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At least 577 records · Page 32

An approach to separating Pu, U, and Ti from high-purity graphite for isotopic analysis by MC-ICP-MS

Information about elemental and isotopic systematics of ultra-trace level actinides (e.g. U and Pu) and main group elements (e.g. Ti) present within nuclear grade graphite is vital to the nuclear community for improved reactor operation and security. In support of this, extensive effort has been placed on improving analysis methods (i.e., inductively coupled plasma-mass spectrometry). However, significantly less effort has been devoted to the optimization of chemical separation methods. Within the separation community, commercially available Eichrom™ resins are often employed, as their elution characteristics for various elements have been well studied, but the direct optimization of actinides and trace metal separations from a single sample have not been widely investigated. Here, methods using various Eichrom pre-packed cartridges were explored to achieve separation of ultra-trace levels of U, Pu, and Ti from a variety of graphite samples. Once the validity of the combined separation scheme was established using certified reference materials, the method was applied to historic, unirradiated and irradiated, graphite samples. For all samples investigated, precise isotope ratio measurements for the titanium isotope systems were made.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Advanced Tri-lab Software Environment (ATSE)

The Advanced Tri-lab Software Environment (ATSE) is an effort to build an open, modular, extensible, community-engaged, and vendor-adaptable software ecosystem that enables the prototyping of new technologies for improving the ASC computing environment. The initial target for ATSE is to accelerate the maturity of the Arm ecosystem for supporting ASC computing and the high-performance computing community more broadly. ATSE provides an integrated and optimized software stack that includes: 1) Application development environment and libraries including compilers, math libraries, tools, MPI, and OpenMP, 2) Low-level system software including optimized Linux, network stack, file systems, containers, and virtual machines, 3) Job scheduling and management including workload manager, application launcher, and user tools, and 4) System administration and management tools supporting booting, monitoring, and operating system image management. SAND2020-12377 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Younge, Andrew J.↗

Status of Low Thrust Work at JSC

High performance low thrust (solar electric, nuclear electric, variable specific impulse magnetoplasma rocket) propulsion offers a significant benefit to NASA missions beyond low Earth orbit. As NASA (e.g., Prometheus Project) endeavors to develop these propulsion systems and associated power supplies, it becomes necessary to develop a refined trajectory design capability that will allow engineers to develop future robotic and human mission designs that take advantage of this new technology. This ongoing work addresses development of a trajectory design and optimization tool for assessing low thrust (and other types) trajectories. This work targets to advance the state of the art, enable future NASA missions, enable science drivers, and enhance education. This presentation provides a summary of the low thrust-related JSC activities under the ISP program and specifically, provides a look at a new release of a multi-gravity, multispacecraft trajectory optimization tool (Copernicus) along with analysis performed using this tool over the past year.

Condon, Gerald L.↗

Atmospheric Mining in the Outer Solar System: Aerial Vehicle Mission and Design Issues

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. With these two additional gases, the potential for fueling small and large fleets of additional exploration and exploitation vehicles exists. The mining aerospacecraft (ASC) could fly through the outer planet atmospheres, for global weather observations, localized storm or other disturbance investigations, wind speed measurements, polar observations, etc. Analyses of orbital transfer vehicles (OTVs), landers, and in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points.

orbital mechanics↗

Hydrogen Recombiner Catalyst Evaluations for Waste Storage

Radiolysis of water in nuclear waste storage generates hydrogen gas that can accumulate within sludge style waste and be rapidly released during agitation events, creating a significant flammability hazard. Engineering controls are therefore required to limit hydrogen concentrations during both quiescent storage and transient disturbances. Catalytic recombination of hydrogen in waste storage offgas is a proven mitigation strategy, maintaining hydrogen levels below flammability limits and managing sudden concentration spikes. Conventional recombiners rely on platinum and/or palladium catalysts, with development efforts focused on extending service life, increasing active surface area, and ensuring safe deployment in radioactive environments. Savannah River National Laboratory (SRNL) is evaluating a newly developed hydrogen recombiner catalyst from Canadian Nuclear Laboratories as a cost-effective and durable alternative for nuclear waste applications. Testing was conducted in SRNL’s Shielded Cells facility, which enables reduced-scale experimental modeling under radiation fields and near-use-case conditions relevant to radioactive waste storage. Catalyst performance was evaluated using a custom offgas characterization system designed for near-zero flow conditions. The experimental apparatus consisted of a gas-tight 2.7 L PTFE vessel equipped with temperature monitoring, gas flow controls, and a variable-speed mixer to simulate sludge agitation. Offgas composition was monitored using a dedicated gas chromatograph with argon carrier gas and a krypton internal standard. Measurements were obtained for an empty vessel, the vessel containing a well characterized radioactive tank waste sample, and the same configuration with the candidate catalyst installed. Results demonstrate that the new catalyst effectively reduced hydrogen concentrations in the offgas within the constraints of the experimental design. In addition to confirming catalytic activity, the testing provided valuable insights into experimental optimization and considerations for future performance evaluations. These findings support the potential scalability of the technology and highlight its applicability to broader nuclear waste management operations, offering improved safety and reduced operational costs through enhanced catalyst durability and lower replacement frequency.

