In an earlier paper (), we proposed a methodology that potentially can be used to address these new challenges in the design and licensing of evolving nuclear technology. The main components of the proposed methodology are verification, validation, calibration, and uncertainty quantification. An enhanced calibration concept was introduced and is accomplished through data assimilation. Since advanced MS/MP codes have not yet reached the level of maturity required for a comprehensive validation and calibration exercise, we considered two legacy fuel codes and apply parts of our methodology to these codes to demonstrate the benefits of the new calibration capabilities we recently developed as a part of the proposed framework. This effort does not directly support ¡°born-assessed¡± validation for advanced MS/MP codes, but is useful to gain insight on legacy modeling deficiencies and to guide and develop recommendations on high and low priority directions for development of advanced codes and advanced experiments, so as to maximize the benefits of advanced validation and uncertainty quantification (VU) efforts involving the next generation of MS/MP code capabilities.
This paper discusses the application of advanced validation techniques (sensitivity, calibration, and prediction) to nuclear fuel performance codes FRAPCON () and LIFE-4 (). FRAPCON is used to predict oxide fuel behavior in light water reactors. LIFE-4 was developed in the 1980s to predict oxide fuel behavior in fast reactors. We introduce a sensitivity ranking methodology to narrow down the selected parameters for follow-up sensitivity and calibration analyses. We use screening methods with both codes and discuss the results. The number of selected modeling parameters was 61 for FRAPCON and 69 for LIFE-4. The screening study resulted in only 24 parameters of importance in the FRAPCON application, whereas LIFE-4 analysis reduced the set of important modeling parameters from 69 to 35.
Sensitivity screening results, combined with post-calibration sensitivity analysis, results in the following ranking of LIFE-4 models for future improvements: fuel creep, fuel thermal conductivity, fission gas transport/release, crack/boundary, and fuel gap conductivity. More data are needed to validate calibrated parameter distributions for future uncertainty quantification studies with LIFE-4.
We apply a collection of different VU methodologies to assess the preliminary performance of an advanced fuel code (see Stull, C.J., Williams, B.J., Unal. C., 2012). We summarize our lessons learned from that study in the discussion section to provide a context for issues often encountered in the application of advanced VU methodologies.