Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “optimization of nuclear systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulation of Liquid Lithium Divertor Geometry Using SOLPS-ITER

Here, plasma-facing component (PFC) geometries are evaluated for a Fusion Nuclear Science Facility (FNSF) design to find solutions that are compatible with flowing liquid lithium components while satisfying requirements from the perspective of plasma and neutral particle transport. Flowing liquid metal (LM) divertor systems offer important advantages due to continual regeneration of the surface material, but may require modifications from standard optimized tokamak divertor designs. Scrape Off Layer Plasma Simulator for the International Thermonuclear Experimental Reactor (SOLPS-ITER) simulations are used to compare standard vertical target, open, and balanced baffled geometries. It is found that the open geometry offers little control of neutral particles and has narrow operating windows where the divertor fluxes can be lowered to acceptable levels, while maintaining the required upstream density. The addition of neutral baffles allows greater control over the divertor conditions with less impact on the upstream density. The divertor neutral pressure in the baffled geometry is slightly higher than the open divertor, but not as large with a vertical target. A first-pass coupling of the SOLPS solution with sheath and implantation/erosion models to compute the lithium emission shows that the lithium is largely confined to the near-surface region due to the small ionization mean free path and large main ion flow toward the surface. The lithium source was varied by three orders of magnitude. At the highest rate, when the sourced lithium approaches the level of the main ion recycling flux, a high core lithium concentration (~10%) is observed with only moderate power dissipation to affect the divertor plasma.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Massively Parallel Bayesian Model Calibration and Uncertainty Quantification with Applications to Nuclear Fuels and Materials

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. Fuel behavior in a nuclear reactor is governed by a complex network of mechanisms interacting with various other physics aspects in the reactor system. Any model developed to represent the fuel behavior will likely be idealized resulting in uncertainties in their predictions compared to the observed data. As such, this report was motivated by the need to identify the sources of uncertainties and quantify and propagate them through the fuel model outputs. Such quantification of uncertainties will establish a level of model trustworthiness, identify approaches to improve the model trustworthiness, and even guide optimal experiment design for maximal information gain. To accomplish the uncertainty quantification for computational models, this report has relied on the Bayesian framework which provides probabilistic treatment of models their inputs and outputs. The current state-of-the-art on performing Bayesian Uncertainty Quantification (UQ) for nuclear engineering models using High Performance Computing (HPC) resources have been reviewed. Implementation of capabilities for massively parallel Bayesian UQ in Multiphysics Object-Oriented Simulation Environment (MOOSE) is discussed. Several verification cases are discussed to verify the accuracy of the quantified uncertainties using the developed computational capabilities in MOOSE. Then, the problem of quantifying the uncertainties in TRI-Structural isOtropic (TRISO) fuel silver release is addressed. For the first time, the uncertainties arising from the TRISO Fission Gas Release (FGR) model due to model inadequacy and experimental noise are quantified. Also, the Bayesian capabilities are applied to the calibration of the MATPRO creep model, a widely used model in several fuel assessment cases. The impact of the prediction uncertainties in the MATPRO model on the fuel cladding behavior as part of the TRIBULATION assessment case (which is an integral effects case) is investigated. This report concludes with a discussion on the future work for the UQ for computational models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2006

Should We Enhance the Observing Systems or Improve Coordination Among the Operating Agencies: What is Needed the Most for Security--A Philosophical Discussion

