Eddies Stream And Convergence Zones In Turbulent Flows PdfBy Friedrich D. In and pdf 15.05.2021 at 20:28 5 min read
File Name: eddies stream and convergence zones in turbulent flows .zip
- The emergence of characteristic (coherent?) motion in homogeneous turbulent shear flows
- Eddies, streams, and convergence zones in turbulent flows
- Understanding vortex identifiication criteria
- Eddy (fluid dynamics)
Turbulence and Coherent Structures pp Cite as. Dynamical coherent structures are isolated regions where the vorticity is large and has a characteristic form and which have their own dynamical life and could exist in isolation Hussain One approach to analyzing the dynamics of CS is to consider how typical forms of these vortex structures interact with each other and with the ambient shear flow.
The emergence of characteristic (coherent?) motion in homogeneous turbulent shear flows
In computational fluid dynamics, there is an inevitable trade off between accuracy and computational cost. In this work, a novel multi-fidelity deep generative model is introduced for the surrogate modeling of high-fidelity turbulent flow fields given the solution of a computationally inexpensive but inaccurate low-fidelity solver.
The resulting surrogate is able to generate physically accurate turbulent realizations at a computational cost magnitudes lower than that of a high-fidelity simulation.
The deep generative model developed is a conditional invertible neural network, built with normalizing flows, with recurrent LSTM connections that allow for stable training of transient systems with high predictive accuracy. The model is trained with a variational loss that combines both data-driven and physics-constrained learning.
This deep generative model is applied to non-trivial high Reynolds number flows governed by the Navier-Stokes equations including turbulent flow over a backwards facing step at different Reynolds numbers and turbulent wake behind an array of bluff bodies. For both of these examples, the model is able to generate unique yet physically accurate turbulent fluid flows conditioned on an inexpensive low-fidelity solution.
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Eddies, streams, and convergence zones in turbulent flows
The low-pressure vortex analysis is performed for the study of dynamical properties of tubular vortices in turbulence. An automatic tracking scheme of arbitrarily chosen vortices is developed which makes it easier to examine the history of individual vortices. The low-pressure vortices have typically two distinct regions of high vorticity, that is, the tubular central core and surrounding spiral arms. The vorticity in these two regions is perpendicular to each other. It is observed that both the length of fluid lines and the area of fluid surfaces increase, in average, exponentially in time with growth rates of 0. The main contribution to these stretching comes from the velocity induced by vortices. Unable to display preview.
The C and streaming (S) zones were defined in order to define the whole flow field. It is concluded that homogeneous and sheared turbulent flow fields are made.
Understanding vortex identifiication criteria
Manuscript received July 11, ; final manuscript received August 19, ; published online October 30, Editor: David Wisler. Rehill, B.
Department of Mechanical Engineering, Shizuoka University. In this study, the direct numerical simulation DNS for homogeneous shear turbulence in the system rotating along the streamwise direction is fulfilled. Due to the rotation effect, the turbulence energy becomes small during the initial short time and the Reynolds shear stress are suppressed more strongly with increasing the system angular velocity.
In computational fluid dynamics, there is an inevitable trade off between accuracy and computational cost. In this work, a novel multi-fidelity deep generative model is introduced for the surrogate modeling of high-fidelity turbulent flow fields given the solution of a computationally inexpensive but inaccurate low-fidelity solver. The resulting surrogate is able to generate physically accurate turbulent realizations at a computational cost magnitudes lower than that of a high-fidelity simulation. The deep generative model developed is a conditional invertible neural network, built with normalizing flows, with recurrent LSTM connections that allow for stable training of transient systems with high predictive accuracy.
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Eddy (fluid dynamics)
Robert D. Xiaohua Wu, Ph. Research Council Sourabh V. Eric S. Ronald J. Sandip Ghosal Associate Professor, Dept.
In fluid dynamics , an eddy is the swirling of a fluid and the reverse current created when the fluid is in a turbulent flow regime. Fluid behind the obstacle flows into the void creating a swirl of fluid on each edge of the obstacle, followed by a short reverse flow of fluid behind the obstacle flowing upstream, toward the back of the obstacle. This phenomenon is naturally observed behind large emergent rocks in swift-flowing rivers. In fluid mechanics and transport phenomena , an eddy is not a property of the fluid, but a violent swirling motion caused by the position and direction of turbulent flow.
Recent studies of turbulent shear flows have shown that many of their important kinematical and dynamical properties can be more clearly understood by.
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