SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
We have developed a model for production of ba-sin ejecta deposits to address provenances of materials collected at the Apollo and Luna landing sites and for consideration in interpreting remote sensing data.
In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.
The three years of Mars Odyssey successful work on the martian orbit provide a lot of new information about peculiarities of long term variations of CO2 seasonal cycle. To start such analysis we have used observations of neutron albedo of Mars obtained by High Energy Neutron detector (HEND) mounted onboard Mars Odyssey spacecraft. The high latitude northern and southern regions of Mars are affected by global redistribution of atmospheric CO2 which resulted in 25% of atmospheric mass condensed on martian surface of these regions during winter period of time. The seasonal deposit is formed starting from 60N/60S latitudes and achieve its maximal thickness about 1 m at latitudes close to martian poles. Changes of CO2 deposit thickness is the reason for significant variations of neutron flux above martian poles from summer to winter seasons because CO2 frost effectively hides upper water rich surface layers from the orbit observations in neutrons and gamma-rays. This effect was used to estimate column density of CO2 deposit at different latitudes on North and South of Mars and reconstruct multidimensional model of CO2 deposit showing how snow depth varies as function of latitude, longitude and time. In this presentation we tried to make a next step in our study of martian seasonal CO2 cycle and look for similarities and differences between two successive martian years.
Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal microgravity; however, much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER results agree with experimental data indicating that indirect effects of radiation (reactive oxygen species generation, metabolic impairment) have a greater impact on microorganisms than direct effects (DNA damage).
Space is tough on organisms. Microorganisms traveling to space experience stress from environmental features such as ionizing radiation and lack of normal gravity, and much remains unknown about the mechanisms by which those environmental features affect microbial physiology. Microbes experience changes in gravity not directly but rather through changes in their fluid environment, and deep-space particle radiation causes cell damage that is complex but rare. Computational modeling at the single-cell level (agent-based modeling) can allow us to probe the spatially heterogeneous processes that characterize space stresses, to gain insight into the relationships of microbial cells with their environments and with each other. Here we present two software packages for simulating microbial population dynamics in space conditions: CAMDLES and AMMPER. Microbes growing in liquid culture medium in the microgravity of an orbital space station experience a quiescent, poorly-mixed fluid environment. CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation) simultaneously simulates biological, chemical, and mechanical processes to predict microbial ecological dynamics in microgravity, and in the rotating culture vessels used to create an artificial microgravity environment in the lab. Initial results demonstrate that the growth of a cross-feeding microbial consortium, dependent on the exchange of soluble metabolites, is sensitive to the initial spatial distribution of cells, and grows differently in real versus artificial microgravity. Microbial populations exposed to deep-space radiation experience spatially and temporally heterogeneous damage from the traversal of high-energy particles. AMMPER (Agent-Based Model for Microbial Populations Exposed to Radiation) pairs a 3d model of energy deposition along a radiation particle track with a microbial population growth and damage model to predict the effects of localized radiation damage on population-level responses. It includes a user-friendly graphical interface. AMMPER growth curves recapitulate experimental results, and allow comparison between direct effects (DNA damage) and indirect effects (reactive oxygen species generation, metabolic impairment) of radiation.
A model of the vaporization and mass transport of mixed organometallics from a single source for thin film metalorganic chemical vapor deposition is presented. A stoichiometric gas phase can be obtained from a mixture of the organometallics in the desired mole ratios, in spite of differences in the volatilities of the individual compounds. Proper film composition and growth rates are obtained by controlling the velocity of a carriage containing the organometallics through the heating zone of a vaporizer.
Climate change, elevating atmosphere CO 2 (eCO 2 ) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon-nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO 2 and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO 2 and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO 2 and ΔMAT rather than ΔMAP and ecosystem types. In this work, process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO 2 led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.
