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Cybersecurity Workforce Training for SMR Integration into Distribution Grids: A Competency Framework and Containerized Hands-On Lab for the SMR/DER/Microgrid Boundary

Small modular reactors (SMRs) and microreactors are entering the U.S. distribution grid as synchronous generation on feeders designed for loads and inverter-based distributed energy resources (DERs). No existing cybersecurity training program addresses this intersection of nuclear operations, DER management, and operational technology security. As subcontractor to Iowa State University on the CyDERMS Center, Argonne analyzed the relevant standards and training landscape, translated the resulting gaps into a twelve-objective competency framework across distribution-operator and graduate-analyst role tracks, and built a containerized training lab using a ∼400-bus composite grid model behind a realistically simulated Modbus TCP SCADA stack. The analysis isolates the balance-of-plant / energy-management-system (BOP/EMS) boundary as the critical jurisdictional seam where, as of March 2026, neither NRC nor NERC CIP cleanly claims cybersecurity responsibility for distribution-connected SMRs. The framework maps each objective across NIST CSF 2.0, ISA/IEC 62443, NIST NICE Task–Knowledge–Skill statements, and NRC RG 5.71 awareness-and-training controls. The training lab implements operator-recognition assessment scenarios spanning grid-side disturbances and telemetry-layer anomalies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Integrated System Planning: Emerging Software Requirements in the Power Industry

Power system planning software remains fragmented across organizational boundaries, with specialized tools for capacity expansion, production cost modeling, power flow, and dynamic analysis operating on incompatible data models and assumptions. This article argues that the fragmentation is not merely a technical problem but a predictable consequence of Conway's law: software architectures mirror the departmental structures within which they are developed. Regulatory milestones like Federal Energy Regulatory Commission (FERC) Order 888 formalized these divisions, but the roots trace back to the distinct engineering disciplines-mechanical, chemical, and electrical-that staffed generation and transmission planning departments in vertically integrated utilities. As the industry moves toward integrated system planning (ISP) that coordinates generation, transmission, and distribution investment decisions, the software ecosystem must evolve accordingly. We identify five categories of software requirements to enable this transition: coherent data inputs decoupled from individual applications, unified and extensible data schemas, modular component representations that support multiple abstraction levels, lifecycle management of planning datasets, and well-defined application programming interface (API) contracts that separate data exchange from algorithmic control. We examine how these requirements interact with three common workflow patterns-serial gate clearing, sequential multiapplication, and convergence oriented-and discuss the interface design principles each demands. We then outline a vision for platform-based planning architectures where specialized analytical services compose through standardized interfaces and where artificial intelligence (AI)/machine learning (ML) tools augment decision support within a disciplined software infrastructure. The practices proposed here offer a path from today's siloed tool collections toward collaborative planning ecosystems capable of handling the complexity of modern power system transformation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bridging Equipment Reliability Data and Risk Informed Decisions in a Plant Operation Context

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry-developed and regulatory programs. The Risk-Informed Asset Management (RIAM) project is tasked to develop tools in support of the equipment reliability and asset management programs at nuclear power plants. These tools are designed to create a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). The goal of this article is to provide a guide for specific use cases that the RIAM project is targeting. We have grouped uses cases into three main areas. The first area focuses on the analysis of equipment reliability data with a particular emphasis on condition-based data, such as test/surveillance reports and component monitoring data. The second area focuses on the integration of equipment reliability into system/plant reliability models to determine system/plant health and identify the components that are critical to maintain an operational system. Lastly, the third area manages plant resources, such as maintenance activities and replacement scheduling using optimization methods. Here the primary focus is on supporting typical system engineer decisions regarding maintenance activity scheduling and component aging management. This is performed in a risk-informed context where the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow.

