Tracking Characteristics Research Articles

Prediction of Geometric Characteristics of Melt Track Based on Direct Laser Deposition Using M-SVR Algorithm.

Geometric characteristics provide an important means for characterization of the quality of direct laser deposition. Therefore, improving the accuracy of a prediction model is helpful for improving deposition efficiency and quality. The three main input variables are laser power, scanning speed, and powder-feeding rate, while the width and height of the melt track are used as outputs. By applying a multi-output support vector regression (M-SVR) model based on a radial basis function (RBF), a non-linear model for predicting the geometric features of the melt track is developed. An orthogonal experimental design is used to conduct the experiments, the results of which are chosen randomly as training and testing data sets. On the one hand, compared with single-output support vector regression (S-SVR) modeling, this method reduces the root mean square error of height prediction by 22%, with faster training speed and higher prediction accuracy. On the other hand, compared with a backpropagation (BP) neural network, the average absolute error in width is reduced by 5.5%, with smaller average absolute error and better generalization performance. Therefore, the established model can provide a reference to select direct laser deposition parameters precisely and can improve the deposition efficiency and quality.

Measurement research on vibro-acoustic characteristics of large-span plate-truss composite bridge in urban rail transit

Large-span plate-truss composite bridge (LPCB) is developing more and more rapidly in urban rail transit. Nevertheless, the bridges are often close to residential buildings, and some even pass through residential areas directly. Compared with small span bridges and ordinary concrete viaducts, the train-induced vibration and noise of LPCB are larger and last longer, and have a greater impact on the residents along the line. Therefore, it is necessary to study the train-induced vibro-acoustic characteristics of LPCB. However, the current research on LPCB mainly focuses on the aspects of bridge structure design, construction, traffic safety and comfortable capability etc, and usually only cares about the global mechanical behavior of bridge structure and train-track-bridge coupling vibration. In order to study the vibro-acoustic characteristics of large-span and complex bridge structures such as LPCB, it is extremely important to obtain and analyze the field measured data. In this paper, the vibration and noise filed measurement of LPCB has been carried out by the authors. The vibration characteristics of track and bridge system have been measured by means of acceleration sensors, which were arranged on the rails, track slab, the center of bridge deck, longitudinal web and transverse web. The noise characteristics of wheel-rail and bridge structure system have been measured by mans of noise sensors, which were arranged beside the track structure and under the bridge structure. Based on the measurement date, the vibro-acoustic characteristic of the LPCB were analyzed in the present paper. It is found that the response of track structures are mainly affected by wheelsets periodic excitation, while the response of bridge structures are determined both by wheelsets periodic excitation and wheel-rail irregularity; the rail and slab are decoupled after beyond the natural frequency of the rail-fastener system (100 Hz); the vibration energy in high frequency band can be effectively suppressed to downward transmission by damping pad floating slab track; the overall vibration level of rail, track slab and bridge are about 130 dB, 114 dB and 118 dB respectively, the overall sound pressure level of track-side and bridge structure are approximately 82 dB(A) and 83 dB(A) respectively.

Development of a Protective Coating for Evaluating the Sub-surface Microstructure of a Worn Material

In the current study, electrolytic deposition using two different electrodes, copper (Cu) and nickel (Ni) was investigated with the aim of protecting the worn surface during mechanical sectioning and polishing, for a posterior examination of the sub-surface microstructure. The efficacies of the two coatings were visually assessed based on its adhesivity and the ability to protect the wear tracks of an as-cast 26% Cr high chromium cast iron (HCCI) alloy. It was observed that electrodeposition using Cu as the electrode was ineffective owing to a poor adhesivity of the coating on the HCCI surface. The coating had peeled off at several regions across the cross-section during the mechanical sectioning. On the other hand, Ni electroplating using Ni strike as the electrolyte was successfully able to protect the wear track, and the sub-surface characteristics of the wear track could be clearly visualized. A uniform coating thickness of about 8 µm was deposited after 30–40 min with the current density maintained between 1 and 5 A/dm2. The presence of the Ni coating also acted as a protective barrier preventing the ejection of the broken carbide fragments underneath the wear track.

