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.
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.
The recent discovery of glacier remains in Noctis Labyrinthus, the "Maze of the Night" near Mars' equator sheds new light on the history of water on Mars, the evolution of the planet’s climate and geology, and the possibility of life. It also opens the possibility for massive amounts of clean glacier ice to be accessed by astronauts at low latitudes on Mars, alleviating the need to operate in more frigid higher latitudes. Further reconnaissance of the site requires a robotic vehicle capable of traversing rough, salt-crusted glacier surfaces and leaping across crevasse fields. To address this need, we propose a conceptual hybrid aerial/ground vehicle, LILI (Long-term Ice-field Levitating Investigator). LILI combines episodic rotary-wing flight with ground mobility as a propeller-driven sled through an arrangement of skis/runners, wheels, and tilting proprotors. A high-level look at the Noctis Labyrinthus "relict glacier" site is presented, along with a notional LILI mission traverse concept designed to ensure critical scientific measurements are captured. The NASA Design and Analysis of Rotorcraft (NDARC) software is utilized to ensure that mission requirements and sizing constraints are met. Furthermore, future work considers guidance, navigation, and control requirements to satisfy mission objectives, and an initial construction for a simplified LILI small-scale prototype.
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.
NASA's successful demonstration of powered flight on Mars through the Ingenuity Helicopter, as part of the Mars 2020 Perseverance rover mission, has led to the development of next generation Martian rotorcraft. The future of Martian rotorcraft has evolved to include high payload-carrying vehicles to possibly contribute to planetary science missions, which will require improved flight dynamics and rotor aerodynamic performance to fly at nominally high forward flight speeds and at higher flight altitudes. To ensure the feasibility and viability of successful mission performance, it is also critical to mature the structural design for advanced Martian rotorcraft to bridge the gap between the best practices of the spacecraft and aircraft communities. This paper focuses on the structural analysis of a Mars Science Helicopter (MSH) blade using finite element methods. Multiple loading conditions including launch and operational flight were applied to investigate the blade’s structural integrity. The blade’s modal natural frequencies were also analyzed to investigate the blade's dynamic behavior.
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.
RPM-controlled hexacopters offer mechanical simplicity and inherent redundancy, but are unable to re-trim under all failure cases in forward flight. This paper investigates the use of reverse-enabled rotors as a means of expanding the attainable trim envelope and improving fault tolerance in RPM-controlled hexacopters. Isolated rotor experiments are conducted to characterize thrust and torque behavior under forward and reverse rotation, providing validation data for aerodynamic modeling. A blade-element-based model implemented in the Rensselaer Multicopter Analysis Code (RMAC) is then used to perform comprehensive trim analyses for a 1200-lb-class hexacopter in hover and in cruise at the best-range speed of 65 kts. Post-failure trim solutions are evaluated for four configurations, including edge-first and vertex-first orientations with different rotor spin directions. Results show that enabling reverse rotation allows trim recovery for all single-rotor failure cases in cruise, including aft-rotor failures that are not trimmable with conventional RPM-controlled rotors. A systematic comparison of peak rotor torque, peak rotor power, and total aircraft power reveals that failure severity is governed primarily by yaw moment deficits arising from the combined loss of hub torque and aerodynamic drag. Among the configurations examined, the edge-first configuration with a counter-clockwise spinning rotor 1 exhibits the lowest rotor torque and rotor power requirements, post-failure.
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.
With the flights of the Ingenuity Mars helicopter completed and the development work on the Titan Dragonfly rotorcraft/lander proceeding, it is now time to consider aerial flight on Venus. Challenges of developing aerial explorers for Venus are discussed along with past and present conceptual design vehicles. A summary of the scientific impact and necessary instrumentation to understand Venus’s climate and geographical makeup is provided. This paper presents possible aerial-vehicle-assisted approaches to exploring Venus, with an emphasis on rotary-wing vehicles/systems. Aerial conceptual design vehicles are presented in three categories that include flying: above the clouds (altitudes greater than 60 km), below the clouds (altitudes less than 50 km), and near the surface.
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.
An experimental investigation was conducted to characterize the effects of partial-ground on the aerodynamics of a hovering rotor. A model-scale rotor was tested at a range of heights above ground and under partial-ground coverage, and rotor hub forces and moments were measured using a six-axis force/torque transducer during constant-power operation. The measurements were used to develop a semi-empirical thrust ratio model that accurately captures trends from out-of-ground effect to full-ground effect conditions. This model predicts realistic thrust behavior at low ground-coverage conditions, exhibiting high adjusted R2 and minimal root mean square error. Time-resolved particle image velocimetry was conducted for selected cases to examine induced flow features and to qualitatively assess changes in the downwash and edge-driven crossflow associated with partial-ground interactions. A geometric rotor-ground interaction area based on a circular-segment formulation was correlated to the thrust coefficient over the interacting region. Results show that thrust increases with ground coverage and decreases with increasing out-of-ground height, whereas moment coefficients increase with decreasing height. The increases in thrust and moment can be attributed to a reduction in the induced velocity above ground, as observed in the measured flow field, thereby increasing the effective ground-induced pressure beneath the rotor.
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.
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.
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.
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.
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.
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.
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 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.
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.
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.
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 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.
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.
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.
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