The formation of double‐strand breaks (DSBs) and chromosomal aberrations (CAs) is of great importance in radiation research and, specifically, in space applications. We are presenting a new particle track and DNA damage model, in which the particle stochastic track structure is combined with the random walk (RW) structure of chromosomes in a cell nucleus. The motivation for this effort stems from the fact that the model with the RW chromosomes, NASARTI (NASA radiation track image) previously relied on amorphous track structure, while the stochastic track structure model RITRACKS (Relativistic Ion Tracks) was focused on more microscopic targets than the entire genome. We have combined chromosomes simulated by RWs with stochastic track structure, which uses nanoscopic dose calculations performed with the Monte‐Carlo simulation by RITRACKS in a voxelized space. The new simulations produce the number of DSBs as function of dose and particle fluence for high‐energy particles, including iron, carbon and protons, using voxels of 20 nm dimension. The combined model also calculates yields of radiation‐induced CAs and unrejoined chromosome breaks in normal and repair deficient cells. The joined computational model is calibrated using the relative frequencies and distributions of chromosomal aberrations reported in the literature. The model considers fractionated deposition of energy to approximate dose rates of the space flight environment. The joined model also predicts of the yields and sizes of translocations, dicentrics, rings, and more complex‐type aberrations formed in the G0/G1 cell cycle phase during the first cell division after irradiation. We found that the main advantage of the joined model is our ability to simulate small doses: 0.05‐0.5 Gy. At such low doses, the stochastic track structure proved to be indispensable, as the action of individual delta‐rays becomes more important.
The formation of double‐strand breaks (DSBs) and chromosomal aberrations (CAs) is of great importance in radiation research and, specifically, in space applications. We are presenting a new particle track and DNA damage model, in which the particle stochastic track structure is combined with the random walk (RW) structure of chromosomes in a cell nucleus. The motivation for this effort stems from the fact that the model with the RW chromosomes, NASARTI (NASA radiation track image) previously relied on amorphous track structure, while the stochastic track structure model RITRACKS (Relativistic Ion Tracks) was focused on more microscopic targets than the entire genome. We have combined chromosomes simulated by RWs with stochastic track structure, which uses nanoscopic dose calculations performed with the Monte‐Carlo simulation by RITRACKS in a voxelized space. The new simulations produce the number of DSBs as function of dose and particle fluence for high‐energy particles, including iron, carbon and protons, using voxels of 20 nm dimension. The combined model also calculates yields of radiation‐induced CAs and unrejoined chromosome breaks in normal and repair deficient cells. The joined computational model is calibrated using the relative frequencies and distributions of chromosomal aberrations reported in the literature. The model considers fractionated deposition of energy to approximate dose rates of the space flight environment. The joined model also predicts of the yields and sizes of translocations, dicentrics, rings, and more complex‐type aberrations formed in the G0/G1 cell cycle phase during the first cell division after irradiation. We found that the main advantage of the joined model is our ability to simulate small doses: 0.05‐0.5 Gy. At such low doses, the stochastic track structure proved to be indispensable, as the action of individual delta‐rays becomes more important.
The formation of double-strand breaks (DSBs) and chromosomal aberrations (CAs) is of great importance in radiation research and, specifically, in space applications. We are presenting a recently developed model, in which chromosomes simulated by NASARTI (NASA Radiation Tracks Image) is combined with nanoscopic dose calculations performed with the Monte-Carlo simulation by RITRACKS (Relativistic Ion Tracks) in a voxelized space. The model produces the number of DSBs, as a function of dose for high-energy iron, oxygen, and carbon ions, and He ions. The combined model calculates yields of radiation-induced CAs and unrejoined chromosome breaks in normal and repair deficient cells. The merged computational model is calibrated using the relative frequencies and distributions of chromosomal aberrations reported in the literature. The model considers fractionated deposition of energy to approximate dose rates of the space flight environment. The merged model also predicts of the yields and sizes of translocations, dicentrics, rings, and more complex-type aberrations formed in the G0/G1 cell cycle phase during the first cell division after irradiation.
