Assessing the quality of neutronics parameters adjustment: an overview of approaches and recommendations for their use
- 作者: Andrianov A.A.1, Andrianova O.N.1
-
隶属关系:
- Obninsk Institute for Nuclear Power Engineering NRNU MEPhI
- 期: 编号 110 (2024)
- 页面: 266-294
- 栏目: Control of technological systems and processes
- URL: https://ogarev-online.ru/1819-2440/article/view/285155
- DOI: https://doi.org/10.25728/ubs.2024.110.10
- ID: 285155
如何引用文章
全文:
详细
The article presents a comprehensive review of state-of-the-art approaches to diagnosing and assessing the quality of data assimilation results in neutronics modeling problems. Despite the widespread use of data assimilation procedures worldwide to refine the parameters of neutronics models based on reactor experiment results there is a lack of attention given to the issues of diagnostics and quality assessment in this specific area. This stage is crucial in ensuring the reliability and accuracy of assimilation results. By adhering to relevant recommendations, it is possible to avoid obtaining non-physical solutions, minimize compensatory effects when adjusting initial data, and include contradictory experiments in the analysis. The article discusses the most popular metrics and approaches for assessing the quality of covariance data, as well as indicators of informativeness and similarity between reactor physics experiments and the target object. It also covers methods for identifying contradictory experiments and diagnosing the quality of the solution using various statistical indicators. The article highlights the areas of application for different metrics and approaches, as well as their advantages and disadvantages, providing recommendations for their use.
作者简介
Andrei Andrianov
Obninsk Institute for Nuclear Power Engineering NRNU MEPhI
Email: andreyandrianov@yandex.ru
Obninsk
Olga Andrianova
Obninsk Institute for Nuclear Power Engineering NRNU MEPhI
Email: o.n.andrianova@yandex.ru
Obninsk
参考
- АНДРИАНОВ А.А., АНДРИАНОВА О.Н. Ассимиляция данных в задачах моделирования нейтронно-физических процессов в объектах использования атомной энергии: текущее состояние и перспективы развития // Управле-ние большими системами: сборник трудов. – 2023. – №104. – С. 118–134. – doi: 10.25728/ubs.2023.104.5.
- АНДРИАНОВ А.А., АНДРИАНОВА О.Н., ГОЛОВ-КО Ю.Е. Методика оценки интегральных эксперимен-тов для использования в задаче оценки точности нейтронно-физических расчетов // Депонированная ру-копись. – №68-В2021. – 2021. – 58 с.
- АНДРИАНОВ А.А., АНДРИАНОВА О.Н., КОРО-ВИН Ю.А. и др. Программный комплекс оптимизации параметров нейтронно-физических моделей с учетом результатов интегральных экспериментов // Известия вузов. Ядерная энергетика. – 2023. – №2. – С. 148–161.
- ВАНЬКОВ А.А., ВОРОПАЕВ А.И., ЮРОВА Л.Н. Анализ реакторно-физического эксперимента. – М.: Атомиздат, 1977. – 88 с.
- МАНТУРОВ Г.Н. Методическое – константное и про-граммное обеспечение нейтронно-физических расчетов быстрых реакторов и оценки погрешностей расчетных предсказаний. – Дисс. д-ра тех. наук. –М.: НИЦ «КИ», 2017. – 202 с.
- УСАЧЕВ Л.Н., БОБКОВ Ю.Г. Теория возмущений и пла-нирование эксперимента в проблеме ядерных данных для реакторов. – М.: Атомиздат, 1980. – 88 c.
- ХУДСОН Д. Статистика для физиков. – М.: Мир, 1970. – 295 с.
- Assessment of Existing Nuclear Data Adjustment Methodolo-gies (2011) Working Party on International Evaluation Co-Operation // Intermediate Report of the WPEC Subgroup 33. Report/NEA/OECD. Paris, 152 pp.
- CACUCI D.G., BUJOR M. Sensitivity and uncertainty anal-ysis, data assimilation, and predictive best-estimate model calibration // Handbook of Nuclear Engineering. Springer, Boston. – 2010. – DOI: https://doi.org/10.1007/978-0-387-98149-9_17 (дата обращения: 18.03.2023).
- NEA (2010) Covariance Data in the Fast Neutron Region // Final report of WPEC subgroup 24, NEA/NSC/WPEC/DOC(2010)427, OECD, Paris.
- GRECHANUK P., RISING M.E., PALMER T.S. Using ma-chine learning methods to predict bias in nuclear criticality safety // Journal of Computational and Theoretical Transport. – 2019. – Vol. 47. – P. 552–565.
- HOEFER A., BUSS O. Assessing and improving model fit-ness in MOCABA data assimilation // Ann. Nucl. Energy. – 2021. – Vol. 162. – P. 10–21.
- IVANOV E., SAINT-JEAN C., SOBES V. Nuclear data as-similation, scientific basis and current status // EPJ Nuclear Sci. Technol. – 2021. – DOI: https://doi.org/10.1051/epjn/2021008 (дата обращения: 18.03.2023).
- NEA (2013) Methods and Issues for the Combined Use of Integral Experiments and Covariance Data // A report by the Working Party on International Nuclear Data Evaluation Co-operation of the NEA Nuclear Science Committee, NEA/NSC/WPEC/DOC(2013)445, OECD, Paris.
- NEA/NSC/R (2016) 6 (2017) Methods and Approaches to Provide Feedback from Nuclear and Covariance Data Ad-justment for Improvement of Nuclear Data Files // Intermedi-ate Report. Nuclear Science NEA/OECD. Paris. – 43 p.
- PALMIOTTI G., SALVATORES M. The role of experiments and of sensitivity analysis in simulation validation strategies with emphasis on reactor physics // Ann. Nucl. Energy. – 2013. – Vol. 52. – P. 10–21.
- DRAGT J.B. Statistical considerations on techniques for ad-justment // RCN-122. – Reactor Centrum Nederland. – 1970. – P. 85–105.
- ROCHMAN D., SCIOLLA C.M. Nuclear data uncertainty propagation for a typical PWR fuel assembly with burnup // Nuclear Engineering and Technology. – 2014. – Vol. 46, No. 3. – P. 353–362.
- ROWLANDS J.L., MACDOUGALL L.D. The use of integral measurements to adjust cross-sections and predicted reactor properties // Proc. of the Int. Conf. on Fast Critical Experi-ments and their Analysis. – ANL-7320. – 1966.
- SIEFMAN D., HURSIN M., ROCHMAN D. et.al. Stochastic vs. sensitivity-based integral parameter and nuclear data adjustments // Eur. Phys. J. Plus. – 2018. – Vol. 133, No. 12. – P. 429–438.
补充文件
