scholarly journals Comparison of methods for uncertainty analysis of nuclear-power-plant safety-system fault-tree models. [PWR; BWR]

1983 ◽  
Author(s):  
H Martz ◽  
R Beckman ◽  
K Campbell ◽  
D Whiteman ◽  
J Booker
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Uncertainty Analysis ◽  
Nuclear Power ◽  
Fault Tree ◽  
Safety System ◽  
Comparison Of Methods ◽  
Plant Safety ◽  
Tree Models ◽  
Nuclear Power Plant Safety

scholarly journals A Dialogic Perspective on Managing Knowledge Differences: Problem-Solving while Building a Nuclear Power Plant Safety System

2021 ◽  
pp. 017084062110618
Author(s):  
Chia-Yu Kou ◽  
Sarah Harvey
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Large Scale ◽  
Knowledge Integration ◽  
Safety System ◽  
Problem Situation ◽  
Plant Safety ◽  
Nuclear Power Plant Safety ◽  
Large Scale Project

To manage knowledge differences, existing research has documented two sets of practices: traversing and transcending knowledge boundaries. What research has yet to explore, however, is the dynamics through which traversing or transcending practices emerge in response to a particular problem situation. Using a qualitative, inductive study of the problem episodes encountered by groups of experts working on a large-scale project to build the safety system for a nuclear power plant, we observed that the emergence of traversing or transcending depended on how experts interpreted problems and initiated dialogues around specific problems. Our work provides insight into the condition through which knowledge integration trajectories may emerge.

An Evaluation of Nuclear Power Plant Safety Parameter Display Systems

1981 ◽  
Vol 25 (1) ◽  
pp. 110-114 ◽  
Author(s):  
David D. Woods ◽  
John A. Wise ◽  
Lewis F. Hanes
Keyword(s):  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Evaluation Tool ◽  
Training Simulator ◽  
Plant Safety ◽  
Power Plant Control ◽  
Safety Parameter ◽  
Nuclear Power Plant Safety ◽  
Display Systems

Two proposed safety parameter display systems, of the type to be required in nuclear power plant control rooms, were evaluated using a training simulator and experienced crews undergoing refresher training. A decision analysis approach was used. The discussion addresses the effectiveness of the training situation as an evaluation tool and methodological issues.

U.S. Nuclear Power Plant Performance Assessment Using the Versatile Economic Risk Tool (VERT)

2021 ◽  
Author(s):  
Jaden C. Miller ◽  
Spencer C. Ercanbrack ◽  
Chad L. Pope
Keyword(s):  
Risk Assessment ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Nuclear Power ◽  
Fault Tree ◽  
Plant Performance ◽  
Economic Risk ◽  
Reliability Data ◽  
Water Reactor ◽  
Tree Models

Abstract This paper addresses the use of a new nuclear power plant performance risk analysis tool. The new tool is called Versatile Economic Risk Tool (VERT). VERT couples Idaho National Laboratory’s SAPHIRE and RAVEN software packages. SAPHIRE is traditionally used for performing probabilistic risk assessment and RAVEN is a multi-purpose uncertainty quantification, regression analysis, probabilistic risk assessment, data analysis and model optimization software framework. Using fault tree models, degradation models, reliability data, and economic information, VERT can assess relative system performance risks as a function of time. Risk can be quantified in megawatt hours (MWh) which can be converted to dollars. To demonstrate the value of VERT, generic pressurized water reactor and boiling water reactor fault tree models were developed along with time dependent reliability data to investigate the plant systems, structures, and components that impacted performance from the year 1980 to 2020. The results confirm the overall notion that US nuclear power plant industry operational performance has been improving since 1980. More importantly, the results identify equipment that negatively or positively impact performance. Thus, using VERT, individual plant operators can target systems, structures, and components that merit greater attention from a performance perspective.

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