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At least 577 records · Page 32

Assessment of Human Factors

Human Factors Engineering, often referred to as Ergonomics, is a science that applies a detailed understanding of human characteristics, capabilities, and limitations to the design, evaluation, and operation of environments, tools, and systems for work and daily living. Human Factors is the investigation, design, and evaluation of equipment, techniques, procedures, facilities, and human interfaces, and encompasses all aspects of human activity from manual labor to mental processing and leisure time enjoyments. In spaceflight applications, human factors engineering seeks to: (1) ensure that a task can be accomplished, (2) maintain productivity during spaceflight, and (3) ensure the habitability of the pressurized living areas. DSO 904 served as a vehicle for the verification and elucidation of human factors principles and tools in the microgravity environment. Over six flights, twelve topics were investigated. This study documented the strengths and limitations of human operators in a complex, multifaceted, and unique environment. By focusing on the man-machine interface in space flight activities, it was determined which designs allow astronauts to be optimally productive during valuable and costly space flights. Among the most promising areas of inquiry were procedures, tools, habitat, environmental conditions, tasking, work load, flexibility, and individual control over work.

Mount, Frances↗

Ensuring US National Aeronautics Test Capabilities

U.S. leadership in aeronautics depends on ready access to technologically advanced, efficient, and affordable aeronautics test capabilities. These systems include major wind tunnels and propulsion test facilities and flight test capabilities. The federal government owns the majority of the major aeronautics test capabilities in the United States, primarily through the National Aeronautics and Space Administration (NASA) and the Department of Defense (DoD). However, changes in the Aerospace landscape, primarily the decrease in demand for testing over the last 20 years required an overarching strategy for management of these national assets. Therefore, NASA established the Aeronautics Test Program (ATP) as a two-pronged strategic initiative to: (1) retain and invest in NASA aeronautics test capabilities considered strategically important to the agency and the nation, and (2) establish a strong, high level partnership with the DoD. Test facility utilization is a critical factor for ATP because it relies on user occupancy fees to recover a substantial part of the operations costs for its facilities. Decreasing utilization is an indicator of excess capacity and in some cases low-risk redundancy (i.e., several facilities with basically the same capability and overall low utilization). However, low utilization does not necessarily translate to lack of strategic importance. Some facilities with relatively low utilization are nonetheless vitally important because of the unique nature of the capability and the foreseeable aeronautics testing needs. Unfortunately, since its inception, the customer base for ATP has continued to shrink. Utilization of ATP wind tunnels has declined by more than 50% from the FY 2006 levels. This significant decrease in customer usage is attributable to several factors, including the overall decline in new programs and projects in the aerospace sector; the impact of computational fluid dynamics (CFD) on the design, development, and research process; and the reductions in wind tunnel testing requirements within the largest consumer of ATP wind tunnel test time, the Aeronautics Research Mission Directorate (ARMD). Retirement of the Space Shuttle Program and recent perturbations of NASA's Constellation Program will exacerbate this downward trend. Therefore it is crucial that ATP periodically revisit and determine which of its test capabilities are strategically important, which qualify as low-risk redundancies that could be put in an inactive status or closed, and address the challenges associated with both sustainment and improvements to the test capabilities that must remain active. This presentation will provide an overview of the ATP vision, mission, and goals as well as the challenges and opportunities the program is facing both today and in the future. We will discuss the strategy ATP is taking over the next five years to address the National aeronautics test capability challenges and what the program will do to capitalize on its opportunities to ensure a ready, robust and relevant portfolio of National aeronautics test capabilities.

Marshall, Timothy J.↗

Concept Design of High Power Solar Electric Propulsion Vehicles for Human Exploration

Human exploration beyond low Earth orbit will require enabling capabilities that are efficient, affordable and reliable. Solar electric propulsion (SEP) has been proposed by NASA s Human Exploration Framework Team as one option to achieve human exploration missions beyond Earth orbit because of its favorable mass efficiency compared to traditional chemical propulsion systems. This paper describes the unique challenges associated with developing a large-scale high-power (300-kWe class) SEP vehicle and design concepts that have potential to meet those challenges. An assessment of factors at the subsystem level that must be considered in developing an SEP vehicle for future exploration missions is presented. Overall concepts, design tradeoffs and pathways to achieve development readiness are discussed.

