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DOE OSTI2021

Completion of Milestone for Receiving Reinstrumentation Equipment from IFE

This set of powerpoint slides demonstrates how milestone "M2CT-21IN0702026: Receive prototype drilling and defueling modules for the re-instrumentation facility procured from the Institute For Energy (Halden, Norway) at the Idaho National Laboratory" was met. It supports an entry in PICS claiming achievement of the milestone. These slides provide a good summary of the purpose and impact of the milestone for our DOE Headquarters colleagues.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

COMBLE Radar b1 Processing: Corrections, Calibrations, and Processing Report

The U.S. Department of Energy’s (DOE) Atmospheric Radiation Measurement (ARM) user facility recently concluded its Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE), with its campaign emphasis on marine boundary-layer clouds and mixed-phase clouds during cold-air outbreaks. The COMBLE campaign featured the deployment of the first ARM Mobile Facility (AMF1) to northern Scandinavia (Andenes, Norway), including its standard complement of ARM cloud radars. In keeping with user demands stemming from the previous AMF Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in Argentina, a post-campaign radar mentor effort was initiated for COMBLE. This activity was intended to improve the usability of the ARM cloud radar data sets in response to overall demands for calibrated, corrected data sets for downstream studies and retrieval applications. In addition to the terrain complexities previously important to CACTI data sets (e.g., clutter designation and/or removal), COMBLE presented new challenges to existing ARM radar mentor capabilities. These included the extension of existing methodologies (e.g., relative calibration adjustment [RCA] target techniques) to frozen environments and the potential issues with their applicability when considering mixed-phase precipitation conditions. As in the previous CACTI documentation (Hardin et al. 2020), the overall calibration and conditioning process in ARM nomenclature is referred to as generating a “b1” datastream. For the radars, these “b1” standards refer to a datastream that has been calibrated (and cross-calibrated), with effort to deliver the highest-quality (well-characterized) data possible. The “b1” radar mentor reporting (this current document) is intended to detail (i) the status/quality of the original “a1” (raw) data sets during the COMBLE AMF campaign, (ii) the corrections and calibrations that are applied to generate the b1 datastreams available on ARM’s Data Discovery, and (iii) the details of the applied methods, e.g., how radar offset/calibration numbers were determined.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Potential Availability of Alternative Fuel to Supply Maritime Activities in Pacific Northwest Ports

The international shipping sector represented 3% of global greenhouse gas emissions in 2023 (Office of Energy Efficiency & Renewable Energy 2024). International shipping has been classified as a difficult-to-decarbonize industry (IRENA 2024). In an effort to drive decarbonization, the U.S. Department of Energy has partnered with Mission Innovation to co-lead the Zero-Emission Shipping Mission, which launched in 2021(Office of Energy Efficiency & Renewable Energy 2021). In addition, the U.S. Department of State partnered with Norway to launch the Green Shipping Challenge in 2022 (Office of the Spokesperson 2022b). As part of the ZESM and Green Shipping Challenge, the United States is collaborating with the Republic of Korea (ROK) to develop a green shipping corridor (U.S. Mission Korea 2023). The United States and ROK have conducted a pre-feasibility study as the first step in developing a green shipping corridor between the countries. The ports included in the study are Seattle, Tacoma, and Everette in the U.S. Pacific Northwest (PNW) and Busan, Ulsan, and Masan in ROK. The National Renewable Energy Laboratory's role in the study was to analyze the availability and technical potential of alternative marine fuels in proximity to U.S. PNW ports. The findings show most of the existing alternative fuel capacity within the region is from renewable diesel, biodiesel, and sustainable aviation fuel facilities. The largest growth in fuel capacity in the region by 2030 is projected to be in renewable diesel and hydrogen. The overall technical readiness of non-drop-in alternative fuel production and conversion technologies is more developed than alternative-fueled ships and associated fueling infrastructure. However, much of the fuel capacity in the region is comprised of drop-in fuels, making it technically possible to use existing infrastructure for transporting and bunkering to the existing fleet. Data to inform regional alternative fuel quantity estimations were collected from an extensive review of databases, reports, announcements, and other publicly available resources. A maturity index and sector competition factor were applied to announced fuel projects to determine the quantity of alternative fuel available to the marine sector in the region by 2030. Demand data were collected from fuel bunkering logs covering the PNW seaports (State of Washington 2021). Both supply and demand data were converted to very-low sulfur fuel oil gallon equivalents (VLSFO-GE) for better comparison. Qualitative data were gathered through interviews with stakeholders, project developers, and industry experts. Total alternative fuel capacity available to the marine sector in the region is estimated to be 824 million VLSFO-GE per year by 2030. This is sufficient to cover the requirements of a green shipping corridor between the United States and ROK. The findings from this report are being used to inform detailed feasibility studies for several U.S. PNW -ROK green shipping corridors. Updates from the U.S. PNW - ROK feasibility studies will continue to be published on Mission Innovation's green corridor tracking website (Zero Emission Shipping Mission, n.d.). In addition, this report has helped to inform further work on shipping decarbonization in the U.S. PNW, including the Pacific Northwest to Alaska Green Corridor focused on cruise vessels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Transformational Sorbent-Based Process for a Substantial Reduction in the Cost of CO2 Capture

