Speed Fluctuations Research Articles

Signatures of geostrophic turbulence in power spectra and third-order structure function of offshore wind speed fluctuations

We analyze offshore wind speeds with a time resolution of one second over a long period of 20 months for different heights above the sea level. Energy spectra extending over more than seven decades give a comprehensive picture of wind fluctuations, including intermittency effects at small length scales and synoptic weather phenomena at large scales. The spectra S(f) show a scaling behavior consistent with three-dimensional turbulence at high frequencies f, followed by a regime at lower frequencies, where fS(f) varies weakly. Lowering the frequency below a crossover frequency f_mathrm{scriptscriptstyle 2D}, a rapid rise of fS(f) occurs. An analysis of the third-order structure function D_3(tau ) of wind speed differences for a given time lag tau shows a rapid change from negative to positive values of D_3(tau ) at tau simeq 1/f_mathrm{scriptscriptstyle 2D}. Remarkably, after applying Taylor’s hypothesis locally, we find the third-order structure function to exhibit a behavior very similar to that obtained previously from aircraft measurements at much higher altitudes in the atmosphere. In particular, the third-order structure function grows linearly with the separation distance for negative D_3, and with the third power for positive D_3. This allows us to estimate energy and enstrophy dissipation rates for offshore wind. The crossover from negative to positive values occurs at about the same separation distance of 400 km as found from the aircraft measurements, suggesting that this length is independent of the altitude in the atmosphere.

Inertia compensation for wind turbine emulator based on anticipation deviation suppression

The wind turbine emulator (WTE) is an important tool for dynamic emulation experiments of wind turbines. This paper studies the problem of high-frequency fluctuation of the rotating speed of the dynamic emulation platform when emulating the mechanical dynamics of large inertia wind turbine under fluctuating wind speed. Through the time domain analysis of the discrete mathematical model of the WTE, it is found that the torque compensation loop of the transmission system will incur the acceleration deviation because of the influence of the time delay, and this anticipatory deviation increases with the increase of the compensation multiple. As a result, the acceleration of the transmission chain oscillates, resulting in high-frequency fluctuations in the rotational speed. To this end, this paper proposes an inertia compensation scheme for the WTE based on the anticipation deviation suppression. Based on the principle of zero-pole configuration, a feedforward suppressor is designed to offset the zero-pole of the closed-loop transfer function of the transmission chain system, in order to eliminate the high-frequency fluctuation of the rotating speed caused by the torque deviation. The effectiveness of the proposed strategy is validated using the maximum power point tracking control experiment.

A novel spatio-temporal generative inference network for predicting the long-term highway traffic speed

Accurately predicting the highway traffic speed can reduce traffic accidents and transit time, which is of great significance to highway management. Three essential elements should be considered in the long-term highway traffic speed prediction: (1) adaptability to speed fluctuation, (2) exploring the spatio-temporal correlation effectively, and (3) prediction of non-error propagation. This paper proposes a novel spatio-temporal generative inference network (STGIN) driven by data and long-term prediction. STGIN consists of three parts; semantic enhancement, spatio-temporal correlation extraction block (ST-Block), and generative inference. Semantic enhancement is first used to model the contextual semantics of traffic speed, improving the adaptability to speed fluctuations. The ST-Block is then used to extract the spatio-temporal correlations of the highway network. Finally, generative inference is used to pay attention to the correlation between historical- and target-sequences to generate the target hidden outputs rather than a dynamic step-by-step decoding way; it avoids long-term prediction error propagation in the spatial and temporal dimensions. The evaluation experiments use the monitoring data of highway in Yinchuan City, Ningxia Province, China. For long-term highway speed prediction, the experimental results demonstrate that the performance of the proposed method is better than that of the baseline methods.

