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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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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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Latest News
College students help develop waste-measuring device at Hanford
A partnership between Washington River Protection Solutions (WRPS) and Washington State University has resulted in the development of a device to measure radioactive and chemical tank waste at the Hanford Site. WRPS is the contractor at Hanford for the Department of Energy’s Office of Environmental Management.
Bart L. Sjenitzer, J. Eduard Hoogenboom
Nuclear Science and Engineering | Volume 175 | Number 1 | September 2013 | Pages 94-107
Technical Paper | doi.org/10.13182/NSE12-44
Articles are hosted by Taylor and Francis Online.
In nuclear reactor physics, deterministic and hybrid calculation methods dominate the field of transient analysis. This implies that important safety assessments are subject to many approximations, which are needed by these methods. This paper proposes the Dynamic Monte Carlo method (Dynamic MC), which solves the coupled Boltzmann and kinetic equations with exact geometry and continuous energy, using only Monte Carlo techniques.For Dynamic MC a number of new techniques are developed, e.g., precursor tracking, forced decay for precursors, and the branchless method. Also, the particle source of the simulation has to be determined differently from what is current standard Monte Carlo practice, and the simulation scheme is adapted.A few example cases are simulated, demonstrating the effectiveness of Dynamic MC. The sample cases vary from simple homogeneous systems to full fuel assemblies with an asymmetric flux profile during the transient. Since Dynamic MC is implemented in the general-purpose Monte Carlo code Tripoli, it can be applied to any geometry.