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
2026 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jul 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
September 2026
Nuclear Technology
August 2026
Fusion Science and Technology
Latest News
In transition: Commercializing fusion power
Commercial fusion power is closer than ever. There are now around 30 U.S. fusion companies, several of which claim to be on track to connect to the grid as early as the 2030s.
Tokamak and laser inertial confinement approaches benefit from decades of research at facilities such as the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory and ITER, with alternative concepts including stellarator, magnetic mirror, and Z-pinch confinement also making notable progress as private and government funding for fusion increases.
Andreas Szeless, Lawrence Ruby
Nuclear Science and Engineering | Volume 45 | Number 1 | July 1971 | Pages 7-13
Technical Paper | doi.org/10.13182/NSE71-A20340
Articles are hosted by Taylor and Francis Online.
A method has been devised to calculate exactly the probability distribution of reactor neutron noise. The distribution is calculated from a complicated generating function which has been known for some time. The method depends on the success achieved in obtaining a closed-form expression for the n'th derivative of a differentiable r-fold composite function. As an application of the technique, exact probability distributions are calculated for a variety of parameters. The resultant distributions are compared with the approximative negative binomial distribution. In some cases, rather similar variances are found, where the negative binomial is not expected to be a good approximation to the exact distribution. The explanation lies in an interlacing of the exact and approximative distributions. A procedure is described for fitting an experimental distribution to the exact distribution, thereby obtaining the best values of the parameters α1 and Y1 ∞. When the negative binomial is a good approximation to the exact distribution, only the product α1 Y1 ∞ can be obtained by the fitting procedure. In such cases, a Feynman-variance experiment can be performed to determine the parameters separately.