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.
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
2022 ANS Annual Meeting
June 12–16, 2022
Anaheim, CA|Anaheim Hilton
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
Latest Journal Issues
Nuclear Science and Engineering
Fusion Science and Technology
The Atlantic: Build what we’ve already invented
“What if I told you that scientists had figured out a way to produce affordable electricity that was 99 percent safer and cleaner than coal or oil, and that this breakthrough produced even fewer emissions per gigawatt-hour than solar or wind?” That’s the question that Derek Thompson, a staff writer at The Atlantic, asks in his article, "The Forgotten Stage of Human Progress," before revealing, “The breakthrough I’m talking about is 70 years old: It’s nuclear power.”
R. Preuss, U von Toussaint
Fusion Science and Technology | Volume 69 | Number 3 | May 2016 | Pages 605-610
Technical Paper | dx.doi.org/10.13182/FST15-178
Articles are hosted by Taylor and Francis Online.
Computer codes modeling plasma-wall interactions of fusion plasmas are costly in computer power and time—the running time for a single parameter setting is easily on the order of weeks or months, not to mention the expenditure for parametric studies. We propose to exploit the already gathered results in order to predict the outcome in the high-dimensional parameter space. For this, we utilize the Gaussian process method within the Bayesian framework. Uncertainties of the predictions are provided that point the way to parameter settings of further (expensive) simulations.