97 - MATHEMATICS AND COMPUTING↗

Analysis of the KROTOS KFC test by coupling X-Ray image analysis and MC3D calculations

During a hypothetical severe accident sequence in a Pressurized Water Reactor (PWR), the hot molten materials (corium) issuing from the degraded reactor core may generate a steam explosion if they come in contact with water and may damage the structures and threaten the reactor integrity. The SERENA program is an international OECD project that aims at helping the understanding of this phenomenon also called Fuel Coolant Interaction (FCI) by providing data. CEA takes part in this program by performing tests in its KROTOS facility where steam explosions using prototypic corium can be triggered. Data about the different phases in the premixing are extracted from the KROTOS X-Ray radioscopy images by using KIWI software (KROTOS Image analysis of Water-corium Interaction) currently developed by CEA. The MC3D code, developed by IRSN, is a thermal-hydraulic multiphase code mainly dedicated to FCI studies. It is composed of two applications: premixing and explosion. An overall FCI calculation with MC3D requires a premixing calculation followed by an explosion calculation. The present paper proposes an alternative approach in which all the features of the premixing are extracted from the X-Ray pictures using the KIWI software and transferred to an MC3D dataset for a direct simulation of the explosion. The main hypothesis are discussed as well as the first explosion results obtained with MC3D for the KROTOS KFC test. These results are rather encouraging and are analyzed on the basis of comparisons with the experimental data. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NDE reliability and probability of detection (POD) evolution and paradigm shift

The subject of NDE Reliability and POD has gone through multiple phases since its humble beginning in the late 1960s. This was followed by several programs including the important one nicknamed “Have Cracks – Will Travel” or in short “Have Cracks” by Lockheed Georgia Company for US Air Force during 1974–1978. This and other studies ultimately led to a series of developments in the field of reliability and POD starting from the introduction of fracture mechanics and Damaged Tolerant Design (DTD) to statistical framework by Bernes and Hovey in 1981 for POD estimation to MIL-STD HDBK 1823 (1999) and 1823A (2009). During the last decade, various groups and researchers have further studied the reliability and POD using Model Assisted POD (MAPOD), Simulation Assisted POD (SAPOD), and applying Bayesian Statistics. All and each of these developments had one objective, i.e., improving accuracy of life prediction in components that to a large extent depends on the reliability and capability of NDE methods. Therefore, it is essential to have a reliable detection and sizing of large flaws in components. Currently, POD is used for studying reliability and capability of NDE methods, though POD data offers no absolute truth regarding NDE reliability, i.e., system capability, effects of flaw morphology, and quantifying the human factors. Furthermore, reliability and POD have been reported alike in meaning but POD is not NDE reliability. POD is a subset of the reliability that consists of six phases: 1) samples selection using DOE, 2) NDE equipment setup and calibration, 3) System Measurement Evaluation (SME) including Gage Repeatability and Reproducibility (Gage R and R) and Analysis Of Variance (ANOVA), 4) NDE system capability and electronic and physical saturation, 5) acquiring and fitting data to a model, and data analysis, and 6) POD estimation. This paper provides an overview of all major POD milestones for the last several decades and discuss rationale for using Integrated Computational Materials Engineering (ICME), MAPOD, SAPOD, and Bayesian statistics for studying controllable and non-controllable variables including human factors for estimating POD. Another objective is to list gaps between “hoped for” versus validated or fielded failed hardware.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Analysis of AP1000 Small-Break Loss-of-Coolant Accident Using Reactor Transient Simulator

The Westinghouse Electric Company’s Advanced Passive Reactor (AP1000) is characterized by the incorporation of passive safety systems (PSSs) designed to ensure core cooling during transient events. The assessment of PSSs requires evaluation of their performance through a combination of experiments and simulations employing various thermal-hydraulic codes. In addition, detailed evaluation of PSSs for a specific reactor system transient analysis such as loss-of-coolant-accident analysis supports understanding representative integral effects test facility development and the further evolution model development and assessment process. Developing a reactor system code is a complex and time-consuming process that requires significant engineering expertise and effort. It can take several months to even years to complete in the early stages of reactor system design and analysis. However, this process can be expedited through the use of transient simulator models for similar reactor systems, which can be used for lesson learning and training purposes. This study uses the Personal Computer Transient Analyzer (PCTRAN) code. The main advantage of PCTRAN is its ease of use and ability to run faster than real time. This study presents the results obtained for a small-break loss-of-coolant accident (SBLOCA) for two breaks using the full version (licensed) of PCTRAN. The purpose of this investigation is to evaluate the overall system behavior during the postulated SBLOCA event as well as assess the capability of the PCTRAN code to reproduce the system response during transient events. The obtained results were compared with the Westinghouse NOTRUMP system code. The PCTRAN code proved to be reliable in predicting the qualitative behavior of the system in both transient cases. As for the system response, it was found that it is contingent on the activation time of the PSSs. The differences in reactor coolant system pressure between the two codes were attributed to the critical flow model and simplification of mass and energy balance. Despite PCTRAN’s limitations, it can still provide a reasonable prediction of various reactor parameters such as pressure, mass flow rate, and void fraction during a SBLOCA scenario. It is worth noting that PCTRAN currently employs a bulk approach similar to that of the Modular Accident Analysis Program (MAAP) and MELCOR codes. However, the upcoming version of PCTRAN will include an artificial intelligence–based detection and accident prevention system, as well as different models for different reactor components. Consequently, PCTRAN has the potential to be upgraded to match the system thermal-hydraulic codes of the U.S. Nuclear Regulatory Commission and become more widely used in cybersecurity to safeguard nuclear power plants from cyberattacks.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Distributed Smart Grid Asset Control Strategies for Providing Ancillary Services

