Download
slide1 n.
Skip this Video
Loading SlideShow in 5 Seconds..
University of Washington ACMS – Spring 2006 PowerPoint Presentation
Download Presentation
University of Washington ACMS – Spring 2006

University of Washington ACMS – Spring 2006

60 Views Download Presentation
Download Presentation

University of Washington ACMS – Spring 2006

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. University of Washington ACMS – Spring 2006 Absolute and convective instability of the two-dimensional wake D.Tordella #, S.Scarsoglio # and M.Belan * # Dipartimento di Ingegneria Aeronautica e Spaziale, Politecnico di Torino, Italy * Dipartimento di Ingegneria Aeronautica e Spaziale, Politecnico di Milano, Italy

  2. Outline • Introduction and state-of-the-art • Basic equations and physical problem • Linear stability theory of normal modes • Stability analysis through spatio-temporal multiscale approach • Perturbative hypothesis – Saddle points sequence • Comparison with numerical and experimental results • Eigenfunctions and eigenvalues asymptotic theory • Conclusions and further developments

  3. Introduction and state-of-the-art A linear stability study for two-dimensional non-parallel flows in the intermediate and far wake behind a circular body is here presented. The hydrodynamic stability analysis is developed within the linear theory of normal modes. Through a synthetic perturbative hypothesis, it is observed the behavior of small oscillations applied to the base flow. An analytical expression of the base flow according to Navier-Stokes model is given by an asymptotic expansion (Tordella and Belan, 2003; Belan and Tordella, 2002), which considers non-parallelism effects (such as exchange of transverse momentum and entrainment). As the system is slowly evolving, a spatio-temporal multiscaling approach is applied to the base flow and then to the stability analysis. In this way, we can evaluate how weakly non-parallel flow assumption influences the behavior of the stability characteristics.

  4. Near-parallel flow assumption • Important feature of most of the linear stability analyses in literature (e.g. Mattingly and Criminale, 1972; Triantafyllou et al., 1986; Hultgren and Aggarwal, 1987); • Sequence of equivalent parallel problems: at each section behind the cylinder the properties of the wake are represented by the stability properties of a parallel flow having the same average velocity profile; • Lateral convection of the base flow neglected; • Instability originates in the near wake, where the streamlines are not parallel. The disturbances grow linearly in a region of absolute instability, that is downstream to the back stagnation point of the body and which is preceded and followed by convectively unstable regions (e.g. Monkewitz, 1988; Young & Zebib, 1989; Pier, 2002) global linear instability as the critical value of the flow control parameter is exceeded; • The nature of the instability is related to the dominant saddle points of the local complex dispersion relation.

  5. Criteria to define the frequency of the global mode are usually based on absolute and convective instability (e.g. Huerre and Monkewitz, 1990). • Absolute instability -> if any initial disturbance grows at any fixed location. For large time, the exponential growth will be limited by nonlinearities and a self-sustained oscillation is established. • Convective instability -> if any initial disturbance is damped in time at fixed point. The perturbation is convected away and, after sufficiently large time, the base flow is again undisturbed locally. • Multiple scale approach • When the flow evolution is slow compared to the disturbance quantities; • Two scales are usually considered: a long scale, the scale of the mean flow variations, and a short scale, the scale over which the disturbances vary; • Spatial multiscale ODE for the wave modulation and correction for the wave number (Schmid and Henningson, 2001; Tordella and Belan, 2005); • Spatio-temporal multiscale PDE for the wave modulation and correction for the wave number and complex frequency (Bouthier 1973).

  6. Basic equations and physical problem Steady, incompressible and viscous base flow described by continuity and Navier-Stokes equations with dimensionless quantities U(x,y), V(x,y), P(x,y),  = c/0  c R =cUcD/ Boundary conditions: symmetry to x, uniformity at infinity and field information in the intermediate wake

  7. To analytically define base flow, its domain is divided into two regions both described by Navier-Stokes model Inner region flow -> , Outer region flow -> , • Pressure longitudinal gradient, vorticity and transverse velocity are the physical quantities involved in matching criteria. • Composite expansion is, by construction, continuous and differentiable over the whole domain. • Accurate representation of the velocity and pressure distributions - obtained without restrictive hypothesis - and analytical simplicity of expansions.

  8. The inner expansion up to third order is the base flow approximation for the wake.

  9. vc vo vi ui uo uc po - p pc - p R = 34, x/D = 20. Fourth order of accuracy – Inner, outer and composite expansions for velocity and pressure. pi - p

  10. R = 34, x/D = 20. Comparison of the present fourth order outer and composite, Chang's outer and composite (1961), Kovasznay's experimental (1948) and Berrone's numerical (2001) longitudinal velocity distributions.

