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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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2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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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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Latest News
High-temperature plumbing and advanced reactors
The use of nuclear fission power and its role in impacting climate change is hotly debated. Fission advocates argue that short-term solutions would involve the rapid deployment of Gen III+ nuclear reactors, like Vogtle-3 and -4, while long-term climate change impact would rely on the creation and implementation of Gen IV reactors, “inherently safe” reactors that use passive laws of physics and chemistry rather than active controls such as valves and pumps to operate safely. While Gen IV reactors vary in many ways, one thing unites nearly all of them: the use of exotic, high-temperature coolants. These fluids, like molten salts and liquid metals, can enable reactor engineers to design much safer nuclear reactors—ultimately because the boiling point of each fluid is extremely high. Fluids that remain liquid over large temperature ranges can provide good heat transfer through many demanding conditions, all with minimal pressurization. Although the most apparent use for these fluids is advanced fission power, they have the potential to be applied to other power generation sources such as fusion, thermal storage, solar, or high-temperature process heat.1–3
Wen Si, Jianghai Li, Xiaojin Huang (Tsinghua Univ)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 1361-1369
This paper focuses on anomaly detection for Instrumentation and Control (I&C) systems at nuclear power plants. Cybersecurity of I&C systems is significant to Nuclear Power Plants (NPPs). When the I&C systems are under cyber-attacks, not only the I&C systems themselves are sabotaged, but also the controlled physical systems may be damaged. Traditional classification-based anomaly detection models are learned from the labeled training data, including normal data instances and abnormal ones. However, during the operation of NPPs, most of the recorded data are normal whereas little abnormal data can be recorded. Therefore, the one-class classification method which assumes all the training data instances only have one class label is suitable for training the anomaly detection model of the I&C systems. A replicator neural network (RNN), as the one-class anomaly detection model, is trained by replicating the input data with one class label to the desired outputs, i.e. the target data. After the RNN training with the recorded data of normal operations, the outputs for the normal data are almost the same as the target data replicated from the inputs. Meanwhile, the outputs for the abnormal data would deviate greatly from the inputs. Therefore, the outliers significant different from normal ones will be detected by the trained RNN. The performance of the RNN-based method are evaluated on the testing datasets consisting of normal data and generated abnormal ones.