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Division Spotlight
Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
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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Latest News
Virginia utility considers SMRs
Dominion Energy Virginia has issued a request for proposals from leading nuclear companies to study the feasibility of putting a small modular reactor at its North Anna nuclear power plant.
While the utility says it is not a commitment to build an SMR at the site, the RFP is “an important first step in evaluating the technology and the North Anna site to support Dominion Energy customers’ future energy needs consistent with the company’s most recent Integrated Resource Plan.”
Eric B. Bartlett, Robert E. Uhrig
Nuclear Technology | Volume 97 | Number 3 | March 1992 | Pages 272-281
Technical Paper | Nuclear Reactor Safety | doi.org/10.13182/NT92-A34635
Articles are hosted by Taylor and Francis Online.
In this work, nuclear power plant operating status recognition is investigated using a self-optimizing stochastic learning algorithm artificial neural network (ANN) with dynamic node architecture learning. The objective is to train the ANN to classify selected nuclear power plant accident conditions and assess the potential for future success in this area. The network is trained on normal operating conditions as well as on potentially unsafe conditions based on nuclear power plant training simulator-generated accident scenarios. These scenarios include hot- and cold-leg loss of coolant, control rod ejection, total loss of off-site power, main steamline break, main feedwater line break, and steam generator tube leak accidents as well as the normal operating condition. Findings show that ANNs can be used to diagnose and classify nuclear power plant conditions with good results. Continued research work is indicated.