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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.”
P. E. Labeau, J. M. Izquierdo
Nuclear Science and Engineering | Volume 150 | Number 2 | June 2005 | Pages 115-139
Technical Paper | doi.org/10.13182/NSE05-A2506
Articles are hosted by Taylor and Francis Online.
The theory of probabilistic dynamics (TPD) offers a framework capable of modeling the interaction between the physical evolution of a system in transient conditions and the succession of branchings defining a sequence of events. Nonetheless, the Chapman-Kolmogorov equation, besides being inherently Markovian, assumes instantaneous changes in the system dynamics when a setpoint is crossed. In actuality, a transition between two dynamic evolution regimes of the system is a two-phase process. First, conditions corresponding to the triggering of a transition have to be met; this phase will be referred to as the activation of a "stimulus." Then, a time delay must elapse before the actual occurrence of the event causing the transition to take place. When this delay cannot be neglected and is a random quantity, the general TPD can no longer be used as such. Moreover, these delays are likely to influence the ordering of events in an accident sequence with competing situations, and the process of delineating sequences in the probabilistic safety analysis of a plant might therefore be affected in turn. This paper aims at presenting several extensions of the classical TPD, in which additional modeling capabilities are progressively introduced. A companion paper sketches a discretized approach of these problems.