Browse Topic: Flight tests
Regarding the external sling load system of heavy-lift helicopters, the influence of the law of lifting point position on flight control stability characteristics has not been distinctly explained. To address this challenge, this paper constructs a sling load flight simulation model based on multi-body dynamics. Overall, the proposed model consists of four parts, including the rotor aeroelastic coupling model, the fuselage rigid body dynamics model, the flexible sling model, and the slung object rigid body model. Furthermore, through the hub six-degree-of-freedom rigid model and the flexible sling model, this paper realizes the dynamic coupling between the components. On this basis, taking the CH-53E heavy-lift helicopter as the research object, this paper utilizes real flight test data to validate the multi-body dynamic model. Subsequently, this paper systematically analyzes the influence of different lifting points’ lateral position, sling load mode, load-mass ratio, and forward flying speed on helicopter control stability characteristics. Simulation results indicate that the lifting point location exerts a significant impact on the helicopter’s trim attitude angles and dynamic stability. Of them, the lifting point location of the front center of gravity is the optimal in terms of trim characteristics and eigenvalue distribution. Furthermore, within a certain flight speed range, the lifting point of the front center of gravity demonstrates superior speed adaptability and system robustness. Apart from providing a solid theoretical basis for the lifting point layout design of the external sling load system of heavy-lift helicopters, the research results have important engineering application value for improving the safety of sling load flight of heavy-lift helicopters.
In response to the current airworthiness regulations’ inability to cover the stall flight test requirements under icing conditions of civil aircraft with high-angle-of-attack restriction function and the lack of relevant flight test technologies in China, a study was conducted on the differences in airworthiness provisions for stall characteristics under icing conditions of such aircraft. Key technologies, including simulated ice accretion stall flight test methods, ice installation strategies, and data analysis techniques, are proposed and successfully applied to a specific civil aircraft. The results demonstrate that the methodologies proposed in this paper can effectively support simulated ice accretion stall tests, providing valuable insights for other similar aircraft.
This paper investigates a sub-scale testing methodology via Froude scaling combined with comprehensive simulation model development to validate Electric Vertical Take-off and Landing (eVTOL) aircraft simulations and disturbance rejection characteristics. Both sub-scale and full-scale quadrotor aircraft were modeled using the Distributed Electric Propulsion Simulation (DEPSim) and the Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) for simulation analysis. The sub-scale simulation was validated using flight data from the sub-scale model, including frequency sweeps and impulsive gust disturbance tests in the Penn State University (PSU) indoor flight facility. The PX4 control architecture was modeled in DEPSim and implemented in both scale models, using Froude-scaling in the control laws with the limitation that the Electronic Speed Controller (ESC) dynamics were not fully replicated in the simulation. The scaling methodology and control laws were verified through gust response tests and the Hovering turn and hold Handling Qualities Task Element (HQTE) test. The results indicate that the sub-scale flight testing and simulation provide a low-risk and low-cost method to evaluate full-scale flight performance and disturbance rejection properties.
The Enhanced Tiltrotor blade, also known as the RGF3 blade, represents a major milestone in Leonardo Helicopters Division's pursuit of advanced rotorcraft technology. Developed at the Yeovil facility in the United Kingdom as part of a dedicated program and in collaboration with the European Clean Sky 2 initiative, it is a key enabler for the Next Generation Civil Tiltrotor Technology Demonstrator. Leveraging the AW609 airframe, the NGCTR integrates a new lateral rotor control system and a V-tail with ruddervators to expand maneuverability and control authority. The RGF3 blade combines aerodynamic efficiency with manufacturability, cost effectiveness, and certification readiness. Innovations include advanced airfoil families, highly swept anhedral tips, dual-redundant anti-ice systems, and full compatibility with legacy components. A comprehensive test campaign—covering structural loads, lightning and bird strikes, icing, and wind tunnel validation—confirmed its robustness and performance. The RGF3 blade embodies Leonardo's vision for high-speed, sustainable, and reliable next-generation rotorcraft.
