Pitch Angle Research Articles

Experimental Investigation on the Motion Characteristics of Air-Floating Tripod Bucket Foundation during Free Floating

In recent years, multi-bucket foundations have been studied and gradually adopted in engineering practices as a novel foundation for offshore wind turbines within a range of water depth of 30 to 50 m. This study investigated the motion characteristics of air-floating tripod bucket foundation (AFTBF) through a series of experiments during free air-floating. The experimental results show that the surge force appears to be the most important factor influencing pitch moment and motion, whether it is a change in water depth or a draft for AFTBF. The maximum amplitudes of surge acceleration and pitch angle show a trend of increasing with narrower spacing and decreasing with wider spacing, while the heave acceleration shows an opposite trend. The added mass and damping of heave motion for AFTBF increase with shallower water due to the increasing pressure difference between the inside and bottom of bucket foundation. The shallower the water depth and the larger the draft, the longer the resonance period of heave.

Modeling the Simultaneous Dropout of Energetic Electrons and Protons by Magnetopause Shadowing

AbstractMagnetopause shadowing (MPS) effect could drive a concurrent dropout of radiation belt electrons and ring current protons. However, its relative role in the dropout of both plasma populations has not been well quantified. In this work, we study the simultaneous dropout of MeV electrons and 100s keV protons during an intense geomagnetic storm in May 2017. A radial diffusion model with an event‐specific last closed drift shell is used to simulate the MPS loss of both populations. The model well captures the fast shadowing loss of both populations at L* > 4.6, while the loss at L* < 4.6, possibly due to the electromagnetic ion cyclotron wave scattering, is not captured. The observed butterfly pitch angle distributions of electron fluxes in the initial loss phase are well reproduced by the model. The initial proton losses at low pitch angles are underestimated, potentially also contributed by other mechanisms such as field line curvature scattering.

Outcomes and Safety with Utilization of Metallic Midfoot Wedges in Foot and Ankle Orthopedic Surgery: A Systematic Review of the Literature

The use of midfoot wedges for the correction of flatfeet disorders, such as progressive collapsing foot disorder, has increased greatly in recent years. However, the wedge material/composition has yet to be standardized. Metallic wedges offer advantages such as comparable elasticity to bone, reduced infection risk, and minimized osseous resorption, but a comprehensive review is lacking in the literature. Therefore, the objective of this systematic review was to organize all studies pertaining to the use of metallic wedges for flatfoot correction to better understand their efficacy and safety. This systematic review adhered to PRISMA guidelines, and articles were searched in multiple databases (PubMED, SPORTDiscus, CINAHL, MEDLINE, and Web of Science) until August 2023 using a defined algorithm. Inclusion criteria encompassed midfoot surgeries using metallic wedges, observational studies, and English-language full-text articles. Data extraction, article quality assessment, and statistical analyses were performed. Among 11 included articles, a total of 444 patients were assessed. The average follow-up duration was 18 months. Radiographic outcomes demonstrated that patients who received metallic wedges experienced improvements in lateral calcaneal pitch angle and Meary’s angle, with an enhancement of up to 15.9 degrees reported in the latter. Success rates indicated superior outcomes for metallic wedges (99.3%) compared to bone allograft wedges (89.9%), while complications were generally minor, including hardware pain and misplacement. Notably, there were no infection complications due to the inert nature of the metallic elements. This review summarizes the effectiveness, success rates, and safety of metallic wedges for flatfoot correction. Radiographic improvements and high success rates highlight their efficacy. Minor complications, including pain and mispositioning, were reported, but the infection risk remained low. Our results demonstrate that metallic midfoot wedges may be a viable option over allograft wedges with proper planning. Future research should prioritize long-term studies and standardized measures.

Robust adaptive control of underwater glider for bottom sitting-oriented soft landing

This paper deals with the formalization, design, theorization, and implementation of a robust adaptive nonlinear control scheme to solve the bottom sitting-oriented soft landing control problem for an underwater glider under model uncertainties, actuator dynamics, and external disturbances. First, uniformized motion equations are derived based on Lie derivatives for describing pitch angle and vertical velocity tracking control. Then, the robust adaptive control framework is enhanced by containing an anti-windup auxiliary system and a disturbance observer. The stability of the closed-loop control system based on Lyapunov theory is proven to guarantee the boundedness of the entire internal signals. Finally, multifarious experimental results are also conducted by a self-developed underwater glider to demonstrate the effectiveness of the proposed controller.