Adsorption processes have the potential to significantly reduce the CO2 capture cost from power plants and industrial flue gases. InnoSepra has developed several sorbent-based technologies to obtain very high CO2 recovery and high purity CO2 while meeting the EOR/sequestration product specifications. A first-generation process was shown to achieve CO2 recoveries greater than 94% at CO2 purities in the range of 98.5-99.5%. The absolute heat energy required for the process was not only 40% lower than MEA but also was needed at a much lower temperature. This work will present the performance of the second-generation InnoSepra process which is based on a breakthrough sorbent regeneration method. This process has a projected 45% lower capital cost compared to MEA, less than 16% loss in plant output for CO2 capture and compression, and a CO2 capture cost at least 55% lower than MEA. Lab scale testing and the process simulations indicate a CO2 capture performance similar to or better than the first-generation process. Pilot scale drying and breakthrough tests were carried out at the Technology Centre Mongstad (TCM), Norway, and lab-scale cyclic tests were carried out at InnoSepra to confirm the process improvement. During these tests, InnoSepra’s flue gas purification technology was also tested at TCM. It can provide a low-cost option for the removal of NO2 and SOX to sub-ppm levels as well as a significant reduction in aerosol emissions.

08 HYDROGEN↗

DOE OSTI2025

Recent Collaborations and Innovations to Demonstrate Next-Generation Techniques for Monitoring Subsurface Carbon Storage

World Carbon Capture, Utilization, and Storage (CCUS) Conference, Bergen, Norway, September 1–4, 2025. This talk provides a high-level overview of many novel and sustainable carbon storage-monitoring methods to accelerate the deployment of CCUS technologies at future CCUS sites across the United States. The Energy & Environmental Research Center’s work impacts the general CCUS industry by providing novel low-impact methods for tracking the injected plume’s migration and more autonomous data collection and processing techniques for performing assurance monitoring. Specifically, the results benefit 1) CCUS community members through knowledge sharing of lessons learned; 2) CCUS operators through commercialization of additional methods, including improvements to workflows and simplification of fieldwork; and 3) CCUS project stakeholders through implementation of low-impact and more autonomous monitoring solutions.