With large-scale plans to integrate renewable generation driven mainly by state-level renewable portfolio requirements, more resources will be needed to compensate for the uncertainty and variability associated with intermittent generation resources. Distributed assets can be used to mitigate the concerns associated with renewable energy resources and to keep costs down. Under such conditions, performing primary frequency control using only supply-side resources becomes not only prohibitively expensive but also technically difficult. It is therefore important to explore how a sufficient proportion of the loads could assume a routine role in primary frequency control to maintain the stability of the system at an acceptable cost. The main objective of this project is to develop a novel hierarchical distributed framework for frequency based load control. The framework involves two decision layers. The top decision layer determines the optimal gain for aggregated loads for each load bus. The gains are computed using decentralized robust control methods, and will be broadcast to the corresponding participating loads every control period. The second layer consists of a large number of heterogeneous devices, which switch probabilistically during contingencies so that aggregated power change matches the desired amount according to the most recently received gains. The simulation results show great potential to enable systematic design of demand-side primary frequency control with stability guarantees on the overall power system. The proposed design systematically accounts for the interactions between the total load response and bulk power system frequency dynamics. It also guarantees frequency stability under a wide range of time varying operating conditions. The local device-level load response rules fully respect the device constraints (such as temperature setpoint, compressor time delays of HVACs, or arrival and departure of the deferrable loads), which are crucial for implementing real load control programs. The promise of autonomous, Grid Friendly™ response by smart appliances in the form of under-frequency load shedding was demonstrated in the GridWise Olympic Peninsula Demonstration in 2006. Each controller monitored the power grid voltage signal and requested that electrical load be shed by its appliance whenever electric power-grid frequency fell below 59.95 Hz. The controllers and their appliances responded reliably to each shallow under-frequency event, which was an average of one event per day and shed their loads for the durations of these events. Another objective of this project was to perform extensive simulation studies to investigate the impact of a population of Grid Friendly™ Appliances (GFAs) on the bulk power system frequency stability. The GFAs considered in this report are represented as demonstration units with water heaters individually modeled.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Summary of Grizzly Development for Advanced Reactor Structural Materials

This summary report contains an overview of work performed during Fiscal Year 2019 under the Nuclear Engineering Advanced Modeling and Simulation (NEAMS) Fuels Product Line work package entitled "MS-19IN020106 - GRIZZLY - INL". Grizzly is a code based on the MOOSE framework that has been under development for several years funded by the US Department of Energy’s Light Water Reactor Sustainability (LWRS) program. Prior to 2019, Grizzly development was focused on development of capabilities needed to simulate the effects of aging mechanisms in light water reactor (LWR) components. The goal of this LWR-focused work has been to develop tools that can be used to assess the ability of existing LWRs to perform safety in long term operation (LTO) scenarios. This LWR-focused work has primarily focused on the effects of reactor pressure vessel (RPV) embrittlement and aging of reinforced concrete structures. Grizzly development to support LWR degradation needs is still ongoing, but starting in 2019, Grizzly’s capabilities are being expanded to also meet growing needs for a tool to address structural component integrity and degradation in advanced reactors. A simulation capability for advanced reactor components has many of the same basic requirements that one for LWRs does, such as the ability to solve coupled systems of partial differential equations that arise from the fact that many of the problems of interest involve multiple coupled physics. The materials issues also inherently involve multiple length scales, with the response at the engineering scale being strongly affected by mechanisms occurring at atomistic and mesoscopic scales.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

