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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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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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ANS Standards Committee publishes joint ASME/ANS standard for Level 1/large early release frequency PRA
ANSI/ASME/ANS RA-S-1.1-2024, Standard for Level 1/Large Early Release Frequency Probabilistic Risk Assessment for Nuclear Power Plant Applications, has been published by the American Nuclear Society. The document, which is a joint standard developed with the American Society of Mechanical Engineers by the ANS/ASME Joint Committee on Nuclear Risk Management, received the approval of the American National Standards Institute on February 29, 2024, and was issued on March 15, 2024.
P. D. Vaswani, P. K. Tamboli, Debraj Chakraborty
Nuclear Technology | Volume 210 | Number 1 | January 2024 | Pages 126-136
Research Article | doi.org/10.1080/00295450.2023.2214662
Articles are hosted by Taylor and Francis Online.
This paper considers an optimized full state feedback (FSF) optimal controller for bulk power control of a 700-MW(electric) pressurized heavy water reactor (PHWR) that minimizes the controller norm to reduce the effect of disturbances. Lyapunov’s linear matrix inequalities (LMIs) have been considered for stability of the model. For the closed loop, these inequalities, which become nonlinear in the unknowns, are converted to LMIs by a suitable variable substitution. The controller’s optimization is achieved by minimizing the upper bound of the state feedback vector’s norm. As a result of this optimization, the controller gain is reduced, which reduces the effect of the disturbance input to the system. We study the stability of the closed loop system and the nonlinear transient performance using the state feedback. We demonstrate that the proposed controller’s transient performance is superior to that of a nonoptimized controller when compared to a conventional proportional-derivative controller. The designed controller has a norm that is about five orders lower than that obtained without optimization while still providing acceptable transient performance.