Browse Topic: Optics
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
This experimental study showcases the changes to tip vortex evolution caused by unsteady plunging and pitching motions. Three cases of motion are tested on a NACA 0012 airfoil using time-resolved stereoscopic particle image velocimetry (PIV). Tests are taken while the airfoil is subjected to sinusoidal plunging and sinusoidal pitching motions. A control test is also taken for a static airfoil for the baseline comparisons. Changes to the tangential velocity, axial velocity, turbulence intensity, and Reynolds shear stress are analyzed for the duration of each cycle of motion and compared to the static results. For the plunging and pitching cases, the swirl velocity magnitude during the downstroke is significantly greater than static values, exhibiting greater levels of turbulence intensity and large Reynolds shear stress peaks about the vortex core. In contrast, data from the upstroke phase yields minimal turbulence contents, due to the loss of lift. The vortex grows weaker during the
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
Rotor-rotor and rotor-boundary aerodynamic interactions of a quadrotor system without a fuselage in ground effect and ceiling effect for varying rotor-boundary distances and hub spacings were investigated. A GPU-accelerated Lattice-Boltzmann Method (LBM) was coupled to new unsteady actuator disk method (ADM) and actuator slice method (ASM) based rotor models for this purpose. Validation was conducted against experiments for both performance and particle image velocimetry flow field data. The trends in thrust and power were accurately predicted by both actuator methods, with high computational efficiency. Interactional flow physics were resolved, causing the consistent performance benefits very close to the ground, the performance penalties caused by the fountain flow effect between rotors occurring over a limited range of ground distances, and the persistent performance augmentation in ceiling effect. The ASM rotor model, with its individual blade representation, was found to predict
This study investigates the interactional aerodynamics of multi-rotor systems with longitudinally canted rotors, focusing on force, moment, and wake behavior. Experiments using two 24-inch, two-bladed rotors in hover varied cant angle (0–20°) and hub spacing (1.1–1.5D). Increasing longtitudinal cant angle had the greatest effect on maximum longitudinal force, (| Fx |), yielding a reduction of up to -6.18% per 1°. Hub spacing had greater influence, especially on longitudinal force, | Fx |, and pitching moment, (| Mx |), which decreased by up to -16.00% and -31.07% per 0.1D increase, respectively. Time averaged flow results from Particle Image Velocimetry (PIV), showed that larger hub spacings and cant angles improved wake separation and flow symmetry. These results provide foundational data for minimizing parasitic loads and maximizing aerodynamic performance in advanced multi-rotor designs.
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.
Accurate and quick-turnaround ship airwake simulations are essential for better understanding of shipboard helicopter aerodynamic interactions. However, for most realistically modeling a ship airwake, the interaction of the ship with the turbulent atmospheric boundary layer (ABL) must be resolved. In this study, an ABL was generated in the Lattice-Boltzmann simulation using the Synthetic Eddy Method (SEM), and the effects of the ABL inflow on the airwake of the Simple Frigate Shape 2 (SFS2) ship model were assessed. The Reynolds stress tensor components necessary for the SEM were obtained from particle image velocimetry (PIV) measurements. Mean velocity and turbulence intensity profiles obtained from experimental measurements and the Lattice-Boltzmann simulation were compared to profiles available in the literature. Results indicated that the profiles obtained from the PIV and simulations closely resembled the profiles in the literature. Ship airwake data from the LBM simulations were
The performance and unsteady loads of a rotor operating in shipboard environments are highly sensitive to the influence of unsteady ship airwakes. In extreme cases, this interaction can significantly degrade rotorcraft handling qualities and constrain the safe launch and recovery flight envelope. This study presents wind tunnel measurements of azimuth-correlated rotor hub loads for a 1:100 scale single main rotor, modeled after the NATO Generic Rotorcraft, hovering above and around the landing deck of the NATO Generic Destroyer. These measurements were complemented with Particle Image Velocimetry (PIV) measurements. Unlike time-averaged data, azimuth-resolved measurements reveal detailed insights into the interactional aerodynamics between the rotor and ship airwake at specific rotor azimuth angles. By comparing phase-averaged rotor load responses to a trimmed reference condition measured up-and-away from the ship airwake, this study discovered both beneficial and detrimental load
The empennage of a helicopter is largely responsible for its stability in forward flight. Its performance is mainly determined by its aerodynamics. In this paper, the empennage of a CoAX 2D ultralight research helicopter is analyzed in detail. For this purpose, the helicopter was equipped with flow measurement devices and flight tests were performed, covering different flight conditions. Measurements from a nose boom as well as the pilot’s control inputs and helicopter's position are available for evaluation. For the empennage in particular, seven-hole flow probes were mounted on it and various cameras were used to record the movement of the surface tufts.
