ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Division Spotlight
Operations & Power
Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
Standards Program
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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Nuclear Science and Engineering
February 2025
Nuclear Technology
January 2025
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Latest News
Article considers incorporation of AI into nuclear power plant operations
The potential application of artificial intelligence to the operation of nuclear power plants is explored in an article published in late December in the Washington Examiner. The article, written by energy and environment reporter Callie Patteson, presents the views of a number of experts, including Yavuz Arik, a strategic energy consultant.
Young A. Choi, Madeline Anne Feltus
Nuclear Technology | Volume 111 | Number 1 | July 1995 | Pages 115-121
Technical Note | Reactor Operation | doi.org/10.13182/NT95-A35150
Articles are hosted by Taylor and Francis Online.
Reliability-centered maintenance (RCM) methods are applied to boiling water reactor plant-specific emergency core cooling system probabilistic risk assessment (PRA) fault trees. The RCM is a technique that is system functionbased, for improving a preventive maintenance (PM) program, which is applied on a component basis. Many PM programs are based on time-directed maintenance tasks, while RCM methods focus on component condition-directed maintenance tasks. Stroke time test data for motor-operated valves (MOVs) are used to address three aspects concerning RCM: (a) to determine if MOV stroke time testing (as required by Section XI of the American Society of Mechanical Engineers Code) was useful as a condition-directed PM task; (b) to determine and compare the plant-specific MOV failure data from a broad RCM philosophy time period compared with a PM period and, also, compared with generic industry MOV failure data; and (c) to determine the effects and impact of the plant-specific MOV failure data on core damage frequency (CDF) and system unavailabilities for these emergency systems. The MOV stroke time test data from four emergency core cooling systems [i.e., highpressure coolant injection (HPCI), reactor core isolation cooling (RCIC), low-pressure core spray (LPCS), and residual heat removal/low-pressure coolant injection (RHR/ LPCI)] were gathered from Philadelphia Electric Company’s Peach Bottom Atomic Power Station Units 2 and 3 between 1980 and 1992. The analyses showed that MOV stroke time testing was not a predictor for eminent failure and should be considered as a go/no-go test. The failure data from the broad RCM philosophy showed an improvement compared with the PMperiod failure rates in the emergency core cooling system MOVs. Also, the plant-specific MOV failure rates for both maintenance philosophies were shown to be lower than the generic industry estimates. A significant decrease in CDF was found when comparing the plant-specific data with the generic data. Only a small difference in CDF was found between plant-specific RCM data compared with PM data, which can be attributed to the few number of essential MOVs modeled in the HPCI, RCIC, RHR/LPCI, and LPCS PRA fault trees.