Force Fluctuations Research Articles

Foot-dominance does not influence force variability during ankle dorsiflexion and foot adduction

ABSTRACT The aim of our study was to compare the force steadiness and the discharge characteristics of motor units in the tibialis anterior (TA) during ankle dorsiflexion and foot adduction produced by submaximal isometric contractions with the dominant and non-dominant foot. Fifteen young men performed maximal and submaximal contractions at five target forces with both legs, and motor unit activity in TA was recorded using high-density electromyography. Maximal force and the fluctuations in force during submaximal contractions were similar between the two legs (p > 0.05). Motor unit activity was characterized by measures of mean discharge rate (MDR), coefficient of variation for interspike interval (CoV for ISI), and standard deviation of the filtered cumulative spike train (SD of fCST). There were no statistically significant differences in motor unit activity between legs during ankle dorsiflexion. In contrast, the MDR and the CoV for ISI but not the SD of fCST, were greater for the non-dominant foot compared with the dominant foot during foot adduction. Nonetheless, these differences in motor unit activity were not sufficient to influence the force fluctuations during the submaximal contractions. These results indicate that control of the force produced by TA during the two actions was not influenced by limb dominance.

Fluctuation of the unsteady force on the rotor blade surface under circumferential distortion in axial flow compressor

To deeply understand the negative impact of circumferential inlet distortion on the internal flow of the compressor, by using the unsteady force testing technique of a rotor blade surface under a rotating coordinate system, the pressure fluctuations on the rotor blade surface are successfully captured when the rotor blade rotates through the distortion region. Results show that the pressure on the suction surface increases and the inlet angle of attack decreases before the rotor blade enters the distorted region. The pressure difference between the pressure and suction surface is obviously enhanced, thereby sharply increasing the blade load and intensifying the flow separation, which is easy to induce instability. When the rotor blade rotates out of the distortion region, the pressure on the suction surface is still low; thus, the inlet angle of attack in this position is larger than before entering the distorted region. It also shows that the outlet of the distorted region is prone to trigger stall. In addition, the dynamic spectrum characteristics of unsteady forces on the blade surface demonstrate that the energy of the rotor frequency and its harmonics increases significantly and the energy of low frequency disturbance is enhanced when the rotor blade rotates through the distorted region. As a result, the vibration is more obvious in the distorted region, especially the energy of natural vibration frequency of the rotor blade is enhanced. When the compressor stalls, the vibration at the rotor blade root is intensified, which is significantly stronger than at the rotor blade tip. It provides support for evaluating the influence of stall and surge on the lifecycle of rotor blade when suffering from circumferential inlet distortion.

Study of axial hydraulic thrust and radial force characteristics of a variable speed pump-turbine unit

Abstract When the pump turbine does variable speed operation, it can improve the operation efficiency in the turbine mode, and it can improve the automatic frequency adjustment efficiency in the pump mode. However, the hydraulic thrust will also change when the speed changes, and the magnitude of the hydraulic thrust is crucial for the safe and stable operation of the unit. The work of this paper is to analyze the changes of the axial hydraulic force and radial force with the change of the speed by numerical simulation method. It is found that the fluctuation of axial hydraulic thrust can reach about 34 t at 398.57rpm speed, 37 t at 412.16rpm speed and 21 t at 428.6rpm speed. the fluctuation of radial force can reach about 13.78 t, 14.4 t and 12.4 t. The purpose of this paper is to use the simulation results to understand the hydraulic thrust characteristics and ensure the stability of the unit to select the appropriate speed range, provide the basis for stable operation of the unit under design conditions.

Consensus for experimental design in electromyography (CEDE) project: Application of EMG to estimate muscle force

