Browse Topic: Vertical take-off and landing (VTOL)
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.
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.
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 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.
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.
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.
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.
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.
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.
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.
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.
Fault detection in autonomous VTOL aircraft is critical because even minor degradations can quickly destabilize multirotor vehicles in safety-critical environments. However, real-flight fault detection remains challenging due to sensor noise, environmental disturbances, and the nonlinear aeromechanics of multirotor platforms. This study proposes a comprehensive machine-learning framework for rotor fault detection, isolation, and severity prediction using real flight data. A convolutional neural network (CNN) architecture is developed to learn spatio-temporal patterns from multivariate flight dynamics, enabling direct inference of both the faulty rotor and its damage level. The framework is first validated using simulated data generated by our in-house flight dynamic model. Next, to verify the framework using real flight data, a hexcopter was designed, fabricated and flight tested for both nominal and faulty cases by introducing controlled blade-tip breakage. The trained model achieves rotor-wise fault classification accuracies above 99% and sample-wise severity estimation accuracy of 96% within a ±1% tolerance in experimental data, demonstrating strong generalization and supporting real-time health monitoring for autonomous VTOL systems.
Advanced Air Mobility (AAM) air vehicles with electric vertical takeoff and landing capability come in a wide variety of configurations and are often equipped with many lift and propulsion devices. Lift rotors of AAM configurations often have high disk loading which produce strong downwash and outwash (DWOW) at low speed and hover close to the ground. Recent outwash surveys of AAM aircraft have confirmed the presence of strong DWOW produced by various aircraft configurations [1]. The capability to predict the DWOW characteristics produced by these aircraft can aid in deriving requirements for vertiport design, ground operation, and landing/takeoff flight safety procedures. This paper investigates the sensitivity of selected aircraft design and operation parameters on the overall DWOW. This includes rotor horizontal and vertical separation distances, and near ground flight maneuvers. The focus in this paper is on the DWOW profile near the aircraft to help inform design and operational decisions. Moreover, transient approach/departure simulation for an AAM aircraft are conducted for an understanding of the complex flow field during unsteady flight maneuvers. The Viscous Vortex Particle Method (VVPM) is used to estimate the aircraft DWOW characteristics.
The current effort presents novel investigations of rotor-wake–surface interactions for the Dragonfly lander, NASA's rotorcraft lander to explore Titan. The numerical framework couples unsteady RANS with blade-element and virtual disk rotor models and a coupled Lagrangian particle tracking method to examine rotor–ground interactions and brownout. Simulations span a range of complexity, from isolated rotor benchmarks and rotor pairs to full eight-rotor configurations without a fuselage and the eight-rotor configuration with a simplified Dragonfly fuselage. To quantify model fidelity and near-ground shear, blade-resolved simulations of the isolated rotor are performed using Spalart–Allmaras and Reynolds Stress turbulence models with vorticity confinement, demonstrating that virtual blade models under-predict tip-vortex strength and local inflow distortion but reproduce wall shear reasonably well, whereas blade-resolved RSM solutions yield higher peak shear levels relevant to brownout prediction. These findings improve understanding of planetary rotorcraft aeromechanics and sediment transport in ground-effect while supporting ongoing efforts to assess environmental risks for Dragonfly operations and inform multi-rotor VTOL design for terrestrial applications.
This paper presents a reinforcement learning (RL)–based outer-loop controller for quadrotor UAV trajectory tracking and its real-world experimental validation. The proposed approach integrates RL into a standard cascaded flight-control architecture by replacing the conventional PID outer loop while retaining the onboard attitude and body-rate PID controllers. This hierarchical design preserves reliable inner-loop stabilization while leveraging RL to address nonlinear dynamics, coupling effects, and modeling uncertainty in translational motion. The controller is trained entirely in a physics-based simulation using Proximal Policy Optimization (PPO) and transferred directly to a Crazyflie quadrotor without additional tuning. Performance is evaluated through real-world figure-8 trajectory tracking experiments with varying time scales to impose increasing dynamic demands. Compared to a conventional PID outer-loop controller operating under identical conditions, the RL-based controller consistently reduces effective phase delay and achieves lower position and velocity tracking errors, particularly for aggressive trajectories. The results demonstrate robust sim-to-real transfer and highlight the potential of learning-based outer-loop control as a drop-in enhancement to classical quadrotor flight controllers.
