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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.”
Simppa Äkäslompolo, Taina Kurki-Suonio, Seppo Sipilä, ASCOT Group
Fusion Science and Technology | Volume 69 | Number 3 | May 2016 | Pages 620-627
Technical Paper | doi.org/10.13182/FST15-184
Articles are hosted by Taylor and Francis Online.
Measuring fast ions, most notably fusion alphas, in ITER and future reactors remains an issue that still lacks an adequate solution. Numerical simulations are invaluable in testing the potential and limitations of various proposed diagnostics. However, the validity of the numerical tools first has to be checked against results from existing tokamaks. In this contribution, various synthetic diagnostics for fast ions (collective Thomson scattering, neutral particle analyzer, neutron camera, infrared measurements, fast ion loss detector, and activation probe) from the orbit-following Monte Carlo code ASCOT are compared to measurements from several tokamaks (ASDEX Upgrade, DIII-D, and JET). Within the limitations of the physics included in the numerical model and availability of input data from experiments, the agreement between synthetic data and measurements is found to be quite good.
