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
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!
Latest Magazine Issues
Jul 2024
Jan 2024
Latest Journal Issues
Nuclear Science and Engineering
August 2024
Nuclear Technology
Fusion Science and Technology
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.”
Hyun-Koon Kim, Seung-Hyuk Lee, Soon-Heung Chang
Nuclear Technology | Volume 101 | Number 2 | February 1993 | Pages 111-122
Technical Paper | Fission Reactor | doi.org/10.13182/NT93-A34773
Articles are hosted by Taylor and Francis Online.
A new approach for estimating the departure from nucleate boiling (DNB) performance of a pressurized water reactor core is proposed in which a neural network model is introduced to predict the DNB ratios (DNBRs) for given reactor operating conditions. This model is trained against the detailed simulation results of DNBRs obtained from optimized random input vectors that are generated by Latin hypercube sampling on a wide range of parameters. The trained network is examined to verify the generalized prediction capability of the model. The test results show that a higher level of accuracy in predicting the DNBR can be achieved with the neural network model for both steady-state and transient operating conditions. The neural network model can be developed as a viable tool for on-line DNBR estimation in a nuclear power plant.