This paper presents an initial handling qualities analysis of an Electric Vertical Take-Off and Landing (eVTOL) hexacopter. The analysis uses the Distributed Electric Propulsion Simulation (DEPSim), developed by Penn State University (PSU) and the Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM), developed by Continuum Dynamics, Inc. (CDI). The study focuses on evaluating a generic AAM hexacopter performing Handling Qualities Task Elements (HQTE) as defined by the DOT / FAA. A trajectory controller was developed to enable simulation of prescribed flight paths, allowing automated simulation of four HQTEs: Heliport Approach, Hovering Turn and Hold, Pirouette, Lateral Reposition and Hold. Design modifications incorporating lateral mast tilt and Direct Side Force Control (DSFC) were implemented to enhance yaw control and ride qualities. Piloted simulations were conducted at the PSU rotorcraft flight simulation facility using DEPSim, employing an Attitude Command Attitude Hold (ACAH) architecture with mode switching to Translational Rate Command / Position Hold (TRC / PH) and TRC plus DSFC modes. Two of the four HQTEs were tested in piloted simulations. Though formal ratings were not collected at this time, pilot commands and performance indicated that TRC / PH and TRC plus DSFC modes enhance handling qualities over ACAH mode. The DSFC control law was found to have substantially reduced roll attitude, which could potentially enhance visual cueing, pilot comfort, and pilot-perceived handling qualities.
This study presents a comprehensive analysis of single-rotor failure tolerance for a classical octocopter configuration, examining both hover and forward flight at the best range speed. Using a state-of-the-art eVTOL comprehensive analysis to retrim the octocopter post-failure, the redistribution of rotor thrust, torque, and power following individual rotor failures was quantified, along with resulting aircraft-level power penalties. In hover, orthogonal rotors to the failed rotor provide primary lift compensation, the opposing rotor operates mostly unchanged, and the four opposite spinning rotors primarily provide pitch/roll moment compensation. This results in a total aircraft level power increase of approximately 10.4%, roughly half that of comparable hexacopters. In forward flight, at best range cruise speed, load redistributions were again calculated for various individual rotor failures. In the worst case, a maximum individual rotor torque increase of 62% and power increase of 108% was observed, while total aircraft power requirements increased between 7-12%. These results demonstrate the fault-tolerant capabilities of octocopters and provide practical guidance for propulsion system sizing, energy management, and failure-case assessment on classical octocopters.
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 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.
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 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 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
Recent flight tests and simulations have suggested that the outwash from eVTOL air-taxis could be larger than conventional helicopters of equal weight and thus pose greater safety issues for their operation than previously anticipated. This has prompted interest in the analytical and experimental study of the aerodynamics related to multi-rotor aircraft outwash. This paper will describe work investigating some of the related issues, specifically (1) how wake models and wake model parameters impact outwash predictions in comprehensive rotorcraft analyses and (2) considerations when scaling results from model scale to full scale. This work will also compare outwash predictions for conventional and multi-rotor VTOL aircraft obtained with a Lagrangian free-vortex wake model and with an Eulerian velocity-vorticity grid based wake model.
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.
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.
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.
A high-fidelity computational study is conducted to investigate the aerodynamic behavior and flight response of an electric Vertical Take-Off and Landing (eVTOL) multirotor configuration using unsteady computational fluid dynamics (CFD) framework. Four simulation cases are considered to examine the vehicle aerodynamics under both prescribed and fully coupled conditions. Prescribed hover and forward-flight cases isolate rotor aerodynamics and rotor-airframe interactions under constrained kinematics. Six-degree-of-freedom (6-DoF) free-flight maneuvering simulations capture the coupled evolution of aerodynamic loads, vehicle attitude, and translational motion. The results demonstrate that the high-fidelity unsteady CFD framework, coupled with rigid-body dynamics, effectively resolves the tightly coupled aerodynamic–dynamic interactions inherent to eVTOL configurations. This work provides a foundation for future investigations into trim strategies, control modeling, and expanded flight envelopes.