As an integrated observing strategy, the concept of sensorweb for Earth observations is appealing in many aspects. For instance, by increasing the spatial and temporal coverage of observations from space and other vantage points, one can eventually aid in increasing the accuracy of the atmospheric models which are precursor to hurricane track prediction, volcanic eruption forecast, and trajectory path of transcontinental transport of dust, harmful nuclear and chemical plumes. In reality, there is little analysis available in terms of benefits, costs and optimized set of sensors needed to make these necessary observations. This is a complex problem that must be carefully studied and balanced over many boundaries such as science, defense, early warning, security, and surveillance. Simplistically, the sensorweb concept from the technological point of view alone has a great appeal in the defense, early warning and security applications. In fact, it can be relatively less expensive in per unit cost as opposed to building and deploying it for the scientific use. However, overall observing approach should not be singled out and aligned somewhat orthogonally to serve a particular need. On the other hand, the sensorweb should be designed and deployed to serve multiple subject areas and customers simultaneously; and can behave as directed measuring systems for both science and operational entities. Sensorweb can be designed to act as expert systems, and/or also provide a dedicated integrated surveillance network. Today, there is no system in the world that is fully integrated in terms of reporting timely multiple hazards warnings, computing the loss of life and property damage estimates, and is also designed to cater to everyone's needs. It is not an easier problem to undertake and more so is not practically solvable. At this time due to some recent events in the world, the scientific community, social scientists, and operational agencies are more cognizant and getting together to address such colossal problems. Increasing our knowledge of the home planet, via amplified set of observations, is certainly a right step in a right direction. Furthermore, this is a pre-requisite in understanding multiple hazard phenomenas. This paper examines various sensorweb options and observing architectures that can be useful specifically in addressing some of these complex issues. The ultimate goal is to serve the society by providing potential natural hazards information to the decision makers in the most expeditious manner so they can prepare themselves to mitigate potential risks to human life, livestock and property.

Habib, Shahid↗
DOE OSTI2022

Proposal and application of ROM-Lasso method for sensitivity coefficient evaluation

We propose a novel method for evaluating sensitivity coefficients of neutronics parameters to cross sections, so-called the reduced-order modeling technique ROM-Lasso. In this method, cross sections of interest are randomly sampled, and corresponding perturbed core analyses are performed. Then, the sensitivity coefficient vector of the higher-level model is expanded via the active subspace bases obtained with the lower-level model whose dimensional complexity is smaller than that of the higher-level model, and the expansion coefficients are estimated by the Lasso regression. A unique feature of the ROM-Lasso method allows the use of different bases optimized for each neutronics parameter. We conducted a verification calculation for an accelerator-driven system and demonstrated that the ROM-Lasso method can reproduce the sensitivity coefficients with a much smaller number of forward calculations than the direct method. The proposed method can be used to practically evaluate sensitivity coefficients. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Dynamic System Scaling Application to Accelerated Nuclear Fuel Testing

The development of nuclear fuel and materials requires a continuous effort to investigate the acute and prolonged effects of irradiation, thermal-material stress, chemical change, or other conceivable damage mechanics acquired during normal operation or accident scenarios throughout its lifetime. As in-core fuel property measurement techniques advance to support in the real-time, non-invasive, and enhanced accuracy realm, it is the future of fuel development to pursue to higher degrees of control, predictability of integral test behavior via separate effects test (SET), and shorter test time intervals. The fuel development life cycle from initial concept to commercial licensing is approximated to be 20 years and current literature suggests by optimizing fuel performance codes with SETs, the process could possibly be compressed to 5 to 10 years. Recently, a research group in the Idaho National Laboratory (INL) is testing reduced scale fuel rods and increased power density to accelerate evolution of fuel phenomena in metallic fuels. In support of nuclear fuel rod development, compressing fuel test process, and accelerating fuel phenomena, it was the purpose of this study to investigate nuclear fuel performance phenomena via literature review and effectively scale the initial conditions, boundary conditions, and geometric properties to describe the time-dependent response including to fuel burnup, thermal and mechanical stress, transmutations and inter-diffusion, and other relevant observed phenomena. The study was based on BISON simulations of historic EBR-II metallic fuel experiments and Dynamical System Scaling (DSS) method are utilized to assess effects of scaling activity including fuel phenomena acceleration and calculations of time-dependent distortions. The research successfully scaled metallic fuel phenomena, accelerated fuel testing, and assessed the distortions for each scaled case derived.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

SDOM (Storage Deployment Optimization Model) [SWR-21-73]

SDOM is designed to accurately represent the operation of energy storage across different timescales, including long-duration and seasonal applications, and the spatiotemporal diversity and complementarity among VRE sources. SDOM uses an hourly temporal resolution, a fine spatial resolution for VRE sources, and a 1-year optimization window. SDOM assumes that all builds of VRE are accompanied by sufficient additional transmission capacity to allow full utilization of these additional resources. Nuclear, hydropower, and other renewable generation (e.g., biomass and geothermal energy sources) are fixed based on operational data (time series) for a given year; thus, SDOM minimizes total system cost using conventional generators as balancing units and using VRE and storage technologies to achieve a user-defined carbon-free or renewable energy target. The total system cost includes capital costs, fixed operation-and-maintenance (FO&M) costs, variable operation-and-maintenance (VO&M) costs, and fuel cost for power generation and storage technologies.

