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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Once-Through Steam Generator Model Analysis Using Python and Advanced Optimization Tools (Summer Internship Report)

This study focuses on the parametric analysis of design parameters for a once-through steam generator (OTSG) model, using python and advanced optimization tools to facilitate applications such as the flowing autoclave steam generator (FASG) test cases. Building on previous research involving another OTSG with a different design, this project aims to enhance our understanding of how steam generators (SGs) behave and how their outputs are influenced by changes in design. The reason for this design change is to allow for more precise modeling and optimization of SG performance, to provide a comparative analysis between the two designs, and to set up the model for integration with the FASG test case. The OTSG python-model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor-type small modular reactor system. Design studies involve changing the model’s input design parameters to observe the resulting effects on the output of the system. By using advanced optimization tools, such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory, detailed design parametric studies and model optimization were performed. Six input parameters—pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid), respectively, of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10% relative changes) for 600 samples. The analysis provides valuable insights into SG optimization and can be used for sensor placement optimization to effectively monitor and obtain experimental data in other tests.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2017

Operational Efficiency Evaluation of a Setup for Removing Stresses in the Steam Header of PGV-1000 Steam Generator

The effectiveness of a setup for removing stresses in the steam header of a PGV-1000 steam generator is evaluated. The evaluation is based on an investigation of the stress state by means of magnetic anisotropy measurements performed in the zone of the No. 111 weld seam of the hot header of steam generators operating in one of the power-generating units with a V-320 series reactor arrangement. Inspections made it possible to obtain cartograms of the distribution of the difference of the principal mechanical stresses along the perimeter of the weld connection of a PGV-1000 header equipped with a cooling mantle and headers without such a mantle. By means of statistical analysis of the data, a diagram of the distribution of the principal mechanical stresses was obtained. In addition, the distribution of the standard deviation of the principal mechanical stresses as a measure of the dispersion of a random quantity relative to its mathematical expectation was determined.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Demonstration of Fully Coupled Calculations in Helical Steam Generator: Toward Predictions of Fluid Elastic Instability

The NEAMS program aims to develop an integrated multi-physics simulation capability “pellet-to-plant” for the design and analysis of future generations of nuclear power plants. In particular, the Reactor Product Line code suite's multi-resolution hierarchy is being designed to ultimately span the full range of length and time scales present in relevant reactor design and safety analyses, as well as scale from desktop to petaflop computing platforms. Flow-induced vibration (FIV) is widespread problem in energy systems because they rely on fluid movement for energy conversion. Vibrating structures may be damaged as fatigue or wear occurs. Given the importance of reliable components in the nuclear industry, flow-induced vibration has long been a major concern in safety and operation of nuclear reactors. In particular, nuclear fuel rods and steam generators have been known to suffer from flow-induced vibration and related failures. Advanced reactors, such as integral Pressurized Water Reactors (PWRs) considered for Small Modular Reactors (SMR), often rely on innovative component designs to meet cost and safety targets. One component that is the subject of advanced designs is the steam generator, some designs of which forego the usual shell-and-tube architecture in order to fit within the primary vessel. In addition to being more cost- and space-efficient, such steam generators need to be more reliable, since failure of the primary vessel represents a potential loss of coolant and a safety concern. A significant amount of data exists on flow-induced vibration in shell-and-tube heat exchangers, and heuristic methods are available to predict their occurrence based on a set of given assumptions. In contrast, advanced designs have far less data available. Advanced modeling and simulation based on coupled structural and fluid simulations have the potential to predict flow-induced vibration in a variety of designs, reducing the need for expensive experimental programs, especially at the design stage. Over the past seven years, the Reactor Product Line has developed the integrated multi-physics code suite SHARP. The goal of developing such a tool is to perform multi-physics neutronics, thermal/fluid, and structural mechanics modeling of the components inside the full reactor core or portions of it with a user-specified fidelity. In particular SHARP contains high-fidelity single-physics codes Diablo for structural mechanics and Nek5000 for fluid mechanics calculations. Both codes are state-of-the-art, highly scalable tools that have been extensively validated. These tools form a strong basis on which to build a flow-induced vibration modeling capability. In the last two years a significant effort was devoted to 1) develop and validate a fully coupled capability in SHARP for Fluid-Structure calculations (FSI) and 2) validate the use of SHARP for one-way coupled calculations in helical steam generators on legacy data available as well as novel experiments. In this report we discuss an extension of previous one-way coupled calculations performed with Nek5000 and Diablo aimed at simulating available FIV experiments in helical steam generators in the turbulent buffeting regime. It was demonstrated that in the buffeting regime one-way coupling was judged sufficient because the pressure loads do not cause substantial displacements. However, higher speeds led to a reduction in accuracy and the need for a fully coupled capability for velocity or approaching the critical velocity and fluid elastic instability. In this report we demonstrate such fully coupled capability on the Argonne test case discussed in previous reports.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Supports with integrated sensors for nuclear reactor steam generators, and associated systems and methods

