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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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Charts of isentropic exponent as function of enthalpy and speed for air, nitrogen, carbon dioxide, and mixtures of nitrogen and carbon dioxide in equilibrium
The dynamic biogeochemical equilibria among the major pools of carbon, nitrogen, sulfur, and phosphorus represented by terrestrial biomes, the world's oceans, and the troposphere are disturbed. Since even the most rapid processes of adjustments among the reservoirs take decades, new equilibria are far from established. These human-induced perturbations and the system's subsequent responses constitute an on-going biogeochemical experiment at the global level. Current and new information must be combined in a way that allows testing of various hypotheses about the workings of global biogeochemical systems. This enables assessment of current knowledge and evaluation of the gaps.
Dynamic tests were performed on self acting (hydrodynamic) carbon face rotary shaft seals to assess their potential, relative to presently used labyrinth seals, for improving performance of aircraft gas turbine engines by reducing air leakage flow rate at compressor end seal locations. Three self acting bearing configurations, designed to supply load support at the interface of the stationary carbon seal and rotating seal race, were tested. Two configurations, the shrouded taper and shrouded flat step, were incorporated on the face of the stationary carbon seal element. The third configuration, inward pumping spiral grooves, was incorporated on the hard faced surface of the rotating seal race. Test results demonstrated seal leakage air flow rates from 75 to 95% lower that can be achieved with best state-of-the-art labyrinth designs and led to identification of the need for a more geometrically stable seal design configuration which is presently being manufactured for subsequent test evaluation.
The Oregon Transect Ecosystem Research (OTTER) project is a study of ecosystem functions in coniferous forests using the methods of computer modeling, experimental and theoretical remote sensing, and ecological field and laboratory techniques. The study is focused on predicting the major fluxes of carbon, nitrogen, and water, and the factors that dynamically regulate them. The OTTER project was conceived to test two major questions: (1) Can a generalized ecosystem simulation model, designed to use mainly parameters available from remote sensing, predict the functioning of forests across an environmentally variable region? and (2) To what extent can the variables required by this model be derived from remotely sensed data? The scientific objectives and scope of the project demanded that a coordinated effort be made to link ground measurements with remote sensing and modeling requirements. OTTER was selected as a focus for a National Aeronautics and Space Administration (NASA)-sponsored Multi-sensor Aircraft Campaign (MAC; combining NASA aircraft and sensors with those of others) on the basis of experience gained in past ecosystem studies and remote-sensing projects, and the importance of the OTTER objectives to NASA's long-range science goals and plans. Having several independent approaches available, both on the ground and from various remote-sensing platforms, proved valuable in estimating and validating many of the critical variables. This experience and cross comparison should help simplify future studies of a similar nature. Edited data sets from the OTTER project are now available to the scientific community on optical disks or via on-line data banks at NASA (Washington, D.C., USA) and Oregon State University (Corvallis, Oregon, USA).
This effort seeks to develop and test high-performance, long operating life, physically stable catalysts for use in spacecraft water reclamation systems. The primary goals are to a) reduce the quantity of expendable water filters used to purify water aboard spacecraft, b) to extend the life of the oxidation catalysts used for eliminating organic contaminants in the water reclamation systems, and c) reduce the weight/volume of the catalytic oxidation systems (e.g. VRA) used. This effort is targeted toward later space station utilization and will consist of developing flight-qualifiable catalysts and long-term ground tests of the catalyst prior to their utilization in flight. Fixed -bed catalytic reactors containing 5% platinum on granular activated carbon have been subjected to long-term dynamic column tests to measure catalyst stability vs throughput. The data generated so far indicate that an order of magnitude improvement can be obtained with the treated catalysts vs the control catalyst, at only a minor loss (approx 10%) in the initial catalytic activity.
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 21-Jun-1995 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used in a way that is similar to training data to classify the image into the different land cover classes. The data are provided in a binary, image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep-1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. This biomass density image covers almost the entire BOREAS SSA. The pixels for which biomass density is computed include areas, that are in conifer land cover classes only. The biomass density values represent the amount of overstory biomass (i.e., tree biomass only) per unit area. It is derived from a Landsat-5 TM image collected on 02-Sep-1994. The technique that was used to create this image is very similar to the technique that was as used to create the physical classification of the SSA. The data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the NSA. A Landsat-5 TM image from 20-Aug-1988 was used to derive this classification. A standard supervised maximum likelihood classification approach was used to produce this classification. The data are provided in a binary image format file. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).
