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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.

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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Robust Learning of Dynamic Interactions for Enhancing Power System Resilience (Final Scientific Report)

The overall goal of the project is to leverage robust graphical learning and phase measurement unit (PMU) data to learn the dynamic interactions of electrical grid components in order to improve the power system resilience. Specifically, the learned dynamic interaction graphs are utilized to detect known and unknown anomalous patterns in power systems, identify high-risk operational conditions, and enable risk-based cascading mitigation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Hydropower Cyber-Physical Configurations

The U.S. Department of Energy’s Water Power Technologies Office funded Pacific Northwest National Laboratory, Argonne National Laboratory, and the National Renewable Energy Laboratory to develop a typology to characterize the variety and pervasiveness of cyber-physical configurations across the nation’s hydropower fleet. Outreach to owners and operators returned configurations for 275 hydropower plants or approximately 12% of the fleet. Components (OT and IT), systems, and connections among systems differed among plants according to function, age, position in the river cascade, and many other factors. Seven cyber-physical configuration types labeled A through I, included from 2 to dozens of plants. They were differentiated by how pervasive data and control connections were among cyber-physical components and how frequently control signals paired with data signals in a feedback loop. The flow of data and control within each type implies what cybersecurity vulnerabilities may exist, and what mitigation actions may be most effective. A self-assessment approach allows plant operators to identify the configuration type similar to their plant and link to the lessons learned and best practices information. The cyber-physical typology reinforces the idea that hydropower facilities vary widely, but it also identifies groups that highlight similarities in how their cyber-physical components interact. This helps address fleetwide cybersecurity needs by identifying a reasonable number of configuration types that share risks, vulnerabilities, and potential mitigations.

13 HYDRO ENERGY↗
DOE OSTI2022

Integration of Control Methods and Digital Twins for Advanced Nuclear Reactors

Advanced nuclear reactors offer a new set of features to energy generation, due to their ability to adapt to variable energy demand, operate autonomously, be deployed in rural locations and monitored remotely, afford compact size and lower power ratings, and rely on novel technologies to achieve safer operations. Thus, a requirement for the success of these reactors is the use of intelligent forms of control to track changing power demands, make autonomous decisions, and reduce the need for human involvement. Regulatory requirements pertaining to control of nuclear reactors could be met via historical means of control; however, these are not expected to enable the level of highly autonomous operations desired in advanced nuclear reactors. Historical control methods rely on both logical and high-performance (HP) control. These two types of control are usually used separately, with a human element being introduced whenever decisions are cascaded from one science to another. AI/ML control, on the other hand, can replace the human element in the current U.S. fleet of nuclear power plants (NPPs) by acting as a supervisory optimizer that understands the plant internal/external variables in order to make control decisions, and can easily handle non-linear and multi-input/multi out (MIMO) decisions—another requirement for advanced nuclear reactors that could be difficult to handle via logical and HP control. Because of the harsh operating environments produced in advanced reactors, resulting in the frequent failure of sensors and other types of equipment, and considering the lack of operating history for advanced nuclear reactors, control of advanced nuclear reactors would necessitate relying on a model that can track and adapt to the actual process (i.e., a digital twin). This digital twin can make approximations when knowledge and data are unavailable and would evolve as more knowledge is gained. The reactor control must also be risk-informed to account for the high-consequence nature of advanced reactors. This report introduces a high-level (i.e., not method- or process-specific) integration of the three different control and digital twinning methods able to meet the requirements for advanced nuclear reactors. These methods could be applied during both the operational and design stages of these reactors. The aim is to demonstrate how each method interfaces with and highlights enabling solutions necessitated by the unique features of advanced nuclear reactors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Understanding and Predictability of Integrated Mountain Hydroclimate (Workshop Report)