MOSCATO Development and Integration in Fiscal Year 2025: Implementation of Multiphase, Multiphysics Modeling Capabilities for Molten Salt Systems

MOSCATO (Molten Salt Chemistry and Transport) is a multiphysics code that provides high-fidelity, coupled simulations of fluid flow, heat transfer, mass transfer, chemistry, electrochemical phenomena, and alloy corrosion for molten salt systems. In FY25, significant developments were made to the code package, enhancing its capabilities for modeling all relevant phenomena within operating moltens salt reactors (MSRs). The developments and activities in FY25 included: 1. Implementation of Level-Set methods to enable modeling of single-bubble behavior in molten salts. In FY25, the Level-Set two-phase flow modeling implementation was improved to simulate single bubble behavior with molten salt media. The large density and viscosity ratios between typical gases and molten salt liquids present challenges for these types of numerical solvers. With enhancements to the pressure projection method, MOSCATO’s Level-Set solver was able to be successfully validated to experiments related to helium bubble rise in stagnant molten salt. The simulated bubble rising velocity showed reasonable good agreement with experimental measurements. The bubble shape and dynamics were also visually compared with experimental snapshots, demonstrating a good qualitative match. 2. Generation of mass transfer correlations for multiphase flow systems. To enable calculations of the tritium transport across the interface between gas bubbles and salt, we modeled high- Schmidt-number mass transfer around a sphere across a broad range of Reynolds numbers. The mesh near the sphere surface was highly refined to resolve steep concentration gradients caused by the low diffusion coefficient. Literature-based mass transfer correlations were compared with the numerical results, and modifications were proposed to improve agreement, particularly at higher Schmidt numbers. These mass transfer correlations were subsequently provided to other national laboratories to help enable high quality mass transfer simulations using lower-order solvers under development within the NEAMS program. 3. Preliminary implementation of a bubbly flow solver. To model bubbly flow in molten salt, we implemented a bubbly flow solver for void fractions less than 5%. To do so, an algebraic relative velocity model that assumes small bubbles with rapid momentum equilibration was added to MOSCATO to compute bubble velocities. Preliminary comparisons with experimental data showed reasonable agreement, and further improvements are underway. 4. Generation of mass transfer correlations for MSRE subchannel The Molten-Salt Reactor Experiment (MSRE) was a landmark historical project that demonstrated the feasibility of molten-salt reactor technology. The MSRE campaign also generated a significant body of experimental data and reports that continue to support molten-salt–related research. In this report, the MSRE core subchannel was used as the reference geometry for a mass transfer study performed with MOSCATO. The geometry and computational mesh were adapted from a previous study, providing adequate resolution for the relatively low Reynolds number in this case. Additional mesh refinement was applied to reach higher Schmidt numbers, enabling the derivation of a reliable mass-transfer correlation for the present scenario. 5. Simulations of oxygen ingressions into molten salt. In the previous fiscal year, we initiated a study to simulate oxygen ingression in stagnant salt. As oxygen enters the salt through its surface, it reacts with Ce 3+ to form solid CeO 2 and other reaction products. To more fully capture the complex diffusion-convection-reaction mechanisms, capabilities for modeling natural convection in the salt vessel were added. These were needed as the flow of the ingressed gas induced flow in the salt caused by surface shear and non-isothermal effects. With these updated physics in place, we were able to successfully reproduce the experimental results for the rate of change of CeCl 3 concentrations versus time. 6. Flow corrosion model validation. In FY24, MOSCATO’s corrosion model was validated against static corrosion experiments. In FY25, this work was extended to a flow corrosion experiment, where FLiNaK salt was driven by natural convection, with initial salt impurities to initiate corrosion. Despite uncertainties in parameters such as elemental diffusion coefficients in the alloy and unknown H + concentrations, the simulations achieved good agreement with experimental results, especially in predicting sample mass losses.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Virtually simulating the next generation of clean energy technologies: NETL's AVESTAR Center is dedicated to the safe, reliable and efficient operation of advanced energy plants with carbon capture

