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
Jan 2026
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.
Federico Di Rocco, Dan G. Cacuci, Madalina C. Badea
Nuclear Science and Engineering | Volume 185 | Number 3 | March 2017 | Pages 549-603
Technical Paper | doi.org/10.1080/00295639.2017.1279943
Articles are hosted by Taylor and Francis Online.
This paper provides the results of the adjoint sensitivity model developed in the accompanying Part I for a natural draft counter-flow cooling tower. The selected responses are (1) outlet air temperature, (2) outlet water temperature, (3) outlet water mass flow rate, (4) air outlet relative humidity, and (5) air mass flow rate. Explicit expressions for the best-estimate nominal values of the model parameters and responses are also provided, together with the best-estimate reduced standard deviations of the predicted model parameters and responses. The results stemming from this work show that the PM_CMPS procedure reduces the predicted standard deviations of all responses and model parameters.