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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

In-depth quantitative proteomic characterization of organotypic hippocampal slice culture reveals sex-specific differences in biochemical pathways

Sex differences in the brain of mammals range from neuroarchitecture through cognition to cellular metabolism. The hippocampus, a structure mostly associated with learning and memory, presents high vulnerability to neurodegeneration and aging. Therefore, we explored basal sex-related differences in the proteome of organotypic hippocampal slice culture, a major in vitro model for studying the cellular and molecular mechanisms related to neurodegenerative disorders. Results suggest a greater prevalence of astrocytic metabolism in females and significant neuronal metabolism in males. The preference for glucose use in glycolysis, pentose phosphate pathway and glycogen metabolism in females and high abundance of mitochondrial respiration subunits in males support this idea. An overall upregulation of lipid metabolism was observed in females. Upregulation of proteins responsible for neuronal glutamate and GABA synthesis, along with synaptic associated proteins, were observed in males. In general, the significant spectrum of pathways known to predominate in neurons or astrocytes, together with the well-known neuronal and glial markers observed, revealed sex-specific metabolic differences in the hippocampus. TEM qualitative analysis might indicate a greater presence of mitochondria at CA1 synapses in females. These findings are crucial to a better understanding of how sex chromosomes can influence the physiology of cultured hippocampal slices and allow us to gain insights into distinct responses of males and females on neurological diseases that present a sex-biased incidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Pressure-induced crystallization of an amorphous martensite alloy

Recently, solid-state amorphization through temperature-induced martensitic transition has been reported. The stability of the amorphous martensite phase, which co-exists with a crystalline counterpart, is intriguing but remains ill-defined. In this work, we studied the structural stability of a Ti 59.1 Zr 37 Cu 2.3 Fe 1.6 amorphous martensite alloy by combining in situ high-pressure synchrotron x-ray diffraction with ex situ transmission electron microscopy. During compression at room temperature, an irreversible pressure-induced crystallization of the amorphous martensite phase into a β-Ti phase is revealed. Qualitative analysis reveals the important role of the local atomic strain in stabilizing/destabilizing amorphous martensite alloys and its high tunability of the local atomic strain under high pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ELM-free enhanced D α H-mode with near zero NBI torque injection in DIII-D tokamak

Enhanced D α H-mode (EDA H-mode), an ELM-free H-mode regime, and the concomitant quasi-coherent mode (QCM) are explored in neutral beam heated, lower single null plasmas with near zero external torque injection. This regime exhibits good energy confinement (H 98y2 ~ 1) with β N ~ 2, high density, regime access at low input power, and no ELMs. New time–resolved measurements of electron and ion density, temperature, plasma rotation, and radial electric field as well as turbulence, flows, thermal and particle transport, and linear instability calculations examining the dynamics of the QCM are presented. Measurements using multiple fluctuation diagnostics reveal the QCM to be a separatrix spanning mode, peaking just inside the separatrix, existing in a wide range of k ⊥ ρ s ~ 0.1–1.2 with multiple harmonics, and propagating with a very small phase velocity in the plasma frame, where k ⊥ is the binormal wavenumber and ρ s is the ion sound radius. Linear gyrokinetic simulations of this EDA H-mode discharge with CGYRO indicate that the trapped electron mode (TEM) and electron temperature gradient mode are the dominant instabilities in the radial region where QCM is also unstable. Qualitative analysis indicates that the properties of TEM are consistent with the experimentally observed characteristics of the QCM. These similarities suggest that the QCM is consistent with a TEM instability existing in the edge region of the EDA H-mode plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

A quantitative imaging framework for lithium morphology: Linking deposition uniformity to cycle stability in lithium metal batteries

