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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Ground calibration plan for the Athena/X-IFU microcalorimeter spectrometer

The X-ray Integral Field Unit is the X-ray imaging spectrometer on board one of ESA’s next large missions, Athena. Athena is set to investigate the theme of the Hot and Energetic Universe, with a launch planned in the late-2030s. Based on a high-sensitivity transition edge sensor (TES) detector array operated at very low temperature (50 mK), X-IFU will provide spatially resolved high-resolution spectroscopy of the X-ray sky in the 0.2 to 12 keV energy band, with an energy resolution goal of 4 eV up to 7 keV [3 eV design goal]. This work presents the current calibration plan of the X-IFU. It provides the requirements applicable to the X-IFU calibration, describes the overall calibration strategy, and details the procedure and sources needed for the ground calibration of each parameter or characteristics of the X-IFU.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Delving into the depths of NGC 3783 with XRISM II. Cross-calibration of X-ray instruments used in the large, multi-mission observational campaign

Context. Accurate X-ray spectroscopic measurements are fundamental for deriving basic physical parameters of the most abundant baryon components in the Universe. The plethora of X-ray observatories currently operational enables a panchromatic view of the high-energy emission of celestial sources. However, uncertainties in the energy-dependent calibration of the instrument transfer functions (e.g. the effective area, energy redistribution, or gain) can limit - and historically, did limit - the accuracy of X-ray spectroscopic measurements. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign. Aims. We revised the status of the cross-calibration among the scientific payload on board four operation missions: Chandra, NuSTAR, XMM-Newton, and the recently launched XRISM. XRISM carries the micro-calorimeter Resolve, which yields the best energy resolution at energies ≥2 keV. For this purpose, we used the data from a 10-day-long observational campaign targeting the nearby active galactic nucleus NGC 3783, carried out in July 2024. Methods. We present a novel model-independent method for assessing the cross-calibration status that is based on a multi-node spline of the spectra with the highest-resolving power (XRISM/Resolve in our campaign). We also estimated the impact of the intrinsic variability of NGC 3783 on the cross-calibration status due to the different time coverages of participating observatories and performed an empirical reassessment of the Resolve throughput at low energies. Results. Based on this analysis, we derived a set of energy-dependent correction factors of the observed responses, enabling a statistically robust analysis of the whole spectral dataset. They will be employed in subsequent papers describing the astrophysical results of the campaign.

Active Galactic Nuclei, individual: NGC 3783↗
DOE OSTI2024

Predictive Indicators of the Performance of Large Language Models

In several mission contexts, it is desirable to estimate the performance of large language models (LLMs) on tasks that we cannot run directly. In light of published “scaling laws” our hypothesis is that some tasks should be consistently more challenging than others based on characteristics of the task. The goal of this project was to begin quantifying how much information about LLM performance can be gained from the features of a model and a task. Two of our statistical models struggled to converge. Pass/fail test results may provide limited information for inference beyond model quality and task difficulty, but we see no evidence at this time for significant feature interaction effect sizes, arguing for simple models. Future work extending the models to capitalize on perplexity of ground truth answers is suggested. This project also introduces “Depth of Knowledge Variant Testing” as a strategy for more finely assessing language models on open domain question and answer tasks. We developed sets of questions that ask a language model to produce similar information while demonstrating increasing depth of knowledge, and also relabeled existing Q&A test questions with their depth of knowledge. Our results suggest further consideration of Bloom’s taxonomy and further refinement of prompts to properly elicit information at varying depths. In the course of this work, we set up a basic infrastructure for standardizing tasks and testing many language models on these tasks. In addition to testing the predictive quality of model features and performance across test suites, with this project we have introduced two new task features to contextualize each test question: the Dewey Classification main category of information covered, and the Bloom’s taxonomy level that corresponds to the depth of knowledge probed by the question. Splits across these and other features produced over five hundred task subtypes with distinct feature vectors, which we tested on half a dozen models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning

Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model consisting of a variety of machine learning (ML) methods. For salinity data, we use satellite measurements of pre-storm sea surface salinity (SSS) as a proxy for the salinity stratification. We train and test the model on various ocean basins, including the Atlantic, eastern North Pacific and western North Pacific. A calibrator is trained on top of the ML models to correct and enhance probability forecasts. The calibrator significantly improves probability forecasts relative to recent works. The ML model performance is improved with the addition of SSS in the Eastern North Pacific, western North Pacific, and the Caribbean subregion of the North Atlantic, and the overall model performance is better than previous studies. SSS decreases model skill for a model trained on the full Atlantic basin. In the Indian Ocean, SSS is also notably correlated with RI occurrence, but the TC samples are not sufficient to train ML models.

hurricane↗
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↗
DOE OSTI2026

Studies of whistler propagation along a plasma density gradient that is parallel to the magnetic field

Low frequency plasma wave generation in space is important for both scientific and practical applications. One of the most promising techniques for doing this is to directly inject whistler waves into the space environment from an antenna onboard one or more satellites. This technique has been discussed for years, but there are still open questions about the best way to generate plasma waves. So far, most theoretical [Kondrat92], lab based [Pribyl2010, Stenzel2016] and space-based experiments [DSX] have focused on studying the generation of whistler waves from an electric dipole antenna. However, a dipole antenna is very inefficient because it puts a lot of energy in waves that are not effective for most applications. Theoretical [Kondrat92] and lab experimental [Stenzel2016] results indicate that a loop antenna is much more efficient at generating whistler waves than a dipole antenna. A satellite experiment will need to be developed to demonstrate that whistler waves can be generated from a loop antenna in the space environment. The challenge is that to efficiently transmit whistler modes in the natural plasma environment of space, the loop antenna will have to be very large. For example, at L=2 (one earth radius away from the surface of the earth) a loop antenna would need a radius on the order of ~200 m to radiate efficiently, as shown in fig. 1, left. The antenna size and complexity would require a prohibitively large and expensive satellite mission. Our proposed innovation is to exploit the fact that the characteristic wavelength of whistler waves decreases in more dense plasma, which reduces the size needed for an antenna to radiate efficiently. Fortunately, a technique already exists for enhancing the local plasma density in space, called a plasma contactor [Kovaleski2001]. A plasma contactor can be used to create a local environment where the plasma density is enhanced around the satellite, which in turn reduces the size of an antenna that is needed to radiate efficiently (Fig. 1, right).

42 ENGINEERING↗
DOE OSTI2025

Multi-Resolution UAV Path Replanning for Inspection of Tailings Dams

Autonomous inspection of large and complex structures with a commercial unmanned aerial vehicle (UAV) is a challenging problem that has been addressed in recent years. In this paper, we address the global motion planning problem of creating autonomous inspection missions for UAVs considering photogrammetry constraints. We focus on the inspection of large tailings dams, which are dam structures used to store waste byproducts of mining. Our method uses a prior sparse point cloud of the dam to generate a voxel grid, where paths satisfying photogrammetry constraints are tested for collisions. We then apply the A* algorithm as a local planner to avoid obstacles within the global mission. Moreover, we address the problem of changing routes online by using octree-based multi-resolution grids for efficient and fast pathfinding. Our results, obtained using tridimensional maps of an actual coal mine tailings dam, show that using octrees for multi-resolution motion planning is faster than using a fixed voxel grid in online missions while inspecting large structures.

42 ENGINEERING↗
DOE OSTI2024

The Evolution of Galaxies and Clusters at High Spatial Resolution with Advanced X-ray Imaging Satellite (AXIS)