02 PETROLEUM↗

DOE OSTI2021

Radical Coupling Reactions of Hydroxystilbene Glucosides and Coniferyl Alcohol: A Density Functional Theory Study

The monolignols, p-coumaryl, coniferyl, and sinapyl alcohol, arise from the general phenylpropanoid biosynthetic pathway. Increasingly, however, authentic lignin monomers derived from outside this process are being identified and found to be fully incorporated into the lignin polymer. Among them, hydroxystilbene glucosides, which are produced through a hybrid process that combines the phenylpropanoid and acetate/malonate pathways, have been experimentally detected in the bark lignin of Norway spruce (Picea abies). Several interunit linkages have been identified and proposed to occur through homo-coupling of the hydroxystilbene glucosides and their cross-coupling with coniferyl alcohol. In the current work, the thermodynamics of these coupling modes and subsequent rearomatization reactions have been evaluated by the application of density functional theory (DFT) calculations. The objective of this paper is to determine favorable coupling and cross-coupling modes to help explain the experimental observations and attempt to predict other favorable pathways that might be further elucidated via in vitro polymerization aided by synthetic models and detailed structural studies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Physicochemical characterization and source apportionment of Arctic ice-nucleating particles observed in Ny-Ålesund in autumn 2019

Abstract. Ice-nucleating particles (INPs) initiate primary ice formation in Arctic mixed-phase clouds (MPCs), altering cloud radiative properties and modulating precipitation. For atmospheric INPs, the complexity of their spatiotemporal variations, heterogeneous sources, and evolution via intricate atmospheric interactions challenge the understanding of their impact on microphysical processes in Arctic MPCs and induce an uncertain representation in climate models. In this work, we performed a comprehensive analysis of atmospheric aerosols at the Arctic coastal site in Ny-Ålesund (Svalbard, Norway) from October to November 2019, including their ice nucleation ability, physicochemical properties, and potential sources. Overall, INP concentrations (NINP) during the observation season were approximately up to 3 orders of magnitude lower compared to the global average, with several samples showing degradation of NINP after heat treatment, implying the presence of proteinaceous INPs. Particle fluorescence was substantially associated with INP concentrations at warmer ice nucleation temperatures, indicating that in the far-reaching Arctic, aerosols of biogenic origin throughout the snow- and ice-free season may serve as important INP sources. In addition, case studies revealed the links between elevated NINP and heat lability, fluorescence, high wind speeds originating from the ocean, augmented concentration of coarse-mode particles, and abundant organics. Backward trajectory analysis demonstrated a potential connection between high-latitude dust sources and high INP concentrations, while prolonged air mass history over the ice pack was identified for most scant INP cases. The combination of the above analyses demonstrates that the abundance, physicochemical properties, and potential sources of INPs in the Arctic are highly variable despite its remote location.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Surface-based observations of cold-air outbreak clouds during the COMBLE field campaign

Abstract. Cold-air outbreaks (CAOs) are characterized by extreme air–sea energy exchanges and low-level convective clouds over large areas in the high-latitude oceans. As such, CAOs are an important component of the Earth's climate system. The CAOs in the Marine Boundary Layer Experiment (COMBLE) deployment of the US Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility (AMF) provided the first comprehensive view of CAOs using a suite of ground-based observations at the northern coast of Norway. Here, cloud and precipitation observations from 13 CAO cases during COMBLE are analyzed. A vertical air motion retrieval technique is applied to the Ka-band ARM Zenith-pointing Radar (KAZR) observations. The CAO cumulus clouds are characterized by strong updrafts with magnitudes between 2–8 m s−1, vertical extents of 1–3 km, and horizontal scales of 0.25–3 km. A strong relationship between our vertical air velocity retrievals and liquid water path (LWP) measurements is found. The LWP measurements exceed 1 kg m−2 in strong updraft areas, and the vertical extent of the updraft correlates well with the LWP values. The CAO cumulus clouds exhibit eddy dissipation rate values between 10−3 and 10−2 m2 s−3 in the lowest 10 km of the atmosphere, and using a radar Doppler spectra technique, evidence of secondary ice production is found during one of the cases.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Aerosol size distribution properties associated with cold-air outbreaks in the Norwegian Arctic