  11. Linear stability theory Base flow is excited with small oscillations. Perturbed system is described by Navier-Stokes model Subtracting base flow equations from those concerning perturbed flow and neglecting non linear oscillating terms, the linearized perturbative equation in term of stream function is Normal modes theory Perturbation is considered as sum of normal modes, which can be treated separately since the system is linear. complex eigenfunction, u*(x,y,t) = U(x,y) + u(x,y,t) v*(x,y,t) = V(x,y) + v(x,y,t) p*(x,y,t) = P0 + p(x,y,t)

  12. k0: wave number • h0 = k0 + i s0 complex wave number s0: spatial growth rate • 0 = 0 + i r0 complex frequency 0: frequency • r0: temporal growth rate • Perturbation amplitude is proportional to • r0 0 for at least one mode unstable flow • r0 0 for all modes stable flow • s0 0 for at least one mode convectively unstable flow • s0 0 for all modes convectively stable flow • Convective instability: r0 0 for all modes, s0 0 for at least one mode. Perturbation spatially amplified in a system moving with phase velocity of the wave but exponentially damped in time at fixed point. • Absolute instability: r0 0 (vg=0/h0=0 local energy increase) for at least one mode. Temporal amplification of the oscillation at fixed point.

  13. Stability analysis through multiscale approach • Slow spatial and temporal evolution of the system slow variables x1 = x, t1 = x. • = 1/R is a dimensionless parameter that characterizes non-parallelism of base flow. • Hypothesis: and are expansions in term of : • By substituting into the linearized perturbative equation, one has • (ODE dependent on ) + (ODE dependent on , ) + O (2) • Order zero theory. Homogeneous Orr-Sommerfeld equation (parametric in x1 ). • where , and A(x1,t1) is the slow spatio-temporal modulation, determined at next order. • By numerical solution eigenfunctions 0 and a discrete set of eigenvalues 0n

  14. First order theory. Non homogeneous Orr-Sommerfeld equation (x1 parameter). is related to base flow and it considers non-parallel effects through transverse velocity presence

  15. To obtain first order solution, the non homogeneous term is requested to be orthogonal to every solution of the homogeneous adjoint problem, so that Keeping in mind that , the complete problem gives First order corrections h1 e 1 are obtained by resolving numerically the evolution equation for modulation and differentiating numerically a(x,t) with respect to slow variables.

  16. Perturbative hypothesis – Saddle points sequence • First approximation of the dispersion relation 0=0(h0, x, R), by selecting the eigenvalue with the largest imaginary part at order 0. • For fixed values of x and R we choose saddle point (h0s, 0s) that satisfies condition 0/  h0 = 0, using multidimensional maps. R = 35, x/D = 4. Frequency and temporal growth rate – Level curves. 0=cost (thick curves), r0=cost (thin curves) s0 k0

  17. 0(k0,s0) - R = 35, x/D = 4.

  18. r0(k0,s0) - R = 35, x/D = 4.

  19. Saddle points determination is sensitive to the extension of the numerical bounded domain and to the number and collocation of grid points. R = 50, x/D = 7. Level curves - 0=cost (dashed curves), r0=cost (solid curves). Problems arise when small values of k0 are reached because, in the complex wave number plane, numerical singularities are present on the s0 axis. This aspect is already important at few diameters behind the body, since k0 rapidly decreases with x. By minimizing the relative error between data and interpolating curves, truncated Laurent series have been used to extrapolate saddle points behavior from data at lower x values that are more accurate.

  20. R = 35 – Computed saddle points (open circles) and extrapolated curve (solid line) • Once h0s(x) is known, the relative 0s(x) is given by dispersion relation; • The system is perturbed at every longitudinal station with those characteristics that at order zero are locally the most unstable for base flow; • The disturbance is conceived as a variable wave number disturbance locally tuned to the values of the complex wave number of the saddle point of the dispersion relation.

  21. Real (a) and Imaginary (b) part of the coefficients of the evolution equation for modulation - R = 35, 50, 100. Base flow and disturbance terms are present in coefficients p(x) and q(x).

  22. In p base flow is present only through u0, while in q also u1 and v1 are present: where is the adjoint eigenfunction.

  23. Comparison between instability characteristics with saddle point perturbation and h0(x0 = 4.10) = cost = 0.6254 – i 2.0754 perturbation at R=50: (a) wave number, (b) spatial growth rate, (c) pulsation, (d) temporal growth rate.

  24. Frequency. Comparison between the present solution (accuracy Δω = 0.05), Zebib's numerical study (1987), Pier’s direct numerical simulations (2002), Williamson's experimental results (1988) .

  25. Eigenfunctions and eigenvalues asymptotic theory An asymptotic analysis for the Orr-Sommerfeld zero order problem is proposed. For x   the eigenvalue problem becomes where This analysis offers a priori inferences in agreement with the far field results yielded by the numerical integration of the modulation equation. Comparison between the asymptotic curve (with unitary proportionality constant) and the saddle point curve r0(x).

  26. Conclusions and further developments • Analytical description of the base flow • Perturbation hypotesis – Saddle point sequence • Spatio-temporal multiscale approach • Comparison with numerical and experimental results • Asymptotic analysis for the far wake • Entrainment • Validity limits for first order corrections