3.2.5. Setting up a Probability Distribution for an Uncertain Input Parameter

This section demonstrates the setup of probability distributions for initial Temperature and Pressure for the closed_homogeneous__transient project. These are both located on the Reactor Physical Properties tab for the C1_Closed Homogeneous node on the Project Tree. On this panel, click on the Uncertainty Analysis icon next to Temperature. The dialog is shown in Figure 3.4: closed_homogeneous__transient.ckprj — Uncertainty Analysis Dialog for Temperature. First, you need to choose a probability density function that can closely represent the uncertain behavior of initial Temperature. In case you do not have enough information to make a selection, choose Normal distribution. Next, fill in the distribution parameters. In the case of Normal distribution, the Mean Value is the same as the nominal value of the initial Temperature, so that you cannot set the Mean Value. Set the Standard Deviation to 50.0. To close the dialog, click the Done button. The Temperature label’s color changes from black to green, which indicates that an Uncertainty Analysis has been set up for this parameter.

Figure 3.4: closed_homogeneous__transient.ckprj — Uncertainty Analysis Dialog for Temperature

closed_homogeneous__transient.ckprj — Uncertainty Analysis Dialog for Temperature

Now click on the Uncertainty Analysis icon next to Pressure, use the Normal distribution and set the Standard Deviation as 0.5. When you click the Done button, an error message pops up, as shown in Figure 3.5: Error Message about Standard Deviation Being Too Large, to tell you that the standard deviation is too large and the distribution will generate negative sampling points for pressure, which has to be positive. You must reduce the standard deviation until this error message no longer appears. Reset the Standard Deviation to 0.1 instead. Click the Done button to close the dialog.

Figure 3.5: Error Message about Standard Deviation Being Too Large

Error Message about Standard Deviation Being Too Large