Stellar and black hole feedback heat and disperse surrounding cold gas clouds, launching gas flows off circumnuclear and galactic disks, producing a dynamic interstellar medium. On large scales bordering the cosmic web, feedback drives enriched gas out of galaxies and groups, seeding the intergalactic medium with heavy elements. In this way, feedback shapes galaxy evolution by shutting down star formation and ultimately curtailing the growth of structure after the peak at redshift 2–3. To understand the complex interplay between gravity and feedback, we must resolve both the key physics within galaxies and map the impact of these processes over large scales, out into the cosmic web. The Advanced X-ray Imaging Satellite (AXIS) is a proposed X-ray probe mission for the 2030s with arcsecond spatial resolution, large effective area, and low background. AXIS will untangle the interactions of winds, radiation, jets, and supernovae with the surrounding interstellar medium across the wide range of mass scales and large volumes driving galaxy evolution and trace the establishment of feedback back to the main event at cosmic noon. This white paper is part of a series commissioned for the AXIS Probe mission concept; additional AXIS white papers can be found at the AXIS website.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Comprehensive framework for assessing and optimizing existing research networks

Conservation, monitoring, and research networks, or collections of ecological research sites unified under a common mission of data collection or a research mission, are essential infrastructure for understanding large landscapes. However, most networks developed opportunistically over decades rather than through systematic design, creating potential limitations in the ability to address conservation challenges across entire regions. We developed a framework to evaluate how well an existing research network represents the environmental conditions its members study and devised an approach to rank sites of priority for strategic expansion. Our approach measures performance through environmental representativeness, geographic coverage, and adequacy for scientific inference and thus optimizes limited monitoring resources to maximize scientific impact. We demonstrated this approach with the U.S. Department of Agriculture (USDA) Forest Service Experimental Forests and Ranges Network (EFRN), a 79‐site network across the United States that grew opportunistically over a century. At the national scale, the network effectively captured high‐biomass forests important for carbon cycle research; 82% of forest biomass was in well‐represented areas. Some areas in Texas, Florida, the Rocky Mountains, and the West Coast had no relevant EFRN sites, which limits the ability to make regional inferences. A fundamental challenge for the EFRN was that sites improving regional extent coverage sometimes provided minimal national benefits, which can create conflicts between local and global priorities. Adding the highest‐ranked candidate site provided a relevant site for 17% of currently poorly represented 1‐km pixel cells nationally, but regional and national site rankings varied considerably due to nested spatial inference. This framework provides quantitative tools for strategic infrastructure decision‐making, ensures that limited monitoring resources maximize conservation impact, and can be applied broadly to address the widespread challenge of optimizing conservation and monitoring networks worldwide.

additional site↗
DOE OSTI2025

Elucidating the Dynamics of Electroweak Symmetry Breaking through Study of High-Multiplicity Boson Final States at the LHC

To understand the full story of the electroweak symmetry breaking (EWSB) and how the universe arrived at today’s universe, the structure of the Higgs potential needs to be probed. We must carefully select and study processes at the LHC that are sensitive to the Higgs potential. In this context, longitudinal vector boson scattering (VBS) processes, V L V L →V L V L , and di-Higgs production, including V L V L →HH at the LHC have been studied for any potential deviation from SM prediction. However, many classes of models beyond the Standard Model (BSM) may result in the 2→2 process being perfectly well-behaved and SM-like but show interesting deviations in 2→3, 2→4, or 2→n(3) processes. If we are to complete the mission objectives the P5 laid out, then a large swath of 2→n(3) must be thoroughly searched and checked. The research supported by this award used data collected at the Compact Muon Solenoid (CMS) detector at the Large Hadron Collider (LHC) to explore VBS produced VVH process in the semi-merged channel. In addition, in the electroweak sector, there are open questions in the multi-gauge boson couplings and the Higgs couplings to the gauge bosons. The research supported by the award also studied the triboson production WWZ process at the LHC, which is a crossed diagram of a VBS process. During the funded period of 9 months, the analysis designs have been finalized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Strengthening U.S. National Security Through Advanced Energy Innovation

NREL's work in strategic energy security is focused on keeping the United States secure and its citizens safe by applying expertise in advanced energy systems and technologies to prevent energy system disruptions from any source, natural or human. NREL pursues national security objectives by providing partners an accurate understanding of national and international security implications of global energy trends; novel installation, facility, and operational energy solutions; access to NREL R&D capabilities to incorporate advanced energy technologies and biomaterials into mission requirements; and the ability to test future technologies using large-scale grid modeling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

