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https://develop.openfoam.com/Development/openfoam.git
synced 2025-11-28 03:28:01 +00:00
ENH: added a general framework for normalization and setting targets
for all objective functions. - The normalization is useful for practically all update methods dealing with constraints (e.g. SQP, MMA). The normalization factor can be either given explicitly or, if not given, will be the value of the objective function in the first optimisation cycle. - The target value is useful when using the objective as a constraint in constrained optimisation problems (e.g. drag - dragTarget). It should only be used with update methods that understand the value of the constraint (e.g. SQP, MMA) but not when the objective in hand is the only objective of the optimisation problem. In such a case, a squared objective should be used (e.g. sqr(drag - dragTarget))
This commit is contained in:
committed by
Andrew Heather
parent
4d67819a2c
commit
6ee7bc66c5
@ -151,14 +151,18 @@ bool objectiveManager::readDict(const dictionary& dict)
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return true;
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}
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void objectiveManager::updateNormalizationFactor()
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{
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// Update normalization factors for all objectives
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for (objective& obj : objectives_)
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{
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if (obj.normalize())
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{
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obj.updateNormalizationFactor();
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}
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}
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}
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void objectiveManager::update()
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@ -128,6 +128,67 @@ autoPtr<objectiveIncompressible> objectiveIncompressible::New
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// * * * * * * * * * * * * * * * Member Functions * * * * * * * * * * * * * //
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void objectiveIncompressible::doNormalization()
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{
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if (normalize_ && normFactor_.valid())
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{
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const scalar oneOverNorm(1./normFactor_());
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if (hasdJdv())
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{
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dJdvPtr_().primitiveFieldRef() *= oneOverNorm;
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}
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if (hasdJdp())
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{
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dJdpPtr_().primitiveFieldRef() *= oneOverNorm;
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}
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if (hasdJdT())
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{
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dJdTPtr_().primitiveFieldRef() *= oneOverNorm;
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}
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if (hasdJdTMVar1())
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{
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dJdTMvar1Ptr_().primitiveFieldRef() *= oneOverNorm;
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}
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if (hasdJdTMVar2())
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{
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dJdTMvar2Ptr_().primitiveFieldRef() *= oneOverNorm;
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}
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if (hasBoundarydJdv())
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{
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bdJdvPtr_() *= oneOverNorm;
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}
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if (hasBoundarydJdvn())
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{
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bdJdvnPtr_() *= oneOverNorm;
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}
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if (hasBoundarydJdvt())
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{
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bdJdvtPtr_() *= oneOverNorm;
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}
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if (hasBoundarydJdp())
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{
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bdJdpPtr_() *= oneOverNorm;
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}
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if (hasBoundarydJdT())
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{
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bdJdTPtr_() *= oneOverNorm;
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}
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if (hasBoundarydJdTMVar1())
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{
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bdJdTMvar1Ptr_() *= oneOverNorm;
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}
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if (hasBoundarydJdTMVar2())
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{
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bdJdTMvar2Ptr_() *= oneOverNorm;
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}
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// Normalize geometric fields
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objective::doNormalization();
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}
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}
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const volVectorField& objectiveIncompressible::dJdv()
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{
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if (dJdvPtr_.empty())
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@ -418,6 +479,9 @@ void objectiveIncompressible::update()
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update_dxdbDirectMultiplier();
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update_boundaryEdgeContribution();
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update_dJdStressMultiplier();
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// Divide everything with normalization factor
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doNormalization();
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}
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@ -165,6 +165,9 @@ public:
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//- Return the objective function value
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virtual scalar J() = 0;
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//- Normalize all fields allocated by the objective
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virtual void doNormalization();
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//- Contribution to field adjoint momentum eqs
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const volVectorField& dJdv();
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@ -247,6 +247,7 @@ void objectivePtLosses::write() const
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setObjectiveFilePtr();
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objFunctionFilePtr_() << setw(4) << "#" << " ";
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objFunctionFilePtr_() << setw(width) << "ptLosses" << " ";
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objFunctionFilePtr_() << setw(width) << "JCycle" << " ";
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forAll(patches_, oI)
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{
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label patchI = patches_[oI];
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@ -258,6 +259,7 @@ void objectivePtLosses::write() const
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objFunctionFilePtr_() << setw(4) << mesh_.time().value() << " ";
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objFunctionFilePtr_() << setw(width) << J_ << " ";
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objFunctionFilePtr_() << setw(width) << JCycle() << " ";
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forAll(patchPt_, pI)
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{
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objFunctionFilePtr_() << setw(width) << patchPt_[pI] << " ";
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@ -59,8 +59,10 @@ class objectivePtLosses
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{
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// Private data
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//- Patches on which to compute losses
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labelList patches_;
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//- Total pressure per patch on patches_
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scalarField patchPt_;
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@ -129,10 +129,13 @@ objective::objective
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objectiveName_(dict.dictName()),
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computeMeanFields_(false), // is reset in derived classes
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nullified_(false),
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normalize_(dict.getOrDefault<bool>("normalize", false)),
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J_(Zero),
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JMean_(this->getOrDefault<scalar>("JMean", Zero)),
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weight_(Zero),
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normFactor_(nullptr),
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target_(dict.getOrDefault<scalar>("target", Zero)),
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integrationStartTimePtr_(nullptr),
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integrationEndTimePtr_(nullptr),
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@ -174,6 +177,20 @@ objective::objective
