Pitch Rate Research Articles

On LiDAR-assisted wind turbine retrofit control and fatigue load reductions

The use of upstream wind speed measurement has motivated the development of LiDAR-assisted control for enhancing rotor speed tracking and fatigue structural load reductions. However, conventional LiDAR-assisted control designs often require altering the existing controller architecture, for example, by sending an additional feed-forward pitch angle signal to the pitch actuator or by incorporating the feed-forward pitch rate into the feedback controller. This work proposes LiDAR-assisted retrofit control solutions that can be implemented without any prior knowledge or modifications of the existing feedback controller. Specifically, the feed-forward pitch action is provoked by modifying the rotor speed measurement. Three retrofit methods are proposed according to the level of retrofit requirement and complexity. Numerical simulation results showed that all three LiDAR-assisted retrofit solutions could achieve good thrust-related load reductions. Thus, the proposed LiDAR-assisted retrofit solutions present a simple control upgrade to extend the lifetime of existing turbines.

Impact of pitch actuator fault on 10-MW semi-submersible floating wind turbine

The pitch actuator of the offshore wind turbine has a high failure rate, and this fault will lead to aerodynamic imbalance on the floating system, especially when the 10 MW wind turbine is applied. In this paper, the impact of actuator faults on the floating platform motion and turbine structure is investigated. The 10-MW OO-Star semi-submersible platform is used as the reference structure. The fault discussed in this study involved one blade seizing, followed by an emergency shutdown. Coupled non-linear aero-hydro-servo-elastic simulations were carried out in the time domain using OpenFAST. The platform motions and structural loads caused by the fault were compared with the normal operating conditions. The effects of the pitch rate at the initial fault on the loads of the critical components are presented. The results revealed that imbalanced loads due to blade seizing can lead to particularly large excitations of the dynamic responses of the wind turbine. The maximum lateral nacelle acceleration is increased by 27.9%. In addition, the parametric study on the effects of the pitch rate for feathering blade was carried out. It was found that the pitch rate of 8 deg/s is favorable to alleviate the structural loads.

UPed: A Quadruped Robot Platform to Study Directional Leg Compliance

Abstract This paper presents UPed, a quadruped robot platform, for studying passive, directional, leg compliance in robots. This work was motivated by the benefits provided by passively and directionally compliant legs in humans and animals. UPed uses under-actuated legs based on the bent-knee model which is capable of changing the direction and magnitude of the leg compliance by adjusting the knee angle and distal leg stiffness. Pneumatic pistons were chosen as variable compliance elements, enabling the leg compliance to be adjusted during locomotion. The platform was validated experimentally by evaluating how the robot’s pitch rate and cost of transport changed with variations in leg compliance and knee angle. Results of these experiments indicated that significant performance improvements are possible by selecting appropriate values of compliance and knee angle. They also demonstrated a unique capability to explore adjustable directional compliance and other parameters in robot legs on a physical robotic system. UPed has the potential to facilitate significant performance improvements of legged robots by enabling additional in-depth studies on directional passive leg compliance.

Drivers’ Visual Distraction Detection Using Facial Landmarks and Head Pose

Drivers’ distraction has been widely studied in the field of naturalistic driving studies. However, it is difficult to use traditional variables, such as speed, acceleration, and yaw rate to detect drivers’ distraction in real time. Emerging technologies have obtained features from human faces, such as eye gaze, to detect drivers’ visual distraction. However, eye gaze is hard to detect in naturalistic driving situations, because of low-resolution cameras, drivers wearing sunglasses, and so forth. Instead, head pose is easier to detect, and has correlation with eye gaze direction. In this study, city-wide videos are collected using onboard cameras from over 289 drivers representing 423 events. Head pose (pitch, yaw, and roll rates) are derived and fed into a convolutional neural network to detect drivers’ distraction. The experiment results show that the proposed model can achieve recall value of 0.938 and area under the receiver operating characteristic curve value of 0.931, with variables from five time slices (1.25 s) used as input. The study proves that head pose can be used to detect drivers’ distraction. The study offers insights for detecting drivers’ distraction and can be used for the development of advanced driver assistance systems.

