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DOE OSTI2020

High-resolution Hindcasts for U.S. Wave Energy Resource Characterization

The marine and hydrokinetic (MHK) industry is at an early stage of development and has the potential to play a significant role in diversifying the U.S. energy portfolio and reducing the U.S. carbon footprint. Wave energy is the largest among all the U.S. MHK energy resources, which include wave energy, ocean current, tidal-instream, ocean thermal energy conversion, and river-instream. Wave resource characterization is an essential step for regional wave energy assessments, Wave Energy Converter (WEC) project development, site selection and WEC design. The present paper provides an overview of a joint modelling effort by the Pacific Northwest National Laboratory and Sandia National Laboratories on high-resolution wave hindcasts to support the U.S. Department of Energy’s Water Power Technologies Office’s program of wave resource characterization, assessment and classifications in all US coastal regions. Topics covered include the modelling approach, model input requirements, model validation strategies, high performance computing resource requirements, model outputs and data management strategies. Examples of model setup and validation for different regions are provided along with application to development of classification systems, and analysis of regional wave climates. Lessons learned and technical challenges of the long-term, high-resolution regional wave hindcast are discussed.

Yang, Zhaoqing↗

DOE OSTI2023

InSPIRE 2.0 (Final Technical Report)

Co-locating solar projects and agriculture can provide mutual benefits to local farmers (e.g., dual revenue streams, increased yields from pollinator services, irrigation reductions) and to the solar projects (e.g., reduced timeline/costs for installation and O&M, expanded market, increased PV efficiency from a cooler, vegetated microclimate). While prior work sought to demonstrate the feasibility of agricultural co-location (or "agrivoltaic") opportunities, there is a fundamental gap in data available to developers, landowners, and state agencies that prevents widespread deployment of these mutually beneficial practices. This project addressed this gap by (1) establishing a stakeholder research working group composed of multi-sector industry leaders and academics to provide guidance and assist with outreach; (2) undertaking targeted field-based research projects evaluating solar and agriculture co-location tradeoffs; (3) conducting analysis and modeling studies that complement the field-based research; and (4) developing a data portal to consolidate all data on this topic in one location.

14 SOLAR ENERGY↗

DOE OSTI2026

Transient uncertainty quantification and Global Sensitivity Analysis of the open-source Molten Chloride Reactor Experiment (MCRE) using GP-PCA surrogate models

Uncertainties in the thermophysical properties of molten salts impact both the steady-state and transient behavior of Molten Salt Reactors (MSRs). In this work, we aim to quantify the influence of such uncertainties on the transient operation of the Molten Chloride Reactor Experiment (MCRE), utilizing the open-source specifications provided for this reactor. Seven representative transient scenarios are considered. For each scenario, we evaluate the impact of thermophysical property uncertainties on four key multiphysics model output variables of interest (VoIs): maximum power density, maximum fuel temperature, maximum reflector temperature, and average fuel velocity magnitude. In addition, we perform a Global Sensitivity Analysis (GSA) by computing Sobol’ indices for the uncertain input parameters to determine their contribution to the variability of each VoI. Conducting GSA is computationally intensive due to the large number of required evaluations of the high-fidelity multiphysics model. To mitigate this cost, we develop a surrogate modeling framework that combines Gaussian Process (GP) regression with Principal Component Analysis (PCA), enabling efficient sample generation for the GSA. Our results show that for energy-related VoIs, thermal conductivity is the dominant contributor to uncertainty. In contrast, for flow-related VoIs, density and dynamic viscosity are the primary sources of uncertainty. The specific heat of the fuel salt was found to play a secondary role in the transient analyses.