Characterizing the morphology of lithium (Li) is crucial for developing long-lasting lithium metal batteries. It is well established that more uniform Li deposition correlates with better cell performance. Li morphology is often characterized through qualitative analysis of scanning electron microscopy (SEM) images; however, there are no widely accepted metrics to quantitatively describe deposition uniformity. Here, we propose a framework to quantify uniformity through SEM image analysis via the index of dispersion (ID) metric, which is defined and presented in the context of Li metal batteries. We also explore experimental impacts of sampling protocols onIDmeasurements. Our results demonstrate that theIDmetric is highly sensitive to variations in deposition uniformity, including the coexistence and uniformity of multiple morphologies, uniformity within a single morphology, and particle size distribution uniformity. Furthermore, it is demonstrated that uniformity, as measured by theID, can be related to the average potential of Li||Li symmetric cells over cycling. Higher capacity cycling leads to more pronounced changes in bothIDand average cell potential. Local minima/maxima are found consistently in bothIDand average cell potential immediately before cells short-circuit, which we suggest may indicate a collapse of the microstructure prior to failure. We put forward this framework as a more robust approach to quantify Li deposition uniformity, advancing the development of Li metal batteries that are safer and longer lasting.

Science & Technology - Other Topics↗
DOE OSTI2025

Implementation of the D1S Methodology for Shutdown Dose Rate Calculations in the OpenMC Monte Carlo Particle Transport Code

We present an implementation of the direct one-step (D1S) methodology for shutdown dose rate (SDR) calculations in the OpenMC Monte Carlo particle transport code. In addition to being the first fully open-source D1S implementation, it is also the first to require no ad hoc source code or nuclear data library modifications. The code can seamlessly switch between production of prompt and decay photons based on a user input parameter, and the decay data needed for decay photon generation are made available through a depletion chain file, which is already used for OpenMC’s built-in depletion/activation solver. A set of Python functions significantly eases the burden of computing and applying time correction factors needed to properly account for the time dependence of radionuclide activity. To assess the accuracy of the D1S implementation, SDR calculations have been carried out for three problems: a prism of iron irradiated by 14-MeV neutrons, the ITER port plug computational benchmark, and the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For each of these problems, comparisons were made to calculations using the rigorous two-step (R2S) method. The results on the iron prism problem illustrate how the D1S method achieves superior spatial resolution compared to the R2S method without the need for spatial discretization of the activation regions. The D1S and R2S results for the ITER port plug benchmark agree well with previously reported results in the literature. While the D1S results are 10% to 15% lower than the R2S results, this may be due to stochastic uncertainty and/or spatial discretization in the R2S calculations. On the FNG dose rate benchmark problem, the D1S method produces dose rate estimates that are within 4% of the dose rates predicted using a cell-based R2S workflow. The D1S estimates of the SDR are also in reasonable agreement with the experimental measurements and show the same basic trends that have been observed in previous works. A qualitative analysis of the execution time and uncertainty for the R2S and D1S workflows suggests that the D1S method would attain a higher figure of merit.

D1S method↗
DOE OSTI2021

COMPASO : A new halo finder for competitive assignment to spherical overdensities

We describe a new method (compaso) for identifying groups of particles in cosmological N-body simulations. compaso builds upon existing spherical overdensity (SO) algorithms by taking into consideration the tidal radius around a smaller halo before competitively assigning halo membership to the particles. In this way, the compaso finder allows for more effective deblending of haloes in close proximity as well as the formation of new haloes on the outskirts of larger ones. This halo-finding algorithm is used in the abacussummit suite of N-body simulations, designed to meet the cosmological simulation requirements of the Dark Energy Spectroscopic Instrument (DESI) survey. compaso is developed as a highly efficient on-the-fly group finder, which is crucial for enabling good load-balancing between the GPU and CPU and the creation of high-resolution merger trees. In this paper, we describe the halo-finding procedure and its particular implementation in abacus, accompanying it with a qualitative analysis of the finder. We test the robustness of the compaso catalogues before and after applying the cleaning method described in an accompanying paper and demonstrate its effectiveness by comparing it with other validation techniques. We then visualize the haloes and their density profiles, finding that they are well fit by the NFW formalism. Finally, we compare other properties such as radius–mass relationships and two-point correlation functions with that of another widely used halo finder, rockstar.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Tackling the Challenges in Scene Graph Generation With Local-to-Global Interactions