Numerical estimation of longitudinal damping derivatives of a flying wing micro aerial vehicle

Longitudinal damping derivatives, [Formula: see text], of an aerial vehicle is important from an aerodynamic stability point of view. Experimental calculation of longitudinal damping derivatives using wind tunnel is not a cost-effective method; therefore, researchers have developed numerical solutions as an alternative. In this research, the longitudinal damping derivatives of a flying wing micro aerial vehicle (FWMAV) were calculated using numerical simulations by adopting pull-up maneuver and forced harmonic motion in pitch axis. Pull-up maneuver with four steady rotational rates was simulated to obtain pitch rate derivative, C mq. Combined derivative, [Formula: see text], was obtained by simulating forced harmonic motion of FWMAV around a mean angle of attack of 0° with amplitude of oscillation of ± 3° using four reduced frequencies (0.02, 0.03, 0.04, and 0.05). Unstructured surface and volume mesh was used in a spherical domain engulfed inside a large cuboid domain for moving reference frame strategy. Reynolds number taking mean aerodynamic chord as a reference length was 2.33 × 105. Spalart–Allmaras turbulence model was used. Pitch rate derivative, combined derivative, and acceleration derivative were found as − 0.03/rad, − 7.39/rad, and − 7.36/rad, respectively, by the use of a phase method at a reduced frequency of 0.03. During flight dynamic analysis, it was found that [Formula: see text] has a significant contribution on damping in short period mode with no effect on Phugoid mode. The research concluded that for tailless configurations, acceleration derivative [Formula: see text] can exist and can provide necessary damping in the longitudinal flight mode.

Influence of Varying Fermentation Parameters of the Yeast Strain Cyberlindnera saturnus on the Concentrations of Selected Flavor Components in Non-Alcoholic Beer Focusing on (E)-β-Damascenone.

The diversification of beer flavor is becoming increasingly popular, especially in the field of non-alcoholic beers, where sales are growing steadily. While flavor substances of traditional beers can largely be traced back to defined secondary metabolites, the production of non-alcoholic beers with non-Saccharomyces yeasts generates novel fruity flavors, some of which cannot yet be assigned to specific flavor substances. In a recently published study, besides pear, cool mint sweets, and banana-like flavor, distinctive red berry and apple flavors were perceived in a non-alcoholic beer fermented with the yeast strain Cyberlindnera saturnus TUM 247, whose secondary metabolites were to be elucidated in this study. The trials were carried out using response surface methodology to examine the fermentation properties of the yeast strain and to optimize the beer with maximum fruitiness but minimal off-flavors and ethanol content. It turned out that a low pitching rate, a moderate fermentation temperature, and an original gravity of 10.5 °P gave the optimal parameters. Qualitative analysis of the secondary metabolites, in addition to standard analysis for traditional beers, was first performed using headspace-gas chromatography with olfactometry. (E)-β-damascenone emerged as the decisive substance for the red berry and apple flavor and so this substance was then quantitated. Although (E)-β-damascenone is a well-known secondary metabolite in beer and this substance is associated with apple or cooked apple- and berry-like flavors, it has not yet been reported as a main flavor component in non-alcoholic beers.