Guerra Fernandez, Omar Jose↗
NASA NTRS1977

Competitively priced hydrogen via high-efficiency nuclear electrolysis

A fully dedicated nuclear-electrolytic hydrogen-production facility, based on advanced (1985) technology, has been synthesized and assessed at the conceptual level. The facility integrates an HTGR operating a binary shaftpower-extraction cycle at 980 C top temperature, direct dc electricity generation via acyclic generators, and high-current density high-pressure electrolyzers based on the solid polymer electrolyte approach. All subsystems are close-coupled and optimally interfaced. Pipeline-pressure hydrogen and coproduct oxygen are produced at 6900 kPa. On consistent costing bases, the advanced facility concept was found to provide hydrogen costs that were approximately half those associated with conventional, contemporary-technology nuclear electrolysis. The nuclear heat-to-hydrogen energy conversion efficiency for the advanced system was estimated as 43%, against 25% for the baseline present-day approach.

Escher, W. J. D.↗
DOE OSTI2024

Mitigating Green's function Monte Carlo signal-to-noise problems using contour deformations

The Green's function Monte Carlo (GFMC) method provides accurate solutions to the nuclear many-body problem and predicts properties of light nuclei starting from realistic two- and three-body interactions. Controlling the GFMC fermion sign problem is crucial, as the signal-to-noise ratio decreases exponentially with imaginary time, requiring significant computing resources. Inspired by similar scenarios in lattice quantum field theory and spin systems, in this work, we employ integration contour deformations to improve the GFMC signal-to-noise ratio. Machine learning techniques are used to select optimal contours with minimal variance from parametrized families of deformations. As a proof of principle, we consider the deuteron binding energies and Euclidean density response functions. Here, we only observe mild signal-to-noise improvement for the binding energy case. On the other hand, we achieve an order of magnitude reduction of the variance for Euclidean density response functions, paving the way for computing electron- and neutrino-nucleus cross sections of larger nuclei.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Potential Supply Chain and Cost Reduction Strategies for Advanced Nuclear Reactors

This milestone represents a level of effort to provide recommendations for a supply chain plan and establish relationships between advanced reactor companies and large companies in the oil & gas and chemical industries. It represents a starting point to develop the plan with options, general equipment lists, and rough associated cost estimates of major equipment and the associated systems needed. This effort will provide an opportunity to leverage the experience that oil & gas and chemicals companies possess in large capital equipment procurement, modularization, acquisition and installation. Potential supply chain solutions will be discussed and preliminary options for worldwide manufacturers will be elucidated. The goal of this effort will be to leverage the years of accumulated experience in the oil & gas and chemical industries in the area of capital equipment acquisition to understand the potential supply chain options and to reduce potential acquisition costs by optimizing the supply chain options for advanced nuclear reactor modularization, manufacturing and acquisition.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1977

Annual Conference on Nuclear and Space Radiation Effects, 14th, College of William and Mary, Williamsburg, Va., July 12-15, 1977, Proceedings

Topics related to processing and hardness assurance are considered, taking into account the radiation hardening of CMOS technologies, technological advances in the manufacture of radiation-hardened CMOS integrated circuits, CMOS hardness assurance through process controls and optimized design procedures, the application of operational amplifiers to hardened systems, a hard off-the-shelf SG1524 pulse width modulator, and the gamma-induced voltage breakdown anomaly in a Schottky diode. Basic mechanisms are examined, giving attention to chemical and structural aspects of the irradiation behavior of SiO2 films on silicon, experimental observations of the chemistry of the SiO2/Si interface, leakage current phenomena in irradiated SOS devices, the avalanche injection of holes into SiO2, the low-temperature radiation response of Al2O3 gate insulators, and neutron damage mechanisms in silicon at 10 K. Other subjects discussed are related to radiation effects in devices and circuits, space radiation effects, and aspects of simulation, energy deposition, and dosimetry.

