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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
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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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.
M. Gobien, R. Guo (NWMO)
Proceedings | 16th International High-Level Radioactive Waste Management Conference (IHLRWM 2017) | Charlotte, NC, April 9-13, 2017 | Pages 255-264
The Nuclear Waste Management Organization (NWMO) is responsible for the implementation of Adaptive Phased Management, the federally-approved plan for the safe long-term management of Canada’s used nuclear fuel. Under this plan, used nuclear fuel will ultimately be placed within a deep geological repository in a suitable host rock formation.
While a site has not yet been identified, NWMO conducts safety assessment studies for hypothetical sites to inform its siting and design programs. This paper presents an overview of a probabilistic assessment completed in support of the postclosure safety assessment evaluating the most recent container and placement concept for a hypothetical crystalline rock geosphere.
The probabilistic assessment consists of Monte Carlo simulations carried out using the system model SYVAC3-CC4 in which the full range of possible parameter values for the hundreds of distributed input parameters were explored. Unlike the deterministic assessment which test specific variations of the conservative Base Case, the probabilistic assessment uses the results from thousands of simulations and allows one to draw conclusions about model sensitivity as well as test the effects of inherent variability in the underlying model data.