/// <summary>Realizes a sample function for respective stochastic domain mapper and parameters.</summary>
/// <param name="iteration">The iteration.</param>
/// <param name="domainMapper">The domain mapper.</param>
/// <param name="parameters">The parameters.</param>
/// <returns></returns>
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
ResetGeneration = (PreviousIteration != iteration);
if (ResetGeneration)
{
ResetSampleGeneration();
}
double[] stochasticDomainPoint = domainMapper.Map(parameters);
var dw = wu / (double)frequencyIntervals;
int i = 0;
double randomCoefficient = 0;
while (i < frequencyIntervals)
{
randomCoefficient += Math.Sqrt(2) * Math.Sqrt(2 * SpectralDensity(dw / 2 + i * dw) * dw) *
(Math.Cos((dw / 2 + i * dw) * stochasticDomainPoint[0] +
phi[i]));
i++;
}
if (randomCoefficient >= .9)
{
randomCoefficient = .9;
}
else if (randomCoefficient <= -.9)
{
randomCoefficient = -.9;
}
PreviousIteration = iteration;
return(MeanValue / (1 + randomCoefficient));
}
/// <summary>Initializes a new instance of the <see cref="StructuralSystemEvaluator"/> class.</summary>
/// <param name="youngModulus">The young modulus.</param>
/// <param name="domainMapper">The domain mapper.</param>
public StructuralSystemEvaluator(double youngModulus, IStochasticDomainMapper domainMapper)
{
YoungModulus = youngModulus;
DomainMapper = domainMapper;
ModelBuilder = new GiannisModelBuilder();
StochasticRealization = new KarhunenLoeveCoefficientsProvider(partition, youngModulus, midpointMethod,
isGaussian, karLoeveTerms, domainBounds, sigmaSquare, correlationLength);
}
//public StructuralStochasticEvaluator(double youngModulus, IStochasticDomainMapper domainMapper)
//{
// YoungModulus = youngModulus;
// DomainMapper = domainMapper;
// ModelBuilder = new ModelBuilder();
// StochasticRealization = new RandomVariable(youngModulus, domainMapper);
//}
/// <summary>Initializes a new instance of the <see cref="StructuralStochasticEvaluator"/> class.</summary>
/// <param name="youngModulus">The young modulus.</param>
/// <param name="domainMapper">The domain mapper.</param>
public StructuralStochasticEvaluator(double youngModulus, IStochasticDomainMapper domainMapper)
{
YoungModulus = youngModulus;
DomainMapper = domainMapper;
ModelBuilder = new GiannisModelBuilder();
StochasticRealization = new KarhunenLoeveCoefficientsProvider(partition, youngModulus, midpointMethod,
isGaussian, karLoeveTerms, domainBounds, sigmaSquare, correlationLength);
//StochasticRealization = new SpectralRepresentation1DRandomFieldGenerator(10, 0.1, youngModulus, .05, 0.1, 256);
}
/// <summary>Realizes the specified iteration based on a stochastic domain mapper and the respective domain parameters.</summary>
/// <param name="iteration">The iteration.</param>
/// <param name="domainMapper">The domain mapper.</param>
/// <param name="parameters">The parameters.</param>
/// <returns></returns>
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
ResetGeneration = (PreviousIteration != iteration);
if (ResetGeneration)
{
ResetSampleGeneration();
}
var stochasticDomainPoint = domainMapper.Map(parameters);
double[] eigenModesAtPoint = CalculateEigenmodesAtPoint(Xcoordinates, Eigenvectors, stochasticDomainPoint[0]);
var value = KarhunenLoeveFredholm1DSampleGenerator(stochasticDomainPoint, Lambda, eigenModesAtPoint, MeanValue, MidpointMethod, IsGaussian);
PreviousIteration = iteration;
return(value);
}
public Model GetModel(RandomVariable randomVariable, IStochasticDomainMapper domainMapper, int iteration)
{
var m = new Model();
m.NodesDictionary.Add(0, new Node(id: 0, x: 0, y: 0, z: 0));
m.NodesDictionary.Add(1, new Node(id: 1, x: 1, y: 0, z: 0));
m.ElementsDictionary.Add(1, new Element()
{
ID = 1,
ElementType = new EulerBeam3D(randomVariable.Realize(iteration, domainMapper, null), 0.3)
});
m.Loads.Add(new Load()
{
Amount = 10, DOF = StructuralDof.TranslationX, Node = m.NodesDictionary[1]
});
return(m);
}
/// <summary>Realizes the specified iteration for given stochasti domain mapper and domain prameters.</summary>
/// <param name="iteration">The iteration.</param>
/// <param name="domainMapper">The domain mapper.</param>
/// <param name="parameters">The parameters.</param>
/// <returns></returns>
/// <exception cref="System.NotImplementedException"></exception>
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
switch (_distributionType)
{
case RandomVariableDistributionType.Normal:
var normalDistribution = new NormalDistribution(_meanValue, _standardDeviation);
return(_randomVariable = normalDistribution.NextDouble());
break;
case RandomVariableDistributionType.Lognormal:
