Import data from a DOE or Monte-Carlo study

This example is a variant of the previous one. Here, instead of an Excel® file, the chosen input file is the log file of a previous Design of Experiment or Monte-Carlo study made with Simcenter Amesim. See the Design Exploration manual for more details.

Note that such a log file contains the values for inputs, outputs and compound outputs organized as columns of the same length (one run per line), which makes it directly usable with the Data Import.

Follow the below steps for using a DOE or Monte-Carlo log file:

Procedure

1. Open the Simcenter Amesim model containing the completed DOE or Monte-Carlo study.

2. In the Data Import GUI, click the Open button and browse the files contained at the location of this Simcenter Amesim model by selecting the All files (*) filtering option. Look for the file called sysname_.mc_studyname for a Monte-Carlo study or sysname_.doe_studyname for a Design of Experiment study.

Note sysname is the name of the Simcenter Amesim model and studyname is the name of the DOE or Monte-Carlo study.

See an example involving a Monte-Carlo study in the figure below: Figure 64: Selecting a file containing results of a Monte-Carlo study

3. Open the file, it should look like this:

Figure 65: Layout of a file containing results of a Monte-Carlo study

4. Select Semicolon as the delimiter:

5. Remove unnecessary rows until you see the row starting with Run status and containing the names of inputs and outputs previously defined in the model where your DOE or Monte-Carlo study was defined.

6. As input and output names are present, you can define this row as Titles row.

7. Continue to "clean up" your data selection (remove empty rows, remove the first column entitled Run status) until a proper data range is defined.

At the end of this process, you should get an XY table similar to the one shown in the Figure 55 figure. Note Note that your data selection cannot contain more than N numerical rows; N being the number of runs of your Design Exploration study. The number of columns should also be equal to the sum of the number of inputs and outputs (including compound outputs) used for your Design Exploration study.

8. Proceed as in the previous example to configure the SIGHULL0 component.

Results

1D Table

data fitting

data interpolation

table

You now have configured the SIGHULL0 submodel based on a previous Monte-Carlo or Design Exploration study made with Simcenter Amesim. You now have a computationally-efficient numerical interpolation of your initial physical model based on multiple runs.