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 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
May 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
June 2026
Nuclear Technology
Fusion Science and Technology
Latest News
NRC proposes changes to its rules on nuclear materials
In response to Executive Order 14300, “Ordering the Reform of the Nuclear Regulatory Commission,” the NRC is proposing sweeping changes to its rules governing the use of nuclear materials that are widely used in industry, medicine, and research. The changes would amend NRC regulations for the licensing of nuclear byproduct material, some source material, and some special nuclear material.
As published in the May 18 Federal Register, the NRC is seeking public comment on this proposed rule and draft interim guidance until July 2.
R. P. Gardner, M. Mickael, K. Verghese
Nuclear Science and Engineering | Volume 98 | Number 1 | January 1988 | Pages 51-63
Technical Paper | doi.org/10.13182/NSE88-A23525
Articles are hosted by Taylor and Francis Online.
A new direction biasing approach to a target point and to finite detectors for Monte Carlo simulation is developed, presented, and tested. It properly accounts for the weight adjustments that must be made for the combined choice of a particular scattering (polar) and rotational (azimuthal) angle to obtain a given biasing angle about either a target point or a finite detector. Sample Monte Carlo simulations for a neutron transport problem with isotropic center-of-mass scattering and a gamma-ray transport problem with Klein-Nishina scattering have been done by both the analog and new direction biasing methods. The results indicate that the direction biasing approach is valid and will be very efficient for deep-penetration problems of these two types.