Nominal Optimization
The menus show the data related to a nominal optimization process.
Nominal Table
Show the nominal table, which lists all computing steps for nominal parameters, constraints, criteria, output variables etc. in the nominal optimization experiment.
Nominal Diagram
Show the nominal diagram. An empty window will appears. Using the drag & drop to move the desired elements as nominal parameters, output variables, criteria etc. from the explorer into the new opened window. Their computing values will be visualized as signal dependent on the optimization steps.
Parallel Chart
Show the parallel chart for a multi-objective optimization. At least, 2 criteria have to be defined in the experiment to make the parallel chart visible.
Diagram
This option can be set to adjust the visualizing of the signal in the nominal diagram.
Y(n)-Diagram
X-axis is the optimization step and Y-axis are the values of inserted element. All signals are visualized dependent on the optimization step.
2D-Diagram
First select a signal as the X-axis. Then activate the menu. All other signals are visualized dependent on this selected signal. This 2D-diagram is used best for evaluation of the multi-objective optimization results.
3D-Diagram
The axis dialog box appears to select X-, Y- and Z-axis from the experiment elements. The Z-signal is visualized as 3D-diagram dependent on X- and Y-signal.
Select Set
The optimization process generates a lot of the data. For the selection the best design from these data, the possibility has to be made available to select, to visualize and to evaluate a subset from them. This is done by the menu "Select Set".
Optimization
all computing steps are selected and visualized in the experiment. This is a standard option.
Pareto Frontier
Only set of the Pareto optimal solution points are selected.
Filtered Pareto Frontier
Only a given number of the Pareto optimal solutions is selected. It is normally 10 points and can be changed.
Best Value
This menu provides different possibilities to select the best design from the data generated by the optimization process.
Calculate
The best design will be calculated from the Pareto-optimal solution based on the weight factors for the defined criteria. User can set different weight factors for the defined criteria to get different best design by a multi-objective optimization.
Show Parameter
Show the table containing the parameters and results of the best design.
Set Parameter
Set the parameters of the best design to the experiment as the start values for the optimization. These parameters however will be not transferred to the external simulation system.
Run Simulation
Transfer the parameters of the best design to the external simulation system und start the simulation process. The start values of the parameters in the experiment are however unchanged.
Rebuild
All results of the experiment workflow will be recalculated as Criterion, Constraint, Transfer-Variable, 1D-Variable and Switcher. The recalculation bases on the outputs of external simulation saved in the dataset for design of experiment which will be updated correspondingly. It is useful if changing the computing rules inside of the workflow for these variables without restarting expensive simulation of the external programs. If a new node as Criterion or Constraint is added to the existing experiment carried out, the dataset for this variable will be automatically calculated and added into existing dataset for design of experiment.
DOE Table
Show the DOE table containing all computing steps of all elements for design of experiment.
Correlation Matrix
Show the correlation matrix for all correlation coefficients between the stochastic parameters, constraints and criteria.
Parallel Chart
Show the parallel chart for parameters, constraints and criteria in design of experiment.
Histogram
Show the histogram of the inserted element. An empty window will appear. Using drag & drop operation to move the desired elements as stochastic parameters, constraints, criteria etc. from the explorer into the new opened window.
The menus are available only by Factorial Design
OA-Table
Show the orthogonal array OA-Table for the Taguchi quality method.
S/N Ratio
Show the S/N Ratio of constraints or criteria for the Taguchi quality method
Sensitivity
Show the Sensitivity of constraints or criteria for the Taguchi quality method
Rebuild
Cluster will be rebuild
2D Scatter Plot
First, select the X- and Y-axis from the elements in the experiment. Then the 2D scatter plot of the selected elements will appear.
3D Scatter Plot
First, select the X-, Y- and Z-axis from the elements in the experiment. Then the 3D scatter plot of the selected elements will appear.
Response Surface
Rebuild
A new response surface will be rebuild based on the generated simulation data.
1D Diagram
Show the 1D Diagram of inserted elements. An empty windows will appear. Using the drag & drop operation to insert the desired elements as stochastic parameters, criteria and constraints to the new opened window.
2D Surface
Show the 2D Surface. User is asked for selection of the X-, Y- and color-axis from elements in the experiment.
3D Surface
Show the 3D Surface. User is asked for selection of the X-, Y-, Z- and color-axis from elements in the experiment.
3D Volume
Show the 3D Volume. User is asked for selection of the X-, Y-, Z-and color-axis from elements in the experiment.
Coefficient Chart
Show the coefficient chart of the inserted element. An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria and constraints to the new opened window.
Coefficient Table
Show the coefficient table listing all coefficients of the meta model.
Residual Plot
Show the residual plot of the inserted element. An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria and constraints to the new opened window.
Residual Histogram
Show the residual histogram of the inserted element. An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria and constraints to the new opened window.
The data of DOE will be sampled based on the response surface and put to the sample table.
Start the local optimization for measurement data to find the design parameters of the meta-model using local optimization method Hooke-Jeeves
Global Fitting Measuement
Start the local optimization for measurement data to find the design parameters of the meta-model using local optimization method Evolution Strategies.