The aerosol particles serving as cloud condensation and ice nuclei contribute to key cloud processes associated with cold-air outbreak (CAO) events but are poorly constrained in climate models due to sparse observations. Here we retrieve aerosol number size distribution modes from measurements at Andenes, Norway, during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) and at Zeppelin Observatory, approximately 1000 km upwind from Andenes at Svalbard. During CAO events at Andenes, the sea-spray-mode number concentration is correlated with strong over-ocean winds with a mean of 8±4 cm −3 that is 71 % higher than during non-CAO conditions. Additionally, during CAO events at Andenes, the mean Hoppel minimum diameter is 6 nm smaller than during non-CAO conditions, though the estimated supersaturation is lower, and the mean number concentration of particles that likely activated in-cloud is 109±61 cm −3 with no statistically significant difference from the non-CAO mean of 99±66 cm −3 . For CAO trajectories between Zeppelin Observatory and Andenes, the upwind-to-downwind change in number concentration is the largest for the accumulation mode with a mean decrease of 93±95 cm −3 , likely attributable primarily to precipitation scavenging. These characteristic properties of aerosol number size distributions during CAO events provide guidance for evaluating CAO aerosol–cloud interaction processes in models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Simulations of the collection of mesospheric dust particles with a rocket instrument

We investigate the collection of dust particles in the mesosphere with the MESS (MEteoric Smoke Sampler) instrument that is designed to fly on a sounding rocket. We assume that the ice particles that form in the polar mesosphere between 80 and 85 km altitude in summer contain meteoric smoke particles; and these should be collected with MESS. The instrument consists of a collection device with an opening and closure mechanism, as well as an attached conic funnel which increases the sampling area in comparison to the collection area. Dust particles are collected either directly after passing through the instrument or indirectly after colliding with and fragmenting on the funnel wall. We calculate the dust and fragment trajectories in the detector to determine the collection efficiency for different particle sizes, rocket velocities, and heights, and we find the final velocities and the temperatures of the particles. The considered design has a sampling area of 62.78 mm diameter and a collection area of 20 mm diameter. For the conditions at the rocket launch site in Andøya, Norway, we estimate the collection of meteoric smoke particles contained in the ice particles to be ~10 12 –10 14 amu mm –2 . The estimated temperatures suggest that the composition of these smoke particles is not affected by the collection. Our calculations also show that keeping the instrument open above 85 km altitude increases the amount of small smoke particles that are directly collected. The directly collected smoke particles are heated as they decelerate, which can affect their composition.

47 OTHER INSTRUMENTATION↗

DOE OSTI2025

Classifying thermodynamic cloud phase using machine learning models

Vertically resolved thermodynamic cloud-phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Thermodynamic Cloud Phase (THERMOCLDPHASE) value-added product (VAP) uses a multi-sensor approach to classify the thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave-radiometer-derived liquid water path, and radiosonde temperature measurements. The measured pixels are classified as ice, snow, mixed phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multi-layer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with 1 year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1 score, and mean intersection over union (IOU). Analysis of ML confidence scores shows that ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential data streams for ML thermodynamic cloud-phase predictions. Lidar measurements exhibit lower feature importance due to rapid signal attenuation caused by the frequent presence of persistent low-level clouds at the NSA site. The ML models' generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. The models demonstrated similar performance to that observed at the NSA site. Finally, we evaluate the ML models' response to simulated instrument outages and signal degradation and show that a CNN U-Net model trained with input channel dropouts performs better when input fields are missing.

