Humans optimally anticipate and compensate for an uneven step during walking

The simple task of walking up a sidewalk curb is actually a dynamic prediction task. The curb is a disturbance that could cause a loss of momentum if not anticipated and compensated for. It might be possible to adjust momentum sufficiently to ensure undisturbed time of arrival, but there are infinite possible ways to do so. Much of steady, level gait is determined by energy economy, which should be at least as important with terrain disturbances. It is, however, unknown whether economy also governs walking up a curb, and whether anticipation helps. Here we show that humans compensate with an anticipatory pattern of forward speed adjustments, predicted by a criterion of minimizing mechanical energy input. The strategy is mechanistically predicted by optimal control for a simple model of bipedal walking dynamics, with each leg's push-off work as input. Optimization predicts a tri-phasic trajectory of speed (and thus momentum) adjustments, including an anticipatory phase. In experiment, human subjects ascend an artificial curb with the predicted tri-phasic trajectory, which approximately conserves overall walking speed relative to undisturbed flat ground. The trajectory involves speeding up in a few steps before the curb, losing considerable momentum from ascending it, and then regaining speed in a few steps thereafter. Descending the curb entails a nearly opposite, but still anticipatory, speed fluctuation trajectory, in agreement with model predictions that speed fluctuation amplitudes should scale linearly with curb height. The fluctuation amplitudes also decrease slightly with faster average speeds, also as predicted by model. Humans can reason about the dynamics of walking to plan anticipatory and economical control, even with a sidewalk curb in the way.

Active Brownian motion with speed fluctuations in arbitrary dimensions: exact calculation of moments and dynamical crossovers

We consider the motion of an active Brownian particle with speed fluctuations in d-dimensions in the presence of both translational and orientational diffusion. We use an Ornstein–Uhlenbeck process for active speed generation. Using a Laplace transform approach, we describe and use a Fokker–Planck equation-based method to evaluate the exact time dependence of all relevant dynamical moments. We present explicit calculations of several such moments and compare our analytical predictions against numerical simulations to demonstrate and analyze the dynamical crossovers, determined by the orientational persistence of activity, speed fluctuation and relaxation. The kurtosis of displacement shows positive and negative deviations from a Gaussian behavior at intermediate times depending on the dominance of speed and orientational fluctuations, respectively.

A Spectrum Correction Method Based on Optimizing Turbulence Intensity

Based on the classical spectral representation method of simulating turbulent wind speed fluctuation, a harmonic superposition algorithm was introduced in detail to calculate the homogeneous turbulence wind field simulation in space. From the view of the validity of the numerical simulation results in MATLAB and the simulation efficiency, this paper discussed the reason for the bias existing between three types of turbulence intensity involved in the whole simulation process: simulated turbulence intensity, setting reference turbulence intensity, and theoretical turbulence intensity. Therefore, a novel spectral correction method of a standard deviation compensation coefficient was proposed. The simulation verification of the correction method was carried out based on the Kaimal spectrum recommended by IEC61400-1 by simulating the uniform turbulent wind field in one-dimensional space at the height of the hub of a 15 MW wind turbine and in two-dimensional space in the rotor swept area. The results showed that the spectral correction method proposed in this paper can effectively optimize the turbulence intensity of the simulated wind field, generate more effective simulation points, and significantly improve the simulation efficiency.

Three-Dimensional CFD Simulations of Start-Up Processes of a Pump-Turbine Considering Governor Regulation

The pumped-storage power station is an efficient stability regulator of the power grid. However, due to the instability of the pump-turbine in the S-shaped characteristic region, rotational speed fluctuation is easy to occur in the speed no-load condition, making synchronization with and connection to the grid difficult. To investigate the key factors of these difficult grid connections, the start-up processes of a practical pump-turbine under the lowest head condition were simulated by using the three-dimensional CFD method, in which the governor regulating equations with different regulating parameters were integrated successfully. The results show that the working points oscillate with the fluctuations of rotational speed, discharge, and torque, and different regulating parameters have a significant influence on the dynamic histories. In addition, the internal flow patterns, especially the backflows at the runner inlet, keep apparent values at the middle span (0.5 span) but have regular transitions near the shroud side (0.7–0.8 span). The faster the guide vanes adjust, the faster the backflows change, and the larger the macro parameters fluctuate. Overall, the instability of the start-up is the result of the periodical evolutions of backflows at the runner inlet, because the trend and period of the radial velocities at different inlet span locations are consistent with those of the discharge.