A new motion platform facility was developed at the University of Maryland to study autonomous landing of vertical lift aircraft on moving ship decks. It includes a 6-by-6-ft platform of 1.5 ton payload, a Vicon system, and a quadrotor. The platform can generate high-frequency / high-amplitude stochastic motions in all six degrees of freedom, including simpler motions typical of DDG-51 class vessels at high seas. The quadrotor is custom-built in-house around a feature-based vision system for detection, tracking, and pose estimation of a moving deck. In this paper, the vision data is coupled with the flight controls to execute autonomous landings. The paper presents a preliminary assessment of the platform, the quadrotor, and the performance of the closed-loop algorithm using simple tracking and landing experiments.
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.
When compared to the commercial sector, it takes the military almost four times longer to develop an aircraft. For example, Boeing Company developed the 767 jetliner from concept to production in four years whereas the F-22 took 16 years. While this example represents two completely different aircraft types, there exists generic commonality across all modern military and commercial air vehicle programs. Consideration in staff interdisciplinary skill sets, digital design tools, and simulations are but a few of the common developmental tools. Shared equipment, materials, and processes can be applied to manufacturing and ground and flight testing. Also important is extending consideration to balancing the logistics systems such as understanding the value associated with the design and support of LRUs and SRAs. As Chair and working with the Vertical Flight Society History Committee, a distinguished panel forum of experts has been invited to address this subject matter from the perspectives of their individual illustrious careers
NASA Airspace Operations and Safety Program is researching the utility of electric vertical takeoff and land (eVTOL) advanced air mobility (AAM) instrument flight procedures. The result will be dynamic and tailored procedures that align to the following modus operandi: maximize safety, optimize efficiency, support passenger comfort and minimize acoustics. This is achieved through dynamic airspace procedure design, which is a modular approach to create an airspace construct that customizes procedures to vehicle design and configuration, operation, and environmental conditions. The test plan supports different eVTOL platforms and envisioned operations for flight test or simulation and may be leveraged by AAM aircraft manufacturers and operators for any given aircraft, location and operation. This white paper is a reduced subset of the flight test plan; the full publication can be found on the NASA Technical Research Server (NTRS), https://ntrs.nasa.gov/citations/20240002788.
Future military missions for Agile Combat Employment (ACE) and next generation Special Operations Forces need an aircraft with effective hover and the ability to operate in transonic cruise. Hover requires significant power that can only be mitigated by larger diameter rotors, but large diameter rotors become a detriment to achieving transonic flight. The stop-fold rotor configuration can “make the rotor disappear” in cruise and stands out as the most viable option for meeting these next-generation air vehicle requirements. This paper discusses the progress Bell has made in developing enabling technologies for a practical and scalable high-speed VTOL (HSVTOL) based on the stop-fold configuration. To this end, a unique Track-Guided Test Vehicle (TGTV) was developed at Bell and tested at the 10-mile High Speed Test Track at Holloman Air Force Base. The test vehicle integrates all subsystems required to demonstrate the key technologies in a representative environment, including multi-mode propulsion, folding proprotors, and fly-by-wire transition controls to automatically manage each step of the prop-to-jet (and reverse) process. The TGTV demonstration validated the stop-fold technical approach and generated critical data to substantiate engineering models. Test results provide confidence that each step in the stop-fold transition process is thoroughly understood and that engineering tools can be used confidently for future aircraft design efforts. This paper documents the first known powered prop-to-jet and jet-to-prop transition and represents a significant milestone in vertical flight technology development.