Characterising the effects of geometry on the natural convection heat transfer in closed even-span gable-roof greenhouses

Over the years, researchers have attempted to reduce the heat loss that arises from the natural convection in confined even-span gable-roof greenhouses due to the temperature difference between the floor and the walls (particularly at night and during winter). However, the effect that the geometry of these greenhouses has on this natural convection does not appear to have been systematically investigated.To address this, this study examined the influence of aspect ratio and roof pitch of greenhouses on the natural convection inside them. In this vein, a numerical model was developed using computational fluid dynamics (CFD) and validated against experimental data. It was found that decreasing the aspect ratio and roof pitch typically reduced the natural convection heat transfer, with changes of up to 25% for aspect ratios and 15% for roof pitch angles being observed. This suggests that a low-profile greenhouse with a low roof pitch offered the best opportunity for reducing heat loss. That said, under some conditions a multicellular flow regime can occur, and this leads to an increase in the heat transferred from the greenhouse. Hence, the choice of aspect ratio and roof pitch angle require careful consideration.Finally, a parametric relationship was developed to assist greenhouse designers determine their heat loss for a range of greenhouse geometries. Designers of greenhouses are encouraged to take advantage of the proposed relationship to develop model-based control strategies that minimize supplementary heating and deliver energy efficient greenhouses into the future.

Field-data-based validation of an aero-servo-elastic solver for high-fidelity large-eddy simulations of industrial wind turbines

Abstract. To design the next generations of wind turbines, engineers from the wind energy industry must now have access to new numerical tools, allowing the high-fidelity simulation of complex physical phenomena and thus a further calibration of lower-order models. For instance, the rotors of offshore wind turbines, whose diameters can now exceed 200 m, are highly flexible and fluid–structure interactions cannot be neglected any longer. Accordingly, this paper presents a new aero-servo-elastic solver designed to perform high-fidelity large-eddy simulation (LES) of wind turbines, as well as of rotor–wake interactions classically occurring in wind farms. In this framework, the turbine blades are modeled as flexible actuator lines. In terms of operating parameters (rotation speed and pitch angles) and power output, the solver is first validated against field data from the Westermost Rough offshore wind farm, for three different operation points. A very good agreement between the numerical results and field data is obtained. To push the validation further, additional results are compared to those given by a certified aero-servo-elastic solver used in the industry, which relies on a blade element momentum (BEM) method. The internal loads throughout the first blade and the deflections at the tip are studied in detail, and some discrepancies are observed. Of a reasonable amplitude overall, those are legitimately related to intrinsic modeling differences between the two solvers.

Observations of Relativistic Electron Enhancement and Butterfly Pitch Angle Distributions at Low L (<3)

AbstractElectrons in Earth's outer radiation belt are highly dynamic, with fluxes changing by up to orders of magnitude. The penetration of electrons from the outer belt to the inner belt is one such change observed during geomagnetic storms and was previously observed in electrons up to 1 MeV for some strong storms observed by the Van Allen Probes. We analyze pulse height analysis data from the Relativistic Electric and Proton Telescope (REPT) on the Van Allen Probes to produce electron flux measurements with lower minimum energy and significantly improved resolution compared to the standard REPT data and show that electron penetrations into the inner belt (L ≤ 2) extend to at least 1.3 MeV and penetrations into the slot region (2 < L < 2.8) extend to at least 1.5 MeV during certain geomagnetic storms. We also demonstrate that these penetrations are associated with butterfly pitch angle distributions from 1 to 1.3 MeV.

