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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Shifting agricultural practices to produce sustainable, low carbon intensity feedstocks for biofuel production

The carbon intensity (CI) of biofuel's well-to-pump life cycle is calculated by life cycle analysis (LCA) to account for the energy/material inputs of the feedstock production and fuel conversion stages and the associated greenhouse gas (GHG) emissions during these stages. The LCA is used by the California Air Resources Board's Low Carbon Fuel Standard (LCFS) program to calculate CI and monetary credits are issued based on the difference between a given fuel's CI and a reference fuel's CI. Through the Tier 2 certification program under which individual fuel production facilities can submit their own CIs with their facility input data, the LCFS has driven innovative technologies to biofuel conversion facilities, resulting in substantial reductions in GHG emissions as compared to the baseline gasoline or diesel. A similar approach can be taken to allow feedstock petition in the LCFS so that lower-CI feedstock can be rewarded. Here we examined the potential for various agronomic practices to improve the GHG profiles of corn ethanol by performing feedstock-level CI analysis for the Midwestern United States. Our system boundary covers GHG emissions from the cradle-to-farm-gate activities (i.e. farm input manufacturing and feedstock production), along with the potential impacts of soil organic carbon change during feedstock production. We conducted scenario-based CI analysis of ethanol, coupled with regionalized inventory data, for various farming practices to manage corn fields, and identified key parameters affecting cradle-to-farm-gate GHG emissions. The results demonstrate large spatial variations in CI of ethanol due to farm input use and land management practices. In particular, adopting conservation tillage, reducing nitrogen fertilizer use, and implementing cover crops has the potential to reduce GHG emissions per unit corn produced when compared to a baseline scenario of corn–soybean rotation. This work shows a large potential emission offset opportunity by allowing feedstock producers a path to Tier 2 petitions that reward low-CI feedstocks and further reduce biofuels' CI. The prevalence of significant acreage that has not been optimized for CI suggests that policy changes that incentivize optimization of this parameter could provide significant additionality over current trends in farm efficiency and adoption of conservation practice.

09 BIOMASS FUELS↗
DOE OSTI2024

Protocols for x-ray transient grating pump/optical probe experiments at x-ray free electron lasers

Abstract Transient grating spectroscopy is a specialized application of the four-wave-mixing methodology and constitutes a versatile technique for investigating the dynamics of vibrational, magnetic and electronic degrees of freedom of matter in a background-free fashion. Recent developments in free-electron laser sources have enabled the extension of this technique into the extreme ultraviolet range. Ongoing efforts to expand transient grating spectroscopy into the x-ray regime promise numerous advantages: (1) substantial penetration depths that allow for probing bulk material properties, (2) element specificity via specific core-excited states, and (3) short wavelengths that allow for excitation gratings with higher momentum transfer and improved spatial resolution. In this study, we comprehensively outline the procedures for conducting x-ray transient grating pump/optical probe experiment. The process encompasses the design and alignment of the experimental setup, as well as the subsequent steps involved in data acquisition and analysis. This paper is intended as a comprehensive guide for researchers interested in implementing x-ray transient grating spectroscopy, providing valuable insights into the intricacies of the experimental workflow required for this novel technique. Furthermore, we discuss the potential for extending this methodology to an x-ray pump/x-ray probe scheme, envisioning a future direction that holds promise for enhancing the capabilities and scope of x-ray transient grating spectroscopy, opening new opportunities for studying ultrafast processes with unprecedented temporal and spatial resolutions.