Modeling and frequency characteristic analysis of DSOGI-PLL in dq reference frame

Dual second-order generalized integrator phase-locked loop (DSOGI-PLL) is widely used in grid-connected system for grid synchronization because of its simple implementation and good filtering capability. However, the frequency characteristics of DSOGI-PLL affect the impedance modeling of the system, which in turn affect the impedance-based stability analysis. In order to improve the accuracy of system modeling, in this paper, the equivalent transfer function of positive-sequence calculator (PSC) block constructed in αβ reference frame in DSOGI-PLL is presented in dq reference frame, where the relationship between DSOGI-PLL and traditional synchronous reference frame PLL (SRF-PLL) small-signal model is investigated. Then, based on the established model, DSOGI-PLL and SRF-PLL are compared from the tracking characteristics and robustness characteristics. It is further demonstrated that DSOGI-PLL is able to improve the robustness performance of PLL while maintaining the same tracking performance as SRF-PLL. Finally, simulation results are presented to validate the established model and frequency characteristic analysis.

Skill, Predictability, and Cluster Analysis of Atlantic Tropical Storms and Hurricanes in the ECMWF Monthly Forecasts

Abstract In this paper we analyze Atlantic Ocean hurricane activity in the European Centre for Medium-Range Weather Forecasts (ECMWF) monthly hindcasts for the period 1998–2017. The main climatological characteristics of Atlantic tropical cyclone (TC) activity are considered at different lead times and across the entire ECMWF ensemble using three diagnostic variables: the number of tropical cyclones, the number of hurricanes, and the accumulated cyclone energy. The impacts of changing horizontal resolution and stochastic parameterization are clear in these diagnostic variables. The model skill scores for the number of tropical cyclones and accumulated cyclone energy by lead time are also computed. Using cluster analysis, we compare the characteristics of the forecast TC tracks with observations. Although four of the ECMWF clusters have similar characteristics to observed ones, one of the ECMWF clusters does not have a corresponding one in observations. We consider the predictability of each of these clusters, as well the modulation of their frequency by climate modes, such as the El Niño–Southern Oscillation and the Madden–Julian oscillation, taking advantage of the very large sample size of TC datasets in these hindcasts.

Improved sliding mode dynamic matrix control strategy: Application on spindle loading and precision measuring device based on piezoelectric actuator

Spindle workload simulation and precision measurement are important in evaluating the precision of the spindle under different working conditions. Controlling the loading and measuring system accurately is difficult due to the robustness requirements of the controller, the complex dynamic model of the spindle loading system, the difficulty of obtaining system parameters, and the hysteresis of the piezoelectric actuator (PEA). To overcome this challenge, this study refers to the dynamic matrix control (DMC) method and proposes a highly versatile, robust, improved sliding mode DMC predictive controller (ISLDMC). ISLDMC is a non-inverse model control method with strong stickiness and good tracking characteristics. To help the controller achieve good versatility, this study regards nonlinear links, such as hysteresis of PEA, as an unknown disturbance and collects the step response signals of the piezoelectric system as the model state equation. In consideration of the practical application of the piezoelectric system, the prediction function of the state equation is used at the feedforward end of the controller, and the sliding mode function and incremental output are unified at the output end via weighted form optimization. In the feedback part, a variable correction coefficient is introduced into the state equation of the controller to enhance the tracking characteristics of the controller. This improvement is independently verified in a simulation environment. The design method of the controller is provided, the Schur stability of the closed-loop control system is proven. Moreover, the proposed controller is applied to machine tool spindle workload simulation and a precision-measuring device based on piezoelectric actuators. ISLDMC-based displacement-tracking and force-tracking controllers are designed. The experiment showed that the tracking performance and anti-interference, anti-model mismatch, and linear compensation capabilities of ISLDMC are better than those of the DMC controller, PI controller, and controllers from other studies. Furthermore, the linear compensation and anti-disturbance characteristics of the ISLDMC controller with the step response as the state equation are verified through force tracking experiments, which reveal that ISLDMC has good force tracking performance and anti-disturbance and linear compensation characteristics. The effectiveness of the introduction of dynamic correction coefficients is verified through a separate simulation involving displacement tracking and piezoelectric load experiments. The findings confirm that compared with the DMC controller, the ISLDMC controller improves tracking characteristics to a certain extent and has higher robustness.

Six pelagic seabird species of the North Atlantic engage in a fly-and-forage strategy during their migratory movements

