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The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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General Kenneth Nichols and the Manhattan Project
Nichols
The Oak Ridger has published the latest in a series of articles about General Kenneth D. Nichols, the Manhattan Project, and the 1954 Atomic Energy Act. The series has been produced by Nichols’ grandniece Barbara Rogers Scollin and Oak Ridge (Tenn.) city historian David Ray Smith. Gen. Nichols (1907–2000) was the district engineer for the Manhattan Engineer District during the Manhattan Project.
As Smith and Scollin explain, Nichols “had supervision of the research and development connected with, and the design, construction, and operation of, all plants required to produce plutonium-239 and uranium-235, including the construction of the towns of Oak Ridge, Tennessee, and Richland, Washington. The responsibility of his position was massive as he oversaw a workforce of both military and civilian personnel of approximately 125,000; his Oak Ridge office became the center of the wartime atomic energy’s activities.”
Fan Li, Belle R. Upadhyaya
Nuclear Technology | Volume 173 | Number 1 | January 2011 | Pages 17-25
Technical Paper | NPIC&HMIT Special / Nuclear Plant Operations and Control | doi.org/10.13182/NT11-A11480
Articles are hosted by Taylor and Francis Online.
Fault diagnosis is an important area in the nuclear industry for effective and continuous operation of power plants. All the approaches for fault diagnosis depend critically on the sensors that measure important process variables in the system. The locations of these sensors determine the effectiveness of the diagnostic methods. However, the emphasis of most fault diagnosis approaches is primarily on procedures to perform fault detection and isolation (FDI) given a set of sensors. Little attention has been given to the actual allocation of sensors for achieving efficient FDI performance. A graph-based approach, the directed graph (DG), is proposed in this paper as a solution for the optimization of sensor locations for efficient fault identification. The application of the DG modeling in deciding the locations of sensors based on the concepts of observability and fault resolution is introduced. A reliability maximization-based optimization framework for sensor placement from a fault diagnosis perspective is described. The helical coil steam generator unit of the International Reactor Innovative and Secure system is outlined to underscore the utility of the algorithms for large systems.