Manganese (Mn) is a redox–active micronutrient that has been shown to accelerate plant litter decomposition; however, the effect of Mn–promoted decomposition on soil C storage is unclear. We present a novel biogeochemical model simulating how Mn bioavailability influences soil organic C (SOC) stocks in a soil profile (<50 cm) within a temperate forest. In our model, foliar Mn increased in response to increasing soluble Mn released through Mn–oxide (birnessite) dissolution in mineral soil layers. The ensuing Mn enrichment in leaf litter redistributed Mn to the surface forest floor layer, promoted enzymatic oxidation of lignin, and decreased SOC stocks. Total SOC loss was partially mitigated by accumulation of lignin–oxidation products as mineral–associated organic C. We also explored how Mn–driven changes to C storage interacted with effects of N deposition and warming. Nitrogen enrichment inhibited Mn–dependent lignin degradation, increasing SOC stocks and weakening their dependence on Mn bioavailability. Warming stimulated decomposition and reduced C stocks but was less effective at low Mn bioavailability. Our model results suggest that SOC stocks are sensitive to Mn bioavailability because increased plant uptake redistributes Mn to surface soils where it can enhance litter decomposition. Finally, based on our simulations, we predict that Mn becomes limiting to litter decomposition where Mn is poorly soluble. Depletion of bioavailable Mn or other cofactors that are critical to decomposition could limit the response of organic C stocks to warming over time, but quantitative projections of the role of Mn bioavailability in regulating decomposition requires additional measurements to constrain model uncertainties.
Small supported metal particles have become a popular area of intense research interest, and important contributions to the considered problems are being made from the fields of uhv technology, thin film physics surface science, and surface and thin film instrumentation. Attention is given to insulating supports, particulate metal deposits and their properties, metal/support interactions and gas exposures, and integrated experimental approaches. It is concluded that major contributions to the field of model catalysis should be forthcoming in the near future from uhv-based methods of research. Catalysis and catalysis-related problem areas expected to benefit from advanced model studies include catalyst preparation processing, sintering mechanisms for metals and alloys, separation of initial and final state effects for supported clusters, and the influence of particle and/or support morphologies.
Recent developments in additive manufacturing (AM) technology have reignited interest in the fabrication of the Nb-based refractory C103 alloy offering solutions to the challenges posed by traditional manufacturing methods. However, the limited numerical and experimental studies on laser direct energy deposition (DED) of C103 have hindered the understanding of the relationships between process parameters and build quality. This has made it challenging to consistently produce parts with the desired quality and microstructure suitable for critical applications. In this study, we focus on optimizing the laser DED process for C103 by employing a hybrid approach that combines experimental techniques and computational fluid dynamics (CFD). This approach facilitates the development of process maps for defect detection and geometric precision. To achieve this, multi-layer C103 samples were fabricated using laser DED under various process parameters, enabling the creation of a process map for defect detection. Additionally, a multi-physics, multiphase simulation framework was developed within a high-performance computing (HPC) environment to establish process maps for geometric precision. Using these process maps, printability windows were identified for achieving both the desired geometric accuracy and defect-free prints. It was observed that prints with a power-to-velocity (P/V) ratio close to unity resulted in defect-free outcomes. This study provides a foundation for reducing design lead time and rejected parts, ultimately optimizing the laser DED process for C103.
A carbonate-silicate geochemical cycle model is developed and used to explore dynamic and climatic consequences of constraints on shallow-water carbonate burial and possible carbon loss to the mantle associated with sea-floor subduction. The model partitions carbonate deposition between shallow-water and deep-water environments and includes carbon fluxes between the mantle and lithosphere. When total lithospheric carbonate mass is constant, there are two stable steady states, one in which the carbonate burial flux is mostly continental and another in which it is mostly pelagic. The continental steady state is characterized by a low metamorphic CO2 flux to the atmosphere and predominantly shallow-water carbonate burial. The pelagic steady state is characterized by a high metamorphic CO2 flux and predominantly deep-water carbonate burial. For reasonable parameter values, when total lithospheric carbonate mass is allowed to vary, the model oscillates between predominantly continental and predominantly pelagic modes. Model results suggest that carbonate deposition patterns established during the Cenozoic may be pushing the Earth system from the continental to the pelagic mode on a time scale of 10(8) yr, with a possible consequent order-of-magnitude increase in the metamorphic CO2 flux to the atmosphere.