Tener, Zachary P. [Savannah River National Laborat↗

Newton trust-region methods with primary variable switching for simulating high temperature multiphase porous media flow

Coupling multiphase flow with energy transport due to high temperature heat sources introduces significant new challenges since boiling and condensation processes can lead to dry-out conditions with subsequent re-wetting. The transition between two-phase and single-phase behavior can require changes to the primary dependent variables adding discontinuities as well as extending constitutive nonlinear relations to extreme physical conditions. Practical simulations of large-scale engineered domains lead to Jacobian systems with a very large number of unknowns that must be solved efficiently using iterative methods in parallel on high-performance computers. Performance assessment of potential nuclear repositories, carbon sequestration sites and geothermal reservoirs can require numerous Monte-Carlo simulations to explore uncertainty in material properties, boundary conditions, and failure scenarios. Due to the numerical challenges, standard NR iteration may not converge over the range of required simulations and require more sophisticated optimization method like trust-region. In this study, we use the open-source simulator PFLOTRAN for the important practical problem of the safety assessment of future nuclear waste repositories in the U.S. DOE geologic disposal safety assessment Framework. The simulator applies the PETSc parallel framework and a backward Euler, finite volume discretization. We demonstrate failure of the conventional NR method and the success of trust-region modifications to Newton’s method for a series of test problems of increasing complexity. Trust-region methods essentially modify the Newton step size and direction under some circumstances where the standard NR iteration can cause the solution to diverge or oscillate. Furthermore, we show how the Newton Trust-Region method can be adapted for Primary Variable Switching (PVS) when the multiphase state changes due to boiling or condensation. The simulations with high-temperature heat sources which led to extreme nonlinear processes with many state changes in the domain did not converge with NR, but they do complete successfully with the trust-region methods modified for PVS. This implementation effectively decreased weeks of simulation time needing manual adjustments to complete a simulation down to a day. Finally, we show the strong scalability of the methods on a single node and multiple nodes in an HPC cluster.

54 ENVIRONMENTAL SCIENCES↗

NEAMS Technical Area Support in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) framework is a foundational capability used by the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program to create over 15 different simulation tools for advanced nuclear reactors. Due to this ubiquity, improvements to the framework in support of modeling and simulation goals are critical to the program. These improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work transcribed in this report was conducted in direct support of the simulation tools and has already been deployed. The capabilities outlined in this report include addition of Times and Positions systems, redesign of mechanical contact constraints to enable the augmented Lagrange algorithm, overhaul of the restart system, and incorporation of p-refinement in MOOSE.

97 MATHEMATICS AND COMPUTING↗

Waste Management Project Success - Regulatory Assurance Systems - 20118

Waste management (WM) and remediation projects are essential within a restorative environmental culture. Despite years of experience, challenges and obstacles associated with efficient and effective WM project execution remain. Although some obstacles are project specific, a common challenge is navigating the regulatory landscape from planning through execution, particularly with first of a kind (FOAK) and first in a while (FIAW) projects. The absence of a comprehensive regulatory assurance strategy places significant hurdles in the path of project success. To clear a path for the successful execution of increasingly complex WM projects, this paper focuses on development of a comprehensive regulatory assurance strategy and implementation plan that effectively engages stakeholders, agencies, and performers to produce project plans that fully and cost effectively integrate applicable regulatory requirements. The most reliable way to align regulatory processes and decisions needed for mission success is through a regulatory assurance system. This system establishes a healthy interface with regulatory decision makers, to work in a collaborative manner, to create a common vision for regulatory decisions on an agreed upon schedule. A regulatory assurance system consists of several elements. Although the mission may vary from cleanup to site closure to nuclear component production, the elements of a regulatory assurance system remain essentially constant and must include: 1) identifying a common vision or end state, 2) developing a long-term, integrated strategy and schedule, 3) establishing a regulatory partnering team consisting of key decision-makers, 4) regular and frequent communication with decision-makers, 5) ensuring consistent surveillance for early identification of issues and changes that may impact the project, 6) quick resolution of emerging issues to prevent schedule impact, 7) identifying core compliance functions, 8) periodically assessing progress of the project as it relates to regulatory assurance and, 9) providing constructive feedback to improve the process. A regulatory assurance system provides a living, multi-faceted approach to planning, visioning, communicating and tracking to avoid surprises and ensure smooth and timely progress to the project. The overall success measures will be whether the system produces common sense regulatory decisions supporting the vision on time without appeal. Effective regulatory frameworks rarely happen on their own. Balanced, common-sense regulatory decisions stem from teams that are trained to work together to achieve shared goals. In this paper, particular attention is placed on the importance of starting with a shared vision for a regulatory assurance and execution strategy that leverages experience to establish optimal approaches. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

