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ANS Student Conference 2025
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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.”
D. Elbèze, D. van Houtte, E. Delchambre
Fusion Science and Technology | Volume 75 | Number 5 | July 2019 | Pages 405-411
Technical Paper | doi.org/10.1080/15361055.2019.1603534
Articles are hosted by Taylor and Francis Online.
In the Reliability, Availability, Maintainability, and Inspectability (RAMI) engineering approach used in nuclear fusion research, criticality identifies the failure modes that have the greatest impact on the availability of the studied system. Criticality is expressed as the product of the occurrence level with the severity level of failure modes. The analytical calculation shows that this formulation is equivalent to their availability provided that the duty cycle of basic functions is introduced to adjust the occurrence and the scales of occurrence and severity are homogeneous.
To consolidate the results obtained with a Reliability Block Diagram analysis, we performed a probabilistic study using an advanced Monte Carlo simulation code: the Primavera® Quantitative Schedule Risk Analysis. This method associates failure modes with conditional activities in a schedule and provides the density distribution of failures and tornado graphs to identify the highest criticality failures.
Statistical tests were performed for two operational systems, and we showed that the criticality evaluated with the RAMI approach was in good agreement with the results of the other methods. Thus, in many cases, the analytical formulas can be used during the Failure Mode, Effects, and Criticality Analysis to quickly assess availability by using a spreadsheet.