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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Seasonal grassland productivity forecast for the U.S. Great Plains using Grass–Cast

Every spring, ranchers in the drought-prone U.S. Great Plains face the same difficult challenge —trying to estimate how much forage will be available for livestock to graze during the upcoming summer grazing season. To reduce this uncertainty in predicting forage availability, we developed an innovative new grassland productivity forecast system, named Grass-Cast, to provide science-informed estimates of growing season above ground net primary production (ANPP). Grass-Cast uses over 30 yr of historical data including weather and the satellite-derived normalized vegetation difference index (NDVI)—combined with ecosystem modeling and seasonal precipitation forecasts—to predict if rangelands in individual counties are likely to produce below-normal, near-normal, or above-normal amounts of grass biomass (lbs/ac). Grass-Cast also provides a view of rangeland productivity in the broader region, to assist in larger scale decision-making—such as where forage resources for grazing might be more plentiful if a rancher’s own region is at risk of drought. Grass-Cast is updated approximately every two weeks from April through July. Each Grass-Cast forecast provides three scenarios of ANPP for the upcoming growing season based on different precipitation outlooks. Near real-time 8-d NDVI can be used to supplement Grass-Cast in predicting cumulative growing season NDVI and ANPP starting in mid-April for the Southern Great Plains and mid-May to early June for the Central and Northern Great Plains. Here, we present the scientific basis and methods for Grass-Cast along with the county-level production forecasts from 2017 and 2018 for ten states in the U.S. Great Plains. The correlation between early growing season forecasts and the end-of growing season ANPP estimate is >50% by late May or early June. In a retrospective evaluation, we compared Grass-Cast end-of-growing season ANPP results to an independent dataset and found that the two agreed 69% of the time over a 20-yr period. Although some predictive tools exist for forecasting upcoming growing season conditions, none predict actual productivity for the entire Great Plains. The Grass-Cast system could be adapted to predict grassland ANPP outside of the Great Plains or to predict perennial biofuel grass production.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Geographically Dependent Sustainability Indicators for Comparison of Conventional Vegetable Production to Controlled-Environment Agriculture

Many food system lifecycle analyses distill agricultural production and supply chain impacts into single-value sustainability metrics for various food categories. These studies provide an overview of the food supply system that highlight striking results such as the GHG impacts of meat production. The supply chain impacts of vegetable production occupy the middle ground; higher than average food loss and waste, lower than average overall energy use, etc. However, aggregated results obscure the sustainability implications of the location of food production, especially for vegetables. Moreover, the increasing instability of food production systems are not captured, as illustrated by a recent Washington Post article. According to a UC Merced study conducted for the state, California farmers left nearly 400,000 acres of agricultural land unplanted last year because of a lack of water. The result, the study found, was a direct economic cost to farmers of $1.1 billion and the loss of nearly 9,000 agricultural jobs. (The Washington Post, March 21, 2022.) Previous work quantified the food-energy-water nexus implications of transitioning vegetable production from large, centralized agricultural operations to smaller distributed production in controlled-environment farms (CEA). The importance of location-specific data is especially evident for water use. Water impacts of the food system are primarily local to the region where food is produced, water impacts vary significantly between locations, and water stress is a major concern in locations that currently host large agricultural operations. Location-specific data is needed to accurately assess the water impacts of transitioning to CEA. The location of farms in relation to consumers impacts transportation energy use, food loss and waste, and requirements for food processing (e.g., to reduce weight, preserve foods for long storage, and package foods to reduce damage and loss) Reducing transport is particularly relevant for agricultural products that could be grown in CEAs (fruits, vegetables, protein). Access to nutritious food is not evenly distributed in the population. Remote communities, communities in harsh environments, and economically-disadvantaged communities often have poor access to healthy foods. CEA is ideally suited to these environments. However, the energy and water use of CEA, while in many respects lower overall than conventional supply chains, are concentrated within communities and could have significant local impacts. This paper reports on development of sustainability metrics that seek to capture the tradeoffs between the current supply chain and a CEA supply chain for vegetables; focusing on the location-dependent implications of water use, the transition from largely fossil fuel based energy use to electricity, and the food access, resilience and wellbeing implications of urban versus rural food production.

