aeroelastic framework is presented for predicting trim conditions in rotary-wing aircraft, with the main focus placed on the DUST implementation and its application to helicopters and quadrotors. The methodology combines aerodynamic and structural solvers of different fidelity, specifically DUST and the multibody dynamics solver MBDyn, through the preCICE coupling interface to enable direct comparison with rigid and coupled aeroelastic solutions. The trim problem is formulated from the six degree of freedom rigid body equilibrium equations in a helical turn reference frame, naturally covering both steady and maneuvering flight. Although the same formulation can be extended to fixed-wing configurations, the present paper is focused on rotorcraft applications. The framework is first applied to the SA330 Puma helicopter, chosen for the availability of validated flight test data. The methodology is then extended to a multirotor derived from a NASA quadrotor, demonstrating that the same trim strategy can be transferred to distributed-lift rotorcraft. Results highlight the potential of the proposed approach to provide physically consistent and computationally affordable predictions of helicopter and multirotor equilibrium states.
This paper presents results of flight tests conducted on a coaxial ultralight helicopter. An automated flight test evaluation method is presented and exemplified through its application to steady horizontal flight. The results shown include pilot controls, helicopter attitude angles, power, thrust and torque distribution between the rotors, rotor harmonic thrust components, and teeter angles, along with their rotor harmonic components across varying flight speeds. This study focuses on the dependencies of these parameters on center of gravity position and sideslip angle.
This organizational process survey provides insight into the technical aspects of approved airworthy aircraft modifications applied in government organization vertical lift flight test. The publication reviews processes applied by the National Research Council of Canada's Flight Research Laboratory (NRC-FRL) and its Airworthiness Control System to enable research flight testing. Dominated by the need for integrating experimental payloads, the NRC-FRL embeds a Design and Fabrication Service organization for modification of internal and external client projects and flight test aircraft. In context of experimental flight testing, this work reviews technical information on process, facilities, and methodology for airworthy integration of flight test payloads. Information is used to synthesize recommendations in experimental vertical lift flight testing that satisfy both formal (regulated compliance) and informal (compliance intent) airworthiness requirements.
Traditional safe-life methodologies for rotorcraft structural components rely on deterministic safety factors to account for uncertainty in loads, material properties, and operational usage. While effective for ensuring safety, these approaches lead to early retirement lives and reduced aircraft availability. This paper presents an updated digital twin-based probabilistic framework for rotorcraft component fatigue life assessment that integrates a probabilistic stress–life (S-N) material model, machine learning-based load estimation from flight data, and Monte Carlo uncertainty propagation. The approach is demonstrated for a critical location on the CH-146 Griffon main rotor yoke. Compared with earlier work, the present study advances the framework through independent validation of the load-estimation model and application to available in-service flight data from multiple mission categories. A probabilistic sensitivity analysis is used to examine the separate and combined effects of material variability and load-estimation uncertainty on fatigue life, cumulative probability of failure, and hazard rate. For the CH-146 demonstration case, the results indicate that the material fatigue strength uncertainty has a major impact on the lower tail of the life distribution and the corresponding reliability-based life, whereas load-estimation accuracy uncertainty has a secondary influence on risk metrics. The application of the digital twin framework to operational, search and rescue, and training mission data further shows that mission-specific usage variability plays an important role in the evolution of fatigue damage accumulation and structural risk. Overall, the proposed framework provides a more informative basis for risk-based rotorcraft life assessment by explicitly quantifying uncertainty and incorporating aircraft-specific operational data. The study is intended as a step toward validation of the framework rather than a completed operational deployment.
Helicopter tail shake constitutes a significant limitation to both passenger comfort and aircraft stability. Under powered descent conditions, elevated Angle of Attack (AoA) cause flow separation around the rotor hub and engine cowling, leading to the development of an unsteady wake dominated by large-scale turbulent structures. To support the helicopter tail shake phenomenon investigation, a dedicated Particle Image Velocimetry (PIV) experimental setup was designed in this work, together with four aerodynamic devices aimed at mitigating tail shake. These components were then tested through a wind tunnel campaign with the PIV setup. The proposed aerodynamic components were conceived to either deflect the hub wake away from the tail empennages or to decrease the Turbulent Kinetic Energy (TKE) within the wake. To achieve these objectives, a dorsal fin, a horse-collar, and two spoiler configurations inspired by automotive applications were designed and experimentally evaluated. The devices were tested both as standalone solutions and in combined arrangements on a scaled helicopter wind tunnel model featuring a rotating hub and blade shanks. The vertical velocity component, was used as an indicator of wake deflection, and the Turbulent Kinetic Energy was used as an indicator of wake turbulence. The Horse Collar and the Large Spoiler showed a reduction in both indicators suggesting possible tail shake mitigating capabilities, and additional improvements were achieved when the two devices were deployed in combination.
