L. Bernstein, David A. Brown, A. Koning, B. Rearden, C. Romano, A. Sonzogni, A. Voyles, W. Younes
{"title":"Our Future Nuclear Data Needs","authors":"L. Bernstein, David A. Brown, A. Koning, B. Rearden, C. Romano, A. Sonzogni, A. Voyles, W. Younes","doi":"10.1146/ANNUREV-NUCL-101918-023708","DOIUrl":null,"url":null,"abstract":"A well-established knowledge of nuclear phenomena including fission, reaction cross sections, and structure/decay properties is critical for applications ranging from the design of new reactors to nonproliferation to the production of radioisotopes for the diagnosis and treatment of illness. However, the lack of a well-quantified, predictive theoretical capability means that most nuclear observables must be measured directly and used to calibrate empirical models, which in turn provide the data needed for these applications. In many cases, either there is a lack of data needed to guide the models or the results of the different measurements are discrepant, leading to the development of evaluation methodologies to provide recommended values and uncertainties. In this review, we describe the nuclear data evaluation process and the international community that carries it out. We then discuss new measurements and improved theory and/or modeling needed to address future challenges in applied nuclear science.","PeriodicalId":8090,"journal":{"name":"Annual Review of Nuclear and Particle Science","volume":" ","pages":""},"PeriodicalIF":9.1000,"publicationDate":"2019-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1146/ANNUREV-NUCL-101918-023708","citationCount":"40","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annual Review of Nuclear and Particle Science","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1146/ANNUREV-NUCL-101918-023708","RegionNum":2,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, NUCLEAR","Score":null,"Total":0}
引用次数: 40
Abstract
A well-established knowledge of nuclear phenomena including fission, reaction cross sections, and structure/decay properties is critical for applications ranging from the design of new reactors to nonproliferation to the production of radioisotopes for the diagnosis and treatment of illness. However, the lack of a well-quantified, predictive theoretical capability means that most nuclear observables must be measured directly and used to calibrate empirical models, which in turn provide the data needed for these applications. In many cases, either there is a lack of data needed to guide the models or the results of the different measurements are discrepant, leading to the development of evaluation methodologies to provide recommended values and uncertainties. In this review, we describe the nuclear data evaluation process and the international community that carries it out. We then discuss new measurements and improved theory and/or modeling needed to address future challenges in applied nuclear science.
期刊介绍:
The Annual Review of Nuclear and Particle Science is a publication that has been available since 1952. It focuses on various aspects of nuclear and particle science, including both theoretical and experimental developments. The journal covers topics such as nuclear structure, heavy ion interactions, oscillations observed in solar and atmospheric neutrinos, the physics of heavy quarks, the impact of particle and nuclear physics on astroparticle physics, and recent advancements in accelerator design and instrumentation.
One significant recent change in the journal is the conversion of its current volume from gated to open access. This conversion was made possible through Annual Reviews' Subscribe to Open program. As a result, all articles published in the current volume are now freely available to the public under a CC BY license. This change allows for greater accessibility and dissemination of research in the field of nuclear and particle science.