controlled-environment agriculture↗
DOE OSTI2025

Characterization and thermometry of dissipatively stabilized steady states

In this work we study the properties of dissipatively stabilized steady states of noisy quantum algorithms, exploring the extent to which they can be well approximated as thermal distributions, and proposing methods to extract the effective temperature T. We study an algorithm called the relaxational quantum eigensolver (RQE), which is one of a family of algorithms that attempt to find ground states and balance error in noisy quantum devices. In RQE, we weakly couple a second register of auxiliary ‘shadow’ qubits to the primary system in Trotterized evolution, thus engineering an approximate zero-temperature bath by periodically resetting the auxiliary qubits during the algorithm’s runtime. Balancing the infinite temperature bath of random gate error, RQE returns states with an average energy equal to a constant fraction of the ground state. We probe the steady states of this algorithm for a range of base error rates, using several methods for estimating both T and deviations from thermal behavior. In particular, we both confirm that the steady states of these systems are often well-approximated by thermal distributions, and show that the same resources used for cooling can be adopted for thermometry, yielding a fairly reliable measure of the temperature. These methods could be readily implemented in near-term quantum hardware, and for stabilizing and probing Hamiltonians where simulating approximate thermal states is hard for classical computers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Spin fluctuations in the 112-type iron-based superconductor Ca 0.82 La 0.18 Fe 0.96 Ni 0.04 As 2

Abstract We report time-of-flight inelastic neutron scattering (INS) investigations on the spin fluctuation spectrum in the 112-type iron-based superconductor (FeSC) Ca 0.82 La 0.18 Fe 0.96 Ni 0.04 As 2 (CaLa-112). In comparison to the 122-type FeSCs with a centrosymmetric tetragonal lattice structure (space group I 4 / m m m ) at room temperature and an in-plane stripe-type antiferromagnetic (AF) order at low temperature, the 112 system has a noncentrosymmetric structure (space group P 2 1 ) with additional zigzag arsenic chains between Ca/La layers and a magnetic ground state with similar wavevector Q A F but different orientations of ordered moments in the parent compounds. Our INS study clearly reveals that the in-plane dispersions and the bandwidth of spin excitations in the superconducting CaLa-112 closely resemble to those in 122 systems. While the total fluctuating moments ⟨ m 2 ⟩ ≈ 4.6 ± 0.2 μ B 2 /Fe are larger than 122 system, the dynamic correlation lengths are similar ( ξ ≈ 10 Å). These results suggest that superconductivity in iron arsenides may have a common magnetic origin under similar magnetic exchange couplings with a dual nature from local moments and itinerant electrons, despite their different magnetic patterns and lattice symmetries.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Exact Ground State of Interacting Electrons in Magic Angle Graphene

One of the most remarkable theoretical findings in magic angle twisted bilayer graphene (TBG) is the emergence of ferromagnetic Slater determinants as exact ground states for the interacting Hamiltonian at the chiral limit. This discovery provides an explanation for the correlated insulating phase which has been experimentally observed at half filling. This work is the first mathematical study of interacting models in magic angle graphene systems. These include not only TBG but also TBG-like systems featuring four flat bands per valley, and twisted trilayer graphene systems with equal twist angles. We identify symmetries of the chiral limit of the Bistritzer-MacDonald Hamiltonian that are responsible for characterizing the Hartree-Fock ground states as zero energy many-body ground states. Furthermore, for a general class of Hamiltonian, we establish criteria that the ferromagnetic Slater determinants are the unique ground states within the class of uniformly half-filled, translation invariant Slater determinants. We then demonstrate that these criteria can be explicitly verified for TBG and TBG-like systems at the chiral limit, using properties of Jacobi-θ$${\theta }$$ and Weierstrass-℘$${\wp }$$ functions.

Becker, Simon↗
DOE OSTI2020

Quantum approximate optimization of the long-range Ising model with a trapped-ion quantum simulator

Quantum computers and simulators may offer significant advantages over their classical counterparts, providing insights into quantum many-body systems and possibly improving performance for solving exponentially hard problems, such as optimization and satisfiability. Here, we report the implementation of a low-depth Quantum Approximate Optimization Algorithm (QAOA) using an analog quantum simulator. We estimate the ground-state energy of the Transverse Field Ising Model with long-range interactions with tunable range, and we optimize the corresponding combinatorial classical problem by sampling the QAOA output with high-fidelity, single-shot, individual qubit measurements. We execute the algorithm with both an exhaustive search and closed-loop optimization of the variational parameters, approximating the ground-state energy with up to 40 trapped-ion qubits. We benchmark the experiment with bootstrapping heuristic methods scaling polynomially with the system size. We observe, in agreement with numerics, that the QAOA performance does not degrade significantly as we scale up the system size and that the runtime is approximately independent from the number of qubits. We finally give a comprehensive analysis of the errors occurring in our system, a crucial step in the path forward toward the application of the QAOA to more general problem instances.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Unsupervised discovery of extreme weather events using universal representations of emergent organization

