110 resultados para Ball velocity


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The fast ignitor scheme for inertial confinement fusion requires forward driving of the critical density surface by light pressure (hole boring) to allow energy deposition close to the dense fuel. The recession velocity of the critical density surface has been observed to be nu/c = 0.015 at an irradiance of 1.0 x 10(19) W cm(-2) at a wavelength of 1.05 micron, in quantitative agreement with modeling. (C) 1996 American Institute of Physics.

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The current study investigated the time-averaged velocity and turbulence intensity at the initial downstream flow from a six-bladed ship propeller. The six-bladed propeller provided the rapid periodical pulses of thrust in one revolution due to the blades leading to a complex downstream jet. The six-bladed propeller is popular as a boat racing propeller, but the presentation of its flow structure was rarely found in the previous studies. In this study, the experiments were carried out in a water tank to measure the time-averaged velocity and turbulence intensity by using a Laser Doppler Anemometry (LDA) system. The jet was produced by rotating the propeller at a constant speed powered by an electric motor. The maximum tangential and radial velocities of the six-bladed propeller were of 76% and 17% of the maximum axial velocity respectively. The study found that the six-bladed propeller has a lower tangential velocity, but a higher radial velocity with its own diffusing mechanism when comparing to the three-bladed propeller.

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The characterisation of soils for civil engineering purposes depends on removing sufficiently high-quality samples from the ground. Accurate evaluation of sample quality is therefore important if reliable design parameters are to be determined. This paper describes the use of unconfined shear wave velocity (V s) and suction (u r) measurements to assess sample quality rapidly in soft clay. Samples of varying quality from three well-characterised soft clay sites are initially assessed using conventional techniques, and their results compared with V s and u r measurements performed on the same samples. It is observed that the quality of samples indicated by these measurements is very similar to those inferred from traditional disturbance measures, with V s being the more reliable indicator. A tentative empirically derived criterion, based on samples tested in this project, is proposed to quantify sample disturbance combining both V s and u r measurements. Further work using this criterion on different materials is important so as to test its usefulness.

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Recent studies suggested that the control of hand movements in catching involves continuous vision-based adjustments. More insight into these adjustments may be gained by examining the effects of occluding different parts of the ball trajectory. Here, we examined the effects of such occlusion on lateral hand movements when catching balls approaching from different directions, with the occlusion conditions presented in blocks or in randomized order. The analyses showed that late occlusion only had an effect during the blocked presentation, and early occlusion only during the randomized presentation. During the randomized presentation movement biases were more leftward if the preceding trial was an early occlusion trial. The effect of early occlusion during the randomized presentation suggests that the observed leftward movement bias relates to the rightward visual acceleration inherent to the ball trajectories used, while its absence during the blocked presentation seems to reflect trial-by-trial adaptations in the visuomotor gain, reminiscent of dynamic gain control in the smooth pursuit system. The movement biases during the late occlusion block were interpreted in terms of an incomplete motion extrapolation--a reduction of the velocity gain--caused by the fact that participants never saw the to-be-extrapolated part of the ball trajectory. These results underscore that continuous movement adjustments for catching do not only depend on visual information, but also on visuomotor adaptations based on non-visual information.

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The authors studied pattern stability and error correction during in-phase and antiphase 4-ball fountain juggling. To obtain ball trajectories, they made and digitized high-speed film recordings of 4 highly skilled participants juggling at 3 different heights (and thus different frequencies). From those ball trajectories, the authors determined and analyzed critical events (i.e., toss, zenith, catch, and toss onset) in terms of variability of point estimates of relative phase and temporal correlations. Contrary to common findings on basic instances of rhythmic interlimb coordination, in-phase and antiphase patterns were equally variable (i.e., stable). Consistent with previous findings, however, pattern stability decreased with increasing frequency. In contrast to previous results for 3-ball cascade juggling, negative lag-one correlations for catch-catch intervals were absent, but the authors obtained evidence for error corrections between catches and toss onsets. That finding may have reflected participants' high skill level, which yielded smaller errors that allowed for corrections later in the hand cycle.

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Besides making contact with an approaching ball at the proper place and time, hitting requires control of the effector velocity at contact. A dynamical neural network for the planning of hitting movements was derived in order to account for both these requirements. The model in question implements continuous required velocity control by extending the Vector Integration To Endpoint model while providing explicit control of effector velocity at interception. It was shown that the planned movement trajectories generated by the model agreed qualitatively with the kinematics of hitting movements as observed in two recent experiments. Outstanding features of this comparison concerned the timing and amplitude of the empirical backswing movements, which were largely consistent with the predictions from the model. Several theoretical implications as well as the informational basis and possible neural underpinnings of the model were discussed.