Experiment


Description:

It represents the interface for an experiment of the project

Properties:

Name Name of the experiment
ID Identification number of the experiment
InitScript Scriptcode, which will be performed at the begin of the optimization process inside the experiment
FinalScript Scriptcode, which will be performed at the end of the optimization process inside the experiment
OptMethod

Optimization Method

0 = Standard

1 = GridSearch

2 = Hooke Jeeves

3 = Evolutionary Algorithms

4 = Simulation

5 = Adaptive Response Surface

6 = Genetic Algorithms

AutoStop

0 = Optimization will be stopped, if the number of the optimization steps has been reached.

1 = Optimization will be  stopped automatically

2 = Optimization will be  stopped automatically within a given number of the optimization steps.

OptSteps Number of the optimization steps
OptParent Number of parent for evolution strategies
OptChild Number of children for evolution strategies
PopulationSize Population size for genetic algorithms
MutationRate Mutation rate for genetic algorithms
CrossoverRate Crossover rate for genetic algorithms
DOEMethod

Method for Design of Experiment

0   = Monte Carlo Sampling

1   = Latin Hypercube Sampling

2   = Second Order Moment

3   = Subset Simulation

4   = Sobol Sampling

5   = Second Order Moment without Interaction

6   = First Order Moment

7   = First Order Moment without Interaction

8..11 = Reserved

12 = Full Factorial Design

13 = Central Composite Design

14 = User Design

15 = Standard

16 = Orthogonal Array

UserData User-defined data for design of experiment
NoiseOptimization Noise will be optimized
WeightOptimization Weights will be optimized
IncludeHilbertSpace Hilbert Space will be used by nonlinear method
MaxIteration Max iterations for linear method
MaxIterationNonlinear Max iterations for nonlinear method
LearningRate Learning rate for stochastic gradient descent method
SGDVariant Variant of stochastic gradient descent method
0 = Momentum
1 = AdaGrad
2 = RSMProp
3 = Adam
NonlinearMethod Nonlinear optimization method
0 = Evolution strategies
1 = Gradient based
2 = BFGS
3 = Stochastic Gradient Descent
LinearMethod Linear optimization method
Regularization Regularization
0 = Non
1 = L1
2 = L2
D1Xmax Max for X-axis of D1-variable
D1XStep Step for X-axis of D1-variable
D1Integration Integration method for D1-variable
0 = Non
1 = Heun
2= Runga-Kutta
SampleSize Sample Size
VirtualSampleSize Virtual Sample Size
DataType