Spontaneous self-organization is ubiquitous in systems far from thermodynamic equilibrium. While organized structures that emerge dominate transport properties, universal representations that identify and describe these key objects remain elusive. Here, we introduce a theoretically grounded framework for describing emergent organization that, via data-driven algorithms, is constructive in practice. Its building blocks are spacetime lightcones that embody how information propagates across a system through local interactions. We show that predictive equivalence classes of lightcones—local causal states—capture organized behaviors in complex spatiotemporal systems. Employing an unsupervised physics-informed machine learning algorithm and a high-performance computing implementation, we demonstrate automatically discovering organized structures in two real-world domain science problems. We show that local causal states identify vortices and track their power-law decay behavior in two-dimensional fluid turbulence. We then show how to detect and track familiar extreme weather events—hurricanes and atmospheric rivers—and discover other novel structures associated with precipitation extremes in high-resolution climate data at the grid-cell level.

Rupe, Adam [Pacific Northwest National Laboratory ↗
DOE OSTI2020

A Multi-Sensor Unoccupied Aerial System Improves Characterization of Vegetation Composition and Canopy Properties in the Arctic Tundra

Changes in vegetation distribution, structure, and function can modify the canopy properties of terrestrial ecosystems, with potential consequences for regional and global climate feedbacks. In the Arctic, climate is warming twice as fast as compared to the global average (known as ‘Arctic amplification’), likely having stronger impacts on arctic tundra vegetation. In order to quantify these changes and assess their impacts on ecosystem structure and function, methods are needed to accurately characterize the canopy properties of tundra vegetation types. However, commonly used ground-based measurements are limited in spatial and temporal coverage, and differentiating low-lying tundra plant species is challenging with coarse-resolution satellite remote sensing. The collection and processing of multi-sensor data from unoccupied aerial systems (UASs) has the potential to fill the gap between ground-based and satellite observations. To address the critical need for such data in the Arctic, we developed a cost-effective multi-sensor UAS (the ‘Osprey’) using off-the-shelf instrumentation. The Osprey simultaneously produces high-resolution optical, thermal, and structural images, as well as collecting point-based hyperspectral measurements, over vegetation canopies. In this paper, we describe the setup and deployment of the Osprey system in the Arctic to a tundra study site located in the Seward Peninsula, Alaska. We present a case study demonstrating the processing and application of Osprey data products for characterizing the key biophysical properties of tundra vegetation canopies. In this study, plant functional types (PFTs) representative of arctic tundra ecosystems were mapped with an overall accuracy of 87.4%. The Osprey image products identified significant differences in canopy-scale greenness, canopy height, and surface temperature among PFTs, with deciduous low to tall shrubs having the lowest canopy temperatures while non-vascular lichens had the warmest. The analysis of our hyperspectral data showed that variation in the fractional cover of deciduous low to tall shrubs was effectively characterized by Osprey reflectance measurements across the range of visible to near-infrared wavelengths. Therefore, the development and deployment of the Osprey UAS, as a state-of-the-art methodology, has the potential to be widely used for characterizing tundra vegetation composition and canopy properties to improve our understanding of ecosystem dynamics in the Arctic, and to address scale issues between ground-based and airborne/satellite observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High energy yield bifacial spectrum-splitting photovoltaic system

In this paper a photovoltaic system is proposed that achieves high energy yield by integrating bifacial silicon cells into a spectrum-splitting module. Spectrum splitting is accomplished using volume holographic optical elements to spectrally divide sunlight onto an array of photovoltaic cells with different bandgap energies. Light that is reflected from the ground surface onto the rear side of the module is converted by the bifacial silicon cells. The energy yield of the system is optimized by tuning the volume holographic element parameters, such as film thickness, index modulation, and construction point source positions. An example is presented for utility-scale illumination parameters in Tucson, Arizona, that attains an energy yield of 1010 k w ⋅ <#comment/> h r y r ⋅ <#comment/> m 2 , which is 32.8% of the incident solar insolation.

