Mercurial > repos > public > sbplib
view +time/CdiffNonlin.m @ 1031:2ef20d00b386 feature/advectionRV
For easier comparison, return both the first order and residual viscosity when evaluating the residual. Add the first order and residual viscosity to the state of the RungekuttaRV time steppers
author | Vidar Stiernström <vidar.stiernstrom@it.uu.se> |
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date | Thu, 17 Jan 2019 10:25:06 +0100 |
parents | d1f9dd55a2b0 |
children | b5e5b195da1e |
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classdef CdiffNonlin < time.Timestepper properties D E S k t v v_prev n end methods function obj = CdiffNonlin(D, E, S, k, t0,n0, v, v_prev) m = size(D(v),1); default_arg('E',0); default_arg('S',0); if isnumeric(S) S = @(v,t)S; end if isnumeric(E) E = @(v)E; end % m = size(D,1); % default_arg('E',sparse(m,m)); % default_arg('S',sparse(m,1)); obj.D = D; obj.E = E; obj.S = S; obj.k = k; obj.t = t0; obj.n = n0; obj.v = v; obj.v_prev = v_prev; end function [v,t] = getV(obj) v = obj.v; t = obj.t; end function [vt,t] = getVt(obj) vt = (obj.v-obj.v_prev)/obj.k; % Could be improved using u_tt = f(u)) t = obj.t; end function obj = step(obj) D = obj.D(obj.v); E = obj.E(obj.v); S = obj.S(obj.v,obj.t); m = size(D,1); I = speye(m); %% Calculate for which indices we need to solve system of equations [rows,cols] = find(E); j = union(rows,cols); i = setdiff(1:m,j); %% Calculate matrices need for the timestep % Before optimization: A = 1/k^2 * I - 1/(2*k)*E; k = obj.k; Aj = 1/k^2 * I(j,j) - 1/(2*k)*E(j,j); B = 2/k^2 * I + D; C = -1/k^2 * I - 1/(2*k)*E; %% Take the timestep v = obj.v; v_prev = obj.v_prev; % Want to solve the seq A*v_next = b where b = (B*v + C*v_prev + S); % Before optimization: obj.v = A\b; obj.v(i) = k^2*b(i); obj.v(j) = Aj\b(j); obj.v_prev = v; %% Update state of the timestepper obj.t = obj.t + obj.k; obj.n = obj.n + 1; end end end