Researchers at the National Aeronautics and Space Administration (NASA) have conducted a series of module-level 50-ft dynamic drop tests on electric Vertical Take-off and Landing (eVTOL) Energy Storage Systems (ESS) for the generation of dynamic impact data to support standards developments. The tests were conducted on zero-state-of-charge Electric Power Systems (EPS) Electric Propulsion Ion Core (EPIC) modules at the National Institute for Aviation Research (NIAR), utilizing the NIAR outdoor drop test setup and conducted by NIAR test personnel. Four total tests were conducted on modules oriented in four different orientations. During initial post-test inspections at the drop facility, it was observed that the modules experienced varying amounts of damage in various locations and forms. The damage was quantified to the maximum extent possible via photogrammetric methods such as digital image correlation and marker tracking. Post-test modules were then disassembled, and forensics were conducted, which involved inspections into various containment structures and the cells themselves. A scoring rubric was developed in order to utilize a common methodology to quantitatively assess the damage incurred into each module as way of determining the least and most amount of damage present. Results in the form of post-test inspections, digital image correlation deformations, and scoring rubric values will be all presented, along with proposed paths forward for future work.
Electric aviation is advancing rapidly, with aircraft from manufacturers like Joby and Archer well on their way to certification, aircraft electrification will continue and begin to apply to larger aircraft. To support larger electrified rotorcraft, rotors will need to grow if disc-loading and hover efficiency are to be maintained. A consequence of this is the need to reduce rotor speed to maintain an acceptable acoustic signature, especially for operation in urban environments. Most current applications utilize radial flux motors, sometimes with a reduction gearbox. Gearboxes can improve overall propulsion system power density by enabling higher motor speeds but are generally not preferred as they introduce additional potential failure modes and maintenance schedules. In this paper a holistic approach is used to understand the trade-offs between rotor and motor and their consequences on propulsion system power density.
This paper details the development of a tailsitter unmanned aerial system (UAS) that has the potential to be airlaunched in the near future. By simultaneously integrating air-launch capability with both rotary-wing vertical flight and fixed-wing horizontal flight, the vehicle can be rapidly deployed, perform hovering flight, and achieve high-speed and efficient cruising flight. The aircraft prototype has a mass of 1 kg (2.2 lbs) with wings that can fold to allow the aircraft to fit inside a 6-inch launch tube. A coaxial propeller with vectored thrust is used for control in vertical flight, and a unique avian-inspired wing-folding mechanism is used for stowing and deploying the wings. The aerodynamic design was characterized through a series of wind tunnel experiments, propeller tests, and flight dynamics simulations. High-fidelity simulations of vehicle dynamics validated its air-launch capability and flight tests performed with the prototype demonstrated the ability of the aircraft to perform hovering, transitioning, and fixed-wing cruising flight. To date, this aircraft has achieved speeds of up to 130 km/hr (81 mph), and range up to 10 km (6.2 miles).
This paper presents the development, verification, and validation results of an electrical Vertical Take-off and Landing (eVTOL) powertrain model. To better understand the potential impact of powertrain limitations on eVTOL aircraft handling qualities, a powertrain model was developed, integrated into revolutionary vertical lift technology (RVLT) reference vehicle designs, and tested in the National Aeronautics and Space Administration (NASA) Ames Vertical Motion Simulator (VMS). The high computational complexity required to capture the relevant powertrain physics may conflict with the ability to execute the simulation models in real time. In this paper, the authors present models and modeling decisions related to motors, batteries, and interconnections. Physics-based models and empirical models are used in tandem to support the modeling effort. Simulated motor-data comparisons are made to data collected from the NASA Scaled Power ElEctrified Drivetrain (SPEED) and Advanced Reconfigurable Electrified Aircraft Lab (AREAL) testbeds. The empirical battery model is compared to experimental 18650 battery data.
