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Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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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.
Emil Wingstedt (IFE), Olli Saarela (VTT Technical Research Centre of Finland)
Proceedings | Nuclear Plant Instrumentation, Control, and Human-Machine Interface Technolgies (NPIC&HMIT 2019) | Orlando, FL, February 9-14, 2019 | Pages 721-732
Data reconciliation is a commonly used technique for correcting random errors in measurement data in the process industry. The technique uses models describing the mutual relationships of process variables related to available measurements. These models are based on knowledge of process physics. Measurement readings are adjusted so that especially mass and energy balances described by the model match. The technique has proven effective in reducing measurement uncertainties. The paper presents a Monte Carlo study of error propagation in data reconciliation of the turbine section of a VVER 440 nuclear power plant. Uncertainties in model parameters describing turbine dry efficiencies and the quality of steam exiting the steam generators are considered in addition to measurement noise. The impact of these factors on estimated reactor thermal power is evaluated, both individually and as joint impacts. For both the measurement signals and the plant parameters, the resulting effect on the uncertainty of thermal power is lower than the 2% uncertainty for reasonable levels of added noise. These results support the use of data reconciliation for reducing the uncertainty in thermal power.