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Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
Standards Program
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.
S. I. Chang, T. W. Kerlin
Nuclear Science and Engineering | Volume 64 | Number 2 | October 1977 | Pages 673-683
Technical Paper | doi.org/10.13182/NSE77-A27399
Articles are hosted by Taylor and Francis Online.
Large linear dynamic models for nuclear reactor systems are widely used for simulation and control system design. It is important to be able to verify these models and the parameters in them. Existing parameter identification techniques are very time consuming for use with large systems. In this study, identification is achieved by an optimization procedure that adjusts system parameters to minimize differences between experimental frequency responses and theoretical frequency responses obtained from the dynamic model. A new method that uses a partitioned martrix technique was developed. This technique constitutes a very efficient analysis algorithm for large models when implemented on the digital computer. The work included a study of methods for assessing the identifiability of parameters by fitting dynamic test data. The Fisher information matrix was found to be useful for this purpose. It was also found that the frequency dependency of the sensitivity function is important in determining identifiability. The measurements should include frequencies where the sensitivity to the parameter of interest is largest. Also, it was found that separate, unique identification of parameters with parallel curves of sensitivity versus frequency is impossible regardless of how large the magnitudes of the sensitivities are. The method was demonstrated in a test case. It used data (from the Oconee I pressurized water reactor) and a 29th-order model. The results demonstrated that the computational requirements are reasonable for large systems and that the procedure can identify parameters if all the necessary conditions are satisfied. In general, the work has provided a systematic method for parameter identification in systems described by large linear dynamic models.