Hoffman, David J.↗

Modeling Meteoroid Densities for Spacecraft Risk Assessment

This report describes the methodologies and algorithms that NASA’s Meteoroid Environment Office (MEO) currently utilizes to measure meteoroid densities. We discuss the needs for an accurate model for the meteoroid density distribution in its Meteoroid Engineering Model (MEM), and its potential implications for spacecraft design. The recently developed process is heavily derived from that of previous work, although subtle differences exist. A thorough comparison of the best-fit densities derived for sixty meteoroids in and with the process described here shows that discrepancies in final densities larger than a factor of two are measured for ∼ 20% of our test events. Such a level of discrepancy suggests that any density calculated using similar methods cannot be assumed to represent a unique fit to the data. Additional observational data for meteoroids beyond those utilized in this work will be essential for producing more reliable and repeatable density measurements.

Ehlert, Steven↗

TPSAS-NF1676L-16988-DND

There has been renewed interest to uniformly recalibrate historical geostationary (GEO) data records to aid in climate monitoring. GEO sensors have annual repeatable angular sampling over a given location. The view angle is fixed and the imaging schedule is usually constant through its lifetime. Given the fact that colocated GEOs are always share the same sub-satellite point and maintain their imaging schedules provides repeatable angular sampling over decades. One of the biggest challenges in transferring a reference sensor calibration using invariant desert targets to another sensor is the accuracy of the bidirectional reflectance distribution function (BDRF). A well-calibrated GEO can be used to predict the daily exoatmospheric radiance model (DERM) over a desert target for a given GMT that is valid for any GEO sensor at the same location. The advantage of this method is that a BRDF is not needed. Another challenge of invariant target calibration is the unique spectra signature of the desert. However, since most GEOs are built in batches, the spectral response functions (SRF) are very similar for most historical GEOs, the spectral band adjustment factor (SBAF) between GEO sensors is much smaller than for MODIS and GEO sensors. Since the water vapor burden over the desert is seasonal, both the TOA and desert surface can be considered invariant for a given day of the year. The reference GEO can be inter-calibrated with MODIS or VIIRS, which have onboard visible calibration using solar diffusers, using other methods, such as ray-matching or deep convective clouds. Also the next generation GEOs will have onboard visible calibration, which will increase the accuracy of this method. Three Meteosats over the Libyan desert will be used to illustrate the DERM method. The reference Meteosat will be inter-calibrated against Aqua-MODIS. The reference GEO DERM will be constructed and used to calibrate the remaining Meteosats. The DERM calibration will be validated by comparing the calibration using Aqua-MODIS ray-matching. Similarly, two GOES sensors using the Sonoran desert will also be highlighted. An uncertainty analysis will also be performed with emphasis on the SBAF, derived over the desert targets using both SCIAMACHY and Hyperion hyper-spectral radiances.

David Doelling↗

Search for CPT and Lorentz invariance violation in the muon $g -2$ experiment at Fermilab

The Muon g-2 experiment at Fermilab (E989) aims to measure the anomalous magnetic moment of the muon, $a_{\mu}= (g-2)/2$, to a groundbreaking precision of $140$ ppb, obtaining a near four-fold increase in precision over the previous experiment, E821, at the Brookhaven National Laboratory (BNL). The value of $a_{\mu}$ from BNL currently differs from the Standard Model prediction by $\sim 3.7$ standard deviations, suggesting the potential for new physics and therefore, motivating a new experiment.Because the theory predicts this number with high precision, testing the g-factor through experiment provides a stringent test of the SM and can suggest physics beyond the Standard Model. The goal of the Fermilab Muon $g-2$ experiment is to increase the statistical precision by more than a factor of 20 and reduce systematic errors by a factor of 3. By measuring muon precession rate ($\omega_a$) in an external magnetic field, the anomalous magnetic moment will be calculated. This is an incredibly challenging experiment with a unique opportunity to provide new insight into nature. \\ The $g-2$ data also provides a great opportunity for setting the most stringent limits on some of the Standard Model Extension CPT Lorentz violating (LV) parameters in the muon sector. One of the CPT and Lorentz violating signatures that we can look for using $g-2$ data is a sidereal variation of $\omega_a(t)$. Extensive simulation studies confirm that the sensitivity regarding the sidereal varation roughly scales with $\omega_a$ uncertainty. Hence, the $g-2$ experiment at FNAL should be able to reach limits of $\sim 5\times10^{-25}$ GeV. Because the CPT and LV analyses are essentially studies of variations in $\omega_a$ as a function of time and charge, performing an $\omega_a$ analysis sets the stage for the CPT and LV measurement. This dissertation focuses on the methodology of a fully functioning framework and analyzing the Fermilab Muon $g - 2$ Run 2 data containing $\sim 11$ billion events above an energy threshold of $1.7$~GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Fibronectin is a survival factor for differentiated osteoblasts

