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view +time/+rk/rungekutta.m @ 1154:3108963cc42c feature/rv
Improve efficiency of diffOps in Burgers2d, the artificial diffusion operator in rv.constructDiffOps and the RungekuttaExteriorRv time-steppers
author | Vidar Stiernström <vidar.stiernstrom@it.uu.se> |
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date | Wed, 06 Mar 2019 09:45:52 +0100 |
parents | c6fcee3fcf1b |
children |
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% Takes one time step of size dt using the rungekutta method % starting from v_0 and where the function F(v,t) gives the % time derivatives. coeffs is a struct holding the RK coefficients % for the specific method. function v = rungekutta(v, t , dt, F, coeffs) % Compute the intermediate stages k k = zeros(length(v), coeffs.s); for i = 1:coeffs.s u = v; for j = 1:i-1 u = u + dt*coeffs.a(i,j)*k(:,j); end k(:,i) = F(u,t+coeffs.c(i)*dt); end % Compute the updated solution as a linear combination % of the intermediate stages. for i = 1:coeffs.s v = v + dt*coeffs.b(i)*k(:,i); end end