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At least 235 records · Page 13

Transient Analysis of a Micro-reactor using the DireWolf Code Suite

Transient analyses of heat pipe micro-reactors are necessary to ensure that hypothetical accident scenarios do not comprise reactor safety. Due to its small size and reliance on heat-pipes for cooling, the micro-reactor design introduced in this paper is a tightly coupled system which requires multi-physics tools to accurately model transient events. Idaho National Laboratory’s DireWolf code suite based on the MOOSE framework is tailor-built to model heat-pipe reactors. This paper demonstrates DireWolf’s ability to simulate the coupled thermal-neutronics transient behavior of a heat-pipe micro-reactor. The transient events presented here include an inadvertent rotation of all control drums simultaneously and a sudden complete ejection of a single control drum. A detailed description of each event is provided along with simulation results, including time dependent power and temperature distributions, and discussion. This is a Westinghouse Electric Company (WEC) led publication.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Preliminary Nuclear Containment Vessel Modeling for Multi-Hazard Probabilistic Risk Assessment under Seismic Hazards and Concrete Degradation

The current practice for natural phenomena hazards (NPH) risk assessment of nuclear facilities is to compute the risk for each hazard independently and then compound the total risk as a combination of single hazard risks. This state of practice does not consider correlations between hazards and the cascading impacts to structures, systems, and components (SSCs), and could thus underestimate the NPH risk or overestimate the nuclear facility safety. Events such as the Fukushima Daiichi accident have highlighted the importance of multi-hazard risk considerations to nuclear power plants (NPPs) that quantify the cascading damage effects to SSCs in the risk models. Moreover, the current fleet of NPPs in the United States is aging; these NPPs are now expected to operate well beyond their initially planned design life. Aging-related deterioration can potentially decrease the capacity of critical structures such as containment vessels to withstand NPH. Such aging considerations may not be adequately accounted for by the current NPH risk assessment guidelines. This paper presents a preliminary modeling and simulation of a representative reinforced concrete containment vessel subjected to seismic mainshock and aftershock considering concrete degradation due to alkali silica reaction. The broader aim is to develop multi-hazard time-dependent fragility functions that could be subsequently used in the probabilistic risk assessment (PRA) model. The multi-hazard component comes into play due to the consideration of damage to the containment vessel under seismic loads and concrete degradation. Consideration of concrete degradation also brings into play the time-dependent nature of the containment vessel response. The response of the containment vessel under varying degrees of concrete degradation to seismic loads is investigated. The results presented are simulated using the Multi-hazard Analysis for STOchastic time-DOmaiN phenomena (MASTODON) software for seismic analysis and the Blackbear software for concrete degradation and damage modeling. Both software are open source and developed within the Multiphysics Object-Oriented Simulation Environment (MOOSE).

42 ENGINEERING↗

Simulation of Peach Bottom turbine trip transient with RETRAN-3D using BXFGEN

The Peach Bottom 2 Turbine Trip transient is used to evaluate the capabilities and accuracy of coupled 3-D neutronics/thermal hydraulics best estimate calculations for support of safety analysis. Selected results, obtained with RETRAN-3D, are compared to available measurements and benchmark results. The comparisons are analyzed and the application of RETRAN-3D for a best estimate analysis approach within the safety analysis methodology is discussed. Overall, both the thermal-hydraulic and neutronic results show a good comparison to the experimental data, and the model is considered to accurately predict test data. In particular, the initial acoustic response of the main steam line and the subsequent main pressurization stages are well-predicted. During the main pressurization stage, the timing and magnitude of the in-core local pressurization and associated void compression are properly predicted based upon the agreement between local power range monitors (LPRM) predictions upwards, but the shift is slightly underpredicted. This indicates the methodology is well-posed for simulating this class of transient response.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Microstructure homogenization of concrete used in nuclear power plants