Bird migration is commonly defined as a seasonal movement between breeding and non-breeding grounds. It generally involves relatively straight and directed large-scale movements, with a latitudinal change, and specific daily activity patterns comprising less or no foraging and more traveling time. Our main objective was to describe how this general definition applies to seabirds. We investigated migration characteristics of 6 pelagic seabird species (little auk Alle alle, Atlantic puffin Fratercula arctica, common guillemot Uria aalge, Brünnich’s guillemot U. lomvia, black-legged kittiwake Rissa tridactyla and northern fulmars Fulmarus glacialis). We analysed an extensive geolocator positional and saltwater immersion dataset from 29 colonies in the North-East Atlantic and across several years (2008-2019). We used a novel method to identify active migration periods based on segmentation of time series of track characteristics (latitude, longitude, net-squared displacement). Additionally, we used the saltwater immersion data of geolocators to infer bird activity. We found that the 6 species had, on average, 3 to 4 migration periods and 2 to 3 distinct stationary areas during the non-breeding season. On average, seabirds spent the winter at lower latitudes than their breeding colonies and followed specific migration routes rather than non-directionally dispersing from their colonies. Differences in daily activity patterns were small between migratory and stationary periods, suggesting that all species continued to forage and rest while migrating, engaging in a ‘fly-and-forage’ migratory strategy. We thereby demonstrate the importance of habitats visited during seabird migrations as those that are not just flown over, but which may be important for re-fuelling.

Circular characteristics of the Philippine storm tracks

Circular characteristics of the Philippine storm tracks

Structure and Evolution of Non-Lake-Effect Snow Producing Alberta Clippers

Alberta Clippers (clippers) have long been associated with lake-effect snow (LES) events due to their frequent passage over the Great Lakes basin. However, not all clippers produce LES, and no research has inquired into which synoptic fields most influence LES formation. This study analyzes clippers during non-LES situations to further knowledge on which atmospheric variables most regulate LES development on the synoptic scale. As no such database currently exists, a clipper repository is developed using National Centers for Environmental Prediction Reanalysis data. The repository is then cross referenced with a previously developed LES repository to identify clippers responsible for LES. Composite synoptic-scale patterns were then constructed on the remaining non-LES clippers to identify synoptic conditions that ultimately inhibited LES formation. This analysis is supplemented by an assessment of lake surface conditions in each composite to evaluate how influential the lake characteristics were in the suppression of LES activity. In total, 51 non-LES clippers were identified, tracked, and separated into three composite map types that exhibited unique storm track and spatial characteristics. Permutation testing revealed that lake surface conditions were not significantly (p ≤ 0.05) different between LES and non-LES associated clippers implying the main LES inhibition factors were meteorological.

Modal Analysis of a Thin-Walled Box-Girder Bridge and Railway Track Using Finite Element Framework

Modal analysis has received widespread acceptance in past few decades for a wide range of applications. Bridges and buildings are two of the most popular structures that use this application in the context of civil engineering. The current study aims to apply finite element technique to estimate the free vibration characteristics of a railway track and a box-girder bridge. The curved bridge is numerically modeled using thin-walled box-beam finite elements that take into account torsional warping, distortion, and distortional warping, all of which are important characteristics of thin-walled box-girders. A commercially available finite element software ANSYS is used to simulate the railway track in three dimensions. The study is restricted to the initial design stage of a thin-walled box-girder bridge decks, in which a full three-dimensional finite element model is not required. For the thin-walled box-girder bridge, a MATLAB code has been built that yields the corresponding modal parameter results, whilst the modal parameters of the railway track system are acquired using ANSYS software.

Impact of SST and Surface Waves on Hurricane Florence (2018): A Coupled Modeling Investigation

AbstractHurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir–Simpson category 4 to category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. In addition to experiments using a fully coupled atmosphere–ocean–wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by ocean waves through data from an uncoupled wave model. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity (r = 0.89) and strength (r = 0.95) coming from the fully coupled simulations. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. Adding ocean and wave features to the model further modified the fluxes due to more realistic cooling beneath the storm, which in turn modified the precipitation field. Our experiments highlight significant differences in how air–sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes.

Experimental validation of a fast wheel wear prediction model

Wheel-rail wear prediction is a fundamental matter in order to study problems such as wheel lifespan prediction and evolution of vehicle dynamic characteristics with time. However, one of the principal drawbacks of the existing methodologies for calculating the wear evolution is the computational cost. The developed methodology is based on (1) representing the whole route in a reduced number of characteristic points and (2) substituting dynamic simulations by quasi-static ones, in order to reduce computational cost significantly. This paper presents its integration into the complete simulation process for predicting wheel wear evolution and its validation by comparing simulated results with in-service wheel profile measurements. The generality of the method has been verified by applying it to two different operational cases with very different track characteristics. For the validation, the evolution of the worn depth in the tread has been compared according to the travelled distance, as well as the morphology of the worn depth (worn area). Promising results have been obtained in the prediction of wheel wear evolution: in both cases, the simulated curve approaches the measurement curve satisfactorily. Therefore, it can be concluded the validation of the developed method adequately.

Educational achievement disparities between second-generation and non-immigrant students: Do school characteristics account for tracking effects?

