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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.
Jiuwu Hui
Nuclear Technology | Volume 211 | Number 8 | August 2025 | Pages 1699-1722
Research Article | doi.org/10.1080/00295450.2024.2426410
Articles are hosted by Taylor and Francis Online.
Accurate estimation of unmeasured system states and disturbances in a pressurized water reactor (PWR) is essential for effective control, operation optimization, and safety monitoring. To this end, this paper investigates the estimation of unmeasured system states and disturbances of the PWR system during load-following operation. First, a mathematical model for the PWR system is established based on the two-point kinetics equations with one equivalent delayed neutron precursor group. Subsequently, an extended state observer (ESO) integration scheme, incorporating two coupled ESOs, is constructed to estimate unmeasured system states, including relative density of delayed neutron precursor, average fuel temperature, total reactivity, xenon concentration, and iodine concentration, along with time-varying disturbances, with the use of measurements of the PWR system only. According to the Lyapunov stability theorem, it is proved that the estimation error dynamic of the proposed ESO integration scheme is uniformly ultimately bounded stable. Finally, simulation results confirm that the proposed ESO integration scheme provides higher estimation accuracy and stronger robustness against measurement noises, model uncertainties, and external disturbances compared to both a high-gain observer and a high-order sliding mode observer.