NMB Research Themes

Currently, the idea is to consolidate input and output on a single Excel sheet to facilitate scenario management. On the other hand, since the output from the NMB is enormous, a method of dumping the output in bulk and visualizing it separately is also considered to be convenient. Furthermore, we will consider how the complex future nuclear energy picture should be organized and communicated to each stakeholder.

It can be estimated how uncertainties in cross sections, input parameters, etc. will affect a particular output by running the NMB many times It is expected to be implemented as a wrap code around to the NMB itself. This function will quantify the uncertainty of future scenarios.

The Pu fraction and cross section of plutonium fuel changes during burnup depending on the plutonium composition. In the current NMB, the Pu fraction is determined to keep the infinite multiplication factor constant at the end of the burnup period, and burnup calculations are performed using representative cross sections, but the validity of this method is unknown. To confirm the validity of this method, it is necessary to set the appropriate Pu fraction for various Pu compositions, obtain cross sections, calculate post-burnup compositions, and compare them with the current model. Furthermore, to make improvements, a promising method is to use machine learning to obtain spent fuel compositions from Pu isotopic compositions without having to go through burnup calculations. This improvement will greatly improve the accuracy of predicting future plutonium utilization and plutonium balance, as well as increase the calculation speed.

Currently only HLW is quantified. Add the ability to quantify low and intermediate level waste quantities. This would quantify the trade-offs, for example, that partitioning and transmutation technologies reduce HLW but increase ILW.

An assessment of public exposure from groundwater scenarios by linear summation of nuclides has been preliminarily implemented. This functionality will be validated and revised for evaluation in comprehensive technical reports by NUMO and other documents. Preliminary dose estimates will be available for a wide variety of wastes, enabling studies that were previously unknown, such as quantification of safety margins and dose reductions from partitioning and transmutation technologies.

Add the ability to calculate material-specific attractiveness, such as critical mass, heat generation, and radioactivity of nuclear materials. Machine learning is expected to be effective in evaluating the critical mass of actinides of diverse composition. It will be possible to provide a preliminary indication of the nonproliferation potential of future nuclear fuel cycles, and to make comparisons among a wide range of scenarios, which has been difficult to do in the past.

A database of public exposures and their frequencies based on probabilistic risk assessment and a method to incorporate them will be studied. It will be possible to make side-by-side comparisons of the safety of various processes, such as reactors and reprocessing facilities, and to identify where and when unsafe parts of the nuclear industry exist. It also makes it possible to quantify the effects of reactor facilities with improved safety features and to estimate the degree of safety that future reactor facilities should have.

The economic evaluation function has been implemented, but the database is not well developed. A database based on a unified idea as much as possible should be developed to enable fair economic evaluation of future technologies.

Although zeolite and metal waste are tentatively set for HLW generated from pyrochemical reprocessing, they should be updated to a reasonable one. Metal fuel fast reactors to which pyrochemical reprocessing is applied have recently attracted attention as a comparison for oxide fuels, but the comparison in terms of waste is not sufficient; this is a research theme that includes not only generation estimates by the NMB but also disposal methods and safety evaluation after disposal.

A database of fuel types and reactor types will be developed for the various SMRs, so that future predictions can be made for the major ones. Although SMRs have been actively developed in recent years, comparisons with conventional reactors and between SMR reactors have rarely been made. In addition, the estimation of spent fuel from SMRs and their treatment and disposal methods are not yet clarified. We will compile a database and clarify these issues.

Molten salt reactors are in a similar situation as SMRs. Molten salt reactors are unique in that they are liquid fuels and are reprocessed at the same time as they are burned, and the advantages of this in the nuclear fuel cycle will be clarified.

Until now, spent fuel from domestic light water reactors has been distinguished only between PWRs and BWRs, but in reality, it can be classified by each electric utility, each site, or each power reactor to predict reprocessing and future LWR MOX use. The development and publication of such a model would be useful in clarifying the characteristics and issues of each electric power company and in planning reprocessing. Furthermore, it will be possible to clarify issues such as spent fuel storage in the near future and the effects of the introduction of individual MOX utilization.

The Fast Reactor Development Strategy Roadmap has provided a roadmap for the future introduction of fast reactors. In order to contribute to the discussion of the roadmap, a standard scenario for the introduction of fast reactors is established and published.

A global model has not been developed by the NMB to date. The global model will be developed and made public to enable research from a broad perspective, such as the study of the limit of uranium resources as well as the possibility of international transfer of plutonium and waste.