Stability of nonlinear electromechanical systems with a magnetic gearbox

On the basis of the block diagram of an open-loop electromechanical system with a radial magnetic gearbox, its absolute stability is proved, taking into account the nonlinearity of the magnetic coupling. In the Simulink MatLab objectvisual modeling environment, a dynamic model of an electromechanical system is implemented. The transient response confirms the presence of significant speed fluctuations at the output of an open loop system. Keywords: magnetic reducer, two-mass system, elastic connection, block diagram, transfer function, stability, Popov's method. sapsalevav@ngs.ru, kharit1@yandex.ru, achitaevaa@gmail.com

Nocturnal Turbulence at Jezero Crater as Determined From MEDA Measurements and Modeling

AbstractMars 2020 Mars Environmental Dynamics Analyzer (MEDA) instrument data acquired during half of a Martian year (Ls 13°–180°), and modeling efforts with the Mars Regional Atmospheric Modeling System (MRAMS) and the Mars Climate Database (MCD) enable the study of the seasonal evolution and variability of nocturnal atmospheric turbulence at Jezero crater. Nighttime conditions in Mars's Planetary Boundary Layer are highly stable because of strong radiative cooling that efficiently inhibits convection. However, MEDA nighttime observations of simultaneous rapid fluctuations in horizontal wind speed and air temperatures suggest the development of nighttime turbulence in Jezero crater. Mesoscale modeling with MRAMS also shows a similar pattern and enables us to investigate the origins of this turbulence and the mechanisms at play. As opposed to Gale crater, less evidence of turbulence from breaking mountain wave activity was found in Jezero during the period studied with MRAMS. On the contrary, the model suggests that nighttime turbulence at Jezero crater is explained by increasingly strong wind shear produced by the development of an atmospheric bore‐like disturbance at the nocturnal inversion interface. These atmospheric bores are produced by downslope winds from the west rim undercutting a strong low‐level jet aloft from ∼19:00 to 01:00 LTST and from ∼01:00 LTST to dawn when undercutting weak winds aloft. The enhanced wind shear leads to a reduction in the Richardson number and an onset of mechanical turbulence. Once the critical Richardson Number is reached (Ri ∼ <0.25), shear instabilities can mix warmer air aloft down to the surface.

Warm-core eddy effects on sound propagation in the South China sea

The spatial and temporal redistribution of sound energy caused by a warm eddy was measured via a multiday experiment conducted in the South China Sea, utilizing two vertical line arrays, a mooring source, and some wide-band explosive sources. In the experiment area, a warm eddy was identified and tracked using an automatic detection method combined with the empirically reconstructed data. During the experimental period, the warm eddy diminished in size and kinetic energy until it vanished. The influence of the warm eddy on sound propagation during its lifespan is comprehensively analyzed and explained. The experimental acoustic results and simulations based on dynamic hydrographic data demonstrate that energy is redistributed both spatially and temporally due to the presence of the warm eddy. In comparison to the environment without an eddy, the first convergence zone disappears and the high-energy region appears in the typical position of the first shadow zone. The oscillating disturbance in energy is mainly affected by the fluctuation of sound speed caused by the warm eddy.

Dynamic modeling and neural network compensation for dual-flexible servo system with an underactuated hand

This paper investigates a difficult problem of nonlinear dynamics and motion control of a dual-flexible servo system with an underactuated hand (DFSS-UH). Variation in grasping mass and nonlinear factors of the DFSS-UH including complex flexible deformation and friction torque aggravate the output speed fluctuation, leading to modeling errors in the dynamics, which in turn affects the underactuated hand motion accuracy. A novel neural network sliding mode control (NNSMC) method is designed to control the DFSS-UH. The strategy utilizes neural networks to compensate for dynamics modeling errors, which takes into account neglected nonlinear factors and inaccurate friction torque. The reaching law with the hyperbolic tangent function is proposed to improve sliding mode control, thereby weakening the chattering phenomenon. First of all, the DFSS-UH mechanical model considering many nonlinear factors is established and a dynamic simplification model which ignores higher-order modes is proposed. Secondly, the adaptive law of weighted coefficients is proposed according to the stability of the DFSS-UH. Finally, the physical control platform of the DFSS-UH is built, and simulation and control experiments are conducted. Experimental results show that the improved NNSMC strategy decreases the tracking error of flexible load, thereby enhancing the control accuracy of the DFSS-UH.