The BOREAS TE-18 team focused its efforts on using remotely sensed data to characterize the successional and disturbance dynamics of the boreal forest for use in carbon modeling. The objective of this classification is to provide the BOREAS investigators with a data product that characterizes the land cover of the SSA. A Landsat-5 TM image from 02-Sep- 1994 was used to derive the classification. A technique was implemented that uses reflectances of various land cover types along with a geometric optical canopy model to produce spectral trajectories. These trajectories are used as training data to classify the image into the different land cover classes. These data are provided in a binary image file format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Center (DAAC).
The Soil Moisture Active and Passive (SMAP) mission is a NASA earth science mission aiming at improving our understanding of the dynamics of the cycles of energy, water, and carbon at global scales. The mission features two complementary sensors on the same low-Earth orbiting platform: an L-band synthetic aperture radar (SAR) operating at 1.26 GHz and an L-band radiometer operating at 1.41 GHz. Together these instruments will provide global mapping of soil moisture and freeze/thaw states in 2-3 days, with a tentative launch date in 2014. The work reported in this study focuses primarily on the development of the SMAP radiometer-only soil moisture data product. For passive soil moisture retrieval at satellite footprint scales, one way to improve retrieval accuracy is to correct for the microwave emission from open water bodies prior to retrieval. The accuracy of this correction will depend on not only the locations of these water bodies, but also the geolocation accuracy of the instrument. As perfect knowledge is never attainable in practice, it is important to assess the impacts of these uncertainties on the SMAP radiometer observations and hence the passive soil moisture retrieval accuracy. In this presentation, we present the results of our preliminary assessment on the impacts of these uncertainties. Our study consists of two parts: (1) a sensitivity analysis on the SMAP radiometer observations due to uncertainties in water-body classification, and (2) realistic global simulations that take into account of additional uncertainties (e.g., geolocation and ancillary data) and SMAP-specific instrument characteristics (e.g., orbit sampling and antenna pattern). The results will provide valuable prelaunch guidance to the SMAP team in identifying different error sources and their relative impacts on the passive soil moisture data product.
The challenge of energy transition is immediate and immense; current projections target 75 TW of photovoltaics (PV) capacity by 2050. While any transition to renewable energy technology is preferable to the current fossil-based system, it is ideal to improve the sustainability of PV to minimize negative environmental and social impacts. Circular economy (CE) has been proposed as a method to improve the sustainability of PV, especially for emerging materials like perovskites. CE is a set of actions, principles, and systems which aim to design out waste and keep products and materials in use, to reduce environmental impacts and enable sustainable development. At the most basic level, CE is "reduce, reuse, recycle", the R-actions, in ranked order. CE of a PV technology can be metricized in a variety of ways, such as the Material Circularity Indicator (Smith and Jones, Ellen MacArthur Foundation, 2019) or recycling rates. Unfortunately, standard CE metrics have several shortcomings for measuring renewable energy technologies in the context of deployment for energy transition (Figge 2018, Saidani 2019): 1) Only measure mass flows; 2) De-prioritization of the use phase in favor of mass circularity when scoring; and 3) Tight focus on a single product scale The use phase and energy flows of PV are key to energy transition, and therefore need to be quantified. Additionally, correlating product-scale to system-scale is necessary for quantifying the environmental impacts of energy transition. Life Cycle Assessment (LCA) can address some of these concerns, but also focuses on a single product scale and has trouble capturing the dynamics of system-scale energy transition, such as the interaction of module lifetime with manufacturing demands for energy transition deployment schedules. Therefore, we developed an open-source Python-based system dynamics model to quantify the mass, energy and carbon impacts of CE R-actions for PV technologies in the energy transition; PV in the CE (PV ICE) (Ovaitt & Mirletz 2021). The tool captures supply chains from material extraction through end of life, incorporating 5 circular end of life pathways. PV ICE takes in any evolving bill of materials, module properties and deployment schedule to support researchers and decision makers with data-backed insights. In this work, we quantify and compare proposed CE sustainable PV module designs and lifecycle management strategies, spanning currently commercialized technologies, government and industry technology targets, and several low Technology Readiness Level (TRL) emerging PV technologies, including perovskites. Our analyses capture the projected evolutions of lifetime, efficiency and material circularity of these PV technologies, as well as their material supply chains. Our analyses emphasize the importance of examining a suite of metrics to identify priorities and tradeoffs, and inform design or lifecycle management decisions holistically. Previous analyses have demonstrated the central importance of PV module lifetime to support energy transition while minimizing impacts. High levels of material circularity (>90%) enable minimizing lifecycle wastes, can reduce virgin material demands if paired with improving efficiency, but demonstrate tradeoffs in energy return on investment. In the fervor of new material and technology development, it is important to remember that CE is not the end goal; decarbonization and energy transition are the end goal. CE should be used in service to improve the sustainability of PV, and R-actions evaluated for their usefulness and efficacy to this end.