Mountainous systems cover approximately 23% of Earth’s land and are distributed across all continents. They can capture and store atmospheric moisture that is then cycled through the terrestrial surface and subsurface system, released to downstream communities, and cycled back to the atmosphere. Mountain hydroclimate—characterized by steep gradients, geological, ecological, and biogeochemical diversity—is influenced by topographic forcing and elevated warming and susceptible to large subseasonal to multidecadal variability and rapid changes. Terrestrial hydrological and biogeochemical cycles also experience cascading effects from global warming impacts, such as multidecadal declines in mountain snowpack, longer growing seasons, and increased frequency and severity of extreme events like droughts and wildfires. However, little is known about the effects of these impacts and their feedbacks on climate systems and surface-subsurface compartments. Also unknown are the full implications of changing hydroclimate and extreme events on hydro biogeochemical cycles across atmosphere, terrestrial, and human systems in mountain regions and beyond. This knowledge gap is critical, given human reliance on mountain systems for stable water supply and quality. Mountain systems’ increasing vulnerability to climate change and human perturbations motivates the need to improve understanding of integrated mountain hydroclimate (IMHC) systems and their feedbacks and impacts on humans across scales. However, due to large heterogeneity and strong gradients, coupled natural-human processes in mountain regions present significant challenges for observations, modeling, predictions, and projections. Motivated by gaps in mountain hydroclimate understanding, observations, and modeling and the need for credible projections of future changes, the U.S. Department of Energy’s (DOE) Biological and Environmental Research (BER) program organized a virtual workshop on “Understanding and Predictability of Integrated Mountain Hydroclimate.” Sponsored by BER’s Earth and Environmental Systems Sciences Division (EESSD), the workshop aimed to inform and catalyze EESSD’s growing interests in enhancing predictive understanding of IMHC. Organizers structured the workshop to identify (1) knowledge gaps, (2) observational and modeling challenges, (3) short-term (1 to 3 years) and long-term (10 years and beyond) research opportunities, and (4) strategies for fostering collaboration and coordination. To address the outstanding challenges of IMHC, the workshop included two sessions organized by disciplinary, cross-disciplinary, and crosscutting science topics. The disciplinary and cross-disciplinary topics focused on essential IMHC elements: atmosphere, terrestrial, and human systems and their interactions. Breakout sessions on disciplinary and cross-disciplinary topics facilitated identification of crosscutting topics and central emerging themes. Session 1 focused on connecting existing DOE investments to accelerate progress related to scientific challenges in understanding mountain hydroclimate. In Session 2, participants further explored key Session 1 takeaways through the lens of multiagency collaborations and coordination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Spatio-temporally shaped deep UV laser source for ultrabright photocathodes using novel upconversion techniques (Final Report)

The goal of this project was to take a VUV laser system designed by Kapteyn-Murnane Labs (KMLabs)—the Hyperion VUV, and increase its functionality, efficiency, and applicability by further probing the fundamental physics taking place in the system and optimizing the system performance. More specifically, DOE accelerator applications—particularly for XFELs that require low-emittance electron beams, require precisely controlled ultrashort pulses in the deep-UV at 250-260 nm to drive the photocathode electron source. This is conventionally done using an ultrafast infrared laser, with subsequent stages of nonlinear upconversion in solid-state nonlinear-optical crystal media (principally BBO, which is commonly used for UV upconversion). However, maintaining high spatial mode beam quality, as well as precisely controlled temporal profile, has proven a persistent challenge. As a possible alternative to this approach, KMLabs has demonstrated a system that generates vacuum ultraviolet light (VUV) by upconverting pulses from an infrared ultrafast laser in a gas-filled hollow waveguide, driving a process of highly cascaded harmonic generation (HCHG). Because HCHG upconversion is done in a gas, rather than a solid, at high intensity in a guided-wave geometry, it retains an excellent beam spatial profile as well as a large spectral bandwidth that allows for control over the temperal structure of the pulse. A challenge, however, is in energy scaling of this HCHG technique to the ~1-20 μJ pulses required for photocathode applications. To-date, the pulse energies used in published HCHG work are sub-10-nJ. This project proposed to explore ways to generate higher-energy pulses using HCHG, as well as to investigate spectral and temporal shaping of the deep UV pulses by pulse shaping the infrared laser used to seed the process. Although we showed that our approach works for generating light at 259 nm, the total pulse energy achieved seems limited to approximately the same value as past work. However, the techniques we investigated may well have benefits for extending this source to much shorter wavelength output.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

CEBAF FFA Energy Upgrade

Encouraged by recent success of CBETA, a proposal was formulated to increase the CEBAF energy from the present 12 GeV to 20-24 GeV by replacing the highest-energy arcs with Fixed Field Alternating Gradient (FFA) arcs. The new pair of arcs would provide six or seven new beam passes, going through this magnet array, allowing the energy to be nearly doubled using the existing CEBAF SRF cavity system. One of the immediate accelerator design tasks is to develop a proof-of-principle FFA arc magnet lattice that would support simultaneous transport of 6-7 passes, with energies spanning a factor of two. We also examine a possibility of using combined function magnets to configure a cascade, six-way beam split switchyard. Finally, a novel, multi-pass linac optics based on a triplet focusing lattice is being explored.