NuSTAR Bounds on Radiatively Decaying Particles from M82

Axions and other putative feebly interacting particles with a mass of tens to several hundreds of keVs can be produced in stellar cores with a Lorentz boost factor E a / m a ≲ 10 . Thus, starburst galaxies such as M82 are efficient factories of slow axions. Their decay a → γ γ would produce a large flux of x-ray photons, peaking around 100 keV and spread around the Galaxy by an angle that can be relatively large. We use observations of the Nuclear Spectroscopic Telescope Array mission to show that the absence of these features can constrain 30–500 keV axion masses into uncharted regions for axion-photon coupling of g a γ ∼ 10 − 10 – 10 − 12 GeV − 1 . Our argument can be applied to other heavy feebly interacting particles and astrophysical sources that are hot enough to produce them, yet cold enough to avoid large boost factors which slow down the decay. Published by the American Physical Society 2025

Candón, Francisco R. (ORCID:0009000231999278)↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Brochure for the DOE Office of Science Workshop on Envisioning Frontiers in AI and Computing for Biological Research

In February of 2025 a joint ASCR/BER workshop was held to identify key transformational research directions for understanding biology using artificial intelligence (AI), digital twins and high-performance (HPC) computational methods to facilitate scientific discovery and innovation in support of the Department of Energy mission. AI technologies offer exciting new groundbreaking methods to analyze large volumes of complex biological data, thereby greatly accelerating the ability to understand, predict, and design biological processes for beneficial purposes. In the laboratory, the bridging of AI-enabled automated experimental technologies, HPC and digital twins will provide potent tools for researchers to explore the fundamental nature of biology and harness its inherent metabolic potential for a variety of beneficial purposes. The focus of this workshop was on how high-performance computational methods can impact this objective by exploring digital twins, foundational models, and data-driven approaches with applications to advance automated laboratory experiments, modeling of complex living systems and engineering new functions into plants and microbial systems relevant to DOE mission. Workshop attendees with expertise in plant science, microbiology, mathematics, computer science, and AI assessed the current state of the science, trends, and AI challenges at the interface of plant and microbial systems biology and computational science to identify opportunities for high-impact research. This collaborative effort capitalized on ASCR's advancements in applied mathematics, computer science, and Exascale systems, and BER's expertise in basic genomics-enabled research on DOE relevant plant and microbial systems. The workshop culminated in four key priority research directions to guide future research and development within DOE Office of Science programs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Blueprint for DOE Quantum Supercomputing: Ensuring U.S. Leadership in the Quantum Decade

Quantum computing stands at the threshold of a transformative decade, where the field will evolve from small-scale demonstrations toward practical scientific computing at scale. This Blueprint identifies fault-tolerant quantum computers (FTQCs) as a viable, scalable, and broadly applicable path to achieving “quantum scientific utility,” defined as solving scientifically valuable problems beyond the reach of conventional, classical computers. This capability is expected to show scientific demonstrations in the late 2020s and to mature in the early-to-mid 2030s. This Blueprint outlines a strategy to prepare the U.S. Department of Energy (DOE) for FTQCs and their integration into the U.S. national scientific computing infrastructure. Its purpose is to identify the steps, milestones, and research directions necessary for DOE to enable initial deployment of FTQCs in 2028 as a scientific tool for the nation and mature this capability into the 2030s. DOE has a long history of supporting quantum information science and technology, contributing significantly to research advancements, training a quantum-ready workforce, and providing access to early small-scale quantum hardware. Given recent demonstrations of logical operations on error-corrected logical qubits and the advancement of commercial hardware roadmaps, DOE should begin preparations for large-scale, fault-tolerant quantum computing deployment for DOE science missions. This Blueprint proposes that DOE focus on (1) deploying first-generation scientifically relevant quantum computers with at least 100 logical qubits and performing at least 10,000 to 100,000 hard logical operations in scientifically relevant calculations; (2) developing essential FTQC programming competencies, system software, and facility readiness; and (3) investing in cutting edge focused R&D that fosters breakthroughs in scientific applications, algorithms, and logical architectures needed to accelerate the advent of scientific utility. This effort will position DOE to transition to larger systems: production-scale quantum computers that comprise 1,000 to 10,000 logical qubits, perform 1 to 10 billion hard logical operations, and execute scientifically useful computations at scale. Achieving these goals will require DOE facilities to evolve with urgency to support scientific campaigns that integrate quantum and classical computing resources into efficient workflows, novel software and firmware environments for compiling and routing quantum programs on FTQC machines, and suitable infrastructure for quantum hardware. It will also require further development and optimization of scientific applications from the fields of materials science, quantum chemistry, and high-energy and nuclear physics. The Blueprint calls for transformative R&D and collective action to accelerate the advent of scientific quantum utility and bring it within reach by 2028.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Ultra Wide Bandgap Laser Addressable Photoconductors