The role of seasonal circulation in the variability of dynamic parameters of internal solitary waves in the Sulu Sea

In-situ observations of the Sulu Sea internal solitary waves (ISWs) are too limited to reveal their variability. In this study, based on verified model reanalysis data, we study the variability of three basic dynamic parameters of ISWs, i.e., linear phase speed, nonlinear and dispersive coefficients, affected by the Sulu Sea circulations. Overall, the linear speed and dispersive coefficient of ISWs modulated by the annual-mean Sulu Sea circulation decrease, while the nonlinear coefficient increases, and these variations are largely attributed to the variable stratification rather than current. Particularly, at the deep basin and near the western boundary of the Sulu Sea, the modulated climatological annual-mean linear phase speed reduces at least ∼10% of that resulted from only topography, while at the deep basin the modulated dispersive (nonlinear) coefficient has a significant decrease (increase) up to approximately 25–30% (20–30%) relative to that resulted from only topography. Moreover, the first EOF mode of the three ISW dynamic parameters, dominant in winter and summer, reflects the modulation of the Sulu Sea basin-scale circulation, while the second EOF mode, dominant in spring and autumn, illustrates the modulation associated with the meander flow along the western boundary. Specifically, it is found that the seasonal cycles of linear phase speed (nonlinear and dispersive coefficients) are largely attributed to the variable current (stratification) induced by the seasonal circulations. The circulation-induced peak-to-peak fluctuations of linear speed, nonlinear and dispersive coefficients reach up to ∼15%, ∼30% and ∼20%, respectively, of those resulted from only topography.

Dynamic response analysis of scraper conveyor under the condition of chain broken

In view of the fact that the traditional study of the chain breaking condition of the scraper conveyor only considers the case of two-way simultaneous chain breaking, this paper mainly studies the single-side chain breaking condition and its influence on the longitudinal vibration and swing vibration characteristics of the scraper chain system. Using the tension calculation principle of the point-by-point tension method, each section of the scraper in the study area is taken as a unit. A coupled dynamic model of longitudinal and oscillating vibration of scrapers is established and connected with Voigt model. The dynamic response laws of the longitudinal and oscillating vibration of the scraper before and after the chain fracture under different transportation conditions are numerically simulated. The calculation results show that when there is material behind the broken chain, the longitudinal tension of the chain and the oscillating vibration of the scraper reach the maximum value, and the chain speed fluctuation reaches 543.1 % compared with the normal operating conditions. Only when there is material in front of the broken chain, the longitudinal tension mutation of the chain and the oscillating vibration value of the scraper are weaker than those of the previous working conditions. When there are materials at the front and back of the broken chain, the sudden change of the longitudinal tension of the chain and the oscillating vibration value of the scraper are the minimum, but they also reach twice the normal working condition, and the chain speed fluctuation reached 194.4 %. The research results of this paper provide a theoretical basis for grasping the operation status of the scraper conveyor in the coal mine and predicting the life of the scraper conveyor.

A Sage-Husa Prediction Algorithm-Based Approach for Correcting the Hall Sensor Position in DC Brushless Motors.

Accurate knowledge of the rotor position is essential for the control of brushless DC motors (BLDCM). Any deviation in this identification can cause fluctuations in motor current and torque, increase noise, and lead to reduced motor efficiency. This paper focused on a BLDCM equipped with a three-phase binary Hall sensor. Based on the principle of minimum deviation, this paper estimated the relative installation offset between the Hall sensors. It also provided a clear method for ideal phase commutation position recognition and eliminated the Hall sensor installation position deviation. The proposed pre-calibration method identified and eliminated the offset of the permanent magnet poles, the delay time caused by the Hall signal conditioning circuit, and the offset of the sensor signal identification due to armature response under different loads. Based on the pre-calibration results, a correction strategy for correcting the rotor position information of BLDCMs was proposed. This paper presented a self-adaptive position information prediction algorithm based on the Sage-Husa method. This filters out rotor position information deviations that are not eliminated in pre-calibration. Experimental results on a hydrogen circulation pump motor showed that, after the pre-calibration method was adopted, the Mean Square Error (MSE) of motor speed fluctuations decreased by 92.0%, motor vibration was significantly reduced, average phase current decreased by 62.8%, and the efficiency of the hydrogen circulation pump system was significantly improved. Compared to the traditional KF prediction algorithm, the Sage-Husa adaptive position information prediction algorithm reduced the speed fluctuation during the uniform speed operation stage and speed adjustment stage, the speed curve overshoot, and the commutation time deviation throughout the process by 44.8%, 56.0%, 54.9%, and 14.7%, respectively. This indicates a higher disturbance rejection ability and a more accurate and stable prediction of the commutation moment.