ARM Aerial Facility↗

DOE OSTI2020

COMBLE-ISLAS water isotopes in precipitation (COMBLEISLASISO)

During the measurement period, precipitation was sampled on daily to sub-daily basis with a sampling kit consiting of a clear plastic box (60x40x40 cm) mounted to a ground structure. Daily sampling lasted from 22 Feb to 24 Mar 2020. At a fixed time of day (10 UTC), samples were collected and the sampling box cleaned for the next sample. Additionally, during intense observations periods (IOPs) announced by ISLAS, ARMS scientists increased sampling frequency to sub-daily sampling. During the campaign period, 2 IOPs were conducted, with in total 12 samples taken. IOP1 lasted from 27 Feb 10 to 02 Mar 2020, and IOP2 lasted from 12 Mar to 14 Mar 2020. Solid precipitation in the box was then melted, transferred to an 8 ml glass vial, sealed and shipped to FARLAB (University of Bergen, Norway) for stable water isotope analysis. Measured stable isotope composition of precipitation samples will be related to conditions at other sampling locations, and at the evaporation site to inform about conservation of water isotope quantities. In the period from 22 Feb to 24 Mar, 23 daily samples were collected at 10 UTC for stable water isotope analysis. During the entire sampling period, a high variability of precipitation phase was encountered. Most samples were recovered in the form of graupel/snow (12 samples), as rain (7 samples), and the remaining samples fell as graupel, snow, rain or frozen rain. Precipitation amounts varied between <1 mm (26 Feb) and 140 mm (25 Feb) within the sampling box. Furthermore, higher-resolution sampling was conducted during 2 intense observation periods (IOPs). During IOP1, lasting from 27 Feb 10 UTC to 02 Mar 10 UTC, 7 samples were collected, all of them as solid phase precipitation. IOP2 lasted from 12 Mar 10 UTC to 14 Mar 09 UTC, and 5 samples (all as graupel/snow) were collected. Samples were processed according to FARLAB standard measurement procedures. In short, samples were transferred to 1.5 ml glass vials with rubber/PTFE septa (part #548-0907, VWR, USA). An autosampler (A0325, Picarro Inc) transferred ca. 2µl per injection into a high-precision vapourizer (A0211, Picarro Inc, USA) heated to 110°C. After blending with dry N2 (< 5 ppm H2O) the gas mixture was directed into the measurement cavity of a Cavity-Ring Down Spectrometer (L2140-i, Picarro Inc) for about 7 min with a typical water concentration of 20 000 ppm. Memory effects were reduced by two times measuring a vapour mixture at a mixing ratio of 50 000 ppm, obtained from 2 injections of 2 µl for 5 min at the beginning of each new sample vial. Thereafter, another 6 injections of 2 µl per sample were measured individually as described above, and averages of the last 5 injections were used for further processing. Three standards were measured at the beginning and end of each batch, including a drift standard DI2 (δD: -50.72±0.73 permil, δ18O: -7.63±0.10 permil), and for calibration the laboratory standards GLW (δD: -307.79±0.75 permil, δ18O: -40.02±0.07 permil) and EVAP2 (δD: 9.52±0.65 permil, δ18O: 1.81±0.13 permil). A detailed calibration report is included with the final uploaded data set.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Thermodynamic Cloud Phase Classifications Using Machine Learning at NSA and ANX

Vertically resolved thermodynamic cloud phase classifications are essential for studies of atmospheric cloud and precipitation processes. The Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) THERMOCLDPHASE Value-Added Product (VAP) uses a multi-sensor approach to classify thermodynamic cloud phase by combining lidar backscatter and depolarization, radar reflectivity, Doppler velocity, spectral width, microwave radiometer-derived liquid water path, and radiosonde temperature measurements. The measured voxels are classified as ice, snow, mixed-phase, liquid (cloud water), drizzle, rain, and liq_driz (liquid+drizzle). We use this product as the ground truth to train three machine learning (ML) models to predict the thermodynamic cloud phase from multi-sensor remote sensing measurements taken at the ARM North Slope of Alaska (NSA) observatory: a random forest (RF), a multilayer perceptron (MLP), and a convolutional neural network (CNN) with a U-Net architecture. Evaluations against the outputs of the THERMOCLDPHASE VAP with one year of data show that the CNN outperforms the other two models, achieving the highest test accuracy, F1-score, and mean Intersection over Union (IOU). Analysis of ML confidence scores shows ice, rain, and snow have higher confidence scores, followed by liquid, while mixed, drizzle, and liq_driz have lower scores. Feature importance analysis reveals that the mean Doppler velocity and vertically resolved temperature are the most influential datastreams for ML thermodynamic cloud phase predictions. The ML models’ generalization capacity is further evaluated by applying them at another Arctic ARM site in Norway using data taken during the ARM Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) field campaign. Finally, we evaluate the ML models’ response to simulated instrument outages and signal degradation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa

Corresponding Standard Reference Material Data used in Partial Least Squares Regression Models for Sugar Composition Estimates in Biomass in: Economic Impact of Yield and Composition Variation in Bioenergy Crops: Populus trichocarpa (for corresponding manuscript: DOI: 10.1002/bbb.2148) PDF Files: Images of 1H NMR spectra for neutralized 2-stage acid hydrolysates of 4 NIST Standard Reference Material biomass samples (Monterey Pine 8493, Sugarcane Bagasse 8491, Wheat Straw 8494, and Eastern Cottonwood/Poplar 8492) and 2 Center for Bioenergy Innovation reference biomass samples (Poplar - Populus trichocarpa and Switchgrass - Panicum Virgatum). Suppression of the water peak was achieved using a NOESY-1D with presaturation, a recycle delay of 5 s, and a total of 64 scans. Spectra were acquired at 298 K and processed with automatic phase correction, baseline correction, and chemical shift referencing to TSP-d4. Images show all 1H data from 10 to 1ppm with inset spectra of region of interest (4.0 to 3.1 ppm). Text Files: Spectra for neutralized 2-stage acid hydrolysates of 4 NIST Standard Reference Material biomass samples (Monterey Pine 8493, Sugarcane Bagasse 8491, Wheat Straw 8494, and Eastern Cottonwood/Poplar 8492) and 2 Center for Bioenergy Innovation reference biomass samples (Poplar - Populus trichocarpa and Switchgrass - Panicum Virgatum) were converted into text files for plotting. Files contain 8192 points of raw spectral data from 12.23 to -2.78 ppm. The text file contains 4 columns of data and includes: Point number, Intensity, Hz, and ppm. Xcel Spreadsheet: HPLC measured monomeric sugar concentrations and bucketed 1H NMR data used to build monomeric sugar composition prediction models. Sugar composition in biomass determined from HPLC analyses are given in mg sugar/mg of biomass. Spectral bucketing was performed using Bruker’s AMIX software. Spectra were divided into 0.005 ppm buckets in the region of 3.10– 4.15 ppm for a total of 210 buckets. Headers for the bucketed data are the chemical shift in ppm of the center of the bucket. Bucketed data was used to build partial least squares models for subsequent predictions in The Unscrambler v. 10.5(CAMO A/S, Trondheim, Norway). The formation of methanol during hydrolysis interferes with the quantitative NMR analysis of sugars, so the methanol peak centered at 3.37 ppm and spanning four buckets (3.2925 – 3.2775 ppm) was set to zero for all spectra.

09 BIOMASS FUELS↗

DOE OSTI2021

Geothermal Energy and Resilience in Arctic Countries

The eight Arctic countries have diverse energy systems but can be split into two distinct groups based on energy characteristics. The first group includes countries which are heavily gridconnected (Iceland, Norway, Sweden, and Finland); the second group includes countries with some grids as well as an abundance of remote microgrids, particularly in their more northern regions (Canada, Russia, the United States [Alaska], and Greenland). The primary energy source for both heat and power in remote communities is almost exclusively diesel. Geothermal energy is currently used in all eight Arctic countries, providing heat and sometimes electricity at utility scales and at the microgrid scale. However, the availability of geothermal resources is poorly defined in Arctic countries. We reframe geothermal heat and power as integrated energy systems, asking the question: are integrated geothermal energy systems - where available and economic - resilient solutions for communities in Arctic countries? Resilience attributes of integrated geothermal energy systems are identified, with a focus on microgrids and small-scale applications.