Electron Diffusion by Magnetosonic Waves in the Earth’s Radiation Belts

AbstractWe conduct a global survey of magnetosonic waves and compute the associated bounce‐ and drift‐averaged diffusion coefficients, taking into account colocated measurements of fpe/fce, to assess the role of magnetosonic waves in radiation belt dynamics. The average magnetosonic wave intensities increase with increasing geomagnetic activity and decreasing relative frequency with the majority of the wave power in the range fcp < f < 0.3fLHR during active conditions. In the region 4.0 ≤ L* ≤ 5.0, the bounce‐ and drift‐averaged energy diffusion rates due to magnetosonic waves never exceed those due to whistler mode chorus, suggesting that whistler mode chorus is the dominant mode for electron energization to relativistic energies in this region. Further in, in the region 2.0 ≤ L* ≤ 3.5, the bounce‐ and drift‐averaged pitch angle diffusion rates due to magnetosonic waves can exceed those due to plasmaspheric hiss and very low frequency (VLF) transmitters over energy‐dependent ranges of intermediate pitch angles. We compute electron lifetimes by solving the 1D pitch angle diffusion equation including the effects of plasmaspheric hiss, VLF transmitters, and magnetosonic waves. We find that magnetosonic waves can have a significant effect on electron loss timescales in the slot region reducing the loss timescales during active times from 5.6 to 1.5 days for 500 keV electrons at L* = 2.5 and from 140.4 to 35.7 days for 1 MeV electrons at L* = 2.0.

Crash Test Methodology for Electric Scooters with Anthropomorphic Test Device (ATD) Riders

<div class="section abstract"><div class="htmlview paragraph">As micromobility devices (i.e., e-bikes, scooters, skateboards, etc.) continue to increase in popularity, there is a growing need to test these devices for varying purposes such as performance assessment, crash reconstruction, and design of new products. Although tests have been conducted across the industry for electric scooters (e-scooters), this paper describes a novel method for crash testing e-scooters with anthropomorphic test devices (ATDs) “riding” them, providing new sources for data collection and research. A sled fixture was designed utilizing a pneumatic crash rail to propel the scooters with an overhead gantry used for stabilization of the ATD until release just prior to impact. The designed test series included impacts with a 5.5-inch curb at varying incidence angles, a stationary vehicle, or a standing pedestrian ATD. Test parameter permutations included changing e-scooter tire sizes, impact speeds, and rider safety equipment. One of the primary focuses of this testing was to establish a methodology which provided consistency in not only impact speed but also ATD orientation and scooter-to-obstacle contact.</div><div class="htmlview paragraph">Over the course of this research, 23 tests were conducted, consisting of 14 curb impacts, five vehicle impacts, and four pedestrian ATD impacts. A SLICE Micro data acquisition system was rigidly mounted on the rear deck region of the scooter and recorded accelerations in the longitudinal, lateral, and vertical directions in addition to yaw, pitch, and roll rates at a frequency of 10 kHz. Tape switches were used as a redundant confirmation of impact speed in addition to high-speed camera views with a calibrated checkerboard for independent analyses. This paper describes the test methodology in detail, provides a summary of test observations, and discusses additional potential uses for such a test system.</div></div>

Data-driven model for accommodation of faulty angle of attack sensor measurements in fixed winged aircraft

On March 10, 2019, Ethiopian Airlines’ Boeing 737-8 MAX nose-dived and crashed shortly after takeoff in the south-east of Addis Ababa, near Ejere Town. The cause of the crash was a faulty angle of attack (AOA) sensor. In the past, many aircraft accidents were associated with faulty AOA sensors. The literature uses triplex and duplex AOA sensor fault detection, isolation, and accommodation (SFDIA). The triplex voting mechanism uses three AOA sensors. A critical problem with the triplex method is that the consolidated value inherently depends on the sensor measurements. This problem makes fault detection and isolation susceptible to simultaneous failure. The duplex fault detection and isolation uses two sensors, reducing cost and providing lower protection. We propose using two AOA sensors and a virtual AOA sensor for faulty AOA SFDIA. The proposed faulty AOA sensor detection and isolation algorithm is based on conventional residual analysis with a fixed threshold for faulty AOA sensor detection and isolation. The virtual sensor is a data-driven model based on a recurrent neural network (RNN) for AOA accommodation. We use a combination of simple RNN (sRNN) and gated recurrent units (GRU). The model aims to effectively use the encoder–decoder behavior of the GRU for better AOA accommodation in the case of faulty AOA measurement, faulty velocity measurement, and faulty pitch rate measurement. Test results show that the proposed method can detect, isolate, and accommodate faulty AOA sensors with a lower number of false alarms than a model that uses only long-term memory (LSTM).

