Iteration-Based Recycling and Reshaping Method for Inflow Turbulence Generation and Its Evaluation

For the analysis of the aerodynamic characteristics of the buildings immersed in the atmospheric boundary layer (ABL), it is necessary to generate a turbulence velocity field with similar temporal and special characteristics to the ABL to obtain a reliable result. In this paper, an improved precursor simulation method called the recycling and reshaping method (RRM) is proposed to generate a turbulent boundary layer in an LES model. The laminar inflow is firstly disturbed by the virtual roughness blocks realized by adding drag force term in the momentum equation, then the inflow velocity profile is reshaped every several steps to adjust the streamwise velocity profile in the downstream target area to meet the requirements. The final turbulence field generated by RRM with virtual roughness blocks is in good agreement with the target velocity conditions. Then, the simulation of the wind-induced pressure on an isolated low-rise building surface is carried out, using the generated turbulence boundary layer as inflow. The comparison between numerical results and TPU aerodynamic database shows that the time-averaged wind-induced surface pressure obtained by LES can be considered in good accordance with the measurements over the whole building surface. However, the non-ignorable deviations for the fluctuating pressure result in the flow separation corners still exist.

Humans can track but fail to predict accelerating objects

Objects in our visual environment often move unpredictably and can suddenly speed up or slow down. The ability to account for acceleration when interacting with moving objects can be critical for survival. Here, we investigate how human observers track an accelerating target with their eyes and predict its time of reappearance after a temporal occlusion by making an interceptive hand movement. Before occlusion, the target was initially visible and accelerated for a brief period. We tested how observers integrated target motion information by comparing three alternative models that predicted time-to-contact (TTC) based on the (1) final target velocity sample before occlusion, (2) average target velocity before occlusion, or (3) target acceleration. We show that visually-guided smooth pursuit eye movements reliably reflect target acceleration prior to occlusion. However, systematic saccade and manual interception timing errors reveal an inability to consider acceleration when predicting TTC. Interception timing is best described by the final velocity model that relies on extrapolating the last available velocity sample before occlusion. These findings provide compelling evidence for differential acceleration integration mechanisms in vision-guided eye movements and prediction-guided interception and a mechanistic explanation for the function and failure of interactions with accelerating objects.

The influence of stimulus and behavioral histories on predictive control of smooth pursuit eye movements

The smooth pursuit system has the ability to perform predictive feedforward control of eye movements. This study attempted to examine how stimulus and behavioral histories of past trials affect the control of predictive pursuit of target motion with randomized velocities. We used sequential ramp stimuli where the rightward velocity was fixed at 16 deg/s while the leftward velocity was either fixed (predictable) at one of seven velocities (4, 8, 12, 16, 20, 24, or 28 deg/s) or randomized (unpredictable). As a result, predictive pursuit responses were observed not only in the predictable condition but also in the unpredictable condition. Linear mixed-effects (LME) models showed that both stimulus and behavioral histories of the previous two or three trials influenced the predictive pursuit responses in the unpredictable condition. Intriguingly, the goodness of fit of the LME model was improved when both historical effects were fitted simultaneously rather than when each type of historical data was fitted alone. Our results suggest that predictive pursuit systems allow us to track randomized target motion using weighted averaging of the information of target velocity (stimulus) and motor output (behavior) in past time sequences.

Research on a Visual Servo Method of a Manipulator Based on Velocity Feedforward

In this paper, a method of predicting the motion state of a moving target in the base coordinate system by hand-eye vision and the position and attitude of the end is proposed. The predicted value is used as the velocity feedforward, and the position-based visual servo method is used to plan the velocity of the end of the manipulator. It overcomes the influence of end coordinate system motion on target prediction in a discrete system and introduces an integral control method to compensate for the prediction velocity, eliminating the end tracking error caused by target velocity prediction error. The effectiveness of this method is verified by simulation and experiment.

Azimuth Resolution Improvement and Target Parameters Inversion for Distributed Shipborne High Frequency Hybrid Sky-Surface Wave Radar

In this paper, the aperture synthesis processing techniques for the distributed shipborne high frequency hybrid sky-surface wave radar (HFHSSWR) are proposed to improve the azimuth resolution and obtain the velocity vector and the azimuth estimation of the moving target. First, the system geometry and the signal model of the moving target for the distributed shipborne HFHSSWR are formulated, and then the azimuth resolution improvement principle is derived. Second, based on the developed signal model, we propose an azimuth resolution improvement algorithm, which can obtain the synthetic azimuth bandwidth and an improved resolution using sub-band combination. Finally, a target parameters inversion method is introduced to estimate the target velocity vector and the target azimuth, by solving the equations regarding the target geometry and echo signal parameters numerically. The simulations are performed to verify the proposed algorithms. The results indicate that the distributed synthetic aperture techniques effectively improve the azimuth resolution of this radar, and can obtain the target velocity vector and the high-precision estimation of the target azimuth.

The influence of stimulus and behavioral histories on predictive control of smooth pursuit eye movements

The pursuit system has the ability to perform predictive control of eye movements. Even when the target motion is unpredictable due to velocity or direction changes, preceding changes in eye velocity are generated based on weighted averaging of past stimulus timing. However, it is still uncertain whether behavioral history influences the control of predictive pursuit. Thus, we attempted to clarify the influences of stimulus and behavioral histories on predictive pursuit to randomized target velocity. We used alternating-ramp stimuli, where the rightward velocity was fixed while the leftward velocity was either fixed (predictable) or randomized (unpredictable). Predictive eye deceleration was observed regardless of whether the target velocity was predictable or not. In particular, the predictable condition showed that the predictive pursuit responses corresponded to future target velocity. The linear mixed-effects model showed that both stimulus and behavioral histories of the previous two or three trials had influences on the predictive pursuit responses to the unpredictable target velocity. Our results suggest that the predictive pursuit system allows to track randomized target motion using the information from previous several trials, and the information of sensory input (stimulus) and motor output (behavior) in the past time sequences have partially different influences on predictive pursuit.

A Macroscopic Traffic Model Based on the Safe Velocity at Transitions

The increasing volume of vehicles on the road has had a significant impact on traffic flow. Congestion in urban areas is now a major concern. To mitigate congestion, an accurate model is required which is based on realistic traffic dynamics. A new traffic model is proposed based on the conservation law of vehicles which considers traffic dynamics at transitions. Traffic alignment to forward conditions is affected by the time and distance between vehicles. Thus, the well-known Lighthill, Whitham, and Richards (LWR) model is modified to account for traffic behavior during alignment. A model for inhomogeneous traffic flow during transitions is proposed which can be used to characterize traffic evolution. The performance of the proposed model is compared with the LWR model using the Greenshields and Underwood target velocity distributions. These models are evaluated using the Godunov technique and numerical stability is guaranteed by considering the Courant, Friedrich, and Lewy (CFL) condition. The results obtained show that the proposed model characterizes the flow more realistically, and thus can provide better insight into traffic behavior for use in controlling congestion and pollution levels, and improving public safety. Doi: 10.28991/cej-2021-03091710 Full Text: PDF