Stahl, R. H.↗
DOE OSTI2022

Integrated Risk-Informed Condition Based Maintenance Capability and Automated Platform: Technical Report 3

This project is a collaborative research effort between PKMJ Technical Services LLC, Idaho National Laboratory, and Public Service Enterprise Group (PSEG) Nuclear, LLC. The collaboration, led by PKMJ Technical Services LLC, is part of the industry Funding Opportunity Announcement (FOA) award under Advanced Nuclear Technology Development FOA #DE-FOA-0001817. The pilot demonstration focuses on the Circulating Water System (CWS), an important non-safety-related system that impacts the power generation capability of the plant site. Achieving riskinformed condition-based Predictive Maintenance (PdM) on the CWS will result in significant economic benefits, and the developed methodologies can also be applied to other plant systems. This approach supports an industry goal of ensuring that nuclear power generation remains a viable, economically competitive option in the energy market. Operation and Maintenance (O&M) costs include labor-intensive Preventive Maintenance (PM) programs that involve manually performed inspection, calibration, testing, and maintenance of plant assets at periodic frequencies as well as time-based replacement of assets, irrespective of condition. This project offers an alternative by focusing on riskinformed condition-based maintenance to reduce O&M costs while still maintaining plant health and safety. This report summarizes the progress made toward achieving a risk-informed condition-based maintenance approach. The research and development (R&D) activities presented in this report are associated with development of a nuclear digital platform application, integration of fault signature models, and automated work management processes. The fault signatures and Machine Learning (ML) models are key components in predictive analytics and are heavily leveraged to improve the insights received by existing plant process data sources. Availability of the analysis results within a centralized digital platform enhances efficiency by enabling automation of activities otherwise performed manually. Personnel are presented with enhanced information that can be used to evaluate plant status and risks. Utilizing the enhancements to data analytics supports automated responses, (i.e. issuance of work orders) to address developing equipment faults and thus preventing forced, unplanned shutdowns of components or systems. The R&D activities described within this report lay the foundation for developing and demonstrating a digital automated platform to centralize the implementation of condition monitoring and response to equipment faults. The digital automated platform is cloud-based and designed to enable improved efficiency of plant processes. The digital platform includes content related to maintenance optimization, fault signature analysis, and plant records, which can all be used to support efficiencies when located within a centralized digital platform. These efficiencies could be further enhanced when deployed through industry-wide deployment of the technology to improve insights and processes based upon economies of scale.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

TCCR Operational Summary and Optimization for Tank 9 Processing - 20314

Savannah River Remediation (SRR) manages and operates the liquid waste facilities at Savannah River Site (SRS) for the Department of Energy (DOE). Stored liquid waste is a complex mixture of insoluble solids (sludge) and soluble salts in an alkaline solution. SRR has deployed the Tank Closure Cesium Removal (TCCR) system, a tank-side ion exchange process, to remove radioactive cesium from salt waste and enable onsite disposal of the resulting decontaminated salt solution as low-level waste at the Saltstone facilities. The TCCR system consists of two prefilters, four ion exchange (IX) columns, one resin trap, and a ventilation system. The IX process uses a form of inorganic crystalline silicotitanate (CST), which has a high affinity for cesium and other alkali metals, strontium, and actinides. This process is currently deployed utilizing salt feed from Tank 10, with future plans to dissolve solid salt in Tank 9 and transfer the salt solution to Tank 10 for processing through TCCR. The feed for TCCR must be created from salt-cake in Tank 10 through a dissolution process. Once enough salt has been dissolved, a qualification process is entered. This process characterizes the feed and ensures the cesium loading on the columns will not cause boiling of waste within the columns during or after processing. Once the batch has been qualified, salt waste is fed to the TCCR system through a transfer pump in the center of the tank. The waste is filtered through a set of two shielded, dead-end prefilters that prevent solids buildup in the columns. The filtered salt solution then travels to the shielded IX columns, which can be operated individually or in series, where the cesium is sorbed on the CST media. The decontaminated salt solution (DSS) then travels through a resin trap and out of the module to Tank 11. TCCR has successfully processed approximately 795,000 L of Tank 10H radioactive salt waste over two batches to date. There has not yet been a system induced shutdown. The prefilters performed as expected with only minor degradation in recovery of differential pressure after a backflush sequence. The time between backflushes decreased as each batch reached the end of processing. The hydraulics in the IXCs mostly performed as expected at all flow rates, except for one IXC that will be further investigated during Batch 3 processing. The TCCR system has shown some opportunities for more efficient processing during the length of the demonstration so far. For future processing of material from Tank 9H through Tank 10H and the TCCR unit, TCCR 1A will implement changes to the prefilters and the IXCs. The prefilters will have an increased surface area and a new filter media in an effort to increase time between filter swaps and improve backwashing cleaning capability. The IXCs will have a reduced diameter to allow for increased heat transfer out of the column and increased loading of Cs-137. Additionally, a new form of CST with an increased kinetic performance is being investigated for use during TCCR 1A operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Bayesian optimization to design a novel x-ray shaping device