Almost all nuclear power plants in the United States are operating past their intended lifetimes or are requesting lifetime extensions. Therefore, understanding changes to the concrete containment structure over time is crucial to evaluate the structure’s continued viability. Concrete materials are heterogeneous particulate composites that exhibit viscoelastic material properties, which can lead to slow deformation over time, causing stress redistribution and the potential for creep cracking. A code to generate random, three dimensional (3D) concrete microstructures has been developed and paired with finite element analysis to predict the long-term viscoelastic properties of concrete. Data from these simulations are used to develop constitutive equations for the viscoelastic behavior of the homogenized concrete. The codes in this work are used to virtualize laboratory experiments, to obtain long-term creep data in a faster, cheaper manner. To validate this work, the simulated creep behavior of concrete is compared to 800 d of experimental data that has been extended to 27 y of data using the Time-Temperature superposition (TTS) principal. Excellent agreement between the simulation results and experimental data is seen.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Quantification of the importance of the modeling fidelity in the Best Estimate Plus Uncertainty analysis

In this work, the multi-physics coupling of CTF-PARCS for both steady-state and transient simulations is evaluated focusing on the quantification of the importance of the modeling fidelity when applied to the Best Estimate Plus Uncertainty safety analysis. For the steady-state, a Picard iteration approach is adopted in the coupled code while for the transient an explicit approach has been developed as a first step. The CTF-PARCS coupling is applied to the REA at HFP BOC scenario proposed in the exercise I-2c of LWR-UAM benchmark Phase III. Two different modeling choices are investigated for the nominal calculations. The first consists of including the 3D burnup information in CTF, and the second of modeling the spacers grids in both PARCS and CTF. It is observed that due to the degradation of the fuel thermal conductivity, the 3D burnup inclusion in CTF leads to significant higher centerline temperatures than the base case, with a difference up to 300 K. The spacer grids modeling shows the expected power and temperature decrease in the axial positions of the spacer grids. For the uncertainty quantification study, the multi-physics modeling including the burnup information in CTF is used. The results show that the inserted reactivity has a relative standard deviation of 13.6% mainly attributed to the nuclear data. The maximum linear power has a relative standard deviation of 16.2% due to the nuclear data as well, while the maximum centerline temperature has a relative standard deviation of 3.5% primarily caused by the fuel thermal conductivity. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

System design and analysis of thermal power dispatch systems for boiling water reactors

Nuclear power plants are crucial to meeting net zero emission goals and achieving energy sustainability. Integrating these plants with clean energy technologies such as high-temperature steam electrolysis (HTSE) may improve the efficiency and economic competitiveness of these plants. Here, the current study investigates the design and operation of a thermal power dispatch (TPD) system for coupling boiling water reactors (BWRs) to HTSE plants. The TPD system extracts a portion of the steam from the reactor’s main steam line and transfers its thermal energy to an HTSE plant through a power transport loop. A TPD system for 5 % steam extraction has been designed and the system performance during steady and transient operations has been analyzed. The TPD system dispatched a total of 197 MW thermal energy to the HTSE plant under nominal design conditions. Saturated steam at 7.17 MPa from the BWR plant was condensed and subcooled to a temperature of 168 °C, while a mass flow rate of 91.1 kg/s of superheated steam was dispatched to the HTSE plant. Furthermore, the system performance during transient operation showed a continuous transition from the initial hot standby mode to the nominal power dispatch level. The transient simulation results emphasized the importance of investigating component level performance for the TPD system design. The current results will guide future works on the development of integrated energy systems for hydrogen production or process heat applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system

New ways to integrate energy systems to maximize efficiency are being sought to meet carbon emissions goals. Nuclear-renewable integrated energy system (NR-IES) concepts are a leading solution that couples a nuclear power plant with renewable energy, hydrogen generation plants, and energy storage systems, such that thermal and electrical power are dispatchable to fulfill grid-flexibility requirements while also producing hydrogen and maximizing revenue. Here, this paper introduces a deep reinforcement learning (DRL)-based framework to address the complex decision-making tasks for NR-IES. The objective is to maximize revenue by generating and selling hydrogen and electricity simultaneously according to their time-varying prices while keeping the energy flow in the subsystems in balance. A Python-based simulator for a NR-IES concept has been developed to integrate with OpenAI Gym and Ray/RLlib to enable an efficient and flexible computational framework for DRL research and development. Three state-of-the-art DRL algorithms have been investigated, including two-delayed deep deterministic policy gradient (TD3), soft-actor critic (SAC), proximal policy optimization (PPO), to illustrate DRL’s superiority for controlling NR-IES by comparing it with a conventional control approach, particle swarm optimization (PSO). In this effort, PPO has shown more-stable performance and also better generalization capability than SAC and TD3. Comparisons with PSO have demonstrated that, on average, PPO can achieve 13.9% more mean episode returns from the training process and 29.4% more mean episode returns from the testing process when different hydrogen-production targets are applied.