Optics↗
DOE OSTI2023

Short-lead seasonal precipitation forecast in northeastern Brazil using an ensemble of artificial neural networks

This study assesses the deterministic and probabilistic forecasting skill of a 1-month-lead ensemble of Artificial Neural Networks (EANN) based on low-frequency climate oscillation indices. The predictand is the February-April (FMA) rainfall in the Brazilian state of Ceará, which is a prominent subject in climate forecasting studies due to its high seasonal predictability. Additionally, the study proposes combining the EANN with dynamical models into a hybrid multi-model ensemble (MME). The forecast verification is carried out through a leave-one-out cross-validation based on 40 years of data. The EANN forecasting skill is compared with traditional statistical models and the dynamical models that compose Ceará’s operational seasonal forecasting system. A spatial comparison showed that the EANN was among the models with the smallest Root Mean Squared Error (RMSE) and Ranked Probability Score (RPS) in most regions. Moreover, the analysis of the area-aggregated reliability showed that the EANN is better calibrated than the individual dynamical models and has better resolution than Multinomial Logistic Regression for above-normal (AN) and below-normal (BN) categories. It is also shown that combining the EANN and dynamical models into a hybrid MME reduces the overconfidence of the extreme categories observed in a dynamically-based MME, improving the reliability of the forecasting system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Event Horizon Telescope imaging of the archetypal blazar 3C 279 at an extreme 20 microarcsecond resolution

3C 279 is an archetypal blazar with a prominent radio jet that show broadband flux density variability across the entire electromagnetic spectrum. We use an ultra-high angular resolution technique – global Very Long Baseline Interferometry (VLBI) at 1.3 mm (230 GHz) – to resolve the innermost jet of 3C 279 in order to study its fine-scale morphology close to the jet base where highly variable γ-ray emission is thought to originate, according to various models. The source was observed during four days in April 2017 with the Event Horizon Telescope at 230 GHz, including the phased Atacama Large Millimeter/submillimeter Array (ALMA), at an angular resolution of ∼20 μas (at a redshift of z = 0.536 this corresponds to ∼0.13 pc ∼ 1700 Schwarzschild radii with a black hole mass MBH = 8 × 108 M⊙). Imaging and model-fitting techniques were applied to the data to parameterize the fine-scale source structure and its variation. We find a multicomponent inner jet morphology with the northernmost component elongated perpendicular to the direction of the jet, as imaged at longer wavelengths. The elongated nuclear structure is consistent on all four observing days and across different imaging methods and model-fitting techniques, and therefore appears robust. Owing to its compactness and brightness, we associate the northern nuclear structure as the VLBI “core”. This morphology can be interpreted as either a broad resolved jet base or a spatially bent jet. We also find significant day-to-day variations in the closure phases, which appear most pronounced on the triangles with the longest baselines. Our analysis shows that this variation is related to a systematic change of the source structure. Two inner jet components move non-radially at apparent speeds of ∼15 c and ∼20 c (∼1.3 and ∼1.7 μas day−1, respectively), which more strongly supports the scenario of traveling shocks or instabilities in a bent, possibly rotating jet. The observed apparent speeds are also coincident with the 3C 279 large-scale jet kinematics observed at longer (cm) wavelengths, suggesting no significant jet acceleration between the 1.3 mm core and the outer jet. The intrinsic brightness temperature of the jet components are ≲1010 K, a magnitude or more lower than typical values seen at ≥7 mm wavelengths. The low brightness temperature and morphological complexity suggest that the core region of 3C 279 becomes optically thin at short (mm) wavelengths.Key words: galaxies: active / galaxies: jets / galaxies: individual: 3C 279 / techniques: interferometric⋆ The data are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/640/A69 and at https://eventhorizontelescope.org/for-astronomers/data⋆⋆ Deceased.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Particle emission with identification from an atmospheric pressure plasma liquid interface

A conspicuous emission phenomenon of luminous particles from the liquid anode surface of an atmospheric pressure DC glow discharge is reported. The emission has been shown to occur when the plasma forms a pattern on the surface of the liquid electrolyte. Here, the spatial-temporal evolutions of the trajectories of emitted particles were studied using a high-speed imaging system. Particles were sampled in flight using a witness plate for analysis. Critical particle characteristics were examined using electron microscope technologies. The morphology of the resulting splats and compositions suggest that they are molten droplets with a great deal of structure, including evidence of nanoprecipitation. A theoretical model was employed to estimate the particle size from the measured splats, which provides a radius range within a hundred micrometers. This experiment leads to the postulation of a mechanism in which particle emission at the plasma liquid interface is likely driven by the Taylor cone effect.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Quasisteady evolution of fast neutrino-flavor conversions