Select of the datasets for the optimization results

0 = all optimization steps

1 = filtered solutions in Pareto-Set

2 = all solutions in Pareto-Set

CycleTime Max load cycle time
CycleTimeStep Step for the time axis of load cycle
FatigueSampleSize Sample size for fatigue life prediction
Application (ReadOnly) Return the Application-object
UserDataCount (ReadOnly) Number of user data sets
RobustCommandCount (ReadOnly) Return the number of the command array for robust design optimization
RobustCommand(Index) Return the command at the index for robust design optimization
Adaptive Adaptive Sampling for adaptive Gaussian process
MaxConfidence Max. confidence interval for adaptive Gaussian process
MaxPoints Max number of all new points for adaptive Gaussian process
AdaptParent Number of parent for evolution strategies of adaptive Gaussian process
AdaptChild Number of children for evolution strategies of adaptive Gaussian process
TrainData Percentage of DOE-data for train data
RDMethod Method for robust design optimization
2 = Hooke-Jeeves
else evolution strategies
RDSteps max.Steps for robust design optimization
RBParent Number of parents for robust design optimzation using evolution strategies
RBChildren Number of children for robust design optimzation using evolution strategies
RSMaxPolyOrder Max polynomial order for plonomila approximation
RSGaussNoiseOpt Noise optimization for Gaussian process
RSGaussMethod Optimization method for Gaussian process
0 = Evolutionsstrategies
1 = Gradient based Optimization
RSGaussSteps Max Steps for Gaussian process optimization
RSGaussParent Number of parent of evolution strategies for Gaussian process
RSGaussChild Number of children of evolution strategies for Gaussian process
MetaDesignParameter(Index) "Design Parameter" of the stochastic parameter with index (1...count) or name
MetaParameter(Index) "Virtual  Nominal" of the stochastic parameter with index (1...count) or name
MetaTolerance(Index) "Virtual  Tolerance" of the stochastic parameter with index (1...count) or name
MetaCost The cost function based on virtual tolerances of all stochastic parameters
MetaConstraint(Index) "Virtual Value" of the constraint with index (1..count) or name based o the mata-model
MetaCriterion(Index) "Virtual Value" of the criterion with index (1..count) or name based o the mata-model
MetaConstraintMean(Index) Mean of the constraint with index (1..count) or name based o the mata-model
MetaCriterionMean(Index) Mean of the criterion with index (1..count) or name based o the mata-model
MetaConstraintVariance(Index) Variance of the constraint with index (1..count) or name based o the mata-model
MetaCriterionVariance(Index) Variance of the criterion with index (1..count )or name based o the mata-model
MetaConstraintSigma(Index) Standard-deviation of the constraint with index (1..count) or name based o the mata-model
MetaCriterionSigma(Index) Standard-deviation of the criterion with index (1..count) or name based o the mata-model
MetaLifeTime(Index) LifeTime of the strain withn index (1..count) or name based on the meta-model
Meta1D(Index, Type, Value) "Virtual Value" of the 1D-variable with index (1..count) or name based o the mata-model
Type = { 0 = last value, 1 = max.value, 2 = min. value, 3 =  mean value, 4 = sum, 5 = absolute sum, 6 = band, 7 = standard deviation, 8 = integral, 9 = constraint, 10 = data-fitting, 11 = X by Y-point, 12 = Y by X-point, 13 = X by X-leap, 14 = X by Y-leap, 15 = Y by X-leap, 16 = Y by Y-leap, 17 = X tangente, 18 = Y tangente, 19 = first value, 20 = X by max. Y, 21 = X by min Y}

Methods:

Start() Start the optimization process of the experiment
Stop() Stop the optimization process of the experiment
Reset() Delete the optimization results and reset the experiment in initial state
Continue() Continue the stopped optimization process
Show() Show all output windows of the experiment
Hide() Hide all output windows of the experiment
RebuildBestValue() Rebuild the best value of the Pareto-Set
RebuildOutput() Rebuild outputs
RebuildCluster() Rebuild clusters
RebuildProbabilistics() Rebuild the probabilistics
RebuildSensitivity() Rebuild the sensitivities
RebuildResponseSurface() Rebuild response surfaces
RebuildFatigue Rebuild fatigue life data
CodeExport(String FilePathName) Export the meta-model of the actual dataset in:

