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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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
NERS publishes report on machine learning and microreactors
The University of Michigan’s Department of Nuclear Engineering and Radiological Sciences (NERS) has published a summary of a study on nuclear microreactors and machine learning (ML) that was conducted by researchers from NERS and Idaho National Laboratory. The full paper, “Nuclear Microreactor Transient and Load-Following Control with Deep Reinforcement Learning,” was featured in the July issue of Energy Conversion and Management: X.
T. W. Kerlin, G. C. Zwingelstein, B. R. Upadhyaya
Nuclear Technology | Volume 36 | Number 1 | November 1977 | Pages 7-38
Technical Paper | Critical Review | doi.org/10.13182/NT77-A31954
Articles are hosted by Taylor and Francis Online.
A great deal of information about a nuclear power plant and the coefficients that describe it is contained in the data that can be collected in plant transients. Much of this information is difficult or impossible to obtain from steady-state measurements. Significant advances have been made in developing techniques to extract the desired performance-related or safety-related information from transient data records. Techniques are available for determining such specific design parameters as reactivity feedback coefficients or heat transfer coefficients. Models, either derived from physical principles or developed empirically, can be tuned by comparison with plant data, and they are capable of very accurate predictions of plant responses to disturbances. Efficient methods, with on-line computing capability, can track performance-related parameters to yield information on plant conditions for surveillance purposes. Methods such as these provide expanded capability for extracting useful information from operating plants.