Chrysler, Benjamin D. (ORCID:0000000186250147)↗
DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗
DOE OSTI2020

Cluster Difference Imaging Photometric Survey. II. TOI 837: A Young Validated Planet in IC 2602

We report the discovery of TOI 837b and its validation as a transiting planet. We characterize the system using data from the NASA Transiting Exoplanet Survey Satellite mission, the ESA Gaia mission, ground-based photometry from El Sauce and ASTEP400, and spectroscopy from CHIRON, FEROS, and Veloce. We find that TOI 837 is a T = 9.9 mag G0/F9 dwarf in the southern open cluster IC 2602. The star and planet are therefore 35$_{-5}^{+11}$ million years old. Combining the transit photometry with a prior on the stellar parameters derived from the cluster color–magnitude diagram, we find that the planet has an orbital period of 8.3 days and is slightly smaller than Jupiter (R p =0.77$_{-0.07}^{+0.09}$ R Jup ). From radial velocity monitoring, we limit M p sin i to less than 1.20 M Jup (3σ). The transits either graze or nearly graze the stellar limb. Grazing transits are a cause for concern, as they are often indicative of astrophysical false-positive scenarios. Our follow-up data show that such scenarios are unlikely. Our combined multicolor photometry, high-resolution imaging, and radial velocities rule out hierarchical eclipsing binary scenarios. Background eclipsing binary scenarios, though limited by speckle imaging, remain a 0.2% possibility. TOI 837b is therefore a validated adolescent exoplanet. The planetary nature of the system can be confirmed or refuted through observations of the stellar obliquity and the planetary mass. Such observations may also improve our understanding of how the physical and orbital properties of exoplanets change in time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hourly Load Profile Dataset for Electric Airport Ground Support Equipment in the United States

Currently, there are limited data on the magnitude and timing of electricity demand from electric ground support equipment (eGSE) across U.S. airports. To address this gap, this study presents a modeling approach for estimating hourly annual electricity demand from eGSE at the 50 largest U.S. commercial airports. These datasets, accessible at data.nrel.gov/submissions/279, provide critical insights into the potential grid impacts and electricity demand associated with eGSE adoption.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Observing low-altitude features in ozone concentrations in a shoreline environment via uncrewed aerial systems

Abstract. Ozone is a pollutant formed in the atmosphere by photochemical processes involving nitrogen oxides (NOx) and volatile organic compounds (VOCs) when exposed to sunlight. Tropospheric boundary layer ozone is regularly measured at ground stations and sampled infrequently through balloon, lidar, and crewed aircraft platforms, which have demonstrated characteristic patterns with altitude. Here, to better resolve vertical profiles of ozone within the atmospheric boundary layer, we developed and evaluated an uncrewed aircraft system (UAS) platform for measuring ozone and meteorological parameters of temperature, pressure, and humidity. To evaluate this approach, a UAS was flown with a portable ozone monitor and a meteorological temperature and humidity sensor to compare to tall tower measurements in northern Wisconsin. In June 2020, as a part of the WiscoDISCO20 campaign, a DJI M600 hexacopter UAS was flown with the same sensors to measure Lake Michigan shoreline ozone concentrations. This latter UAS experiment revealed a low-altitude structure in ozone concentrations in a shoreline environment showing the highest ozone at altitudes from 20–100 m a.g.l. These first such measurements of low-altitude ozone via a UAS in the Great Lakes region revealed a very shallow layer of ozone-rich air lying above the surface.

