Method Of Multiple Scales
   HOME

TheInfoList



OR:

In
mathematics Mathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics ...
and
physics Physics is the natural science that studies matter, its fundamental constituents, its motion and behavior through space and time, and the related entities of energy and force. "Physical science is that department of knowledge which r ...
, multiple-scale analysis (also called the method of multiple scales) comprises techniques used to construct uniformly valid
approximation An approximation is anything that is intentionally similar but not exactly equality (mathematics), equal to something else. Etymology and usage The word ''approximation'' is derived from Latin ''approximatus'', from ''proximus'' meaning ''very ...
s to the solutions of perturbation problems, both for small as well as large values of the
independent variable Dependent and independent variables are variables in mathematical modeling, statistical modeling and experimental sciences. Dependent variables receive this name because, in an experiment, their values are studied under the supposition or demand ...
s. This is done by introducing fast-scale and slow-scale variables for an independent variable, and subsequently treating these variables, fast and slow, as if they are independent. In the solution process of the perturbation problem thereafter, the resulting additional freedom – introduced by the new independent variables – is used to remove (unwanted) secular terms. The latter puts constraints on the approximate solution, which are called solvability conditions. Mathematics research from about the 1980s proposes that coordinate transforms and invariant manifolds provide a sounder support for multiscale modelling (for example, see
center manifold In the mathematics of evolving systems, the concept of a center manifold was originally developed to determine stability of degenerate equilibria. Subsequently, the concept of center manifolds was realised to be fundamental to mathematical modellin ...
and
slow manifold In mathematics, the slow manifold of an equilibrium point of a dynamical system occurs as the most common example of a center manifold. One of the main methods of simplifying dynamical systems, is to reduce the dimension of the system to that of ...
).


Example: undamped Duffing equation


Differential equation and energy conservation

As an example for the method of multiple-scale analysis, consider the undamped and unforced
Duffing equation The Duffing equation (or Duffing oscillator), named after Georg Duffing (1861–1944), is a non-linear second-order differential equation used to model certain damped and driven oscillators. The equation is given by :\ddot + \delta \dot + \ ...
: \frac + y + \varepsilon y^3 = 0, y(0)=1, \qquad \frac(0)=0, which is a second-order
ordinary differential equation In mathematics, an ordinary differential equation (ODE) is a differential equation whose unknown(s) consists of one (or more) function(s) of one variable and involves the derivatives of those functions. The term ''ordinary'' is used in contrast w ...
describing a
nonlinear In mathematics and science, a nonlinear system is a system in which the change of the output is not proportional to the change of the input. Nonlinear problems are of interest to engineers, biologists, physicists, mathematicians, and many other ...
oscillator Oscillation is the repetitive or periodic variation, typically in time, of some measure about a central value (often a point of equilibrium) or between two or more different states. Familiar examples of oscillation include a swinging pendulum ...
. A solution ''y''(''t'') is sought for small values of the (positive) nonlinearity parameter 0 < ''ε'' ≪ 1. The undamped Duffing equation is known to be a Hamiltonian system: \frac=-\frac, \qquad \frac=+\frac, \quad \text \quad H = \tfrac12 p^2 + \tfrac12 q^2 + \tfrac14 \varepsilon q^4, with ''q'' = ''y''(''t'') and ''p'' = ''dy''/''dt''. Consequently, the Hamiltonian ''H''(''p'', ''q'') is a conserved quantity, a constant, equal to ''H'' = ½ + ¼ ''ε'' for the given initial conditions. This implies that both ''y'' and ''dy''/''dt'' have to be bounded: \left, y(t) \ \le \sqrt \quad \text \quad \left, \frac \ \le \sqrt \qquad \text t.


Straightforward perturbation-series solution

A regular perturbation-series approach to the problem proceeds by writing y(t) = y_0(t) + \varepsilon y_1(t) + \mathcal(\varepsilon^2) and substituting this into the undamped Duffing equation. Matching powers of \varepsilon gives the system of equations \begin \frac + y_0 &= 0,\\ \frac + y_1 &= - y_0^3. \end Solving these subject to the initial conditions yields y(t) = \cos(t) + \varepsilon \left \tfrac \cos(3t) - \tfrac \cos(t) - \underbrace_\text \right + \mathcal(\varepsilon^2). Note that the last term between the square braces is secular: it grows without bound for large , ''t'', . In particular, for t = O(\varepsilon^) this term is ''O''(1) and has the same order of magnitude as the leading-order term. Because the terms have become disordered, the series is no longer an asymptotic expansion of the solution.