The skeletal extracellular matrix produced by osteoblasts contains the glycoprotein fibronectin, which regulates the adhesion, differentiation and function of various adherent cells. Interactions with fibronectin are required for osteoblast differentiation in vitro, since fibronectin antagonists added to cultures of immature fetal calvarial osteoblasts inhibit their progressive differentiation. To determine if fibronectin plays a unique role in fully differentiated osteoblasts, cultures that had already formed mineralized nodules in vitro were treated with fibronectin antagonists. Fibronectin antibodies caused >95% of the cells in the mature cultures to display characteristic features of apoptosis (nuclear condensation, apoptotic body formation, DNA laddering) within 24 hours. Cells appeared to acquire sensitivity to fibronectin antibody-induced apoptosis as a consequence of differentiation, since antibodies failed to kill immature cells and the first cells killed were those associated with mature nodules. Intact plasma fibronectin, as well as fragments corresponding to the amino-terminal, cell-binding, and carboxy-terminal domains of fibronectin, independently induced apoptosis of mature (day-13), but not immature (day-4), osteoblasts. Finally, transforming growth factor-beta1 partially protected cells from the apoptotic effects of fibronectin antagonists. Thus, in the course of maturation cultured osteoblasts switch from depending on fibronectin for differentiation to depending on fibronectin for survival. These data suggest that fibronectin, together with transforming growth factor-beta1, may affect bone formation, in part by regulating the survival of osteoblasts.

NASA Center ARC↗

Wings: A New Paradigm in Human-Centered Design

Many aircraft accidents/incidents investigations cite crew error as a causal factor (Boeing Commercial Airplane Group 1996). Human factors experts suggest that crew error has many underlying causes and should be the start of an accident investigation and not the end. One of those causes, the flight deck design, is correctable. If a flight deck design does not accommodate the human's unique abilities and deficits, crew error may simply be the manifestation of this mismatch. Pilots repeatedly report that they are "behind the aircraft" , i.e., they do not know what the automated aircraft is doing or how the aircraft is doing it until after the fact. Billings (1991) promotes the concept of "human-centered automation"; calling on designers to allocate appropriate control and information to the human. However, there is much ambiguity regarding what it mean's to be human-centered. What often are labeled as "human-centered designs" are actually designs where a human factors expert has been involved in the design process or designs where tests have shown that humans can operate them. While such designs may be excellent, they do not represent designs that are systematically produced according to some set of prescribed methods and procedures. This paper describes a design concept, called Wings, that offers a clearer definition for human-centered design. This new design concept is radically different from current design processes in that the design begins with the human and uses the human body as a metaphor for designing the aircraft. This is not because the human is the most important part of the aircraft (certainly the aircraft would be useless without lift and thrust), but because he is the least understood, the least programmable, and one of the more critical elements. The Wings design concept has three properties: a reversal in the design process, from aerodynamics-, structures-, and propulsion-centered to truly human-centered; a design metaphor that guides function allocation and control and display design; and a deliberate distinction between two fundamental functions of design, to complement and to interpret human performance. The complementary function extends the human's capabilities beyond his or her current limitations - this includes sensing, computation, memory, physical force, and human decision making styles and skills. The interpretive (or hermeneutic, Hollnagel 1991) function translates information, functionality, and commands between the human and the aircraft. The Wings design concept allows the human to remain aware of the aircraft through natural interpretation. It also affords great improvements in system performance by maximizing the human's natural abilities and complementing the human's skills in a natural way. This paper will discuss the Wings design concept by describing the reversal in the traditional design process, the function allocation strategy of Wings, and the functions of complementing and interpreting the human.

