11.7. CIRCE method

The CIRCE method is a statistical approach proposed as an alternative to expert judgement, designed to determine the uncertainty of parameters in a physical model. Such uncertainties are often difficult to assess because some parameters may not be directly measurable. However, by relying on separate-effect tests (SET) experiments, that are sensitive to the physical model, it becomes possible to infer estimates of these uncertainties.

As explained in Introduction, CIRCE is not a strict calibration method, its logic differs from the standard framework (see [Bla17] for details). For this reason, it does not inherit from the TCalibration class (and therefore does not provide the common calibration methods presented in Common methods of the calibration classes). Instead, it has its own dedicated structure, implemented in Uranie through the TCirce class.

The usage of the TCirce class can be summarised in a few key steps:

1. Prepare the data and the model:

   • Specify the experimental dataserver;

   • Construct the TCirce object by specifying the experimental attribute, the code attribute, and the sensitivity attributes (see Constructing the TCirce object).

2. Set the algorithm properties:

   • Initialise the algorithm;

   • Define optional behaviours (see Defining the TCirce properties).

3. Perform the estimate:

   • Run the estimate process (see Running the estimate).

4. Perform post-processing:

   • Extract the results for post-treatment (see Looking at the results).

• 11.7.1. Constructing the TCirce object
• 11.7.2. Defining the TCirce properties
• 11.7.3. Running the estimate
• 11.7.4. Looking at the results

An example is also provided in the use-case section (see Macro “calibrationCirce.C”).