42 - ENGINEERING↗

DOE OSTI2021

Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) (Final Scientific/Technical Report)

This report summarizes the activities conducted under the DOE VTO funded project DE- EE0008451, where ABB Inc. (ABB), in collaboration with Idaho National Laboratory (INL), APS Global (APS), and XOS Trucks (XOS) pursued the development of a cyber-resilient extreme fast charging (XFC) management system. This project entitled Cybersecurity for Grid Connected eXtreme Fast Charging (XFC) Station (CyberX) focuses on a resilient architecture for smart charging EV Supply Equipment (EVSE) device control and Coordinated Anomaly Detection System (CADS) features that can be added at the charging site depot level to increase cybersecurity. The project was split into two budget periods focused first on developing the threat model and resilient control concepts and second on testing, improving, and validating those developed resilient control algorithms and features with a focus on key vulnerabilities identified during the threat assessment portion of the project. During the first budget period of the CyberX project, the ABB led team focused on activities to identify, model, and quantitatively prioritize high-impact attack scenarios with potential cyber-physical effects while also modeling and developing concepts for a resilient control system that could securely address integration of DERs and other resources with EV charging. Development of the security focused XFC management system (XMS) was accomplished first by offline simulation using a developed XFC station or depot with 480V input level and simulating measurement inputs to monitoring and control systems in concept development. A representative distribution grid model was developed supporting an EV charging site model with BESS and 6 general EV charging models. These EV charging models allowed multiple configurations of charging level, multiple connected protection and measurement devices, and simulation function to show general compromise of EV, BESS, and protection features based on parallel threat analysis. During the second budget period, the EV site and supporting systems model was developed in more detail and converted from offline model to real-time to real-time with EV charging hardware in the loop (HIL). The resilient control architecture developed as concept in the first part of the project was further tested and validated for integration of local energy resources and XFC charging station site equipment while maintaining cybersecure operating principles. The proposed resilient architecture for smart charging and cybersecurity features consists of two main concepts developed and tested within the project. The first concept is an XFC management system (XMS) consisting of a hardware gateway, software platform, and Supervisory Control and Data Acquisition (SCADA) or Distribution Management System integration components. The second concept is a Coordinated Anomaly Detection System (CADS) which forms a primarily software-related subsystem of the total CyberX solution focused on monitoring system measurements, estimation of measurement states, and predicting current at the utility point of interaction based on machine learning for anomaly detection.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Evaluation of Joint Cyber/Safety Risk in Nuclear Power Systems

This report presents an analysis of the Emergency Core Cooling System (ECCS) for a generic Boiling Water Reactor (BWR)-4 NPP. The Electric Power Research Institute (EPRI) developed Hazards and Consequences Analysis for Digital Systems (HAZCADS) process is applied to the ECCS and its subsystems to identify unsafe control actions (UCAs) which act as possible cyber events of concern. The analysis is performed for two design basis events: Small-break Loss of Coolant Accident (SLOCA) and general transients (TRANS), such as unintended reactor trip. In previous work, HAZCADS UCAs were combined with other cyber-attack analysis to develop a risk-informed approach; however, this was for a single system. This report explores advanced systems engineering modeling approaches to model the interactions between digital assets across multiple systems which may be targeted by cyber adversaries. The complex and interdependent design of digital systems has the potential to introduce emergent cyber properties that are generally not covered by hazard analyses nor formal nuclear Probabilistic Risk Assessment (PRA). The R&D and supporting analysis presented here explores approaches to predict and manage how interdependent system properties effect risk. To show the potential impact of a successful cyber-attack to formal PRA event tree probabilities, HAZCADS analysis was also used. HAZCADS was also used to model the automatic depressurization system (ADS) automatic actuation. This analysis extended to an integrated system analysis for common-cause failure (CCF). In this aspect, the HAZCADS analysis continued by analyzing plant design details for system connectivity in support of critical plant functions. A dependency matrix was developed to depict the integrated functionality of the interconnected systems. Areas of potential CCF are indicated. Future work could include adversary attack development to show how CCF could be caused, resulting in PRA events. Across the multiple systems that comprise the ECCS, the analysis shows that the change in such probabilities was very different between systems. This indicates that some systems have a larger potential risk impact from successful cyber-attack or digital failure, which indicates a need for these systems to have a higher priority for design and defensive measures. Furthermore, we were able to establish that a risk analysis using any arbitrary threat model establishes an ordering of components with regard to cyber-risk. This ordering can be used to influence the overall system design with an eye to lowering risk, or as a way to understand real-time risk to operational systems based on a current threat landscape. Expert knowledge of both the analysis process and the system being analyzed is required to perform a HAZCADS analysis. The need for a tiered risk analysis is demonstrated by the results of this report.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Opportunities and data requirements for data-driven prognostics and health management in liquid hydrogen storage systems

