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Remembering ANS member Gil Brown
Brown
The nuclear community is mourning the loss of Gilbert Brown, who passed away on July 11 at the age of 77 following a battle with cancer.
Brown, an American Nuclear Society Fellow and an ANS member for nearly 50 years, joined the faculty at Lowell Technological Institute—now the University of Massachusetts–Lowell—in 1973 and remained there for the rest of his career. He eventually became director of the UMass Lowell nuclear engineering program. After his retirement, he remained an emeritus professor at the university.
Sukesh Aghara, chair of the Nuclear Engineering Department Heads Organization, noted in an email to NEDHO members and others that “Gil was a relentless advocate for nuclear energy and a deeply respected member of our professional community. He was also a kind and generous friend—and one of the reasons I ended up at UMass Lowell. He served the university with great dedication. . . . Within NEDHO, Gil was a steady presence and served for many years as our treasurer. His contributions to nuclear engineering education and to this community will be dearly missed.”
Andrea Murari, Guido Vagliasindi, Sebastiano De Fiore, Eleonora Arena, Paolo Arena, Luigi Fortuna, Y. Andrew, M. Johnson, JET-EFDA Contributors
Fusion Science and Technology | Volume 58 | Number 2 | October 2010 | Pages 695-705
Selected Paper from the Sixth Fusion Data Validation Workshop 2010 (Part 1) | doi.org/10.13182/FST10-A10894
Articles are hosted by Taylor and Francis Online.
Dynamical systems are often considered immune from memory effects, i.e., the dependence of their time evolution on the previous history. This assumption has been tested for two phenomena in nuclear fusion that are believed to sometimes show sensitivity to the previous history of the discharge: disruptions and the transition from the L mode to the H mode of confinement. To this end, two neural network architectures, tapped delay lines and recurrent networks of the Elman type, have been applied to the Joint European Torus (JET) database to extract these potential memory effects from the time series of the available signals. Both architectures can detect the dependence on the previous evolution quite effectively. In the case of disruptions, only the ones triggered by locked modes seem to be influenced by the previous history of the discharge. With regard to the L-H transition, memory effects are present only in the time interval very close to the transition, whereas once the plasma has settled down in one of the two regimes, no evidence of dependence on the previous evolution has been detected.