noiseModel.C

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/*---------------------------------------------------------------------------*\
  =========                 |
  \\      /  F ield         | OpenFOAM: The Open Source CFD Toolbox
   \\    /   O peration     |
    \\  /    A nd           | www.openfoam.com
     \\/     M anipulation  |
-------------------------------------------------------------------------------
    Copyright (C) 2015-2020 OpenCFD Ltd.
-------------------------------------------------------------------------------
License
    This file is part of OpenFOAM.
 
    OpenFOAM 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 3 of the License, or
    (at your option) any later version.
 
    OpenFOAM 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 OpenFOAM.  If not, see <http://www.gnu.org/licenses/>.
 
\*---------------------------------------------------------------------------*/
 
#include "noiseModel.H"
#include "functionObject.H"
#include "argList.H"
#include "fft.H"
#include "OFstream.H"
 
// * * * * * * * * * * * * * * Static Data Members * * * * * * * * * * * * * //
 
namespace Foam
{
    defineTypeNameAndDebug(noiseModel, 0);
    defineRunTimeSelectionTable(noiseModel, dictionary);
}
 
 
const Foam::Enum<Foam::noiseModel::weightingType>
Foam::noiseModel::weightingTypeNames_
({
    {weightingType::none, "dB"},
    {weightingType::dBA, "dBA"},
    {weightingType::dBB, "dBB"},
    {weightingType::dBC, "dBC"},
    {weightingType::dBD, "dBD"},
});
 
 
void Foam::noiseModel::setOctaveBands
(
    const scalarField& f,
    const scalar fLower,
    const scalar fUpper,
    const scalar octave,
    labelList& fBandIDs,
    scalarField& fCentre
)
{
    // Set the indices of to the lower frequency bands for the input frequency
    // range. Ensure that the centre frequency passes though 1000 Hz
 
    // Low frequency bound given by:
    //     fLow = f0*(2^(0.5*bandI/octave))
 
    // Initial (lowest centre frequency)
    scalar fTest = 15.625;
 
    const scalar fRatio = pow(2, 1.0/octave);
    const scalar fRatioL2C = pow(2, 0.5/octave);
 
    // IDs of band IDs
    labelHashSet bandIDs(f.size());
 
    // Centre frequencies
    DynamicList<scalar> fc;
 
    // Convert to lower band limit
    fTest /= fRatioL2C;
 
    forAll(f, i)
    {
        if (f[i] >= fTest)
        {
            // Advance band if appropriate
            while (f[i] > fTest)
            {
                fTest *= fRatio;
            }
            fTest /= fRatio;
 
            if (bandIDs.insert(i))
            {
                // Also store (next) centre frequency
                fc.append(fTest*fRatioL2C);
            }
            fTest *= fRatio;
 
            if (fTest > fUpper)
            {
                break;
            }
        }
    }
 
    fBandIDs = bandIDs.sortedToc();
 
    if (fc.size())
    {
        // Remove the last centre frequency (beyond upper frequency limit)
        fc.remove();
 
        fCentre.transfer(fc);
    }
}
 
 
// * * * * * * * * * * * * * Protected Member Functions  * * * * * * * * * * //
 
void Foam::noiseModel::readWriteOption
(
    const dictionary& dict,
    const word& lookup,
    bool& option
) const
{
    dict.readIfPresent(lookup, option);
 
    // Only writing on the master process
    option = option && Pstream::master();
 
    if (option)
    {
        Info<< "        " << lookup << ": " << "yes" << endl;
    }
    else
    {
        Info<< "        " << lookup << ": " << "no" << endl;
    }
}
 
 
Foam::scalar Foam::noiseModel::checkUniformTimeStep
(
    const scalarList& times
) const
{
    scalar deltaT = -1.0;
 
    if (times.size() > 1)
    {
        // Uniform time step
        deltaT = (times.last() - times.first())/scalar(times.size() - 1);
 
        for (label i = 1; i < times.size(); ++i)
        {
            scalar dT = times[i] - times[i-1];
 
            if (mag(dT/deltaT - 1) > 1e-8)
            {
                FatalErrorInFunction
                    << "Unable to process data with a variable time step"
                    << exit(FatalError);
            }
        }
    }
    else
    {
        FatalErrorInFunction
            << "Unable to create FFT with a single value"
            << exit(FatalError);
    }
 
    return deltaT;
}
 
 
bool Foam::noiseModel::validateBounds(const scalarList& p) const
{
    forAll(p, i)
    {
        if ((p[i] < minPressure_) || (p[i] > maxPressure_))
        {
            WarningInFunction
                << "Pressure data at position " << i
                << " is outside of permitted bounds:" << nl
                << "    pressure: " << p[i] << nl
                << "    minimum pressure: " << minPressure_ << nl
                << "    maximum pressure: " << maxPressure_ << nl
                << endl;
 
