3. Adding new rule classes

Previously, we stated that the failure probability was 10 times greater if there was live steam in the room than if there was not. We also don't want the expected failure probability for the motor operated valve to change from its old value 0.001858. Solving the resulting equation, we get that the failure rate of the MOV conditioned on live steam in the room is 0.017046 and is 0.001705 without the live steam.

However, before we add these conditional rules to the model we need to be wary. We will want to compare the model before and after changes. Even though Graphical-Belief has some very nice tools for comparing changes in a model after it is compiled, those tools don't work if we make structural changes to the model (adding variables or rules) and hence need to recompile it. To get around this difficulty, we can create a conditional distribution for the MOV which looks a lot like the old MOV-rule and does not depend on "Live-Steam" even though it is an input. After we compile the model, we can change the valuation and assess the effect with the standard history tools.

As there are two MOV's we can once again take advantage of Graphical-Belief's object-oriented model construction to organize the information. To do this, we will want to define a new class of MOV rule and make our changes there.

Figure 6. Model after creating "Steam-Mov-Rule".

We start by creating a new "Cond-Pmf" rule (previously we added "Cond-Pmf" to the template with the "Finding tool", Figure 1) and naming it "Steam-MOV-Rule". As this is a conditional rule, it has two input handles, one for input variables and one for output variables. We connect "Live-Steam" as an input and "MOV-25-B" as an output. The result looks like Figure 6.


Continue with this example and edit the properties of the new rule.

Model Construction. Go back to the begining of this example.

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Russell Almond, <lastname> (at) acm.org
Last modified: Fri Aug 16 18:45:29 1996