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Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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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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Fusion Science and Technology
Latest News
Zap Energy hits 37-million-degree electron temperatures in compact fusion device
Zap Energy announced April 23 that it has reached 1-3 keV plasma electron temperatures—roughly the equivalent of 11 to 37 million degrees Celsius—using its sheared-flow-stabilized Z-pinch approach to fusion. Reaching temperatures above that of the sun’s core (which is 10 million degrees Celsius temperature) is just one hurdle required before any fusion confinement concept can realistically pursue net gain and fusion energy.
Steven E. Aumeier, Bulent Alpay, John C. Lee, A. Ziya Akcasu
Nuclear Science and Engineering | Volume 153 | Number 2 | June 2006 | Pages 101-123
Technical Paper | doi.org/10.13182/NSE06-A2599
Articles are hosted by Taylor and Francis Online.
We present probabilistic techniques that make synergistic use of available process information for diagnosis and detection of component fault manifestation in a multicomponent system. We begin by describing the motivation for using probabilistic techniques for systems diagnostics and then define probabilistic expressions that embody the diagnostics knowledge of interest. We show that a combination of a Bayesian expression with the solution to the Chapman-Kolmogoroff equation contains the diagnostic information of interest while explicitly making use of available process information including plant data or measurements, mathematical system models, and individual component reliability data. Given these probabilistic expressions, we introduce a practical means of obtaining the necessary constituent probability density functions corresponding to feasible component transitions via an adaptive Kalman filtering formulation. To demonstrate the consolidated probabilistic technique, we consider a low-order model of a balance of plant of a boiling water reactor, represented by 11 system variables, 9 component characteristics, and 5 observations. We simulate 5 to 10% degradations in two components subject to 1% signal noise in two different transient events. Our test calculations indicate that the proposed algorithm is able to provide correct fault detection and diagnosis of the faulted components and fault magnitudes, together with a rank-ordered likelihood of the binary faults.