2018
DOI: 10.1017/9781108566834
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Theory and Computation in Hydrodynamic Stability

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Cited by 33 publications
(42 citation statements)
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“…In a general turbulent flow, fluctuations are stationary random functions, which can be meaningfully characterised either via single-point statistics such as the mean, the variance or the autocorrelation function; or in terms of twopoint statistics, via the cross-correlation function. In the frequency domain, the most complete description of two-point statistics is provided by the cross-spectral density function, which is the Fourier transform of the cross-correlation function [56], but can also be defined as the expected value, P qq = E(qq H ), (24) where q here denotes a Fourier transform taken for a given realisation, and E is the expected-value operator, which amounts to an average of several realisations. Once q is discretised, P qq becomes a cross-spectral-density matrix, which is Hermitian; its main diagonal contains the real, positive power spectral densities (PSDs) of flow quantities at given spatial locations.…”
Section: Response To Stochastic Forcing 241 Frequency-domain Statismentioning
confidence: 99%
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“…In a general turbulent flow, fluctuations are stationary random functions, which can be meaningfully characterised either via single-point statistics such as the mean, the variance or the autocorrelation function; or in terms of twopoint statistics, via the cross-correlation function. In the frequency domain, the most complete description of two-point statistics is provided by the cross-spectral density function, which is the Fourier transform of the cross-correlation function [56], but can also be defined as the expected value, P qq = E(qq H ), (24) where q here denotes a Fourier transform taken for a given realisation, and E is the expected-value operator, which amounts to an average of several realisations. Once q is discretised, P qq becomes a cross-spectral-density matrix, which is Hermitian; its main diagonal contains the real, positive power spectral densities (PSDs) of flow quantities at given spatial locations.…”
Section: Response To Stochastic Forcing 241 Frequency-domain Statismentioning
confidence: 99%
“…The possibility of using linear stability theory to model turbulence dynamics is clearly attractive. Due to the interest in laminar-turbulent transition, a substantial body of knowledge exists and has been compiled in monographs [23,24] and review articles [25,26,27]. Linearisation of the flow equations simplifies most of the numerical work, and, perhaps more importantly, leads to a clearer understanding of relevant flow mechanisms, which become analogous to phenomena seen in transition: the growth of structures near the nozzle can, for instance, be associated with the equivalent Kelvin-Helmholtz instability observed in transitional flows.…”
Section: Introductionmentioning
confidence: 99%
“…By taking appropriate linear combinations of ̂( 0) and ̂ 2, two families of solutions can be formed that are distinguished by the value of ̂ at = 0. Specifically, "even" and "odd" modes can be identified such that for the even mode ̂≠ 0 at = 0, while for the odd mode In this investigation, however, only the even mode is considered, primarily because very many related stability problems the even mode is known to be the fastest-growing mode [34] .…”
Section: Appendixmentioning
confidence: 99%
“…Напомним, что в соответствии с существующим представлением об устойчивости плоских течений наличие точки перегиба : 2 2 ( ) = 0 профиля скорости ( ) является необходимым условием возникновения неустойчивости при пренебрежимо малой вязкости (так называемый механизм возникновения «невязкой неустойчивости»). При этом в случае нейтральной устойчивости (Re = Re L ) точка перегиба должна совпадать с «критической» точкой , в которой скорость основного течения равна фазовой скорости ведущей моды: ( ) = [59]. Это позволяет объяснить зависимость устойчивости основного течения от профиля его скорости и предсказать области наибольших значений модуля продольной компоненты скорости ведущей моды, то есть области возникновения и развития неустойчивости.…”
Section: линейное критическое число рейнольдсаunclassified