Skeletal muscles power movement. Deriving the forces produced by individual muscles has applications across various fields including biomechanics, robotics, and rehabilitation. Since direct in vivo measurement of muscle force in humans is invasive and challenging, its estimation through non-invasive methods such as electromyography (EMG) holds considerable appeal. This matrix, developed by the Consensus for Experimental Design in Electromyography (CEDE) project, summarizes recommendations on the use of EMG to estimate muscle force. The matrix encompasses the use of bipolar surface EMG, high density surface EMG, and intra-muscular EMG (1) to identify the onset of muscle force during isometric contractions, (2) to identify the offset of muscle force during isometric contractions, (3) to identify force fluctuations during isometric contractions, (4) to estimate force during dynamic contractions, and (5) in combination with musculoskeletal models to estimate force during dynamic contractions. For each application, recommendations on the appropriateness of using EMG to estimate force and justification for each recommendation are provided. The achieved consensus makes clear that there are limited scenarios in which EMG can be used to accurately estimate muscle forces. In most cases, it remains important to consider the activation as well as the muscle state and other biomechanical and physiological factors— such as in the context of a formal mechanical model. This matrix is intended to encourage interdisciplinary discussions regarding the integration of EMG with other experimental techniques and to promote advances in the application of EMG towards developing muscle models and musculoskeletal simulations that can accurately predict muscle forces in healthy and clinical populations.

Axial transfer characteristics of a drillstring in conjunction with bit penetration behavior in horizontal wells

Nonlinear friction and interaction between bit and rock often result in a lower weight on bit (WOB) than the intended design value. The analysis of the dynamic transmission mechanism of a drillstring in complex horizontal wells is a crucial engineering problem that aims to enhance drilling efficiency. In this paper, a mechanical model was developed, integrating nonlinear bit penetration behavior and variable axial loads, aiming to unveil the nonlinear axial vibration characteristics and elucidate the transmission mechanisms within the drillstring. Notably, the mean value of axial force distributed along the drillstring is dictated by wellhead pulling force, while the amplitude is shaped by the interaction between bit and rock, and rotary speed. In calculated examples for horizontal wells, the analysis reveals that significant losses in power axial transmission, resulting in WOB is only 38% of the intended value. And reducing the wellhead pulling force by 30 kN leads to a maximum increase in WOB only of 9.51 kN. Extended region in drillstring with negative axial forces exhibit maximum values 5–6 times higher than the WOB. Specific zones, such as 20 m–40 m and 0–20 m from the bit, experience axial force fluctuation amplitudes of 40.5% and 138.8% of the mean value respectively, with the latter identified as an intense vibration zone, while the acceleration values 0–10 m from the bit signal a high-risk zone. In prolonged horizontal section, stability issues manifest, with spiral buckling observed in the holding section and sinusoidal buckling in the horizontal section. Mitigating the synchronous vibrations between the bit and the surrounding drillstring can effectively reduce the intensity of axial vibration. To ensure successful drilling to target formation, adjusting the wellhead pulling force to keep the WOB in the range of 60–90 kN and limiting the rotary speed to 90 r/min are recommended practices. This comprehensive analysis offers valuable insights for optimizing drilling parameters, pinpointing high-vibration zones, and mitigating risks associated with drilling, providing a holistic approach to enhancing drilling efficiency.

Heterogeneity and wage growth of full-time workers in Japan: An empirical analysis using micro data

In this paper we examine the driving forces of fluctuations in wage growth of full-time workers in Japan, taking into account the heterogeneity of wage structures among the workers and using micro data including those from the Basic Survey on Wage Structure. To this end, we first divide full-time workers into two classes with distinct wage structures, based on a finite mixture model estimated using various characteristics of the workers and the firms they work for. We find that the two classes correspond to what previous studies have called an "internal labor market," where labor is reallocated within firms and wages follow a seniority-based system under long-term employment practices, and an "external labor market," where labor moves across firms and wages are mainly determined by supply and demand factors in the market. We next analyze the effects of economic factors on individual full-time workers' wage growth rates. We show that in the internal labor market, neither labor market conditions at the industry and firm-size level nor the output gap at the macro level have influenced the wage growth rates in recent years at least until 2021, while higher potential growth has increased them. By contrast, in the external and the overall labor markets for full-time workers, improvements in labor market conditions and the output gap have accelerated the wage growth rates, even in recent years.

