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Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
Can hydrogen be the transportation fuel in an otherwise nuclear economy?
Let’s face it: The global economy should be powered primarily by nuclear power. And it probably will by the end of this century, with a still-significant assist from renewables and hydro. Once nuclear systems are dominant, the costs come down to where gas is now; and when carbon emissions are reduced to a small portion of their present state, it will become obvious that most other sources are only good in niche settings. I mean, why use small modular reactors to load-follow when they can just produce that power instead of buffering it?
Stephen D. Unwin, Peter P. Lowry, Michael Y. Toyooka
Nuclear Science and Engineering | Volume 171 | Number 1 | May 2012 | Pages 69-77
Technical Paper | doi.org/10.13182/NSE11-18
Articles are hosted by Taylor and Francis Online.
Conventional probabilistic risk assessments (PRAs) are not well suited to addressing long-term reactor operations. Since passive structures and components are among those for which replacement can be least practical, they might be expected to contribute increasingly to risk in an aging plant; yet, passives receive limited treatment in PRAs. Furthermore, PRAs produce only snapshots of risk based on the assumption of time-independent component failure rates. This assumption is unlikely to be valid in aging systems. The treatment of aging passive components in PRA presents challenges. Service data to quantify component reliability models are sparse, and this is exacerbated by the greater data demands of age-dependent reliability models. Another factor is that there can be numerous potential degradation mechanisms associated with the materials and operating environment of a given component. This deepens the data problem since risk-informed management of component aging will demand an understanding of the long-term risk significance of individual degradation mechanisms. In this paper we describe a Bayesian methodology that integrates metrics of materials degradation susceptibility with available plant service data to estimate age-dependent passive component reliabilities. Integration of these models into conventional PRA will provide a basis for materials degradation management informed by predicted long-term operational risk.