arctic energy↗

DOE OSTI2023

The Innovation of I-Loop

The closing and decommissioning of Halden Boiling Water Reactor in Norway resulted in the loss of many nuclear irradiation testing facilities, notably those providing boiling water reactor (BWR) environments. To lighten the loss of such an important asset, the Advanced Test Reactor (ATR) is being called upon. The recent overhaul of the ATR’s core and the installation of the new Top Head Closure Plate now makes it possible to utilize the ATR’s I-loop locations for I-Loop Tube test facilities. Similar to the current in-pile tube facilities, these new I-Loop facilities will capitalize on the available space and neutron flux the ATR generates in this region of the core for fuels and materials testing. Current efforts are underway to add new PWR and BWR I-Loop Tube facilities to the I-Loop positions for these purposes.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Feasibility of Power Ramp Testing in the Advanced Test Reactor

For decades, the Halden Boiling Water Reactor (HBWR) in Norway was an international resource for assessing nuclear fuels and materials behavior and its unexpected shutdown in 2018 represented a significant loss in experimental capability for prototypical irradiation testing. In the aftermath of the closure, a study was performed to assess capability gaps related to the Accident Tolerant Fuels (ATF) program. It was concluded that the primary capability gaps left by the closure of the HBWR were the loss of prototypic in-pile Light Water Reactor (LWR) loops that provide operational transient testing and in-pile Loss-of-Coolant Accident (LOCA) testing capabilities. The study also concluded that the Advanced Test Reactor (ATR) and Transient Reactor Test Facility (TREAT) likely have the necessary key capabilities to absorb the breadth of the HBWR mission gaps related to the ATF program, but additional investments in experimental infrastructure were needed. One such investment is the design and installation of additional pressurized water loops in the medium-I positions of the ATR, hereafter referred to as I-Loops, to support power ramp testing and testing in Boiling Water Reactor (BWR) conditions. This paper gives an overview of the planned ATR I-Loops and assesses the feasibility of performing power ramp testing inside such a loop.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2025

Influence of Phase-Change Materials and Operating Periods on Load Shifting for Thermal Storage Heat Pumps in European Climate Zones

As the reliance on heat pumps (HPs) for space conditioning increases worldwide, ex-tensive grid strains during utility peak hours are expected. Significant research efforts focus on investigating the use of integrated thermal energy storage (TES) systems to reduce peak energy demands. Conventionally, TES systems are often integrated to store and provide either cooling or heating, but not both. In this work, a single room-temperature phase-change material (PCM)-TES was integrated for dual-mode opera-tion with an R290 air-to-water 10.5 kW (3-Ton) HP. Two PCM melting temperatures (17°C, 22°C) were assessed to investigate their impact on system performance and cost reductions for Milan, Italy (4A); Barcelona, Spain (3A); and Oslo, Norway (6A). HP and HP-TES performance maps were generated using Modelica-based transient models and co-simulated with a prototype residential building using the Spawn of En-ergyPlusTM with simple rule-based controls. Our simulations indicate that PCM-17°C provided annual cost savings at higher peak-to-off-peak cost ratios, as the demand re-duction dominated the savings potential. The recharge energy costs and requirements became more dominant at lower cost ratios, making PCM-22°C more beneficial at lower cost ratios. Finally, despite Oslo's heating-dominated climate, the utility peak hours favor cooling demand reductions, making PCM-17°C more appealing. In all cases, the cost savings potential stabilized between 4 – 10% regardless of cost ratio, suggesting that system-level component and operation control optimization is required to maximize cost savings further.

25 ENERGY STORAGE↗