08 HYDROGEN↗

Experimental investigation of a closed vapour box module for a divertor-like configuration in Magnum-PSI

Efficient management of extreme heat fluxes in the divertor region to extend the lifetime of the components remains a critical challenge for the realization of nuclear fusion-based power plants. Among the alternative concepts explored for the divertor region, the use of liquid metals, particularly lithium, is of interest due its ability to dissipate the incoming plasma heat flux through the vapour shielding effect (VS). In this work, we experimentally investigated a ‘closed’ configuration of a dedicated Vapour Box Module (VBM) in the linear plasma device Magnum-PSI. The goal of the experiments is to simulate the vapour box divertor environment conditions and assess its performance in terms of power mitigation and redistribution and lithium confinement. Initial testing without Li demonstrated the efficacy of a closed VBM structure in inducing detachment via neutral gas accumulation. Apertures which enabled non-condensing gas to be effectively pumped while ensuring lithium condensed on the inner surfaces were therefore added. With a lithium capillary porous structure target used, lithium is directly vaporized by the plasma, forming a dense lithium vapour cloud that interacts with the incoming plasma. This resulted in a significant reduction of the target temperature of at least 48%, together with a temperature locking effect, a phenomenon typically observed in the VS regime. Lithium vapour confinement within the VBM was strongly correlated with the wall temperature. Relatively cold walls promoted Li re-condensation and therefore improved Li confinement, although with the expected trade-off of increased hydrogenic retention on lithium-wetted surfaces. As the wall temperature increased, the confinement efficiency decreased, consistent with reduced Li re-condensation and thermally activated Li–H chemistry and remobilization at the walls. Diagnostic measurements through embedded thermocouples and calorimetry revealed that lithium vaporization and re-condensation processes also playedsignificant roles in plasma power dissipation. The results advance the case for a closed divertor chamber with direct lithium evaporation from the strike-points as a viable method to manage divertor heat fluxes in future fusion reactors.

Romano, Fabio [Dutch Institute for Fundamental Ene↗

Analysis and Down Select of Flow Passages for Thermal Hydraulic Testing of a SNAP Derived Reactor

As past of the Vision for Space Exploration, man will return to the moon. To enable safe and productive time on the lunar surface will require adequate power resources. To provide the needed power and to give mission planners all landing site possibilities, including a permanently dark crater, a nuclear reactor provides the most options. Designed to be l00kWt providing approx. 25kWe this power plants would be very effective in delivering dependable, site non-specific power to crews or robotic missions on the lunar surface. An affordable reference reactor based upon the successful SNAP program of the 1960's and early 1970's has been designed by Los Alamos National Laboratory that will meet such a requirement. Considering current funding, environmental, and schedule limitations this lunar surface power reactor will be tested using non-nuclear simulators to simulate the heat from fission reactions. Currently a 25kWe surface power SNAP derivative reactor is in the early process of design and testing with collaboration between Los Alamos National Laboratory, Idaho National Laboratory, Glenn Research Center, Marshall Space Flight Center, and Sandia National Laboratory to ensure that this new design is affordable and can be tested using non-nuclear methods as have proven so effective in the past. This paper will discuss the study and down selection of a flow passage concept for a approx. 25kWe lunar surface power reactor. Several different flow passages designs were evaluated using computational fluid dynamics to determine pressure drop and a structural assessment to consider thermal and stress of the passage walls. The reactor design basis conditions are discussed followed by passage problem setup and results for each concept. A recommendation for passage design is made with rationale for selection.