A Crewed Mission to Apophis Using a Hybrid Bimodal Nuclear Thermal Electric Propulsion (BNTEP) System

A BNTEP system is a dual propellant, hybrid propulsion concept that utilizes Bimodal Nuclear Thermal Rocket (BNTR) propulsion during high thrust operations, providing 10's of kilo-Newtons of thrust per engine at a high specific impulse (Isp) of 900 s, and an Electric Propulsion (EP) system during low thrust operations at even higher Isp of around 3000 s. Electrical power for the EP system is provided by the BNTR engines in combination with a Brayton Power Conversion (BPC) closed loop system, which can provide electrical power on the order of 100's of kWe. High thrust BNTR operation uses liquid hydrogen (LH2) as reactor coolant propellant expelled out a nozzle, while low thrust EP uses high pressure xenon expelled by an electric grid. By utilizing an optimized combination of low and high thrust propulsion, significant mass savings over a conventional NTR vehicle can be realized. Low thrust mission events, such as midcourse corrections (MCC), tank settling burns, some reaction control system (RCS) burns, and even a small portion at the end of the departure burn can be performed with EP. Crewed and robotic deep space missions to a near Earth asteroid (NEA) are best suited for this hybrid propulsion approach. For these mission scenarios, the Earth return V is typically small enough that EP alone is sufficient. A crewed mission to the NEA Apophis in the year 2028 with an expendable BNTEP transfer vehicle is presented. Assembly operations, launch element masses, and other key characteristics of the vehicle are described. A comparison with a conventional NTR vehicle performing the same mission is also provided. Finally, reusability of the BNTEP transfer vehicle is explored.

Electric Propulsion↗

Sum-of-Fractions Methodology for Actinides in Water- and Polyethylene-Moderated and -Reflected Systems

Sum-of-fractions is a method intended to make sure a subcritical margin for aqueous solutions and slurries of fissionable isotopes exists. The method indicates that a system is subcritical if the sum of the ratios of the mass of each isotope (in a mixture) to its individual minimum subcritical mass limit is less than or equal to one. Historically, the basis of the sum-of-fractions has been derived from allowances given in the American National Standards Institute (ANSI)/ American Nuclear Society (ANS)-8.15-1981. However, the allowance was removed in ANSI/ANS-8.15-2014 due to a lack of technical basis. A methodology was developed to assess the validity of using the sum-of-fractions for water- or polyethylene-moderated systems for the following nuclides: 232 U, 233 U, 234 U, 235 U, 237 Np, 236 Pu, 238 Pu, 239 Pu, 240 Pu, 241 Pu, 242 Pu, 241 Am, 242 m Am, 243 Am, 242 Cm, 243 Cm, 244 Cm, 245 Cm, 246 Cm, 247 Cm, 249 Cf, and 251 Cf. The methodology uses available benchmark data for mixtures of 233 U, 235 U, and 239 Pu to establish the calculational margin, and a mass limit reduction to establish the margin of subcriticality. Water- or polyethylene-moderated and -reflected mixtures containing the nuclides are evaluated with the code system, SCALE 6.2.4. Including the calculational margin, subcritical mass limits for each nuclide were computed for optimally water- or polyethylene-moderated and fully reflected systems. These masses were used to create nuclide mixtures in which the sum of the mass to subcritical mass limit ratios is one. The various nuclide mixtures were modeled over a range of moderation and demonstrate the keff does not exceed the calculational margin. For additional assurance of subcriticality, a significant mass reduction is applied to each computed minimum critical mass of the nuclides without adequate benchmark data consistent with the method in ANSI/ANS-8.15-2014.