This paper evaluates the feasibility of Restricted Icing operations for light to medium helicopters, which typically lack Full Ice Protection Systems (FIPS). Current regulations normally prohibit these aircraft from flying in known icing conditions, leading to frequent mission cancellations for HEMS and SAR operators. To address this, Airbus conducted flight test campaigns in Norway (2023, 2025) to characterize a safe icing envelope for "cold blade" operations. Results demonstrate that the H145 was able to sustain continuous flight in icing conditions between 0°C and -3°C and perform time-limited operations (5–10 minutes) down to -6°C without compromising safety, handling, or structural integrity. Safe Restricted Icing operations require an operational framework that ensures proper planning, safe routing, briefing, in-flight decision making, and specialized crew training. The study concludes that a Restricted Icing Clearance could significantly enhance winter flight safety. By providing an IFR alternative to VFR flights in marginal weather within a clear operational framework, the introduction of a Restricted Icing Clearance could ensure the availability of critical life-saving missions in typical winter weather.
The paper presents the successful drag reduction of the Racer demonstrator's rotor head through its innovative full fairing, based on a robust de-risking methodology leveraging 2D Robust Design Optimization (RDO) for airfoils, 3D CFD analysis with multiple fidelity levels, and experiments. We provide a unique end-to-end comparison across the full development cycle, correlating simulation predictions with both experimental and flight-test data. The fully faired architecture achieves a significant 42% reduction in rotor-hub form drag. At the full-vehicle level, flight tests confirm a 10% net drag reduction, including complex interactions with the airframe. This real-world measurement correlates highly with dynamic URANS predictions (11-12%), while effectively contextualizing the more optimistic 16% gains observed during static wind-tunnel and steady RANS evaluations. These findings provide a comprehensive validation of the low-drag fairing concept, offering valuable insights for the aerodynamic design of future high-speed rotorcraft.
The aerospace industry is undergoing a profound transformation driven by emerging aviation technologies, including Advanced Air Mobility (AAM), electric vertical takeoff and landing (eVTOL) aircraft, and highly automated flight control systems. These complex systems often feature tightly coupled flight controls and power plants where traditional methods of compliance — relying heavily on physical ground and flight testing — are becoming increasingly impractical due to the vast number of potential interaction cases. To address this challenge, the SAE G-35 Modeling, Simulation, and Training for Emerging Aviation Technologies and Concepts Committee was formed to develop industry consensus standards. This presentation discusses the landmark release of SAE ARP7094, "Recommended Practice for Using Modeling and Simulation for Certification of Aircraft, Products, and Systems" and its role in establishing a standardized, simulation-based path to certification. The SAE G35C group is responsible for developing standards and procedures for using modeling and simulation as a method of compliance for the certification of AAM aircraft similar to the RCbS project conducted in collaboration between EASA, academia and industry in Europe.
The National Research Council of Canada and International Test Pilot School collaborated in the experimentation with Supervised Deep Learning methods for prediction of high-order rotor dynamics and blade loads. Using an intentionally limited flight dataset (431 samples, 6.7 seconds) from the NRC Bell 412 Advanced Systems Research Aircraft (ASRA), an evaluation framework was developed to expose limitations of conventional validation practices. Latin Hypercube Sampling is used to improve training data coverage, restoring temporal generalization and yielding positive (R2) across all eleven rotor quantities, including hub dynamics and blade bending at two spanwise stations. Peak results include beam bending at R2 = 0.94, (CNN, (r=0.97)) and inboard chord bending at R2 = 0.81, (r = 0.90). Ensemble averaging further improves temporal-split performance from R2 = 0.33 to R2 = 0.64 at no additional cost. Results provide guidance for rotor load estimation under data-constrained conditions.
