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Nuclear News 40 Under 40 discuss the future of nuclear
Seven members of the inaugural Nuclear News 40 Under 40 came together on March 4 to discuss the current state of nuclear energy and what the future might hold for science, industry, and the public in terms of nuclear development.
To hear more insights from this talented group of young professionals, watch the “40 Under 40 Roundtable: Perspectives from Nuclear’s Rising Stars” on the ANS website.
Alessandro Petruzzi, Dan G. Cacuci, Francesco D'Auria
Nuclear Science and Engineering | Volume 165 | Number 1 | May 2010 | Pages 45-100
Technical Paper | doi.org/10.13182/NSE09-37C
Articles are hosted by Taylor and Francis Online.
This work presents a paradigm application of a new methodology for simultaneously calibrating (adjusting) model parameters and responses, through assimilation of experimental data, to the benchmark transient thermal-hydraulic experiment IC1, performed at London's Imperial College. Following the description of the experimental setup, the corresponding mathematical model is developed and solved numerically. The sensitivities of typically important responses (e.g., temperatures, pressures) to model parameters are computed by applying both the forward and the adjoint sensitivity analysis procedures. These sensitivities not only identify the most important model parameters but also propagate, within the data assimilation procedure, parameter uncertainties for obtaining predictive best-estimate quantities, with reduced best-estimate uncertainties (i.e., “smaller” values for the variance-covariance matrices). This assimilation procedure also provides a quantitative indication of the degree of agreement between computations and experiments. In particular, the paradigm application presented in this work indicates the path for validating and calibrating thermal-hydraulic computational models used for reactor safety analyses. The concluding remarks highlight several important open issues, the resolution of which would significantly advance the area of predictive best-estimate modeling, while opening new avenues for applications in nuclear reactor engineering and safety.