A novel 3-DOF active vibration isolation method for TBM’s laser target

In the process of full-face tunnel boring machine (TBM) tunneling, pitch angle measurement accuracy of the laser target is greatly reduced by low frequency vibrations with large amplitude and multiple degrees of freedom. In order to improve pitch angle measurement accuracy of laser target under vibration, a three-degree-of-freedom (3-DOF) active vibration isolation system is designed in this paper. A plate-type voice coil motor with large air gap and large thrust is designed based on genetic algorithm. In order to increase damping of the vibration isolation system, an eddy current damper is designed by combining copper plate and permanent magnet of the voice coil motor. An active vibration isolation device for laser target was built by using the designed plate-type voice coil motor and eddy current damper, and the dynamic model of the system was established. Aiming at control and stability problems caused by the nonlinear factors, a High-Frequency sliding mode controller which can ensure system asymptotically stable is designed in this paper. A 1–30 Hz sinusoidal sweep excitation experiment was performed on a shaking table. The experimental results show that the active vibration isolation system has a good damping effect. The root mean square (RMS) of acceleration in Y direction can be attenuated by 90.5%, in Z direction can be attenuated by 95.8%. The active isolation system effectively attenuates the vibration transmitted to the laser target, and pitch angular fluctuation of the laser target is reduced by 75.8%. The designed active vibration isolation system improves the pitch angle measurement accuracy of the laser target.

Research on ADRC algorithm for longitudinal attitude of hydrofoil craft based on improved convergence law

When a hydrofoil sails at high speed, the wave force and moment become critical factors causing instability. The longitudinal motion of the hydrofoil exhibits strong coupling and parameter uncertainty. To ensure stable sailing, a multivariate decoupling control method is proposed for the longitudinal motion of the hydrofoil. This method involves real-time estimation of the total effect of wave disturbance force and internal perturbations using a state observer, compensation for disturbances in the control loop, and the utilization of improved sliding-mode control instead of nonlinear feedback control to achieve the stabilization of the hydrofoil’s longitudinal motion. In this paper, the proposed method is simulated and analyzed using the PCH-1 boat as a model under different wave disturbance environments. The results indicate that, in comparison with active disturbance rejection control (ADRC), the heave displacement and pitch angle of the active disturbance rejection sliding mode control with improved reaching law (ADRC-ISMC) are reduced by approximately 30%–50%. This improvement is significant compared to H-∞ control and results in faster stress response. The method effectively mitigates the effect of longitudinal motion on the hydrofoil, demonstrating its effectiveness and superiority.

Hydrodynamic force on a hemispheroidal particle attached to a planar surface in linear shear flow

This paper presents a computational fluid dynamics (CFD) study of the hydrodynamic force exerted on a prolate hemispheroidal particle (as a model geometry for debris formed during glass cutting) attached to a planar solid surface under linear shear flow. The three-dimensional conservation equations for mass and momentum are solved using a finite-volume scheme on a polyhedral mesh to compute the steady flow field around the particle and determine the hydrodynamic force on the particle as a function of particle aspect ratio (ε), pitch angle (θp) with respect to the surface, and orientation angle (θf) with respect to the flow direction. The computational results are used to develop a correlation for the drag coefficient (CD) in terms of more general shape descriptors that can be used for particles of irregular shape (i.e., with no symmetry)– namely, lateral view factor (ψl), particle separation (ψs), and dimensionless hydraulic radius (ψh). Computations are also performed for several particles with irregular shapes (resembling glass debris) and the CFD results for drag coefficient are compared to predictions of the empirical correlation. The drag coefficient correlation resulting from this study will be useful for estimating the hydrodynamic drag force exerted by the flow of cleaning fluids on irregularly-shaped particles adhering to planar solid surfaces.

An improved attitude estimation algorithm for suppressing magnetic vector disturbance based on extended Kalman filter

This paper proposes an improved attitude estimation algorithm based on the extended Kalman filter (EKF), and it is applied to suppress the accuracy reduction in attitude estimation caused by fusing magnetometer data under large angular motion. In the proposed attitude estimation structure, the approximate variance of the estimated horizontal northbound magnetic vector is used to dynamically adjust the participation of magnetometer data in attitude estimation, as the approximate variance increases significantly under large angular motion and fusing magnetometer data will reduce estimation accuracy. A three-axis position-velocity controlled turntable is used to conduct rocking experiments for validating the proposed attitude estimation algorithm. The results show a significant improvement in yaw angle estimation accuracy with the proposed attitude estimation algorithm and correspondingly enhance the distribution of pitch and roll angle errors.