The current work presents a methodology to estimate the mission and performance capabilities of a generic rotorcraft configuration, to satisfy the need of evaluating the integration of a full electric powertrain in the aircraft design. To include all the design steps, two different approaches are proposed. For the preliminary phase, the "Analytic Method" is considered, which exploits a purely resistive model. Conversely, a method based on look-up tables called "Table Method" is intended to be used in more advanced phase, when the battery pack is defined. Both approaches are tested by evaluating a reference mission and a hover chart. Finally, a verification of the presented methodology is carried out by comparing the mission results with a commercial software, specialized in the evaluation of the cell discharge when a given power spectrum is provided.
Emerging technologies in the field of electrified propulsion systems offer a promising solution to reduce the dependence on fossil fuels and improve efficiency. However, the design of high-power density electric machines introduces new challenges, including limited passive cooling potential and the issue of the weight of electric motors. To address these challenges, this paper considers analysis and design methods for high torque-to-weight ratio axial flux motors. A magnetic equivalent circuit model coupled with a lumped parameter thermal network is developed for design space exploration and optimization. This inexpensive analytical model predicts the performance of a single-stator dual-rotor axial flux motor based on geometry, loading condition, and slot and pole pair combination. To enable comparisons against real-world data, the optimization study was demonstrated using the hover mission requirements from the Research Aircraft for eVTOL Enabling techNologies (RAVEN) vehicle to minimize the mass of the motor. In tandem with the analytical model, a higher-fidelity finite element model was also developed, and good agreement between predicted power and efficiency was demonstrated across a range of axial flux motor designs. The lightest weight design that satisfied the hover mission requirements was the 12 pole pair 27 slot (12PP 27S) configuration with a fixed weight of 9.28 kg. The analytic model undersized the output power of the electric motor by approximately 9% across a range of slot and pole pair combinations.
Deep learning (DL) models have attained state-of-the-art performance in numerous fields. Nevertheless, for certain real-world applications, existing models encounter diverse challenges, ranging from a lack of generability to new data to issues of scalability and overfitting. In this context, integrating information extracted from different modalities holds promise as a potential solution to alleviate these challenges. This paper introduces MAVEN, a multimodal deep-learning framework for long-range atmospheric visibility estimation. Using multimodal deep learning, MAVEN fuses various modalities to estimate long-range atmospheric visibility. These modalities include RGB imagery, Edge Map, Entropy Map, Depth Map, and Normal Surface Map. Results show that in contrast to single-modality RGB, which achieves only 87.92% accuracy, multimodal deep learning models achieve an accuracy of over 96%. This significant improvement highlights the potential of multimodal approaches to enhance the accuracy and reliability of atmospheric visibility estimation, which is crucial for improving safety in applications such as aviation, maritime navigation, and autonomous vehicles. By addressing challenges such as data variability, environmental factors, and the inherent complexity of atmospheric conditions, MAVEN contributes to more reliable and robust visibility estimation systems, thereby enhancing safety and operational efficiency in critical environments.
This paper presents an efficient numerical framework for prediction of broadband noise scattering through time-domain synthesis and propagation. For efficient scattering of broadband noise sources, a time-domain boundary element method is applied to propagate all frequencies together in a single computation. To obtain a time-resolved incident field without high-fidelity aerodynamic simulation, a stochastic broadband noise synthesis method is developed based on a semi-analytical airfoil broadband noise modeling approach. The framework is validated for airfoil trailing edge noise prediction, and the correspondence of the time-domain broadband noise synthesis method to existing semi-analytical broadband noise models is demonstrated. The framework is then applied to predict fuselage scattering of rotor tonal and broadband noise for a full-size urban air mobility concept vehicle. Significant differences are observed between the scattering effects in the tonal and broadband contributions.
The certification of highly integrated electric Vertical Take-Off and Landing (eVTOL) aircraft requires a rigorous bridge between simulation and flight reality. This paper presents the Joby Disturbance Generator, a high-integrity software framework natively integrated into the aircraft flight control system. The system utilizes a deterministic state machine to inject a library of signals, ranging from standard doublets and chirps to complex waveforms, directly into internal control loops. Applications include frequency sweeps for stability margin extraction and structural mode identification, time-domain inputs for handling qualities assessment, synthetic fault injection for redundancy management verification, and precise loads model validation. The system continuously monitors vehicle health, automatically aborting test points upon detecting genuine failures. For loads validation, it coordinates temporary relaxation of flight envelope protections with precise disturbance injection. This methodology accelerates development by shifting risk from flight execution to software verification, providing deterministic, data-driven evidence for certification. Flight test results demonstrating these capabilities are presented.
A technique for rapidly designing roughness tolerant low drag airfoils has been developed. Airfoils of varying thickness to chord ratio, ranging from 10% to 22% have been designed. A target pressure distribution is specified by the designer for a notional lift coefficient, Reynolds number, and Mach number. The specified pressure distribution is first analyzed using classical integral boundary layer analyses and empirical transition criteria for smooth and rough airfoils to ensure laminar flow over much of the airfoil under design conditions. The resulting airfoil is subsequently analyzed under natural transition, and forced transition caused by the tripping of the boundary layer due to roughness near the leading edge. It is found that the present approach performs well for a broad range of lift coefficients. An in-house propeller design and analysis tool has been used to examine the impact of the low drag airfoil on the pusher propeller performance designed for a fixed wing UAV drone configuration.
