ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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!
Latest Magazine Issues
Aug 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
September 2025
Nuclear Technology
August 2025
Fusion Science and Technology
Latest News
Lightbridge to test uranium-zirconium fuel alloy in INL’s ATR
Lightbridge Corporation has fabricated samples of nuclear fuel materials made of an enriched uranium-zirconium alloy, matching the composition of the alloy that the company intends to use for its future commercial Lightbridge Fuel product. The fuel is designed to improve the performance, safety, and proliferation resistance of nuclear reactors, according to the company. The enriched coupon samples will now be placed into capsules for irradiation testing in Idaho National Laboratory’s Advanced Test Reactor.
François Bachoc, Guillaume Bois, Josselin Garnier, Jean-Marc Martinez
Nuclear Science and Engineering | Volume 176 | Number 1 | January 2014 | Pages 81-97
Technical Paper | doi.org/10.13182/NSE12-55
Articles are hosted by Taylor and Francis Online.
This paper addresses the use of experimental data for calibrating a computer model and improving its predictions of the underlying physical system. A global statistical approach is proposed in which the bias between the computer model and the physical system is modeled as a realization of a Gaussian process. The application of classical statistical inference to this statistical model yields a rigorous method for calibrating the computer model and for adding to its predictions a statistical correction based on experimental data. This statistical correction can substantially improve the calibrated computer model for predicting the physical system on new experimental conditions. Furthermore, a quantification of the uncertainty of this prediction is provided. Physical expertise on the calibration parameters can also be taken into account in a Bayesian framework. Finally, the method is applied to the thermal-hydraulic code FLICA 4, in a single-phase friction model framework. It allows significant improvement of the predictions of FLICA 4.