Cooperative optimization of energy recovery and braking feel based on vehicle speed prediction under downshifting conditions

Regenerative braking can effectively recover vehicle kinetic energy, but its energy conversion efficiency is low under low-speed conditions, and there is also the problem of premature exit from energy recovery due to insufficient reverse electromotive force. The cooperation of gearbox gears can increase the speed range for the motor to recover energy, but unreasonable shifting will cause fluctuations in braking force and affect the consistency of the braking feel. Therefore, this paper aims to collaboratively optimize energy recovery and braking force fluctuations during gear shifting. Firstly, based on the model of braking system and transmission, the influence of shift strategy on braking impact and energy recovery is studied. In view of the challenge of determining a shift strategy with uncertain target braking speeds, a speed prediction model reconstructed by the support vector regression (SVR) model and the hybrid nonlinear autoregressive neural network (NAR) is proposed. On the basis of NAR-SVR speed prediction, the coupling effect of braking impact force and energy recovery efficiency is considered, and the collaborative optimization of regenerative braking torque and shift time is solved through a multi-objective cuckoo search algorithm. The hardware-in-the-loop test results verified that under high-speed conditions, the braking energy recovery rate of the proposed strategy was increased by 47.06 %, and the peak braking impact was reduced by 61.4 %. This research can provide a reference for the brake downshift optimization strategy and regenerative braking research of vehicles with non-decoupled electro-hydraulic composite braking systems.

Vertical vibration model for the roll system of a six-high rolling mill based on the Timoshenko beam theory

During the production of cold-rolled strips, the high-speed operation of rolling mills generates vibrations that significantly impact the production efficiency, the strip quality, and the rolling mill service life. Therefore, investigating the vibration characteristics of rolling mills is of paramount importance. Previous studies predominantly treated the rolls as point masses, overlooking variations in the vibrations along the lengths of the rolls. In this study, the working, intermediate, and backup rolls were regarded as continuous elastic bodies, and they were simplified as Timoshenko beams. The modal superposition method was used to solve the vertical vibration equations for the rolls of a six-high rolling mill; thus, the natural frequencies and modal shapes for the rolls were obtained for both free and forced vibrations. A finite-element model validation confirmed that the accuracy of the novel Timoshenko beam six-high rolling mill vibration model introduced in this paper is significantly higher than that of the traditional Euler beam model when the roller length-to-diameter ratio is relatively small. Further analysis based on this model indicates that the forced vibration of the rolls is primarily influenced by fluctuations in rolling force. The amplitude of forced vibration is affected by factors such as the friction coefficient in the deformation zone, rolling speed, and cumulative rolling distance of the work rolls. These findings provide a precise representation of the characteristics of forced vibrations in rolling mills and offer valuable theoretical insight to ensure stable rolling mill operation.

Numerical Analysis of Dynamic Response in Large Caissons during Wet-towing after Cable Breakage

Variable and complex marine environmental loads combined with wave resistance and the insufficient controllability of large caisson structures pose serious challenges during maritime towing. Cable breakage events are common, and improper behaviors could give rise to a variety of accidents. This work explored the dynamic responses of large caisson structures following towing cable breakage under irregular waves combined with harsh currents. Two types of cable breakage, i.e., main bridle and towing bridle breakage, were taken into account. Four potential wave–current combinations were assumed for each situation according to direction. The obtained results show that drag rope breakage could give rise to lateral shifts in the structure, which can become a serious condition when exposed to angled waves. Additionally, following breakage, significant force fluctuations took place in the remaining intact cables. For main cable breakage, both lateral and backward displacements were observed in the structure, which gradually entered a ‘flowing with the wave’ state. Furthermore, under the two abovementioned cable breakage conditions, the structure air gap consistently exceeded 2.3 m, ignoring the possibility of a wave slamming event.

Flow past a random array of statistically homogeneously distributed stationary Platonic polyhedrons: Data analysis, Probability maps and Deep Learning models