Bogacz, S.↗
DOE OSTI2023

Next-Generation Modular Flexible Low-Cost SiC-based High-Frequency-Link Transformer (Final Technical Report)

This project, led by the small business NextWatt LLC, led to the design and development of a novel high-frequency-link (HFL) transformer that yields reduce number of semiconductor devices compared to conventional solid-state transformers (SSTs). The HFL transformer is based on SiC device technology and nanocrystalline-core-based magnetics techniology. The control actuation of the SiC devices are algorithmically implemented in digital signal processor (DSP) platform. The overall HFL transformer technology is conceived and developed using a modular approach. During the course of the project the novel technology and its experimental performances at the module, multi-phase, and cascaded multi-phase levels have been demonstrated to the sponsor U.S. Department of Energy (DOE).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Imaging Nanoscale Energy Transport and Conversion with Ultrafast Electron Microscopy (Final Technical Report)

Light-matter interactions are ubiquitous in nature and reside at the heart of innumerable technologies. The cascade of processes that occur when a material absorbs a photon of light are exceedingly complex and are interwoven in both space and time, rendering precise determination of the atomic-scale and ultrafast mechanisms immensely challenging. The advent of methods for generating short pulses of light several decades ago led to major advances in understanding the initial moments of light absorption and the resultant effects, though directly interrogating the response of the atoms within the material continued to prove challenging. More recently, methods for generating ultrashort pulses of X-rays and fast electrons have opened the way to probing photoinduced structural dynamics of a wide range of matter in multiple phases. An especially promising laboratory-scale method is ultrafast electron microscopy (UEM), wherein the modalities of conventional transmission electron microscopes (imaging, diffraction, spectroscopy) are extended into the femtosecond temporal regime. Here, the ultrafast imaging and diffraction modalities of UEM were used to study the transient structural aspects of photoexcitation of semiconducting materials (e.g., spatially-resolved electron-phonon coupling, excitation and emission of acoustic phonons, and discrete nanoscale scattering processes). The project had three main objectives: (1) determination of the excitation mechanisms of dense, hypersonic charge-carrier waves and the spatially mediated means by which they couple to the lattice via coherent phonon emission, especially with UEM imaging, wherein effects of nanoscale structural and morphological features on the coupling and relaxation dynamics are expected to dictate nucleation sites and preferred wave vectors, (2) elucidation of photoinduced acoustic-phonon seeding, emergence, propagation, and decay over nanoscale crystal regions and especially with respect to local strain fields and atomic-scale disruptions in lattice order, and (3) interwoven with the first two were efforts aimed at realizing combined angstrom-femtosecond spatiotemporal imaging with UEM. The outcomes and impacts of this project were the generation of new knowledge with respect to fundamental light-matter interactions and, especially, the spatially-mediated excitation and evolution of the structural response of materials following coherent photoexcitation. Importantly, the spatial and temporal resolutions of the UEM imaging modalities used are well-suited for such studies and enable spatially-resolved mechanisms to be determined as a function of atomic order, structural features, and morphology. In addition, ultrafast crystallographic measurements were used to correlate real- and reciprocal-space dynamics in order to determine atomic-scale preferential wave vectors and ultrafast scattering mechanisms, especially as dictated by specimen boundary conditions. The obtained results, as detailed in peer-reviewed publications and presentations, illustrate the importance of ultrafast, angstrom-scale real-space imaging for developing a comprehensive understanding of energy transport and conversion in materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Using Taylor Green Vortex to Assess Modeling Turbulence Transition

The Taylor Green Vortex problem is an interesting problem to study the transition from laminar flow to fully developed turbulence. The problem consists initially of large-scale vortices that interact and eventually form smaller vortices that create a cascade of energy from larger scales to smaller scales. This document describes a) when fully developed turbulence occurs, and b) the scale separation in the inertial range. In addition, the resolution needed to capture perturbations in transitional flow is also proposed.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Experimental and Computational Studies of Stress Corrosion Cracking of Alloys 308/309 and 82/182 Weldments in Corrosive and Radiation Environment

