44 rodas34::d2 = -0.1043,
46 rodas34::d4 = -0.3620000000000023e-01,
47 rodas34::a21 = 0.1544e1,
48 rodas34::a31 = 0.9466785280815826,
49 rodas34::a32 = 0.2557011698983284,
50 rodas34::a41 = 0.3314825187068521e1,
51 rodas34::a42 = 0.2896124015972201e1,
52 rodas34::a43 = 0.9986419139977817,
53 rodas34::a51 = 0.1221224509226641e1,
54 rodas34::a52 = 0.6019134481288629e1,
55 rodas34::a53 = 0.1253708332932087e2,
56 rodas34::a54 = -0.6878860361058950,
57 rodas34::c21 = -0.56688e1,
58 rodas34::c31 = -0.2430093356833875e1,
59 rodas34::c32 = -0.2063599157091915,
60 rodas34::c41 = -0.1073529058151375,
61 rodas34::c42 = -0.9594562251023355e1,
62 rodas34::c43 = -0.2047028614809616e2,
63 rodas34::c51 = 0.7496443313967647e1,
64 rodas34::c52 = -0.1024680431464352e2,
65 rodas34::c53 = -0.3399990352819905e2,
66 rodas34::c54 = 0.1170890893206160e2,
67 rodas34::c61 = 0.8083246795921522e1,
68 rodas34::c62 = -0.7981132988064893e1,
69 rodas34::c63 = -0.3152159432874371e2,
70 rodas34::c64 = 0.1631930543123136e2,
71 rodas34::c65 = -0.6058818238834054e1,
72 rodas34::gamma = 0.25;
134 odes_.jacobian(x0,
y0, dfdx_, dfdy_);
136 for (label i=0; i<n_; i++)
138 for (label j=0; j<n_; j++)
140 a_(i, j) = -dfdy_(i, j);
143 a_(i, i) += 1.0/(
gamma*dx);
151 k1_[i] = dydx0[i] + dx*d1*dfdx_[i];
159 y[i] =
y0[i] + a21*k1_[i];
162 odes_.derivatives(x0 +
c2*dx,
y, dydx_);
166 k2_[i] = dydx_[i] + dx*d2*dfdx_[i] + c21*k1_[i]/dx;
174 y[i] =
y0[i] + a31*k1_[i] + a32*k2_[i];
177 odes_.derivatives(x0 + c3*dx,
y, dydx_);
181 k3_[i] = dydx_[i] + dx*d3*dfdx_[i] + (c31*k1_[i] + c32*k2_[i])/dx;
189 y[i] =
y0[i] + a41*k1_[i] + a42*k2_[i] + a43*k3_[i];
192 odes_.derivatives(x0 + c4*dx,
y, dydx_);
196 k4_[i] = dydx_[i] + dx*d4*dfdx_[i]
197 + (c41*k1_[i] + c42*k2_[i] + c43*k3_[i])/dx;
205 dy_[i] = a51*k1_[i] + a52*k2_[i] + a53*k3_[i] + a54*k4_[i];
206 y[i] =
y0[i] + dy_[i];
209 odes_.derivatives(x0 + dx,
y, dydx_);
214 + (c51*k1_[i] + c52*k2_[i] + c53*k3_[i] + c54*k4_[i])/dx;
223 y[i] =
y0[i] + dy_[i];
226 odes_.derivatives(x0 + dx,
y, dydx_);
231 + (c61*k1_[i] + c62*k2_[i] + c63*k3_[i] + c64*k4_[i] + c65*k5_[i])/dx;
238 y[i] =
y0[i] + dy_[i] + err_[i];
241 return normalizeError(
y0,
y, err_);
virtual scalar solve(const scalar x0, const scalarField &y0, const scalarField &dydx0, const scalar dx, scalarField &y) const =0
Solve a single step dx and return the error.
Abstract base class for the systems of ordinary differential equations.
virtual bool resize()=0
Resize the ODE solver.
A list of keyword definitions, which are a keyword followed by a number of values (eg...
void LUDecompose(scalarSquareMatrix &matrix, labelList &pivotIndices)
LU decompose the matrix with pivoting.
const dimensionedScalar c2
Second radiation constant: default SI units: [m.K].
dimensionedScalar y0(const dimensionedScalar &ds)
An ODE solver for chemistry.
Macros for easy insertion into run-time selection tables.
#define forAll(list, i)
Loop across all elements in list.
bool resize(const label n)
Resize the ODE solver.
void resizeMatrix(scalarSquareMatrix &m) const
Field< scalar > scalarField
Specialisation of Field<T> for scalar.
rodas34(const ODESystem &ode, const dictionary &dict)
Construct from ODESystem.
defineTypeNameAndDebug(combustionModel, 0)
Abstract base-class for ODE system solvers.
static void resizeField(UList< Type > &f, const label n)
virtual scalar solve(const scalar x0, const scalarField &y0, const scalarField &dydx0, const scalar dx, scalarField &y) const
Solve a single step dx and return the error.
label n_
Size of the ODESystem (adjustable)
virtual bool resize()
Resize the ODE solver.
void LUBacksubstitute(const scalarSquareMatrix &luMmatrix, const labelList &pivotIndices, List< Type > &source)
LU back-substitution with given source, returning the solution in the source.
addToRunTimeSelectionTable(functionObject, pointHistory, dictionary)