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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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Proving DRACO will deliver
The United States is now closer than it has been in over five decades to launching the first nuclear thermal rocket into space, thanks to DRACO—the Demonstration Rocket for Agile Cislunar Orbit.
P. K. Sarkar, Herbert Rief
Nuclear Science and Engineering | Volume 124 | Number 2 | October 1996 | Pages 291-308
Technical Paper | doi.org/10.13182/NSE96-A28579
Articles are hosted by Taylor and Francis Online.
The amounts of change in the variance and in the efficiency of nonanalog Monte Carlo simulations for certain variations in the biasing parameters are important quantities when optimizing such simulations. Anew approach, based on the differential operator sampling technique, is outlined to estimate the derivatives of variance and efficiency with respect to the biasing parameters; the same simulation constructed to solve the primary problem is used. An algorithm requiring the first- and higher order derivatives of the natural logarithm of the second moment to predict minimum-variance-biasing parameters is presented. Equations pertaining to the algorithm are derived and solved numerically for an exponentially transformed one-group slab transmission problem for various slab thicknesses and scattering probabilities. The results indicate that optimization of nonanalog simulations can be achieved so that the present method will be useful in self-learning Monte Carlo schemes.