scholarly journals Asymptotic Approximation of the Eigenvalues and the Eigenfunctions for the Orr-Sommerfeld Equation on Infinite Intervals

2019 ◽  
Vol 09 (12) ◽  
pp. 967-989
Author(s):  
Victor Nijimbere
SIAM Review ◽  
1987 ◽  
Vol 29 (4) ◽  
pp. 597-620 ◽  
Author(s):  
Isom H. Herron

2019 ◽  
Vol 14 (1) ◽  
pp. 52-58 ◽  
Author(s):  
A.D. Nizamova ◽  
V.N. Kireev ◽  
S.F. Urmancheev

The flow of a viscous model fluid in a flat channel with a non-uniform temperature field is considered. The problem of the stability of a thermoviscous fluid is solved on the basis of the derived generalized Orr-Sommerfeld equation by the spectral decomposition method in Chebyshev polynomials. The effect of taking into account the linear and exponential dependences of the fluid viscosity on temperature on the spectral characteristics of the hydrodynamic stability equation for an incompressible fluid in a flat channel with given different wall temperatures is investigated. Analytically obtained profiles of the flow rate of a thermovisible fluid. The spectral pictures of the eigenvalues of the generalized Orr-Sommerfeld equation are constructed. It is shown that the structure of the spectra largely depends on the properties of the liquid, which are determined by the viscosity functional dependence index. It has been established that for small values of the thermoviscosity parameter the spectrum compares the spectrum for isothermal fluid flow, however, as it increases, the number of eigenvalues and their density increase, that is, there are more points at which the problem has a nontrivial solution. The stability of the flow of a thermoviscous fluid depends on the presence of an eigenvalue with a positive imaginary part among the entire set of eigenvalues found with fixed Reynolds number and wavenumber parameters. It is shown that with a fixed Reynolds number and a wave number with an increase in the thermoviscosity parameter, the flow becomes unstable. The spectral characteristics determine the structure of the eigenfunctions and the critical parameters of the flow of a thermally viscous fluid. The eigenfunctions constructed in the subsequent works show the behavior of transverse-velocity perturbations, their possible growth or decay over time.


Author(s):  
S. G. Rajeev

Thenumerical solution of ordinary differential equations (ODEs)with boundary conditions is studied here. Functions are approximated by polynomials in a Chebychev basis. Sections then cover spectral discretization, sampling, interpolation, differentiation, integration, and the basic ODE. Following Trefethen et al., differential operators are approximated as rectangular matrices. Boundary conditions add additional rows that turn them into square matrices. These can then be diagonalized using standard linear algebra methods. After studying various simple model problems, this method is applied to the Orr–Sommerfeld equation, deriving results originally due to Orszag. The difficulties of pushing spectral methods to higher dimensions are outlined.


2021 ◽  
Vol 16 (1) ◽  
pp. 15-23
Author(s):  
Hal M. Switkay

We construct a model for the progress of the 2020 coronavirus epidemic in the United States of America, using probabilistic methods rather than the traditional compartmental model. We employ the generalized beta family of distributions, including those supported on bounded intervals and those supported on semi-infinite intervals. We compare the best-fit distributions for daily new cases and daily new deaths in America to the corresponding distributions for United Kingdom, Spain, and Italy. We explore how such a model might be justified theoretically in comparison to the apparently more natural compartmental model. We compare forecasts based on these models to observations, and find the forecasts useful in predicting total pandemic deaths.


1989 ◽  
Vol 26 (03) ◽  
pp. 512-523
Author(s):  
Clifton Sutton

Codes having all pairs of words separated by a Hamming distance of at least d are stochastically constructed by sequentially packing randomly generated q-ary n-tuples. Estimates of the random packing densities are obtained by repeated simulation. Using non-linear regression to fit the estimated densities, an asymptotic approximation formula is obtained for the packing densities which depends only on q, n, d, and an empirical constant.


2006 ◽  
Vol 76 (12) ◽  
pp. 1191-1200 ◽  
Author(s):  
Vladimir V. Ulyanov ◽  
Hirofumi Wakaki ◽  
Yasunori Fujikoshi

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