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/* This file is part of the OpenLB library
*
* Copyright (C) 2013 Mathias J. Krause, Jonas Latt
* E-mail contact: info@openlb.net
* The most recent release of OpenLB can be downloaded at
* <http://www.openlb.net/>
*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public
* License along with this program; if not, write to the Free
* Software Foundation, Inc., 51 Franklin Street, Fifth Floor,
* Boston, MA 02110-1301, USA.
*/
/** \file
* MRT Dynamics with adjusted omega -- generic implementation.
*/
#ifndef STOCHASTIC_SGS_DYNAMICS_HH
#define STOCHASTIC_SGS_DYNAMICS_HH
#include <algorithm>
#include <limits>
#include "stochasticSGSdynamics.h"
#include "mrtDynamics.h"
#include "mrtHelpers.h"
#include "core/cell.h"
#include "core/util.h"
#include "math.h"
#include <stdlib.h>
#include <math.h>
#include <time.h>
#include <stdio.h>
using namespace std;
namespace olb {
/// Implementation of the Stochastic relaxation based on
/// " A stochastic subgrid model with application to turbulent flow and scalar mixing"; Phys. of Fluids 19; 2007
////////////////////// Class StochasticsSGSdynamics //////////////////////////
/** \param vs2_ speed of sound
* \param momenta_ a Momenta object to know how to compute velocity momenta
* \param momenta_ a Momenta object to know how to compute velocity momenta
*/
template<typename T, typename DESCRIPTOR>
StochasticSGSdynamics<T,DESCRIPTOR>::StochasticSGSdynamics (
T omega_, Momenta<T,DESCRIPTOR>& momenta_, T turbulenceInt_, T charU_, T smagoConst_, T dx_, T dt_)
: MRTdynamics<T,DESCRIPTOR>(omega_, momenta_),
turbulenceInt(turbulenceInt_),
smagoConst(smagoConst_),
charU(charU_),
preFactor(computePreFactor(omega_,smagoConst_) )
{
// T invM_S_SGS[DESCRIPTOR::q][DESCRIPTOR::q];
// T rtSGS[DESCRIPTOR::q]; // relaxation times vector for SGS approach.
// for (int iPop = 0; iPop < DESCRIPTOR::q; ++iPop)
// {
// rtSGS[iPop] = DESCRIPTOR::S[iPop];
// }
// for (int iPop = 0; iPop < DESCRIPTOR::shearIndexes; ++iPop)
// {
// rtSGS[DESCRIPTOR::shearViscIndexes[iPop]] = omega;
// }
// for (int iPop = 0; iPop < DESCRIPTOR::q; ++iPop)
// {
// for (int jPop = 0; jPop < DESCRIPTOR::q; ++jPop)
// {
// invM_S_SGS[iPop][jPop] = T();
// for (int kPop = 0; kPop < DESCRIPTOR::q; ++kPop)
// {
// if (kPop == jPop)
// {
// invM_S_SGS[iPop][jPop] += DESCRIPTOR::invM[iPop][kPop] *
// rtSGS[kPop];
// cout << "wert"<<iPop <<jPop << "= "<< invM_S_SGS[iPop][jPop]<< endl;
// }
// }
// }
// }
//
}
template<typename T, typename DESCRIPTOR>
void StochasticSGSdynamics<T,DESCRIPTOR>::collide(
Cell<T,DESCRIPTOR>& cell,
LatticeStatistics<T>& statistics )
{
T rho, u[DESCRIPTOR::d], pi[util::TensorVal<DESCRIPTOR >::n];
T drift = computeTimeScale(preFactor, rho, pi, smagoConst, X_lang_n);
T result = getRandBMTrans(cell, turbulenceInt, charU);
// cout << "vor neu setzen: "<<X_lang_n<< endl;
X_lang_n = getRandomWalk(cell, drift, result);
// cout << "nach neu setzen: "<<X_lang_n<< endl;
//cout << X_lang_n<< endl;
// cout << drift<< endl;
// cout << result<< endl;
this->_momenta.computeAllMomenta(cell, rho, u, pi);
T newOmega = computeOmega(this->getOmega(), preFactor, rho, pi, X_lang_n);
T invM_S_SGS[DESCRIPTOR::q][DESCRIPTOR::q];
T rtSGS[DESCRIPTOR::q]; // relaxation times vector for SGS approach.