Supports with integrated sensors for nuclear reactor steam generators, and associated systems and methods, are disclosed. A representative method for forming a nuclear-powered steam generator includes forming an instrumented support, the instrumented support including a carrier portion and a retainer portion, with at least one of the carrier portion or the retainer portion being integrally formed with a sensor via an additive manufacturing process. The method can further include coupling the sensor to a communication link, supporting a helical steam conduit on the instrumented support, and installing the helical steam conduit and the instrumented support in a nuclear reactor. The helical steam conduit is positioned along a primary flow path, which is in turn positioned to circulate a heated primary flow in thermal communication with the helical steam conduit.

Welter, Kent↗
DOE OSTI2017

Numerical Analysis of Flow Instability in Once-through Steam Generator

Two-phase flow instability is a critical area to consider in the design of steam generators. Oscillation of the flow rate and the system pressure caused by heating may cause several problems and is unfavorable in an extreme case because it causes a burnout of the heat transfer surface. A large amplitude variation in the heat transfer tube wall temperature generally occurs under density wave oscillation (DWO) conditions, and a continuous cycling tube wall temperature may lead to damage to the tube, causing thermal fatigue problems. Therefore, instability of the flow should be avoided, and a two-phase flow system should be designed to have a sufficient margin to avoid this. A computer program was developed for predicting a two-phase flow instability in a steam generator heated by liquid sodium, and the results of numerical studies for several parameters are presented in this paper.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

Comparing Velocity Profiles Along the Rod Length of a Helical Coil Steam Generator Model

A model of a specific type of tube and shell heat exchanger, the helical coil steam generator (HCSG), was designed and constructed to study multiple fluidic properties that attribute to the efficiency of the heat transfer it provides. Tube and shell heat exchangers are currently used throughout industry in chemical, power and petroleum engineering. Most commonly, a primary flow is circulated through a shell, while the secondary flow is run through several small tubes that are bundled together. Methods to increase the heat transfer between the two flows include adding baffles to force shell side flow over more tubes, fins added in-between layers of tubes and passing tubes multiple times through the shell to increase heat exchanger effectiveness. The HCSG incorporates many of the proposed methods but also relies on a complex geometry to increase the heat transfer between tube and shell side flow. In an area where cost effectiveness is favorable, such as inside a nuclear reactor, helically banked steam generators makes extensive use of the room with no sharp tube bends. This increases the pressure loss on the secondary flow and can solve potential temperature manufacturing issues at the welds of junctions. Additionally, they have exhibited pure cross flow behaviors with high heat transfer coefficients and axial temperature profiles that correspond to pure counter-flow with high mean temperature differences. Early work showed that helical banks can have a significant increase of 16 to 43% higher heat transfer coefficient than straight pipe heat exchangers. While many previous studies have looked at the heat transfer, pressure drop and flow fields of a tube and shell heat exchanger, they all focus on tube bundles that are either in-line or staggered. The early flow visualization studies on these types of bundle arrangements reported that attached eddies were formed alternatively behind each of the rods and were occasionally dragged into the main stream of shell side flow. Later studies suggested that observable periodic vortex shedding was dependent on geometry. Experimental data taken using techniques such as laser Doppler anemometry (LDV) by Simonin and Barcouda (1986) as mentioned in Hassan (2002), hot-wire anemometry with Tsuchida (1982) and particle image velocimetry (PIV) conducted by researchers as late as 2007 have been used to characterize turbulent flow and distinguish flow field structures within in-line and staggered tube bundles. By studying these flow field structures, their contribution to fluidic properties such as heat transfer efficiency and pressure drop can be characterized effectively. Literature review lead to a design that incorporated five layers of coils wrapped around one another. The outermost and middle layers of tubes coiled at a specific pitch in a clockwise direction while the other two layers coiled counterclockwise. The proposed design incorporates a constantly changing lateral pitch ratio, a, between adjacent rods. The constructed test section isolates a single interface between two adjacent coiling rod bundles of twelve rods. Three distinct cross sectional planes along the rod bundles were looked at to study the effect of the local geometry to flow fields, Section A, B and C. Particle Image Velocimetry (PIV) frames of 896 x 848 pixels were captured at each section across a specific height. Profiles of mean velocity fields for each section are compared and discussed as possible features of the changing lateral pitch ratio.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A dynamic model of once-through steam generator (OTSG) for prototypical advanced reactor - 374