This paper presents a spatio-temporal graph neural network (STGNN) centric approach to enable heterogeneous agents to collaborate and cooperate for different types of missions. The STGNN-centric approach and corresponding autonomy are encapsulated in the Advanced Graph-enabled Network Technology for Collaborative Autonomous Agents (AGENTCA) technology. Various decentralized and distributed control architectures are reported in the literature, but in some instances these approaches do not leverage the inherent graph network which can increase scalability to larger teams and algorithmic efficiency. Specifically, in this paper advances in artificial intelligence are leveraged to parameterize and encode optimal, or nearly optimal, swarm control techniques. For this work, the team focused on developing a diffusion-based STGNN swarm controller using imitation learning. An expert, centralized swarm control law was used to guide the STGNN during the learning process. The STGNN controller enables the swarm to follow a leader while avoiding static and dynamic obstacles and maintaining a desired separation distance from neighbors and obstacles. The approach is demonstrated in simulation with hundreds of agents and in flight tests with up to thirteen test vehicles.
This paper utilizes a combined experimental and modeling approach to investigate techniques for improving the forward-flight roll-control authority of a Quadrotor Biplane Tailsitter (QBiT). QBiT is a mechanically simple, efficient hover/cruise aircraft whose roll authority in forward flight is traditionally limited by differential propeller-torque-based control. The two roll-control enhancement techniques investigated are propeller canting and the use of ailerons. A 2-kg instrumented QBiT platform was developed and flight tested to collect high-fidelity flight data across multiple flight regimes including hover, transition, cruise, and coordinated turns. A flight dynamics model was developed and validated using wind tunnel measurements and flight-test data. Flight tests showed that the cant-only configuration exhibited limited roll authority during coordinated turns due to motor control saturation, whereas the cant-plus-aileron configuration provided improved roll performance. Using test data from forward-flight roll excitation maneuvers, roll-control authority was evaluated both in the time domain and frequency-domain. The results showed that adding ailerons increased forward-flight roll-control authority by about 2.3 times from analyzing the flight data and by up to 2.6 times based on the flight dynamics simulations.
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.
The Vortex Ring State (VRS) is an intriguing phenomenon where rotary wings are trapped in their own wake. It is inherently difficult to model with the classic momentum theory due to the breakdown of slipstream assumptions. In practice, it is still a critical safety concern for helicopters and emerging multi-rotor platforms. Despite extensive wind tunnel tests, flight tests, and modelling over the past decades, our quantitative understanding of the underpinning flow details is still limited, because of limitations in measurements and modelling resolution. First-principles-based, high-resolution simulations could uncover the flow details, but the modelling is still rare and challenging due to complexities in the flow and flight physics, and particularly the associated high computational costs. Nevertheless, in this work, a series of high-resolution simulations of the VRS phenomenon are presented. Fully blade-resolved and unsteady simulations of an isolated helicopter rotor within the VRS were carried out for over 20 revolutions. The simulations were performed using the Helicopter Multi-Block 3 (HMB3) CFD framework developed at the University of Glasgow, solving the fully compressible and unsteady Reynolds-averaged Navier-Stokes (RANS) equations with a Scale-Adaptive Simulation (SAS) closure. The modelling revealed the formation of the large vortex ring stemming from the discrete tip vortices, and its evolution over the 20 revolutions. The blade loading distribution and evolution were analysed and compared with test data. Moreover, we extracted the inflow features from the CFD results via direct extraction and inverse Blade Element Theory (BET). The results highlighted the strong induction of the vortex ring, and the influence of secondary flow features besides the inflow. It was also noted, with the correct inflow information, the BET was able to reconstruct the VRS loading with reasonable accuracy. These high-fidelity results provide unique insight into the flow and flight physics underpinning the VRS, and contribute to the ongoing GARTEUR AG28 collaboration on multi-rotor VRS investigation.
Pilot compensation — the effort required to maintain task performance in the face of deficient vehicle characteristics, as rated on the Cooper–Harper Handling Quality Rating (HQR) scale – is the task-performance-anchored measure of workload. While it has traditionally been inferred from control activity alone, recent work shows that eye-movement activity carries complementary information: as compensation rises, control inputs increase while visual scanning narrows, so neither channel alone captures the full picture. This paper proposes the pilot action metric, which combines control-stick and eye-movement activity rates so that both channel responses reinforce the compensation signal. A shared-slope regression model with per-pilot intercepts is evaluated via leave-one-out cross-validation on 16 simulator runs flown by three military test pilots across four mission task elements. The combined metric succeeds where either channel alone fails, reproducing 94% of ratings to within ±1 HQR. The model further yields a conservative maximum-tolerable-compensation boundary that is consistent with independently derived flight-test data.