Add Points
Show the dialog for Add Points
Export Model
Export and save the surrogate model into C-code, Modelica or m-Matlab.
Rebuild
The sensitivities will be rebuild based on the new virtual nominal and tolerance of the stochastic parameters.
Sensitivity Chart
Show the sensitivity chart. An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria,constraints or 1D-variable to the new opened window.
Interaction Chart
Show the interaction chart. An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria, constraints or 1D-variable to the new opened window.
Sensitivity Table
Show the sensitivity table.
Global Sensitivity Chart
Show the global sensitivity chart for all constraints and criteria of the experiment
Global Interaction Chart
Show the global interaction chart for all constraints and criteria of the experiment
Rebuild
The probabilistic properties as PDF and CDF will be rebuild based on the new virtual nominal and tolerance of the stochastic parameters. The defined virtual sample size is used to generate the output distributions.
Probability Density
Show the probability density function (PDF). An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria, constraints or 1D-variable to the new opened window.
Cumulative Distribution
Show the cumulative distribution function (CDF). An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria, constraints or 1D-variable to the new opened window.
Distribution Table
Show the distribution table.
Robust-Design Optimization
The robust design optimization process will start based on the global meta models. The objectives are created by Robust-Design in post-processing. The robust optimization variates virtual nominal as well as tolerance values and distribution of stochastic parameters for obtaining of these objective functions.
Design-Table
It contains all optimal parameter points found by robust design optimization. It is only one ore more points depending on number of defined objective functions. User can limit the number of design points by Pareto Number for multi-objective optimization.
Parallel Chart
It shows the Parallel Chart for the Design-Table
Update Pareto Set
The process will cut of the numer of design poinrts in Design-Table to the Pareto Number.
Run/Add Design-Table
All design points in thsi table will be run by original model. The data will be added to DOE-Table to generate the new meta-models.
Delete Design-Table
All design points will be deleted. The Design-Table will be empty.
Nominal Optimization
The nominal optimization process will start based on global meta models. The objective is the defined constraints and criteria of the experiment. The nominal optimization considers only virtual nominal values of stochastric parameters based on nominal constraints and criteria. Tolerance values and distribution are ignored.
Run Simulation
The simulation with the virtual nominal of the stochastic parameters will be run by original model.
Run/Add Simulation
The simulation with the virtual nominal of the stochastic parameters will be run by original model. The data will be added to DOE-Table to generate the new meta-models.
Show Parameters
It shows the virtual nominal and tolerance of the stochastic parameters in a table as the actual value (red lines).
Reset Parameters
All virttual nominal values of the stochastic parameters will be reset as initial values for design of experiment.
Scatter Plot
Show either 1D signal for nominal optimization or 1D signal scatter for design of experiment. An empty windows will appear. Use drag& drop to move an element from 1D-variables in the explorer into the opened window.
Residual Plot
Show 1D signal residual. An empty windows will appear. Use drag& drop to move an element from 1D-variables in the explorer into the opened window.
Response Surface
Show 1D signal response surface. An empty windows will appear. Use drag& drop to move an element from 1D-variables in the explorer into the opened window.
Probability Density
Show 1D signal probabiliuty density. An empty windows will appear. Use drag& drop to move an element from 1D-variables in the explorer into the opened window.
Sensitivity
Show 1D signal sensitivity. An empty windows will appear. Use drag& drop to move an element from 1D-variables in the explorer into the opened window.
Coefficient Table
Show the coefficient table listing all coefficients of the meta model.
Reset X-Axis
Reset the X-Value of all 1D-Variables to its first values of the X-axis.
Start Animation
Start the animation process. The X-Value of all 1D-Variables will be incremented and all opened grafical windows will be updated. The frequency of the updated pictures per minute can be edited by animation setings.
Stop Animation
The animation process started before will be stoped.
Rebuild
The fatigue life data will be recalculate based on the existing response surface. It is required if either the response surface or the load function or the time axis for the cycle have been changed.
Load Diagram
Show the load diagram of the cycle. An empty windows will appear. Using the drag & drop operation to insert the desired elements as stochastic design parameters to the new opened window.
Strain Diagram
Show the strain diagram of the cycle. An empty windows will appear. Using the drag & drop operation to insert the desired elements as strain energy density to the new opened window.
Stress Diagram
Show the stress diagram of the cycle. An empty windows will appear. Using the drag & drop operation to insert the desired elements as strain energy density to the new opened window.
Stress-Strain Hysteresis
Show the stress-strain hysteresis of the cycle. An empty windows will appear. Using the drag & drop operation to insert the desired elements as strain energy density to the new opened window.
Strain Energy Density
Show the strain energy density of the cycle. An empty windows will appear. Using the drag & drop operation to insert the desired elements as strain energy density to the new opened window.
Failure Probability
Show the failure probability. An empty windows will appear. Using the drag & drop operation to insert the desired elements as criteria and constraints to the new opened window.
Fatigue Life Table
Show the fatigue life table of the prediction.