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The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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College students help develop waste measuring device at Hanford
A partnership between Washington River Protection Solutions (WRPS) and Washington State University has resulted in the development of a device to measure radioactive and chemical tank waste at the Hanford Site. WRPS is the contractor at Hanford for the Department of Energy’s Office of Environmental Management.
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.