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.
This paper presents the development, optimization, and flight test validation of a Trajectory Control System (TCS)-based flight control system for a tiltwing unmanned aerial vehicle. The TCS is a configuration-independent middle-loop longitudinal controller for vertical takeoff and landing aircraft and is integrated here with explicit model following inner-loop controllers, inverse propulsor models, and a tiltwing-specific control allocation scheme. The resulting flight control system provides coordinated control across vertical flight mode, hybrid flight mode, transition flight mode, and forward flight mode while relying on a concise feedback set and requiring only airspeed from the air data system. The control laws are obtained using a formal constrained optimization framework and transferred directly from simulation to flight without additional on-site retuning. Flight test results from piloted, semi-autonomous, and fully autonomous operations demonstrate stable and predictable behavior throughout the flight envelope, including tight hover performance, simultaneous climb rate and speed tracking in hybrid flight, and successful departure and arrival transitions at multiple speeds. Selected simulation-versus-flight comparisons further show that the nonlinear model captures the dominant trends in the measured response while also identifying specific aerodynamic and transition regime effects that warrant further refinement. Overall, the results demonstrate that the TCS + EMF architecture provides a practical and effective control solution for tiltwing VTOL aircraft.
Accurate monitoring of helicopter operational usage relies heavily on robust regime recognition algorithms. How-ever, evaluating these approaches is challenging when they operate as opaque, "black boxes", as in the case of machine learning-based models. This paper introduces a comprehensive evaluation framework designed to assess regime recog-nition models from a number of perspectives and investigate anomalies in the predicted regimes. Centered around a high-fidelity data set derived from scripted flight tests covering a complete usage spectrum, the developed method-ology provides a comparative baseline. The analytical suite includes 3D spatial visualization tools for flight path mapping, sequential anomaly detection, and confusion matrix metrics. While applying the labeled data set to other platforms presents inherent limitations in terms of mapping features and regimes appropriately, the integrated toolset successfully exposes weaknesses in the model and highlights gaps in training data. Ultimately, this evaluation frame-work enhances the interpretability of model outputs and builds confidence in the use of regime recognition algorithms.
In this study, a multifidelity aeroelastic framework is presented for predicting trim conditions in rotary-wing aircraft, with the main focus placed on the DUST implementation and its application to helicopters and quadrotors. The methodology combines aerodynamic and structural solvers of different fidelity, specifically DUST and the multibody dynamics solver MBDyn, through the preCICE coupling interface to enable direct comparison with rigid and coupled aeroelastic solutions. The trim problem is formulated from the six degree of freedom rigid body equilibrium equations in a helical turn reference frame, naturally covering both steady and maneuvering flight. Although the same formulation can be extended to fixed-wing configurations, the present paper is focused on rotorcraft applications. The framework is first applied to the SA330 Puma helicopter, chosen for the availability of validated flight test data. The methodology is then extended to a multirotor derived from a NASA quadrotor, demonstrating that the same trim strategy can be transferred to distributed-lift rotorcraft. Results highlight the potential of the proposed approach to provide physically consistent and computationally affordable predictions of helicopter and multirotor equilibrium states.
This paper presents results of flight tests conducted on a coaxial ultralight helicopter. An automated flight test evaluation method is presented and exemplified through its application to steady horizontal flight. The results shown include pilot controls, helicopter attitude angles, power, thrust and torque distribution between the rotors, rotor harmonic thrust components, and teeter angles, along with their rotor harmonic components across varying flight speeds. This study focuses on the dependencies of these parameters on center of gravity position and sideslip angle.