The goal of the project was to determine factors that influence SCC and IASCC in weldments found in LWR nuclear power plants. We focused on a SA508-304L SS weldment fabricated by EPRI using gas tungsten arc welding and used an aggressive BWR normal water chemistry (NWC) immersion environment. This weldment used 309L butter and 308L groove filler material. The microstructure of the 309L butter was non-uniform, exhibiting a 20–30μm thick martensitic layer closest to the SA508 interface, a 1–4 mm thick single γ austenite phase dilution zone, and a γ–δ duplex region extending to the 308L groove filler. The 308L groove filler had an entirely γ–δ duplex microstructure. Two approximately 1-inch thick 304L and SA508 plates approximately 12 by 6 square inches were joined using standard nuclear grade welding techniques. This included a post weld heat treatment of the 309L butter after application, a 0.32 cm fit-up root opening, and 57 bead lines of 308L groove filler applied in 18 layers. A 60 degree weld bevel angle was used and the 309L butter was 1.5 cm thick. Displacement cascade damage was induced using proton irradiation at the Michigan Ion Beam Laboratory. The incident proton energy was 2 MeV, the sample temperature was 360 ºC, and the calculated dpa value at 10 μm (60% of the Bragg peak depth of ~18 μm) was 5 dpa using the quick Kinchin-Pease model. Proton irradiation to this damage level required approximately 125 hours of beam time. Two types of samples were irradiated, tensile specimens and TEM bars. Samples were selected from all regions of the weldment, including the SA508-309L butter interface, the 309L-308L interface, and 308L-304L interface. The stainless steel alloys (304L, 308L, and 309L) within the heat affected zone are characterized by a duplex skeletal morphology of δ-ferrite and γ-austenite resulting from the recrystallization associated with weld fabrication. Approximately 7 to 8 mm of length along the specimen was irradiated. The gauge volume surfaces were mechanically polished and then electro-polished to remove mechanical damage from the mechanical polishing step prior to irradiation. Immersion tests were performed in a recirculating autoclave under BWR NWC conditions (2000 ppb wt. dissolved oxygen, neutral pH, 288 ºC, 10 MPa, and inlet water conductivity <100 nS/cm) to accelerate corrosion. Constant strain rate tests were performed either to failure or to approximately 5% strain. Strain rates of 10 -7 to 10 -6 mm/mm/s were used and typical immersion testing required four to six weeks to achieve failure or strains near 5%. Analysis primarily used advanced electron microscopy techniques of FIB lift out specimens.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

RECLAIM: Electrochemical Lithium and Nickel Extraction with Concurrent Carbon Dioxide Mineralization

This project aims to develop technologies toward the production of Li and Ni from CO 2 -reactive minerals and rocks that contain Ca and Mg, while sequestering CO 2 . The technologies include acoustic stimulation and electrolytic proton production, which use electricity to liberate valuable metal ions from the surrounding mineral matrix at sub-boiling temperatures (~20-80°C). Feedstocks include Li/Ni/Ca/Mg-rich igneous and sedimentary rocks and minerals such as holmquistite, hectorite, lateritic Ni ores enriched in Mg-rich serpentine. Other examples of feedstocks that could be used include coarse grained orthocumulate, mine tailings, etc. In the first step, the electrolytic breakdown of water to H + and OH – (as well as O 2 and H 2 ) will be induced by applying an electric potential to simultaneously produce acidity and alkalinity. The solid feedstocks will be dissolved in the acidic anolyte under acoustic stimulation. Solubilized species will then undergo separation using our unique Li + -selective membranes driven by electrodialysis, leading to concentration of Li as soluble lithium silicate, from which Li 2 CO 3 can be derived by reaction with CO 2(g) while supplying cathode alkalinity. Also at the cathode, stepwise electrolytic precipitation of metal hydroxides, including Ni(OH) 2 , Ca(OH) 2 , and Mg(OH) 2 is performed along a cascade reactor in which both the applied potential and pH increase downstream, thereby simultaneously extracting and separating the metals. Finally, exposure of Ca(OH) 2 and Mg(OH) 2 to dilute CO 2 will result in CO 2 uptake in the form of Ca and Mg carbonates. The primary accomplishments include sample procurement and characterization. Progress has been made on precursor identification and mapping, establishing protocols for assessing metal extractability under sonication, and preliminary technoeconomic analysis (TEA) and life cycle analysis (LCA).