            return false;
        }
    }
 
    return true;
}
 
 
Foam::label Foam::noiseModel::findStartTimeIndex
(
    const instantList& allTimes,
    const scalar startTime
) const
{
    forAll(allTimes, timeI)
    {
        const instant& i = allTimes[timeI];
 
        if (i.value() >= startTime)
        {
            return timeI;
        }
    }
 
    return 0;
}
 
 
Foam::fileName Foam::noiseModel::baseFileDir(const label dataseti) const
{
    return
    (
        argList::envGlobalPath()
      / functionObject::outputPrefix
      / "noise"
      / outputPrefix_
      / type()
      / ("input" + Foam::name(dataseti))
    );
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::uniformFrequencies
(
    const scalar deltaT
) const
{
    const auto& window = windowModelPtr_();
    const label N = window.nSamples();
 
    auto tf = tmp<scalarField>::New(N/2 + 1, Zero);
    auto& f = tf.ref();
 
    const scalar deltaf = 1.0/(N*deltaT);
    forAll(f, i)
    {
        f[i] = i*deltaf;
    }
 
    return tf;
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::octaves
(
    const scalarField& data,
    const scalarField& f,
    const labelUList& freqBandIDs
) const
{
    auto toctData = tmp<scalarField>::New(freqBandIDs.size() - 1, Zero);
 
    if (freqBandIDs.size() < 2)
    {
        WarningInFunction
            << "Octave frequency bands are not defined "
            << "- skipping octaves calculation"
            << endl;
 
        return toctData;
    }
 
    auto& octData = toctData.ref();
 
    for (label bandI = 0; bandI < freqBandIDs.size() - 1; ++bandI)
    {
        label fb0 = freqBandIDs[bandI];
        label fb1 = freqBandIDs[bandI+1];
 
        if (fb0 == fb1) continue;
 
        for (label freqI = fb0; freqI < fb1; ++freqI)
        {
            label f0 = f[freqI];
            label f1 = f[freqI + 1];
            scalar dataAve = 0.5*(data[freqI] + data[freqI + 1]);
            octData[bandI] += dataAve*(f1 - f0);
        }
    }
 
    return toctData;
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::Pf(const scalarField& p) const
{
    if (planInfo_.active)
    {
        if (p.size() != planInfo_.windowSize)
        {
            FatalErrorInFunction
                << "Expected pressure data to have " << planInfo_.windowSize
                << " values, but received " << p.size() << " values"
                << abort(FatalError);
        }
 
        List<double>& in = planInfo_.in;
        const List<double>& out = planInfo_.out;
        forAll(in, i)
        {
            in[i] = p[i];
        }
 
        ::fftw_execute(planInfo_.plan);
 
        const label n = planInfo_.windowSize;
        const label nBy2 = n/2;
        auto tresult = tmp<scalarField>::New(nBy2 + 1);
        auto& result = tresult.ref();
 
        // 0 th value = DC component
        // nBy2 th value = real only if n is even
        result[0] = out[0];
        for (label i = 1; i <= nBy2; ++i)
        {
            const auto re = out[i];
            const auto im = out[n - i];
            result[i] = sqrt(re*re + im*im);
        }
 
        return tresult;
    }
 
    return mag(fft::realTransform1D(p));
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::meanPf(const scalarField& p) const
{
    const auto& window = windowModelPtr_();
    const label N = window.nSamples();
    const label nWindow = window.nWindow();
 
    auto tmeanPf = tmp<scalarField>::New(N/2 + 1, Zero);
    auto& meanPf = tmeanPf.ref();
 
    for (label windowI = 0; windowI < nWindow; ++windowI)
    {
        meanPf += Pf(window.apply<scalar>(p, windowI));
    }
 
    meanPf /= scalar(nWindow);
 
    return tmeanPf;
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::RMSmeanPf
(
    const scalarField& p
) const
{
    const auto& window = windowModelPtr_();
    const label N = window.nSamples();
    const label nWindow = window.nWindow();
 
    scalarField RMSMeanPf(N/2 + 1, Zero);
    for (label windowI = 0; windowI < nWindow; ++windowI)
    {
        RMSMeanPf += sqr(Pf(window.apply<scalar>(p, windowI)));
    }
 
    return sqrt(RMSMeanPf/scalar(nWindow))/scalar(N);
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::PSDf
(
    const scalarField& p,
    const scalar deltaT
) const
{
    const auto& window = windowModelPtr_();
    const label N = window.nSamples();
    const label nWindow = window.nWindow();
 
    auto tpsd = tmp<scalarField>::New(N/2 + 1, Zero);
    auto& psd = tpsd.ref();
 
    for (label windowI = 0; windowI < nWindow; ++windowI)
    {
        psd += sqr(Pf(window.apply<scalar>(p, windowI)));
    }
 
    scalar fs =  1.0/deltaT;
    psd /= scalar(nWindow)*fs*N;
 