Method of multiple scales

To construct a solution that is valid beyond t = O(\epsilon^), the method of ''multiple-scale analysis'' is used. Introduce the slow scale ''t''1: t_1 = \varepsilon t and assume the solution ''y''(''t'') is a perturbation-series solution dependent both on ''t'' and ''t''1, treated as: y(t) = Y_0(t,t_1) + \varepsilon Y_1(t,t_1) + \cdots. So: \begin \frac &= \left( \frac + \frac \frac \right) + \varepsilon \left( \frac + \frac \frac \right) + \cdots \\ &= \frac + \varepsilon \left( \frac + \frac \right) + \mathcal(\varepsilon^2), \end using ''dt''1/''dt'' = ''ε''. Similarly: \frac = \frac + \varepsilon \left( 2 \frac + \frac \right) + \mathcal(\varepsilon^2). Then the zeroth- and first-order problems of the multiple-scales perturbation series for the Duffing equation become: \begin \frac + Y_0 &= 0, \\ \frac + Y_1 &= - Y_0^3 - 2\, \frac. \end


Solution

The zeroth-order problem has the general solution: Y_0(t,t_1) = A(t_1)\, e^ + A^\ast(t_1)\, e^, with ''A''(''t''1) a complex-valued amplitude to the zeroth-order solution ''Y''0(''t'', ''t''1) and ''i''2 = −1. Now, in the first-order problem the forcing in the
right hand side In mathematics, LHS is informal shorthand for the left-hand side of an equation. Similarly, RHS is the right-hand side. The two sides have the same value, expressed differently, since equality is symmetric.\left -3\, A^2\, A^\ast - 2\, i\, \frac \right, e^ - A^3\, e^ + c.c. where ''c.c.'' denotes the complex conjugate of the preceding terms. The occurrence of ''secular terms'' can be prevented by imposing on the – yet unknown – amplitude ''A''(''t''1) the ''solvability condition'' -3\, A^2\, A^\ast - 2\, i\, \frac = 0. The solution to the solvability condition, also satisfying the initial conditions and , is: A = \tfrac 1 2\, \exp \left(\tfrac 3 8\, i \, t_1 \right). As a result, the approximate solution by the multiple-scales analysis is y(t) = \cos \left \left( 1 + \tfrac38\, \varepsilon \right) t \right+ \mathcal(\varepsilon), using and valid for . This agrees with the nonlinear
frequency Frequency is the number of occurrences of a repeating event per unit of time. It is also occasionally referred to as ''temporal frequency'' for clarity, and is distinct from ''angular frequency''. Frequency is measured in hertz (Hz) which is eq ...
changes found by employing the Lindstedt–Poincaré method. This new solution is valid until t = O(\epsilon^). Higher-order solutions – using the method of multiple scales – require the introduction of additional slow scales, i.e., , , etc. However, this introduces possible ambiguities in the perturbation series solution, which require a careful treatment (see ; ).


Coordinate transform to amplitude/phase variables

Alternatively, modern approaches derive these sorts of models using coordinate transforms, like in the method of normal forms, as described next. A solution y\approx r\cos\theta is sought in new coordinates (r,\theta) where the amplitude r(t) varies slowly and the phase \theta(t) varies at an almost constant rate, namely d\theta/dt\approx 1. Straightforward algebra finds the coordinate transform y=r\cos\theta +\frac1\varepsilon r^3\cos3\theta +\frac1\varepsilon^2r^5(-21\cos3\theta+\cos5\theta)+\mathcal O(\varepsilon^3) transforms Duffing's equation into the pair that the radius is constant dr/dt=0 and the phase evolves according to \frac = 1 + \frac 3 8 \varepsilon r^2 -\frac\varepsilon^2r^4 +\mathcal O(\varepsilon^3). That is, Duffing's oscillations are of constant amplitude r but have different frequencies d\theta/dt depending upon the amplitude. More difficult examples are better treated using a time-dependent coordinate transform involving complex exponentials (as also invoked in the previous multiple time-scale approach). A web service will perform the analysis for a wide range of examples.


See also

* Method of matched asymptotic expansions * WKB approximation * Method of averaging *
Krylov–Bogoliubov averaging method The Krylov–Bogolyubov averaging method (Krylov–Bogolyubov method of averaging) is a mathematical method for approximate analysis of oscillating processes in non-linear mechanics. The method is based on the averaging principle when the exact diff ...


Notes


References

* * *


External links

*{{scholarpedia , title=Multiple scale analysis , urlname=Multiple_scale_analysis , curator=Carson C. Chow Mathematical physics Asymptotic analysis Perturbation theory