Godfroy, T. J.↗

Modelling and analysis of nuclear reactor system coupled with a liquid metal battery

Traditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.

25 ENERGY STORAGE↗

Coupling of nTRACER to COBRA-TF for full core high-fidelity analysis of VVERs

The evolution of computing clusters allows the use of high-resolution multi-physics solvers for reactor analysis. Despite the continuous expansion of VVER technology, only one other high-fidelity sub-pin multi-physics core solver is currently developed for safety analysis. To that end the Laboratory of Reactor Physics and Thermal-Hydraulics (LRT) of Paul Scherrer Institut is developing such a tool with the coupling of the neutronic code nTRACER and the sub-channel code COBRA-TF. This work follows the initial steps of the coupling and focuses to the extension of the core solver to full core VVER geometries. The X2 VVER-1000 benchmark is modeled with the novel core solver. The results are compared to the ones of a standalone nTRACER calculation where the feedbacks are provided by a simplified 1D thermal-hydraulic solver. Despite relatively good agreement in power distribution, the limitations of the simplified solver become apparent especially when comparing global temperature profiles. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Time Distribution Analysis for Task Primitives to Support Dynamic Human Reliability Analysis

To support data collection for dynamic human reliability analysis (HRA), this study investigates time distributions for task primitives defined in the Goals, Operators, Methods, and Selection rules (GOMS)–Human Reliability Analysis (HRA) method and Human Reliability data EXtraction (HuREX). GOMS-HRA was developed to provide cognition-based time and human error probability (HEP) information for dynamic HRA calculations within the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER) framework, while HuREX is a comprehensive HRA data collection method developed by the Korea Atomic Energy Research Institute (KAERI). In this paper, we examine time distributions by using experimental data collected from the Simplified Human Error Experimental Program (SHEEP) study, which proposes an HRA data collection framework to complement full-scope simulator research and gather input data for dynamic HRA by using simplified simulators such as the Rancor Microworld simulator. This paper investigates whether the time required for GOMS-HRA and HuREX task primitives fits 13 statistical distributions. Additionally, we compare and discuss the time distributions obtained from both student operators and professional operators. The result was that this study identified several time distributions for five GOMS-HRA and four HuREX task primitives. In the future, the results of this study are expected to provide objective reference data on the elapsed time for task primitives and aid in realistically simulating scenarios within dynamic HRA.

Dynamic Human Reliability Analysis↗

Thermal Integration of Advanced Nuclear Reactors with a Reference Refinery, Methanol Synthesis, and a Wood Pulp Plant (Rev.1)

The present report is intended to provide process flow diagrams (PFDs) and energy and mass balance data sheets for a U.S. industrial sector subset with which nuclear heat and power could be integrated—a subset that includes the oil refining, methanol and pulp and paper industries. Coupling options for integrating nuclear energy into these industries are quantitatively outlined for reference systems, and future work will extend this analysis in greater detail. Opportunities for integrating small modular nuclear reactors (SMNRs) were investigated for each of the industrial process configurations. Aspen HYSYS and Cycle-Tempo models for a high-temperature gas-cooled reactor were developed to evaluate the proposed integration. This introductory evaluation provides a general description and assessment of the operating principles, reactor coolant core outlet temperature, and reactor size to be integrated with industry. The industrial processes of oil refining and the production of methanol, pulp and paper were simulated by using Aspen HYSYS, Aspen Plus, and the PRELIM (Petroleum Refinery Life Cycle Inventory Model) tool to develop process details. Cycle-Tempo models then extend the process modeling results to obtain net energy demands (e.g., heat, steam, and electricity) when accounting for process steam and waste heat recovery. This information is intended to foster the analysis of integrating an SMNR to decarbonize industrial facilities. The SMNR would provide reliable, competitive, and sustainable clean energy while reducing carbon emissions and other environmental impacts, such as water withdrawals, consumption, and contamination. The refining industry, exhibited in Figure ES1, is a leading consumer of fossil -fuel-based heat, power, and hydrogen in the U.S. industrial sector, generating over 164 million metric tons (MMT) of CO 2 emissions in 2023. The overall mass and energy pertaining to a generalized complex refinery in the United States is reflected in Figure ES1, along with energy metrics regarding integration with a nuclear power plant (NPP). Data sheets were developed to indicate the energy requirements for the overall refinery and each refinery process. The data sheet for the overall refinery is shown in Table ES2.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Automated Control for Nuclear Thermal Propulsion Start-Up using MOOSE-based Applications