for (int iPop = 0; iPop < DESCRIPTOR::q; ++iPop) {
rtSGS[iPop] = DESCRIPTOR::S[iPop];
}
for (int iPop = 0; iPop < DESCRIPTOR::shearIndexes; ++iPop) {
rtSGS[DESCRIPTOR::shearViscIndexes[iPop]] = newOmega;
}
for (int iPop = 0; iPop < DESCRIPTOR::q; ++iPop) {
for (int jPop = 0; jPop < DESCRIPTOR::q; ++jPop) {
invM_S_SGS[iPop][jPop] = T();
for (int kPop = 0; kPop < DESCRIPTOR::q; ++kPop) {
if (kPop == jPop) {
invM_S_SGS[iPop][jPop] += DESCRIPTOR::invM[iPop][kPop] *
rtSGS[kPop];
//cout << "wert"<<iPop <<jPop << "= "<< invM_S_SGS[iPop][jPop]<< endl;
}
}
}
}
T uSqr = mrtHelpers<T,DESCRIPTOR>::mrtSGSCollision(cell, rho, u, newOmega, invM_S_SGS);
statistics.incrementStats(rho, uSqr);
}
template<typename T, typename DESCRIPTOR>
void StochasticSGSdynamics<T,DESCRIPTOR>::setOmega(T omega)
{
this->setOmega(omega);
preFactor = computePreFactor(omega, smagoConst);
}
template<typename T, typename DESCRIPTOR>
T StochasticSGSdynamics<T,DESCRIPTOR>::getSmagorinskyOmega(Cell<T,DESCRIPTOR>& cell, T X_lang_n )
{
T rho, uTemp[DESCRIPTOR::d], pi[util::TensorVal<DESCRIPTOR >::n];
this->_momenta.computeAllMomenta(cell, rho, uTemp, pi);
T newOmega = computeOmega(this->getOmega(), preFactor, rho, pi, X_lang_n);
return newOmega;
}
template<typename T, typename DESCRIPTOR>
T StochasticSGSdynamics<T,DESCRIPTOR>::getRandBMTrans(
Cell<T,DESCRIPTOR>& cell,
T turbulenceInt, T CharU )
{
/// Random number generator based on Box Müller transform to produuce random normal
/// distributed numbers with zero mean and
T mean = 0.;
T TKE_ini = 1.5*turbulenceInt*turbulenceInt*charU*charU;
T velStDev = sqrt(2./3.*TKE_ini);
static double n2 = 0.0;
static int n2_cached = 0;
if (!n2_cached) {
double x, y, r;
do {
x = 2.0*rand()/RAND_MAX - 1;
y = 2.0*rand()/RAND_MAX - 1;
r = x*x + y*y;
} while ( util::nearZero(r) || r > 1.0);
{
double d = sqrt(-2.0*log(r)/r);
double n1 = x*d;
n2 = y*d;
double result = n1*velStDev + mean;
n2_cached = 1;
return result;
}
} else {
n2_cached = 0;
return n2*velStDev + mean;
}
}
/// Create Random walk
template<typename T, typename DESCRIPTOR>
T StochasticSGSdynamics<T,DESCRIPTOR>::getRandomWalk(
Cell<T,DESCRIPTOR>& cell,
T drift, T result)
{
/// initialisation of model standard variation, see Pope pp 484
T sigma = 2.3;
X_lang_n *=drift;
X_lang_n += sigma*sqrt(drift*2)*result;
return X_lang_n;
}
/// set random walk
// template<typename T, typename DESCRIPTOR>
// void StochasticSGSdynamics<T,DESCRIPTOR>::setRandomWalk(
// Cell<T,DESCRIPTOR>& cell,
// T CharU, T drift, T result )
// {
// /// initialisation of model standard variation, see Pope pp 484
// T X_lang_n = getRandomWalk(cell, CharU, drift, result);
// }
// /// get time sclae
template<typename T, typename DESCRIPTOR>
T StochasticSGSdynamics<T,DESCRIPTOR>::computeTimeScale(
T preFactor, T rho, T pi[util::TensorVal<DESCRIPTOR >::n], T smagoConst, T X_lang_n )
{
T Const = 0.2;
T PiNeqNormSqr = pi[0]*pi[0] + 2.0*pi[1]*pi[1] + pi[2]*pi[2];
if (util::TensorVal<DESCRIPTOR >::n == 6) {
PiNeqNormSqr += pi[2]*pi[2] + pi[3]*pi[3] + 2*pi[4]*pi[4] +pi[5]*pi[5];
}
T PiNeqNorm = sqrt(PiNeqNormSqr);
/// SGS dissipation is calcualted directly withou any filter size due to effeiciency in tau
// for post processing this has to be evaluated seperately with S_ij³
T diss_corr = smagoConst*smagoConst*PiNeqNorm*PiNeqNorm*PiNeqNorm*(1+ X_lang_n);
T tau= Const*pow(( 1. / diss_corr ), 1./3.);
T drift = 1./tau;
/// deterministic drift time scale T_L see Pope pp. 484
return drift;
}
// // // /// set timescale
// template<typename T, typename DESCRIPTOR>
// void StochasticSGSdynamics<T,DESCRIPTOR>::setTimeScale(
// T preFactor, T rho, T pi[util::TensorVal<DESCRIPTOR >::n], T smagoConst, T X_lang_n)
// {
// T drift = computeTimeScale(preFactor, rho, pi, smagoConst, X_lang_n);
// }
template<typename T, typename DESCRIPTOR>
T StochasticSGSdynamics<T,DESCRIPTOR>::computePreFactor(T omega, T smagoConst)
{
return (T)smagoConst*smagoConst*descriptors::invCs2<T,DESCRIPTOR>()*descriptors::invCs2<T,DESCRIPTOR>()*2*sqrt(2);
}
template<typename T, typename DESCRIPTOR>
T StochasticSGSdynamics<T,DESCRIPTOR>::computeOmega(T omega0, T preFactor, T rho, T pi[util::TensorVal<DESCRIPTOR >::n], T X_lang_n)
{
T PiNeqNormSqr = pi[0]*pi[0] + 2.0*pi[1
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