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Full-Text Articles in Physics
Prediction Of The Stochastic Behavior Of Nonlinear Systems By Deterministic Models As A Classical Time-Passage Probabilistic Problem, L. M. Ivanov, A. D. Kirwan Jr., O. V. Melnichenko
Prediction Of The Stochastic Behavior Of Nonlinear Systems By Deterministic Models As A Classical Time-Passage Probabilistic Problem, L. M. Ivanov, A. D. Kirwan Jr., O. V. Melnichenko
CCPO Publications
Assuming that the behaviour of a nonlinear stochastic system can be described by a Markovian diffusion approximation and that the evolution equations can be reduced to a system of ordinary differential equations, a method for the calculation of prediction time is developed. In this approach, the prediction time depends upon the accuracy of prediction, the intensity of turbulence, the accuracy of the initial conditions, the physics contained in the mathematical model, the measurement errors, and the number of prediction variables. A numerical application to zonal channel flow illustrates the theory. Some possible generalizations of the theory are also discussed.
Multigrid Acceleration Of Time-Dependent Solutions Of Navier-Stokes Equations, Sarafa Oladele Ibraheem
Multigrid Acceleration Of Time-Dependent Solutions Of Navier-Stokes Equations, Sarafa Oladele Ibraheem
Mechanical & Aerospace Engineering Theses & Dissertations
Recent progress in Computational Fluid Dynamics is encouraging scientists to look at fine details of flow physics of problems in which natural unsteady phenomena have hitherto been neglected. The acceleration methods that have proven very successful in steady state computations can be explored for time dependent computations. In this work, an efficient multigrid methods is developed to solve the time-dependent Euler and Navier-Stokes equations. The Beam-Warming ADI method is used as the base algorithm for time stepping calculations. Application of the developed algorithm proved very efficient in selected steady and unsteady test problems. For instance, the inherent unsteadiness present in …