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.
N. Gurvitz, A. Dubi
Nuclear Science and Engineering | Volume 109 | Number 3 | November 1991 | Pages 304-318
Technical Paper | doi.org/10.13182/NSE91-A23855
Articles are hosted by Taylor and Francis Online.
The general direct statistical approach theory is analyzed for single-path cases. Through this analysis, some conclusions are reached about the optimum benefit that may be obtained with geometric splitting as a function of the number of splitting surfaces used. Also, some useful expressions are derived for predicting the optimum splitting parameters in simple cases. The predictions obtained are compared with the results of the general optimization procedure for a number of test cases, and the results of these comparative calculations are reported.