During the past decade, Prognostics and Health Management (PHM) has become an important set of tools in various areas of industry and academic reliability engineering. PHM consists of a variety of mathematical and computational methods used to support data-driven decision-making to increase the safety, availability, and reliability of complex engineering systems. In particular, PHM can provide crucial insight into reliability and safety design improvements for developing technologies where historical performance and failure data are limited. This is the case of hydrogen fueling and storage technologies. This work presents a high-level approach for designing data-driven PHM applications for bulk liquid hydrogen (LH 2 ) storage systems for hydrogen fueling stations. This paper addresses core aspects of the design, development, and implementation of data-driven PHM applications that can improve the reliability assessment of hydrogen components. The analysis focuses on the relationship between data availability and diagnostic/prognostic capabilities; potential challenges; and integration schemes for current risk mitigation measures. We identify potential condition-monitoring data sources for key components in an LH 2 storage system, including storage tanks, piping, and pumps. Further, we determine that the short-term goals for the implementation of data-driven models in PHM frameworks in hydrogen systems should focus on developing adequate data collection and analysis strategies, as well as exploring the effect on reliability, safety, and regulations for hydrogen systems.

08 HYDROGEN↗

DOE OSTI2026

Control Parameter Sensitivity Study for Inverter-Based-Resource Dominated Grids: A Small Signal Stability Approach and Framework

The growing adoption of renewable energy is driving the prevalence of inverter-based resources (IBRs) within power grids. Future power grids will integrate both grid-following IBRs (GFM-IBRs) and grid-forming IBRs (GFL-IBRs) alongside synchronous generators. Therefore, it is crucial to perform stability studies that account for all components and especially control interactions related to IBRs. Extensive research has performed to study the IBR-related stability, however, the sensitivity study of IBRs' control parameters on system stability has not been adequately studied yet, especially from a systematic way. Therefore, this paper conducts a small signal stability analysis for a generic grid with multiple types of resources and develops an analytical framework for assessing the sensitivity of control parameters affecting stability margins. To achieve that, the non-autonomous reduced-order non-linear dynamic model is developed for a generic power system with multiple synchronous generator-based resources (SGBRs), GFM-IBRs, and GFL-IBRs. Based on the analytic model, a systematic framework for parametric sensitivity on systems' asymptotic stability is developed. A parameter sensitivity analysis based on eigenvalue methods is proposed. The impact of the droop controllers of GFM-IBRs, PQ-dispatch and the PLL controller of GFL-IBR on the system asymptotic stability is discussed. This sensitivity study is aiming to provide deep insights on control parameters' impact on system stability, and gives direction for parameter tuning in case of instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Usability Evaluation of the Innovation Portal and Integrated Capability Analysis Platform

The usability evaluation of the ICAP and IP tools was conducted as part of the United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) ION effort with two evaluators for the Idaho National Laboratory. Many nuclear operations in the United States are facing challenges of increased business, operations, and maintenance costs due to subsidized renewables and natural gas. The commercial NPP industry has looked to other industries to develop methods such as Integrated Operations (IO) to use available technologies to reduce operating costs. One concept for reducing costs that has been developed is the Integrated Operations for Nuclear (ION). A capability Stack model was developed as part of the ION effort to break down information related to People, Technology, Processes, and Governance (PTPG). The Innovation Portal (IP) and Integrated Capability Analysis Platform (ICAP) were created from the Capability Stack model as part of the ION effort to help utilities reduce O&M costs by identifying work reduction opportunities. Two heuristic evaluations and a cognitive walkthrough of the ICAP and IP tools were completed to identify usability issues to further develop the tools for use in the ION effort. Usability issues identified were rated by priority levels and across both tools. The priority levels identified were high (5), medium (11), and low (10). Recommendation were made to help reduce usability issues of the systems and help increase the user response rate of using the systems once they are implemented for utilities. Future work on designs for the IP tool and additional heuristic evaluations and external testing are being developed to continue refinement of the ICAP and IP tools for the ION effort.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2022

