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Avoids the clutter and maintenance effort associated with providing the function signature string.
353 lines
8.3 KiB
C
353 lines
8.3 KiB
C
/*---------------------------------------------------------------------------*\
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========= |
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\\ / F ield | OpenFOAM: The Open Source CFD Toolbox
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\\ / O peration |
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\\ / A nd | Copyright (C) 2011-2015 OpenFOAM Foundation
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\\/ M anipulation |
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-------------------------------------------------------------------------------
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License
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This file is part of OpenFOAM.
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OpenFOAM is free software: you can redistribute it and/or modify it
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under the terms of the GNU General Public License as published by
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the Free Software Foundation, either version 3 of the License, or
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(at your option) any later version.
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OpenFOAM is distributed in the hope that it will be useful, but WITHOUT
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ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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for more details.
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You should have received a copy of the GNU General Public License
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along with OpenFOAM. If not, see <http://www.gnu.org/licenses/>.
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\*---------------------------------------------------------------------------*/
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#include "tensor.H"
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#include "mathematicalConstants.H"
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using namespace Foam::constant::mathematical;
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// * * * * * * * * * * * * * * Static Data Members * * * * * * * * * * * * * //
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namespace Foam
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{
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template<>
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const char* const tensor::typeName = "tensor";
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template<>
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const char* tensor::componentNames[] =
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{
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"xx", "xy", "xz",
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"yx", "yy", "yz",
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"zx", "zy", "zz"
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};
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template<>
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const tensor tensor::zero
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(
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0, 0, 0,
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0, 0, 0,
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0, 0, 0
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);
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template<>
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const tensor tensor::one
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(
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1, 1, 1,
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1, 1, 1,
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1, 1, 1
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);
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template<>
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const tensor tensor::max
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(
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VGREAT, VGREAT, VGREAT,
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VGREAT, VGREAT, VGREAT,
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VGREAT, VGREAT, VGREAT
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);
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template<>
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const tensor tensor::min
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(
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-VGREAT, -VGREAT, -VGREAT,
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-VGREAT, -VGREAT, -VGREAT,
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-VGREAT, -VGREAT, -VGREAT
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);
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template<>
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const tensor tensor::I
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(
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1, 0, 0,
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0, 1, 0,
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0, 0, 1
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);
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}
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// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * //
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Foam::vector Foam::eigenValues(const tensor& t)
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{
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// The eigenvalues
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scalar i, ii, iii;
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// diagonal matrix
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if
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(
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(
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mag(t.xy()) + mag(t.xz()) + mag(t.yx())
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+ mag(t.yz()) + mag(t.zx()) + mag(t.zy())
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)
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< SMALL
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)
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{
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i = t.xx();
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ii = t.yy();
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iii = t.zz();
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}
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// non-diagonal matrix
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else
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{
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// Coefficients of the characteristic polynmial
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// x^3 + a*x^2 + b*x + c = 0
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scalar a =
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- t.xx() - t.yy() - t.zz();
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scalar b =
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t.xx()*t.yy() + t.xx()*t.zz() + t.yy()*t.zz()
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- t.xy()*t.yx() - t.yz()*t.zy() - t.zx()*t.xz();
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scalar c =
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- t.xx()*t.yy()*t.zz()
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- t.xy()*t.yz()*t.zx() - t.xz()*t.zy()*t.yx()
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+ t.xx()*t.yz()*t.zy() + t.yy()*t.zx()*t.xz() + t.zz()*t.xy()*t.yx();
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// Auxillary variables
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scalar aBy3 = a/3;
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scalar P = (a*a - 3*b)/9; // == -p_wikipedia/3
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scalar PPP = P*P*P;
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scalar Q = (2*a*a*a - 9*a*b + 27*c)/54; // == q_wikipedia/2
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scalar QQ = Q*Q;
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// Three identical roots
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if (mag(P) < SMALL && mag(Q) < SMALL)
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{
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return vector(- aBy3, - aBy3, - aBy3);
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}
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// Two identical roots and one distinct root
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else if (mag(PPP/QQ - 1) < SMALL)
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{
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scalar sqrtP = sqrt(P);
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scalar signQ = sign(Q);
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i = ii = signQ*sqrtP - aBy3;
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iii = - 2*signQ*sqrtP - aBy3;
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}
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// Three distinct roots
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else if (PPP > QQ)
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{
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scalar sqrtP = sqrt(P);
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scalar value = cos(acos(Q/sqrt(PPP))/3);
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scalar delta = sqrt(3 - 3*value*value);
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i = - 2*sqrtP*value - aBy3;
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ii = sqrtP*(value + delta) - aBy3;
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iii = sqrtP*(value - delta) - aBy3;
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}
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// One real root, two imaginary roots
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// based on the above logic, PPP must be less than QQ
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else
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{
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WarningInFunction
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<< "complex eigenvalues detected for tensor: " << t
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<< endl;
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if (mag(P) < SMALL)