In radiation therapy, x-ray dose must be precisely sculpted to the tumor, while simultaneously avoiding surrounding organs at risk. This requires modulation of x-ray intensity in space and/or time. Typically, this is achieved using a multi leaf collimator (MLC) - a complex mechatronic device comprising over one hundred individually powered tungsten ‘leaves’ that move in or out of the radiation field as required. Here, an all-electronic x-ray collimation concept with no moving parts is presented, termed “SPHINX”: Scanning Pencil-beam High-speed Intensity-modulated X-ray source. SPHINX utilizes a spatially distributed bremsstrahlung target and collimator array in conjunction with magnetic scanning of a high energy electron beam to generate a plurality of small x-ray “beamlets.” A simulation framework was developed in Topas Monte Carlo incorporating a phase space electron source, transport through user defined magnetic fields, bremsstrahlung x-ray production, transport through a SPHINX collimator, and dose in water. This framework was completely parametric, meaning a simulation could be built and run for any supplied geometric parameters. This functionality was coupled with Bayesian optimization to find the best parameter set based on an objective function which included terms to maximize dose rate for a user defined beamlet width while constraining inter-channel cross talk and electron contamination. Designs for beamlet widths of 5, 7, and 10 mm 2 were generated. Each optimization was run for 300 iterations and took approximately 40 h on a 24-core computer. For the optimized 7-mm model, a simulation of all beamlets in water was carried out including a linear scanning magnet calibration simulation. Finally, a back-of-envelope dose rate formalism was developed and used to estimate dose rate under various conditions. The optimized 5–, 7–, and 10-mm models had beamlet widths of 5.1 , 7.2 , and 10.1 mm 2 and dose rates of 3574, 6351, and 10 015 Gy/C, respectively. The reduction in dose rate for smaller beamlet widths is a result of both increased collimation and source occlusion. For the simulation of all beamlets in water, the scanning magnet calibration reduced the offset between the collimator channels and beam centroids from 2.9 ±1.9 mm to 0.01 ±0.03 mm. A slight reduction in dose rate of approximately 2% per degree of scanning angle was observed. Based on a back-of-envelope dose rate formalism, SPHINX in conjunction with next-generation linear accelerators has the potential to achieve substantially higher dose rates than conventional MLC-based delivery, with delivery of an intensity modulated 100 x 100 mm 2 field achievable in 0.9 to 10.6 s depending on the beamlet widths used. Bayesian optimization was coupled with Monte Carlo modeling to generate SPHINX geometries for various beamlet widths. A complete Monte Carlo simulation for one of these designs was developed, including electron beam transport of all beamlets through scanning magnets, x-ray production and collimation, and dose in water. These results demonstrate that SPHINX is a promising candidate for sculpting radiation dose with no moving parts, and has the potential to vastly improve both the speed and robustness of radiotherapy delivery. A multi-beam SPHINX system may be a candidate for delivering magavoltage FLASH RT in humans.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Non-Equilibrium Actinide Radiation Chemistry and the Nuclear Fuel Cycle