Floodplain soils are vast reservoirs of organic carbon often attributed to anaerobic conditions that impose metabolic constraints on organic matter degradation. What remains elusive is how such metabolic constraints respond to dynamic flooding and drainage cycles characteristic of floodplain soils. Here, in this work, we show that microbial depolymerization and respiration of organic compounds, two rate-limiting steps in decomposition, vary spatially and temporally with seasonal flooding of mountainous floodplain soils (Gothic, Colorado, USA). Combining metabolomics and -proteomics, we found a lower abundance of oxidative enzymes during flooding coincided with the accumulation of aromatic, high-molecular weight compounds, particularly in surface soils. In subsurface soils, we found that a lower oxidation state of carbon coincided with a greater abundance of chemically reduced, energetically less favorable low-molecular weight metabolites, irrespective of flooding condition. Our results suggest that seasonal flooding temporarily constrains oxidative depolymerization of larger, potentially plant-derived compounds in surface soils; in contrast, energetic constraints on microbial respiration persist in more reducing subsurface soils regardless of flooding. Our work underscores that the potential vulnerability of these distinct anaerobic carbon storage mechanisms to changing flooding dynamics should be considered, particularly as climate change shifts both the frequency and extent of flooding in floodplains globally.
This data package contains global-scale Earth System Model simulations run with DOE's E3SM Model. The package includes one set of simulations run in the default configuration and a second set of simulations run with the dynamic root module enabled. These two datasets can be used to assess the impact that dynamic roots have on Land Surface fluxes such as carbon and water. The outputs are provided here on a 0.5 x 0.5 global grid at monthly resolution. The simulations were run with atmospheric forcing from the Global Soil Wetness Project. We provide specifically here Gross Primary Production, Transpiration, relative root fraction per soil layer as well as Air Temperature, Precipitation and all the parameterizations used for the simulations. Our purpose for generating and analyzing these simulations was to assess the role that root dynamics and foraging for water has in the recovery timescale of ecosystems following climate perturbation. All data provided are in the "netcdf" format using standard CF-1 (Climate and Forecast) Convention. The data are broken up into 20 year chunks to facilitate easier read-in. The data are all machine readable using various software platforms including Matlab, NCO, Panoply and GrADS.
Abstract The ability to control phase structures and surface sites of ultrasmall alloy nanoparticles under reaction conditions is essential for preparing catalysts by design. This is, however, challenging due to limited understanding of the atomic‐scale phases and their correlation with the ensemble‐averaged structures and activities of catalysts during catalytic reactions. We reveal here a dynamic structural stability of alumina‐supported ultrasmall and equiatomic copper‐gold alloy nanoparticles under reaction conditions as a model system in the in situ/operando study. In situ atomic‐scale morphological tracking under oxygen reveals temperature‐dependent dynamic crystalline‐amorphous dual‐phase structures, showing dynamic stability over an elevated temperature range. This atomic‐scale dynamic phase stability coincides with a “conversion plateau” observed for carbon monoxide oxidation on the catalyst. It is substantiated by the stable lattice ordering/disordering structures and surface sites with oscillatory characteristics shown by operando ensemble‐average structural tracking of the catalyst during the oxidation reaction. The understanding of the atomic‐scale dynamic phase structures in correlation with the ensemble‐average dynamic ordering/disordering phase structures and surface sites provides fresh insights into the unique synergy of the supported alloy nanoparticles. This understanding has implications for the design and structural tuning of active and stable ultrasmall alloy catalysts under elevated temperatures.