An experimental investigation was conducted to explore the loads, acoustics, and tip vortex trajectories of coaxial counter-rotating (CCR) rotor with unequal upper and lower radii. The upper and lower rotor radii were tested both at the nominal radius of 1.108 m, and also with a lower rotor radius of 90% nominal radius, for a constant rotor speed of 1180 RPM and a constant inter-rotor spacing of z/R = 0.108. Rotors were torque balanced and tested for a range of upper rotor collective pitch from -2◦ to 10◦ . The power required for both CCR systems was within 0.9% for most trim conditions, and equal thrust was produced at upper rotor collectives of 6◦ and 8◦ (within 1.0%). At low loading conditions the unequal radii configuration produced more thrust for the same power due to a reduction in profile drag. The overall sound pressure level (OASPL) was lower for the CCR rotor with shortened lower rotor blades at all angles of elevation. Larger reductions in A-weighted OASPL(A) were observed, due to a larger contribution of broadband noise to the total OASPL(A).
A comprehensive numerical study was conducted to reduce helicopter rotor hub vibratory loads and fuselage vibrations using the Higher Harmonic Control (HHC) technique. A CAMRAD II model of a medium utility helicopter was developed for aeromechanical simulation, and a linear system model representing both hub vibratory load and fuselage vibration characteristics was identified offline. Optimal control inputs were then computed to minimize vibration responses under different weightings on hub vibratory load and fuselage vibration in the objective function. The predicted performance was verified through CAMRAD II simulations. Additionally, a closed-loop HHC system incorporating actuator amplitude limitations was investigated. A control algorithm regulated actuator amplitudes while maintaining phase consistency, dynamically adjusting control inputs after each iteration. The results demonstrate that the amplitude-limited closed-loop control limits excessive pitch link loads while maintaining effective vibration suppression, thereby maintaining structural safety and ensuring practical feasibility for real-world helicopter applications.
This paper details comprehensive analysis modeling and analysis supporting the development of the Research Aircraft for eVTOL Enabling techNologies (RAVEN). An isolated rotor model was developed in CAMRAD II, and predictions of rotor performance and rotor aeroelastic stability were generated. The rotor stability predictions are part of assessing airworthiness of the RAVEN vehicle. The performance predictions were used to calibrate the surrogate model for the NASA Design of Rotorcraft (NDARC).
This paper presents a comprehensive evaluation of data-driven machine learning (ML) frameworks for the estimation of critical operational parameters, gross weight (GW), longitudinal center-of-gravity (CGx ), and airspeed (Ux ) for a UAM-scale Lift plus Cruise eVTOL aircraft. Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and Support Vector Machines (SVM) are compared for their ability to track these dynamic parameters across both low-speed rotor-borne and high-speed wing-borne flight regimes. The models are rigorously tested on steady-state clean data and stochastic atmospheric turbulence data sets to assess performance trade-offs between computational cost, noise robustness, and predictive accuracy. Results demonstrate that GPR consistently achieves the highest accuracy on clean data, particularly for GW and CGx estimation, though it exhibits the highest sensitivity to stochastic noise. Conversely, SVM demonstrates the greatest relative robustness under turbulent conditions and superior computational efficiency, identifying it as a practical candidate for resource-constrained onboard flight computers. Furthermore, a dynamic continuous-time analysis reveals a critical trade-off between responsiveness and accuracy. Instantaneous predictions are shown to suffer from severe transient error spikes during maneuvers, whereas a moving average filtering strategy effectively mitigates these errors at the cost of response latency. These analyses demonstrate the feasibility of ML-based parameter estimation for UAM operations and highlight the necessity of adaptive temporal filtering to balance agility with resilience in turbulent environments.
During conceptual presizing of electric vertical takeoff and landing aircraft, it is critically important to predict the weight and efficiency of powertrain subsystems as accurately as possible, since these components usually represent a large fraction of the vehicle design gross weight. This paper compares the electric powertrain weight and efficiency models implemented in three aircraft conceptual design and performance estimation tools: HYDRA, NDARC, and CREATION. Using a common lift plus cruise vehicle configuration and mission, this paper investigates the effects of motor, electronic speed controller, battery, and other powertrain subsystem models on vehicle sizing. Results for both operating conditions with all rotors operational and cases accounting for the failure of one or two lifting rotors are presented. Results show that differences in powertrain subsystem models - particularly in motor scaling laws and battery sizing assumptions—lead to large variations in vehicle design gross weight, an effect that is exacerbated when sizing for motor/rotor failures. While HYDRA and CREATION predicted similar battery system weights for all cases, NDARC estimated lower battery weights but higher motor/ESC weights at lower power and torque, with convergence closer to the other two codes at higher power and torque requirements. This paper presents a comparison of methodologies from modern conceptual presizing codes, and proposes areas of improvement where full vehicle sizing accuracy can be improved.