    // Scaling due to use of 1-sided FFT
    // Note: do not scale DC component
    psd *= 2;
    psd.first() /= 2;
    psd.last() /= 2;
 
    if (debug)
    {
        Pout<< "Average PSD: " << average(psd) << endl;
    }
 
    return tpsd;
}
 
 
Foam::scalar Foam::noiseModel::RAf(const scalar f) const
{
    const scalar c1 = sqr(12194.0);
    const scalar c2 = sqr(20.6);
    const scalar c3 = sqr(107.7);
    const scalar c4 = sqr(739.9);
 
    const scalar f2 = f*f;
 
    return
        c1*sqr(f2)
       /(
            (f2 + c2)*sqrt((f2 + c3)*(f2 + c4))*(f2 + c1)
        );
}
 
 
Foam::scalar Foam::noiseModel::gainA(const scalar f) const
{
    return 20*log10(RAf(f)) - 20*log10(RAf(1000));
}
 
 
Foam::scalar Foam::noiseModel::RBf(const scalar f) const
{
    const scalar c1 = sqr(12194.0);
    const scalar c2 = sqr(20.6);
    const scalar c3 = sqr(158.5);
 
    const scalar f2 = f*f;
 
    return
        c1*f2*f
       /(
            (f2 + c2)*sqrt(f2 + c3)*(f2 + c1)
        );
}
 
 
Foam::scalar Foam::noiseModel::gainB(const scalar f) const
{
    return 20*log10(RBf(f)) - 20*log10(RBf(1000));
}
 
 
Foam::scalar Foam::noiseModel::RCf(const scalar f) const
{
    const scalar c1 = sqr(12194.0);
    const scalar c2 = sqr(20.6);
 
    const scalar f2 = f*f;
 
    return c1*f2/((f2 + c2)*(f2 + c1));
}
 
 
Foam::scalar Foam::noiseModel::gainC(const scalar f) const
{
    return 20*log10(RCf(f)) - 20*log10(RCf(1000));
}
 
 
Foam::scalar Foam::noiseModel::RDf(const scalar f) const
{
    const scalar f2 = f*f;
 
    const scalar hf =
        (sqr(1037918.48 - f2) + 1080768.16*f2)
       /(sqr(9837328 - f2) + 11723776*f2);
 
    return
        f/6.8966888496476e-5*Foam::sqrt(hf/((f2 + 79919.29)*(f2 + 1345600)));
}
 
 
Foam::scalar Foam::noiseModel::gainD(const scalar f) const
{
    return 20*log10(RDf(f));
}
 
 
// * * * * * * * * * * * * * * * * Constructors  * * * * * * * * * * * * * * //
 
Foam::noiseModel::noiseModel(const dictionary& dict, const bool readFields)
:
    dict_(dict),
    rhoRef_(1),
    nSamples_(65536),
    fLower_(25),
    fUpper_(10000),
    startTime_(0),
    windowModelPtr_(),
    graphFormat_("raw"),
    SPLweighting_(weightingType::none),
    minPressure_(-0.5*VGREAT),
    maxPressure_(0.5*VGREAT),
    outputPrefix_(),
    writePrmsf_(true),
    writeSPL_(true),
    writePSD_(true),
    writePSDf_(true),
    writeOctaves_(true),
    planInfo_()
{
    planInfo_.active = false;
 
    if (readFields)
    {
        read(dict);
    }
 
    if (debug)
    {
        writeWeightings();
    }
}
 
 
// * * * * * * * * * * * * * * * Member Functions  * * * * * * * * * * * * * //
 
bool Foam::noiseModel::read(const dictionary& dict)
{
    dict.readIfPresent("rhoRef", rhoRef_);
    dict.readIfPresent("N", nSamples_);
    dict.readIfPresent("fl", fLower_);
    dict.readIfPresent("fu", fUpper_);
    dict.readIfPresent("startTime", startTime_);
    dict.readIfPresent("graphFormat", graphFormat_);
    dict.readIfPresent("minPressure", minPressure_);
    dict.readIfPresent("maxPressure", maxPressure_);
    dict.readIfPresent("outputPrefix", outputPrefix_);
 
    if (fLower_ < 0)
    {
        FatalIOErrorInFunction(dict)
            << "fl: lower frequency bound must be greater than zero"
            << exit(FatalIOError);
    }
 
    if (fUpper_ < 0)
    {
        FatalIOErrorInFunction(dict)
            << "fu: upper frequency bound must be greater than zero"
            << exit(FatalIOError);
    }
 
    if (fUpper_ < fLower_)
    {
        FatalIOErrorInFunction(dict)
            << "fu: upper frequency bound must be greater than lower "
            << "frequency bound (fl)"
            << exit(FatalIOError);
 