We perform particle-resolved direct numerical simulations (PR-DNS) of the flow past a random array of stationary Platonic polyhedrons seeded in a tri-periodic box at Reynolds number Re=1, 10, and 100 and solid volume fraction 0.05, 0.1 and 0.2. Using Platonic polyhedrons enables us to examine the effects of particle angularity on the hydrodynamic force and torque exerted on the stationary particles in a controlled manner. We report the average drag, lift, and torque coefficients as well as their respective distribution. We explore the relationship between the particle angularity, particle angular position, flow disturbances created by the neighboring particles, and the hydrodynamic force and torque exerted on each individual particle. We attempt to extend our probability map based model (MPP), our Physics Informed neural network (PINN) model previously developed for spheres to Platonic polyhedrons, and propose an additional NN architecture. We show that ignoring the angular position and actual shape of the reference and neighboring particles constitutes a reasonable first order approximation that significantly simplifies the construction of deterministic models of hydrodynamic forces and torques at low Re=1 to moderate Re=10. At high Re=100, both the MPP model and the PINN model without any additional knowledge of the particle shape and angular position fail to properly predict the force and torque fluctuations. We then design a Convolutional Neural Network (CNN) architecture that is able to maintain a satisfactory performance at Re=100 but requires additional input data in the form of a coarse-grained velocity field around each particle. Overall, predicting the torque fluctuation remains a significant challenge.

Fatigue Alleviation by Low-Level Laser Preexposure in Ischemic Neuromuscular Electrical Stimulation.

Despite its susceptibility to muscle fatigue, combined neuromuscular electrical stimulation (NMES) and blood flow restriction (BFR) are effective regimens for managing muscle atrophy when traditional resistance exercises are not feasible. This study investigated the potential of low-level laser therapy (LLLT) in reducing muscle fatigue after the application of combined NMES and BFR. Thirty-six healthy adults were divided into control and LLLT groups. The LLLT group received 60 J of 850-nm wavelength LLLT before a training program of combined NMES and BFR of the nondominant extensor carpi radialis longus (ECRL). The control group followed the same protocol but received sham laser therapy. Assessments included maximal voluntary contraction, ECRL mechanical properties, and isometric force tracking for wrist extension. The LLLT group exhibited a smaller normalized difference in maximal voluntary contraction decrement (-4.01 ± 4.88%) than the control group (-23.85 ± 7.12%) ( P < 0.001). The LLLT group demonstrated a smaller decrease in muscle stiffness of the ECRL compared with the control group, characterized by the smaller normalized changes in frequency ( P = 0.002), stiffness ( P = 0.002), and relaxation measures ( P = 0.011) of mechanical oscillation waves. Unlike the control group, the LLLT group exhibited a smaller posttest increase in force fluctuations during force tracking ( P = 0.014), linked to the predominant recruitment of low-threshold MU ( P < 0.001) without fatigue-related increases in the discharge variability of high-threshold MU ( P > 0.05). LLLT preexposure reduces fatigue after combined NMES and BFR, preserving force generation, muscle stiffness, and force scaling. The functional benefits are achieved through fatigue-resistant activation strategies of motor unit recruitment and rate coding.

Rapid Adaptation for Active Pantograph Control in High-Speed Railway via Deep Meta Reinforcement Learning.

Active pantograph control is the most promising technique for reducing contact force (CF) fluctuation and improving the train's current collection quality. Existing solutions, however, suffer from two significant limitations: 1) they are incapable of dealing with the various pantograph types, catenary line operating conditions, changing operating speeds, and contingencies well and 2) it is challenging to implement in practical systems due to the lack of rapid adaptability to a new pantograph-catenary system (PCS) operating conditions and environmental disturbances. In this work, we alleviate these problems by developing a revolutionary context-based deep meta-reinforcement learning (CB-DMRL) algorithm. The proposed CB-DMRL algorithm combines Bayesian optimization (BO) with deep reinforcement learning (DRL), allowing the general agent to adapt to new tasks quickly and efficiently. We evaluated the CB-DMRL algorithm's performance on a proven PCS model. The experimental results demonstrate that meta-training DRL policies with latent space swiftly adapt to new operating conditions and unknown perturbations. The meta-agent adapts quickly after two iterations with a high reward, which require only ten spans, approximately equal to 0.5 km of PCS interaction data. Compared with state-of-the-art DRL algorithms and traditional solutions, the proposed method can promptly traverse scenario changes and reduce CF fluctuations, resulting in an excellent performance.

A Reinforcement Learning-Based Pantograph Control Strategy for Improving Current Collection Quality in High-Speed Railways.