Data-driven control of the coupled loads for floating wind turbine systems based on deformable trailing edge flaps

Load controller design for floating wind turbine systems (FWTS) poses unique challenges owing to the couplings of platform motions, blade loads and rotor power. Any controller based on a single objective is likely to worsen other performance metrics. This paper presented a data-driven control system to comprehensively handle that muti-objective coupling problem. The control system was realized by introducing a model free adaptive control (MFAC) based on deformable trailing edge flap (DTEF) and a feedback compensation in the blade pitch control loop. The identification error and actuator saturation were considered while designing the control law. The proposed control system was numerically tested in the modified FAST code equipped with DTEF interfaces. Numerical results showed considerable load reductions on blades and floating platforms at the cost of the added DTEF actuation and a minor increase in blade pitch rate. Moreover, the generator power fluctuations and the fatigue loading on drive train and tower were also alleviated. In addition, the synchronous aero-hydro-elastic coupling relationships in the wind-blade-wave-platform system were impaired by introducing the servo-dynamics of DTEF and blade pitch feedback compensation. Hence the total energy flowing into FWTS was dissipated.

Comparative Study of Quasi Steady and Unsteady Damping Derivatives for Delta Wings in Hypersonic Flow for Half Sine Wave

Correlation investigation of quasi-steady and unsteady damping derivatives of delta wing is analyzed and contemplated, with leading edges bent in the current paper. The current paper realizes that the quasi-steady damping derivative considers only the rate of pitch, not the rate of the angle of attack. In contrast, unsteady damping derivatives account for pitch rate and the rate of the angle of attack. Results show a reformist reduction in the damping derivatives as the Mach number increases in quasi-steady and unsteady cases. Outcomes are computed for a varied range of Mach Numbers and deflection angles due to the pitch rate of different amplitudes of half-sine waves. The outcomes for the damping derivative for a fixed pivot position show different behaviour for different values of the flow deflection angles observed here. As in straight leading edge, even in the curved leading edge, steady-state is attained earlier in quasi-steady than unsteady.

Characterizing the suckling behavior by video and 3D-accelerometry in humpback whale calves on a breeding ground.

Getting maternal milk through nursing is vital for all newborn mammals. Despite its importance, nursing has been poorly documented in humpback whales (Megaptera novaeangliae). Nursing is difficult to observe underwater without disturbing the whales and is usually impossible to observe from a ship. We attempted to observe nursing from the calf’s perspective by placing CATS cam tags on three humpback whale calves in the Sainte Marie channel, Madagascar, Indian Ocean, during the breeding seasons. CATS cam tags are animal-borne multi-sensor tags equipped with a video camera, a hydrophone, and several auxiliary sensors (including a 3-axis accelerometer, a 3-axis magnetometer, and a depth sensor). The use of multi-sensor tags minimized potential disturbance from human presence. A total of 10.52 h of video recordings were collected with the corresponding auxiliary data. Video recordings were manually analyzed and correlated with the auxiliary data, allowing us to extract different kinematic features including the depth rate, speed, Fluke Stroke Rate (FSR), Overall Body Dynamic Acceleration (ODBA), pitch, roll, and roll rate. We found that suckling events lasted 18.8 ± 8.8 s on average (N = 34) and were performed mostly during dives. Suckling events represented 1.7% of the total observation time. During suckling, the calves were visually estimated to be at a 30–45° pitch angle relative to the midline of their mother’s body and were always observed rolling either to the right or to the left. In our auxiliary dataset, we confirmed that suckling behavior was primarily characterized by a high average absolute roll and additionally we also found that it was likely characterized by a high average FSR and a low average speed. Kinematic features were used for supervised machine learning in order to subsequently detect suckling behavior automatically. Our study is a proof of method on which future investigations can build upon. It opens new opportunities for further investigation of suckling behavior in humpback whales and the baleen whale species.