Schutte, Paul C.↗

Identifying Climate Patterns Using Clustering Autoencoder Techniques

Abstract The complexity of growing spatiotemporal resolution of climate simulations produces a variety of climate patterns under different projection scenarios. This paper proposes a new data-driven climate classification workflow via an unsupervised deep learning technique that can dimensionally reduce the vast volume of spatiotemporal numerical climate projection data into a compact representation. We aim to identify distinct zones that capture multiple climate variables as well as their future changes under different climate change scenarios. Our approach leverages convolutional autoencoders combined with k -means clustering (standard autoencoder) and online clustering based on the Sinkhorn–Knopp algorithm (clustering autoencoder) across the conterminous United States (CONUS) to capture unique climate patterns in a data-driven fashion from the Geophysical Fluid Dynamics Laboratory Earth System Model with GOLD component (GFDL-ESM2G). The developed approach compresses 70 years of GFDL-ESM2G simulation at 0.125° spatial resolution across the CONUS under multiple warming scenarios to a lower-dimensional space by a factor of 660 000 and then tested on 150 years of GFDL-ESM2G simulation data. The results show that five climate clusters capture physically reasonable and spatially stable climatological patterns matched to known climate classes defined by human experts. Results also show that using a clustering autoencoder can reduce the computational time for clustering by up to 9.2 times when compared to using a standard autoencoder. Our five unique climate patterns resulting from the deep learning–based clustering of the lower-dimensional space thereby enable us to provide insights on hydrometeorology and its spatial heterogeneity across the conterminous United States immediately without downloading large climate datasets. Significance Statement This paper presents a data-driven climate classification approach using unsupervised deep learning to dimensionally reduce climate model outputs and to identify distinct climate regions for their future changes. Our approach compresses climate information for 70 years of Geophysical Fluid Dynamics Laboratory Earth System Model data across the conterminous United States (CONUS) at 0.125° spatial resolution. The results reveal that five climate clusters capture reasonable and stable climatological patterns matched to known climate patterns. The embedded clustering process in deep learning provides ×9.2 times faster execution than the k -means clustering technique. These results give us insight about climate spatial patterns and heterogeneity of hydrological patterns across the conterminous United States without downloading large climate datasets.

Kurihana, Takuya↗

Anatomy of a mega‐radiation: Biogeography and niche evolution in Astragalus

Premise Astragalus (Fabaceae), with more than 3000 species, represents a globally successful radiation of morphologically highly similar species predominant across the northern hemisphere. It has attracted attention from systematists and biogeographers, who have asked what factors might be behind the extraordinary diversity of this important arid-adapted clade and what sets it apart from close relatives with far less species richness. Methods Here, for the first time using extensive phylogenetic sampling, we asked whether (1) Astragalus is uniquely characterized by bursts of radiation or whether diversification instead is uniform and no different from closely related taxa. Then we tested whether the species diversity of Astragalus is attributable specifically to its predilection for (2) cold and arid habitats, (3) particular soils, or to (4) chromosome evolution. Finally, we tested (5) whether Astragalus originated in central Asia as proposed and (6) whether niche evolutionary shifts were subsequently associated with the colonization of other continents. Results Our results point to the importance of heterogeneity in the diversification of Astragalus, with upshifts associated with the earliest divergences but not strongly tied to any abiotic factor or biogeographic regionalization tested here. The only potential correlate with diversification we identified was chromosome number. Biogeographic shifts have a strong association with the abiotic environment and highlight the importance of central Asia as a biogeographic gateway. Conclusions Our investigation shows the importance of phylogenetic and evolutionary studies of logistically challenging “mega-radiations.” Our findings reject any simple key innovation behind high diversity and underline the often nuanced, multifactorial processes leading to species-rich clades.

59 BASIC BIOLOGICAL SCIENCES↗

Out With the Old: Empirical Trends in U.S. Land‐Based Wind Turbine Decommissioning and Repowering

A growing number of wind turbines (WTs) across the globe are now reaching or exceeding their expected service lifetime; WT decommissioning is on the rise. Accordingly, questions pertaining to WT end-of-life have risen in importance in policy and practice. Yet, research on the various factors relating to WT decommissioning is relatively sparse. Moreover, the key assumptions underpinning that prior research (e.g., the lifespan of WTs, characteristics of WTs being decommissioned, and whether the site is repowered with new WTs) have never been empirically tested across a large set of decommissioned WTs. Leveraging a uniquely comprehensive and spatially explicit dataset of decommissioned WTs in the United States, this research analyzes spatial, technological, and temporal trends in WT decommissioning and develops a novel predictive model for WT decommissioning. Our analysis pinpoints more than 12,400 WTs that have been fully decommissioned in the United States., the majority of which have been relatively old (> 30 years) and small (< 200 kW). While a WT's age alone is a good predictor of the likelihood of decommissioning, other factors such as the size of the WT and recent performance are also important and significant predictors. Most sites where decommissioning has occurred have seen subsequent repowering, with repowered plants featuring substantially fewer WTs (−86 on average) and higher rated plant capacity (+62 MW on average). Many existing WTs in the U.S. are approaching the end of their expected life with roughly 7500 being 20 or more years old. Findings can help policymakers and stakeholders begin preparing for this potential wave of future decommissioning and repowering.