new design of Small Modular Reactor, the Prototypical Advanced Reactor (PAR), features two sodium primary systems each connected to dedicated steam generators (SGs) and sharing a balance of plant (BOP) system. PAR adopts once-through steam generators (OTSG) for its compact structure. The existence of superheated steam in a OTSG improves turbine design by eliminating the need of bulky moisture separator in SG. The two cores and SGs' design enable PAR to adjust power flexibly, as a result, introduce more challenges to the control. Therefore, a fast simulation model with high accuracy OTSG model is needed. In this paper, a dynamic model is built for OTSG of PAR based on the conservation of mass, momentum, and energy. The OTSG is simulated as lumped pipe and divided into subcooled, evaporating, and superheated regions by moving boundaries. SIMULINK is adopted to this OTSG simulation to be merged into existing PAR system models easily. The steady state results show that key parameters are rational. The 5% step increase of feedwater enthalpy transient demonstrates that the model is capable to respond to the perturbations. Since the basic laws and algebraic method used in this paper are suitable for other fluids, the model can be easily applied to any other OTSG. Future work will also focus on model optimization, merging and improved control. The final aim is to perform full scope realtime simulations for PAR under normal operational transients. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

A Semi-Empirical Correlation for the Onset of Density Wave Oscillations in a Helical Coil Steam Generator

NuScale Power has completed full length helical coil steam generator (HCSG) tests at SIET Laboratories in Piacenza, Italy. The test program included an investigation of the onset and evolution of density wave oscillations (DWO). This paper describes the mechanisms leading to the onset of DWO as inferred from tests performed in the full-height TF-2 counter-flow test facility. This research supports the concept that the onset of DWO is caused by liquid bridging inside the boiling length of the tubes. Using a separate cylinders approximation, a DWO onset correlation is obtained by performing a steady-state momentum balance on the density front created by liquid bridging. This yields a momentum balance equation in terms of a set of dimensionless superficial velocities, a corresponding dimensionless pressure drop term and an average void fraction. Envelope theory is then used to obtain a critical void fraction which is substituted into the dimensionless momentum balance to obtain a DWO onset correlation similar to the Wallis counter-current flooding correlation. A comparison of the DWO onset correlation to the TF-2 DWO experimental data is presented and shows excellent agreement when the average equilibrium vapor quality is greater than 0.2.