This paper considers the opportunities and challenges of supporting Disaster Relief and Emergency Response (DRER) missions employing new aerial vehicle and systems concepts. This paper is a broad survey of the possible aerial-vehicle-assisted approaches to aid in DRER missions. The intent of this paper is to elevate this DRER mission application domain as a critical area of investigation for rotorcraft, robotics, intelligent systems, and other research. Current work is primarily focused on assessing air space integration challenges for Commercial Off-The-Shelf (COTS) aerial platforms (typically small multirotor drones and/or small fixed-wing uncrewed aerial vehicles (UAVs)) in disasters such as earthquakes and wildfires. Though this is an important area of investigation, truly efficient and effective DRER systems and response efforts will not be possible without the development of novel aircraft, technologies, and system architectures of COTS DRER drones/UAVs. This paper seeks to address that knowledge gap and encourage government, academia, and industry to pursue DRER mission research.
A 4-rotor uninhabited air vehicle is described, with a primary mission of supporting personnel fighting wildfires. The paper demonstrates the use of technical design tools for a small Uninhabited Aircraft System (sUAS). A description of the design process is provided, including developing requirements, identifying constraints, the software tools employed, and examination of results. The vehicle is capable of delivering more than 20 kg of supplies to a delivery point 10 nm away while penetrating 30 kt winds. The sized vehicle is transportable in a medium-duty pickup truck and can be picked up and moved for ground handling by one or two individuals. The vehicle information will be publicly released for NDARC software users. Future work will examine other requirements, such as maneuvering and gust rejection.
This paper discusses the design of a 2000-lb manned eVTOL aircraft propelled by a novel cycloidal rotor propulsion system. To systematically evaluate the performance of the proposed configuration, a coupled trim model was developed to quantitatively evaluate the performance of the configuration across a range of forward flight speeds. The trim framework integrates an efficient physics-guided neural-network-based aerodynamic model for cycloidal rotor performance with a vehicle-level dynamic response model. This framework is used to conduct a systematic parametric study to identify key cycloidal rotor and airframe design parameters. The selected configuration is verified using high-fidelity CFD simulations, and a detailed structural design, powertrain design, and CAD model of the aircraft is developed. In addition to CFD validation, the proposed cycloidal rotor underwent structural optimization to confirm the validity of such a concept at this scale. The results demonstrate that the cycloidal rotors provide a viable propulsion alternative for eVTOL aircraft with strong potential to overcome limitations of existing configurations.
Forward flight rotorcraft analyses typically require time-marching aeroelastic trim of coupled rotor-airframe models, which is expensive for repeated evaluations. This paper presents a non-intrusive model-order reduction framework based on Dynamic Mode Decomposition with control (DMDc) identified from snapshot data. A POD projection reduces the state dimension; the DMDc operators are identified in the reduced coordinates and used for fast time-marching. Two sequential maps are constructed: DMDc-A reconstructs aeroelastic sectional airloads from low-cost rigid-blade airloads, and DMDc-S predicts coupled deformation, including blade and airframe degrees of freedom (DOFs), from the reconstructed airloads. The method is demonstrated for the XV-15 airplane mode configuration using a stick airframe model and a coupled rotor-airframe solver. Over 160-400 knots, it is found that the surrogate reproduces blade airloads and structural deformation of blade and airframe.
Dimensional reduction of data can be accomplished through various methods and has applications critical to machine learning and surrogate modeling. Within the rotorcraft community, leveraging these techniques allows for improved rotor parameterization and performance prediction. Machine learning models generally perform faster and better with lower input dimensions, so long as all necessary information is retained, making appropriate dimension reduction paramount. Data can also be arranged in a one-dimensional (concatenated/stacked) or two-dimensional arrays to take advantage of function correlations, and this arrangement may allow for greater reduction at lower reconstruction costs. Principal Component Analysis with a stacked input shape proves to be the most effective reduction method considered, with reconstruction accuracy being validated though a suite of mid-fidelity aerodynamic simulations. A blade geometry defined using 204 original parameters can be fully described using just 10 component parameters with the reconstructed blade maintaining performance figures within 1% of the original blade.