The present article investigates the relationship between the degree of tracking and inequalities in reading literacy of second-generation and non-immigrant students in 28 Western countries. The article takes into account that next to between-school tracking, there are also more subtle forms of tracking, such as tracking within schools or classes. By elaborating how the distinct mechanisms of different tracking characteristics generate achievement inequalities, I assume that any negative effects of tracking on second-generation immigrant students’ achievements are primarily driven by differences in the quality of school environments. Data from the Programme for International Student Assessment 2018 are used and multilevel regression analysis with country-fixed effects are applied. The findings reveal that a higher tracking degree is related to substantial disadvantages in reading literacy for immigrant children. Furthermore, a higher immigrant concentration in schools is associated with immigrant inequalities in reading performance as the degree of tracking increases, whereas unequal distributions of teacher and instructional quality were found to generate inequalities in countries with less tracking. Even though the results are only partly in line with the theory of tracking influences on immigrant achievement disadvantages, they suggest that the interplay between institutional tracking and school characteristics are crucial for learning inequalities.

Railway track location estimation using onboard inertial sensors

In railways, using a track- and ride-quality monitoring system on in-service train has become desirable for coordination and security. Identification of the track- or train-related rough rides via train crew can be estimated to the nearest kilometre. However, if the train is equipped with a monitoring system a better location and track quality evaluation can be provided. These systems commonly use information such as GNSS and/or an odometer to provide location information. This work proposes a practical method for track alignment estimation using real data from an in-cab inertial measurement system and using also a novel method based on crosslevel variations. The speed estimation is done through speed-related harmonics detected on inertial sensors, which depend on speed and track characteristics; and distance correction is provided by comparing crosslevel derived from inertial sensors and a reference track geometry. The effectiveness and accuracy of the method is demonstrated with data collected between London and Ashford.

Micro selective laser melting of SS316L: Single Tracks, Defects, microstructures and Thermal/Mechanical properties

With the rapid development of physical science, medical, automotive, biotechnology, energy, communication and optical fields, the demand for micro manufacturing technology is increasing. Micro selective laser melting (MSLM) is advantageous in forming precision and micro manufacturing parts because of its small spot diameter, fine powder and small layer thickness. In this paper, the surface morphology and geometric characteristics of the single tracks were studied and analyzed. The optimization of process parameters by orthogonal tests on the density, surface roughness, microstructure, microhardness and tensile strength were studied and analyzed. Besides, the effect of heat treatment on the organization of the alloy was studied, and tensile experiment and fracture morphology observations were carried out. It is shown that the laser power and scanning speed have a significant effect on the continuity of single tracks forming, and the width of the molten pool is (55 ± 5)μm. A process windows for “Scanning speed-Hatch spacing” was determined, which was divided into four zones: discontinuous, continuous butunstable, continuous stable, excessive melting and unstable. The orthogonal experiment was used to obtain the optimal process parameters. The density of the part was 99.79 ± 0.1%, the surface roughness Ra of the X-Y plane was 2.53 ± 0.3μm, and the Vickers hardness was 209 ± 2.4 HV. After heat treatment, residual stress relief and dissolution of segregation compounds resulted in grain refinement, uniform organization and better mechanical properties. After SRAT + ST, the tensile strength was 499 ± 4.3 MPa, the elongation was 50 ± 1.88%, and the hardness was176 ± 2.0 HV. The tensile fracture dimples are uniformly distributed in size and show equiaxial dimples morphology.

Modified PID like fuzzy servo control applied to smart actuator based miniature Parallel Robot

Miniature flexible parallel robots, popularly used for micro positioning application demands the use of non conventional actuators. Shape memory alloys (SMA) are popular smart actuators because of its light weight, integration compatibility, ease of actuation and high power density. Inclusion of shape memory alloy actuators to the parallel robot brings in control challenges due to its nonlinearity, coupling effects and cocontraction of antagonistic pair of actuators in the mechanism in order to achieve bi directional motion. In this paper, a PID like fuzzy controller is designed and applied to a nonlinear SMA spring actuator connected to a symmetric 2 DOF miniature parallel robot. The fuzzy rules are designed from the general response plot and modified to be applied to a parallel mechanism which involves cocontraction of antagonistic actuators. The paper has also presented the control and electrical circuit design used in the experimental set up. The fuzzy control is implemented in the hardware controller with model based position feedback and tested for the trajectory tracking characteristics of the end effector with disturbances. Experimental results are presented with quantitative analysis to show the effectiveness of the proposed controller in handling nonlinearities and disturbances compared to the conventional PID control and nonlinear Sliding mode control (NSMC). The test results has demonstrated the superior nature of proposed control over other controllers in the trajectory tracking with disturbances and also linearizing the hysteresis of controlled system.