FilePathName = *.c      : C Code

FilePathName = *.mo   : Modelica Code

FilePathName = *.m     : m-Matlab Script

FilePathName = *.vb    : Visual Basic Code

RobustOptimization() Start the robust design optimization based on the meta model
VirtualOptimization() Start the virtual optimization based on the meta model
VirtualSimulation() Start the external simulation with the virtual value of the stochastic parameters
DeleteLink(Integer ID) Delete the link with the ID number
DeleteNode(Variant Index) Delete the node with the index as either its ID or its name
Nominal(Variant Index) Return a Nominal-object with the index as the name or its forthcoming number in the experiment
Stochastic(Variant Index) Return a Stochastic-object with the index as the name or its forthcoming number in the experiment
Output(Variant Index) Return a Output-object with the index as the name or its forthcoming number in the experiment
Transfer(Variant Index) Return a Transfer-object with the index as the name or its forthcoming number in the experiment
Switcher(Variant Index) Return a Switcher-object with the index as the name or its forthcoming number in the experiment
Criterion(Variant Index) Return a Criterion-object with the index as the name or its forthcoming number in the experiment
Constraint(Variant Index) Return a Constraint-object with the index as the name or its forthcoming number in the experiment
D1Variable(Variant Index) Return a D1Variable-object with the index as the name or its forthcoming number in the experiment
GeometryData(Variant Index) Return a GeometryData-object with the index as the name or its forthcoming number in the experiment
Strain(Variant Index) Return a Strain-object with the index as the name or its forthcoming number in the experiment
RobustDesign(Variant Index) Return a RobustDesign-object with the index as the name or its forthcoming number in the experiment
Nominals() Return the Nominals-object. It is the collection of all nodes "Nominal Parameter" of the experiment
Stochastics() Return the Stochastics-object. It is the collection of all nodes "Stochastic Parameter" of the experiment
Outputs() Return the Outputs-object. It is the collection of all nodes "Output" of the experiment
Transfers() Return the Transfers-object. It is the collection of all nodes "Transfer Variable" of the experiment
Switchers() Return the Switchers-object. It is the collection of all nodes "Switcher" of the experiment
Criterions() Return the Criterions-object. It is the collection of all nodes "Criterion" of the experiment
Constraints() Return the Constraints-object. It is the collection of all nodes "Constraint" of the experiment
D1Variables() Return the D1Variables-object. It is the collection of all nodes "1D" of the experiment
GeometryDatas() Return the GeometryDatas-object. It is the collection of all "GeometryData" of the experiment
Strains() Return the Strains-object. It is the collection of all nodes "Strain Energy Density" of the experiment
RobustDesigns() Return the RobustDesigns-object. It is the collection of all nodes "Robust Design" of the experiment
DataSets() Return the DataSets-object. It is the collection of all datasets of the experiment as results
CSTStudio(String Name) Return the CSTStudio-object with the name in the experiment
Data(String Name) Return the Data-object with the name in the experiment
Excel(String Name) Return the Excel-object with the name in the experiment
ExternScript(String Name) Return the ExternScript-object with the name in the experiment
InputFile(String Name) Return the InputFile-object with the name in the experiment
InternScript(String name) Return the InternScript-object with the name in the experiment
Matlab(String Name) Return the Matlab-object with the name in the experiment
OutputFile(String Name) Return the OutputFile-object with the name in the experiment
NetCOM(String Name) Return the NetCOM-object with the name in the experiment
SimX(String Name) Return the SimX-object with the name in the experiment
User(String Name) Return the User-object with the name of the node
Users() Return the Users-object of the experiment. Its is the collection of all nodes "User" of the experiment
SimXs() Return the SimXs-object. It is the collection of all nodes "SimX" of the experiment
NetCOMs() Return the NetCOMs-object. It is the collection of all nodes "NetCOM" of the experiment
OutputFiles() Return the OutputFiles-object. It is the collection of all nodes "OutputFile" of the experiment
Matlabs() Return the Matlabs-object. It is the collection of all nodes "Matlab" of the experiment
InternScripts() Return the InternScripts-object. It is the collection of all nodes "InternScript" of the experiment
InputFiles() Return the InputFiles-object. It is the collection of all nodes "InputFiles" of the experiment
