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Division Spotlight
Robotics & Remote Systems
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.
Meeting Spotlight
2027 ANS Winter Conference and Expo
October 31–November 4, 2027
Washington, DC|The Westin Washington, DC Downtown
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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November 2024
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Gail H. Marcus—ANS member since 1973
I like to say that I ended up at Massachusetts Institute of Technology because of my father. He saw that I seemed intimidated by the prospect of going there, so he dared me, figuring I would take the bait. And I did.
I graduated with a bachelor’s and master’s in physics in 1968, and two days later I married my classmate, Mike Marcus. After a summer at Ft. Monmouth, where I studied radiation damage to semiconductors, we spent the next few years back at MIT in grad school—Mike in electrical engineering and I in nuclear engineering. It was Mike who steered me toward nuclear engineering, noting that my interest was radiation damage to materials, and the nuclear engineering department was doing more of that than the physics department.
D. Rochman, W. Zwermann, S. C. van der Marck, A. J. Koning, H. Sjöstrand, P. Helgesson, B. Krzykacz-Hausmann
Nuclear Science and Engineering | Volume 177 | Number 3 | July 2014 | Pages 337-349
Technical Paper | doi.org/10.13182/NSE13-32
Articles are hosted by Taylor and Francis Online.
A new and faster Total Monte Carlo (TMC) method for the propagation of nuclear data uncertainties in Monte Carlo nuclear simulations is presented (the fast TMC method). It addresses the main drawback of the original TMC method, namely, the necessary large time multiplication factor compared to a single calculation. With this new method, Monte Carlo simulations can now be accompanied with an uncertainty propagation (other than statistical), with small additional calculation time. The fast TMC method is presented and compared with the TMC and fast GRS methods for criticality and shielding benchmarks and burnup calculations. Finally, to demonstrate the efficiency of the method, uncertainties due to uncertainties in 235,238U, 239Pu, and thermal scattering nuclear data, for the local deposited power in 12.7 million cells, are calculated for a full-size reactor core.