Imagine using a real-time virtual simulator to learn to fly a space shuttle or rebuild your car's transmission without touching a piece of equipment or getting your hands dirty. Now, apply this concept to learning how to operate and control a state-of-the-art, electricity-producing power plant capable of carbon dioxide (CO{sub 2}) capture. That's what the National Energy Technology Laboratory's (NETL) Advanced Virtual Energy Simulation Training and Research (AVESTAR) Center (www.netl.doe.gov/avestar) is designed to do. Established as part of the Department of Energy's (DOE) initiative to advance new clean energy technology for power generation, the AVESTAR Center focuses primarily on providing simulation-based training for process engineers and energy plant operators, starting with the deployment of a first-of-a-kind operator training simulator for an integrated gasification combined cycle (IGCC) power plant with CO{sub 2} capture. The IGCC dynamic simulator builds on, and reaches beyond, conventional power plant simulators to merge, for the first time, a 'gasification with CO{sub 2} capture' process simulator with a 'combined-cycle' power simulator. Based on Invensys Operations Management's SimSci-Esscor DYNSIM software, the high-fidelity dynamic simulator provides realistic training on IGCC plant operations, including normal and faulted operations, as well as plant start-up, shutdown and power demand load changes. The highly flexible simulator also allows for testing of different types of fuel sources, such as petcoke and biomass, as well as co-firing fuel mixtures. The IGCC dynamic simulator is available at AVESTAR's two locations, NETL (Figure 1) and West Virginia University's National Research Center for Coal and Energy (www.nrcce.wvu.edu), both in Morgantown, W.Va. By offering a comprehensive IGCC training program, AVESTAR aims to develop a workforce well prepared to operate, control and manage commercial-scale gasification-based power plants with CO{sub 2} capture. The facility and simulator at West Virginia University promotes NETL's outreach mission by offering hands-on simulator training and education to researchers and university students.

01 COAL, LIGNITE, AND PEAT↗

Advanced Long-Term Environmental Monitoring Systems (ALTEMIS) Artificial Intelligence Data Management Plan

Across the Department of Energy’s Environmental and Legacy Management sites, complex groundwater plumes exist that will require long-term monitoring to ensure remedial actions that have been put in place remain effective decades into the future. The current monitoring paradigm predominantly consists of groundwater well sampling, whereby samples are collected, concentrations analyzed, and plume anomalies are detected after they have occurred. The Advanced Long Term Environmental Monitoring Systems (ALTEMIS) program is a multi-lab, multi-institution team of researchers that is deploying spatially integrative technologies (i.e., real-time in situ sensor networks), coupled with artificial intelligence and machine learning, to establish a more proactive monitoring paradigm. Within this approach, plume anomalies can be predicted, and corrective actions can be established prior to the occurrence, offering a more cost-effective and robust approach to long-term monitoring. The team has deployed a variety of different in situ sensing technologies at the Savannah River Site’s F-Area Hazardous Waste Management Facility around the F-Area Seepage Basins, which are unlined basins that received 7 billion liters of acidic low-level radioactive waste from the 1950s until the late 1980s. The technologies and techniques that the team is deploying are intended to ensure that the remedial actions that have been taken by the site remain effective decades into the future. Foundational to this approach is a robust, integrated data management and analysis plan to ensure accurate and timely reporting from the variety of sensor systems that are in place. This report will outline the data management plan that has been implemented by the ALTEMIS team at the Savannah River Site and will serve as a blueprint as the technology is translated to new sites across the DOE Complex.

54 ENVIRONMENTAL SCIENCES↗

Integrated Simulation Capabilities for Analysis of Experiments in the Versatile Test Reactor

The DOE-initiated Versatile Test Reactor (VTR) program aims to establish a domestic fast-neutron irradiation testing capability that meets a variety of domestic and international nuclear energy needs. Currently, integrated tools capable of mechanistic modeling of VTR and a test vehicle do not exist. To address this modeling and analysis deficiency, Argonne's SAS4A/SYSSYS-1 safety analysis code has been coupled with SAM (System Analysis Module) to provide a novel modeling capability that supports VTR and other fast test facilities. This report documents the design, implementation, and testing of this integrated capability. A coupling boundary has been identified at the test vehicle and primary coolant interface, where SAS4A/SASSYS-1 treats primary coolant thermal hydraulics outside the test vehicle, while SAM treats all thermal hydraulic behavior within the test vehicle, including the vehicle walls. Essential to this integrated tool is its newly developed capability to properly model the conjugate heat transfer process which ensures equality of temperatures and heat fluxes at the vehicle wall interface while ensuring energy conservation. A range of testing has been completed to support demonstration of this interface. The testing scope includes steady-state verification using a series of increasingly complex analytical solutions and transient demonstration for a range of design basis accident scenarios using prototypic VTR and test vehicle (i.e. cartridge loop) configurations. Results of this testing confirm verification of the steady-state solutions and provide reasonable and expected transient behavior. The coupling interface has been developed to be robust yet flexible. The implementation within SAS4A/SASSYS-1 supports coupling to any external software or module. The use of decomposed domains and the existing in-core thermal-hydraulic calculational framework within SAS4A/SASSYS-1 enable treatment of arbitrary test vehicle geometries with nonuniform meshing between SAS4A/SASSYS-1 and the coupled code. Modeling of multiple test locations is also supported. Furthermore, computational efficiency is enhanced by utilizing named pipes (or FIFOs), an interface for interprocess communication (IPC).