Electric Vertical Takeoff and Landing (eVTOL) vehicles undergoing advanced air mobility (AAM) operations feature increasingly autonomous systems (IAS) with non-traditional role allocations. Ensuring the safety of these operations and their novel human–machine teaming (HMT) paradigms requires an appropriate body of knowledge created through relevant, reproducible research. In this paper, we briefly examine the meaning of teaming; current regulation, standards, and guidance; and the knowledge required to build resilient HMTs before turning our attention to how this knowledge is being created by recent research and what conclusions or recommendations can be made. We identify the need for further research into the holistic performance of HMTs, the effect of novel allocations of roles between humans and machines, the ability of humans to provide resilience to unforeseen dangers when acting as a part of these teams; and the characteristics required for clear, timely, and accurate communication between the humans and machines. This work is done in the context of eVTOL aircraft with an indirect flight control system (IFCS) undergoing urban air mobility operations.
Urban Air Mobility (UAM) is quickly developing with the objective of transporting passengers and cargo in urban areas using electric vertical take-off and landing aircraft (EVTOLs). This paper presents the process developed to design and optimize the noise control treatment in EVTOLs. The process leverages CAE simulation models to predict the acoustic performance inside the aircraft due to the propellers acoustic noise sources and the turbulent flow around the fuselage during cruising. The model includes a representation of the noise control treatments modeled as multi-layer poro-elastic materials and allows performing multi-attribute optimization to balance the vibro-acoustic performance with the costs, weight, and packaging constraints. This process has been applied successfully to support the development of EVTOLS before physical prototypes become available, therefore reducing the development time and corresponding costs. A demonstrator model serves as an example to illustrate the proposed simulation process.
The vertical flight industry is on its way to a transformative era, with autonomous technologies set to alter aerial vehicle operations. While it seems certain that fully autonomous helicopters will eventually be deployed for a variety of missions, some high-stakes situations—like medical evacuations (MEDEVAC)—will for the foreseeable future demand human participation in the form of Emergency Medical Care-giving Crew. This study describes the testbed built to run and investigate hypothetical future situations in which a helicopter is autonomously piloted while a human medic with no aviation training, subjected to aviation and medical emergencies, manages patient care onboard. A total of 22 participants, with emergency medical technician certification, nursing or a medical board certification, were invited to run and evaluate the use of AI pilot (AP) in different scenarios of medical evacuation under the following emergencies: medical, empty fuel tank, pressure sensor miscalibration, and engine failure. A comprehensive evaluation of both objective and subjective performance metrics revealed that novice medical professionals could effectively execute medical evacuation operations in conjunction with an AI pilot, even during unforeseen circumstances. The analysis of response times unveiled distinct perspectives on how medics perceive and manage various emergency situations when an AP functions as a collaborative and effective team member.
This paper presents a comprehensive evaluation of machine learning approaches for real-time operational/ flight parameter estimation in large electric vertical takeoff and landing (eVTOL) vehicles, addressing the challenges of time-varying payloads and atmospheric disturbances in Advanced Air Mobility (AAM) missions. Artificial Neural Networks (ANN), Gaussian Process Regression (GPR), and Support Vector Machines (SVM), are compared for their ability to estimate gross weight (GW), longitudinal center of gravity position (CGx), and airspeed (Ux) using readily available flight control inputs and aircraft attitudes. The models are tested on clean data, turbulence-affected data, and reduced training data to assess performance trade-offs between computational cost and prediction accuracy. Results demonstrate that GPR consistently achieves the highest accuracy across all prediction tasks with maximum errors below 0.3% of nominal values, though at significantly higher computational cost compared to ANN and SVM. Under turbulent conditions, ANN and GPR exhibit notable reductions in accuracy, resulting in all three models (ANN, GPR, and SVM) achieving similar levels of prediction performance. Data reduction analysis reveals that using the Multipoint Maximal Variance Retention (MMVR) algorithm allows an 85–90% reduction in training data while keeping errors below 3.5%, striking an optimal balance between accuracy and efficiency. These analyses demonstrate the feasibility of ML-based operational/flight parameter estimation for AAM operations where direct measurement systems are impractical or cost-prohibitive.