Decommissioning / End-of-life↗

Zeolitic Imidazolate Framework Membranes: Novel Synthesis Methods and Progress Toward Industrial Use

In the last decade, zeolitic imidazolate frameworks (ZIFs) have been studied extensively for their potential as selective separation membranes. In this review, we highlight unique structural properties of ZIFs that allow them to achieve certain important separations, like that of propylene from propane, and summarize the state of the art in ZIF thin-film deposition on porous substrates and their modification by postsynthesis treatments. We also review the reported membrane performance for representative membrane synthesis approaches and attempt to rank the synthesis methods with respect to potential for scalability. To compare the dependence of membrane performance on membrane synthesis methods and operating conditions, we map out fluxes and separation factors of selected ZIF-8 membranes for propylene/propane separation. Finally, we provide future directions considering the importance of further improvements in scalability, cost effectiveness, and stable performance under industrially relevant conditions.

Chemistry↗

Predicting the superconducting critical temperature in transition metal carbides and nitrides using machine learning

Transition metal carbides and nitrides have unique mechanical and chemical characteristics. At low temperatures many of them also exhibit superconductivity, which can be controlled by substitutions into both the transition metal and carbon/nitrogen sites. To investigate the factors governing the superconducting state, we apply machine learning methods. Here we collected a dataset containing 147 materials, which was used to create a pipeline for predicting their superconducting critical temperature. When this pipeline is applied to a randomly selected test set, it shows a good performance, with of 0.82 and RMSE of 1.9 K. To explore the limits of the machine learning approach, we also use it to predict entire substitution series within the dataset. This represents a realistic test for the predictive models, which can be extremely useful when applied to new substitutions in materials systems. The performance of the pipeline in this case is much more uneven, with good predictions for some series, while for others the model shows minimal predictive power. We discuss possible reasons for these results, as well as methods to estimate the performance of machine learning on new substitution series.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Solidification cracking of laser melted commercial-purity tungsten

The high melting temperature of tungsten (W) makes it an attractive candidate for energy generation applications; however, its use is limited by its poor ductility at low temperatures. This limitation affects even melt-based additive manufacturing (AM) processes such as laser powder bed fusion (PBF-LB), with as-fabricated pure W exhibiting both longitudinal and transverse cracks. Metallurgical and processing factors that affect these cracks are still being explored. This work utilizes powderless single-tracks on pure W plates made over a range of power and velocity combinations in three unique PBF-LB setups: one with flowing argon, one with continuous vacuum, and an in situ high-speed synchrotron X-ray radiography setup. Each had different oxygen activities in their build environments. Longitudinal cracks with oxides appearing to exude from the crack were found for tracks deposited in a build environment with argon shield gas, while no such cracks were observed for builds conducted in vacuum. A calculation showed that direct oxygen ingress into the melt pool from the build environment is negligible when argon shield gas is present. Thus, incorporation of spatter is a likely mechanism for oxygen ingress into the melt pool. Radiography showed extensive keyholing, spatter generation, and crack formation at keyhole porosity. A heat transfer calculation showed the crack formation time was consistent with cooling below its ductile-to-brittle transition (DBT) temperature. This work identifies solidification cracking as a feasible mechanism in pure W beyond the well-known DBT related cracking.

