Interactive Visualization of Highly Time-Dependent Data from Numerical Simulations of Transitional and Turbulent Supersonic Flows

2001 ◽  
Author(s):  
Hermann F. Fasel
Keyword(s):  
Numerical Simulations ◽  
Interactive Visualization ◽  
Supersonic Flows ◽  
Time Dependent ◽  
Dependent Data

Time Dependent Data Mining in RAVEN

2016 ◽  
Author(s):  
Joshua Joseph Cogliati ◽  
Jun Chen ◽  
Japan Ketan Patel ◽  
Diego Mandelli ◽  
Daniel Patrick Maljovec ◽  
...  
Keyword(s):  
Data Mining ◽  
Time Dependent ◽  
Dependent Data

scholarly journals Learning Bounds of ERM Principle for Sequences of Time-Dependent Samples

2015 ◽  
Vol 2015 ◽  
pp. 1-8
Author(s):  
Mingchen Yao ◽  
Chao Zhang ◽  
Wei Wu
Keyword(s):  
Time Dependent ◽  
Dependent Data ◽  
Empirical Risk Minimization ◽  
Risk Minimization ◽  
Practical Applications ◽  
Empirical Risk ◽  
Learning Tasks ◽  
Generalization Bound ◽  
Erm Principle ◽  
Dependent Samples

Many generalization results in learning theory are established under the assumption that samples are independent and identically distributed (i.i.d.). However, numerous learning tasks in practical applications involve the time-dependent data. In this paper, we propose a theoretical framework to analyze the generalization performance of the empirical risk minimization (ERM) principle for sequences of time-dependent samples (TDS). In particular, we first present the generalization bound of ERM principle for TDS. By introducing some auxiliary quantities, we also give a further analysis of the generalization properties and the asymptotical behaviors of ERM principle for TDS.

Flow Mixing Enhancement from Balloon Pulsations in an Intravenous Oxygenator

2004 ◽  
Vol 127 (3) ◽  
pp. 400-415 ◽  
Author(s):  
Amador M. Guzmán ◽  
Rodrigo A. Escobar ◽  
Cristina H. Amon
Keyword(s):  
Numerical Simulations ◽  
Oxygen Transfer ◽  
Fiber Bundle ◽  
Transfer Rate ◽  
Oxygen Transfer Rate ◽  
Three Dimensional ◽  
Time Dependent ◽  
Fiber Placement ◽  
Flow Mixing ◽  
Dependent Flow

Computational investigations of flow mixing and oxygen transfer characteristics in an intravenous membrane oxygenator (IMO) are performed by direct numerical simulations of the conservation of mass, momentum, and species equations. Three-dimensional computational models are developed to investigate flow-mixing and oxygen-transfer characteristics for stationary and pulsating balloons, using the spectral element method. For a stationary balloon, the effect of the fiber placement within the fiber bundle and the number of fiber rings is investigated. In a pulsating balloon, the flow mixing characteristics are determined and the oxygen transfer rate is evaluated. For a stationary balloon, numerical simulations show two well-defined flow patterns that depend on the region of the IMO device. Successive increases of the Reynolds number raise the longitudinal velocity without creating secondary flow. This characteristic is not affected by staggered or non-staggered fiber placement within the fiber bundle. For a pulsating balloon, the flow mixing is enhanced by generating a three-dimensional time-dependent flow characterized by oscillatory radial, pulsatile longitudinal, and both oscillatory and random tangential velocities. This three-dimensional flow increases the flow mixing due to an active time-dependent secondary flow, particularly around the fibers. Analytical models show the fiber bundle placement effect on the pressure gradient and flow pattern. The oxygen transport from the fiber surface to the mean flow is due to a dominant radial diffusion mechanism, for the stationary balloon. The oxygen transfer rate reaches an asymptotic behavior at relatively low Reynolds numbers. For a pulsating balloon, the time-dependent oxygen-concentration field resembles the oscillatory and wavy nature of the time-dependent flow. Sherwood number evaluations demonstrate that balloon pulsations enhance the oxygen transfer rate, even for smaller flow rates.

scholarly journals Progress and Regress of Time Dependent Data and Application in Bank Branch

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
F. Hosseinzadeh Lotfi ◽  
Z. Taeb ◽  
S. Abbasbandy
Keyword(s):  
Decision Making ◽  
Commercial Bank ◽  
Spline Function ◽  
Time Dependent ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Dependent Data ◽  
Bank Branch ◽  
Decision Making Unit ◽  
Cubic Spline Function

To evaluate each decision making unit having time dependent inputs and outputs data, a new method has been developed and reported here. This method uses the Malmquist productivity index, and is a very simple function based on Cubic Spline function to determine the progress and regress of that unit. To show the capability of this developed method, the data of 9 branches of a commercial bank has been used, evaluated, and reported.