In astrophysical environments such as core-collapse supernovae (CCSNe) and binary neutron star mergers (BNSMs), neutrinos potentially experience substantial flavor mixing due to the refractive effects of neutrino self-interactions. Determining the survival probability of neutrinos in asymptotic states is paramount to incorporating flavor conversions’ effects in the theoretical modeling of CCSN and BNSM. Some phenomenological schemes have shown good performance in approximating asymptotic states of fast neutrino-flavor conversions (FFCs), known as one of the collective neutrino oscillation modes induced by neutrino self-interactions. However, a recent study showed that they would yield qualitatively different asymptotic states of FFC if the neutrino number is forced to evolve. It is not yet fully understood why the canonical phenomenological models fail to predict asymptotic states. In this paper, we perform detailed investigations through numerical simulations and then provide an intuitive explanation with a quasihomogeneous analysis. Based on the analysis, we propose a new phenomenological model, in which the quasisteady evolution of FFCs is analytically determined. The model also allows us to express the convolution term of spatial wave number as a concise form, which corresponds to useful information on analyses for the nonlinear feedback from small-scale flavor conversions to large-scale ones. Furthermore, our model yields excellent agreement with numerical simulations, which lends support to our interpretation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

H 2 O absorption spectroscopy via focused laser differential interferometry

A modification of focused laser differential interferometry (FLDI) is demonstrated with an infrared tunable diode laser (TDL) to achieve simultaneous absorption spectroscopy (AS) measurements. Measurements from this absorbing-FLDI (A-FLDI) are shown for a Hencken burner plume. Initial comparison measurements are recorded using TDLAS and an electrical hygrometer. Raw voltage and estimated absorbance measurements illustrate that the technique detects five distinct absorbance peaks of the methane–air flame while retaining the expected behavior of typical FLDI. This modification furthers efforts to enable FLDI to conduct analysis of the pressures, temperatures, and molecular densities of flows. It also explores the potential for reducing path-integration (PI) effects in absorption spectroscopy and potentially enabling spatially and temporally resolved local flow measurements. Reductions in PI length as high as 82%–84% are observed.

Holladay, Seth (ORCID:0009000650875421)↗
DOE OSTI2021

Industry Level Integrated Fire Modeling Using Fire Risk Investigation in 3D (FRI3D)

The software Fire Risk Investigation in 3D (FRI3D) has been developed over the last 2 years to integrate 3D spatial modeling with existing fire probabilistic risk assessment (PRA) models and fire simulation codes. The goal of this research and development is to automate many of the fire analysis manual tasks to reduce industry efforts in the initial fire modeling and operational costs for the model maintenance and evaluations required during normal plant operations. The tasks for Fiscal Year (FY) 2021 include first testing the FRI3D modeling capabilities by importing an industry fire model into FRI3D and making a 3D model of a complex/high-risk significant area. (For this work, the switchgear room was chosen.) Then, the second task of FY 2021 is to develop a dynamic fire PRA process that can help optimize traditional fire PRA models. The switchgear room model will be used for the dynamic fire PRA work. This report describes the work and insights learned when using FRI3D software to model both a Nuclear Regulatory Report (NUREG) example models and a full industry switchgear room.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed: Modeling Archive

This Modeling Archive is in support of a NGEE-Arctic publication: Shirley et al. (2022) “Near-Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub-Arctic Watershed". [DOI].The dataset contains outputs from the global sensitivity analysis (GSA) of the “ecosys” model as reported in Shirley et al. (2022). The study showed that discontinuous permafrost environments are characterized by complex feedback loops and strong spatial heterogeneity which is created by variability in near-surface hydrology and soil properties. Additionally, the study demonstrated that missing representation of sub-grid heterogeneity in terrestrial ecosystem models can lead to biased estimates of the high-latitude carbon budget. Included in this dataset are the factor values for each run in the GSA and the model outputs used in this study. Included are two *.csv data files and one *.pdf.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Simulating Catalysis with Realistic Pellet Geometries Using Mesoflow: A Case Study of Catalytic Propane Dehydrogenation