36 MATERIALS SCIENCE↗
DOE OSTI2024

Machine Learning and Data Science to Advance Laboratory Earthquake Prediction and Illuminate the Mechanics of Precursors to Failure

Earthquakes represent one of our greatest natural hazards and in recent years human induced seismicity is adding to the threat. Even a modest improvement in the ability to forecast devastating large earthquakes or smaller shallow events associated with fluid injection could save thousands of lives and billions of dollars. Current efforts to forecast earthquakes are limited by knowledge of earthquake physics and hampered by a lack of reliable lab or field observations. However, recent work has provided a critical opportunity for advancement. We have found: 1) clear and consistent precursors prior to earthquake-like failure in the laboratory and 2) that lab earthquakes can be predicted using machine learning (ML). These works show that stick-slip failure events –the lab equivalent of earthquakes– are preceded by a cascade of micro-failure events that radiate elastic energy in a manner that foretells catastrophic failure. Remarkably, ML predicts the fault zone stress state, the failure time and in some cases the magnitude of lab earthquakes. In addition, the observations include clear precursors to failure in the form of changes in fault zone properties prior to lab earthquakes. Precursors have been observed in previous laboratory studies but their origin is poorly understood and their possible connection to ML based earthquake prediction is unknown. The work conducted under our project has dramatically expanded these efforts. We have developed an integrated data science approach to illuminate the physics of earthquake precursors and lab earthquake prediction. Our work has accelerated the development of ML, artificial intelligence (AI), and related data science approaches by providing massive data sets that are tightly connected to critical scientific problems and by bringing together leading subject matter experts and data scientists. Earthquake physics involves phenomena that are far from equilibrium. Our work has leveraged data science methods to illuminate these phenomena and investigate how they relate to earthquake prediction. In addition to a large database with many types of labeled events that is available to everyone, our work has advanced the fundamental understanding of seismic forecasting, earthquake physics, and fault rheology

58 GEOSCIENCES↗
DOE OSTI2023

Overview of Nuclear Data Measurement and Analysis at RP [Slides]

This presentation details neutron capture in 54 Fe along with neutron capture yield and γ-ray cascade spectra measurements. The presentation then follows with thermal neutron die-away measurements and concludes with URR improvement to SAMMY.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Catalytic Upgrading of Renewable Feedstock (Final Technical Report)

The goal of this DOE-funded project was to investigate the fundamental science related to the development of homogeneous (de)hydrogenation catalysts in order to enable energy-relevant transformations of bio-relevant chemical feedstocks including ethanol. The primary focus was to improve the activity of ethanol upgrading catalysts, specifically informed through mechanistic studies, in order to enable rational design optimization strategies. Following in depth mechanistic studies, targeted reaction optimization approaches included ligand redesign to improve catalyst stability, developing new carbon-carbon bond forming reactions using ethanol as a precursor, and examining photochemically-mediated reactions, ultimately to integrate within other reactor designs such as continuous flow reactors. The high modularity of the catalyst components (ligands) has enabled the preparation and analyses of multiple catalyst precursors. These studies uncovered an unexpectedly beneficial substitution pattern of the ligand structure that led to the development of new catalysts that are the best in class for upgrading ethanol to butanol with a turnover number of 155,890 and a turnover frequency of 12,690 h –1 . In addition to upgrading ethanol to butanol, cascade reaction sequences were developed to form new C-C bonds using ethanol as a bio-relevant feedstock, providing access to platform chemicals from renewable sources. As part of the reaction discovery process, new mechanistic details were uncovered that provided insights into: a) catalyst speciation, b) decomposition pathways, c) carbon monoxide releasing pathways, and d) carbon-carbon and carbon hydrogen bond breaking pathways. Most of these outcomes were previously not known; however, they provide important directions for new catalyst design strategies. Finally, use of high throughput and in situ photochemical reaction analyses enabled detailed studies into changes to the catalyst structure upon irradiation. Irradiation was found to improve hydrogen transfer catalysis, by promoting a ligand dissociation event.

