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Human Factors, Instrumentation & Controls
Improving task performance, system reliability, system and personnel safety, efficiency, and effectiveness are the division's main objectives. Its major areas of interest include task design, procedures, training, instrument and control layout and placement, stress control, anthropometrics, psychological input, and motivation.
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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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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NRC cuts fees by 50 percent for advanced reactor applicants
The Nuclear Regulatory Commission has announced it has amended regulations for the licensing, inspection, special projects, and annual fees it will charge applicants and licensees for fiscal year 2025.
C. K. Sanathanan, J. C. Carter, L. T. Bryant, L. W. Amiot
Nuclear Science and Engineering | Volume 28 | Number 1 | April 1967 | Pages 82-92
Technical Paper | doi.org/10.13182/NSE67-A18670
Articles are hosted by Taylor and Francis Online.
The use of a hybrid computer results in an efficient method of analyzing the transience in high-performance nuclear reactor cores using ceramic fuels such as UO2. The nature of the space dependence of the variables is such that a great deal of multiplexing of computer components is possible. Asa consequence of multiplexing, an iterative procedure is necessary to obtain the closed-loop system response for a finite (but arbitrary) interval of time. A mathematical proof of the uniform convergence of the iterative process has been obtained. This proof is based on the principle of contraction mapping. The economy which may be realized in computer equipment and programming effort for this area of system analysis is discussed with illustrative examples. The computing techniques developed are applicable to the analysis of any nonlinear feedback control system.