We present a case study of catalytic propane dehydrogenation with our open-source multiphysics solver, Mesoflow. The solver was developed to simulate reactive flow coupled to heterogeneous catalytic reactions and deactivation in the context of complex, mesoscale geometry. The method leverages cartesian block-structured adaptive mesh refinement to capture realistic catalyst microstructural features acquired directly from X-ray computed tomography data. A kinetic model for propane dehydrogenation and catalyst deactivation was developed based on temporal analysis of products (TAP) reactor experiments. The TAP reactor experiments allow for precise characterization of intrinsic kinetic reaction steps which are implemented into Mesoflow simulations to model the spatial and temporal evolution of reactants, products, and catalyst active sites. The short-term and long-term deactivation behavior is studied by using XCT data collected from fresh and aged catalyst pellets, which exhibit different microstructural features. This study employs time-splitting algorithms to connect disparate reaction and flow timescales, enabling the simulations to achieve realistic deactivation timescales on the order of minutes while the flow time-scales for small particles (100 microns) are several milliseconds. We also introduce a flexible automated python script that writes the necessary files to construct a Mesoflow simulation from user-created chemical mechanisms. We will also introduce a few new features that are added to Mesoflow such as higher order schemes, implicit chemistry integrators and the ability to run on AMD and NVIDIA graphics-processing-units.

AMReX↗
DOE OSTI2020

Observational Study of the Thermodynamics and Morphological Characteristics of a Midlatitude Continental Cold Pool Event

Abstract Convectively generated cold pools are important to the Earth system as they exert strong controls on deep convective-storm initiation, intensity, and life cycle. Despite their importance, efforts to introduce such cold pool controls into weather and climate models lack guidance and/or physical constraints from cold pool observations. This work presents a detailed, purely observational analysis of a cold pool event that took place on 23–24 May 2011 in north-central Oklahoma. The characteristics of the cold pool, and the spatiotemporal evolution of the hydrometeors and dynamics in the proximity of the cold pool, are studied with high-resolution observations. The unprecedented dataset used in this work to study cold pool characteristics includes an enhanced network of surface weather stations, a high-temporal-frequency sounding array, and the NEXRAD and Atmospheric Radiation Measurement (ARM) Southern Great Plains radar networks. The potential use of NEXRAD surveillance scans to estimate height and propagation speed of the leading edge of the cold pool (LECP) is presented in this work. Manual identification and tracking of the LECP from NEXRAD imagery shows a spatial and temporal heterogeneity of the LECP properties. Surprisingly, over its detected life cycle, the LECP speed remains almost constant, even though the strength of the cold pool diminishes in time and its height varies. Radar analysis shows that pulses of graupel and hail within downdrafts in the convective system generating the cold pool appeared to be related to temporary increases in the LECP height.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Multimorphic Materials: Spatially Tailoring Mechanical Properties via Selective Initiation of Interpenetrating Polymer Networks

Access to multimaterial polymers with spatially localized properties and robust interfaces is anticipated to enable new capabilities in soft robotics, such as smooth actuation for advanced medical and manufacturing technologies. Here, orthogonal initiation is used to create interpenetrating polymer networks (IPNs) with spatial control over morphology and mechanical properties. Base catalyzes the formation of a stiff and strong polyurethane, while blue LEDs initiate the formation of a soft and elastic polyacrylate. IPN morphology is controlled by when the LED is turned “on”, with large phase separation occurring for short time delays (≈1–2 min) and a mixed morphology for longer time delays (>5 min), which is supported by dynamic mechanical analysis, small angle X-ray scattering, and atomic force microscopy. Through tailoring morphology, tensile moduli and fracture toughness can be tuned across ≈1–2 orders of magnitude. Furthermore, a simple spring model is used to explain the observed mechanical behavior. Photopatterning produces “multimorphic” materials, where morphology is spatially localized with fine precision (<100 µm), while maintaining a uniform chemical composition throughout to mitigate interfacial failure. As a final demonstration, the fabrication of hinges represents a possible use case for multimorphic materials in soft robotics.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Advancing Elemental and Isotopic Analysis of Uranium Mineral Inclusions: Rapid Screening via Laser-Induced Breakdown Spectroscopy and High-Resolution Laser Ablation-ICP-MS Mapping