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

MOOSE-Based Fast Reactor Core Bowing Capabilities: Coupled Structural Mechanics – Thermal Fluids Demonstration and Related Verification Efforts

Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. Verification and assessment efforts continued on the Multiphysics Object Oriented Simulation Environment (MOOSE) capabilities relevant for modeling thermo-mechanical core bowing behavior. IAEA Verification Problem 4, which was started in FY23, was further examined with MOOSE capabilities to rectify discrepancies observed in previous years when compared to IAEA benchmark participant data. Meshing and postprocessing capabilities in MOOSE were also advanced by other teams and utilized this year. A thermal fluids-structural mechanical coupling demonstration has performed on 7-assemblyand 19-assembly fast reactor assembly configurations using MOOSE. Subchannel capabilities are used to calculate coolant temperature, and heat conduction capabilities calculate duct wall temperature as well as heat transfer through the inter-assembly gap. Structural mechanical capabilities then deform the mesh, accounting for contact between assemblies, according to the temperature gradients calculated by the thermal solvers. Power distributions are imposed rather than calculated to demonstrate different deformations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

IBR Digital Supply Chain Gap Analysis and Recommendations

The adoption of clean energy technologies, including solar photovoltaics, continues to introduce non-traditional stakeholders to the operations and planning of the electric system. Stakeholders such as manufacturers, vendors, owners, aggregators, and others are enabling the adoption, integration, and optimum operations of solar technologies at accelerated rates. Inverters form the foundation of many digitally controlled energy sources for clean energy technologies, including Solar, Battery Energy Storage Systems, Hybrid Systems, and Hydrogen Fuel Cells. Their supply chain is complex, a series of microchips, electronic switches and other components making up its primary functions. The complexity of this space and the growing digitization associated with these components can create supply chain cyber risks. One measure to mitigate cybersecurity attacks is proper digital supply chain security. The U.S. Department of Energy (DOE) Solar Energy Technologies Office (SETO), in partnership with the Cybersecurity, Energy, Security, and Emergency Response (CESER) office, is hosting a workshop to bring together solar vendors and services providers to discuss digital supply chain security for solar systems and challenges and opportunities in the transitioning to a fully domestic supply chain for solar energy in the U.S. This workshop will support the Securing Solar for the Grid (S2G) and Energy Cyber Sense program activities. During the workshop, industry experts and researchers from DOE National Laboratories will discuss the current solar supply chain landscape and the transition to domestic manufacturing of solar components in the U.S. Tools and techniques to better manage and secure the digital supply chain of solar devices and systems will be discussed.

cybersecurity↗

Dispatch optimization of concentrating solar power with utility-scale photovoltaics