07 ISOTOPE AND RADIATION SOURCES↗

Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems

Abstract Maintenance optimization is a process for improving the efficiency of maintenance strategies and activities, considering various aspects of the target system and components, such as the probabilities of system failures and the cost of repair and replacement of a failed component. The improvement of maintenance optimization algorithms generally requires information from various data sources. For example, it may require the system risk information derived from risk analysis tools or the residual lifetime of a component from fault prognosis tools. The requirements of data acquisition (DAQ) and aggregation pose new challenges for maintenance management systems (MMSs) that implement and use these maintenance optimization algorithms. This paper proposes a multiple aspects maintenance ontology-based framework to facilitate DAQ from MMSs, online monitoring systems, fault detection and discrimination tools, risk assessment tools, decision-making tools, and component identification tools, and accelerate the implementation and verification of contemporary maintenance optimization models and algorithms. The proposed framework consists of a multi-aspect maintenance ontology with critical information for maintenance optimization and application interfaces for collecting information from various data sources, such as fault prognosis tools, online monitoring tools, risk assessment tools, and decision-making algorithms. In addition, this paper proposes a heuristic method for integrating concepts and properties from other existing ontologies into the proposed framework when the existing ontology is not fully compatible with the ontology under construction. Finally, the paper verifies the proposed ontology framework using a feedwater system designed for nuclear power plants with valves and filters as the components under maintenance.

Diao, Xiaoxu (ORCID:0000000346726352)↗

Thermal Energy Storage Model Development within the Integrated Energy Systems Hybrid Repository

This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of concrete, latent heat, and packed-bed thermocline energy storage technologies for deployment in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to cyclically charge and discharge when exposed to time-varying boundary conditions. In addition, low-level surrogate models for some of the thermal energy storage technologies were created using Python. These lower order Python files are much cheaper to run (i.e., computationally faster) and thus operate well when incorporated within the stochastic optimization problems run for the IES program. Moreover, economic data was collected for use within the INL-developed Framework for Optimization of ResourCes and Economics (FORCE). This information is incorporated within the FORCE platform. This work has resulted in creation of systems-level models for concrete, latent heat, and thermocline thermal energy storage systems with associated control systems. Now that these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies (e.g., Storworks Power, EnergyNest) can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.

25 ENERGY STORAGE↗

Reference document for LANL stack sampling and ANSI N13.1 (Article) Gielow RL and McNamee MR 1993. Numerical Flue Gas Flow Modeling for Continuous Emissions Monitoring Applications. EPRI CEM Users Group Meeting. Baltimore. RP1961-13

American National Standard N13.1 “sets forth guidelines and performance criteria for sampling the emissions of airborne radioactive substances in the air discharge ducts and stacks of nuclear facilities. Emphasis is on extractive sampling from a location in a stack or duct where the contaminant is well mixed. At such a location, sampling may be conducted at a single point. This standard provides performance-based criteria for the use of air sampling probes, transport lines, sample collectors, sample monitoring instruments, and gas flow measuring methods. This standard also covers sampling program objectives, quality assurance issues, developing air sampling action levels, system optimization, and system performance verification. Workplace, containment, and environmental air monitoring are not addressed. Specific sample analysis methods and the reporting or interpreting of results are also not addressed.” (HPS 2011).

61 RADIATION PROTECTION AND DOSIMETRY↗

Improved Nuclear Reactor and Shield Mass Model for Space Applications

New technologies are being developed to explore the distant reaches of the solar system. Beyond Mars, solar energy is inadequate to power advanced scientific instruments. One technology that can meet the energy requirements is the space nuclear reactor. The nuclear reactor is used as a heat source for which a heat-to-electricity conversion system is needed. Examples of such conversion systems are the Brayton, Rankine, and Stirling cycles. Since launch cost is proportional to the amount of mass to lift, mass is always a concern in designing spacecraft. Estimations of system masses are an important part in determining the feasibility of a design. I worked under Michael Barrett in the Thermal Energy Conversion Branch of the Power & Electric Propulsion Division. An in-house Closed Cycle Engine Program (CCEP) is used for the design and performance analysis of closed-Brayton-cycle energy conversion systems for space applications. This program also calculates the system mass including the heat source. CCEP uses the subroutine RSMASS, which has been updated to RSMASS-D, to estimate the mass of the reactor. RSMASS was developed in 1986 at Sandia National Laboratories to quickly estimate the mass of multi-megawatt nuclear reactors for space applications. In response to an emphasis for lower power reactors, RSMASS-D was developed in 1997 and is based off of the SP-100 liquid metal cooled reactor. The subroutine calculates the mass of reactor components such as the safety systems, instrumentation and control, radiation shield, structure, reflector, and core. The major improvements in RSMASS-D are that it uses higher fidelity calculations, is easier to use, and automatically optimizes the systems mass. RSMASS-D is accurate within 15% of actual data while RSMASS is only accurate within 50%. My goal this summer was to learn FORTRAN 77 programming language and update the CCEP program with the RSMASS-D model.

