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 Nuclear Energy Conference & Expo (NECX)
August 24–27, 2026
Dallas, TX|Hilton Anatole
Latest Magazine Issues
Jul 2026
Jan 2026
2026
Latest Journal Issues
Nuclear Science and Engineering
September 2026
Nuclear Technology
August 2026
Fusion Science and Technology
Latest News
The human factor in licensing and operating the next generation of nuclear plants
As human factors specialists working at the intersection of human performance and nuclear operations, we are witnessing one of the nuclear sector’s most significant transitions in decades. The emergence of small modular reactors, microreactors, and other advanced designs is reshaping the industry’s landscape. Digital instrumentation and controls, passive safety systems, and increased automation are creating opportunities for greater safety margins and more flexible operation. These same features also fundamentally redefine what it means to “operate” a nuclear plant. Interactions among human roles, automation, and passive systems shape how people maintain awareness, exercise judgment, and intervene when necessary. These developments affect both operational realities and the regulatory foundations on which nuclear safety is built.
Roman Shaffer, Weidong He, Robert M. Edwards
Nuclear Technology | Volume 147 | Number 2 | August 2004 | Pages 240-257
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT04-A3529
Articles are hosted by Taylor and Francis Online.
Design applications for robust feedback and optimized feedforward control, with confirming results from experiments conducted on the Pennsylvania State University TRIGA reactor, are presented. The combination of feedforward and feedback control techniques complement each other in that robust control offers guaranteed closed-loop stability in the presence of uncertainties, and optimized feedforward offers an approach to achieving performance that is sometimes limited by overly conservative robust feedback control. The design approach taken in this work combines these techniques by first designing robust feedback control. Alternative methods for specifying a low-order linear model and uncertainty specifications, while seeking as much performance as possible, are discussed and evaluated. To achieve desired performance characteristics, the optimized feedforward control is then computed by using the nominal nonlinear plant model that incorporates the robust feedback control.