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) |