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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!
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Powering the future: How the DOE is fueling nuclear fuel cycle research and development
As global interest in nuclear energy surges, the United States must remain at the forefront of research and development to ensure national energy security, advance nuclear technologies, and promote international cooperation on safety and nonproliferation. A crucial step in achieving this is analyzing how funding and resources are allocated to better understand how to direct future research and development. The Department of Energy has spearheaded this effort by funding hundreds of research projects across the country through the Nuclear Energy University Program (NEUP). This initiative has empowered dozens of universities to collaborate toward a nuclear-friendly future.
Thomas E. Booth
Nuclear Science and Engineering | Volume 138 | Number 1 | May 2001 | Pages 96-103
Technical Paper | doi.org/10.13182/NSE01-A2204
Articles are hosted by Taylor and Francis Online.
It is well known that zero-variance Monte Carlo solutions are possible if an exact importance function is available to bias the random walks. Geometric convergence with iteration has been demonstrated when the importance function estimated on the n'th iteration is used to bias the random walks on the n + 1st iteration, i.e., adaptive importance sampling. Note that geometric convergence with iteration may be less efficient than a nonadaptive Monte Carlo calculation if the time per iteration grows too fast. This paper shows a general method for sampling the zero-variance kernels enabling a Monte Carlo solution that converges inversely with the computer time.