New technique for improving transient stability of standalone microgrid using superconductor fault current limiter

This study proposes a new insertion topology for Superconductor Fault Current Limiter (SFCL) to maintain and enhance the transient stability of a wind generation system in a standalone microgrid. The proposed topology is inserting the SFCL in series with the faulty phase only. The new insertion topology performance is compared with the traditional insertion method. The proposed insertion topology of the SFCL displays excellent performance compared to the traditional method. The overall performance of the Micro-Grid is improved. The performance of the wind generator is improved dramatically after employing the proposed controller. The proposed insertion topology suppresses the fluctuations of the wind generator speed (from ± 6% to less than ± 1%) as well as the post fault wind generator real power and imaginary power. For a single line to ground fault, the wind generator active power fluctuates between + 80 kW, and − 40 kW with traditional SFCL insertion topology. When using the proposed insertion topology, the wind generator active power fluctuates between + 27 kW, and + 12 kW. Also, the proposed SFCL insertion topology mitigates the fluctuations in voltage, real power and imaginary power not only at the generator bus but also at all other Micro-Grid buses (PV bus, and storage batteries bus). The voltage at all buses recover to steady state values fast (0.01 s) compared with the recovering time when using the traditional method (nearly 1 s). The proposed method is very simple and low cost because there is no additional hardware is required. This fact makes the proposed method highly attractive from the economical and implementation point of views.

Information theory-based dynamic feature capture and global multi-objective optimization approach for organic Rankine cycle (ORC) considering road environment

Efficient capture and global optimization of organic Rankine cycle (ORC) operating features in road environment is the key to obtain actual waste heat recovery potential. The complexity of time-varying characteristics intensifies the nonlinear coupling relationship between ORC performance and parameters. This paper first designs and builds an ORC experimental system for recovering waste heat from internal combustion engine (ICE). The experimental system includes ICE and its measurement subsystem, ORC subsystem, expander lubrication subsystem, cooling subsystem, and ORC measurement subsystem. R245fa is used as working fluid; The expander adopts a specially designed single screw expander. The performance of ORC waste heat recovery is tested by adjusting the operating conditions of the ICE, expander, pump, and valve opening. The temperature range of waste heat is 627–686 K. Subsequently, a dynamic feature capture and global multi-objective optimization approach for ORC is proposed. The results show that the precision of dynamic feature capture can be improved at least 41.78% with the introduction of information theory in complex environment. Frequent fluctuation of vehicle speed is not conducive to the improvement of evaporator inlet temperature at working fluid side. As the speed of the vehicle is greatly reduced, the evaporator inlet temperature drops sharply. The frequent fluctuation of speed will intensify the nonlinear correlation between operating parameters and system performance and make the system performance more dependent on the coupling correlation between operating parameters. The approach proposed in this paper can provide a new idea for efficient capture of dynamic characteristics and global multi-objective optimization of ORC in road environment.

Adaptive time-domain sliding average method for spall size estimation of roller bearing with skidding

The size of the bearing spall fault can be estimated by the time interval between the roller's entry and exit points in the bearing vibration signal. However, the entry vibration response is typically low amplitude and masked in environmental noise. The time-domain average (TDA) method is effective for periodic impulse enhancement. However, bearing skidding is unavoidable during its running, and the cage's speed fluctuations caused by skidding will lead to non-periodicity of the impulses. The performance of TDA seriously deteriorated with such skidding because of the time-varying period. This paper presents the adaptive time-domain sliding average (ATDSA) method to address the bearing skidding problem. The similarity feature between each impulse segment is utilized, and a time delay matrix is constructed to estimate the skidding rate and mitigate the skidding effect. The frequency spectrum of the reconstructed signal shows clear sidebands with BCF interval. And the obtained averaged waveform has high resolution in both the low-frequency entry and high-frequency exit events. Simulation and experiment results show that it can effectively suppress the skidding effect and estimate the spall size correctly under different speeds.

