Running Conditions Research Articles

Fretting wear behaviors of Cr-coated Zr–1Nb alloy cladding tube mated with Zr-4 alloy dimple under different tangential displacements

The fretting wear behaviors and wear mechanism of the Cr-coated Zr–1Nb alloy cladding tube mated with Zr-4 alloy dimple were investigated under different tangential displacements. With the increasing tangential displacement, the fretting running status changes from mixed fretting regime to gross slip regime, the friction coefficient increases first and then decreases, and the removed material volume, maximum wear depth, and wear coefficient of the Cr-coated Zr–1Nb alloy cladding tube increase. Fouvry's criteria were used to verify the correctness of the fretting running status. The primary wear mechanisms in the mixed fretting regime are adhesive wear and oxidative wear, while those in the gross slip regime are delamination wear and oxidative wear. The wear mechanism of the dimple is mainly delamination wear. Cr coating inhibits the wear of the cladding tube. After the coating is completely removed, the volume of material removed from the cladding tube increases dramatically, eventually exceeding the volume of material removed by dimple.

Comparison of muscle activity of the lower limbs while running on different treadmill models.

Treadmill running is a common method of exercise and to study human locomotion. Research has examined the kinematics and kinetics of overground and treadmill running, but there has been less focus on the levels of muscle activity during treadmill running. We investigated if muscle activity is different while running overground compared to running on a variety of treadmills. A total of 11 healthy individuals ran at 3 speeds (2.6, 3.6, 4.5 m/s) under 4 different running conditions (3 treadmills, overground). The three treadmills included a typical home exercise treadmill, a midsize commercial research treadmill, and a large, instrumented research treadmill. Surface EMG of the tibialis anterior (TA), gastrocnemius medialis (GM), rectus femoris (RF) and biceps femoris (BF) muscles were measured for each running condition. The integrated EMG was computed for each running condition for the stance and swing phase, as well as 100 ms before and after the heel-strike. Friedman analysis revealed significant effects during the stance phase for GM and RF at all speeds, such that muscle activation was lower on the treadmills relative to overground. During the stance phase at faster speeds, the muscle activity was higher for the TA and lower for the BF while running on the different treadmills compared to overground running. Before heel-strike, the TA was significantly less active during treadmill compared to overground running at 2.6 m/s and the RF showed significantly higher activity at 3.6 m/s and 4.5 m/s while running on the different treadmills. Summarizing, differences were mainly observed between the different treadmill conditions relative to overground running. Muscle activation differences between the different treadmill conditions were observed at faster running speeds for RF during the pre-heel-strike phase only. Different types of treadmills with different mechanical properties affects the muscle activity during stance phase as well as in preparation to heel-strike. Additionally, the muscle activity is greater during overground compared to treadmill running during the stance phase for the GM, BF, and RF.

Development of Two Wheel Drive Electric Bikes for Extreme Road and A Long-Range Capabilities

This paper aims to develop the electric bicycle by using a two-wheel drive that has a long range of use. This development is motivated by many extreme roads and the absence of a charging station except in the user’s own house. A folding bicycle type bicycle for adults with 16-inch wheels was used in this study. The two-wheel drive can be adjusted using the driving motor to be more flexible and adapt to road conditions, although the motor power used is small, 350-Watt 24 Volt for one wheel. The battery capacity used is quite large for the range quite far away, which is 24 volts 80 Amps, and the charging time is about 2 hours. The placement of the battery has calculated the center of gravity and balance of the bike. Results show that this electric bicycle can be used for slippery road conditions and slopes of not more than 1A maximum speed of the bicycle can reach up to 30 km/hour, on flat road conditions. Likewise, the bicycle’s range for a full charge is around 220-260 km, with an average speed of 15-16 km/hour. Two drives can be implemented independently, adjusting the running conditions by moving the drive motor selection button. For extreme conditions, it is recommended to use two electric motors.