A Quantitative Method to Evaluate the Performance of Climate Models in Simulating Global Tropical Cyclones

The capability to reproduce tropical cyclones (TCs) realistically is important for climate models. A recent study proposed a method for quantitative evaluation of climate model simulations of TC track characteristics in a specific basin, which can be used to rank multiple climate models based on their performance. As an extension of this method, we propose a more comprehensive method here to evaluate the capability of climate models in simulating multi-faceted characteristics of global TCs. Compared with the original method, the new method considers the capability of climate models in simulating not only TC tracks but also TC intensity and frequency. Moreover, the new method is applicable to the global domain. In this study, we apply this method to evaluate the performance of eight climate models that participated in phase 5 of the Coupled Model Intercomparison Project. It is found that, for the overall performance of global TC simulations, the CSIRO Mk3.6.0 model performs the best, followed by GFDL CM3, MPI-ESM-LR, and MRI-CGCM3 models. Moreover, the capability of each of these models in simulating global TCs differs substantially over different ocean basins.

An ultra-short-term scheduling model for cascade hydropower regulated by multilevel dispatch centers suppressing wind power volatility

In China, cascade hydropower stations are widely used in the ultra-short-term scheduling of power grids to eliminate power fluctuations caused by large-scale wind power grid integration due to their quick load tracking characteristics. They are usually operated jointly by multilevel dispatch centers (MLDCs). However, the ultra-short-term hydropower scheduling (USHS) of cascade hydropower stations controlled by MLDCs faces difficulties in coordinating power output regulation (POR) among stations with different dispatch levels, frequent fluctuations in the station power output, and complex solution difficulties. In this paper, a USHS model for cascade hydropower regulated by MLDCs suppressing wind power volatility is developed to address the above problems based on mixed-integer linear programming. First, a novel objective function that minimizes the POR of cascade hydropower considering the planed load rate and operating state is combined with the coordination strategy to cooperate the POR among MLDC stations. Then, the minimum continuous generating period constraint containing the output ramping limit is proposed to prevent the hydropower station power output from fluctuating frequently. Finally, the power output function of the hydropower station, obtained by aggregation technology from multiple nonlinear characteristic curves, is linearized by improved special ordered sets of type two to achieve an efficient solution. The scheduling results from the Beipan River in southwest China demonstrate the feasibility and validity of the model, and the model can obtain reasonable POR results in an acceptable computational time.

The Detailed Representation and Computation of the Traction Network and its Application to the Transient Analysis in Electrified Railways

This paper intends to derive a detailed representation and attain a suitable computation method for the traction network. The transient analysis of the lossy multiconductor transmission lines (MTLs) is performed considering the electromagnetic characteristics of the rail track, which accounts for the frequency‐dependent and distributed nature of the line parameters over the entire frequency range for the traction network. Due to the practical difficulty in wideband parameter determination and the complex layout for the traction power supply system, the model implemented has been validated by comparison to several field tests that are carried out on a real high speed railway line for the purpose of identifying possible power quality problem. The good high representation of the frequency‐dependent parameter and the numerical solution will provide a reliable method for the transient analysis of the electrified railway. Afterwards, the transient calculation using vector fitting and modal decomposition is presented to evaluate how the emission is propagating along the MTLs of the electrified railways. Performing detailed and suitable analysis is necessary to determine the overvoltage conditions during the transients. The outcome of the analysis could be beneficial for the transient protection study in the electrified railway system. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Attribute Reduction Algorithm Based Early Warning Model of Sports Injury

With the continuous development of track and field sports, a relatively complete and scientific system has been formed in terms of training, and more attention has been paid to the planned training of teenagers for many years, psychological training and recovery training, and strengthening medical supervision and scientific research. In order to speed up the scientific training of track and field and improve the level of track and field training in China, in view of the characteristics of track and field injuries such as multiple causes and complexity, this paper analyzes and studies the attribute reduction algorithm based on attribute reduction algorithm, and proposes a sports injury early warning model based on mutual information. Taking the reduction results as input neurons, a BP neural network with hidden layer is established in MATLAB environment. The results show that: call 85% of the track and field athletes in the sample information as training samples for training. After the simulation experiment of the model, it is found that the error value of the prediction results is basically controlled in the range of-0.025-0.05, which meets the requirements of early warning accuracy of injury risk level of athletes, and the accuracy rate of early warning of sports injury risk reaches 100%.