Intelligent algorithms for incident detection and management in smart transportation systems

Prior research on traffic event detection has encountered two problems: limited sample numbers and unbalanced datasets. Moreover, the real-time properties of event detection models must be enhanced to meet traffic management demands. To solve these issues, suitable measures must be implemented, like developing an intelligent algorithm for incident detection employing Artificial Intelligence (AI) and Machine Learning (ML). Automated Incident Detection (AID) methods are the focus of current Intelligent Transportation System (ITS) technology. Modern vehicles can connect with one other and with Roadside Infrastructure Units (RSUs) to improve road safety thanks to advancements in wireless connectivity and sensor technology. Deep Learning (DL)-based methods have recently demonstrated strong performance in computer vision issues involving complicated feature associations. This work proposes a Hybrid Deep Learning-based Automated Incident Detection and Management (HDL-AIDM) system to identify traffic incidents and improve traffic management. In the suggested model, a Temporal and Spatial Stacked Autoencoder (TSSAE) is used to collect temporal and spatial associations of traffic conditions and identify events. At the same time, a generative adversarial network (GAN) is employed to improve the number of samples and equalize datasets. The proposed model is assessed from many perspectives using the dataset from real-world situations. Based on the HDL output for AID, an efficient and intelligent traffic management algorithm has been accomplished using Road Side Units (RSUs) to gather traffic information. The suggested incident management algorithm considers lane shifts and the fluctuation in vehicle speed over time, which are heavily influenced by traffic incidents. These developments in ITS enable traffic management systems to use information gathered from HDL-based AID methods using TSSAE and GAN. The proposed strategies have been devised to notify drivers about traffic issues and help them avoid congestion. The suggested method provides higher incident detection rates with an accuracy of 94.1%, a 3.9% false alarm rate, and an incident classification rate of 93.3%.

Association between the Upper Quarter Dynamic Balance, Anthropometrics, Kinematics, and Swimming Speed.

Besides recurrently assessed water-based parameters, there are also some individual characteristics that affect swimming performance that are not water related. In the past few years, dynamic balance has been associated with land sports performance. Conversely, evidence on this topic in swimming is scarce. The purpose of this study was to assess the association between on-land dynamic balance and swimming performance. Sixteen young adults and recreational swimmers were recruited for the present study (8 males 20.8 ± 2.0 years, and 8 females 20.1 ± 1.9 years). A set of anthropometric features were measured. The upper quarter Y-balance test was selected as a dynamic balance outcome, and swimming speed as the swimming performance indicator. The results showed a moderate and positive correlation between dynamic balance and swimming performance (p < 0.05). Speed fluctuation was highly and negatively related to swimming speed (p < 0.001), i.e., swimmers who had higher scores in the dynamic balance were more likely to deliver better performances. This suggests that in recreational swimmers, the stability and mobility of the upper extremity had a greater influence on swimming performance. Therefore, swimming instructors are advised to include dynamic balance exercises in their land-based training sessions to improve their swimmers' performance.

Use of vibration signal to estimate instantaneous angular frequency under strong nonstationary regimes

Instantaneous angular frequency (IAF) is an inherent characteristic associated with mechanical dynamics and contains adequate diagnostic information about rotating machinery, especially under speed fluctuation conditions. However, not all machines have the facility to install tachometers or encoders for tracking the instantaneous angular speed (IAS). An alternate solution is using vibration measurements and recovering the missing speed by exploring the acceleration signal. Thus, accurate IAF estimation is crucial to the consequent fault diagnosis. To date, multiple methods have been developed to address this issue, but most present poor results when dealing with the significant variations of IAS, which are common in practical applications. To overcome this deficiency, a new method consisting of time–frequency ridge extraction and an improved multi-order probabilistic approach is proposed in the paper. The described method fully exploits the information within the vibration response while promising robustness to the variations of the running regimes. The proposed method is demonstrated by assessing its performance on three benchmark data sets and two experimental signals collected from our laboratory and comparing them with five advanced IAF estimation methods.

Cavitation characteristics and energy loss in high-pressure differential control valve

PurposeThe purpose of this study is to determine the cavitation flow characteristics of the high-pressure differential control valve. The relationship between cavitation, flow coefficient and spool angle is obtained. By analyzing the relationship between different spool angles and energy loss, the energy loss at different spool angles is predicted.Design/methodology/approachA series of numerical simulations were performed to study the cavitation problem of a high-pressure differential control valve using the RNG k–e turbulence model and the Zwart cavitation model. The flow states and energy distribution at different spool angles were analyzed under specific working conditions.FindingsThe cavitation was the weakest when the spool angle was 120° or the outlet pressure was 8 MPa. The pressure and speed fluctuations of the valve in the throttle section were greater than those at other locations. By calculating the entropy production rate, the reason and location of valve energy loss are analyzed. The energy loss near the throttling section accounts for about 92.7% of the total energy loss. According to the calculated energy loss relationship between different regions of the spool angle, the relationship between any spool angle and energy loss in the [80,120] interval is proposed.Originality/valueThis study analyzes the cavitation flow characteristics of the high-pressure differential control valve and provides the law of energy loss in the valve through the analysis method of entropy. The relationship between spool angle and energy loss under cavitation is finally proposed. The research results are expected to provide a theoretical basis for the optimal design of valves.

