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  2. Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta_methods

    The consequence of this difference is that at every step, a system of algebraic equations has to be solved. This increases the computational cost considerably. If a method with s stages is used to solve a differential equation with m components, then the system of algebraic equations has ms components.

  3. Numerical methods for ordinary differential equations - Wikipedia

    en.wikipedia.org/wiki/Numerical_methods_for...

    For example, the second-order equation y′′ = −y can be rewritten as two first-order equations: y′ = z and z′ = −y. In this section, we describe numerical methods for IVPs, and remark that boundary value problems (BVPs) require a different set of tools. In a BVP, one defines values, or components of the solution y at more than one ...

  4. List of Runge–Kutta methods - Wikipedia

    en.wikipedia.org/wiki/List_of_Runge–Kutta_methods

    On Padé approximations to the exponential function and A-stable methods for the numerical solution of initial value problems (PDF) (Thesis). Hairer, Ernst; Nørsett, Syvert Paul; Wanner, Gerhard (1993), Solving ordinary differential equations I: Nonstiff problems , Berlin, New York: Springer-Verlag , ISBN 978-3-540-56670-0 .

  5. Runge–Kutta–Fehlberg method - Wikipedia

    en.wikipedia.org/wiki/Runge–Kutta–Fehlberg...

    By performing one extra calculation, ... "New high-order Runge-Kutta formulas with step size control for systems of first and second-order differential equations".

  6. Linear multistep method - Wikipedia

    en.wikipedia.org/wiki/Linear_multistep_method

    Single-step methods (such as Euler's method) refer to only one previous point and its derivative to determine the current value. Methods such as Runge–Kutta take some intermediate steps (for example, a half-step) to obtain a higher order method, but then discard all previous information before taking a second step. Multistep methods attempt ...

  7. Euler method - Wikipedia

    en.wikipedia.org/wiki/Euler_method

    The next step is to multiply the above value by the step size , which we take equal to one here: h ⋅ f ( y 0 ) = 1 ⋅ 1 = 1. {\displaystyle h\cdot f(y_{0})=1\cdot 1=1.} Since the step size is the change in t {\displaystyle t} , when we multiply the step size and the slope of the tangent, we get a change in y {\displaystyle y} value.

  8. Midpoint method - Wikipedia

    en.wikipedia.org/wiki/Midpoint_method

    In numerical analysis, a branch of applied mathematics, the midpoint method is a one-step method for numerically solving the differential equation, ′ = (, ()), =. The explicit midpoint method is given by the formula

  9. Kutta–Joukowski theorem - Wikipedia

    en.wikipedia.org/wiki/Kutta–Joukowski_theorem

    Equation is a form of the Kutta–Joukowski theorem. Kuethe and Schetzer state the Kutta–Joukowski theorem as follows: [ 5 ] The force per unit length acting on a right cylinder of any cross section whatsoever is equal to ρ ∞ V ∞ Γ {\displaystyle \rho _{\infty }V_{\infty }\Gamma } and is perpendicular to the direction of V ∞ ...