Optimal guidance laws for diffractive solar sails with Littrow transmission grating

The use of advanced and highly engineered membrane films in solar sail design enables the thrust vector to achieve some specific characteristics that are capable of affecting the performance of a sail-based spacecraft trajectory in a transfer mission scenario. In this field, the recently proposed diffractive sail uses metamaterial films to coat the very thin sail membrane as a potential and effective (in some mission scenarios) alternative to the more common metallic reflective coating. The purpose of this work is to study the optimal guidance law, as a function of sail pitch angle, of a diffractive sailcraft with a Littrow transmission grating film in a typical two-dimensional heliocentric transfer. In particular, the optimal steering law is obtained through a classical indirect approach, depending on the characteristics of Lawden's primer vector, either in exact (by numerical simulation) or approximate (by analytical means) form. The performance of a diffractive sailcraft with a Littrow transmission grating film is then analyzed in a number of potential mission scenarios such as, for example, a phasing in a circular orbit, an interplanetary transfer between coplanar Keplerian trajectories, a circular orbit flip maneuver, and an escape from the Solar System. Simulation results indicate that this specific diffractive sailcraft is potentially capable of executing a typical solar sail-based mission scenario with a simple steering law.

Asynchronous distributed optimal power control for fatigue load minimization in wind farms

An asynchronous distributed optimal power control (OPC) scheme is proposed to minimize fatigue load in the wind farms (WFs) in this paper. To better satisfy the grid code, each wind turbine (WT) in the scheme is equipped with an energy storage system (ESS) at the DC link of the WT converter. Based on the WT topology, a WT-ESS control model is established, thus developing an OPC scheme to control the generator torque, pitch angle, and ESS output simultaneously for reducing fatigue load. By formulating the model predicted control (MPC)-based optimal problems, the virtual mechanical power control is proposed to regulate the ESSs output for clarifying the power interactions among WTs and ESSs. In order to achieve more effective control of the above three parameters among multiple WTs-ESSs, an asynchronous distributed alternating direction method of multipliers (AD-ADMM) is developed to simultaneously minimize the variations of thrust force, shaft torque, and flapping moment load of the WTs in a wider range. Considering the impact of communication delays, the proposed AD-ADMM algorithm has the higher time efficiency and system robustness. The convergence of the proposed AD-ADMM algorithm is analyzed, and several cases are used to validate the performance of the OPC scheme.© 2017 Elsevier Inc. All rights reserved.

A Study of a Gain-Scheduled Individual Pitch Controller for an NREL 5 MW Wind Turbine

In order to reduce the asymmetric load acting on the blades of MW-class wind turbines, it is necessary to apply an individual pitch controller that independently adjusts the pitch angles of the three blades. This paper takes a new look at the relationship between the individual pitch controller applied to MW-class wind turbines and the vibration mode of the blades. The purpose of this study is to propose a method in which the individual pitch controller further reduces the 1P component of the bending moment in the out-of-plane direction acting on the blade, without exciting the in-plane vibration mode of the blade within the entire wind speed range, from the rated wind speed to the cut-out wind speed. To this end, a problem related to the excitation of the blade’s vibration mode that may occur when applying the individual pitch controller to an NREL 5 MW wind turbine is examined, and a method that uses gain scheduling to overcome this problem is presented. It is confirmed that it is possible to solve the problem of exciting the first-order vibration mode in the in-plane direction of the blade that can occur in the high wind speed range by applying the proposed gain scheduling method to the individual pitch controller aimed at reducing the 1P component of the out-of-plane bending moment of the blade.

Quantifying the impact of sensor precision on power output of a wind turbine: A sensitivity analysis via Monte Carlo simulation study

Wind turbines (WTs) are complex systems with multiple interacting components, posing challenges in identifying factors affecting power output (PO). Sensors play an important role; however, sensor precision can result in measured values differing from actual values. Analyzing the impact of sensor precision on PO is essential. In this study, we employ sensitivity analysis (SA) via Monte Carlo (MC) simulation, offering a novel approach to quantify the influence of sensor precision on the PO of a 4.8 MW WT. We focus on evaluations under 5–20 m/s wind profiles, representing partial and full load regions that portray normal operation. Based on mean squared error (MSE) and parameter sensitivity (PS) index analyses, findings show the generator speed sensor’s precision significantly impacts PO. Therefore, designers should prioritize high-impact sensors like the generator speed, while sensorless strategies may be considered as alternatives to low-impact sensors like the blade pitch angle sensor, where appropriate.

