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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
Commercial nuclear innovation "new space" age
In early 2006, a start-up company launched a small rocket from a tiny island in the Pacific. It exploded, showering the island with debris. A year later, a second launch attempt sent a rocket to space but failed to make orbit, burning up in the atmosphere. Another year brought a third attempt—and a third failure. The following month, in September 2008, the company used the last of its funds to launch a fourth rocket. It reached orbit, making history as the first privately funded liquid-fueled rocket to do so.
Anurag Gupta, R. S. Modak
Nuclear Science and Engineering | Volume 194 | Number 2 | February 2020 | Pages 87-103
Technical Paper | doi.org/10.1080/00295639.2019.1668655
Articles are hosted by Taylor and Francis Online.
Monte Carlo calculations for the evaluation of fundamental mode solution of k-eigenvalue problems generally make use of the Power Iteration (PI) method, which suffers from poor convergence, particularly in the case of large, loosely coupled systems. In the present paper, a method called Meyer’s Subspace Iteration (SSI) method, also called the Simultaneous vector iteration algorithm, is applied for the Monte Carlo solution of the k-eigenvalue problem. The SSI method is the block generalization of the single-vector PI method and has been found to work efficiently for solving the problem with the deterministic neutron transport setup. It is found that the convergence of the fundamental k-eigenvalue and corresponding fission source distribution improves substantially with the SSI-based Monte Carlo method as compared to the PI-based Monte Carlo method. To reduce the extra computational effort needed for simultaneous iterations with several vectors, a novel procedure is adopted in which it takes almost the same effort as with the single-vector PI-based Monte Carlo method. The algorithm is applied to several one-dimensional slab test cases of varying difficulty, and the results are compared with the standard PI method. It is observed that unlike the PI method, the SSI-based Monte Carlo method converges quickly and does not require many inactive generations before the mean and variance of eigenvalues could be estimated. It has been demonstrated that the SSI method can simultaneously find a set of the most dominant higher k-eigenmodes in addition to the fundamental mode solution.