Rotorcraft pilots operating in degraded visual environments encounter significant challenges during hover flight, where the absence of critical visual cues increases the risk of spatial disorientation. At low altitudes and in obstacle-rich environments, even minor losses in situational awareness can have severe consequences. Understanding the visual cues that support stable hover in good visual environments, and how their absence impacts performance and cognitive workload, is essential for mitigating these risks. This study examined key human factors in hover flight, focusing on the role of peripheral vision and microtextures in supporting pilot performance. It evaluated whether naturally relied-upon visual cues in good visual environment conditions can be artificially replicated to restore visual dominance in simulated degraded visual environments. Analysis included flight performance metrics, control inputs, physiological workload indicators, subjective assessments, and pilot feedback. The findings contribute to improved understanding of visual cueing and pilot adaptation in degraded conditions.
This paper presents the development flight test campaign of autopilot Upper Modes for T-625 Gökbey helicopter. The primary objective of the test campaign is to evaluate the newly developed Upper Modes in the frequency and time domain across the operational flight envelope. For quantification of performance and stability, various metrics are selected from the literature. Flight tests are designed to extract the metrics from time domain data and tests are conducted. Initial flight tests revealed discrepancies between theoretical design models and actual aircraft dynamics, requiring iterative control law gain optimizations. Furthermore, combined mode engagements required targeted simultaneous tuning of different modes to maintain stability margins in combined engagement. By integrating quantitative data analysis with qualitative pilot feedback, engagement logic and control parameters were successfully refined.
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.
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 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.
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.
From Test Flights to Revenue
The German Aerospace Center's (DLR) solar-powered high altitude platform (HAP) has completed ground vibration testing, in preparation for low altitude flight testing planned for 2026. German Aerospace Center (DLR), Cologne, Germany High-altitude uncrewed aircraft can remain in the lower stratosphere for extended periods, performing a wide range of Earth observation and communications tasks - from monitoring shipping lanes and supporting disaster response to providing internet access. The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) has now taken an important step in the development of its own high-flying solar aircraft by successfully completing a Ground Vibration Test (GVT) on its innovative HAP-alpha high-altitude platform. Extensive ground trials took place at DLR's National Experimental Test Center for Unmanned Aircraft Systems in Cochstedt, Germany. Further tests will follow and the first low-altitude flight trial is planned for 2026, subject to ideal weather conditions. “With HAP-alpha, DLR is demonstrating its comprehensive systems expertise in the complete design, development and operation of a new and innovative aircraft, incorporating all disciplines,” explains DLR Executive Board Member for Aeronautics, Markus Fischer. “This illustrates our engagement in an important field of innovation, to strengthen Germany as a location for technology and business and to open up new perspectives for our public stakeholders in collaboration and knowledge exchange.”
The return to Earth is a rough ride for astronauts, from the violent turbulence of atmospheric entry to a jarring landing. Hitting the ground in a Soyuz capsule is the equivalent of driving a car backward into a brick wall at 20 mph, and it’s resulting in more head and neck injuries than NASA computer models predicted. To collect more data, NASA’s Johnson Space Center in Houston commissioned a Small Business Innovation Research (SBIR) project to develop a wearable data recorder for astronaut spacesuits. One result, created by Diversified Technical Systems Inc. (DTS), is a miniature commercial device that now collects and transmits data for any application from airplane test flights to tracking high-value shipments.
Advancements in embedded processing, software, new product introductions, partnerships and recent demonstration flights reflect the growth in development of artificial intelligence (AI) and machine learning (ML) for military aircraft avionics systems occurring in the aerospace industry. This article highlights trends across several industry partnerships, demonstration flights and the enabling elements that are providing opportunities to integrate AI and ML into military avionics systems. In a June press release, Helsing, the Munich, Germany-based native software company and Saab, the Swedish defense manufacturer, announced their completion of a series of test flights where Helsing's “Centaur” AI agent controlled the aerial movements of a Gripen E fighter jet. AI agents are growing in popularity across many different industries for a variety of use cases. In a November 2024 blog about the topic, Microsoft described them as taking “the power of generative AI a step further, because instead of just assisting you, agents can work alongside you or even on your behalf. Agents can do a range of things, from responding to questions to more complicated or multistep assignments. What sets them apart from a personal assistant is that they can be tailored to have a particular expertise.”