This report presents a Griffin/Bison/RELAP-7 numerical model of a prototypical NTP system that features fuel assemblies arranged in rings, and which was designed to simulate rapid startup transients. The physics modeled include full-core neutronics, assembly-wise heat conduction, and conjugate heat transfer, with the balance of plant mainly imposed through boundary conditions. In addition, various forms of automated reactivity control were deployed by using the MOOSE to autonomously drive the model and simulate the reactor transitioning from assumed initial conditions to nominal power in a fraction of a minute. To generate the cross-sections of the neutronics model, and in an effort to simultaneously account for the tremendous axial temperature gradients in the reactor and to limit the number of state points required for cross-section generation, the average component temperatures and hydrogen densities in the cooling channels were correlated to the average fuel and moderator temperatures, and fixed axial profiles were derived for nominal conditions and then used during the transient. With this approximation, a tractable cross-section library tabulated with fuel/moderator temperatures and CD angles was generated using Serpent. The full-core SPH correction procedure and the CD decusping technology in Griffin, respectively, ensure preservation of the multiplication factor and reaction rates at state points, along with a reasonably accurate reactivity worth between tabulated CD angles, despite using a coarse mesh. Feedback from other physics was calculated by modeling one representative fuel assembly per ring, along with the corresponding fuel and moderator cooling channels. To limit power overshoots during startup, another layer of multiphysics coupling was added to the model in order to automatically control the drums. Two different technologies presented herein showed outstanding performance in this regard: (1) a novel hybrid PID controller based on both power and reactivity signals, and (2) a PGC that relies on kinetics parameters and reactivity coefficients to predict future behavior and adjust the desired signal accordingly. A challenging benchmark was devised, featuring a power demand curve that exponentially increases by a factor of 500 within 30 seconds, then levels out after that. Both control approaches create a simulated power curve that closely follows the power demand curve and limits power overshoots to 1% or less. While the former approach requires more tuning of the internal parameters, the latter requires additional knowledge of the reactivity feedback coefficients and rates of change of the corresponding variables, including fuel and moderator temperature, which could be difficult to dynamically measure for a real NTP system. Fortunately, some inaccuracy in these quantities will not drastically degrade the PGC performance. Subsequently, a more realistic startup sequence was considered, in which the mass flow rate and outlet pressures are ramped up to model bootstrap and thrust build-up phases prior to reaching steady-state conditions, demonstrating the ability of the hybrid PID and PGCs to handle such transients, with both types of controllers exhibiting very similar behavior. Nevertheless, a significant chamber temperature overshoot was observed, caused by the demanded power signal and assumed mass flow rate. This issue could be mitigated by deploying a reactor controller that follows the chamber temperature signal and actuates both the control valves and drums (rather than using a power signal based solely on the drums to control reactivity). Enhancement of the hydrogen fluid properties available in MOOSE, as well as a better understanding of prototypical initial conditions, are also needed to further enhance this startup model. Finally, a study was performed to model decay heat post-shutdown, and to prepare for extending this model to predict shutdown behavior and post-shutdown pulsed cooling requirements.

