15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022最新文献

Zr Nuclear Data Campaign: Measurement of 90Zr(n,γ) cross section [Slides] Zr核数据运动:90Zr(n，γ)截面的测量[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-28 DOI: 10.2172/1901527

Jesse M. Brown, K. Guber, C. Paradela, P. Schillebeeckx, S. Kopecky

引用次数: 0

Advanced Modeling and Simulations for Evaluation of Thermal Neutron Scattering Materials [Slides] 热中子散射材料评价的先进建模与仿真[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-28 DOI: 10.2172/1900247

C. Chapman, G. Arbanas, Jesse M. Brown, K. Ramić, Yongqiang Cheng, Jiao Y. Y. Lin, D. Abernathy, Alexander Kolesnikov, Matthew Stone, L. Daemen, Anibal Cuesta, Xunxiang Hu

引用次数: 0

Recent Developments in the Nuclear Data Processing Code AMPX [Slides] 核数据处理代码AMPX的最新发展[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-28 DOI: 10.2172/1901554

J. McDonnell, Jesse M. Brown, C. Chapman, D. Wiarda, A. Holcomb

引用次数: 0

Open-source release of CGMF 1.1 and Integration into the MCNP6.3® Code [Slides] CGMF 1.1的开源发布和集成到MCNP6.3®代码中[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-28 DOI: 10.2172/1898322

M. Rising, P. Talou, I. Stetcu, P. Jaffke, A. Lovell, T. Kawano

引用次数: 0

Experiments for validation of TSL evaluations [Slides] 验证TSL评价的实验[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-28 DOI: 10.2172/1902618

Y. Danon, D. Fritz, Benjamin Wang, K. Cook, Sukhjinder Singh, A. Ney, P. Brain, M. Rapp, A. Daskalakis, D. Barry, T. Trumbull, C. Chapman, G. Arbanas

引用次数: 0

How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data? [Slides] 一组不同的积分和半积分测量如何为鉴别核数据差异提供信息?(幻灯片)

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-27 DOI: 10.2172/1898082

A. Clark

{"title":"How can a diverse set of integral and semi-integral measurements inform identification of discrepant nuclear data? [Slides]","authors":"A. Clark","doi":"10.2172/1898082","DOIUrl":"https://doi.org/10.2172/1898082","url":null,"abstract":"Nuclear data are used for a variety of applications, including criticality safety, reactor performance, and material safeguards. Despite the breadth of use-cases, the effective neutron multiplication factor, keff, of ICSBEP critical assemblies are primarily used for nuclear data validation; these are sensitive to specific energy regions and nuclides and are unable to uniquely constrain nuclear data. As a consequence, general-purpose nuclear data libraries, such as ENDF/B-VIII.0 [1], may have deficiencies that, while not apparent in criticality applications, negatively impact other applications, such as non-destructive analysis of special nuclear material [2, 3] and neutron diagnosed subcritical experiments [4].\u0000Recent work by the Experiments Underpinned by Computational Learning for Improvements in Nuclear Data (EUCLID) project developed a machine learning tool, RAFIEKI, which uses random forests and the SHAP metric to determine which nuclear data contribute most to predicted bias between measured and simulated responses (e.g. keff). This paper contrasts RAFIEKI analysis applied to keff only against RAFIEKI analysis with keff paired with either LLNL pulsed sphere measurements or subcritical benchmarks. Two examples show that a) including pulsed sphere measurements substantially increases 9Be nuclear data importance to bias between 2 and 15 MeV, and b) including subcritical benchmarks has the potential for disentangling compensating errors between 240Pu (n,el) and (n,il) cross-sections between 0.1 and 10 MeV. These results show that RAFIEKI analysis applied to response sets that include, but go beyond, keff can aid nuclear data evaluators in identifying issues in nuclear data.","PeriodicalId":405872,"journal":{"name":"15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128527765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Comparison of URR Implementations in GNDS Format [Slides] GNDS格式URR的实施比较[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-27 DOI: 10.2172/1898111

M. Descalle, C. Mattoon, B. Beck, G. Gert, David Brown, Matteo Verabbi

引用次数: 0

Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters [Slides] 基于非侵入式蒙特卡罗灵敏度分析的数据同化反应器动力学参数[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-27 DOI: 10.2172/1898325