This study investigates the performance and vibration characteristics of representative lift rotors for a notional lift+cruise electric vertical takeoff and landing (eVTOL) configuration. As new eVTOL concepts continue to be developed and others progress towards FAA certification, it is crucial to understand the performance and vibratory considerations associated with different lift rotor design choices, including the number of blades and the method of thrust control (e.g., variable blade pitch/fixed RPM vs. fixed blade pitch/variable RPM). The NASA Revolutionary Vertical Lift Technology (RVLT) Lift+Cruise configuration was chosen as the baseline vehicle for this analysis (Ref 1). The investigation includes the evaluation of multiple lift rotors with 2-, 3-, and 4-bladed configurations as well as variable- vs. fixed-pitch designs. Both isolated rotor and full vehicle simulations were assessed to demonstrate some of the design variables applicable to the full vehicle performance and vibratory content. Industry-standard rotorcraft comprehensive analysis software, the Rotorcraft Comprehensive Analysis System (RCAS) (Ref 3), was used to evaluate and compare each configuration for performance and vibratory loads at key points in the rotors and in the fuselage
Previous researchers developed equations to model the induced flow on a 2D airfoil in the finite-state as opposed to the closed-form. Those models, however, were limited in that they could not handle an oscillating free stream that became negative. Recently, a new model was developed to include a single factor to carry the effects of the free stream changing signs. In developing this model, a Floquet instability was discovered at the instant when the flow changes direction. The effect of the instability grows with increasing number of oscillations of the sign of the free stream. The effects can be limited depending on the parameters of the flow. In this paper, the previous 2D model is amended to include a term that considers the effects of the induced flow from all previous vorticity segments that have been generated from each oscillation of the flow. This paper details the beginnings of the testing on the stability limits of the theory, based on changing the parameters of the free stream, airfoil, and timing. It is the intention of this research to further investigate the limits of this model in reversing flow in hopes of using the lessons learned to extend 3D finite-state models that are currently incapable of handling cases where the sign of the free-stream velocity changes as a result of the rotor reentering its own wake such as when a helicopter or quadcopter quickly descends after ascending to avoid an obstacle.
Urban Air Mobility (UAM) concepts require multidisciplinary analyses across multiple modes of operation and often involve discrete architectural differences such as propulsion type, rotor configuration, and mission context. Existing optimization and workflow frameworks support continuous design variables but provide limited mechanisms for handling discrete variants, multi-modal vehicle definitions, and vehicle management for UAM vehicles. This paper presents uam4x, an open-source Python framework that addresses these challenges through a structured problem definition representation, a plugin-based execution engine, integrated version control, and a function-based branching script mechanism for constructing analysis scenarios. The framework provides integration of existing tools including Open Vehicle Sketch Pad (OpenVSP), NASA Design and Analysis of Rotorcraft (NDARC), M4 Structures Studio (M4SS), and Intelligent Cross Section Generator (IXGEN) through unified plugin interfaces. Parameter sweeps, nested analyses, and optimization via OpenMDAO are supported within the same architecture. This paper also presents demonstrations that were created to illustrate the various capabilities and integration efforts of the framework.
Propeller driven rotors utilize propellers on the main rotor blade to spin the rotor. Past research efforts have highlighted dynamic issues that arise from the rotor-propeller Coriolis interaction. For this paper, a comprehensive multi-body analysis methodology, called Elastic Rotorcraft Analysis (ERA), was applied to various propeller driven rotor datasets. The focus of the modeling effort was on propeller driven rotor twirl phenomenon, which arises from rotor-propeller inertial couplings interacting with rotor blade modes. After describing the phenomenon, the paper is split into two parts: validations and predictions. In Part I of the paper, the ERA propeller driven rotor model was validated using three datasets: (i) a propeller flapping vacuum chamber experiment, (ii) a propeller/rotor loads vacuum chamber experiment, and (iii) a propeller driven rotor hover experiment. The ERA model showed good agreement with the data, and captured the important rotor-propeller Coriolis interaction. In Part II of the paper, predictions for several propeller driven rotor configurations were generated and analyzed. Loads were computed for an isolated propeller and are compared to propeller loads during propeller driven rotor operation. The analysis showed that operating the propeller on the rotor blade introduces significant inertial loads on the propeller. Finally, propeller placement along the main rotor blade span was investigated. The results of the present study agree with earlier research, which showed placing the propeller at the midspan location reduced the electrical power coefficient by nearly half compared to a tip mounted propeller.
This paper presents the design, development, and subscale flight testing of an optionally-autonomous lift-plus-cruise (LPC) eVTOL aircraft for emergency response missions that bridges the gap between existing aerial capabilities and the needs of first responders. A 4+1 LPC configuration consisting of four vertical lift propellers and a single pusher propeller was selected to balance hover performance and cruise efficiency. The vehicle is sized around a 600 lbs gross takeoff weight with a 125 lbs payload capacity. VTOL and Pusher propeller blades were optimized using parametric studies, resulting in a high Figure of Merit and propulsive efficiency. Trim analysis demonstrates efficient hover to cruise transition, lift-to-drag ratios of 10-11 between 70-90 knots, and propulsive efficiency exceeding 0.9 at the cruise speed of 100 knots. The subscale configuration utilized a simulation framework for trim and optimization of flight control laws, which were subsequently implemented on a 1/3-scale subscale demonstrator. Subscale flight tests showed stable hover and robust trajectory tracking under wind disturbances throughout the flight envelope, which demonstrates the feasibility of the proposed LPC architecture.