var lognormal = new LognormalDistribution(_meanValue, _standardDeviation * _meanValue);
return(_randomVariable = lognormal.NextDouble());
break;
default:
return(0);
throw new NotImplementedException();
break;
}
}
public double[] GetDerivative(IStochasticDomainMapper domainMapper, double[] parameters)
{
double[] stochasticDomainPoint = domainMapper.Map(parameters);
var dk = kupper / (double)frequencyIntervals;
double[] derivative = { 0, 0 };
for (int i = 0; i < frequencyIntervals; i++)
{
for (int j = 0; j < frequencyIntervals; j++)
{
derivative[0] += -(dk / 2 + i * dk) * Math.Sqrt(2) * (Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, dk / 2 + j * dk) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] + (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi1[i, j])) +
Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, -(dk / 2 + j * dk)) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] - (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi2[i, j])));
derivative[1] += -(dk / 2 + j * dk) * Math.Sqrt(2) * (Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, dk / 2 + j * dk) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] + (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi1[i, j])) -
Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, -(dk / 2 + j * dk)) * dk) *
(Math.Sin((dk / 2 + i * dk) * stochasticDomainPoint[0] - (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi2[i, j])));
}
}
return(derivative);
}
public double Realize(int iteration, IStochasticDomainMapper domainMapper, double[] parameters)
{
ResetGeneration = (PreviousIteration != iteration);
if (ResetGeneration)
{
ResetSampleGeneration();
}
double[] stochasticDomainPoint = domainMapper.Map(parameters);
var dk = kupper / (double)frequencyIntervals;
double randomCoefficient = 0;
for (int i = 0; i < frequencyIntervals; i++)
{
for (int j = 0; j < frequencyIntervals; j++)
{
randomCoefficient += Math.Sqrt(2) * (Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, dk / 2 + j * dk) * dk) *
(Math.Cos((dk / 2 + i * dk) * stochasticDomainPoint[0] + (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi1[i, j])) +
Math.Sqrt(2 * SpectralDensity(dk / 2 + i * dk, -(dk / 2 + j * dk)) * dk) *
(Math.Cos((dk / 2 + i * dk) * stochasticDomainPoint[0] - (dk / 2 + j * dk) * stochasticDomainPoint[1] + phi2[i, j])));
}
}
return(randomCoefficient);
}
public Model GetModel(IUncertainParameterRealizer stochasticRealizer, IStochasticDomainMapper domainMapper, int iteration)
{
var m = new Model();
m.SubdomainsDictionary.Add(0, new Subdomain(0));
m.NodesDictionary.Add(0, new Node(id: 0, x: 0.0, y: 0, z: 0));
m.NodesDictionary.Add(1, new Node(id: 1, x: 0.1, y: 0, z: 0));
m.NodesDictionary.Add(2, new Node(id: 2, x: 0.2, y: 0, z: 0));
m.NodesDictionary.Add(3, new Node(id: 3, x: 0.3, y: 0, z: 0));
m.NodesDictionary.Add(4, new Node(id: 4, x: 0.4, y: 0, z: 0));
m.NodesDictionary.Add(5, new Node(id: 5, x: 0.5, y: 0, z: 0));
m.NodesDictionary.Add(6, new Node(id: 6, x: 0.6, y: 0, z: 0));
m.NodesDictionary.Add(7, new Node(id: 7, x: 0.7, y: 0, z: 0));
m.NodesDictionary.Add(8, new Node(id: 8, x: 0.8, y: 0, z: 0));
m.NodesDictionary.Add(9, new Node(id: 9, x: 0.9, y: 0, z: 0));
m.NodesDictionary.Add(10, new Node(id: 10, x: 1, y: 0, z: 0));
for (int i = 0; i < m.NodesDictionary.Count - 1; i++)
{
var e = new Element()
{
ID = i,
ElementType = new EulerBeam3D(stochasticRealizer.Realize(iteration, domainMapper,
new[]
{
(m.NodesDictionary[i + 1].X + m.NodesDictionary[i].X) / 2,
(m.NodesDictionary[i + 1].Y + m.NodesDictionary[i].Y) / 2,
(m.NodesDictionary[i + 1].Z + m.NodesDictionary[i].Z) / 2,
}), 0.3)
{
Density = 7.85,
SectionArea = 1,
MomentOfInertiaY = 1,
MomentOfInertiaZ = 1,
MomentOfInertiaPolar = 1,
}
};
e.AddNodes(new[] { m.NodesDictionary[i], m.NodesDictionary[i + 1] });
m.ElementsDictionary.Add(i, e);
m.SubdomainsDictionary[0].Elements.Add(e);
}
m.NodesDictionary[0].Constraints.Add(new Constraint {
DOF = StructuralDof.TranslationX, Amount = 0
});
m.NodesDictionary[0].Constraints.Add(new Constraint {
DOF = StructuralDof.TranslationY, Amount = 0
});
m.NodesDictionary[0].Constraints.Add(new Constraint {
DOF = StructuralDof.TranslationZ, Amount = 0
});
m.NodesDictionary[0].Constraints.Add(new Constraint {
DOF = StructuralDof.RotationX, Amount = 0
});
m.NodesDictionary[0].Constraints.Add(new Constraint {
DOF = StructuralDof.RotationY, Amount = 0
});
m.NodesDictionary[0].Constraints.Add(new Constraint {
DOF = StructuralDof.RotationZ, Amount = 0
});
m.Loads.Add(new Load()
{
Amount = 10, Node = m.NodesDictionary[10], DOF = StructuralDof.TranslationZ
});
//m.ConnectDataStructures();
return(m);
}