Density Wave Oscillations, Helical Coil Steam Gene↗
DOE OSTI2017

Eulerian Two-Fluid RANS-based CFD Simulations of a Helical Coil Steam Generator Boiling Tube

As part of a larger effort to demonstrate a simulation-based capability for the evaluation and optimization of helical coil steam generators, the performance of a helical coil steam generator tube is being considered using a Eulerian two-fluid multiphase flow capability implemented within the commercial computational fluid dynamics (CFD) code STAR-CCM+. The objective of these evaluations is to characterize boiling and the resultant two-phase flow structures within the helical coil heat exchanger tube so that structural analyses can more accurately account for vibration sources and damping. These studies have shown that CFD predictions using the two-fluid model are consistent with published measurements of pressure drop and heat transfer characteristics. The sensitivity of model predictions to both flow conditions and modeling parameters associated with bubble dynamics closure models has been investigated.

Pointer, Dave↗
NASA NTRS2009

Design and Activation of a LOX/GH Chemical Steam Generator

The purpose of this paper is to give a detailed description of the design and activation of the LOX/GH fueled chemical steam generator installed in Cell 2 of the E3 test facility at Stennis Space Center, MS (SSC). The steam generator uses a liquid oxygen oxidizer with gaseous hydrogen fuel. The combustion products are then quenched with water to create steam at pressures from 150 to 450 psig at temperatures from 350 to 750 deg F (from saturation to piping temperature limits).

Saunders, G. P.↗
DOE OSTI2020

Versatile coating with multifunctional performance for solar steam generation

In this work, a new kind of material, composite complex coating (CCC), with multifunctional performance has been developed for solar steam generation. The CCC has many advantages: (a) Scalability. The fabrication process is facile and mild; it can be realized in aqueous solution at room temperature, without high pressure, toxic organic solvents, or complex equipment. (b) Cost-effectiveness. The reagents used for preparation of CCC are low-cost and readily available. (c) Universality and stability. CCC firmly adheres on surfaces of various substrates with diverse shapes (cotton, filter paper, wood, polyurethane sponge, and even chemically inert and highly hydrophobic polyvinylidene fluoride membranes), and can withstand rinsing treatment (3000 r/min for 96 h), cyclic frost-thaw test (-18 °C ⇌ 30 °C, 90 times), and both high and low pH environments. In addition, many other reported coatings, such as carbon black, fail under similar process strain. (d) Anti-crude oil-fouling property. The CCC possesses stable superhydrophilicity and underwater superoleophobicity, which collectively endow substrates with the ability to resist fouling by oils. (e) Broad and strong light absorption. CCC can transform various substrates with diverse shapes into black materials with broadband light absorption due to its d-d transitions and rough surface. Together, these properties of CCC enable substrates with nearly any structural design to be easily transformed into photothermal materials for efficient solar steam generation. Furthermore, as a proof of concept, poplar wood is treated with CCC, achieving a water evaporation rate of ~1.8 kg m-2 h-1 (one sun), which is a record among wood-based photothermal materials.

14 SOLAR ENERGY↗
DOE OSTI2020

A data-driven model for thermodynamic properties of a steam generator under cycling operation

The varying electricity demand from coal power plants due to the intermittent nature of renewable sources leads to load-follow and on/off operations referred to as cycling. Cycling causes transients of properties such as pressure and temperature within various components of the steam generation system.These transients cause increased damage because of fatigue and creep-fatigue interactions shortening the life of components. An algorithm is developed to identify cycling operations from the gross power data. The data-driven model based on artificial neural networks (ANN) is developed using 10 years data from Coal Creek Station power plant located in North Dakota, USA to estimate properties of the steam generator components during cycling operations. Furthermore, the uniqueness of this model is the ability to predict component properties for the cycling as well as base-load operations and is reported for the first time. The ANN model estimates the component properties, for a given gross power profile and initial conditions, as they vary during cycling operations. As a representative example, the ANN estimates are presented for the superheater outlet pressure, reheater inlet temperature, and flue gas temperature at the air heater inlet. The changes in these variables as a function of the gross power over the time duration are compared with measurements to assess the predictive capability of the model. Mean square errors of 4.49E-04 for superheater outlet pressure, 1.62E-03 for reheater inlet temperature, and 4.14E-04 for flue gas temperature at the air heater inlet were observed.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Ultrasonic measurement of temperature distributions in extreme environments: Electrical power plants testing in utility-scale steam generators