This paper presents the characterization of a new 5.92 m × 8.51 m × 3.05 m recirculation delayed anechoic chamber (RDAC) according to the guidance of ISO 3745 free-field testing and an experimental study on the effects of RPM variation on rotorcraft unsteady aerodynamic loading and broadband noise. The chamber is shown to have a cutoff frequency of 250 Hz. UCD-Quietfly was used to predict the propeller noise of constant RPM. The loading and broadband noise of a 16 × 5.4 inches rotor were obtained while operating under constant RPM, impulse, step, linear, and sinusoidal RPM variation, as well as a simulated unmanned aerial vehicle (UAV) flight path and battery-powered operation. The results demonstrated a strong correlation between broadband noise and RPM across all cases, while abrupt or periodic RPM changes introduced larger unsteady aerodynamic loading and elevated broadband noise not only during the cycles but also after the rotor returned to a constant RPM. Linearly increasing and decreasing RPM were found to be ideal for smoother thrust transitions and lower overall sound pressure levels (OASPL). The battery-powered operation introduced additional RPM fluctuations that resulted in OASPL variations exceeding 6 dB. These findings highlight the importance of RPM control strategies in mitigating rotorcraft noise and provide the correlations of the varying rotational speed and the unsteady loading noise.
This paper presents the design and validation of the Rotor Optimization for the Advancement of Mars eXploration (ROAMX) Hover Test Stand, a vacuum compatible stand developed to measure rotor performance under Mars aerodynamic conditions. The stand integrates a high-speed water-cooled motor, a variable pitch hub, and a structural safety system capable of withstanding the high loads resulting from rotor blade loss while enabling continued experimental operations. The stand also maintains the measurement fidelity required for thrust and torque characterization at low Reynolds number. Aerodynamic blockage was limited to less than 20% through geometric constraints on the stand architecture. Calibration and sensor procedures ensured correct load transfer through the intended structural load path and also verified sensor accuracy. Test Entry 1 demonstrated successful test stand performance and testing of experimental blades. The stand spun blades to 4,000 Revolutions per Minute (RPM) for Test Entry 1, but the motor is capable of continuous operation at 5,900 RPM. The ROAMX Hover Test Stand provides a reusable experimental capability that enables high-fidelity evaluation of Mars rotor designs.
This paper presents the investigation of experimental data belonging to main rotor loads during Never-Exceed-Speed demonstration of T625 Gökbey helicopter. Load data from the critical flight conditions in the VVNNNN envelope including cold-weather testing are collected. Maximum advancing tip Mach number demonstration, power-on and power-off flight conditions are investigated in terms of pitch link loads and blade loads. Blade loads including flapwise and chordwise bending moments, torsional moments and pitch link loads are examined to assess any divergence due to compressibility effects and the onset of stall. Load trends that are correlated with the tip Mach number are isolated from the effect of increasing dynamic pressure. Compressibility effects are observed to be the most dominant factor on the blade torsional moment and pitch link loads in advancing blade. The retreating blade stall phenomenon is apparent cases with a high advance ratio and mainly leads to dynamic stall cycles on the retreating blade, resulting in torsional moments and pitch link loads. Experimental results are compared with blade-resolved Unsteady Reynolds-Averaged Navier-Stokes simulations.
NASA is conducting investigations in Advanced Air Mobility (AAM) aircraft and operations, including the development of Urban Air Mobility (UAM) aircraft designs that can be used to focus and guide research activities in support of AAM. This report is an investigation of the impact of technology and mission variations on several of the NASA AAM concept aircraft: quadrotor, quiet single main rotor, side-by-side, and tiltrotor configurations, with turboshaft and electric propulsion variants for each. First, the mission and aircraft models of the baseline designs were reassessed and updated, including rotor geometry optimization, update of the rotor performance models, and disk loading optimization. For these eight designs, technology and mission excursions were performed. Relative to the calibration cases that can be considered examples of good design practice, the impact of the weight technology factors is significant. For the electric aircraft, there is a very large impact of battery specific energy (Wh/kg), and correspondingly a very large impact of mission range. The vision of Advanced Air Mobility is driven by missions that will enable new transportation capabilities. Hence it is appropriate to compare Concept Vehicles of different lift and propulsive architectures, all designed to accomplish the same UAM mission. It is also useful however to consider specific missions that can take advantage of the strengths of individual aircraft configurations. So alternate designs were also developed for the concept vehicles: for turboshaft aircraft, longer unrefueled range, including faster cruise speed for the tiltrotor; for electric aircraft, shorter range and more realistic battery weight.