Actinides are inherently unstable elements that frequently coexist with other radioisotopes, generating intense ionizing radiation fields that drive the formation of non equilibrium oxidation states. These transient species exert a profound mechanistic influence on the radiation response of actinide containing systems due to their unique redox chemistry. Despite their importance, they remain poorly understood, yet such insight is essential for advancing actinide science and accurately predicting radiation driven behavior. Actinide separations—critical for nuclear energy technologies, strategic deterrence, space exploration, and nuclear medicine—depend on precise control of actinide oxidation states to recover targeted elements from complex matrices such as used nuclear fuel. However, during these processes, actinides, their coordination complexes, and the separation media are all exposed to intense, multicomponent (alpha, beta, gamma, etc.) radiation fields that can alter process efficiency, selectivity, and chemical stability. Understanding, controlling, and mitigating radiation induced reactions is therefore key to innovating and optimizing next generation separation technologies. This seminar will provide an overview of the nuclear fuel cycle and non equilibrium actinide radiation chemistry in the context of recovering actinides from used nuclear fuel, with a particular emphasis on direct dissolution–based reprocessing strategies. We will explore time resolved electron pulse radiolysis and alpha and gamma dose accumulation studies, integrated with multiscale computational modeling, to elucidate the molecular level roles of radiation driven, non equilibrium actinide species in process performance and in the radiolytic stability of organic ligands used for actinide recovery. These insights offer new pathways for designing advanced separation methods and next generation solvent systems, with broad implications for the future of the nuclear fuel cycle.

37 - INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL C↗
DOE OSTI2022

Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source

This work describes the initial development of dynamic system models of the cryogenic moderator system (CMS) of the Spallation Neutron Source (SNS) at ORNL as a part of the ORNL LDRD funded project Building TRANSFORM to Accelerate Digital Twin Applications for Nuclear Systems, LOIS 10563. The goal of the work is to start the dynamic system modeling effort with the end goal of using them for real-time applications as digital twins. The CMS is a cryogenic liquid hydrogen flow loop that provides moderation of the neutrons that are generated by the SNS. For optimal neutron production, the CMS needs to maintain a steady and controlled density of cryogenic hydrogen in the moderator section thus requiring precise temperature and pressure control. Due to the varied time scales and system characteristics, control of the system is complex, and diagnostics are also difficult. Difficulty in accessing the flow loop during operations, limited instrumentation and unknown design details of the equipment combine to make the case for having sophisticated digital twin models of the system. Operationally the CMS also provides a strong use case for digital twins due to the constant need of optimization and for troubleshooting/diagnostics. The large amount of data collected which are freely available for using in building the model and verifying and validating the model also makes it a great candidate for a proof-of-concept for digital twins. The project extends ORNL's capacity of development and implementation of the open-source dynamic system modeling tool TRANSFORM for engineering design and digital twin/real-time applications. Specific system configuration data for the CMS have been gathered and an initial dynamic model was created in the TRANSFORM library using Dymola as the solution platform. Models of increasing complexity are created to demonstrate the need for a multi-layered approach in digital twin modeling depending on the scale and phenomena being focused on. The dynamic modeling is shown to bring the dynamic operational aspects to the design process for systems as well as serve as a digital twin to the hardware and allow for models to be tuned and compared against real time operational data. These aims should help to push forward strategic goals of application of digital twins and increase the impact of ORNL systems modeling capabilities with TRANSFORM/Modelica for various advanced energy systems.

42 ENGINEERING↗
DOE OSTI2024

Extension of SCALE/Sampler’s sensitivity index for the assessment of cross section, fission yield, and decay data uncertainties

Accurate prediction of nuclide compositions and neutron and gamma sources and spectra for fresh and spent nuclear fuel through computational modeling and simulations is the basis for safeguards instruments design, optimization, and calibration, and for validation of the measured responses. The accuracy of these simulations can be significantly impacted by uncertainties in input parameters to the applied computer code. Input parameters are, for example, dimensions, material compositions, and temperatures of the model. Additionally, important but sometimes neglected input parameters for simulations of nuclear systems are the nuclear data that include nuclear reaction cross sections, fission product yields, and decay data. It has been shown that uncertainties of calculated results are dominated by uncertainties of these nuclear data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Nuclear-Renewable-Storage Systems: Enhancing Planning and Operations of Integrated Energy Systems

Nuclear-renewable-storage integrated energy systems (IES) are multi-carrier energy systems that include not only electricity but also other forms of demands. Because individual IES components must observe their thermo-physical limits, including ramp rates, start-up, and shut-down time, we formulate operations of the IES as an optimization model by minimizing the total operations costs subject to physical limits of all constituent components. In addition, we develop a data-driven approach to improve the computational performance of the economic dispatch model by using reinforcement learning, where an agent is rewarded by meeting demands and penalized otherwise when shifting to the next state.

25 ENERGY STORAGE↗