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Aerospace Nuclear Science & Technology
Organized to promote the advancement of knowledge in the use of nuclear science and technologies in the aerospace application. Specialized nuclear-based technologies and applications are needed to advance the state-of-the-art in aerospace design, engineering and operations to explore planetary bodies in our solar system and beyond, plus enhance the safety of air travel, especially high speed air travel. Areas of interest will include but are not limited to the creation of nuclear-based power and propulsion systems, multifunctional materials to protect humans and electronic components from atmospheric, space, and nuclear power system radiation, human factor strategies for the safety and reliable operation of nuclear power and propulsion plants by non-specialized personnel and more.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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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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New laws offer nuclear industry incentives for existing power plant uprates
This year, the U.S. nuclear industry received a much-needed economic boost that could help preserve operating nuclear power plants and incentivize upgrades that extend their lifespan and power output.
Signed into law in 2022, the Inflation Reduction Act offers production tax credits (PTCs) for existing nuclear power plants and either PTCs or investment tax credits (ITCs) for new carbon-free generation. These credits could make power uprates—increasing the maximum power level at which a commercial plant may operate—a much more appealing option for utilities.
Laurian Dinca, Tunc Aldemir
Nuclear Science and Engineering | Volume 127 | Number 2 | October 1997 | Pages 199-219
Technical Paper | doi.org/10.13182/NSE97-A28597
Articles are hosted by Taylor and Francis Online.
A model-based parameter estimation method for nonlinear systems that does not require the linearization of the system equations and that can account for uncertainties in the monitored data as well as the parameters (e.g., random variations) is described. The method is particularly suitable for fault diagnosis because of its capability to assign probabilities of occurrence to user-specified parameter magnitude intervals that may be associated with system faults. The method regards system evolution in time as transitions between these intervals as well as user-specified magnitude intervals of the dynamic variables. These transition rates are obtained on-line from the system model and the monitored dynamic variable data and constitute a Markov chain in discrete time. The method then compares predicted and observed data at a given time step to narrow the estimated parameter range in the next time step. Implementations using a second-order van der Pol oscillator and a third-order system describing temporal xenon oscillations in a hypothetical reactor indicate that the method is computationally efficient and can be used for multiparameter estimation with incomplete information on the system state.