Assessment of Sensorized Insoles in Balance and Gait in Individuals With Parkinson's Disease.

Individuals with Parkinson's disease (PD) are characterized by gait and balance disorders limiting their independence and quality of life. Home-based rehabilitation programs, combined with drug therapy, demonstrated to be beneficial in the daily-life activities of PD subjects. Sensorized shoes can extract balance- and gait-related data in home-based scenarios and allow clinicians to monitor subjects' activities. In this study, we verified the capability of a pair of sensorized shoes (including pressure-sensitive insoles and one inertial measurement unit) in assessing ground-level walking and body weight shift exercises. The shoes can potentially be combined with a sensory biofeedback module that provides vibrotactile cues to individuals. Sensorized shoes have been assessed in terms of the capability of detecting relevant gait events (heel strike, flat foot, toe off), estimating spatiotemporal parameters of gait (stance, swing, and double support duration, stride length), estimating gait variables (vertical ground-reaction force, vGRF; coordinate of the center of pressure along the longitudinal axes of the feet, yCoP; and the dorsiflexion angle of the feet, Pitch angle). The assessment compared the outcomes with those extracted from the gold standard equipment, namely force platforms and a motion capture system. Results of this comparison with 9 PD subjects showed an overall median absolute error lower than 0.03 s in detecting the foot-contact, foot-off, and heel-off gait events while performing ground-level walking and lower than 0.15 s in body weight shift exercises. The computation of spatiotemporal parameters of gait showed median errors of 1.62 % of the stance phase duration and 0.002 m of the step length. Regarding the estimation of vGRF, yCoP, and Pitch angle, the median across-subjects Pearson correlation coefficient was 0.90, 0.94, and 0.91, respectively. These results confirm the suitability of the sensorized shoes for quantifying biomechanical features during body weight shift and gait exercises of PD and pave the way to exploit the biofeedback modules of the bidirectional interface in future studies.

Artificial Intelligence-Driven All-Terrain Vehicle Crash Prediction and Prevention System

HighlightsAn AI-driven system for predicting and preventing ATV crashes was developed.Machine learning model achieved rollover prediction accuracy of over 99%.The system has the potential to significantly reduce ATV-related injuries and fatalities by enabling preemptive actions.Abstract.All-Terrain Vehicle (ATV) crashes have become a public health concern in the U.S. over the past decades, resulting in numerous fatalities and hospitalizations. Most of those incidents could have been prevented if riders could better assess their ability to handle risks. Currently, risk factors associated with ATV incidents have already been studied. However, little effort has been made toward developing practical applications that assist the rider in preventing crashes. Commercial ATV safety systems, such as Farm Angel, focus on post-crash detection and emergency medical services (EMS) alerting rather than preventive measures. Machine learning prediction models can be used to assist riders in taking preventive measures to avoid an imminent crash. In this study, we developed a system that leverages the predictive power of machine learning algorithms to assess the likelihood of a crash in real-time and alert the riders, thus allowing them to prevent the crash. To the best of our knowledge, this is the only system ever developed for ATVs specifically that can predict rollover incidents. The crash likelihood is estimated by a deep neural network that considers the ride parameters (e.g., ATV speed, turning radius, and roll and pitch angles), ATV characteristics (e.g., width, length, wheelbase), and human factors (i.e., presence of a rider). The ATV characteristics and the presence of a rider are retrieved from the rider’s input through a smartphone application developed specifically for this study. The ride parameters are retrieved from an embedded system (attached to the ATV). Validation and performance tests indicated that: (1) the proposed device has a rollover prediction system with an accuracy superior to 99%; (2) the system can detect roll and pitch angles with average errors of 0.26 and 0.54 degrees, respectively; and (3) the system can detect the ATV’s speed with an average error of 0.75 m s-1. Keywords: ATV safety, Crash prediction, Machine learning, Rollover prevention.