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new scalar(dict.get<scalar>("integrationEndTime"))
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);
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}
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// Set normalization factor, if present
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if (normalize_)
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{
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scalar normFactor(Zero);
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if (dict.readIfPresent("normFactor", normFactor))
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{
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normFactor_.reset(new scalar(normFactor));
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}
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else if (this->readIfPresent("normFactor", normFactor))
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{
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normFactor_.reset(new scalar(normFactor));
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}
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}
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}
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@ -234,13 +251,26 @@ scalar objective::JCycle() const
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{
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J = JMean_;
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}
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// Subtract target, in case the objective is used as a constraint
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J -= target_;
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// Normalize here, in order to get the correct value for line search
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if (normalize_ && normFactor_.valid())
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{
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J /= normFactor_();
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}
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return J;
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}
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void objective::updateNormalizationFactor()
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{
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// Does nothing in base
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if (normalize_ && normFactor_.empty())
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{
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normFactor_.reset(new scalar(JCycle()));
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}
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}
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@ -289,6 +319,62 @@ scalar objective::weight() const
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}
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bool objective::normalize() const
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{
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return normalize_;
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}
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void objective::doNormalization()
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{
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if (normalize_ && normFactor_.valid())
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{
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const scalar oneOverNorm(1./normFactor_());
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if (hasdJdb())
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{
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dJdbPtr_().primitiveFieldRef() *= oneOverNorm;
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}
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if (hasBoundarydJdb())
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{
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bdJdbPtr_() *= oneOverNorm;
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}
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if (hasdSdbMult())
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{
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bdSdbMultPtr_() *= oneOverNorm;
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}
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if (hasdndbMult())
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{
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bdndbMultPtr_() *= oneOverNorm;
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}
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if (hasdxdbMult())
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{
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bdxdbMultPtr_() *= oneOverNorm;
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}
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if (hasdxdbDirectMult())
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{
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bdxdbDirectMultPtr_() *= oneOverNorm;
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}
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if (hasBoundaryEdgeContribution())
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{
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bEdgeContribution_() *= oneOverNorm;
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}
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if (hasDivDxDbMult())
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{
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divDxDbMultPtr_() *= oneOverNorm;
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}
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if (hasGradDxDbMult())
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{
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gradDxDbMultPtr_() *= oneOverNorm;
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}
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if (hasBoundarydJdStress())
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{
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bdJdStressPtr_() *= oneOverNorm;
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}
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}
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}
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bool objective::isWithinIntegrationTime() const
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{
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if (hasIntegrationStartTime() && hasIntegrationEndTime())
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@ -667,6 +753,10 @@ void objective::writeMeanValue() const
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bool objective::writeData(Ostream& os) const
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{
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os.writeEntry("JMean", JMean_);
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if (normFactor_.valid())
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{
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os.writeEntry("normFactor", normFactor_());
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}
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return os.good();
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}
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@ -72,6 +72,7 @@ protected:
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const word objectiveName_;
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bool computeMeanFields_;
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bool nullified_;
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bool normalize_;
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//- Objective function value and weight
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scalar J_;
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@ -82,12 +83,21 @@ protected:
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//- Objective weight
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scalar weight_;
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// Objective integration start and end times (for unsteady flows)
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//- Normalization factor
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autoPtr<scalar> normFactor_;
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//- Target value, in case the objective is used as a constraint
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// Should be used in caution and with updateMethods than get affected
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// by the target value, without requiring a sqr (e.g. SQP, MMA)
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scalar target_;
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//- Objective integration start and end times (for unsteady flows)
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autoPtr<scalar> integrationStartTimePtr_;
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autoPtr<scalar> integrationEndTimePtr_;
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// Contribution to field sensitivity derivatives
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// Topology optimisation
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//- Contribution to field sensitivity derivatives
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// Topology optimisation or other variants with
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// as many design variables as the mesh cells
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//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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autoPtr<volScalarField> dJdbPtr_;
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@ -248,6 +258,12 @@ public:
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//- Return the objective function weight
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scalar weight() const;
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//- Is the objective normalized
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bool normalize() const;
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//- Normalize all fields allocated by the objective
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virtual void doNormalization();
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//- Check whether this is an objective integration time
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bool isWithinIntegrationTime() const;
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