Robb, Kevin↗

ASTROS: A multidisciplinary automated structural design tool

ASTROS (Automated Structural Optimization System) is a finite-element-based multidisciplinary structural optimization procedure developed under Air Force sponsorship to perform automated preliminary structural design. The design task is the determination of the structural sizes that provide an optimal structure while satisfying numerous constraints from many disciplines. In addition to its automated design features, ASTROS provides a general transient and frequency response capability, as well as a special feature to perform a transient analysis of a vehicle subjected to a nuclear blast. The motivation for the development of a single multidisciplinary design tool is that such a tool can provide improved structural designs in less time than is currently needed. The role of such a tool is even more apparent as modern materials come into widespread use. Balancing conflicting requirements for the structure's strength and stiffness while exploiting the benefits of material anisotropy is perhaps an impossible task without assistance from an automated design tool. Finally, the use of a single tool can bring the design task into better focus among design team members, thereby improving their insight into the overall task.

Neill, D. J.↗

TCR Central Shutdown Rod Fine Motion Control

Transformational Challenge Reactor (TCR) is a Helium cooled 3 MWt test reactor that leverages advances in materials and manufacturing, computing, and AI in its design. Classical design of a shutdown rod uses either gravity, pneumatic, or springs to quickly release the Central Shutdown Rod (CSR) containing neutron absorber into the reactor core stopping nuclear reaction. Generally, the motor/actuator resides outside the reactor, but the motion is transmitted through a penetration into the pressure vessel. There are also designs where the control rod drive incorporates magnetic latches with coil residing outside the pressure boundary for precise position control of the rod. We are proposing a magnetic coupling to position the shutdown rod without any penetration into the pressure vessel for the entire drive length of TCR shutdown rod. Electromagnets are currently used in non-power nuclear reactors for shutdown rods, but these electromagnets are resident inside the reactor pressure vessel. This paper will describe the use of an electromagnet outside the pressure vessel to position and release the shutdown rod. A prototype was developed at ORNL to demonstrate the concept, and a design optimization of the ferritic core and material was conducted to maximize the lift force of the electromagnet. An elevated temperature testing was also performed to ensure that the system will perform under the temperature conditions inside an operating reactor.

Fountain, Eliott J.↗

Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power

Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.

08 HYDROGEN↗

A hybrid surrogate modeling framework for the Digital Twin of a Fluoride-salt-cooled High-temperature Reactor (FHR)

While nuclear energy is a non-greenhouse-gas emitting energy source, expensive operational costs due to the high-level of safety requirements decreases their competitiveness in the sustainable energy market. Advanced reactor concepts paired with Digital Twins aim to increase the commercialization gains of nuclear energy by reducing operational costs, increasing reactor reliability and enhancing power generation. To support Digital Twin tasks such as real-time autonomous control, proactive maintenance monitoring or optimizing power demand operations, a fast and accurate virtual representation of the Nuclear Power Plant (NPP) is required. The computational cost of high-fidelity, physics-based models are unsuitable for real-time analysis or scalability. Here, in this work, a hybrid surrogate modeling framework is developed fora Fluoride-salt-cooled High-temperature Reactor (FHR) that leverages physics-inspired models for key reactor components and uses data-driven methods for rapid system state space prediction. The Xenon reactivity feedback model is integrated to inform the surrogate model about the reactor core and the homologous pump theory model is the basis for representing pump degradation. Using a detailed, two dimensional thermal hydraulics model to generate data on the FHR, we train a network of Vectorized Autoregressive Moving-Average with eXogenous input (VARMAX) models to predict the remaining state values. The result is a surrogate model that provides a detailed reactor state representation of 41 system states and a pump degradation analysis. The framework is applied to Load Follows profiles, yielding high accuracy and a speedup that is more than 4000x faster compared to the higher- fidelity thermal hydraulics model, enabling real-time operational intelligence and applications in long horizon predictions. While the surrogate model framework is demonstrated for the particular case of FHR, the hybrid physical/data-driven modeling approach including the network of surrogates and the underlying modularity has the potential to be applied to other physical asset systems.

Digital Twins↗