Hydrogen-electric vertical takeoff and landing (H2eVTOL) (or fuel cell-electric VTOL) aircraft technologies are poised to emerge in the next coming decades and start operating from existing heliports and new vertiports. This paper assesses how key H2eVTOL design features interact with the ground infrastructure and how facility designers can address H2eVTOL specific facility requirements–especially the supply of hydrogen to the aircraft. Vertiport design should maximize compatibility are important to facilitate the accommodation of hydrogen technologies, minimize the need for extensive capital investments, and promote safety and operational efficiency. Considerations should be given to factors such as general aircraft configuration, electric and hybrid propulsion systems, and refueling infrastructure. The definition of notional aircraft concepts representing the evolution of critical VTOL aircraft over the next coming decades can help aviation facility planners and designers understand the type of vehicles they need to account for and also evaluate the future hydrogen demand. The lack of aviation-specific standards, especially when it comes to fire prevention, might adversely impact vertiports. Strategies are proposed for mitigating the effects of hydrogen operations at space-constrained facilities.
The NASA Revolutionary Vertical Lift Technology project aims to support and guide the development of vertical flight vehicles for the benefit of the U.S. rotorcraft community and to increase the quality of life of the public. As part of this effort, the Multirotor Test Bed (MTB) – designed and built by NASA – has been tested twice at the U.S. Army 7- by 10-Foot Wind Tunnel at NASA Ames Research Center in 2019 (MTB1) and 2022 (MTB2). This study utilizes MTB2 experimental data for sensitivity studies on rotor aerodynamic performance of a quadrotor configuration using two mid-fidelity tools, the Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) as well as Blade Element Theory based disk modeling in the OVERFLOW CFD solver. Additionally, this study leverages analyzing computational rotor performance predictions with experimental data to help identify future test configurations for the upcoming MTB3 test in the National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel.
This paper carries out experimental investigation of propeller and wing interactions under various geometric variations such as the horizontal and vertical distance between the propeller axis and the leading edge of the wing under different angle of attack conditions for a half wing setup for a wing made of symmetric airfoil. Rotor and wing performance is measured using independent six-component load cells. Through this study it is identified that for a wing made of symmetric airfoil optimal aerodynamic performance is significantly influenced by the position of the propeller. Positioning the propeller near the leading edge (x/c = 0.25) and on the negative side of the y-axis (y/c = −0.75) yields the best lift-to-drag ratios and enhanced lift, particularly in the moderate α range (4°–6°). Forward movement of the propeller along the x-axis (towards x/c = 0.75 or 1.00) increases drag and adversely affects performance.
The biography of Henrich Focke is well known and documented. During a small period from October 1954 to February 1956 he held lectures at the Technical University of Stuttgart during the winter semester. In the summer period he returned to Brazil for continuation of his contract work on the "Convertiplane" (a quad-tiltrotor aircraft) and the "Bei-jaflor" (a small single rotor helicopter). The topic of Focke's lecture in the winter semester 1954-55 was "Design of Fixed-Wing Aircraft", but the lecture manuscript of it is unavailable. In the following period 1955-56 Focke lectured about "Helicopter Design" and the manuscript was recently found in the central archive of DLR. It covers 123 pages of text with sketches and graphs and provides deep insights into the helicopter design philosophy of Henrich Focke.
