Abstract

Measurements of reactor physics quantities aimed at identifying the reactivity worth of materials, spectral ratios of cross-sections, and reactivity coefficients have ensured reactor physics codes can accurately predict nuclear reactor systems. These measurements were critical in the absence of sufficiently accurate differential data, and underpinned the need for experiments through the 50s, 60s, 70s and 80s. Data from experimental campaigns were routinely incorporated into nuclear data libraries either through changes to general nuclear data libraries, or more commonly in the local libraries generated by a particular institution or consortium interested in accurately predicting a specific nuclear system (e.g. fast reactors) or parameters (e.g. fission gas release, yields). Over the last three decades, the model has changed. In tandem access to computing power and monte carlo codes rose dramatically. The monte carlo codes were well suited to computing k-eff, and owing to the availability of high quality criticality benchmarks and these benchmarks were increasing used to test the nuclear data. Meanwhile, there was a decline in the production of local libraries as new nuclear systems were not being built, and the existing systems were considered adequately predicted. The cost-to-benefit ratio of validating new libraries relative to their improved prediction capability was less attractive. These trends have continued. It is widely acknowledged that the checking of new nuclear data libraries is highly skewed towards testing against criticality benchmarks, ignoring many of the high quality reactor physics benchmarks during the testing and production of general-purpose nuclear data libraries. However, continued increases in computing power, methodology (GPT), and additional availability reactor physics experiments from sources such as the International Handbook of Evaluated Reactor Physics Experiments should result in better testing of new libraries and ensured applicability to a wide variety of nuclear systems. It often has not. Leveraging the wealth of historical reactor physics measurements represents perhaps the simplest way to improve the quality of nuclear data libraries in the coming decade. Resources at the Nuclear Energy Agency can be utilized to assist in interrogating available identify benchmarks in the reactor physics experiments handbook, and expediting their use in verification and validation. Additionally, high quality experimental campaigns that should be examined in validation will be highlighted to illustrate potential improvements in the verification and validation process.

Highlights

  • Neutronics predictions underpin the safety, economics, and operation of reactor systems

  • Despite improvements to methods and data, the cost benefit ratio of the validation process is prohibitive to adopting these updates; a case in point is that the nuclear data library of reference for many applications in the UK is JEF2.2, released in 1992

  • A rethink is needed about how nuclear data validation is done, and the roles and priorities of the various stakeholders

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Summary

INTRODUCTION

Neutronics predictions underpin the safety, economics, and operation of reactor systems. The amount of measured data is far less than the number of reactor states, and advanced simulations based on more accurate data allow better interpolation and extrapolation away from the measured state points; incentivizing the use of improved methods. Given the above, it should be common practice for nuclear data evaluations to be vetted against the gauntlet of collected experimental data. The gold standard would be to have good reactor physics benchmarks of all relevant phenomena, coupled with tools and data that make them easy to use and test by nuclear data evaluators and validation committees. The available benchmarks in the reactor physics handbook [23] will be explored that are readily available for improved nuclear data testing

REACTOR PHYSICS EXPERIMENTAL BENCHMARKS FOR NUCLEAR DATA TESTING
Criticality
Spectral Characteristics
Available Measurements
Reactivity Effects and Coefficients
Method
Temperature Reactivity
Control Rod Worth
Available Measurements Burnup Reactivity
Kinetics Parameters
Reaction Rate and Power Distributions
CONCLUSIONS

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