Microwave-assisted hydrogen generation from hydrocarbon-bearing reservoir rocks is strongly influenced by mineralogy, methane activation, carbonate reactions, and thermal runaway behavior. This study investigates a new approach in which carbonate phases are generated in-situ through the reaction of internally produced CO2 with Ca(OH)2 under microwave heating conditions. The objective is to evaluate how rock mineralogy, methane injection, and Ca(OH)2 addition influence hydrogen generation, carbon redistribution, and stage-dependent reaction pathways during microwave exposure. Microwave heating experiments were conducted using Permian Basin reservoir rocks under three experimental conditions: rock-only experiments under Ar atmosphere, CH4–Ar experiments without additive, and CH4–Ar experiments containing 5 wt% Ca(OH)2. Methane-assisted experiments were performed under continuous injection of 30 standard cubic centimeters per minute (sccm) CH4 and 30 sccm Ar. Based on thermal runaway behavior, each experiment was divided into three operational stages: Before Thermal Runaway (BR), After Thermal Runaway–Decrease in Microwave Power (ARD), and After Thermal Runaway– Increase in Microwave Power (ARI). Temperature and gas composition were continuously monitored throughout the experiments. The rock-only experiments demonstrated that hydrogen generation can occur intrinsically from hydrocarbon-bearing rocks under microwave heating, even without externally injected methane. However, hydrogen production did not correlate solely with kerogen content, indicating that mineralogy strongly influences hydrogen-generation pathways. Correlation analyses suggested that kerogen decomposition initially generated CH4, CO, and CO2, followed by secondary hydrocarbon reactions associated with H2 and C2 hydrocarbon formation. Methane-assisted experiments substantially increased hydrogen production; however, identical methane injection rates produced significantly different hydrogen yields among the rock samples, confirming that mineralogical composition controls methaneconversion behavior under microwave heating conditions. The addition of Ca(OH)2 significantly altered carbon evolution behavior in a stage-dependent manner. During the BR stage, Ca(OH)2 reduced gas-phase CO2 production, particularly in carbonate-rich rocks, indicating favorable conditions for in-situ carbonation and carbonate deposition prior to extensive thermal decomposition. The suppression of CO2 during BR became more pronounced with increasing carbonate content of the rock system. After thermal runaway, carbonate-containing systems exhibited enhanced hydrogen generation behavior, suggesting that carbonatederived mineral transformations and carbonate-mediated reactions contribute to high-temperature hydrogen-generation pathways. In carbonate-poor rocks, Ca(OH)2 addition enabled simultaneous URTeC 4493775 2 enhancement of hydrogen production and partial suppression of CO2 release during the post-runaway stages. Overall, the results demonstrate that microwave-assisted hydrogen generation is governed by dynamically evolving interactions among kerogen decomposition, methane activation, mineral transformations, carbonate formation/decomposition, and thermal runaway behavior. This work introduces in-situ carbonate engineering with Ca(OH)2 as a strategy for coupling hydrogen generation with partial insitu carbon management under microwave heating conditions.
We have conducted an experimental study on the photo double ionization (PDI) of carbon dioxide dimers and oxygen dimers, while focusing on the dissociation dynamics upon single photon absorption. The results in terms of the kinetic energy and angular distributions of the charged particles show unambiguous experimental evidence of intermolecular Coulombic decay (ICD) in carbon dioxide dimers. In the oxygen dimer, the results show that ICD is accompanied by knock-off ionization mechanisms.
The fate of organic carbon (C) in permafrost soils is important to the climate system due to the large global stocks of permafrost C. Thawing permafrost can be subject to dynamic hydrology, making redox processes an important factor controlling soil organic matter (SOM) decomposition rates and greenhouse gas production. In iron (Fe)-rich permafrost soils, Fe(III) can serve as a terminal electron acceptor, promoting anaerobic respiration of SOM and increasing pH. Current large-scale models of Arctic C cycling do not include Fe cycling or pH interactions. Here, a geochemical reaction model was developed by coupling Fe redox reactions and C cycling to simulate SOM decomposition, Fe(III) reduction, pH dynamics, and greenhouse gas production in permafrost soils subject to dynamic hydrology. In this study we parameterized the model using measured CO 2 and CH 4 fluxes as well as changes in pH, Fe(II), and dissolved organic C concentrations from oxic and anoxic incubations of permafrost soils from polygonal permafrost sites in northern Alaska, United States. In simulations of repeated oxic-anoxic cycles, Fe(III) reduction during anoxic periods enhanced CO 2 production, while the net effect of Fe(III) reduction on cumulative CH 4 fluxes depended on substrate C availability. With lower substrate availability, Fe(III) reduction decreased total CH 4 production by further limiting available substrate. With higher substrate availability, Fe(III) reduction enhanced CH 4 production by increasing pH. Our results suggest that interactions among Fe-redox reactions, pH and methanogenesis are important factors in predicting CH 4 and CO 2 production as well as SOM decomposition rates in Fe-rich, frequently waterlogged Arctic soils.