To prepare a design of experiment (DOE) in ANSYS Workbench, you need to follow these steps:
- First, you need to define the parameters that you want to vary in your model. You can do this by right-clicking on the Parameters branch in the Project Schematic and selecting Define Parameters. You can also use the Parameter Manager to create and edit parameters1.
- Next, you need to assign the parameters to the appropriate inputs or outputs in your model. For example, if you want to vary the load magnitude or the material properties, you can assign parameters to these values in the Engineering Data or the Mechanical branches. You can also use expressions to define parameters as functions of other parameters1.
- Then, you need to create a new Design of Experiments system by dragging and dropping it from the Toolbox under Design Exploration. You can connect it to the Parameter Set and the Analysis system that you want to perform the DOE on2.
- After that, you need to double-click on the Design of Experiments system and select the type of DOE that you want to use. There are different types of DOE methods, such as Full Factorial, Central Composite, Box-Behnken, Latin Hypercube, etc. Each method has its own advantages and disadvantages depending on the number of parameters, levels, and design points. You can also specify the lower and upper bounds for each parameter and the number of levels or design points23.
- Finally, you need to update the Design of Experiments system by clicking on the Update icon in the toolbar. This will run the analysis for each combination of parameter values and generate a table and a chart with the results. You can also export the data to a file or a report2.
How to specify upper and lower bounds and number of levels in Design Of Experiments in Ansys Workbench ?
To specify upper and lower bounds and number of levels in Design of Experiments in ANSYS Workbench, you can follow these steps:
- First, you need to create a new Design of Experiments system by dragging and dropping it from the Toolbox under Design Exploration. You can connect it to the Parameter Set and the Analysis system that you want to perform the DOE on1.
- Next, you need to double-click on the Design of Experiments system and select the type of DOE that you want to use. There are different types of DOE methods, such as Full Factorial, Central Composite, Box-Behnken, Latin Hypercube, etc. Each method has its own advantages and disadvantages depending on the number of parameters, levels, and design points23.
- Then, you need to click on the Details view and expand the Input Parameters branch. You will see a list of parameters that you have defined in your model. For each parameter, you can specify the lower and upper bounds by entering the values in the corresponding columns. You can also use expressions to define the bounds as functions of other parameters or constants2.
- After that, you need to expand the Output Parameters branch. You will see a list of outputs that you have defined in your model. For each output, you can specify the number of levels by entering the value in the corresponding column. The number of levels determines how many discrete values the output can take within its range2.
- Finally, you need to update the Design of Experiments system by clicking on the Update icon in the toolbar. This will run the analysis for each combination of parameter values and generate a table and a chart with the results. You can also export the data to a file or a report2.
What are advantages and disadvantages of Full Factorial, Central Composite, Box-Behnken, Latin Hypercube in Ansys Workbench Design Of Experiements ?
The advantages and disadvantages of Full Factorial, Central Composite, Box-Behnken, and Latin Hypercube designs in ANSYS Workbench Design of Experiments are as follows:
- Full Factorial design: This design involves all possible combinations of the levels of the factors. It can estimate all main effects and interactions, as well as higher-order terms. It is the most powerful and accurate design, but also the most expensive and time-consuming. It requires a large number of runs, especially when the number of factors or levels is high12.
- Central Composite design: This design is a fractional factorial design with center points and axial points (also called star points). It can estimate first- and second-order terms, as well as some interactions. It can model curvature in the response surface and find the optimal settings for the factors. It is useful for sequential experiments, as it can build on previous factorial experiments. It requires fewer runs than a full factorial design, but more than a Box-Behnken design. It may also involve extreme values for the factors that are outside the safe operating zone123.
- Box-Behnken design: This design is a fractional factorial design with center points, but no axial points. It can also estimate first- and second-order terms, but not all interactions. It can model curvature in the response surface and find the optimal settings for the factors. It requires fewer runs than a central composite design, but more than a Latin Hypercube design. It does not involve extreme values for the factors, so it ensures that all runs are within the safe operating zone124.
- Latin Hypercube design: This design is a random sampling method that ensures that each factor is varied over its entire range. It can estimate main effects and some interactions, but not higher-order terms. It cannot model curvature in the response surface or find the optimal settings for the factors. It requires the least number of runs among the four designs, but it is also the least accurate and precise. It may also involve extreme values for the factors that are outside the safe operating zone12 .
How to read results from other design points in Ansys Workbench ?
To read the results from other design points in ANSYS Workbench, you can follow these steps:
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