This paper presents a multi-scale sizing and optimization framework for a vertical take-off and landing (VTOL) aircraft designed for disaster-relief operations, addressing both conceptual full-scale design and feasibility analysis of a subscale prototype. A tandem tilt-wing configuration with eight distributed propulsors is considered in the context of the GoAero Stage 2 mission. The full-scale aircraft employs a hybrid-electric propulsion architecture centered around a Rotax 916 iS engine, with propulsion and energy system components sized to satisfy point-performance, mission, and dynamic maneuvering requirements. The aircraft is sized and optimized using the Parametric Energy-Based Aircraft Configuration Evaluator (PEACE), which integrates aero-propulsive modeling, energy-based mission analysis, and power-flow-based propulsion sizing. Hover maneuvering constraints based on ADS-33E-PRF are explicitly enforced and are shown to be a dominant driver of motor and propulsion system sizing. Batteries are sized to support power-intensive off-nominal conditions, including engine-out vertical climb. A genetic algorithm is used to solve optimization problems involving continuous and discrete design variables, with maximum takeoff mass and range as multiple objectives. For the full-scale design, stall speed is identified as the dominant active constraint in the optimal design. The optimized configuration is subsequently scaled down by 35% to obtain a subscale prototype. In contrast to full-scale rubber-propulsion sizing, the subscale design adopts a fixed-propulsion sizing approach using commercial off-the-shelf components. The resulting design satisfies all geometric, performance, stability, and payload constraints while remaining within regulatory mass limits of 55 lbs.
This study examines the capability of medium-fidelity comprehensive analysis models to predict the acoustics for manned and unmanned rotorcraft configurations. Using the automated tool NDARC2RCAS developed at DEVCOM Army Research Laboratory, multiple configurations including a single main rotor, tilt rotor, coaxial and pusher, quadcopter, and hexacopter are evaluated at various mission segments including hover, advancing climb, and forward flight. Each configuration and condition is evaluated using a range of aerodynamic models from lower to higher fidelity, including uniform inflow, dynamic inflow, prescribed wake, free wake, and viscous vortex particle method (VVPM). These evaluations are then used with another automated tool, RCAS Acoustics, to predict noise on a Voronoi observer sphere. A comparison of the results for the single main showed good agreement between all of the aerodynamic models except VVPM. For the tilt rotor in forward flight, the higher-fidelity models produced changes in rotor loads due to the interaction with the wing. With prescribed and free wake models, this change in load is sharp and causes noise increases of up to 40 dB in front of and behind the vehicle, while the VVPM model produced a smoother change that results in a smaller, 20 dB increase in noise. The quadcopter and hexacopter show similar in-plane noise levels for all models, with alternating cancellation and amplification patterns due to rotor phasing, while out-of-plane noise is increased on the hexacopter when using the higher fidelity models.
The induced and profile power of a hovering rotor was evaluated using experimental and computational methods. Momentum theory principles were coupled with experimental measurements over a range of thrust conditions to characterize the induced and profile power consumption at low Reynolds number conditions ∼ 105. An empirical induced power factor, κi, was extracted to quantify the non-ideal losses. Results show that these losses increase as the Reynolds number reduces, and nearly twice the power is required at Retip = 0.27×105 than the ideal momentum theory prediction. These results were compared with high-fidelity computational fluid dynamics simulations using the partial-pressure field (PPF) force/power decomposition to extract the induced and profile power contributions of the rotor. The PPF method decomposes the static pressure field of a numerical Reynolds-averaged Navier-Stokes solution into Euler and dissipative partial pressure fields. Simulations were performed across a range of thrust conditions, from which the induced power factor and profile drag coefficient,Cd0 , were computed for each simulation from the extracted power contributors.
Achieving noise reduction in rotorcraft requires an analysis of various design parameters and flight conditions. However, high-fidelity methods are computationally expensive. To overcome this limitation, reduced order model (ROM)-based surrogate models have been applied to aerodynamics and aeroacoustics prediction. This study proposes a ROM-based surrogate model employing a variational autoencoder (VAE) to predict rotor aerodynamic loads and associated noise. Train and test datasets were generated using reformulated vortex particle method across a wide range of flight conditions. The proposed framework was applied to a single rotor, and its performance was evaluated qualitatively and quantitively in comparison with proper orthogonal decomposition (POD)-based surrogate model. The results show that VAE-based model consistently outperformed the POD model in noise prediction. These results demonstrate that the proposed framework enables accurate rotor noise prediction under various flight conditions and provides a promising approach for low-noise rotorcraft design and operational planning.
This paper discusses uncrewed aerial vehicles (UAVs) that can have additional applications beyond their respective civilian, industry, or military applications. The increasing popular electric UAVs in advanced air mobility (AAM) and urban air mobility (UAM) networks can be utilized to increase the efficiency and impact of emergency response in both urban and remote settings. The paper will explore the design considerations and requirements for these dual-use vehicles for specific public good missions, while presenting a survey of additional public good missions that could significantly benefit from additional ready-to-go drones. Additionally, this paper aims to explore the logistics required to implement a system for incorporating civilian, industrial, and military drones into a reserve fleet for emergency and disaster relief efforts.