Launching atop NASA’s Space Launch System (SLS) rocket, Orion will carry four astronauts to lunar orbit and safely return them to Earth on Artemis missions. The Artemis II test flight will be NASA’s first mission with crew under Artemis. Astronauts on their first flight aboard NASA’s Orion spacecraft will confirm all of the spacecraft’s systems operate as designed with crew aboard in the actual environment of deep space.
In this paper, we develop a new feature-based algorithm using stereo cameras to estimate stochastic ship-deck motion at high sea states. Unlike our previous algorithms, this algorithm is able to estimate the motion of arbitrary ship structures without prior information on the ship's visual appearance or geometry. The algorithm requires an initial pose and suffers from drift over time, which was resolved by fusing it with our previous 2D feature-based vision algorithm. The combined vision algorithm is validated using a simulated ship featuring 3D ship structures and 2D flight deck markings representative of a DDG-51 ship. The results indicate that the algorithm can accurately estimate the pose of a simulated ship undergoing Sea-State 6 motion. The vision algorithm was further validated in a simple free-flight test.
Flight test students must explore a wide range of helicopter dynamic responses to learn how to assess conditions ranging from good conditions operation to those approaching, or even experiencing, loss of control. To introduce this evaluation process, the Flight Test and Research Institute (IPEV) implemented a helicopter flight dynamics model. This model is stitched in the x-body velocity (u) and y-body velocity (v) to achieve more accurate simulation, combined with a Variable Stability Augmentation System to assess different conditions prior to experiencing them in real flight. The use of robust control, where a fixed controller is applied to flight control systems under various operating conditions, presents an alternative to the traditional gain scheduling technique commonly used in aeronautical systems. This paper explores the potential to reduce controller design complexity while evaluating the impact on the helicopter’s full flight envelope through quantitative analysis and handling qualities evaluation by piloted simulation according to ADS-33E-PRF standard.
A robust velocity stability augmentation system was developed for the CoAX 600/2D coaxial-rotor helicopter to enable safe testing of a fly-by-wire system on an optionally piloted variant of the aircraft, developed by Piasecki Aircraft Corporation. The control law design and subsequent stability analysis were based on a validated nonlinear model of the CoAX 600 rotorcraft. A subset of helicopter handling qualities were evaluated through both analytical methods and piloted simulations, conducted with and without the stability augmentation system. Additionally, flight test data contributed to the analysis, albeit to a limited extent.
By its seventh flight after the first take-off, the RACER (Rapid And Cost-Effective Rotorcraft) demonstrator smoothly reached the targeted 220kts speed in stabilized forward flight, validating the high-speed compound architecture developed by Airbus Helicopters in the frame of Clean Sky 2 programme. During the flight envelope exploration, the dynamic behavior of the main rotor was carefully assessed, by monitoring the vibratory loads and validating its aeroelastic stability. Particular care was taken to validate the predicted stability domain of the Dual Rotor phenomenon, a particular case of flap-lag coupling associated with high-speed flight conditions. This paper presents the most significant results shaping the success of RACER flight test campaign. After having introduced the theoretical background and the associated analytical equations, the simulation framework based on the comprehensive analysis tool STORM is presented to discuss the numerical resolution of the stability problem. Then, the rotor dynamics loads and airframe vibratory behavior of RACER are closely examined to demonstrate the absence of any sign of instability, in the various flight conditions offered by its rotor and wing configuration. At last the flight test results are compared to the computed stability domain to assess the margins and estimate the high-speed potential of the rotorcraft.
This paper explores the effect of addition of a horizontal tail on the longitudinal stability and performance of a Biplane Tailsitter Unmanned Aerial Vehicle (UAV). Biplane tailsitters a type of hybrid UAVs, often exhibits poor longitudinal stability during forward flight, necessitating continuous active control through application of differential motor thrust to maintain attitude. To address this challenge, this work proposes the integration of a horizontal tail on a quadrotor biplane tailsitter UAV, aiming to improve pitch stability and control authority during critical flight phases. Experimental flight data was utilized to determine the appropriate sizing of the elevator. A detailed flight dynamics model validated the effectiveness of the elevator control. The design was validated through outdoor flight testing, comparing the performance of tail-less and tail-attached configurations. The results demonstrate that the modified design results in a reduction control power requirement for pitch control on the motors, enhancing longitudinal stability, and improved ascent and descent rates. This study provides a systematic approach to improving the operational capabilities of tailsitter UAVs, contributing valuable insights for the design of future UAVs requiring enhanced maneuverability and efficiency in VTOL and forward flight modes.