Unveiling the reasoning processes of robots through introspective dialogues in a storytelling system: A study on the elicited empathy

The work studies the empathy elicited by a storytelling system in which the characters in the story are interpreted by humanoid robots and modelled as cognitive agents. The ACT-R architecture is exploited to shape the characters’ personalities and equip them with knowledge and behaviours typical of social practices. The narration is enriched with gestures and emotional expressions obtained by setting parameters that can be correlated to some emotions, such as the pitch and speech rate, the LEDs colour and the head inclination. The system has been evaluated by comparing a simple narrative modality with an enhanced one, where an introspective dialogue is adopted to explain and let transparent the internal reasoning processes of the characters. The obtained results show that storytelling affected the cognitive component of empathy, especially through the advanced narrative mode.

Control Considerations for Very Large Floating Wind Turbines

Increasingly large floating wind turbines (FWTs) are being introduced to access the offshore wind resource over deep water at lower cost. In connection with designing a 25 MW semi-submersible wind turbine, we examine the scaling trends associated with the dynamic performance of the generator torque and blade pitch controllers and highlight the challenges that may be encountered for such devices. The increased rotor inertia, reduced blade pitch rates, longer platform pitch and surge natural periods, and flexible modes of the tower, platform, and rotor all affect the ability of the controller to track the desired rotor speed. The effects of control design and tuning choices on the FWT behavior in representative wind and wave conditions are shown.

Comparative Study of Machine Learning Modeling for Unsteady Aerodynamics

Modern fighters are designed to fly at high angle of attacks reaching 90 deg as part of their routine maneuvers. These maneuvers generate complex nonlinear and unsteady aerodynamic loading. In this study, different aerodynamic prediction tools are investigated to achieve a model which is highly accurate, less computational, and provides a stable prediction of associated unsteady aerodynamics that results from high angle of attack maneuvers. These prediction tools include Artificial Neural Networks (ANN) model, Adaptive Neuro Fuzzy Logic Inference System (ANFIS), Fourier model, and Polynomial Classifier Networks (PCN). The main aim of the prediction model is to estimate the pitch moment and the normal force data obtained from forced tests of unsteady delta-winged aircrafts performing high angles of attack maneuvers. The investigation includes three delta wing models with 1, 1.5, and 2 aspect ratios with four determined variables: change rate in angle of attack (0 to 90 deg), non-dimensional pitch rate (0 to .06), and angle of attack. Following a comprehensive analysis of the proposed identification methods, it was found that the newly proposed model of PCN showed the least error in modeling and prediction results. Based on prediction capabilities, it is seen that polynomial networks modeling outperformed ANFIS and ANN for the present nonlinear problem.

Load mitigation method for wind turbines during emergency shutdowns

Wind turbines experience countless shutdowns during their lifetimes. A shutdown is a transient process characterised by a pitch-to-feather manoeuvre of three blades. Such a pitch manoeuvre is often collective, open-loop, and can substantially slow the rotor speed within several seconds. However, undesirable structural responses may arise because of the imbalanced aerodynamic loads acting on the rotor. To address this issue, this paper proposes a method that actively adjusts the individual pitch rate of each blade during an emergency shutdown. This method is founded on a minimal intervention principle and uses the blade-root bending moment measurements as the only inputs. The control objective is to minimise the differences in the blade-root flapwise bending moment among the three blades during the shutdown. Using a high-fidelity aeroelastic model, we demonstrate the controller performance under representative steady wind conditions with vertical wind shear. Compared with the baseline shutdown strategy, the proposed method effectively reduces the maximum nontorque bending moment at the main shaft and the tower bottom bending moment; the reductions vary between 10% and 40% under the investigated conditions. The present work can be further extended to reduce structural fatigue damages or to handle complex loading scenarios of offshore wind turbines during shutdowns.

