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El Salvador: Looking to nuclear
In 2022, El Salvador’s leadership decided to expand its modest, mostly hydro- and geothermal-based electricity system, which is supported by expensive imported natural gas and diesel generation. They chose to use advanced nuclear reactors, preferably fueled by thorium-based fuels, to power their civilian efforts. The choice of thorium was made to inform the world that the reactor program was for civilian purposes only, and so they chose a fuel that was plentiful, easy to source and work with, and not a proliferation risk.
Tomasz Skorek
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1540-1553
Technical Paper | doi.org/10.1080/00295450.2019.1580532
Articles are hosted by Taylor and Francis Online.
The input uncertainties propagation methods are the most frequently applied statistical methods in uncertainty analyses. Among them, particularly popular are the methods based on Wilks’ formula. Numerous studies on uncertainty analyses show that the identification and quantification of input uncertainties is a major problem with uncertainty analyses. Among input uncertainties evaluation, the identification and quantification of physical model uncertainties in thermal-hydraulic codes appear to be particularly difficult.
This paper deals with this problem by proposing inherent model uncertainties quantification by code developers in the frame of code development and validation. The introduction of the extended code validation would not only contribute to potential uncertainty analyses, solving to a large degree the problem of model uncertainties quantification, but also contribute to code validation, and as a consequence, improve the safety issues. A not-negligible factor is also better management of the resources. Instead of uncertainty quantification repeatedly performed by each user, the quantification could be performed once and, in addition, by experts having the required know-how.
Introducing this new standard in code validation would require additional effort from the code developers but integral quantification of the model uncertainties would be profitable also for code development. In fact, by code development, in particular if the model is own development of the team, such an accuracy (or uncertainty) evaluation is usually performed. The additional effort, in this case, would be to describe the present information in the form of probability distribution functions or at least in the form of ranges.