Visualization for the analysis of fluid motion
TL;DR: In the present issue, Vol.
Abstract: In the present issue, Vol. 8 / No. 1 of the Journal of Visualization, seven technical papers are presented. In many of them, visualization plays key role for the analysis of fluid motions. The authors spread all over the world such as the countries, China, Hong-Kong, Denmark, Turkey, Korea, U. S. A., Jordan and Japan, which indicates JOV is becoming popular journal in the world. On behalf of the Editorial Board, the editors of the present issue acknowledge all the authors, referees and the people that contributed to the publication of this issue. Fluid Motions are nonlinear in their nature. As a result, very different features of fluid motions appear when key parameters are changed. The key parameters in fluid dynamics are, for instance, Reynolds number, Mach number, Prandtl number, and else. Key parameters also lie in body geometries and their configurations immersed in fluid motion. There is infinite choice of the parameters for the problem settings. There are many methods for the approach to research of fluid motion. Theoretical, experimental and computational methods are the basic three. Fortunately, new measurement techniques especially using visualized allow us to carry out experiments for any flow configuration. Same is true for computational techniques. Now, there is a lot of good software available and progressed computer performance allowed us to carry out sophisticated simulations using PC’s. Based on the flow parameters, geometry parameters and the method of approach, we may prepare any number of technical papers by changing the key parameters. It may be necessary to do so for good understanding of nonlinear nature of fluid motions. When looking at the papers in this issue, we notice that it actually happens. They handle compressible flows/incompressible flows. Their approaches are experimental/computational. Their applications are so wide. There is an old publication “Journal of the Aeronautical Research Institute, Tokyo Imperial University”. The “Aeronautical Research Institute” now is the Institute of Space and Astronautical Science, Japan Aerospace Exploration Agency (ISAS/JAXA) for which one of the editors of the present issue works. As a No. 65 of this old journal published in January 1930, there appeared the lecture given by Prof. L. Prandtl in October 1929. Within 23 pages of this journal (which would be only four or five pages of JOV), he explained all about boundary layer theory, flow instability, mixing-length (turbulence models) and effect of compressibility (Prandtl-Glauert law). As fluid motion is nonlinear and the research became so difficult, deep analysis in a very narrow research area is required and we, researchers have fallen into such narrow region of fluid dynamics. When I saw the paper by Prof. Prandlt, I felt that we may need to stop and think what we are doing and how we are contributing to the research field of “Fluid Dynamics” from the global viewpoint. Visualization is a very good tool not only to understand the details of fluid motion but also to understand key feature of fluid motion. With this tool, we may be able to make much higher contributions to Fluid Dynamics.
Citations
More filters
TL;DR: Understanding the diverse roles of noise in neural computation will require the design of experiments based on new theory and models, into which biologically appropriate experimental detail feeds back at various levels of abstraction.
Abstract: Although typically assumed to degrade performance, random fluctuations, or noise, can sometimes improve information processing in non-linear systems One such form of 'stochastic facilitation', stochastic resonance, has been observed to enhance processing both in theoretical models of neural systems and in experimental neuroscience However, the two approaches have yet to be fully reconciled Understanding the diverse roles of noise in neural computation will require the design of experiments based on new theory and models, into which biologically appropriate experimental detail feeds back at various levels of abstraction
641 citations
TL;DR: These observations outline the essentials of an Active Sensing paradigm, and argue for increased emphasis on the study of sensory processes as specific to the dynamic motor/attentional context in which inputs are acquired.
557 citations
TL;DR: The psychological and neural underpinnings of metacognitive accuracy are reviewed, and a neural synthesis in which dorsolateral and anterior prefrontal cortical subregions interact with interoceptive cortices (cingulate and insula) to promote accurate judgements of performance is proposed.
Abstract: Ability in various cognitive domains is often assessed by measuring task performance, such as the accuracy of a perceptual categorization. A similar analysis can be applied to metacognitive reports about a task to quantify the degree to which an individual is aware of his or her success or failure. Here, we review the psychological and neural underpinnings of metacognitive accuracy, drawing on research in memory and decision-making. These data show that metacognitive accuracy is dissociable from task performance and varies across individuals. Convergent evidence indicates that the function of the rostral and dorsal aspect of the lateral prefrontal cortex (PFC) is important for the accuracy of retrospective judgements of performance. In contrast, prospective judgements of performance may depend upon medial PFC. We close with a discussion of how metacognitive processes relate to concepts of cognitive control, and propose a neural synthesis in which dorsolateral and anterior prefrontal cortical subregions interact with interoceptive cortices (cingulate and insula) to promote accurate judgements of performance.
538 citations
TL;DR: A serial dependence in perception characterized by a spatiotemporally tuned, orientation-selective operator—which the authors call a continuity field—that may promote visual stability over time is revealed.
Abstract: Visual input often arrives in a noisy and discontinuous stream, owing to head and eye movements, occlusion, lighting changes, and many other factors. Yet the physical world is generally stable; objects and physical characteristics rarely change spontaneously. How then does the human visual system capitalize on continuity in the physical environment over time? We found that visual perception in humans is serially dependent, using both prior and present input to inform perception at the present moment. Using an orientation judgment task, we found that, even when visual input changed randomly over time, perceived orientation was strongly and systematically biased toward recently seen stimuli. Furthermore, the strength of this bias was modulated by attention and tuned to the spatial and temporal proximity of successive stimuli. These results reveal a serial dependence in perception characterized by a spatiotemporally tuned, orientation-selective operator-which we call a continuity field-that may promote visual stability over time.
522 citations
TL;DR: The true effect of action video game playing may be to enhance the ability to learn new tasks, and such a mechanism may serve as a signature of training regimens that are likely to produce transfer of learning.
491 citations