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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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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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Deep Space: The new frontier of radiation controls
In commercial nuclear power, there has always been a deliberate tension between the regulator and the utility owner. The regulator fundamentally exists to protect the worker, and the utility, to make a profit. It is a win-win balance.
From the U.S. nuclear industry has emerged a brilliantly successful occupational nuclear safety record—largely the result of an ALARA (as low as reasonably achievable) process that has driven exposure rates down to what only a decade ago would have been considered unthinkable. In the U.S. nuclear industry, the system has accomplished an excellent, nearly seamless process that succeeds to the benefit of both employee and utility owner.
Luv Sharma, Tunc Aldemir, Robert Parker
Nuclear Technology | Volume 169 | Number 1 | January 2010 | Pages 18-33
Technical Paper | Reactor Safety | doi.org/10.13182/NT10-A9340
Articles are hosted by Taylor and Francis Online.
In the simulation of nuclear plant behavior through system codes, there are often uncertainties associated with the large number of model parameters required as code inputs. The use of the Taguchi method is investigated for the importance ranking of uncertainties when a single metric is used to characterize system performance. The proposed procedure is illustrated on a simplified boiling water reactor (BWR) model to determine the dominant parameters affecting the maximum limit cycle amplitude (MLCA) in BWRs. A reduced-order BWR model is used for the analysis. A regression model is also generated to predict the MLCA as a function of the parameter values in their assumed uncertainty regions. The results indicate that (a) 7 out of the 11 parameters (factors) under consideration have a significant impact on the MLCA, (b) a linear regression model can be constructed to predict the MLCA with 88% confidence, (c) higher-order effects of the control factors are negligible, and, (d) cross effects between the factors are negligible compared to their individual effects. The results also indicate that the use of the Taguchi method leads to a 99.4% reduction in the computational effort over a full factorial experiment design. The use of the Taguchi method is not proposed to replace the well-established conventional methods for sensitivity and uncertainty analysis but rather to assist them in the selection of the parameters that may require more detailed analysis.
