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Title: Estimation of the time for steam generator trip due to cyber intrusions

Journal Article · · Annals of Nuclear Energy
 [1];  [2];  [3];  [1];  [1];  [1];  [1]
  1. Univ. of Michigan, Ann Arbor, MI (United States)
  2. Brookhaven National Lab. (BNL), Upton, NY (United States)
  3. Idaho National Lab. (INL), Idaho Falls, ID (United States)

The time required to trip a pressurized water reactor (PWR) by inserting malicious signals into its steam generator (SG) control system has been studied using the Generic PWR (GPWR) Simulator. A semi-analytical model is developed to approximately reproduce the simulator response and understand the dynamics of the control unit. A series of two proportional-integral controllers determines control action according to preset constants, the readings from the feedwater level sensor, and those from feedwater and steam flowrate transmitters. It is observed that the most important factor that determines whether a trip will occur is how much additional water is added to or withheld from the SG over time compared to normal operating conditions. In order to determine the effects of control action on the SG, changes in mass inventory are considered. This approach models the SG water level as a function of mass inventory and has a backward temporal memory. A Python interface is developed for the GPWR framework to automatically simulate different spoofing scenarios and post-process the related data. We observe that the trip times predominantly depend on flow mismatch and/or level errors. Controller parameters, including the integral time and gain constants, either speed up or slow down the rate of progression to a trip setpoint but do not cause a trip by themselves. The reactor can trip on a high-level signal when the reading crosses above 78%, increased from its reference level of 57%, or a low-level reading when it is below 25%. The present results show roughly how long the operators would have to respond to an attack, given a specific set of spoofing signals within the issue space analyzed. Furthermore, we have generated a simple surface by fitting a combination of exponential functions to the data obtained from the GPWR Simulator. In general, trips on a low level have been observed to occur faster than those on a high level.

Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Nuclear Physics (NP)
Grant/Contract Number:
SC0012704; NE0008783
OSTI ID:
1875475
Alternate ID(s):
OSTI ID: 1860998; OSTI ID: 1895442
Report Number(s):
BNL-223107-2022-JAAM
Journal Information:
Annals of Nuclear Energy, Journal Name: Annals of Nuclear Energy Vol. 173; ISSN 0306-4549
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

References (9)

Array programming with NumPy journal September 2020
Mathematical modeling of a steam generator for sensor fault detection journal December 1988
Cyber security issues imposed on nuclear power plants journal March 2014
Large Sample Properties of Simulations Using Latin Hypercube Sampling journal May 1987
Cybersecurity Assessment Framework for Digital Interface Between Safety and Security at Nuclear Power Plants journal September 2021
Fault identification and diagnosis based on KPCA and similarity clustering for nuclear power plants journal January 2021
Cyber attack taxonomy for digital environment in nuclear power plants journal May 2020
Matplotlib: A 2D Graphics Environment journal January 2007
SciPy 1.0: fundamental algorithms for scientific computing in Python journal February 2020

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