Concentrating solar power (CSP) tower technologies capture thermal radiation from the sun utilizing a field of solar-tracking heliostats. When paired with inexpensive thermal energy storage (TES), CSP technologies can dispatch electricity during peak-market-priced hours, day or night. The cost of utility-scale photovoltaic (PV) systems has dropped significantly in the last decade, resulting in inexpensive energy production during daylight hours. The hybridization of PV and CSP with TES systems has the potential to provide continuous and stable energy production at a lower cost than a PV or CSP system alone. Hybrid systems are gaining popularity in international markets as a means to increase renewable energy portfolios across the world. Typically, CSP-PV hybrid systems have been evaluated using either monthly averages of hourly PV production or scheduling algorithms that neglect the time-of-production value of electricity in the market. To more accurately evaluate a CSP-PV-battery hybrid design, we develop a profit-maximizing mixed-integer linear program ($\mathcal{H}$) that determines a dispatch schedule for the individual sub-systems with a sub-hourly time fidelity. We introduce the mathematical formulation of such a model and show that it is computationally expensive to solve. To improve model tractability and reduce solution times, we offer techniques that: (1) reduce the problem size, (2) tighten the linear programming relaxation of ($\mathcal{H}$) via reformulation and the introduction of cuts, and (3) implement an optimization-based heuristic (that can yield initial feasible solutions for (($\mathcal{H}$) and, at any rate, yields near-optimal solutions). Applying these solution techniques results in a 79% improvement in solve time, on average, for our 48-h instances of (($\mathcal{H}$); corresponding solution times for an annual model run decrease by as much as 93%, where such a run consists of solving 365 instances of (($\mathcal{H}$), retaining only the first 24 h' worth of the solution, and sliding the time window forward 24 h. We present annual system metrics for two locations and two markets that inform design practices for hybrid systems and lay the groundwork for a more exhaustive policy analysis. A comparison of alternative hybrid systems to the CSP-only system reflects that hybrid models can almost double capacity factors while resulting in a 30% improvement related to various economic metrics.

14 SOLAR ENERGY↗

NEAMS Update: Quarterly report for January - March 2012

Quarterly highlights are: (1) The integration of Denovo and AMP was demonstrated in an AMP simulation of the thermo-mechanics of a complete fuel assembly; (2) Bison was enhanced with a mechanistic fuel cracking model; (3) Mechanistic algorithms were incorporated into various lower-length-scale models to represent fission gases and dislocations in UO2 fuels; (4) Marmot was improved to allow faster testing of mesoscale models using larger problem domains; (5) Component models of reactor piping were developed for use in Relap-7; (6) The mesh generator of Proteus was updated to accept a mesh specification from Moose and equations were formulated for the intermediate-fidelity Proteus-2D1D module; (7) A new pressure solver was implemented in Nek5000 and demonstrated to work 2.5 times faster than the previous solver; (8) Work continued on volume-holdup models for two fuel reprocessing operations: voloxidation and dissolution; (9) Progress was made on a pyroprocessing model and the characterization of pyroprocessing emission signatures; (10) A new 1D groundwater waste transport code was delivered to the used fuel disposition (UFD) campaign; (11) Efforts on waste form modeling included empirical simulation of sodium-borosilicate glass compositions; (12) The Waste team developed three prototypes for modeling hydride reorientation in fuel cladding during very long-term fuel storage; (13) A benchmark demonstration problem (fission gas bubble growth) was modeled to evaluate the capabilities of different meso-scale numerical methods; (14) Work continued on a hierarchical up-scaling framework to model structural materials by directly coupling dislocation dynamics and crystal plasticity; (15) New 'importance sampling' methods were developed and demonstrated to reduce the computational cost of rare-event inference; (16) The survey and evaluation of existing data and knowledge bases was updated for NE-KAMS; (17) The NEAMS Early User Program was launched; (18) The Nuclear Regulatory Commission (NRC) Office of Regulatory Research was introduced to the NEAMS program; (19) The NEAMS overall software quality assurance plan (SQAP) was revised to version 1.5; and (20) Work continued on NiCE and its plug-ins and other utilities, such as Cubit and VisIt.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The MELCOR Analysis of Chinshan Nuclear Power Plant Spent Fuel Pool for Fukushima-like Accident

