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
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!
Latest Magazine Issues
Dec 2025
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
January 2026
Nuclear Technology
December 2025
Fusion Science and Technology
November 2025
Latest News
AI at work: Southern Nuclear’s adoption of Copilot agents drives fleet forward
Southern Nuclear is leading the charge in artificial intelligence integration, with employee-developed applications driving efficiencies in maintenance, operations, safety, and performance.
The tools span all roles within the company, with thousands of documented uses throughout the fleet, including improved maintenance efficiency, risk awareness in maintenance activities, and better-informed decision-making. The data-intensive process of preparing for and executing maintenance operations is streamlined by leveraging AI to put the right information at the fingertips for maintenance leaders, planners, schedulers, engineers, and technicians.
S. K. Penny, C. D. Zerby
Nuclear Science and Engineering | Volume 10 | Number 1 | May 1961 | Pages 75-82
Technical Paper | doi.org/10.13182/NSE61-A25933
Articles are hosted by Taylor and Francis Online.
The conditional Monte Carlo method of sampling has been applied to the spatial part of the gamma-ray transport problem in an infinite medium for the purpose of evaluating its general usefulness and its applicability to deep penetration problems. A simplified derivation of the application is presented, and the results of calculations for a water medium and a lead medium are shown. The calculations indicate that the conditional Monte Carlo method, as used in this application and without the aid of other special techniques, gives reasonably good results in a physical deep penetration problem out to approximately 10 mean free paths penetration distance independent of the absorbing properties of the material and can be carried out to 20 mean free paths if some inaccuracy can be tolerated.