Performance of a capstone gas turbine based power plant working on high Butane LPG

This paper presents the operational performance results of a 30 kW microturbine generator (MTGs) fed with high butane content liquefied petroleum gas, while subjected to a test procedure involving steady and transient load conditions. To evaluate the performance, measurements of turbine and generator parameters were gathered from its original unit controller, as load changes were applied. For the stand-alone mode detailed graphs of the test results are presented, showing the transparency and robustness of the turbine-generator set to the used fuel, judging by the quality of the output electric parameters. The results from this performance testing provide good insight into the use of high-butane content liquefied petroleum gas as fuel for the tested microturbine. The continuous use of a fuel would need more tests to establish that the life of the critical components of the microturbine are not hampered from what they are on the baseline fuel. The course of selected performance parameters in the microturbine generator is described in this document. The analysis of test results of the microturbine under steady-state and transient operation have been made. Both in steady state and transient conditions, values of output power, speed fluctuation, emissions, noise levels, and exhaust gas temperatures remained under acceptable levels.

Control Performance Improvement of Hydro-Viscous Clutch Based on Fuzzy-PID Controller

As a rotational speed controller, a hydro-viscous clutch (HVC) is usually used in the constant pressure water supply system to maintain the needed water pressure constant. However, when the hydro-viscous clutch is working, it often suffers from the problem of output rotational speed fluctuation since the spool of proportional relief valve can easily get stuck. Consequently, water pressure will fluctuate too. A special pump control system of HVC was proposed based on the Fuzzy-PID controller for the purpose of reducing the fluctuation rate. The MATLAB simulation was carried out according to the mathematical model and the results show that the Fuzzy-PID control strategy is superior to traditional PID control. The corresponding experiment was performed and the result indicate that through applying the Fuzzy-PID controller based pump control system, the rotational output speed fluctuation of HVC can be inhibited from ±60π to ±6π rad/min, and the water pressure fluctuation is dropped from ±0.1 to ±0.002 MPa.

A Novel Adaptive Cruise Control Strategy for Electric Vehicles Based on a Hierarchical Framework

Conclusive evidence has demonstrated the critical importance of adaptive cruise control (ACC) in relieving traffic congestion. To improve the performance of the ACC system, this paper proposes a novel ACC strategy for electric vehicles based on a hierarchical framework. Three main efforts have been made to distinguish our work from the existing research. Firstly, a sliding acceleration identification model is established based on the recursive least squares algorithm with multiple forgetting factors (MFF-RLS). Secondly, with vehicle following, economy, and comfort as the optimization objectives, the upper-level controller is developed based on the model predictive control (MPC) algorithm. Benefit from the identification of the sliding acceleration, the MPC controller holds better capability in accommodating environmental changes. Thirdly, an iterative learning lower-level controller is designed to control the driving and braking systems. Considering the efficiency of regenerative braking, the braking force distribution strategy is also designed in the lower-level controller. Simulation results show that, compared with the conventional MPC-based ACC strategy, the proposed strategy has similar performance in vehicle following, but it makes great improvements in comfort and economy. The specific features are that the vehicle acceleration and speed fluctuation are significantly reduced, and the energy consumption is also reduced by 2.05%.

Exhausted mature dendritic cells exhibit a slower and less persistent random motility but retain chemotaxis against CCL19

Dendritic cells (DCs), which are immune sentinels in the peripheral tissues, play a number of roles, including patrolling for pathogens, internalising antigens, transporting antigens to the lymph nodes (LNs), interacting with T cells, and secreting cytokines. The well-coordinated migration of DCs under various immunological or inflammatory conditions is therefore essential to ensure an effective immune response. Upon maturation, DCs migrate faster and more persistently than immature DCs (iDCs), which is believed to facilitate CCR7-dependent chemotaxis. It has been reported that lipopolysaccharide-activated DCs produce IL-12 only transiently, and become resistant to further stimulation through exhaustion. However, little is known about the influence of DC exhaustion on cellular motility. Here, we studied the cellular migration of exhausted DCs in tissue-mimicked confined environments. We found that the speed of exhausted matured DCs (xmDCs) decreased significantly compared to active matured DCs (amDCs) and iDCs. In contrast, the speed fluctuation increased compared to that of amDCs and was similar to that of iDCs. In addition, the diffusivity of the xmDCs was significantly lower than that of the amDCs, which implies that DC exhaustion reduces the space exploration ability. Interestingly, CCR7-dependent chemotaxis against CCL19 in xmDCs was not considerably different from that observed in amDCs. Taken together, we report a unique intrinsic cell migration behavior of xmDCs, which exhibit a slower, less persistent, and less diffusive random motility, which results in the DCs remaining at the site of infection, although a well-preserved CCR7-dependent chemotactic motility is maintained.