In this work, we seek new insights into the underlying challenges of the scene graph generation (SGG) task. Quantitative and qualitative analysis of the visual genome (VG) dataset implies: 1) ambiguity: even if interobject relationship contains the same object (or predicate), they may not be visually or semantically similar; 2) asymmetry: despite the nature of the relationship that embodied the direction, it was not well addressed in previous studies; and 3) higher-order contexts: leveraging the identities of certain graph elements can help generate accurate scene graphs. Motivated by the analysis, we design a novel SGG framework, Local-to-global interaction networks (LOGINs). Locally, interactions extract the essence between three instances of subject, object, and background, while baking direction awareness into the network by explicitly constraining the input order of subject and object. Globally, interactions encode the contexts between every graph component (i.e., nodes and edges). Finally, Attract and Repel loss is utilized to fine-tune the distribution of predicate embeddings. By design, our framework enables predicting the scene graph in a bottom-up manner, leveraging the possible complementariness. To quantify how much LOGIN is aware of relational direction, a new diagnostic task called Bidirectional Relationship Classification (BRC) is also proposed. Overall, experimental results demonstrate that LOGIN can successfully distinguish relational direction than existing methods (in BRC task), while showing state-of-the-art results on the VG benchmark (in SGG task).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Phenomenological Thermal Spray Wall Interaction Modeling Framework Applied to a High Temperature Ignition Assistant Device

Airborne compression ignition engines must operate with reliable ignition systems to achieve proper ignition at every cycle, particularly at high altitudes. Glow-plug-based ignition-assistant (IA) devices can provide the necessary energy to preheat the fuel and ensure ignitability of the fuel-air mixture. Ignitability of liquid sprays can be facilitated via direct impingement onto the hot IA surface, however this comes with adverse effects on the IA durability. Therefore, optimizing an IA’s design requires detailed understanding of the physics of fuel spray impingement of superheated surfaces. While spray impingement on relatively low wall temperatures has been extensively studied and appropriate numerical models have been proposed through the years, fundamental understanding of high-speed liquid spray impingement on superheated walls is still elusive. This work aims to formulate a phenomenological thermal spray-wall interaction framework for modeling the film-boiling-induced heat transfer, atomization, and dispersion of fuel spray droplets impinging onto a superheated IA device. A qualitative comparison of the new phenomenological model is performed against optical experiments from the literature of an F-24 fuel spray injected onto an IA device located 12 mm away from the injector tip. The temperature of the IA was set at 1400 K. The fuel injection pressure was 400 bar, while the ambient gas pressure and temperature were 30 bar and 800 K, respectively. The performance of the phenomenological model is evaluated in comparison with two other state-of-art models from the literature. A qualitative analysis of the different spray and fuel-air mixture characteristics is performed to outline the differences in the predictions offered by the new phenomenological model and the two state-of-art spray-wall interaction models.

droplet dispersion↗
DOE OSTI2024

RuBisCO activity assays: a simplified biochemical redox approach for in vitro quantification and an RNA sensor approach for in vivo monitoring

