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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.
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2027 ANS Winter Conference and Expo
October 31–November 4, 2027
Washington, DC|The Westin Washington, DC Downtown
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Latest News
Disney World should have gone nuclear
There is extra significance to the American Nuclear Society holding its annual meeting in Orlando, Florida, this past week. That’s because in 1967, the state of Florida passed a law allowing Disney World to build a nuclear power plant.
Tanay Mazumdar, Anurag Gupta
Nuclear Science and Engineering | Volume 192 | Number 2 | November 2018 | Pages 153-188
Technical Paper | doi.org/10.1080/00295639.2018.1499340
Articles are hosted by Taylor and Francis Online.
In our earlier work, a computer code based on Method of Characteristics (MOC) was developed to solve the neutron transport equation for mainly assembly-level lattice calculations with reflective and periodic boundary conditions and to some extent core-level calculation with a vacuum boundary condition. Performance of the MOC code was also demonstrated with flat and linear flux approximations. Since neutron transport calculations involve extensive computation, an attempt is made to develop an efficient numerical recipe that will reduce the computation time. First, a conventional MOC solution of the neutron transport equation is transformed into a matrix equation to apply the Krylov subspace iteration method for accelerating the solution. It is found that even in the most sophisticated and compact formats, forming the matrix equation explicitly by storing its nonzero elements requires extremely large computer memory. Hence, an alternate way to apply the Krylov iteration is demonstrated by incorporating the effect of the matrix-based approach into the solution without storing the matrix elements. This computationally viable and novel acceleration technique is used in combination with the existing formalism of flat as well as linear flux approximation to solve a number of benchmark problems. Results show significant improvement in terms of faster convergence of the solution over the conventional inner-outer iteration without compromising accuracy.