Godunov's Theorem
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In
numerical analysis Numerical analysis is the study of algorithms that use numerical approximation (as opposed to symbolic computation, symbolic manipulations) for the problems of mathematical analysis (as distinguished from discrete mathematics). It is the study of ...
and
computational fluid dynamics Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid flows. Computers are used to perform the calculations required to simulate th ...
, Godunov's theorem — also known as Godunov's order barrier theorem — is a mathematical
theorem In mathematics, a theorem is a statement that has been proved, or can be proved. The ''proof'' of a theorem is a logical argument that uses the inference rules of a deductive system to establish that the theorem is a logical consequence of th ...
important in the development of the theory of
high resolution scheme High-resolution schemes are used in the numerical solution of partial differential equations where high accuracy is required in the presence of shocks or discontinuities. They have the following properties: *Second- or higher-Order of accuracy, ...
s for the numerical solution of
partial differential equations In mathematics, a partial differential equation (PDE) is an equation which imposes relations between the various partial derivatives of a multivariable function. The function is often thought of as an "unknown" to be solved for, similarly to ...
. The theorem states that: :''Linear numerical schemes for solving
partial differential equations In mathematics, a partial differential equation (PDE) is an equation which imposes relations between the various partial derivatives of a multivariable function. The function is often thought of as an "unknown" to be solved for, similarly to ...
(PDE's), having the property of not generating new extrema (
monotone scheme Monotone refers to a sound, for example music or speech, that has a single unvaried tone. See: monophony. Monotone or monotonicity may also refer to: In economics *Monotone preferences, a property of a consumer's preference ordering. *Monotonici ...
), can be at most first-order accurate.'' Professor
Sergei K. Godunov Sergei Konstantinovich Godunov (russian: Серге́й Константи́нович Годуно́в; born July 17, 1929) is a Soviet and Russian professor at the Sobolev Institute of Mathematics of the Russian Academy of Sciences in Novosibirs ...
originally proved the theorem as a Ph.D. student at
Moscow State University M. V. Lomonosov Moscow State University (MSU; russian: Московский государственный университет имени М. В. Ломоносова) is a public research university in Moscow, Russia and the most prestigious ...
. It is his most influential work in the area of applied and numerical mathematics and has had a major impact on science and engineering, particularly in the development of methods used in
computational fluid dynamics Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to analyze and solve problems that involve fluid flows. Computers are used to perform the calculations required to simulate th ...
(CFD) and other computational fields. One of his major contributions was to prove the theorem (Godunov, 1954; Godunov, 1959), that bears his name.


The theorem

We generally follow Wesseling (2001). Aside Assume a continuum problem described by a PDE is to be computed using a numerical scheme based upon a uniform computational grid and a one-step, constant step-size, ''M'' grid point, integration algorithm, either implicit or explicit. Then if x_ = j\,\Delta x and t^ = n\,\Delta t , such a scheme can be described by : \sum\limits_^ \varphi _^ = \sum\limits_^ . \quad \quad ( 1) In other words, the solution \varphi _j^ at time n + 1 and location j is a linear function of the solution at the previous time step n. We assume that \beta _m determines \varphi _j^ uniquely. Now, since the above equation represents a linear relationship between \varphi _j^ and \varphi _j^ we can perform a linear transformation to obtain the following equivalent form, :\varphi _j^ = \sum\limits_m^ . \quad \quad ( 2) Theorem 1: ''Monotonicity preserving'' The above scheme of equation (2) is monotonicity preserving if and only if :\gamma _m \ge 0,\quad \forall m . \quad \quad ( 3) ''Proof'' - Godunov (1959) Case 1: (sufficient condition) Assume (3) applies and that \varphi _j^n is monotonically increasing with j . Then, because \varphi _j^n \le \varphi _^n \le \cdots \le \varphi _^n it therefore follows that \varphi _j^ \le \varphi _^ \le \cdots \le \varphi _^ because : \varphi _j^ - \varphi _^ = \sum\limits_m^ \ge 0 . \quad \quad ( 4) This means that monotonicity is preserved for this case. Case 2: (necessary condition) We prove the necessary condition by contradiction. Assume that \gamma _p^ < 0 for some p and choose the following monotonically increasing \varphi_j^n \quad , :\varphi _i^n = 0, \quad i < k;\quad \varphi _i^n = 1, \quad i \ge k . \quad \quad ( 5) Then from equation (2) we get : \varphi _j^ - \varphi _^ = \sum\limits_m^M \left( \right) = \left\ \right)^2 - , \quad \varphi _j^0 = \left( \right)^2 - . \quad \quad (12) The exact solution is : \varphi \left( \right) = \left( \right)^2 - . \quad \quad (13) If we assume the scheme to be at least second-order accurate, it should produce the following solution exactly : \varphi _j^1 = \left( \right)^2 - , \quad \varphi _j^0 = \left( \right)^2 - . \quad \quad (14) Substituting into equation (2) gives: : \left( \right)^2 - = \sum\limits_m^ . \quad \quad (15) Suppose that the scheme IS monotonicity preserving, then according to the theorem 1 above, \gamma _m \ge 0 . Now, it is clear from equation (15) that : \left( \right)^2 - \ge 0, \quad \forall j . \quad \quad (16) Assume \sigma > 0, \quad \sigma \notin \mathbb and choose j such that j > \sigma > \left( j - 1 \right) . This implies that \left( \right) > 0 and \left( \right) < 0 . It therefore follows that, : \left( \right)^2 - = \left( j - \sigma \right) \left(j - \sigma - 1 \right) < 0, \quad \quad (17) which contradicts equation (16) and completes the proof. The exceptional situation whereby \sigma = \left, c \ \in \mathbb{N} is only of theoretical interest, since this cannot be realised with variable coefficients. Also, integer
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numbers greater than unity would not be feasible for practical problems.


See also

*
Finite volume method The finite volume method (FVM) is a method for representing and evaluating partial differential equations in the form of algebraic equations. In the finite volume method, volume integrals in a partial differential equation that contain a divergenc ...
*
Flux limiter Flux limiters are used in high resolution schemes – numerical schemes used to solve problems in science and engineering, particularly fluid dynamics, described by partial differential equations (PDEs). They are used in high resolution schemes, su ...
*
Total variation diminishing In numerical methods, total variation diminishing (TVD) is a property of certain discretization schemes used to solve hyperbolic partial differential equations. The most notable application of this method is in computational fluid dynamics. The conc ...


References

*Godunov, Sergei K. (1954), ''Ph.D. Dissertation: Different Methods for Shock Waves'', Moscow State University. *Godunov, Sergei K. (1959), A Difference Scheme for Numerical Solution of Discontinuous Solution of Hydrodynamic Equations, ''Mat. Sbornik, 47, 271-306'', translated US Joint Publ. Res. Service, JPRS 7226, 1969. *Wesseling, Pieter (2001), ''Principles of Computational Fluid Dynamics'', Springer-Verlag.


Further reading

*Hirsch, C. (1990), ''Numerical Computation of Internal and External Flows'', vol 2, Wiley. *Laney, Culbert B. (1998), ''Computational Gas Dynamics'', Cambridge University Press. *Toro, E. F. (1999), ''Riemann Solvers and Numerical Methods for Fluid Dynamics'', Springer-Verlag. *Tannehill, John C., et al., (1997), ''Computational Fluid mechanics and Heat Transfer'', 2nd Ed., Taylor and Francis. Numerical differential equations Theorems in analysis Computational fluid dynamics