Assessing high fidelity multi-component models to facilitate safeguards at Gas Centrifuge Enrichment Plants

We report that the International Atomic Energy Agency (IAEA) inspectors routinely carry out environmental sampling (ES) as a verification method. Collection of environmental swipe samples at various locations in Gas Centrifuge Enrichment Facilities (GCEPs) is an important process in detecting misuse of a declared facility and possibly the existence of undeclared nuclear material. These samples are measured for isotopic composition in uranium containing particles by Thermal Ionization Mass Spectrometry (TIMS) or Inductively Coupled Plasma Mass Spectrometry (ICP-MS). Even though ES is highly effective in detecting the absolute value of enrichments and their deviations from the declared values, it cannot explain the cause of those changes. Several potential explanations can serve as possibilities for particles detected above or other than the declared enrichment. These include normal and non-malicious events such as the design of the enrichment cascades, unintentional failures of the machines, or overshoot during startup of a cascade. It can also be the result of deliberate misuse by the facility operators. The primary objective of this work is to understand how these factors affect the enrichments produced by a cascade and quantify anticipated multi-isotopic concentrations for each case. The following methodology is employed to determine signatures at a particular facility. 1) Utilize a new two-dimensional multi-component diffusion code to obtain centrifuge performance data and use that information to design and perform cascade analysis. Compare and contrast the results with previous 1-D radially averaged solutions from the Pancake code. 2) Design a GCEP cascade with the production goal of 19.75% 235 U for each set of machine data above. Investigate two cascade scenarios that include enrichment of natural uranium (NU) feed to 19.75% 235U in a single cascade compared to a two-step process of NU to 5% and then 5% to 19.75%. 3) Simulate the intentional vs. unintentional off-normal scenarios in the cascades to assess the differences in isotopic concentrations. A non-ideal squared-off cascade model developed at the University of Virginia is used to calculate flow rates and isotopic concentrations of the process gas. The analysis is performed using the Rome machine model operated at 600 m/s rotor speed. The upper and lower bounds of normal and abnormal enrichments in a typical facility are used in conjunction with ES results to understand the root causes of such observations.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2022

Computer-aided quantization and numerical analysis of superconducting circuits

The development of new superconducting circuits and the improvement of existing ones rely on the accurate modeling of spectral properties which are key to achieving the needed advances in qubit performance. Systematic circuit analysis at the lumped-element level, starting from a circuit network and culminating in a Hamiltonian appropriately describing the quantum properties of the circuit, is a well-established procedure, yet cumbersome to carry out manually for larger circuits. We present work utilizing symbolic computer algebra and numerical diagonalization routines versatile enough to tackle a variety of circuits. Results from this work are accessible through a newly released module of the scqubits package.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Brittle failure analysis and modeling of high-burnup PWR fuel cladding alloys

The aim of this research is the development of methods for predicting mechanical behavior and identification of limiting conditions to prevent brittle failure of high-burnup (HBU) pressure water reactor (PWR) fuel cladding alloys. A finite element (FE) model of the ring compression test (RCT) was created to analyze the failure behavior of zirconium-based alloys with radial hydrides during the RCT. An elastic-plastic material model describes the zirconium alloy. The stress-strain curve needed for the elastic-plastic material model was derived by inverse finite element analyses. Cohesive zone modeling is used to reproduce sudden load drops during RCT loading. Based on the failure mechanism in non-irradiated ZIRLO (R) claddings, a micro-mechanical model was developed that distinguishes between brittle failure along hydrides and ductile failure of the zirconium matrix. Two different cohesive laws representing these types of failure are present in the same cohesive interface. The key differences between these constitutive laws are the cohesive strength, the stress at which damage initiates, and the cohesive energy, which is the damage energy dissipated by the cohesive zone. Statistically generated matrix-hydride distributions were mapped onto the cohesive elements and simulations with focus on the first load drop were performed. Computational results are in good agreement with the RCT results conducted on high-burnup M5 (R) samples. It could be shown that crack initiation and propagation strongly depend on the specific configuration of hydrides and matrix material in the fracture area.