Abstract Background Ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is the most abundant soluble protein in nature. Extensive studies have been conducted for improving its activity in photosynthesis through approaches like protein engineering. Concurrently, multiple biochemical and radiolabeling assays have been developed for determining its activity. Although these existing assays yield reliable results, they require addition of multiple external components, rendering them less convenient and expensive. Therefore, in this study, we have developed two relatively cheaper, convenient, and easily reproducible assays for quantitative and qualitative estimation of RuBisCO activity. Results We simplified a contemporary NADH based spectrophotometric RuBisCO assay by using cyanobacterial cell lysate as the source for Calvin cycle enzymes. We analyzed the influence of inorganic carbon substrates, CO 2 and NaHCO 3 , and varying protein concentrations on RuBisCO activity. Ribulose-1,5-bisphosphate (RuBP) consumption rates for the cultures grown under 5% CO 2 were 5–7 times higher than the ones grown with 20 mM NaHCO 3 , at different protein concentrations. The difference could be due to the impaired activity of carbonic anhydrase in the cell lysate, which is required for the conversion of HCO 3 − to CO 2 . The highest RuBisCO activity of 2.13 nmol of NAD + / µg of Chl-a/ min was observed with 50 µg of protein and 5% CO 2 . Additionally, we developed a novel RNA-sensor based fluorescence assay that is based on the principle of tracking the kinetics of ATP hydrolysis to ADP during the conversion of 3-phosphoglycerate (3-PG) to 1,3-bisphosphoglycerate (1,3-BPG) in the Calvin cycle. Under in vitro conditions, the fluorometric assay exhibited ~ 3.4-fold slower reaction rate (0.37 min −1 ) than the biochemical assay when using 5% CO 2 . We also confirmed the in vivo application of this assay, where increase in the fluorescence was observed with the recombinant strain of Synechocystis sp. PCC 6803 (SSL142) expressing the ADP-specific RNA sensor, compared to the WT. In addition, SSL142 exhibited three-fold higher fluorescence when supplemented with 20 mM NaHCO 3 as compared to the cells that were grown without NaHCO 3 supplementation. Conclusions Overall, we have developed a simplified biochemical assay for monitoring RuBisCO activity and demonstrated that it can provide reliable results as compared to the prior literature. Furthermore, the biochemical assay using 5% CO 2 (100% relative activity) provided faster RuBP consumption rate compared to the biochemical assay utilizing 20 mM NaHCO 3 (30.70% relative activity) and the in vitro fluorometric assay using 5% CO 2 (29.64% relative activity). Therefore, the absorbance-based biochemical assay using 5% CO 2 or higher would be suitable for in vitro quantification of the RuBisCO activity. On the other hand, the RNA-sensor based in vivo fluorometric assay can be applied for qualitative analysis and be used for high-throughput screening of RuBisCO variants. As RuBisCO is an enzyme shared amongst all the photoautotrophs, the assays developed in this study can easily be extended for analyzing the RuBisCO activities even in microalgae and higher plants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Inferring microbial interactions with their environment from genomic and metagenomic data

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized , and so name our tool MetConSIN: Met abolically Con textualized S pecies I nteraction N etworks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Fire is historically and analytically a significant contributor to nuclear power plant risk. The level of fire risk and the methods, tools and data for modeling this risk is highly debated by experts. One area of debate is the input data used in fire modeling and how to deal with this data’s high uncertainty. This report outlines initial work performed for determining the key parameters causing this uncertainty and how it propagates into nuclear power plant models. This research paves the way for the development of methods to reduce fire data uncertainty used in modeling. The Nuclear Regulatory Commission has mandated that nuclear power plants perform fire risk modeling. However, there are several issues with the current risk modeling implementation that affect the results. Approved modeling methods can be overly conservative and often do not match plant experience. Also, the data used in the modeling can have high uncertainties and is influenced by expert judgement. To evaluate input data uncertainty, researchers performed an initial review of several fire experiments done at Sandia National Laboratories. Uncertainties for fire data can come from many sources, such as experiment design constraints, environmental conditions, or other plant-specific aspects. There are many different significant and insignificant parameters driving the uncertainty. Additionally, the uncertainty of the different input data used in the fire modeling could have a significant or insignificant effect on the entire plant risk. A four-step methodology was developed to perform Integrated Probabilistic Risk Assessment Importance Ranking. A demonstration case using these steps was set up and three of the four steps were completed in fiscal year (FY) 2019 and the fourth step done FY 2020. These steps are: 1. The qualitative analysis of potential sources was conducted with the following items identified for the demonstration. • Maximum heat release rate • Time to maximum heat release rate • Duration of max heat release rate • Time to decay • Thermal conductivity of concrete • Specific heat of concrete • Density of concrete • Cable jacket thickness 2. A quantitative characterization of dominant sources of uncertainty was performed. A list of distributions and determined values of the dominant sources is shown in Appendix A. 3. A quantitative screening of the potential sources of uncertainty using Morris Elementary Effects Analysis was completed. An experimental model using the physics-based fire modeling tool Fire Dynamics Simulator was developed and coupled with the Risk Analysis Virtual Environment. The Morris analysis identified at least two parameters that can be eliminated as significant contributors (specific heat of concrete and cable jacket thickness). 4. Global importance measure (Global IM) analysis to generate a comprehensive ranking based on their influence on the plant risk. In this research, a moment-independent Global IM is used since it can address (a) uncertainty in the input parameters of the fire model, (b) uncertainty in the risk outputs, and (c) non-linearity and interactions among input parameters in the fire model, more accurately than the correlation-based and variance-based global methods. The observations from the research showed that, depending on the initial and boundary conditions of the fire scenarios, fire-induced damage could have a very small probability and could be dominated by the tail of the uncertainty distribution; hence, the accuracy of the correlation-based and variance-based methods is questionable. The moment-independent Global IM analysis in this research provides a better understanding of how experimental uncertainty data affects industry’s plant models and where improvements in that data will have the largest benefit for improving fire modeling accuracy in causing core damage. Among the five unscreened parameters obtained from the Morris EE analysis, the Global IM analysis results for the case study indicated that max heat release rate and fire location are the most important parameters. The report also outlines benefits of using a unified computational platform that integrates the underlying simulations (e.g., a fire progression model), quantitative screening (using the Morris EE method), and the Global IM analysis. A unified platform can (i) facilitate the ranking of input parameters considering multiple key fire scenarios simultaneously, rather than considering one scenario at a time, (ii) contribute to more explicit and accurate treatment of dependencies at multiple levels of Fire PRA, (iii) facilitate the sampling-based uncertainty quantification for Fire PRA, and (iv) help generating both “industry-wide” and "plant-specific" ranking of uncertainty sources in Fire PRA. Future research should be done to include additional parameters such as detection/suppression or cable fire spread. Adding a PRA software such as SAPHIRE to the RAVEN platform would help with plant model integration and improve treatment of fire-induced dependency. The I-PRA risk importance ranking methodology offered in this report can provide valuable information for efficiently (a) enhancing the realism of Fire PRA for existing plants and (b) supporting the development of Dynamic Fire PRA for advanced reactors and new plants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Integrated Strategies to Enable Lower-Cost Biofuels

