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Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
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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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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.
Svein Sunde, Øivind Berg, Lennart Dahlberg, Nils-Olof Fridqvist
Nuclear Technology | Volume 143 | Number 2 | August 2003 | Pages 103-124
Technical Paper | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technologies | doi.org/10.13182/NT03-A3401
Articles are hosted by Taylor and Francis Online.
A mathematical model for a boiling water reactor steam-turbine cycle was assembled by means of a configurable, steady-state modeling tool TEMPO. The model was connected to live plant data and intermittently fitted to these by minimization of a weighted least-squares object function. The improvement in precision achieved by this reconciliation was assessed from quantities calculated from the model equations linearized around the minimum and from Monte Carlo simulations. It was found that the inclusion of the flow-passing characteristics of the turbines in the model equations significantly improved the precision as compared to simple mass and energy balances, whereas heat transfer calculations in feedwater heaters did not. Under the assumption of linear model equations, the quality of the fit can also be expressed as a goodness-of-fit Q. Typical values for Q were in the order of 0.9. For a validated model Q may be used as a fault detection indicator, and Q dropped to very low values in known cases of disagreement between the model and the plant state. The sensitivity of Q toward measurement faults is discussed in relation to redundancy. The results of the linearized theory and Monte Carlo simulations differed somewhat, and if a more accurate analysis is required, this is better based on the latter. In practical application of the presently employed techniques, however, assessment of uncertainties in raw data is an important prerequisite.