In high-speed railways, the pantograph-catenary system (PCS) is a critical subsystem of the train power supply system. In particular, when the double-PCS (DPCS) is in operation, the passing of the leading pantograph (LP) causes the contact force of the trailing pantograph (TP) to fluctuate violently, affecting the power collection quality of the electric multiple units (EMUs). The actively controlled pantograph is the most promising technique for reducing the pantograph-catenary contact force (PCCF) fluctuation and improving the current collection quality. Based on the Nash equilibrium framework, this study proposes a multiagent reinforcement learning (MARL) algorithm for active pantograph control called cooperative proximity policy optimization (Coo-PPO). In the algorithm implementation, the heterogeneous agents play a unique role in a cooperative environment guided by the global value function. Then, a novel reward propagation channel is proposed to reveal implicit associations between agents. Furthermore, a curriculum learning approach is adopted to strike a balance between reward maximization and rational movement patterns. An existing MARL algorithm and a traditional control strategy are compared in the same scenario to validate the proposed control strategy's performance. The experimental results show that the Coo-PPO algorithm obtains more rewards, significantly suppresses the fluctuation in PCCF (up to 41.55%), and dramatically decreases the TP's offline rate (up to 10.77%). This study adopts MARL technology for the first time to address the coordinated control of double pantographs in DPCS.

Research on force-controlled polishing system for robotic arm based on compliance control

This thesis enhances robotic arm control in intricate polishing environments by using impedance control for consistent force regulation between the arm and workpiece. An adaptive impedance control algorithm accommodates contact force variations, boosting system robustness. The PSO-BP variable impedance controller integrates particle swarm optimization and BP neural network for real-time optimization, overcoming limitations of fixed-parameter impedance control on surfaces with curvature changes. Experimental results show a significant reduction in polishing force fluctuations and improved force tracking. These findings support efficient robotic arm utilization in polishing tasks.

Deformation and Frictional Failure of Granular Media in 3D Analog and Numerical Experiments

Frictional sliding along grain boundaries in brittle shear zones can result in the fragmentation of individual grains, which ultimately can impact slip dynamics. During deformation at small scales, stick–slip motion can occur between grains when existing force chains break due to grain rearrangement or failure, resulting in frictional sliding of granular material. The rearrangement of the grains leads to dilation of the granular package, reducing the shear stress and subsequently leading to slip. Here, we conduct physical experiments employing HydroOrbs, an elasto-plastic material, to investigate grain comminution in granular media under simple shear conditions. Our findings demonstrate that the degree of grain comminution is dependent on both the normal force and the size of the grains. Using the experimental setup, we benchmark Discrete Element Method (DEM) numerical models, which are capable of simulating the movement, rotation, and fracturing of elasto-plastic grains subjected to simple shear. The DEM models successfully replicate both grain comminution patterns and horizontal force fluctuations observed in our physical experiments. They show that increasing normal forces correlate with higher horizontal forces and more fractured grains. The ability of our DEM models to accurately reproduce experimental results opens up new avenues for investigating various parameter spaces that may not be accessible through traditional laboratory experiments, for example, in assessing how internal friction or cohesion affect deformation in granular systems.

Indentation-induced plastic behavior of nanotwinned CuNi alloy: an atomic simulation

This study uses molecular dynamics simulations to explore the mechanical properties of a nano-twinned copper–nickel alloy during indentation. We investigate the impact of twin boundary (TB) angles and spacing on the alloy’s behavior. The plastic deformation process is primarily driven by dislocation generations, slips, and TB interactions, directly affecting the alloy’s hardness. Significant findings include: (1) hardness initially decreases, then increases with increasing TB angle θ, and for TB spacing d greater than 1.25 nm, hardness can be predicted using a simple proposed model; (2) dislocation density ρ experiences significant variations, leveling off at an indentation depth around 1.0 nm; (3) when TB spacing d exceeds 1.25 nm, plastic deformation is dominated by dislocation nucleation, slips, and boundary interactions, while smaller spacings lead to TB migration and the presence of independent dislocation loops, giving rise to force fluctuations along indentation.

