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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.
Kazys K. Almenas, Yih-Yun Hsu, Marino Dimarzo, Zen-You Wang, Gary A. Pertmer, Richard Lee
Nuclear Technology | Volume 82 | Number 3 | September 1988 | Pages 341-354
Technical Paper | Heat Transfer and Fluid Flow | doi.org/10.13182/NT88-A34135
Articles are hosted by Taylor and Francis Online.
A sufficiently large data base of repeated integral thermal-hydraulic loop tests has been accumulated recently from which generalized conclusions can be drawn. Evidence obtained from experiments performed in the University of Maryland College Park (UMCP) loop show that qualitative as well as quantitative differences exist between integral and separate effect tests. For separate effect tests, flow conditions are controlled continuously and usually steady (or quasi-steady) states are of interest. Integral facilities are “closed” systems and reactor safety oriented investigations center on transient behavior for which only initial conditions can be specified. It is shown that integral flow systems have a generic capability of amplifying (or damping) small perturbations and usually can operate in one of several possible alternate flow states. These characteristics can lead to two distributions of interexperiment variations; the differences can follow a Gaussian distribution or a bifurcation. In the UMCP test program, several examples of repeat experiments whose trajectories fall outside a Gaussian distribution were observed. Such experimental results have implications for the planning of experimental test programs and for the verification process of computational models.