A Inverter Dead-time Compensation Method Based on Phase current Polarity Determination and Voltage Partitioning

The introduction of the dead time of the inverter solves the straight-arm conduction problem of the upper and lower power devices of the inverter, but also leads to the deviation of the actual output voltage of the inverter from the given voltage. Dead time increases the harmonic components of phase voltage and phase current, which is also an important factor leading to motor torque ripple. In this paper, the mechanism of the deviation of phase voltage and phase current caused by the dead time of voltage space vector modulation is analyzed, and the effect of dead time on phase voltage and phase current harmonic components is studied. A simple and effective dead time compensation method based on phase voltage division and phase current polarity determination is proposed to directly compensate the dead time. This method can suppress the current harmonic and torque ripple in the running state of the motor, and can greatly simplify the calculation process of the traditional dead time compensation method. Through the system modeling and simulation, it is verified that the method can significantly improve the current waveform distortion, and has good practical value.

Climate change-associated declines in water clarity impair feeding by common loons.

Climate change has myriad impacts on ecosystems, but the mechanisms by which it affects individual species can be difficult to pinpoint. One strategy to discover such mechanisms is to identify a specific ecological factor related to survival or reproduction and determine how that factor is affected by climate. Here we used Landsat imagery to calculate water clarity for 127 lakes in northern Wisconsin from 1995 to 2021 and thus investigate the effect of clarity on the body condition of an aquatic visual predator, the common loon (Gavia immer). In addition, we examined rainfall and temperature as potential predictors of water clarity. Body mass tracked July water clarity strongly in loon chicks, which grow chiefly in that month, but weakly in adult males and females. Long-term mean water clarity was negatively related to chick mass but positively related to adult male mass, suggesting that loons foraging in generally clear lakes enjoy good foraging conditions in the long run but might be sensitive to perturbations in clarity during chick-rearing. Finally, chick mass was positively related to the density of docks, perhaps because angling removes large fishes and thus boosts the abundance of the small fishes on which chicks depend. Water clarity itself declined strongly from 1995 to 2021, was negatively related to July rainfall, and was positively related to July air temperature. Our findings identified both long-term and short-term water clarity as strong predictors of loon foraging efficiency, and suggest that climate change, through water clarity, impacts freshwater ecosystems profoundly. Moreover, our results identified the recent decrease in water clarity as a likely cause of population decline in common loons.

Characterizing ambulatory function in children with PPP2R5D-related neurodevelopmental disorder

BackgroundIndividuals with PPP2R5D-related neurodevelopmental disorder have an atypical gait pattern characterized by ataxia and incoordination. Structured, quantitative assessments are needed to further understand the impact of these impairments on function. Research questionHow do gait parameters and ambulatory function of individuals with PPP2R5D-related neurodevelopmental disorder compare to age and sex matched healthy norms? MethodsTwenty-six individuals with PPP2R5D pathogenic genetic variants participated in this observational, single visit study. Participants completed at least one of the following gait assessments: quantitative gait analysis at three different speeds (preferred pace walking (PPW), fast paced walking (FPW) and running, six-minute walk test (6MWT), 10-meter walk run (10MWR), and timed up and go (TUG). Descriptive statistics were used to summarize gait variables. Percent of predicted values were calculated using published norms. Paired t-tests and regression analyses were used to compare gait variables. ResultsThe median age of the participants was 8 years (range 4–27) and eighteen (69.2 %) were female. Individuals with PPP2R5D-related neurodevelopmental disorder walked slower and with a wider base of support than predicted for their age and sex. Stride velocity ranged from 48.9 % to 70.1 % and stride distance from 58.5 % to 81.9 % of predicted during PPW. Percent of predicted distance walked on the 6MWT ranged from 30.6 % to 71.1 % representing varied walking impairment. Increases in stride distance, not cadence, were associated with changes in stride velocity in FPW (R2 = 0.675, p =< 0.001) and running conditions (R2 = 0.918, p =< 0.001). SignificanceWe quantitatively assessed the abnormal gait in individuals with PPP2R5D-related neurodevelopmental disorder. These impairments may affect ability to adapt to environmental changes and participation in daily life.Rehabilitative interventions targeting gait speed and balance may improve function and safety for individuals with PPP2R5D-related neurodevelopmental disorder.