Compressible FSI of elastic spikes for drag reduction under hypersonic flow

In this study, a new fluid structure interaction (FSI) algorithm is developed for the aerodynamic-elasticity problem, aiming to address the coupling problem between compressible fluids and deformable solid structures. To verify the feasibility of the proposed model, a two-dimensional cantilever panel case under shock waves was conducted. Our numerical results present good consistency with the data from literatures. Furthermore, the validated FSI algorithm is applied on an elastic spike under compressible hypersonic flow. The complicated interaction between the fluid and solid structure under various spike geometry sizes and materials were revealed in respect of the spike deformation, pressure, temperature, and flow fields distribution. The main findings show that the spike deformation largely affects pressure and temperature on the blunt, the aerodynamic drag and lift force, indicating the necessity of FSI. For the spike diameters and lengths, it is found that larger spike diameters and shorter spikes benefits for deformation reduction, thereby minimizing fluctuations in aerodynamic drag force. For spike materials, spikes with larger elastic moduli and lower densities are preferred for the drag reduction. Thus, the proposed FSI model can accurately predict flow fields around and deformations for elastic spikes and offer guidance for drag reduction design in aerospace engineering.

Impedance control for force tracking of a dual-arm cooperative robot based on particle swarm optimization

PurposeThe purpose of this paper aims to investigate the adaptive impedance control and its optimized PSO algorithm for force tracking of a dual-arm cooperative robot. Because the dual-arm robot is directly in contact with external environment, controlling the mutual force between robot and external environment is of great importance. Besides, a high compliance of the robot should be guaranteed.Design/methodology/approachAn impedance control based on Particle Swarm Optimization (PSO) algorithm is designed to track the mutual force and achieve compliance control of the robot end.FindingsThe experimental results show that the impedance control coefficients can be automatically tuned converged by PSO algorithm.Originality/valueThe system can reach a steady state within 0.03 s with overshoot convergence, and the force fluctuation range at the steady state decreases to about ±0.08 N even under the force mutation condition.

Influence of visual feedback and cognitive challenge on the age-related changes in force steadiness.

Force steadiness can be influenced by visual feedback as well as presence of a cognitive tasks and potentially differs with age and sex. This study determined the impact of altered visual feedback on force steadiness in the presence of a difficult cognitive challenge in young and older men and women. Forty-nine young (19-30yr; 25 women, 24 men) and 25 older (60-85yr; 15 women; 10 men) performed low force (5% of maximum) static contractions with the elbow flexor muscles in the presence and absence of a cognitive challenge (counting backwards by 13) either with low or high visual feedback gain. The cognitive challenge reduced force steadiness (increased force fluctuation amplitude) particularly in women (cognitive challenge × sex: P < 0.05) and older individuals (cognitive challenge × age: P < 0.05). Force steadiness improved with high-gain visual feedback compared with low-gain visual feedback (P < 0.01) for all groups (all interactions: P > 0.05). Manipulation of visual feedback had no influence on the reduced force steadiness in presence of the cognitive challenge for all groups (all P > 0.05). These findings indicate that older individuals and women have greater risk of impaired motor performance of the upper extremity if steadiness is required during a low-force static contraction. Manipulation of visual feedback had minimal effects on the reduced force steadiness in presence of a difficult cognitive challenge.

IoT-based framework for digital twins in steel production: A case study of key parameter prediction and optimization for CSR

Cold-rolled strips are a pivotal product of advanced strip rolling technology in iron and steel production with stringent process standards. Over an extended period, the existence of 'information silos' between cold strip rolling (CSR) and its upstream processes, particularly hot strip rolling (HSR), causes a persistent challenge in achieving collaborative optimization throughout the entire process, thereby constraining progress in product quality. To overcome this challenge, a digital twin framework was proposed to consolidate diverse data from HSR and CSR production lines into a centralized data centre, forming a 'data continent.' This approach establishes a comprehensive dataset for model-driven training and prediction in virtual space. An improved Light gradient boosting machine (IlightGBM) is introduced, enabling high-precision rolling force prediction in unsteady-state rolling and providing essential variables for establishing the tension optimization objective function. A control function is implemented to minimize rolling force fluctuations, and three population algorithms (TPA) are devised for its solution. This strategy successfully realizes collaborative tension optimization across multiple stands, with the rolling speed acting as a follower. The proposed approach was implemented in a large-scale steel plant equipped with a complete HSR and CSR production line, effectively mitigating flatness defects and thickness deviation in the strip's head section. Thus, the proposed framework is reliable and can be flexibly applied to strip manufacturing processes.