Simbruner, Kai↗

DOE OSTI2021

Developing Generic Prior Distributions for Common Cause Failure Alpha Factors and Causal Alpha Factors

This report is a revision of the original report, INL/LTD-17-43723. Distribution of the original report was to the Nuclear Regulatory Commission (NRC) only, and the report was not made available to the public. The original report was revised as this report for public distribution. This report presents the latest update of generic prior distributions for common cause failure (CCF) alpha factors, as well as the development of new generic prior distributions for CCF causal alpha factors. The history of CCF treatment and parameter estimations is reviewed. The existing process for developing generic prior distributions is reviewed and used to develop new priors for CCF alpha factors and causal alpha factors. For causal alpha factors, different priors are developed for the five different CCF cause groups: Component (GC), Design (GD), Environment (GE), Human (GH), and Other (GO). These generic prior distributions could be used in the Standardized Plant Analysis Risk (SPAR) models for CCF parameter estimation. The issues and preliminary thoughts regarding prior distribution development are documented. Potential future work is then proposed for improving the process of developing priors.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2021

Grizzly Development for Light Water Reactor and Advanced Reactor Applications in Fiscal Year 2021

This report summarizes work performed during Fiscal Year (FY) 2021 at Idaho National Laboratory (INL) for the U.S. Department of Energy’s Nuclear Engineering Advanced Modeling and Simulation (NEAMS) program for the Structural Materials and Chemistry Technical Area in the work package entitled “MS-21IN050106 - Structural Materials - INL.” This effort mainly focused on development and application of capabilities for engineering-scale analysis of nuclear reactor structural components in the Grizzly and BlackBear codes. These efforts include performance improvements and application of models for high-temperature component response, cluster dynamics modeling of precipitation in light water reactor pressure vessel steel, engineering-scale capability development in the areas of concrete simulation and reactor pressure vessel analysis, and preparation for and conducting an independent assessment of the adherence of these codes to software quality standards.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Data-driven Quasi-static Surrogate Models for Nuclear-powered Integrated Energy Systems

The integration of nuclear power into energy systems presents a promising avenue to address the growing global energy demands while minimizing greenhouse gas emissions. In this paper, we introduce a data-driven quasi-static surrogate model for nuclear-powered Integrated Energy Systems (IES) that comprises various components, including a small modular reactor (SMR), steam manifold, balance of plant (BOP), high-temperature steam electrolysis (HTSE), and district heating (DH) system. Traditional physics-based models for these components often entail significant computational resource and time consumption, necessitating the development of efficient surrogate models. The development of a complete surrogate model for the IES involves the creation of individual surrogate models for each component, leveraging machine learning techniques and simulated data. These isolated surrogate models are subsequently integrated, enabling a holistic view of the IES and reducing the computational burden associated with detailed physics-based simulations. This paper outlines the development process, validation, and the performance evaluation of the surrogate models. The exceptional performance, with low root-mean-squared errors and R-squared scores of at least 99.8% across all individual surrogate models, underscores their accuracy and practical applicability. These results demonstrate the potential of these models to expedite the analysis of nuclear-powered IES, offering insights that can shape future research and development efforts.

08 HYDROGEN↗

DOE OSTI2021

Insights for Canadian electricity generation planning from an integrated assessment model: Should we be more cautious about hydropower cost overruns?