Angle of attack prediction using recurrent neural networks in flight conditions with faulty sensors in the case of F-16 fighter jet

The angle of attack (AOA) is one of the critical parameters in a fixed-wing aircraft because all aerodynamic forces are functions of the AOA. Most methods for estimation of the AOA do not provide information on the method’s performance in the presence of noise, faulty total velocity measurement, and faulty pitch rate measurement. This paper investigates data-driven modeling of the F-16 fighter jet and AOA prediction in flight conditions with faulty sensor measurements using recurrent neural networks (RNNs). The F-16 fighter jet is modeled in several architectures: simpleRNN (sRNN), long-short-term memory (LSTM), gated recurrent unit (GRU), and the combinations LSTM-GRU, sRNN-GRU, and sRNN-LSTM. The developed models are tested by their performance to predict the AOA of the F-16 fighter jet in flight conditions with faulty sensor measurements: faulty total velocity measurement, faulty pitch rate and total velocity measurement, and faulty AOA measurement. We show the model obtained using sRNN trained with the adaptive momentum estimation algorithm (Adam) produces more exact predictions during faulty total velocity measurement and faulty total velocity and pitch rate measurement but fails to perform well during faulty AOA measurement. The sRNN-GRU combinations with the GRU layer closer to the output layer performed better than all the other networks. When using this architecture, the correlation and mean squared error (MSE) between the true (real) value and the predicted value during faulty AOA measurement increased by 0.12 correlation value and the MSE decreased by 4.3 degrees if one uses only sRNN. In the sRNN-GRU combined architecture, moving the GRU closer to the output layer produced a model with better predicted values.

읽기장애아동과 일반아동의 통사적 다양성에 따른 운율 특성 비교*

Proper prosody in reading allows the reader to naturally convey the meaning, which manifests as changes in pitch, loudness, and speech rate. Children with reading disability face difficulty in delivering information due to poor prosody. This study identified the difference in prosodic features between children with reading disabilities and nondisabled children through means of reading tasks. Reading tasks, according to sentence types (short sentences, assumptions/ conditions, intentions, relative-clause), were recorded by 15 children studying in the 3rd to 6th grade in elementary school. Children with reading disability had a statistically significant wider range of pitch, slower speech rate, more frequent usage of pauses, longer total pause duration, and steeper pitch slope than nondisabled one in sentence-final and -medial words. Children with reading disability, therefore, exhibited a less natural and expressive reading than nondisabled children. Through this study, the characteristics of prosody observed in children with reading disability were identified and the need for an approach for effective intervention was also suggested.

Voice Performance Chart: A Pedagogical Tool to Enhance Vocal Expressive Ability in Acting Students.

The purpose of the present study was to explore the effectiveness of the Voice Performance Chart (VPCH) as a pedagogical training tool to enhance vocal expressive ability of 1st year acting students. Forty recorded audio samples were perceptually assessed by six blinded raters, using a five-points Likert scale for each of the dependent variables observed. Results showed that loudness, pitch, and speech rate variations significantly differ when comparing the vocal condition before and after a 11 weeks training period. That suggests that VPCH can be an effective pedagogical tool to develop vocal expressive capabilities of acting students, by enhancing their expressive nuances level, according to the text content. Additionally, it might be argued that VPCH is an effective pedagogical tool not only for acting students, but also for individuals from any discipline requiring the use of the spoken voice in a professional context and/or in an expressive sense.

Предотвращение колебаний, вызванных летчиком при посадке воздушного судна

The paper focuses on a manned aircraft landing control system. It is known that actuator level and rate limitations can cause pilot-induced oscillations. This phenomenon occurs during intensive pilot control in a closed-loop system under certain initiating conditions associated with both the influence of the external environment and changes in the system dynamics. Oscillations appear unintentionally and unexpectedly for the pilot, which jeopardizes flight safety. The study shows the possibility of preventing aircraft oscillations using the method of nonlinear correction of systems by sequential introduction of a pseudo-linear correcting device into the control loop, the phase-frequency characteristic of the device not depending on the amplitude of the input signal. The airplane-pilot closed-loop system for various parameters of the input signal is analyzed by calculating the generalized function of sensitivity and the excitation index. The results of the study are presented in the form of angle and the pitch rate time processes, and landing trajectories.