The work presented herein employs two laser-based analytical techniques (laser-induced breakdown spectroscopy (LIBS) and laser ablation – inductively coupled plasma – mass spectrometry (LA-ICP-MS)) to spatially determine the elemental and isotopic composition of uranium bearing minerals. Uniquely, this work leverages the high-speed applicability of LIBS to “screen” the sample(s) for their elemental constituents. After determining the location of the uranium inclusions (via LIBS), high-resolution LA-ICP-MS was employed to further characterize the inclusions. The high-resolution (sub-µm) capabilities of LA-ICP-MS were able to extract important information from the uranium minerals including discerning its chemical form (e.g., finchite from carnotite, Sr- and K-bearing uranyl vanadates, respectively) as well as their 235 U/ 238 U isotopic composition. This approach, LIBS followed by LA-ICP-MS, significantly reduces the analysis time (~95 %) in comparison to employing a LA-ICP-MS only approach. Furthermore, this work presented a novel approach to analyzing inclusions via a particle/inclusion analysis tool which is commercially available within the iolite 4 software. This tool allowed for a more accurate characterization of the isotopic distribution of the inclusions, as well as allowing for rapid sizing of the inclusions. Finally, this analytical approach could readily be applied to other sample types in which the target species (e.g., µm-sized inclusions) are embedded in complex matrices (e.g., cm-sized samples).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Analysis of Polarized Dust Emission Using Data from the First Flight of SPIDER

Using data from the first flight of Spider and from the Planck High Frequency Instrument, we probe the properties of polarized emission from interstellar dust in the Spider observing region. Component-separation algorithms operating in both the spatial and harmonic domains are applied to probe their consistency and to quantify modeling errors associated with their assumptions. Analyses of diffuse Galactic dust emission spanning the full Spider region demonstrate (i) a spectral energy distribution that is broadly consistent with a modified-blackbody (MBB) model with a spectral index of β d = 1.45 ± 0.05 (1.47 ± 0.06) for E (B)-mode polarization, slightly lower than that reported by Planck for the full sky; (ii) an angular power spectrum broadly consistent with a power law; and (iii) no significant detection of line-of-sight polarization decorrelation. Tests of several modeling uncertainties find only a modest impact (~10% in σ r ) on Spider's sensitivity to the cosmological tensor-to-scalar ratio. The size of the Spider region further allows for a statistically meaningful analysis of the variation in foreground properties within it. Assuming a fixed dust temperature T d = 19.6 K, an analysis of two independent subregions of that field results in inferred values of β d = 1.52 ± 0.06 and β d = 1.09 ± 0.09, which are inconsistent at the 3.9σ level. Furthermore, a joint analysis of Spider and Planck 217 and 353 GHz data within one subregion is inconsistent with a simple MBB at more than 3σ, assuming a common morphology of polarized dust emission over the full range of frequencies. This evidence of variation may inform the component-separation approaches of future cosmic microwave background polarization experiments.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Intentional Uranium Tagging for Material Provenance and Pathway Forensics (LA19-Intentional-Forensics-NDD3Bb) (Annual Report for FY21)

