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Journal Articles

Great achievements of M. Salvatores for nuclear data adjustment study with use of integral experiments

Yokoyama, Kenji; Ishikawa, Makoto*

Annals of Nuclear Energy, 154, p.108100_1 - 108100_11, 2021/05

https://doi.org/10.1016/j.anucene.2020.108100

Times Cited Count：1 Percentile：25.87(Nuclear Science & Technology)

In the design of innovative nuclear reactors such as fast reactors, the improvement of the prediction accuracies for neutronics properties is an important task. The nuclear data adjustment is a promising methodology for this issue. The idea of the nuclear data adjustment was first proposed in 1964. Toward its practical application, however, a great deal of study has been conducted over a long time. While it took about 10 years to establish the theoretical formulation, the research and development for its practical application has been conducted for more than half a century. Researches in this field are still active, and the fact suggests that the improvement of the prediction accuracies is indispensable for the development of new types of nuclear reactors. Massimo Salvatores, who passed away in March 2020, was one of the first proposers to develop the nuclear data adjustment technique, as well as one of the great contributors to its practical application. Reviewing his long-time works in this area is almost the same as reviewing the history of the nuclear data adjustment methodology. The authors intend that this review would suggest what should be done in the future toward the next development in this area. The present review consists of two parts: a) the establishment of the nuclear data adjustment methodology and b) the achievements related to practical applications. Furthermore, the former is divided into two aspects: the study on the nuclear data adjustment theory and the numerical solution for sensitivity coefficient that is requisite for the nuclear data adjustment. The latter is separated to three categories: the use of integral experimental data, the uncertainty quantification and design target accuracy evaluation, and the promotion of nuclear data covariance development.

Journal Articles

Dimension-reduced cross-section adjustment method based on minimum variance unbiased estimation

Yokoyama, Kenji; Yamamoto, Akio*; Kitada, Takanori*

Journal of Nuclear Science and Technology, 55(3), p.319 - 334, 2018/03

https://doi.org/10.1080/00223131.2017.1397563

Times Cited Count：8 Percentile：68.49(Nuclear Science & Technology)

A new formulation of the cross-section adjustment methodology with the dimensionality reduction technique has been derived. This new formulation is proposed as the dimension reduced cross-section adjustment method (DRCA). Since the derivation of DRCA is based on the minimum variance unbiased estimation (MVUE), an assumption of normal distribution is not required. The result of DRCA depends on a user-defined matrix that determines the dimension reduced feature subspace. We have examine three variations of DRCA, namely DRCA1, DRCA2, and DRCA3. Mathematical investigation and numerical verification have revealed that DRCA2 is equivalent to the currently widely used cross-section adjustment method. Moreover, DRCA3 is found to be identical to the cross-section adjustment method based on MVUE, which has been proposed in the previous study.

Journal Articles