Thermal heterogeneities within energy conversion and storage, material processing, nuclear processes, aerospace, and military applications are often inaccessible to characterization by insertion sensors. When sensor deployment is possible, conventional pointwise temperature probes quickly degrade when inserted into harsh environments typical of such processes. We developed spatially-resolved ultrasonic thermometry to noninvasively measure the spatial distributions of thermal properties in such applications, even when sizable thermal gradients are present. Our method divides the path of ultrasonic propagation into segments bound by echogenic features, which create echoes in pulse-echo mode, encoding the information about interior temperature distributions. We use the acquired ultrasonic responses to estimate the internal temperature distributions by solving an inverse problem or concatenating segmental estimates. This work describes the implementation and industrial testing of the developed method at a coal-fired electrical power generation plant. We inserted an echogenically segmented Inconel 625 waveguide into the combustion zone of the utility-scale boiler and continuously acquired ultrasonic data while keeping sensitive components away from the damaging combustion environment. The accuracy of the time-dependent temperature distributions reconstructed from the ultrasonic measurements was comparable to that of thermocouples. The resiliency of ultrasonic thermometry to harsh combustion conditions was far superior to conventional insertion sensors. The measurements obtained during plant operation captured daily steam generation cycles in response to changing customer demand and intermittent contributions of renewable power sources to the power grid. These measurements have revealed new insights into the relationship between the dynamic power generation load and the conditions inside the steam generator. As a result, the successful industrial testing of spatially-resolved ultrasonic thermometry in solids indicates that the developed technology has matured to become an attractive alternative to conventional sensing in solving challenging problems of long-term thermal characterizations in extreme environments.

42 ENGINEERING↗
DOE OSTI2024

Prognostic model and failure mechanisms of steam generators in Sodium-Cooled fast reactors

This paper presents a prognostic model for sodium-cooled fast reactor (SFR) steam generators (SGs). Here, the purpose of the model is to estimate the remaining useful life of SFR SGs and thus to support the decision-making of autonomous control. SFR SGs are of great interest for plant integrity due to their harsh operation environment. They operate at higher temperatures and higher coolant-to-steam pressure differences than those of current light water reactors (LWR). The severity of the SFR SG failure consequences, which include water-sodium contact, is another reason. Understanding its failure mechanisms is important for the development of its prognostic model. Based on our literature review and physics-based analysis, we concluded that creep would be a dominant degradation mode of SFR SGs due to SFR’s high-temperature and high-pressure environment. Thus, creep is the focus of the prognostic model. Various other failure modes were also investigated in this study. The mechanical fatigue due to flow-induced vibration is usually observed in early developmental phases and would not be an important issue during normal operation. The thermal fatigue due to thermal stripping is occasionally observed in other components in SFRs but does not affect SG integrity. Pure water stress corrosive crack, fretting, and so on are commonly observed in LWR SGs but are significantly less important in SFR SGs because of the high temperatures, high pressure differences, and chemical properties of liquid sodium. Based on these investigations, a prognostic model focusing on creep failures was developed. It estimates the failure probability profile by sampling the Larson-Miller parameter (LMP) and temperature and associated uncertainties through Monte Carlo methods. Two case studies were presented. The first one demonstrated the model’s capability to calculate the failure probability for a new specimen within a given time. If the tube is working under temperatures of 500C ± 3 and pressures of 15.2 MPa, which leads to LMP of 20,100 ± 50, the failure probabilities within 50, 70, and 90 years are approximately 0.1 %, 3.2 %, and 17.5 %. The second demonstrated how adjusting the workload can help to protect the integrity of the component. For an old tube reaching 99 % of its lifespan, continuing to run at temperatures of 500C ± 3 and LMP of 20,100 ± 50 leads to a failure probability of about 29.0 % within a year. If the temperature is reduced by 5C, the failure probability can be reduced to 2.5 %, and, if the pressure is also reduced such that the LMP is increased by 100, the failure probability can further be reduced to 0.12 %.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

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

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.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