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{
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i = cbrt(QQ/2);
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}
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else
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{
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scalar w = cbrt(- Q - sqrt(QQ - PPP));
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i = w + P/w - aBy3;
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}
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return vector(-VGREAT, i, VGREAT);
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}
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}
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// Sort the eigenvalues into ascending order
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if (i > ii)
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{
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Swap(i, ii);
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}
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if (ii > iii)
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{
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Swap(ii, iii);
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}
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if (i > ii)
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{
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Swap(i, ii);
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}
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return vector(i, ii, iii);
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}
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Foam::vector Foam::eigenVector
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(
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const tensor& t,
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const scalar lambda
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)
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{
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// Constantly rotating direction ensures different eigenvectors are
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// generated when called sequentially with a multiple eigenvalue
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static vector direction(1,0,0);
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vector oldDirection(direction);
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scalar temp = direction[2];
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direction[2] = direction[1];
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direction[1] = direction[0];
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direction[0] = temp;
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// Construct the linear system for this eigenvalue
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tensor A(t - lambda*I);
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// Determinants of the 2x2 sub-matrices used to find the eigenvectors
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scalar sd0, sd1, sd2;
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scalar magSd0, magSd1, magSd2;
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// Sub-determinants for a unique eivenvalue
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sd0 = A.yy()*A.zz() - A.yz()*A.zy();
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sd1 = A.zz()*A.xx() - A.zx()*A.xz();
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sd2 = A.xx()*A.yy() - A.xy()*A.yx();
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magSd0 = mag(sd0);
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magSd1 = mag(sd1);
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magSd2 = mag(sd2);
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// Evaluate the eigenvector using the largest sub-determinant
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if (magSd0 >= magSd1 && magSd0 >= magSd2 && magSd0 > SMALL)
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{
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vector ev
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(
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1,
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(A.yz()*A.zx() - A.zz()*A.yx())/sd0,
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(A.zy()*A.yx() - A.yy()*A.zx())/sd0
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);
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return ev/mag(ev);
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}
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else if (magSd1 >= magSd2 && magSd1 > SMALL)
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{
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vector ev
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(
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(A.xz()*A.zy() - A.zz()*A.xy())/sd1,
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1,
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(A.zx()*A.xy() - A.xx()*A.zy())/sd1
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);
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return ev/mag(ev);
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}
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else if (magSd2 > SMALL)
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{
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vector ev
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(
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(A.xy()*A.yz() - A.yy()*A.xz())/sd2,
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(A.yx()*A.xz() - A.xx()*A.yz())/sd2,
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1
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);
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return ev/mag(ev);
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}
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// Sub-determinants for a repeated eigenvalue
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sd0 = A.yy()*direction.z() - A.yz()*direction.y();
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sd1 = A.zz()*direction.x() - A.zx()*direction.z();
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sd2 = A.xx()*direction.y() - A.xy()*direction.x();
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magSd0 = mag(sd0);
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magSd1 = mag(sd1);
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magSd2 = mag(sd2);
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// Evaluate the eigenvector using the largest sub-determinant
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if (magSd0 >= magSd1 && magSd0 >= magSd2 && magSd0 > SMALL)
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{
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vector ev
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(
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1,
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(A.yz()*direction.x() - direction.z()*A.yx())/sd0,
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(direction.y()*A.yx() - A.yy()*direction.x())/sd0
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);
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return ev/mag(ev);
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}
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else if (magSd1 >= magSd2 && magSd1 > SMALL)
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{
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vector ev
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(
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(direction.z()*A.zy() - A.zz()*direction.y())/sd1,
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1,
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(A.zx()*direction.y() - direction.x()*A.zy())/sd1
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);
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return ev/mag(ev);
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}
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else if (magSd2 > SMALL)
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{
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vector ev
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(
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(A.xy()*direction.z() - direction.y()*A.xz())/sd2,
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(direction.x()*A.xz() - A.xx()*direction.z())/sd2,
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1
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);
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return ev/mag(ev);
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}
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// Triple eigenvalue
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return oldDirection;
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}
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Foam::tensor Foam::eigenVectors(const tensor& t)
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{
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vector evals(eigenValues(t));
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tensor evs
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(
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eigenVector(t, evals.x()),
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eigenVector(t, evals.y()),
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eigenVector(t, evals.z())
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);
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return evs;
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}
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Foam::vector Foam::eigenValues(const symmTensor& t)
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{
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return eigenValues(tensor(t));
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}
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Foam::vector Foam::eigenVector(const symmTensor& t, const scalar lambda)
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{
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return eigenVector(tensor(t), lambda);
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}
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Foam::tensor Foam::eigenVectors(const symmTensor& t)
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{
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return eigenVectors(tensor(t));
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}
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// ************************************************************************* //
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