Wide Band Gap (WBG) and Ultra Wide Band Gap (UWBG) photoconductors have the potential to meet several critical mission needs for LLNL and the broader USG due to their exceptional characteristics related to large critical electric field. In particular, high energy laser systems such as the National Ignition Facility would benefit from the development of new materials for active optical devices such as the Optically Addressable Light Valve (OALV) used in the Programmable Spatial Shaper System. Missions in Global Security would benefit from higher performance Photoconductive Semiconductor Switches for pulsed power and radiofrequency amplifiers. This project examined the suitability of both commercially available and custom synthesized semi insulating WBG and UWBG materials for several of these applications. We developed high laser damage threshold OALVs for optical systems based on several of these materials as well as new RF, pulsed power, and power electronics devices based on the same. These devices show superior power handling in terms of laser damage threshold, electric field, and power output. A number of the technologies developed have been transitioned to both internal and external customers.

42 ENGINEERING↗
DOE OSTI2024

Space radiation measurements during the Artemis I lunar mission

Space radiation is a notable hazard for long-duration human spaceflight. Associated risks include cancer, cataracts, degenerative diseases and tissue reactions from large, acute exposures. Space radiation originates from diverse sources, including galactic cosmic rays, trapped-particle (Van Allen) belts5 and solar-particle events. Previous radiation data are from the International Space Station and the Space Shuttle in low-Earth orbit protected by heavy shielding and Earth’s magnetic field and lightly shielded interplanetary robotic probes such as Mars Science Laboratory and Lunar Reconnaissance Orbiter. Limited data from the Apollo missions and ground measurements with substantial caveats are also available. Here we report radiation measurements from the heavily shielded Orion spacecraft on the uncrewed Artemis I lunar mission. At differing shielding locations inside the vehicle, a fourfold difference in dose rates was observed during proton-belt passes that are similar to large, reference solar-particle events. Interplanetary cosmic-ray dose equivalent rates in Orion were as much as 60% lower than previous observations. Furthermore, a change in orientation of the spacecraft during the proton-belt transit resulted in a reduction of radiation dose rates of around 50%. These measurements validate the Orion for future crewed exploration and inform future human spaceflight mission design.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Hydrogen Transportation and Distributed Energy Systems Risk Assessment for Airport Facilities (CRADA 555) (Final Report)

Portland International Airport (PDX), Oregon, operated by the Port of Portland (Port) is exploring the possibility of operating a fleet of 28 fuel cell electric buses and developing a distributed energy system to support airport operations during various operating modes including large-scale power outages. This study investigates the compatibility of these two missions, which will be key to resilience management at PDX. This study also investigated the risks associated with deploying a hydrogen system that could support bus operations and be utilized during an emergency to ensure continued operation of the airport. This will be a key innovation for the deployment of hydrogen systems at airports. Utilizing the unique benefits of hydrogen infrastructure for multiple roles will aid adopters in justifying new projects and serve to demonstrate the versatility of hydrogen as an energy-carrier to a wider market.

08 HYDROGEN↗