09 BIOMASS FUELS↗
DOE OSTI2024

Development of Additive Manufacturing for Ceramic Matrix Composite Vanes

This report discusses the development of additive manufacturing for polymer-derived ceramic materials to create novel cooled gas turbine airfoils made from ceramics. Gas turbine engines have extremely high temperatures in the hot section of the engine that exceed the melting point of nickel superalloy materials that the engine is made from. Advanced cooling technologies have been developed over decades for metallic parts. Ceramic materials have higher temperature capabilities than superalloys, but are difficult to shape in the complex designs used in modern turbines. Several thrusts were investigated during the project, including development of higher material strength resins, improvement of ultraviolet (UV) photopolymerization and post-processing techniques to increase survivability of ceramic parts, thermomechanical modeling of novel ceramic airfoil designs for higher cooling effectiveness, and experimental validation of the modeling and manufacturing in a turbine vane test facility at nondimensional conditions that are relevant to modern gas turbines. Some major findings of the work include a significant increase in ceramic survivability during pyrolysis (a high temperature process that converts the organic material to a ceramic) by adjusting the composition ratios of the resins, as well as a tolulene soak after printing to remove unreacted polymer material. Thermomechanical optimization of the internal cooling structure indicated that a high density pin fin array would enable an 80% increase in overall cooling effectiveness relative to a baseline geometry, which was later verified during experimental testing in a high speed linear cascade. Ceramic vanes were tested at Mach numbers of up to 0.9 which is relevant to modern gas turbines. High temperature capability of the ceramic vanes was not tested in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Best Practices Guide for Energy-Efficient Data Center Design

This guide provides an overview of best practices for energy-efficient data center design which spans the categories of information technology (IT) systems and their environmental conditions, data center air management, cooling and electrical systems, and heat recovery. IT system energy efficiency and environmental conditions are presented first because measures taken in these areas have a cascading effect of secondary energy savings for the mechanical and electrical systems. This guide concludes with a section on metrics and benchmarking values by which a data center and its systems energy efficiency can be evaluated. No design guide can offer “the most energy-efficient” data center design but the guidelines that follow offer suggestions that provide efficiency benefits for a wide variety of data center scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A Review of Resilience and Long-Term Planning in Power and Water Systems in the United States

There is recognition among power and water utilities that the frequency and magnitude of high consequence and low probability events could increase as a result of climate change. The interconnected nature of energy-water systems raises the possibility of cascading failures, increasing complexity and risks. Resilience and long-term planning are important ways of weathering the effects of climate change. First, to understand more about resilience, we reviewed existing literature on resilience definitions, metrics, and modeling, focusing on integrated water-power systems. Second, to understand how resilience and planning are being applied in practice, we interviewed utilities and organized, curated, and synthesized the interview data to arrive at several key findings, which are presented here. We found that there is not a consistent definition for resilience, yet it is something that utilities regularly plan for, often with different names and varying methods/measures. However, there is a tangible shift in the industry towards defining and determining measurable resilience metrics. While the exact metrics are a work in progress, utilities are taking steps forward by (1) putting people and culture at the center of resilience, (2) recognizing their own interdependencies, and (3) pursuing better cross-sector collaboration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Supporting Risk-informed Decision-making During Reactor Accidents

Uncertainty in severe accident evolution and outcome is driven by event bifurcations that represent distinctive challenges to defensive layers and tend to promote the emergence of discrete classes of core damage and accident risk. This discrete set of "attractor" states arise from the complex networks of competing physical phenomena and conditional event cascades occurring as the overall system degrades – a process that yields increasing degrees of freedom and accident progression pathways. Characterization of these event spaces has proven elusive to more traditional data interrogation methods, but proves tractable by application of more advanced data collection and machine learning approaches. Through application of these approaches we demonstrate a conceptual framework that enables real-time/robust, risk-informed decision-making support to improve accident mitigation and encourage “graceful exits” during low probability, extreme events limiting accident consequences. In this analysis, we simulated over 8,000 short-term station blackout (STSBO) accidents with the state-of-the-art integral severe accident code, MELCOR, and demonstrate the potential for ML approaches to predict simulation outcomes. We chose to pair ML tools with interpretable and mechanistic event trees for the considered STSBO accident space to predict the likelihood of future event paths along the tree. In addition to the current state of the system, we use information from recent trajectories of temperature, pressure, and other physical features, combining both the current state and past trajectories to forecast future event paths. Finally, we simulate the random injection of variable amounts of water to quantify the efficacy of available actions at reducing risks along the many branches in the event tree. We identify scenarios and windows of opportunity to mitigate risk as well as scenarios in which such actions are unlikely to alter the accident end-state.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