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Quantification of integral data effectiveness using the concept of active subspace in evaluated nuclear data validation
| Title: | Quantification of integral data effectiveness using the concept of active subspace in evaluated nuclear data validation |
| Authors: | Chiba, Go Browse this author →KAKEN DB | | Imazato, Daichi Browse this author |
| Keywords: | Evaluated nuclear data | | integral data | | benchmark calculations | | active subspace |
| Issue Date: | Nov-2020 |
| Publisher: | Taylor & Francis |
| Journal Title: | Journal of nuclear science and technology |
| Volume: | 57 |
| Issue: | 11 |
| Start Page: | 1245 |
| End Page: | 1255 |
| Publisher DOI: | 10.1080/00223131.2020.1780992 |
| Abstract: | In order to know the performance of evaluated nuclear data in reactor physics or radiation shielding calculations, its benchmark testing with integral data is mandatory. Nowadays we have a huge amount of integral data, but some of them are quite similar to each other. We need to know the independency of available integral data, and also to choose a proper set of a limited number of integral data for benchmark calculations. Furthermore, it is beneficial to know how effective a set of integral data is for independent validation of each nuclear data in performing the validation test of nuclear data. In order to quantify the effectiveness of integral data in nuclear data validation, we propose several methods based on a concept of the active subspace. With the proposed methods, we can quantify the independency of a set of integral data, choose a minimum set of proper integral data, and quantify the possibility of independent validation of nuclear data from a set of integral data. These methods are adopted to a set of fictitious integral data and a set of actual integral data including experimental data aboutand reaction rate ratio. Through these applications, effectiveness of these integral data has been successfully quantified. Furthermore, the proposed concept is utilized to interpret the nuclear data compensation effect, which has been recently discussed in the community of nuclear data. |
| Rights: | This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of nuclear science and technology on Nov 2020, available online: http://www.tandfonline.com/10.1080/00223131.2020.1780992. |
| Type: | article (author version) |
| URI: | http://hdl.handle.net/2115/83118 |
| Appears in Collections: | 工学院・工学研究院 (Graduate School of Engineering / Faculty of Engineering) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: 千葉 豪
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