This paper discusses the development of a quantitatively-accurate non-linear hybrid flight dynamics model of a hover-capable Air-Launched Tailsitter Unmanned Aerial System (ALUAS) in order to 1) understand its dynamics during complicated maneuvers, and 2) provide a high-fidelity framework to develop novel control laws. Wind tunnel tests were conducted on a 1:1 scale model of the full aircraft to measure the airloads, which were used in the simulation as a lookup table. Flight tests of the ALUAS were performed in hover, transition, and cruise to collect a large amount of unique state measurements by providing large excitations to induce highly transient motion. The flight dynamics predictions using Rotorcraft Comprehensive Analysis System (RCAS) software were then compared with experimental flight test data. To correct any discrepancies in the RCAS physics-based predictions, a correction was learned from the experimental measurements, making use of the large amount of collected flight test data. Using a neural network to learn this correction, the end result was a quantitatively accurate neural network assisted flight dynamics model. The accuracy of current simulations in complex flight states successfully demonstrates the applicability of the proposed methodology for correcting the dynamics model of novel out-of-the-box aircraft configurations.
Pilot workload assessment has been a keen area of research for many years and has key applicability in flight testing. This paper outlines the development of a novel workload rating scale and index, the Comeau-Duggan Pilot Workload Index, which bridges gaps, such as causal factor identification, between some of the most widely used rating scales in flight test. The conceptualization and evolution of this index has been a multi-year and multi-nation research effort that has built upon the foundation and fundamental principles that underpin current widely accepted workload rating scales used in Human Factors and Handling Qualities engineering. The pilot workload index facilitates a rigorous and robust methodology for identifying the factors contributing to a given flying task, quantifying their impact through a structured suffix flowchart approach. It can provide, for example, a quantifiable link between pilot workload and the operational use of the aircraft, and therefore could inform aircraft and system design, as well as tactics and procedural development. It was developed through flight trials conducted at the National Research Council of Canada and flight simulator trials conducted at the University of Liverpool.
This paper introduces a comprehensive model, specifically developed to inherently capture interactional effects. Due to the high computational cost associated with the large analysis matrix including variations in angle of attack, angle of sideslip, velocity, and weight, a surrogate model is used in creating aerodynamic databases. This database, which reflects interactional effects under a wide range of flight speed, angle of attack, angle of sideslip, and weight configuration, is integrated into a rotorcraft analysis tool. Simulations are performed, and results are compared against flight test data for the T625 Gökbey, covering low-speed, high-speed, rightward and climb conditions. The results highlight the impact of interactional aerodynamics on flight characteristics and load predictions. Overall, the study emphasizes the importance of including interactional effects to ensure accurate and reliable rotorcraft design in the early design stages without requiring flight test data.
Big Data technologies have become quite ubiquitous in the last years, allowing for the storage of substantial amounts of data, typically flight test data as recorded by the flight test installation. On recent helicopter prototypes, we generate in excess of 50 GB of raw data per flight hour, usually in a format not adequate for efficient large-scale processing. With some specific optimizations and the setup of a specialized infrastructure, there are now practicable means to store timeseries in ways that allow for requests spanning hundreds or thousands of flights to complete within minutes, opening the way to some substantial savings and new insights. However, to make the most of these data and make informed decisions it is often quite important to store contextual data that go beyond the pure timeseries data, typically on helicopters where optional installations can have a significant impact on aircraft performance or behavior. This paper explores the various kinds of data and metadata related with flight tests, how to collect them and relate them with one another in order to maximize raw data value and avoid some common pitfalls. We define more accurately the data of interest, where to collect them and some ideas to further improve data collection in the future.
Items per page:
50
1 – 50 of 1451