This report summarizes the findings of a qualitative analysis to identify integrated strategies needed for more affordable biofuels. It outlines five key strategies needed to achieve lower fuel production costs in an integrated biorefinery and provides high-level research needs across the biofuel supply chain.

09 BIOMASS FUELS↗
DOE OSTI2021

Computed Tomography Scanning and Geophysical Measurements of the Wabash No.1 Core

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize Mt. Simon core from the Wabash CarbonSAFE project, Wabash No. 1 well. The primary impetus of the work in this report is a collaboration between NETL Research and Innovation Center and the Illinois State Geological Survey at the Prairie Research Institute, University of Illinois Urbana-Champaign in Champaign, Illinois. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/wabash-no-1-well. The Wabash No. 1 well was drilled as part of a U.S. Department of Energy (DOE) funded Carbon Storage Assurance Facility Enterprise field project to assess the feasibility of developing a commercial-scale geological storage complex at the Wabash Valley Resources Integrated Gasification Combined Cycle plant near Terre Haute, Indiana. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. None of the equipment used was suitable for direct visualization of the pore space in fine-grained structures; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy-related examinations traditionally performed at NETL.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Core Characterization of Bakken Shale from the Bedwell 33-52-1-1H Well, Sheridan County, Montana

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize core of the Bedwell 33-52-1-1H well (API 25-091-21920), a wildcat field in Sheridan County, Montana. The primary impetus of this work is to provide a unique dataset to researchers at universities, national laboratories, geological surveys, and other locations for additional analyses. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/bedwell-33-52-1-1h-well. The equipment and techniques used to characterize the full core were non-destructive, enabling future examinations and analyses to be performed on these cores. However, none of the equipment used was suitable for direct visualization of the pore space in fine-grained structures such as those found in shales; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. A selection of samples (Table 1) were cored, sliced, and powdered for additional characterization analyses. These analyses did involve destructive subsampling of the full core at discrete sections, and the results are presented here in the context of the larger core description. Selected sections of the core were removed from the full core for detailed analyses using the following destructive techniques: bulk inductively coupled plasma-optical emission spectroscopy (ICP-OES), isolation of carbon and sulfur, Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and higher resolution CT scan with NETL’s micro-CT scanning systems. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy related examinations traditionally performed at NETL.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Evaluating China's Road to Cyber Super Power