Effect of thoracolumbosacral braces on running ground reaction force components in male individuals with kyphosis

Background & aimsBraces are one of the methods for kyphosis treatment, but they can relocate the center of gravity of the trunk, affecting the ground reaction force (GRF) during running. Therefore, this study aimed to investigate the effects of two types of thoracolumbosacral braces on running GRF components in individuals with kyphosis. Materials & methodsParticipants were 15 males diagnosed with kyphosis who volunteered in this quasi-experimental study. Each subject performed the barefoot running trials on the force plate with one simple brace, with a sensor brace, and without the brace condition. The ground reaction forces components were calculated in the stance phase. Statistical analysis was done with repeated measures test with a significant level of 0.05. ResultsPeak medial ground reaction force when running with a sensor brace was lower than running with a simple brace (p = 0.017). Free moments were similar during three running conditions (p > 0.05). ConclusionLower maximum medial ground reaction force while using a sensor brace may possibly demonstrate the beneficial effects of a sensor brace in individuals with kyphosis.

A novel rotor-stator rub-impact fault and locations recognition method

Rub-impact fault is a kind of typical secondary fault encountered by large-sized rotation machinery. When it happens, the fault information contained is often weak, complicated and compound. This makes it difficult to correctly identify a rub-impact fault and affected part. Signals captured by sensors vary greatly in terms of energy, stability and complexity before and after a rub-impact fault occurs and when affected part is different. Graph indexes are sensitive to the variation of energy, stability and complexity in graph signal. Based on this, the paper has raised a method based on graph indexes to identify rub-impact fault and its locations and graph indexes are used to describe different running status of equipment. Firstly, to reduce the influence of noise components, vibration signals are given an auto-correlation analysis. Secondly, each auto-correlation function is converted to graph signals and five graph indexes of each graph signal are calculated. Thirdly, when running state of equipment is the same, an analysis is given to the consistency of graph indexes of signals from the same sensor, as well as the difference of graph indexes of each signal from different sensors. Fourthly, when running state of equipment is different, the difference of graph indexes of signals from the same sensor is analyzed. Fifthly, an analysis is given to the effectiveness and sensibility of graph indexes of signals from different sensors to running state. Finally, by the excellent consistency and difference shown by graph indexes, it is treated as a feature vector and according to two classical classification algorithms, rub-impact fault and location is identified. The result indicates that the mean identification rate of proposed method for rub-impact fault and locations can reach to 96%; graph indexes can serve as fault feature index to effectively represent a rub-impact fault and locations and has very excellent robustness.

Design and Testing of Innovative Type of Dual-Motor Drive Electric Wheel Loader

The electric wheel loader is a new prototype in powertrains and drivetrains that saves energy consumption and diminishes emissions as earthmoving machinery. Dual-motor drive in the front and rear axles of electric wheel loaders helps the distribution of drive torque. However, challenges arise during shoveling conditions, particularly when one motor generates torque exceeding the ground’s adhesion force, leading to tire slippage. This study thoroughly examines the mechanical structure of the working unit and elucidates the correlation between wheel load and hydraulic pressure in the base chamber of the tilt cylinder. This analysis is accomplished through a combination of theoretical derivations and experimental tests. The experiments involve a 5 ton rated load electric wheel loader tested across five running cases as well as weighing tests on a 15 ton rated load electric wheel loader. Based on the experiment discoveries, a dual-motor drive electric wheel loader is designed with specific transmission ratios for the front and rear drivetrains, and a torque distribution strategy is proposed based on wheel load during shoveling. Running condition tests demonstrate sufficient drive force for the new electric wheel loader, and shoveling tests reveal a significant reduction in tire slippage when employing the proposed torque distribution strategy compared to evenly distributed torque in the front and rear axles. Moreover, the driving force during the shoveling process remains undiminished. This indicates that the newly designed loader, in conjunction with the proposed strategy, exhibits excellent shoveling efficiency.