ExternScripts() Return the ExternScripts-object. It is the collection of all nodes "ExternScript" of the experiment
Excels() Return the Excels-object. It is the collection of all nodes "Excel" of the experiment
Datas() Return the Datas-object. It is the collection of all nodes "Data" of the experiment
CSTStudios() Return the CSTStudios-object. It is the collection of all nodes "CSTStudio" of the experiment
ExternAPIs() Return the ExternAPIs-object. It is the collection of all nodes "ExternAPI" of the experiment.
NodeNominal(String Name) Return the NodeNominal-object with the name in the experiment
GroupNominal(String Name) Return the GroupNominal-object with the name in the experiment
NodeStochastic(String Name) Return the NodeStochastic-object with the name in the experiment
GroupStochastic(String Name) Return the GroupStochastic-object with the name in the experiment
CreateLink(String OrgName, String DstName) Create a link from the node with the name OrgName to the node with the name DstName and return its Link-object
CreateConstraint(Integer X, Integer Y) Create a constraint at the (X,Y)-screen-position on the workflow editor and return its Constraint-object
CreateCriterion(Integer X, Integer Y) Create a criterion at the (X,Y)-screen-position on the workflow editor and return its Criterion-object
CreateRobustDesign(Integer X, Integer Y) Create a robust designat the (X,Y)-screen-position on the workflow editor and return its RobustDesign-object
CreateNodeNominal(Integer X, IntegerY) Create a nominal parameter at the (X,Y)-screen-position on the workflow editor and return its NodeNominal-object
CreateNodeStochastic(Integer X, Integer Y) Create a stochastic parameter at the (X,Y)-screen-position on the workflow editor and return its NodeStochastic-object
CreateGroupNominal(Integer X, Integer Y) Create a group of nominal parameters at the (X,Y)-screen-position on the workflow editor and return its GroupNominal-object
CreateGroupStochastic(Integer X, Integer Y) Create a group of stochastic parameters at the (X,Y)-screen-position on the workflow editor and return its GroupStochastic-object
CreateOutput(Integer X, Integer Y) Create a output variable at the (X,Y)-screen-position on the workflow editor and return its Output-object
CreateTransfer(Integer X, Integer Y) Create a transfer variable at the (X,Y)-screen-position on the workflow editor and return its Transfer-object
CreateSwitcher(Integer X, Integer Y) Create a switcher variable at the (X,Y)-screen-position on the workflow editor and return its Switcher-object
CreateD1Variable(Integer X, Integer Y) Create a 1D variable at the (X,Y)-screen-position on the workflow editor and return its D1Variable-object
CreateGeometryData(String Name) Create a geometry data with the name and return its GeometryData object.
CreateStrain(Integer X, Integer Y) Create a strain energy density at the (X,Y)-screen-position on the workflow editor and return its Strain-object
CreateData(Integer X, Integer Y) Create a node "Data" at the (X,Y)-screen-position on the workflow editor and return its Data-object
CreateExcel(Integer X, Integer Y) Create a node "Excel" at the (X,Y)-screen-position on the workflow editor and return its Excel-object
CreateExternScript(Integer X, Integer Y) Create a node "ExternScript" at the (X,Y)-screen-position on the workflow editor and return its ExternScript-object
CreateInputFile(Integer X, Integer Y) Create a node "InputFile" at the (X,Y)-screen-position on the workflow editor and return its InputFile-object
CreateInternScript(Integer X, Integer Y) Create a node "InternScript" at the (X,Y)-screen-position on the workflow editor and return its InternScript-object
CreateMatlab(Integer X, Integer Y) Create a node "Matlab" at the (X,Y)-screen-position on the workflow editor and return its Matlab-object
CreateOutputFile(Integer X, Integer Y) Create a node "OutputFile" at the (X,Y)-screen-position on the workflow editor and return its OutputFile-object
CreateNetCOM(Integer X, Integer Y) Create a node "NetCOM" at the (X,Y)-screen-position on the workflow editor and return its NetCOM-object
CreateSimX(Integer X, Integer Y) Create a node "SimX" at the (X,Y)-screen-position on the workflow editor and return its SimX-object
CreateUser(Integer X, Integer Y) Create a node "User" at the (X,Y)-screen-position on the workflow editor and return its User-object
CreateExternAPI(Integer X, Integer Y) Create a node "ExternAPI" at the (X,Y)-screen-position on the workflow editor and return its ExternAPI-object
InitUserData() Delete all user data and set the user data size to the number of stochastic parameters
AddUserData(System.Array newVal) Add the value list as user data set to the user data.
DeleteUserData(Integer Index) Delete the user data with the index (1..UserDataCount)
GetUserData(Integer Index) Get the user data with index (1..UserDataCount)