In January 1984, the Georgia Tech School of Aerospace Engineering (AE) hired Dr. Daniel P. Schrage as the Rotorcraft Design Professor and the Associate Director of the Georgia Tech Center of Excellence in Rotary Wing Aircraft Technology (CERWAT), one of the Army-sponsored Rotorcraft Centers of Excellence (RCOE). Dr. Schrage left St. Louis, MO at the end of 1983 as the Director for Advanced Systems (DAS) and the Associate Director of Army Aviation Science and Technology in the Aviation Research and Development Command (AVRADCOM). His departure was a tough decision for Dr. Schrage as he was designated to become the Technical Director of the new Aviation Systems Command (AVSCOM). However, the new AVSCOM motto was "Readiness Immediate and Development Eventual," which, as it turned out, meant that new Army Aviation Systems would not be developed for the next 35 years. Dr. Schrage was also recruited by Bob Lynn, Bell Helicopters VP Engineering, as the Bell Helicopters Director of Technology, with a promotion to VP Engineering upon Lynn's retirement in the next few years. This was one of the most challenging decisions of his life for Dr. Schrage and his family, as they had to move from their home in O'Fallon, IL - a great town and home for his growing family.. In addition, his wife Nancy's parents and his mother and sisters, all lived within a half hour from his home. His father, Albin, had passed away while we were moving to the St. Louis Area following his MSAE graduation from Georgia Tech in May 1974. When he arrived at Georgia Tech in January 1974, he started teaching the Rotorcraft Design Courses, which were similar in content to what he had developed in AVRADCOM and to what Dr. Dick Carlson taught at Stanford U. He also developed and taught design courses in his two weeks each year in the Department of Mechanics at USMA West Point during his reserve duty from 1978-1983. He continued in the U.S. Army Reserves and taught two weeks at USMA until 1996. He then retired as Colonel in the USAR in 2004. He used a computer-integrated environment and the top-down design decision support process taught at West Point. This provided a Framework for using Systems Engineering Methods for Product Design Driven and Quality Engineering Methods for Process Design Driven, as illustrated in Figure 1. Value-based Acquisition decision-making is a lost art in Digital Engineering and other attempts to produce effective and affordable systems. The Army FARA Contract termination in 2022 was primarily due to lack of Development Assurance Value Based Acquisition (DAVBA) (Ref. 1).
Advanced Air Mobility (AAM) is an innovative concept that aims to revolutionize air transportation through electric and unmanned aircraft, enabling applications such as urban air taxis and medical transport. However, one of the key challenges to its widespread adoption is ensuring safety, particularly in collision avoidance. This study focuses on the development of a perception and guidance system for avoiding collisions with non-cooperative targets, which do not share their position or trajectory. To achieve this, a Frequency-Modulated Continuous Wave (FMCW) radar and an InfraRed(IR) camera are used. Compared to traditional pulsed or panel radars, FMCW radars offer higher resolution, better detection of small and slow-moving objects, and improved performance in cluttered environments. The IR camera enhances situational awareness by providing visual confirmation and additional tracking capability, making this sensor fusion approach particularly suitable for AAM applications. Our collision avoidance system follows ACAS Xu standards, which provide autonomous conflict detection and resolution for unmanned aerial vehicles. The maneuver selection process is based on precomputed lookup tables generated through a Markov Decision Process (MDP), optimizing responses based on risk and energy consumption. The entire system is tested in a simulation environment using Ansys AVxcelerate, a physics-based simulator capable of generating realistic sensor data. This approach allows for comprehensive testing of detection, tracking, and maneuver execution in a highly realistic scenario, ensuring the effectiveness of the proposed solution before real-world deployment.
This research analyzes flight safety occurrences such as incidents and accidents in the vertical lift community over the last two decades. A study of civil vertical lift occurrence data was performed for flight occurrences from 2000 to 2024. Focusing on North America (Canada, United States), research data was acquired from the respective government Transportation Safety Board agency of either country. The study data set consisted of 4623 occurrences (occ.) or observations (i.e.; 861 for Canada and 3762 for the United States). The research methodology involved a 6-step process to analyze data quantitatively (descriptive statistics) and qualitatively (trends, mitigation projections). For the study period, quantitative findings indicated occurrence rates (4.53 occ. per 100k flight hours (Canada); 3.39 occ. per 100k flight hours (United States)), occurrence rates of change (declining Canadian and United States rates (-2.3%/yr. & -2.2%/yr.) respectively), and occurrence event types (in Canada, Engine Failures (121 occ.) while in United States Loss of Control (589 occ.) events indicated the most occurrences). For this investigation, qualitative findings highlighted a series of general groupings or conditions in areas of System Failures, Flight Control, Vehicle Collisions, Flight Operations, and Pilotage. It was projected that technologically, open-loop and closed-loop control systems may provide the best potential for occurrence mitigation. Key pilot assistance domain systems include envelope/limit protection, detect/avoid, perception, and flight control (stability, trajectory following, navigation).
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