Genetic algorithm based terahertz multifunctional reconfigurable Dirac semi-metallic coded metasurface

Digitally encoded hypersurfaces show great potential in the field of electromagne-tic wave modulation. Currently, digitally encoded hypersurfaces in the terahertz band are mainly classified into two types: structure-encoded and controllable material-encoded. Once a structure-encoded hypersurface is fabricated, its function is fixed, which makes it difficult to adapt to changing application requirements. In contrast, the controllable material-encoded hypersurfaces can achieve dynamic regulation and multifunctional switching of terahertz beams by changing the external excitation, which shows good reconfigurability. To address this challenge, a Dirac semimetal-based encoded hypersurface is proposed in this paper. The Fermi energy level of the Dirac semimetal is varied by changing the bias voltage, which in turn dynamically adjusts its relative permittivity to obtain the coded unit. Besides, the traditional gradient-phase method encodes arrays by periodically arranging the cell structure, but there are limitations in the flexibility and accuracy of beam modulation. In order to break through these limitations, this paper employs a genetic algorithm for the inverse design of hypersurface coding arrays, which effectively improves the initiative and flexibility of beam modulation. In this paper, a three-layer terahertz-encoded hypersurface unit with a “back” structure composed of Dirac semimetallic materials is firstly designed, and the Dirac semimetallic dielectric constant is dynamically adjusted by using an applied bias voltage, so that the hypersurface unit is at 1.95 THz when the Fermi energy levels are 0.01 eV, 0.05 eV, 0.09 eV, and 0.55 eV can achieve 2bit coding. The results show that, for beam configuration, single-beam and multi-beam (two-beam to five-beam) modulation can be achieved at 1.95 THz within 40° pitch angle and 360° azimuth angle; for vortex beam generation, single-vortex beams with ±1 and ±2 topological charges can be generated, with mode purity exceeding 60%, and single-vortex, double-vortex and triple-vortex beams in pitch angle and 360° azimuth angle can be realised with the vortex-phase convolution. In terms of RCS reduction, in the frequency range of 1.72–2.51 THz, the hypersurface is able to achieve more than 10 dB of RCS reduction, especially in the frequency range of 1.82 THz, the maximum reduction value is up to 27.5 dB. achieves the diversity of functions, but also has a high degree of reconfigurability to meet the needs of complex application scenarios.

On the Stability of Nonlinear Model Predictive Control for 3D Target Tracking

In this study, we present the stability analysis of a Nonlinear Model Predictive Control (NMPC) of a 3D ground target tracking system model. The system model is derived considering the 3D kinematic system model referenced to the ground target. The NMPC adeptly track errors across five states: range, bearing angle, altitude, pitch angle, and speed. This objective is achieved through the utilization of yaw angle, pitch angle, and acceleration as control inputs. The contribution of this paper is the establishment of stability conditions within the Lyapunov framework for the closed-loop system. To demonstrate the efficacy of our proposed model, we conducted simulations, which shows high accuracy in tracking all designated states.

Optimization and control strategy for wind turbine aerodynamic performance under uncertainties

Aerodynamic performance of wind turbine governs the overall energy efficiency, which has been an ever-lasting research focus in the field of wind power technology. Due to the coupling effect among the highly complex environmental and structural uncertainties, the practical aerodynamic performance may not be reliably predicted. To aggravate, this performance declines with time in service. It is of great significance to efficiently and reliably assess the impact of uncertain factors and reduce these influences on wind turbine aerodynamic performance. This paper establishes an uncertainty analysis and robustness optimization model of wind turbine aerodynamic performance considering wind speed and pitch angle error uncertainties. An approach combined the no-instrusive probabilistic collocation method is used, and the blade element momentum theory is applied to quantify influences of variable uncertainties on NREL 5 MW wind turbine aerodynamic performance. The optimization target is to reduce the sensitivity of wind turbine aerodynamic performance to uncertainties, as well as maintain capture power. The results show that the wind turbine aerodynamic and mechanical performance will be greatly affected with uncertain factors. By optimizing and adjusting wind turbine rotor speed and blade pitch angle, the wind turbine rotor power and thrust load variation can be reduced to 9.14% and 9.36%, respectively, which indeed reduces the uncertainty effects.