    }
 
    Info<< "    Frequency bounds:" << nl
        << "        lower: " << fLower_ << nl
        << "        upper: " << fUpper_ << endl;
 
    weightingTypeNames_.readIfPresent("SPLweighting", dict, SPLweighting_);
 
    Info<< "    Weighting: " << weightingTypeNames_[SPLweighting_] << endl;
 
    Info<< "    Write options:" << endl;
    dictionary optDict(dict.subOrEmptyDict("writeOptions"));
    readWriteOption(optDict, "writePrmsf", writePrmsf_);
    readWriteOption(optDict, "writeSPL", writeSPL_);
    readWriteOption(optDict, "writePSD", writePSD_);
    readWriteOption(optDict, "writePSDf", writePSDf_);
    readWriteOption(optDict, "writeOctaves", writeOctaves_);
 
 
    windowModelPtr_ = windowModel::New(dict, nSamples_);
 
    cleanFFTW();
 
    const label windowSize = windowModelPtr_->nSamples();
 
    if (windowSize > 1)
    {
        planInfo_.active = true;
        planInfo_.windowSize = windowSize;
        planInfo_.in.setSize(windowSize);
        planInfo_.out.setSize(windowSize);
 
        // Using real to half-complex fftw 'kind'
        planInfo_.plan =
            fftw_plan_r2r_1d
            (
                windowSize,
                planInfo_.in.data(),
                planInfo_.out.data(),
                FFTW_R2HC,
                windowSize <= 8192 ? FFTW_MEASURE : FFTW_ESTIMATE
            );
    }
 
    Info<< nl << endl;
 
    return true;
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::PSD
(
    const scalarField& PSDf
) const
{
    return 10*log10(PSDf/sqr(2e-5));
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::SPL
(
    const scalarField& Prms2,
    const scalar f
) const
{
    tmp<scalarField> tspl(10*log10(Prms2/sqr(2e-5)));
    scalarField& spl = tspl.ref();
 
    switch (SPLweighting_)
    {
        case weightingType::none:
        {
            break;
        }
        case weightingType::dBA:
        {
            spl += gainA(f);
            break;
        }
        case weightingType::dBB:
        {
            spl += gainB(f);
            break;
        }
        case weightingType::dBC:
        {
            spl += gainC(f);
            break;
        }
        case weightingType::dBD:
        {
            spl += gainD(f);
            break;
        }
        default:
        {
            FatalErrorInFunction
                << "Unknown weighting " << weightingTypeNames_[SPLweighting_]
                << abort(FatalError);
        }
    }
 
    return tspl;
}
 
 
Foam::tmp<Foam::scalarField> Foam::noiseModel::SPL
(
    const scalarField& Prms2,
    const scalarField& f
) const
{
    tmp<scalarField> tspl(10*log10(Prms2/sqr(2e-5)));
    scalarField& spl = tspl.ref();
 
    switch (SPLweighting_)
    {
        case weightingType::none:
        {
            break;
        }
        case weightingType::dBA:
        {
            forAll(spl, i)
            {
                spl[i] += gainA(f[i]);
            }
            break;
        }
        case weightingType::dBB:
        {
            forAll(spl, i)
            {
                spl[i] += gainB(f[i]);
            }
            break;
        }
        case weightingType::dBC:
        {
            forAll(spl, i)
            {
                spl[i] += gainC(f[i]);
            }
            break;
        }
        case weightingType::dBD:
        {
            forAll(spl, i)
            {
                spl[i] += gainD(f[i]);
            }
            break;
        }
        default:
        {
            FatalErrorInFunction
                << "Unknown weighting " << weightingTypeNames_[SPLweighting_]
                << abort(FatalError);
        }
    }
 
    return tspl;
}
 
 
void Foam::noiseModel::cleanFFTW()
{
    if (planInfo_.active)
    {
        planInfo_.active = false;
        fftw_destroy_plan(planInfo_.plan);
        fftw_cleanup();
    }
}
 
 
void Foam::noiseModel::writeWeightings() const
{
    scalar f0 = 10;
    scalar f1 = 20000;
 
    OFstream osA("noiseModel-weight-A");
    OFstream osB("noiseModel-weight-B");
    OFstream osC("noiseModel-weight-C");
    OFstream osD("noiseModel-weight-D");
 
    for (label f = f0; f <= f1; ++f)
    {
        osA << f << " " << gainA(f) << nl;
        osB << f << " " << gainB(f) << nl;
        osC << f << " " << gainC(f) << nl;
        osD << f << " " << gainD(f) << nl;
    }
}
 
 
// ************************************************************************* //