A New Time-dependent Theory of Tropical Cyclone Intensification

2021 ◽  
Author(s):  
Yuqing Wang ◽  
Yuanlong Li ◽  
Jing Xu
Keyword(s):  
Boundary Layer ◽  
Tropical Cyclone ◽  
Numerical Simulations ◽  
Strong Dependence ◽  
Surface Wind ◽  
Time Dependent ◽  
Quasi Equilibrium ◽  
Free Atmosphere ◽  
Near Surface ◽  
Tangential Wind

AbstractIn this study, the boundary-layer tangential wind budget equation following the radius of maximum wind, together with an assumed thermodynamical quasi-equilibrium boundary layer is used to derive a new equation for tropical cyclone (TC) intensification rate (IR). A TC is assumed to be axisymmetric in thermal wind balance with eyewall convection becoming in moist slantwise neutrality in the free atmosphere above the boundary layer as the storm intensifies as found recently based on idealized numerical simulations. An ad-hoc parameter is introduced to measure the degree of congruence of the absolute angular momentum and the entropy surfaces. The new IR equation is evaluated using results from idealized ensemble full-physics axisymmetric numerical simulations. Results show that the new IR equation can reproduce the time evolution of the simulated TC intensity. The new IR equation indicates a strong dependence of IR on both TC intensity and the corresponding maximum potential intensity (MPI). A new finding is the dependence of TC IR on the square of the MPI in terms of the near-surface wind speed for any given relative intensity. Results from some numerical integrations of the new IR equation also suggest the finite-amplitude nature of TC genesis. In addition, the new IR theory is also supported by some preliminary results based on best-track TC data over the North Atlantic and eastern and western North Pacific. Compared with the available time-dependent theories of TC intensification, the new IR equation can provide a realistic intensity-dependent IR during weak intensity stage as in observations.

scholarly journals Applying Time-Dependent Data for Fluorescence Tomography

2007 ◽  
Author(s):  
Ralf B. Schulz ◽  
Martin Schweiger ◽  
Cosimo D'Andrea ◽  
Gianluca Valentini ◽  
Jörg Peter ◽  
...  
Keyword(s):  
Time Dependent ◽  
Dependent Data ◽  
Fluorescence Tomography

Modeling the magnetic structure of CMEs in the inner heliosphere based on data-driven time-dependent simulations of active region evolution

2021 ◽  
Author(s):  
Jens Pomoell ◽  
Emilia Kilpua ◽  
Daniel Price ◽  
Eleanna Asvestari ◽  
Ranadeep Sarkar ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Active Region ◽  
Magnetic Structure ◽  
Interplanetary Space ◽  
Coronal Magnetic Field ◽  
Time Dependent ◽  
Data Driven ◽  
Dependent Data ◽  
Heliospheric Physics ◽  
The Magnetic Field

<p>Characterizing the detailed structure of the magnetic field in the active corona is of crucial importance for determining the chain of events from the formation to the destabilisation and subsequent eruption and propagation of coronal structures in the heliosphere. A comprehensive methodology to address these dynamic processes is needed in order to advance our capabilities to predict the properties of coronal mass ejections (CMEs) in interplanetary space and thereby for increasing the accuracy of space weather predictions. A promising toolset to provide the key missing information on the magnetic structure of CMEs are time-dependent data-driven simulations of active region magnetic fields. This methodology permits self-consistent modeling of the evolution of the coronal magnetic field from the emergence of flux to the birth of the eruption and beyond. </p><p>In this presentation, we discuss our modeling efforts in which time-dependent data-driven coronal modeling together with heliospheric physics-based modeling are employed to study and characterize CMEs, in particular their magnetic structure, at various stages in their evolution from the Sun to Earth. </p>

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