This paper presents findings from a joint computational-experimental venture that seeks to advance the physical understanding and validation-quality database for a model-scale generic tractor proprotor–wing system during the tiltrotor conversion maneuver. This study evaluates the interactions in a quasi-static manner for various proprotor tilt angles (θ) across the tiltrotor conversion maneuver. Independent experimental measurements of the wing and proprotor loads accompany synchronous wing surface pressure measurements along with stereoscopic particle image velocimetry flow field measurements at discrete spanwise locations. High-fidelity computational fluid dynamics simulations leverage the multi-disciplinary rotorcraft simulation tool CREATE™-AV Helios to assess the interactional aerodynamics of the proprotor–wing configuration across the tiltrotor conversion maneuver. Computational simulations use a newly implemented Helios module to trim to the experimental proprotor thrust
Launch, recovery, and deck handling operational performance on smaller ship platforms like Corvettes, Frigates and Destroyers are qualified as the most challenging tasks in the UAS ship-deployment of a VTOL Uncrewed Air System (UAS). One of the main hurdles is the random nature of seaway-created deck motions coupled with ship structure disturbed air wake patterns. The MoD has supported a range of work aimed at bringing Quiescent Period Prediction (QPP) technology to fruition. QPP firstly requires Wave Profiling RADAR to measure the sea wave system out to approximately 2km in the region around a vessel. Secondly these measurements are employed in a wave propagation model to predict the actual wave forces acting on a vessel. Using the wave predictions as inputs to a vessel model makes possible to predict the actual (deterministic as opposed to statistical) motions of a vessel. Wave systems naturally alternate groups of large waves with smaller waves, this property, combined with the
As part of maintenance improvement on helicopters, Airbus Helicopters has made available a proactive analysis service based on Health and Usage Monitoring System data generated during the flight. The present paper describes the new approach used to detect and classify any changes in time series behavior thanks to A.I. (Artificial Intelligence) especially computer vision. This new approach is more efficient and relevant than the classical approach based one statistical law [Ref 1]; in fact, it is acting, as the human eye, which is able to identify easily any abrupt change on the time series, and classifies it, whether Machine learning or Deep Neural Networks both have shown excellent results in term of classification accuracy. First part of this paper highlights how the learning data were prepared, then the second and the third parts give more details about how the time series are transformed into image presentation and how the different Artificial Intelligence models were selected and
In this paper, we develop and validate a 3D feature-based algorithm for tracking stochastic ship-deck motion at high sea states, specifically Sea-State 6 using data from the Navy SCONE dataset. The new vision algorithm was developed from the structure-from-motion technique, which recovers the 3D structure of an object from a series of 2D images, and was validated using a simulated 3D ship-deck attached to a moving Stewart platform. Algorithm performance with different feature detectors and image resolutions was compared. In hand-held tests, the vision algorithm was demonstrated to accurately estimate the pose of a moving ship-deck using a quadrotor. Visually degraded conditions were also evaluated; the algorithm is robust to occlusion and low illumination, but performance reduces in severe glare. The vision algorithm was then validated in a simple free-flight test. All results were compared with Vicon ground-truth data. Additionally, as the 3D algorithm is computationally demanding, we
The rotorcraft community faces significantly higher accident rates compared to fixed-wing commercial aircraft, underscoring the critical need for enhanced safety measures. While Helicopter Flight Data Monitoring programs hold promise in improving safety, their widespread adoption remains limited, partly due to challenges associated with the acquisition and analysis of flight data. This paper proposes a Deep Learning (DL) solution to address safety concerns within the rotorcraft community by efficiently acquiring and analyzing flight data for a more automated and comprehensive safety assessment. Specifically, we leverage data obtained with cost-effective off-the-shelf cameras, and process it through Convolutional Neural Networks for automated detection and classification of gauges from several helicopters' cockpits. Our DL pipeline integrates a classifier for helicopter identification, an object detector for cockpit gauges detection and classification, and a network to infer the reading
Quadrotor performance and stereoscopic particle image velocimetry (PIV) flow field wind tunnel measurements presented in this work aim to quantify rotor-rotor interactions and their manifestations for various hub spacings, including vertical offset. Three quadrotor configurations were examined; the cross configuration and two plus (+) configurations. In the cross configuration, the fore rotors were lowered relative to the aft rotors. In the Plus 1 configuration the fore and aft rotors were lowered, whereas in the Plus 2 configuration the side rotors were lowered. In the cross configuration, increases in hub spacing led to decreases in the thrust coefficient (CT ) of the fore rotors for the same rotational speed. An increase in the rotor vertical separation resulted in an increase in CT of the aft rotors of up to 24%. Results showed that large vertical rotor separation and close hub spacings yielded best performance. The side rotors in the Plus 1 and Plus 2 configurations showed
AAM concepts use multiple distributed electric motors driving propellers and rotors to augment or directly generate lift and propulsive forces. Several current concepts incorporate separate drive systems for providing vertical lift, for takeoff and landing, and propulsive thrust for wing-borne cruising flight. Measurement of loads and performance on these rotating systems is very important in both the design and development stage, as well as for certification use and ultimately supporting HUMS monitoring. However, providing instrumentation in the rotating frame and extracting their associated measurements is often problematical, as it requires some means for both power and signals to bridge the rotating interface between the blade of the rotor/propeller and the fixed frame (fuselage) system. This paper describes work conducted to leverage prior CDI development of a novel optical telemetry/instrumentation system to create a prototype unit that can support ground and flight tests
Rotorcraft shipboard operations are risky and demand high piloting skills. Computational simulations are invaluable for pilot training and understanding of the complicated aerodynamic environment. Yet, simulations may not capture a realistic response of the rotorcraft due to simplified modeling of the interactional aerodynamics. Thus, improvements to modeling and simulation are required, and experimental data are needed that unveil the interactional aerodynamics and dynamics between the rotor and ship for computational validation efforts. In this study, an extensive experimental investigation of the ship-rotor dynamic interface problem was conducted to gain a general understanding of the interactional aerodynamics between a 1:100 wind-tunnel-scale NATO Generic Destroyer and a representative single main rotor, operating both stationary and dynamically in the vicinity of the landing deck. Data obtained through simultaneous measurements of rotor hub loads, ship deck surface pressures, and
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