This report describes the outcomes of the third and final year of a project to research the feasibility of tagging uranium materials, especially nuclear fuels. The experimental focus remained on metallic uranium forms under prospective surface and bulk tagging scenarios. Overall, the results showed that the tags could be successfully imparted and characterized in both as-built and degraded conditions. This was in line with expectations coming into this project, indicating promise for both surface and bulk tagging of metallic forms of uranium. Multiple surface tagging techniques and detection strategies were explored in FY21, with an emphasis on improving tag quality, readability, and detection in the field. Non-radioactive materials were used as a testbed. Selective deposition via laser beam was determined to be successful in imparting a readable titanium deposit on a stainless steel base plate, and can be read with high resolution characterization techniques (e.g., scanning electron microscopy) and field capable tools (e.g., eddy current testing). Other deposition techniques, such as selective deposition via electron beam and photoluminescent tags, were explored in FY21, and while success for these techniques would be dependent on additional work, these techniques showed potential for surface tagging applications. To survey bulk taggant elements for bulk uranium metal, 16 tagging elements were spread among 18 depleted uranium castings (4 baseline, 3 mix, 1 dilution, and 10 recycle). Most of these were made and characterized in FY21. Taggant acceptability was based upon manufacturability, detectability, and persistence from the standpoint of two detection options: bulk chemical analysis (for “chemical taggants”) and microstructural analysis (for “second phase taggants”). Taggant detection in both up-front manufacturing and in the face of “degradations” such as dilution, mixing, and recycling was generally good. Two independent laboratories carried out chemical analysis on most of the castings, and often at several locations within a casting, and the results are discussed. Scanning electron microscopy+EDS microanalysis revealed the second phases mostly contained the expected tagging elements. The shapes and 2 spatial distributions of these micron-sized carbides, oxides, and intermetallic particles offers opportunities for further science-based investigation and tagging optimization. Overall, V and Co currently appear as the best choices for chemical taggants while Al, Ti, Mn, Co, Pd, and Tb all look good as second phase taggants. The other elements considered here – Sc, Ni, Ge, Nb, Ce, Ta, W, Ir, and Au – while not being ruled out, require more study to become viable options. It is of special note that in the recycling study only one of the 12 elements fell out of detection even after 10 meltings, demonstrating their persistence. An Appendix tabulates all chemical analysis results to enable more quantitative and statistical studies of detection opportunities and limitations, as a part of a related project.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗
DOE OSTI2025

Tracking seasonal variability in plant traits from spaceborne PRISMA and NEON AOP across forest types and ecoregions

Plant traits serve as critical indicators of how plants adapt to environmental changes and influence ecosystem functions. While airborne hyperspectral remote sensing effectively maps plant traits through detailed reflectance properties, it is limited by cost and scale, making large-scale and temporal studies challenging. The recently launched spaceborne hyperspectral imager, PRecursore IperSpettrale della Missione Applicativa (PRISMA), offers frequent, large scale and high-fidelity observations on a spatial resolution of 30 m and a revisit time of around 29 days, making it suitable for large-scale seasonal trait mapping. However, their potential remains largely unexplored. This study developed a multi-stage framework by leveraging the PRISMA spaceborne hyperspectral data and National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) hyperspectral data to investigate the seasonal dynamics of four key plant traits — chlorophyll content, carotenoid content, equivalent water thickness, and nitrogen content — across eleven NEON sites representing diverse forest types and ecoregions in the contiguous U.S. Our results demonstrated that PRISMA hyperspectral data can reliably track seasonal variability in plant traits, achieving overall R 2 values ranging from 0.78 to 0.88 and normalized root mean square error (NRMSE) values ranging from 5.4% to 8.4% for the four traits. Seasonal patterns revealed bell-shaped trajectories for chlorophyll and carotenoids, while equivalent water thickness decreased steadily across most sites, driven by structural changes during leaf maturation and senescence. Nitrogen content exhibited less pronounced seasonal variation but followed expected nutrient resorption patterns. Analysis of environmental drivers showed that seasonal variability is primarily controlled by solar radiation and day length in northern sites, vapor pressure in semi-arid regions, and temperature in mid-southeastern sites. Spatial variability, meanwhile, was primarily driven by soil properties, particularly during the peak growing season. However, the influence of soil variables slightly declines toward the end of the season at several sites, as climatic factors become more prominent. This study highlights the capability of PRISMA, and potentially other similar spaceborne hyperspectral data for large-scale, time-series plant trait mapping and provides valuable insights into the interactions between plant traits and environmental factors. In conclusion, these findings contribute to advancing our understanding of plant functional ecology and improving predictions of ecosystem responses to environmental changes.

Environmental drivers↗