Meteorology & Atmospheric Sciences↗
DOE OSTI2020

Phonons, Q-dependent Kondo spin fluctuations, and 4f phonon resonance in YbAl 3

4f intermediate valence (IV) compounds are canonical hosts of correlated electron physics and can contribute to our understanding of the larger class of correlated electron materials. In this work, we study the prototype IV compound YbAl 3 which exhibits a nonintegral valence with a moderately heavy fermion ground state and a large Kondo temperature (T K ~500–600K). To better characterize the correlated physics of YbAl 3 , we have measured the phonon and the magnetic excitation spectra on single crystals of this material by time-of-flight inelastic neutron scattering and inelastic x-ray scattering. We have also performed theoretical calculations of the phonon spectra. We present three findings of these measurements. First, we observe that the measured phonon spectra can be described adequately by a calculation based on standard DFT+U density functional theory. The calculated energies, however, are 10% too low compared to the measured energies. This discrepancy may reflect a hardening of the phonons due to dynamic 4f correlations. Second, the low-temperature spin fluctuations on the Kondo energy scale k B T K have a momentum (Q) dependence similar to that seen recently in the IV compound CePd 3 . For that system, the Q dependence has been attributed to particle-hole excitations in a coherent itinerant 4f correlated ground state. We suggest a similar origin for the momentum dependence seen in YbAl 3 . This Q dependence disappears as the temperature is raised towards room temperature and the 4f electron band states become increasingly incoherent. Such a coherent/incoherent crossover is expected to be generic for correlated electron systems. Third, a low-temperature magnetic peak observed in the neutron scattering near 30 meV shows dispersion identical to a particular optic-phonon branch. This 4f/phonon resonance disappears for T≥150K. The phonon spectrum appears to be unaffected by the resonance. We discuss several possibilities for the origin of this unusual excitation, which may be unique to YbAl 3 . We suggest that the excitation may arise from the large amplitude beating of the light Al atoms against the heavy Yb atoms, resulting in a dynamic 4f/3p hybridization.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)

As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.

03 NATURAL GAS↗
DOE OSTI2021

Assessing the Consistency of Estimated Ground Cover Fractions between the BLM AIM Method and Optical Remote Sensing Method

Since 2012, Argonne National Laboratory (Argonne) has supported the Bureau of Land Management (BLM) in developing remote sensing methodologies for long-term environmental monitoring of Palo Verde Mesa in eastern Riverside County, California, including methods for: detailed mapping of ephemeral streams, estimating fractional cover of desert-land surface components (e.g., trees, shrubs, litters, and bare ground), evaluating erosion risk or land stability, and characterizing vegetation alliances using spatial structure and geostatistical approaches. These studies showed the promise of remote sensing for monitoring changes in desert landscapes by providing information that would be difficult to obtain through field surveys. During this time the BLM has also worked to establish long-term monitoring protocols and compiled field-observation data collected using standardized protocols from the Assessment, Inventory, and Monitoring (AIM) strategy. The AIM data can be compared to data derived from remote sensing methods to evaluate their relative operational utility in monitoring landscape change. If ground cover estimated using remotely sensed imagery is comparable to AIM ground cover estimates, then remote sensing can be used to monitor whether any land cover change in desert landscapes may be related to solar energy development. Therefore, the goal of this study was to determine the consistency in ground cover estimates between AIM data and those derived from publicly- available remotely sensed imagery, such as that available through the U.S. Department of Agriculture, National Agricultural Imagery Program (NAIP), to examine feasibility of a remote sensing method for complementing AIM monitoring. Based on the image analysis in this study, we also provide recommendations for how small unmanned aerial system (sUAS) data may be used to complement BLM’s AIM data and NAIP imagery for future vegetation monitoring. The ground cover types we originally planned to investigate were trees, shrubs, and bare ground. However, the small sample size and a limited range of cover fraction of trees and shrubs in the AIM dataset (e.g., 33 samples with a maximum shrub cover of 18%, 14 samples with a maximum tree cover of 17%) did not allow for performing a meaningful evaluation for the remote sensing approach. Therefore, we conducted the study focusing on bare ground, foliar, and rock cover, all of which are indicators reported in the AIM remote sensing dataset.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Multiscale maps of Active Layer Depth for Teller site Mile Marker 27 and Kougarok Mile Marker 80, Seward Peninsula, AK

Remote sensing maps of active layer depth derived from Unmanned Areal System (UAS) data. The UAS datasets were stepwise scaled until matching the AVIRIS-NG (Airborne Visible / Infrared Imaging Spectrometer - Next Generation) and Sentinel-2 spatial resolutions. Using the field observed Active Layer Depth (ALD) measurement in combination with spectral and topographic predictors derivatives from DJI UAS imagery, we used a spatially explicit RF regression model to predict and map ALD across our study landscapes. This package includes maps for Next-Generation Ecosystem Experiment Arctic (NGEE Arctic)’s Teller Mile Marker (MM) 27, and Kougarok MM80 (aka Mile 80) watersheds. The field, map data, and metadata are provided as geoTIF and text (*.csv) formats. These datasets are provided in support of Hantson et al., 2024 (accepted) “Scaling Arctic landscape and permafrost features improves active layer depth modeling”

54 ENVIRONMENTAL SCIENCES↗