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
Mar 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
April 2026
Nuclear Technology
February 2026
Fusion Science and Technology
Latest News
60 Years of U: Perspectives on resources, demand, and the evolving role of nuclear energy
Recent years have seen growing global interest in nuclear energy and rising confidence in the sector. For the first time since the early 2000s, there is renewed optimism about the industry’s future. This change is driven by several major factors: geopolitical developments that highlight the need for secure energy supplies, a stronger focus on resilient energy systems, national commitments to decarbonization, and rising demand for clean and reliable electricity.
Arvind Sundaram, Hany Abdel-Khalik
Nuclear Technology | Volume 207 | Number 8 | August 2021 | Pages 1163-1181
Technical Paper | doi.org/10.1080/00295450.2020.1812349
Articles are hosted by Taylor and Francis Online.
Can predictive models develop cognizance or awareness of how they have been used? Can models detect if they are being manipulated or executed in nonauthorized manners? Can a software track information propagation through its subroutines to improve execution efficiency? Can this be achieved in a covert manner, i.e., avoiding the use of additional variables, additional lines of code, and conventional logging files, and instead rely directly on the physics being simulated to develop the required cognizance? Achieving these goals under the looming threat of insiders is considered an open challenging problem. This paper introduces a new modeling paradigm to covertly develop cognizance that is of critical value when predictive software is used in both adversarial and nonadversarial settings. Given the wide range of applications possible with this new modeling paradigm, the paper will focus on introducing the mathematical theory and limit the initial demonstration to a physics-based model of a nuclear reactor. This model describes a representative industrial control system of a nuclear reactor model containing two coupled subsystems: a heat-producing core and a steam generator. The goal is to demonstrate how each subsystem physics model can remain cognizant of the state of the subsystem. The proposed methodology will provide communication solutions for future reactor technologies to enable advanced reactor control and remote reactor operations.