N. Kleedtke, J. Hutchinson, T. Cutler, I. Michaud, M. Rising, M. Hua, J. Alwin, M. Grosskopf, S. V. Vander Wiel, D. Neudecker, N. Thompson

{"title":"Data Assimilation using Non-invasive Monte Carlo Sensitivity Analysis of Reactor Kinetics Parameters [Slides]","authors":"N. Kleedtke, J. Hutchinson, T. Cutler, I. Michaud, M. Rising, M. Hua, J. Alwin, M. Grosskopf, S. V. Vander Wiel, D. Neudecker, N. Thompson","doi":"10.2172/1898325","DOIUrl":"https://doi.org/10.2172/1898325","url":null,"abstract":"Accurately predicting the criticality of an experiment before interacting with the experimental components is very important for criticality safety. Radiation transport software can be utilized to calculate the effective neutron multiplication factor of a nuclear system. Because of the integral nature of the effective neutron multiplication factor, the value calculated contains various sources of nuclear-data induced uncertainty. The sensitivity analysis and data assimilation technique presented in this paper exhibit one possible method of identifying and reducing the effective neutron multiplication factor nuclear-data induced uncertainty. The results presented in this work show that it is possible to use relative sensitivity coefficients of the prompt neutron decay constant and the effective delayed neutron fraction to 239Pu nuclear data to reduce nuclear-data induced uncertainties in the effective neutron ultiplication factor. This work has been utilized by members of the Los Alamos National Laboratory project EUCLID (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) for optimally designing a new experiment, which will be used to reduce compensating errors in 239Pu nuclear data.","PeriodicalId":405872,"journal":{"name":"15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122651625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

EUCLID: A New Approach to Improve Nuclear Data Coupling Optimized Experiments with Validation using Machine Learning [Slides] EUCLID:利用机器学习改进核数据耦合优化实验的新方法[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-27 DOI: 10.2172/1898108

J. Hutchinson, J. Alwin, A. Clark, T. Cutler, M. Grosskopf, W. Haeck, M. Herman, N. Kleedtke, J. Lamproe, R. Little, I. Michaud, D. Neudecker, M. Rising, T. Smith, N. Thompson, S. V. Vander Wiel

引用次数: 6

Modernization efforts for the R-Matrix code SAMMY [Slides] r -矩阵代码SAMMY的现代化工作[幻灯片]

15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022 Pub Date : 2022-07-26 DOI: 10.2172/1900408

D. Wiarda, G. Arbanas, Jesse M. Brown, A. Holcomb, M. Pigni, J. McDonnell, C. Chapman

{"title":"Modernization efforts for the R-Matrix code SAMMY [Slides]","authors":"D. Wiarda, G. Arbanas, Jesse M. Brown, A. Holcomb, M. Pigni, J. McDonnell, C. Chapman","doi":"10.2172/1900408","DOIUrl":"https://doi.org/10.2172/1900408","url":null,"abstract":"The R-Matrix code SAMMY [1] is a widely used nuclear data evaluation code focused on the resolved range, which includes corrections for experimental effects. The code is still mostly written in FORTRAN 77 and uses a memory management system suitable for the time of its initial writing in 1984. A modernization effort is underway to update the code to modern software development practices. A continuous-integration testing framework was added to automate the large existing set of test cases. Improvements in memory management were implemented to make the code easier to maintain and enable enhancements. The resonance parameters and covariance information are now stored in C++ objects shared by SAMMY and AMPX [2], which is the processing code that generates nuclear data libraries for SCALE [3]. Further plans include switching to the Evaluated Nuclear Data File (ENDF) reading and writing routines in AMPX because these routines are more robust, easier to maintain, and support more features. Support for the new Generalized Nuclear Database Structure (GNDS) format [4] is also of interest. GNDS will share not only the resonance parameters but also the parameters associated with experimental correction in GNDS. The data are currently available in a binary SAMMY format, and the ability to export them to GNDS would make them more widely available and shareable. The next step will be to use the same resonance processing code at 0K in AMPX and SAMMY as an available formalism. Then, any improvements in the formalism can immediately be tested in SCALE because the reconstruction in AMPX will use the same cross section model. The new data library can then be used for testing using the VALID Benchmark suite [5] or other suitable benchmark suites.","PeriodicalId":405872,"journal":{"name":"15.International Conference on Nuclear Data for Science and Technology (ND2022), Held Virtually, Sacramento, CA (United States), 21-29 Jul 2022","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121901799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0