Car following models for alleviating the degeneration of CACC function of CAVs in weak platoon intensity

ABSTRACT To alleviate the performance degeneration of the cooperative adaptive cruising control (CACC) of connected and automated vehicles (CAVs) with low market penetration rates (MPRs), it is necessary to resolve the performance degeneration of CAVs operating at weak mixed-platoon intensities for any-MPR CAVs. A car following model (PMCC) for CAVs is proposed, accounting for human reaction time, communication delay, traffic information memory, and vehicle-to-vehicle (V2V) communication. Linear stability analysis was conducted to validate the stability of mixed platoons at weak platoon intensities for different CAV following models. Numerical simulations were conducted to simulate weak-intensity mixed platoons for different CAV following models operating at high and low equilibrium velocities. The results suggest that PMCC exhibits wider stability equilibrium intervals under different theoretical time headway scenariosand performs well at dissipating the speed fluctuation propagation and minimizing the speed fluctuation amplitude.

New Evidence on the Origin of Solar Wind Microstreams/Switchbacks

Microstreams are fluctuations in the solar wind speed and density associated with polarity-reversing folds in the magnetic field (also denoted switchbacks). Despite their long heritage, the origin of these microstreams/switchbacks remains poorly understood. For the first time, we investigated periodicities in microstreams during Parker Solar Probe (PSP) Encounter 10 to understand their origin. Our analysis was focused on the inbound corotation interval on 2021 November 19–21, while the spacecraft dove toward a small area within a coronal hole (CH). Solar Dynamics Observatory remote-sensing observations provide rich context for understanding the PSP in situ data. Extreme ultraviolet images from the Atmospheric Imaging Assembly reveal numerous recurrent jets occurring within the region that was magnetically connected to PSP during intervals that contained microstreams. The periods derived from the fluctuating radial velocities in the microstreams (approximately 3, 5, 10, and 20 minutes) are consistent with the periods measured in the emission intensity of the jetlets at the base of the CH plumes, as well as in larger coronal jets and in the plume fine structures. Helioseismic and Magnetic Imager magnetograms reveal the presence of myriad embedded bipoles, which are known sources of reconnection-driven jets on all scales. Simultaneous enhancements in the PSP proton flux and ionic (3He, 4He, Fe, O) composition during the microstreams further support the connection with jetlets and jets. In keeping with prior observational and numerical studies of impulsive coronal activity, we conclude that quasiperiodic jets generated by interchange/breakout reconnection at CH bright points and plume bases are the most likely sources of the microstreams/switchbacks observed in the solar wind.

Parameterized Domain Mapping for Order Tracking of Rotating Machinery

Because of the periodicity of vibration signals from the cyclic motion of rotating machinery, many spectrum-based methods are widely applied. However, frequency distortion often occurs under non-stationary conditions, which weakens the effectiveness of spectrum-based methods. Order tracking can overcome the frequency distortion problem, but the instantaneous angular speed is hard to detect, especially under strong noise or with close-spaced frequencies. In this paper, we map the signal into a new domain called the pseudo time domain to eliminate the non-stationarity based on the mechanism of rotating machinery. A parameterized domain mapping function (PDMF) is used to represent the relationship between the time and pseudo time domains. Instead of conducting order tracking after detecting the instantaneous angular speed, we directly optimize the parameter set of the PDMF to construct an appropriate pseudo time domain. A new spectrum concentration indicator considering the continuity of the spectrum is built as the optimization objective. The Legendre polynomial, which shows good approximation property, is applied as the general kernel function of PDMF. Numerical and experimental verification shows good anti-noise performance and the ability to deal with complex and close-spaced frequencies under speed variation or speed fluctuation conditions.