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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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International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver Downtown
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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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Dragonfly, a Pu-fueled drone heading to Titan, gets key NASA approval
Curiosity landed on Mars sporting a radioisotope thermoelectric generator (RTG) in 2012, and a second NASA rover, Perseverance, landed in 2021. Both are still rolling across the red planet in the name of science. Another exploratory craft with a similar plutonium-238–fueled RTG but a very different mission—to fly between multiple test sites on Titan, Saturn’s largest moon—recently got one step closer to deployment.
On April 25, NASA and the Johns Hopkins University Applied Physics Laboratory (APL) announced that the Dragonfly mission to Saturn’s icy moon passed its critical design review. “Passing this mission milestone means that Dragonfly’s mission design, fabrication, integration, and test plans are all approved, and the mission can now turn its attention to the construction of the spacecraft itself,” according to NASA.
Yuichi Niibori, Joonhong Ahn, Hitoshi Mimura
Nuclear Technology | Volume 175 | Number 3 | September 2011 | Pages 641-651
Technical Paper | NURETH-13 Special / Radioactive Waste Management and Disposal | doi.org/10.13182/NT11-A12512
Articles are hosted by Taylor and Francis Online.
Relative permeability kr is a practical tool to describe two-phase flow in the performance assessment of a geological disposal system of radioactive waste. So far, to avoid thermal alteration of an engineered barrier system such as bentonite, the maximum temperature in the conceptual design of a Japanese geological disposal system has been limited to <373 K. However, for a limited time period, even if the temperature exceeds 373 K or the boiling point at the underground level, the robustness of the system is expected to be sufficient. An upward revision of the permissible maximum temperature would reduce the total space of the repository and would result in more effective use of the space. Therefore, when two-phase flow is also considered, a more reliable estimate of the thermal impact on the repository system is needed.In general, the fluid flow velocities of two phases are described by Darcy's law including the relative permeabilities defined as the functions of liquid-water saturation (or steam saturation), e.g., Corey's equations. However, such saturation (e.g., liquid-water saturation Sw) is not always uniformly distributed in the grid cells of the numerical implementation. In this study, the uncertainty of kr due to the distribution of Sw was examined by using various kinds of probability density functions (pdf's). The results suggest that the apparent kr value can be numerically described by the arithmetic mean, the standard deviation, and the skewness of Sw. (In other words, the apparent value of kr does not depend on the types of pdf's.) Since the value of Sw is in the range of 0 to 1, the standard deviation and the skewness are limited. Therefore, the apparent values of kr also are in a limited range. Using the Lagrange multiplier method, this study examined the ranges of the kr value for each arithmetic mean of saturation Swa. Furthermore, by considering both the frequency distribution and the spatial distribution of saturation, this study quantitatively shows the degree of uncertainty of relative-permeability curves. These curves can explain the scattered data of two-phase-flow experiments.