A 4.75-ft diameter hingeless hub proprotor model was wind tunnel tested up to the very high speeds of 205 knots, loosely corresponding to 480 knots full-scale, with parametric variations in blades, wing spar, and pylon center of gravity. Testing revealed that a gimballed-hub configuration that reached whirl flutter at 160 knots was completely stabilized when converted to a hingeless hub – using identical blades, span, and pylon. While the gimballed-hub model encountered whirl flutter at 160 knots, the hingeless-hub configuration remained stable throughout the entire test envelope up to 205 knots. The key conclusions are that a hingeless hub can eliminate whirl flutter, and that the most stable configuration is a swept-tip blade hingeless-hub rotor with the pylon center of gravity aft of the wing spar.
Vertical Take-Off and Landing (VTOL) aircraft introduce complex monitoring challenges due to distributed propulsion, lightweight structures, and variable operating conditions. This paper presents advanced Frequency and Orders domain techniques that repurpose existing flight control, propulsion, and structural sensor data to enhance observability without additional instrumentation. By transforming vibration, acoustic, and electrical signals into frequency and order domains, the approach enables detection of harmonics, resonance, and fault signatures tied to rotor dynamics, supporting adaptive control and predictive maintenance. Beyond rotor systems, these techniques are equally effective for monitoring electric motor health, gearbox wear, bearing degradation, and structural coupling effects in composite airframes. They also provide insight into power electronics and thermal management systems by identifying spectral anomalies linked to electrical imbalance or cooling inefficiencies. Aggregated fleet data strengthens prognostic capabilities, enabling early detection of systemic issues and trend analysis. Applications include mitigating ground resonance and modal instabilities, as well as improving reliability of propulsion and structural subsystems. Integration into avionics emphasizes computational efficiency, scalability, and compliance with standards such as DO-160 [1], DO-178 [2], ARP4761 [3] and ARP4764 [4]. Simulation and bench testing confirm feasibility, demonstrating potential to enhance safety, reliability, and lifecycle cost for next-generation urban air mobility platforms.
Winged electric vertical takeoff and landing (eVTOL) aircraft commonly employ multiple lift rotors mounted on underwing booms to enable efficient cruise while retaining vertical flight capabilities, making resilience to rotor failure a critical consideration in design and certification. While prior studies have primarily assessed fault tolerance through control feasibility and allocation strategies, the physical consequences of rotor failure on individual motor loading and overall aircraft power requirements remain relatively unexplored. This paper investigates the effects of single-rotor failure on an eVTOL aircraft with eight rotors on four underwing booms in hover using a physics-based comprehensive rotorcraft model. Three rotor spin configurations are examined, including the baseline NASA Lift plus Cruise arrangement and two alternate configurations inspired by emerging industry designs. Post-failure trim solutions are obtained using both power-optimal and intuitive paired-rotor shutdown strategies. Results quantify changes in rotor thrust, torque, and power, revealing that rotor spin configuration strongly influences load redistribution and peak motor demands despite similar increases in total aircraft power. These findings highlight the importance of incorporating physical motor loading considerations alongside control feasibility in fault-tolerant eVTOL design.
The paper discusses the design and high-fidelity flight dynamics modeling of a 13-lb lift-plus-cruise unmanned aerial vehicle (UAV) using Rotorcraft Comprehensive Analysis System (RCAS) in order to (1) better understand its physics of flight during a wide range of maneuvers, and (2) provide insight into the fidelity needed to achieve quantitative accuracy when compared to flight test data. Wind tunnel tests of the full aircraft were performed at a 65% scale to provide lookup tables for the flight dynamics model. Flight test data was collected while providing high control inputs to excite a variety of dynamic states in hovering and cruising modes to systematically validate the physics model. Near quantitative agreement was observed between the model predictions and test data during hover; however, the predictions began to disagree at higher forward cruising speeds. To address the discrepancy between the prediction and experiment, the flight dynamics model was improved by learning a correction from flight test data using a neural network. This hybrid physics plus data-driven approach reduced the error between the physics model and experiment by 74% and only needing 12 minutes of flight data for training. This hybrid methodology presents an alternate approach to high fidelity modeling which only needs a relatively small amount of flight test data.
The Rotor Optimization for the Advancement of Mars eXploration (ROAMX) project has demonstrated that rotor designs optimized for the Mars aerodynamic regime can provide substantial improvements in aerodynamic efficiency relative to heritage designs. This paper evaluates the vehicle-level performance implications of these improvements using the NASA Design and Analysis of Rotorcraft (NDARC) tool. Performance predictions for Ingenuity-class and Mars Science Helicopter (MSH)-class rotorcraft are generated using ROAMX rotor aerodynamic inputs and are compared against a configurations using the Ingenuity rotor. Parametric studies are conducted to investigate the trade between increasing payload mass and resulting changes in vehicle range and hover time, including the effects of rotor solidity and rotor type. The results show that ROAMX rotor designs enable significant increases in payload capability and operational range across both vehicle classes. These findings demonstrate how ROAMX rotor performance gains translate directly into enhanced mission capability at the vehicle level and provide a quantitative foundation for future Mars rotorcraft designs.
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