This report examines open source, non-classified qualitative analysis to evaluate China’s current cyber maturity. Evidence for this document draws on materials from academia, private cybersecurity companies, and national security research institutions. Private sector threat intelligence firms produce high quality analysis on Chinese APTs tactics, techniques, and procedures (TTPs), and investigation from companies such as FireEye illuminate China’s ability to wield cyber means for its security ends. None of the materials cited in this assessment originate from classified United States or foreign government sources. Any references to United States government sources are sourced entirely to unclassified information.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

ECAR-5021 Source Term Estimates for SCO Micro-Reactor Designs

The purpose of this document is to provide source term estimates and the associated technical basis for Strategic Capabilities Office (SCO) microreactor designs that use TRISO fuel. This estimate can be used for relevant environmental and safety analyses that will be done as part of the project for all of the selected suppliers for a safety design strategy. This is a combined quantitative and qualitative analysis.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Geothermal Energy and Resilience in Arctic Countries

The eight Arctic countries - Iceland, Canada, Denmark (Greenland and the Faroe Islands) Norway, Sweden, Finland, Russia, and the United States (Alaska) - have diverse energy systems, but can be split into two distinct groups based on energy characteristics. The first group includes systems in Europe (Finland, Norway, Sweden, and Iceland), which are heavily grid-connected. The second group includes the United States (Alaska), Canada, Russia, and Greenland, which have grid-connected energy systems in their more densely populated southern regions, but are also defined by the prevalence of remote microgrids. Energy sources for heat and power vary across grid-connected communities in the Arctic nations. The primary energy source for remote communities, on the other hand, is almost exclusively diesel. This is true for both heat and power. Despite these and other key distinctions, Arctic countries share many commonalities with regard to their energy systems. One is a fundamental need for heat. Heat and electric energy are linked in most communities - remote, rural, and urban - and those linked systems are increasingly vulnerable to disruptions. Several of the Arctic countries use baseload renewable energy resources for heat and power. Iceland uses geothermal and hydroelectric; Canada, the United States, Sweden, Norway, and Finland use hydroelectric. Utilization of baseload renewable energy resources on-site for combined heat and power appears to enhance the resilience of communities in Arctic countries with high penetration of those resources. On the other hand, reliance on diesel by remote communities in other Arctic countries may be amplifying vulnerabilities. Although geothermal energy is currently used in all eight Arctic countries, resources are poorly mapped, and details can be difficult to come by. Despite this, geothermal energy provides heat and sometimes electricity at both utility scales and at the microgrid scale. Geothermal electricity is produced in Iceland, Russia, and the United States (Alaska). Direct use of geothermal heat is used in Iceland, Russia, United States, Canada, and Norway. Geo-exchange is used in Sweden, Finland, Norway, Canada, and the United States. In this paper, we reframe geothermal heat and power systems as integrated energy systems, asking the question: are integrated geothermal energy systems - where available and economic - resilient solutions for communities in Arctic countries? We identify resilience attributes of integrated geothermal energy systems, with a focus on microgrids and small-scale applications. Based on the high-level, qualitative analysis presented in this paper, the answer appears to be yes. Further work should prioritize refining our understanding of geothermal resources in Arctic countries, because development of the most economic geothermal resources in Arctic countries has the potential to enhance the energy resilience of its residents, whether in a grid-connected or remote off-grid context.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Scoping Study for Direct Power Extraction (DPE) Systems (Final Report)

NETL led a detailed scoping study of various direct power extraction systems and concepts for utility power generation. The study consisted of qualitative analysis along with quantitative techno-economic analysis of selected systems which use magnetohydrodynamic (MHD) power generators.

24 POWER TRANSMISSION AND DISTRIBUTION↗