Environmental Interference Suppression by Hybrid Segmentation Algorithm for Open-Area Electromagnetic Capability Testing

Compared with electromagnetic compatibility (EMC) testing in anechoic rooms, open-area EMC testing takes advantage of in situ and engine running status measurement but suffers from non-negligible external electromagnetic interference. This paper proposes a novel environmental interference suppression method (named the EMC environmental interference suppression algorithm (E2ISA)) that separates signals from backgrounds via image segmentation and recognizes the near–far site signal via a group of time-varying features based on the difference in the near-site EM radiative characteristic. We find that the proposed E2ISA method, which combines the deep learning segmentation network with the classical recognition methods, is able to suppress environmental interference signals accurately. The experiment results show that the accuracy of E2ISA reaches up to 95% in the face of VHF (Very High Frequency) EMC testing tasks.

Rated load state performance assessment and analysis of ultra-supercritical coal-fired power plant

ABSTRACT To address the problems of unclear assessment standards and incomplete assessment systems in the performance assessment of ultra-supercritical coal-fired power plants. This study utilized the running dataset from a 660 MW ultra-supercritical coal-fired power plant in Xinjiang, China. By combining the analytic hierarchy process and the entropy weight method, a system of assessment indicators was established that used three layers of criteria. A running line graph representing power plant performance and containing 149 moments was obtained, which provided a theoretical basis and optimization direction for improving the power plant. The results show that the 149 running states of the power plant performance are all at level I. The boiler running level had 143 moments (95.97%), the steam-turbine level had 135 moments (90.60%), the power consumption rate level had 148 moments (99.33%), and the environmental performance level had 143 moments (89.94%) of running states at level I.

Signed-data reinforced observer-based fault diagnosis for virtually-coupled electric multiple units trains

Virtual coupling has been recognized as a promising yet challenging technology for the next generation of train control systems. As a mean of guaranteeing the safety of closer-running of virtually-coupled electric multiple units (EMU) trains, fault detection and diagnosis play a critical role in perceiving abnormal running conditions. This paper develops a new signed-data reinforced observer-based technique for dealing with actuator faults’ detection and diagnosis for virtually-coupled EMU trains. The introduction of novel signed-data reinforcement technique ensures that unbiased fault diagnosis can be guaranteed with any regressor vector composed of control signals on EMU trains. Fault detection and diagnosis observers, together with fault alarming principle, information transmission coding strategy are elaborated using Lyapunov stability theorem. Simulation results are given to demonstrate the effectiveness of proposed algorithm.

Fretting corrosion running regime and damage mechanism evolution of zirconium alloy mated with Inconel 718 alloy in high temperature high pressure water environment

Fretting corrosion behavior and damage mechanism of Zr-4 alloy mated with Inconel 718 alloy under different fretting regimes in high temperature high pressure water were studied. The corresponding running condition fretting corrosion map (RCFM) and material response fretting corrosion map (MRFM) were established. The results showed that the change of fretting regime led to the differences of fretting corrosion behavior and damage mechanism. Based on the damage mechanism, the MRFM could be divided into partial slip regime with only slight surface damage; mixed fretting regime-I dominated by cracks; mixed fretting regime-II dominated by cracks and abrasive wear; and gross slip regime dominated by severe adhesive wear and oxidation. The transformation of fretting regime also resulted in different oxides.

Deep Reinforcement Learning and Auto-Differential Evolution Co-Guided Coal Washing

Background. Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. Methods. Through the intelligent transformation of jig, this paper proposes an intelligent washing method with cooperated deep reinforcement learning and evolutionary computation. First, it designs a fault warning method based on statistical analysis, helping to recover the normal running state of jig with manual maintenance. Then, it constructs a regulation strategy generation method with deep reinforcement learning supported by the fusion of artificial experience and historical data. Last, for the lack of monitoring data caused by poor communication quality and environment, the regulation strategy prediction method with evolutionary computation and surrogate model is proposed. Results. In practice, this method shows accurate fault warning accuracy and rapid cleaned coal ash adjustment response ability. Conclusions. This shows that the method proposed in this paper is of great significance for intelligent washing and can better cope with the special situation when the washing equipment sensing data are missing.