The safety analysis of the nuclear power plant (NPP) is very important work in the NPP safety. Especially after the Fukushima NPP accident occurred, the importance of NPP safety analysis has been raised and there is more concern for the safety of NPPs in Taiwan. Because the earthquake and tsunami occurred, the cooling system of spent fuel pool failed and the safety issue of spent fuel pool generated in Japan's Fukushima NPP. Chinshan NPP is the first NPP in Taiwan which is BWR/4 plant and OLTP (Original Licensed Thermal Power) for each unit is 1775 MWt. Chinshan NPP finished SPU (stretch power uprate) and the operating power is 103.66% of the OLTP, which is 1840 MWt now. After Fukushima NPP accident occurred, in order to concern the safety of Chinshan NPP spent fuel pool, we performed the safety analysis of spent fuel pool by using MELCOR/SNAP which also assumed the cooling system of spent fuel pool failed. The geometry of Chinshan NPP spent fuel pool is 12.17 m x 7.87 m x 11.61 m and the initial condition is 60 deg. (water temperature) / 1.013 x 10{sup 5} Pa. And, the total power of the fuels is roughly 8.9 MWt initially. MELCOR is developed by Sandia National Laboratories. MELCOR is a fully integrated, engineering-level computer code that models the progression of severe accidents in light water reactor NPPs, including containment response and leakage of activity to the environment. A broad spectrum of severe accident phenomena in both BWRs and PWRs is treated in MELCOR in a unified framework. These include thermalhydraulic response in the reactor coolant system, reactor cavity, containment, and confinement buildings; core heatup, degradation, and relocation; core-concrete attack; hydrogen production, transport, and combustion; fission product release and transport behavior. Current uses of MELCOR include estimation of severe accident source terms and their sensitivities and uncertainties in a variety of applications. According to Dr. Carbajo's paper, MELCOR was used to perform the study of spent fuel pool of Fukushima Daiichi Unit 4. Niina E. Koenoenen used MELCOR to establish the spent fuel pool model of a Nordic BWR. The loss-of-pool-cooling accidents was simulated and analyzed by this model. The above studies indicate that MELCOR is capable of handling the simulation of the spent fuel pool. An increasing number of researchers are using MELCOR code to analyze test facilities and nuclear power plants. Jun Wang et al. used MELCOR to perform core degradation simulation and MELCOR results were compared with CORA experimental data. Through this work, they reviewed the performance of MELCOR COR package in detail. Tae Woon Kim et al. developed MELCOR model of APR1400 (an advanced pressurized water reactor). They used this model to perform the LBLOCA transient simulation and sensitivity study. Longze Li et al. established the MELCOR model of CPR1000 (a Chinese pressurized reactor 1000-MW power plant). The station blackout (SBO) with failure of the steam generator (SG) safety relief valve (SRV) transient was simulated and analyzed by this model. SNAP is a graphic user interface program that processes the inputs and outputs of MELCOR. In addition, there is an animation function in SNAP which can present the animation of analysis results. There are two main steps in this research. The first step was the establishment of Chinshan NPP spent fuel pool MELCOR/SNAP model. And the transient analysis of Chinshan NPP spent fuel pool MELCOR/SNAP model under the cooling system failure condition was performed. The next step was the comparison among the MELCOR, TRACE and CFD data. TRACE and CFD data were from INER reports. In addition, the animation model of Chinshan NPP spent fuel pool was presented by using the animation function of SNAP with MELCOR/SNAP analysis results. This study has developed MELCOR/SNAP model of Chinshan NPP spent fuel pool successfully. By using the above model, the safety analysis of the spent fuel pool was performed under the cooling system of spent fuel pool failed condition. The analysis results of MELCOR, TRACE and CFD were similar in this case. It indicated that there was a respectable accuracy in MELCOR/SNAP model. The analysis results depicted that the uncovered of the fuels occurred at 2.6 day and the metal-water reaction of fuels occurred roughly at 3.7 day after the cooling system failed. The above results indicated that the failure of cladding occurred after 3.7 day. This study's results can help to evaluate the safety issue of Chinshan NPP spent fuel pool. In addition, the cooling system and some mitigation measures of spent fuel pool is not simulated in the above model. However, we will do it in the future. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Creating an Interprocedural Analyst-Oriented Data Flow Representation for Binary Analysts (CIAO)

National security missions require understanding third-party software binaries, a key element of which is reasoning about how data flows through a program. However, vulnerability analysts protecting software lack adequate tools for understanding data flow in binaries. To reduce the human time burden for these analysts, we used human factors methods in a rolling discovery process to derive user-centric visual representation requirements. We encountered three main challenges: analysis projects span weeks, analysis goals significantly affect approaches and required knowledge, and analyst tools, techniques, conventions, and prioritization are based on personal preference. To address these challenges, we initially focused our human factors methods on an attack surface characterization task. We generalized our results using a two-stage modified sorting task, creating requirements for a data flow visualization. We implemented these requirements partially in manual static visualizations, which we informally evaluated, and partially in automatically generated interactive visualizations, which have yet to be integrated into workflows for evaluation. Our observations and results indicate that 1) this data flow visualization has the potential to enable novel code navigation, information presentation, and information sharing, and 2) it is an excellent time to pursue research applying human factors methods to binary analysis workflows.

42 ENGINEERING↗