Materials science↗

Urban morphology and urban water demand: a case study in the land constrained Los Angeles region using urban growth modeling

The interactions between population growth, urban morphology, and water demand have important implications for water resources and supply in urban regions. Water use for irrigation comprises a significant fraction of urban water demand, and is potentially influenced by long-term changes in urban morphology. To investigate this, we used spatially explicit projections of urban land development intensity (fraction impervious area) generated from a 30 m resolution urban growth model for the Los Angeles (LA) region. Recent historical data on water use and high resolution landcover were used to establish relationships between green area, urban development intensity, and outdoor water demand. These relationships were then used to project outdoor and total water demand in 2100 using the urban growth model outputs. We considered two different population scenarios informed by the shared socioeconomic pathway (SSP) projections for the region (SSP3 and SSP5), and three scenarios of urban development intensification. Our analysis is resolved for over 80 water providers in the region, from the urban core to suburban fringe, and highlights diverse demand responses influenced by initial urban form and water demand attributes. Assumptions about outdoor water use factors based on recent water supply data were found to be nearly as influential on future outdoor demand as the urban growth scenario settings. Compared to previous studies, our work is unique in coherently linking high resolution SSP population scenarios, urban land cover evolution, and urban water demand projections, demonstrating the approach for the LA region—the largest population center in the western United States.

54 ENVIRONMENTAL SCIENCES↗

Global optimization of harmonic oscillator basis in covariant density functional theory

The present investigation focuses on the improvement of the accuracy of the description of binding energies within moderately sized fermionic basis. Using the solutions corresponding to infinite fermionic basis it was shown that in the case of meson exchange (ME) covariant energy density functionals (CEDFs) the global accuracy of the description of binding energies in the finite $N_F$ = 16 - 20 bases can be drastically (by a factor ranging from ~3 up to ~9 dependent on the functional and $N_F$) improved by a global optimization of oscillator frequency of the basis. This is a consequence of the unique feature of the ME functionals in which with increasing fermionic basis size fermionic and mesonic energies approach the exact (infinite basis) solution from above and below, respectively. As a consequence, an optimal oscillator frequency $\hbar\omega_0$ of the basis can be defined which provides an accurate reproduction of exact total binding energies by the ones calculated in truncated basis. This leads to a very high accuracy of the calculations in moderately sized $N_F=20$ basis when mass dependent oscillator frequency is used: global rms differences $\delta B_{rms}$ between the binding energies calculated in infinite and truncated bases are only 0.025 MeV and 0.031 MeV for the NL5(Z) and DD-MEZ functionals, respectively. Optimized values of the oscillator frequency $\hbar\omega_0$ are provided for three major classes of CEDFs, i.e. for density dependent meson exchange functionals, nonlinear meson exchange ones and point coupling functionals.

Binding energy & masses↗

A reactive ferroelectric tuner for microphonics compensation

Jefferson Lab (JLab) is actively pursuing an extensive research program focused on developing advanced Nb₃Sn superconducting technology for particle accel-eration. Due to the brittle nature of Nb₃Sn coatings, a Ferroelectric Tuner (FRT) currently represents the most viable approach for microphonics compensation in these next-generation cavities. We suggest a novel, fast-responding FRT integrated directly into the main coupler, eliminating the need for an additional RF port. Leveraging a unique RF design based on a magic-T configuration, this advanced FRT will enable micro-phonics compensation in the ±30 Hz range without undesirable changes to the external quality factor.

Accelerator Physics↗

Hydrogen Life-Cycle Analysis in Support of Clean Hydrogen Production

Hydrogen is a basic molecule which is commonly used in the production of chemicals or as an energy carrier or a fuel. Its zero-carbon content means that it does not produce carbon dioxide upon its use. However, depending on the energy source and technology for hydrogen production and delivery, there can be greenhouse gas (GHG) emissions associated with the hydrogen for various end use applications. To provide the largest reduction in GHG emissions, hydrogen produced from clean energy sources should be used. As concerns regarding climate change grows, there is an increasing focus on economic production of clean hydrogen to displace less climate neutral sources of hydrogen. However, there are many different methods of hydrogen production with unique processes that result in different levels of life cycle GHG emissions of hydrogen production and its end use applications. Therefore, a comprehensive life cycle accounting methodology that takes all these factors into account is required. he GREET ® (Greenhouse gases, Regulated Emissions, and Energy use in Technologies) model was first developed in 1995 by Argonne National Laboratory with the support from the various offices of the U.S. Department of Energy (DOE). GREET provides in-depth Life Cycle Analysis (LCA) simulations for a variety of products and is available as an Excel spreadsheet (GREET Excel), or as an application (GREET .Net). Both versions are available for public download at no cost. This report accompanies GREET 2022 release to describe the major updates and expansions to the hydrogen technology pathways, and to provide data sources and sample carbon intensity results for each of the pathways.

08 HYDROGEN↗