A Review on Automotive Heavy-Duty Chassis

The chassis frame is a significant part in a vehicle which it carries the entire load acting on the truck as well as different parts of the automobile. So, chassis must be robust enough to resist the shock, twist, vibration and other stresses. Therefore, the study of chassis under both static and dynamic load are crucial. The variable sections of chassis structure are shaped on the basis of varied loads acting along the length of the automotive to overcome the failure and preserve the safety. But the direct major or minor impacts on chassis frames in accidental cases may root the dynamic unbalancing, chassis misalignment and other problems which affect the vehicle performance as well as the appearance. Due to large and sudden bumps during running conditions may produce the vibrations inside the chassis which cause the prior failure in chassis members. This paper focus on the automotive heavy-duty 407 vehicle chassis under maximum load.

Experiments on Tuned UHBR Open-Test-Case Fan ECL5/CATANA: Performance and Aerodynamics

Abstract With the advancement of modern fan architectures, the lack of experimental benchmarks for the research community became apparent in the recent years. Enormous effort in the method development could not be validated on representative geometries and motivated the development of the open-test-case ECL5/CATANA. A carbon fiber fan stage has been designed by Ecole Centrale de Lyon and shared with the community in 2021. The fan is representative of a modern ultra high bypass ratio (UHBR) architecture with sonic design speed. The reference configuration has been investigated experimentally on a novel test facility with multiphysical instrumentation. In this publication, the results of the first experimental campaign are presented with a detailed analysis of the aerodynamic performance and system symmetry. The presented results comprise full stage mappings across the whole operating range for three main speedlines (55%, 80%, and 100%) using performance rakes, unsteady wall pressure arrays, tip clearance, and stagger angle measurements. Radial profiles of intake boundary layer and rotor exit conditions at selected conditions complete the full validation dataset for steady and unsteady aerodynamic simulations. Results are discussed in comparison to blind-test Reynolds-averaged Navier–Stokes (RANS) simulations of different international institutes. Significant prediction inaccuracies of the tip flow and corner separations of the stator are observed and reveal the requirement of real blade geometry measurements at running conditions. This article is accompanied by a publication with a focus on aeroelastic instabilities observed near the stability limit. The results represent a comprehensive dimensional benchmark dataset and allow method validation on multiple levels of fidelity for the aerodynamic and aeroelastic research community.

Hybrid Multimodal Feature Fusion with Multi-Sensor for Bearing Fault Diagnosis.

Aiming at the traditional single sensor vibration signal cannot fully express the bearing running state, and in the high noise background, the traditional algorithm is insufficient for fault feature extraction. This paper proposes a fault diagnosis algorithm based on multi-sensor and hybrid multimodal feature fusion to achieve high-precision fault diagnosis by leveraging the operating state information of bearings in a high-noise environment to the fullest extent possible. First, the horizontal and vertical vibration signals from two sensors are fused using principal component analysis, aiming to provide a more comprehensive description of the bearing's operating condition, followed by data set segmentation. Following fusion, time-frequency feature maps are generated using a continuous wavelet transform for global time-frequency feature extraction. A first diagnostic model is then developed utilizing a residual neural network. Meanwhile, the feature data is normalized, and 28 time-frequency feature indexes are extracted. Subsequently, a second diagnostic model is constructed using a support vector machine. Lastly, the two diagnosis models are integrated to derive the final model through an ensemble learning algorithm fused at the decision level and complemented by a genetic algorithm solution to improve the diagnosis accuracy. Experimental results demonstrate the effectiveness of the proposed algorithm in achieving superior diagnostic performance with a 97.54% accuracy rate.