33 ADVANCED PROPULSION SYSTEMS↗

Microfluidic Liquid-Liquid Extraction Chip with Integrated Raman Sensors (Phase I and Phase II Final Report)

As demand for electricity continues to increase worldwide, the world’s nuclear power generating capacity will continue to grow. Nuclear power is the most environmentally benign way of producing electricity on a large scale. The long-term successful use of nuclear power, however, is critically dependent upon adequate and safe processing and disposal of spent nuclear fuels. A very important feature of nuclear energy is that spent fuels can be reprocessed to recover fissile and fertile materials that can then be used as fresh fuel for nuclear power plants. The DOE-NE Fuel Cycle Research and Development (FCR&D) is currently developing nuclear material reprocessing technologies. In a typical nuclear fuel reprocessing system, centrifugal contactors are used as liquid-liquid extraction devices where two immiscible liquids are mixed at high speeds using a rotor, which creates a fine dispersion of droplets of organic phase in an aqueous phase that contains the analyte. Understanding the extraction efficiency at these contactors through modeling and simulation is important in the development of reprocessing technologies and the optimization of current technologies such as the PUREX process. The outcome of this program will be a liquid-liquid microfluidic flow cell chip with embedded spectroscopic sensors for the analysis of extracted analytes. This device will be useful in the optimization of new fuel reprocessing schemes as well as existing reprocessing processes by providing a microfluidic modeling platform to optimize extraction parameters. The Phase I and Phase II work developed a microfluidic chip design that allows integration of Raman and absorption fiber optic probes and successfully demonstrated the feasibility of using Raman and absorption probes to detect key analytes that partition into the aqueous and organic phases.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗

Chlorine gas and anion radical reactivity in molten salts and the link to chlorobasicity

Next-generation nuclear power plants may include exciting novel designs in which molten salts are the coolant or a combination of the coolant and fuel. Whereas it is straightforward to see why having a low volatility coolant can be advantageous for safety, much is not understood about the production of volatile halogen gases as a result of radiation and even less is known about the distribution of these species at and away from interfaces. Using first principles molecular dynamics simulations, we investigate the product of the disproportionation reaction between chlorine anion radicals (nominally Cl 2 ˙ − ) in the bulk and slab configurations. We find that the product depends on the chlorobasicity of the medium. For example, in ZnCl 2 , Cl 2 forms, but in a eutectic mixture of LiCl and KCl, Cl 3 − is formed as a product. We also find that Cl 3 − prefers to form at the vapor interface and this may have implications for corrosion and reactivity. Furthermore, the mechanisms of the mobility of Cl 2 and Cl 3 − are radically different, the first one being vehicular and the second Grotthus-like. Chlorobasicity is linked to the electronic structure of the host melt; ZnCl 2 forms extended networks along which metal ions and anionic counterions have significant electronic orbital overlap forming long, linear, molecular-like constructs; the opposite is true for the alkali metal eutectic salt.

Nguyen, Hung H. [Univ. of Iowa, Iowa City, IA (Uni↗

Diagnosing nuclear power plant pipe wall thinning due to flow accelerated corrosion using a passive, thermal non-destructive evaluation method: Feasibility assessment via numerical experiments

Flow accelerated corrosion (FAC) in nuclear power plant pipes is one of the leading causes of accidents, fatalities, damage and outages. Current FAC identification methods employ expensive sensing technology and are “active” methods, where the response of the piping system to an externally-generated thermal, mechanical or optical excitation must be measured. As a result, these techniques require a disruptive and time-consuming setup. Here we propose a method that utilizes pipe surface temperature measurements to passively monitor for FAC-induced pipe wall thinning without the need for expensive equipment or post-installation setup time. This diagnostic method utilizes a simulation data-driven diagnostic model to estimate the amount of thickness reduction in a pipe based on changes in measured steady-state pipe temperatures. In order to reduce the computational burden of generating large, simulation-based datasets, the behavior of the insulation of the pipe was modeled using a suitably calibrated heat transfer boundary parameter. Additionally, global sensitivity analysis was performed to determine system parameter(s), such as the temperature of water flowing inside the pipe, which significantly affect the steady state pipe wall temperature and could cause errors in diagnosis. Two diagnostic models, one using only the change in steady-state temperature as an indicator for FAC-induced pipe wall thinning and the other using water temperature as an additional diagnostic model input were evaluated for their ability to estimate thickness reductions in a pipe using simulated pipe wall temperature data. For the numerical experiments conducted in this work, both models estimated wall thickness with errors within 0.5 mm, indicating that the proposed technique can potentially be used as a low-cost, first-pass method for FAC monitoring.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