Hydropower accounts for approximately 60% of electricity generation in Canada, with growth expected in the coming decades as part of renewable energy transitions; however, frequent cost overruns threaten the viability of this growth. Here, using the integrated assessment model GCAM, we develop an endogenous representation of hydropower for Canada that accounts for market dynamics, thus permitting analysis of hydropower competition with other electricity generation technologies, both with and without cost overruns. Results show that modelling hydropower resources endogenously increases Canadian hydropower deployment relative to an assumption of fixed hydropower production, from 417 to 495 TWh annually by 2050. In scenarios that apply cost overruns at historical levels, hydropower loses market share to more easily scalable technologies like wind power. When including high cost overrun assumptions, the model determines that hydropower falls from about 73% to 65% of Canadian electricity generation by 2050, while wind power increases from about 8% to 11%. Countries may be better able to achieve electrification and renewable energy targets at lower cost by avoiding large-scale, overrun-prone hydropower and nuclear generation projects. Model results support that cost overruns are important considerations for policy decisions related to electricity sector development in Canada and elsewhere.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Toward a high-fidelity tritium transport modeling for retention and permeation experiments

We report Tritium Migration Analysis Program version 8 (TMAP8), the latest version of TMAP, was developed within the framework of the Multiphysics Object-Oriented Simulation Environment (MOOSE). Created at Idaho National Laboratory (INL), MOOSE is an open-source, dimension-agnostic, fully coupled, and fully implicit multiphysics platform featuring massively parallel computation capabilities. Using TMAP8, tritium transport in a divertor monoblock was analyzed to elucidate the effects of pulsed operation (up to fifty 1,600 s plasma discharge and cool-down cycles) on the tritium in-vessel inventory source term and ex-vessel release term (i.e., tritium retention and permeation) for safety analysis. With its built-in Message Passing Interface capability, TMAP8 can, in under 2 h, simulate tritium transport in three different layered materials (i.e., tungsten, copper, and copper-chromium-zirconium alloy) in 2D geometry, using a single device/computer with 10 cores. The MOOSE-based TMAP8 code can leverage other MOOSE tools developed under the Nuclear Energy Advanced Modeling and Simulation program to perform tritium and thermal transport in complex geometries and multiphysics environments. And via its massively parallel computation, MOOSE will enable the fusion pilot plant designers to conduct high-fidelity multiphysics modeling for the design of the divertor and blanket systems as well as for the safety analysis.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Cookoff experiments of a melt cast explosive (Comp-B3)

Validated models of melt cast explosives exposed to accidental fires are essential for safety analysis. In the current work, we provide several experiments that can be used to develop and validate cookoff models of melt cast explosives such as Comp-B3 composed of 60:40 wt% RDX:TNT. We present several vented and sealed experiments from 2.5 mg to 4.2 kg of Comp-B3 in several configurations. We measured pressure, spatial temperature, and ignition time. Some experiments included borescope images obtained during both vented and sealed decomposition. We observed the TNT melt, the suspension of RDX particles in the melt, bubble formation caused by RDX decomposition, and bubble-induced mixing of the suspension. The RDX suspension did not completely dissolve, even as temperatures approached ignition. Our results contrast with published measurements of RDX solubility in hot TNT that suggest RDX would be completely dissolved at these high temperatures. These different observations are attributed to sample purity. We did not observe significant movement of the two-phase mixture until decomposition gases formed bubbles. Bubble generation was inhibited in our sealed experiments and suppressed mixing.

42 ENGINEERING↗

DOE OSTI2020

SCALE Code System

The SCALE Code System is a widely used modeling and simulation suite for nuclear safety analysis and design that is developed, maintained, tested, and managed by the Reactor and Nuclear Systems Division (RNSD) of Oak Ridge National Laboratory (ORNL). SCALE provides a comprehensive, verified and validated, user-friendly tool set for criticality safety, reactor and lattice physics, radiation shielding, spent fuel and radioactive source term characterization, and sensitivity and uncertainty analysis. Since 1980, regulators, licensees, and research institutions around the world have used SCALE for safety analysis and design. SCALE provides an integrated framework with dozens of computational modules, including three deterministic and three Monte Carlo radiation transport solvers that are selected based on the desired solution strategy. SCALE includes current nuclear data libraries and problem-dependent processing tools for continuous-energy (CE) and multigroup (MG) neutronics and coupled neutron-gamma calculations, as well as activation, depletion, and decay calculations. SCALE includes unique capabilities for automated variance reduction for shielding calculations, as well as sensitivity and uncertainty analysis. SCALE’s graphical user interfaces assist with accurate system modeling, visualization of nuclear data, and convenient access to desired results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