Compression fatigue of elastomeric foams used in midsoles of running shoes

Due to their excellent specific mechanical properties, closed cell elastomeric foams are the main element in the soles of running shoes to absorb repetitive shocks from strides and to release a maximum of the absorbed energy. However, these cellular materials are gradually damaged. To enhance their mechanical durability by slowing their damage kinetics, it is critical to understand their mechanical behaviour in fatigue. The objective of this work is thus to clarify the link between the microstructure and the fatigue properties of five commercial elastomeric foams used in the midsoles of running shoes. The 3D cellular structures of each foam were finely analysed using X-ray microtomography. Foam samples were then subjected to cyclic compression which were close to running conditions. During cycling, samples exhibited a rapid densification associated with noticeable decreases of (i) the stress levels required to deform them as well as (ii) the cushioning and (iii) the rebound properties. We show that the two midsoles filled with micro-sized mineral fillers present the highest specific mechanical properties during the first compression cycle and during fatigue. However, their damage kinetics and rebound properties could probably be improved by tuning the fillers-matrix compatibility. The lightest foam, being very porous and presenting process-induced tortuous cell walls, is the best cushioning system but exhibits high damage kinetics. The densest foam presents poor specific mechanical properties, but very slow damage kinetics. Its double hierarchical architecture probably prevents the occurrence of micro-cracks in the cell walls.

Diffusion of active Brownian particles under quenched disorder.

The motion of a single active particle in one dimension with quenched disorder under the external force is investigated. Within the tailored parameter range, anomalous diffusion that displays weak ergodicity breaking is observed, i.e., non-ergodic subdiffusion and non-ergodic superdiffusion. This non-ergodic anomalous diffusion is analyzed through the time-dependent probability distributions of the particle's velocities and positions. Its origin is attributed to the relative weights of the locked state (predominant in the subdiffusion state) and running state (predominant in the superdiffusion state). These results may contribute to understanding the dynamical behavior of self-propelled particles in nature and the extraordinary response of nonlinear dynamics to the externally biased force.

Criterion-Related Validity of Consumer-Wearable Activity Trackers for Estimating Steps in Primary Schoolchildren under Controlled Conditions: Fit-Person Study.

The purposes were to examine the criterion-related validity of the steps estimated by consumer-wearable activity trackers (wrist-worn activity trackers: Fitbit Ace 2, Garmin Vivofit Jr, and Xiomi Mi Band 5; smartphone applications: Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health) and their comparability in primary schoolchildren under controlled conditions. An initial sample of 66 primary schoolchildren (final sample = 56; 46.4% females), aged 9-12 years old (mean = 10.4 ± 1.0 years), wore three wrist-worn activity trackers (Fitbit Ace 2, Garmin Vivofit Jr 2, and Xiaomi Mi Band 5) on their non-dominant wrist and had three applications in two smartphones (Pedometer, Pedometer Pacer Health, and Google Fit/Apple Health for Android/iOS installed in Samsung Galaxy S20+/iPhone 11 Pro Max) in simulated front trouser pockets. Primary schoolchildren's steps estimated by the consumer-wearable activity trackers and the video-based counting independently by two researchers (gold standard) were recorded while they performed a 200-meter course in slow, normal and brisk pace walking, and running conditions. Results showed that the criterion-related validity of the step scores estimated by the three Samsung applications and the Garmin Vivofit Jr 2 were good-excellent in the four walking/running conditions (e.g., MAPE = 0.6-2.3%; lower 95% CI of the ICC = 0.81-0.99), as well as being comparable. However, the Apple applications, Fitbit Ace 2, and Xiaomi Mi Band 5 showed poor criterion-related validity and comparability on some walking/running conditions (e.g., lower 95% CI of the ICC < 0.70). Although, as in real life primary schoolchildren also place their smartphones in other parts (e.g., schoolbags, hands or even somewhere away from the body), the criterion-related validity of the Garmin Vivofit Jr 2 potentially would be considerably higher than that of the Samsung applications. The findings of the present study highlight the potential of the Garmin Vivofit Jr 2 for monitoring primary schoolchildren's steps under controlled conditions.