Design and development activities were carried out for the Ultraviolet Imager (UVI) to be flown on the Polar Spacecraft of the INternational Solar Terrestrial Physics (ISTP) Mission. The following tasks were performed: (1) design and fabrication of prototype/engineering model of the UVI imager; (2) preliminary design review; (3) vacuum ultraviolet filter design; (4) auroral energy deposition code; (5) model of LBH vehicle glow; (6) laboratory measurement program of collision cross-sections; and (7) support of ISTP meetings.
Critical components, such as detonators, in Sandia's stockpile contain heterogeneous materials whose performance and reliability depend on accurate, predictive models of coupled, complex phenomena to predict their synthesis, processing, and operation. Ongoing research in energetic materials has shown that microstructural properties, such as density, pore-size, morphology, and specific surface area are correlated to their initiation threshold and detonation behavior. However, experiments to study these specific characteristics of energetic materials are challenging and time consuming. Therefore, in this work, we turn to mesoscale modeling methods that may be capable of reproducing some observed phenomena to refine and predict outcomes beforehand. Even so, we have no physics-based modeling capability to predict how the microstructure of an energetic material will evolve over near- and long-term time scales. Thus, the goal of this work is to (i) identify any knowledge gaps in how the underlying microstructure forms and evolves during the synthesis process, and (ii) develop and test a mesoscale phase-field model for vapor deposition to capture critical mechanisms of microstructure formation, evolution, and variability in vapor-deposited energetic materials, such as processing conditions, material properties, and substrate interactions. Based on this work, the phase-field method is shown to be a valuable tool for developing the necessary models containing coupled, complex phenomena to investigate and understand the synthesis and processing of energetic materials.
The debate concerning the evolution of CO2 on Mars continues. It would appear that in order to explain the valley networks and other relict fluvial landforms it is necessary to accept that liquid water was once present at the surface of Mars. This in turn requires, at some point in the planet's history, a higher surface temperature than exists today, proposition explained traditionally by an early dense CO2, atmosphere. However, there are a number of problems with this notion: for instance, CO2 alone is not an efficient greenhouse gas because of its tendency to form clouds. Moreover, if there was an early dense CO2 atmosphere, it is necessary to explain where the elemental constituents now reside. There are two possibilities for the latter, namely loss to outer space of atmospheric CO2 or the formation of vast carbonate deposits. While some models of atmospheric loss predict that up to 0.4 bar of CO2 could be removed from the Martian surface, this is still not enough to account for the original atmospheric inventory, usually considered to have been in the range of 1-5 bar. Thus, most models of the evolution of the Martian surface require removal of CO2 from the atmosphere and into carbonate deposits. However, as yet, the evidence for the existence of carbonates on Mars is fairly scant. This is an issue that would have been resolved by results obtained from Mars Observer.
This project focused on providing observational constraints on dry deposition of black carbon and aerosol particles, and the extent to which wet and dry deposition impacts the lifetime of aerosols in the atmosphere. The proposed work tackled the following questions: To what extent dry versus wet deposition controls the removal of BC from the atmosphere, and thus atmospheric BC concentrations? Is BC dry deposition controlled by the same processes as non-refractory aerosol dry deposition? We successfully made eddy covariance flux measurements at the DOE Southern Great Plains site of size-resolved aerosol number fluxes with an ultra high sensitivity aerosol spectrometer (UHSAS) and of black carbon mass and number fluxes using a single particle soot photometer (SP2). We also collected precipitation samples for off-line measurement of rBC using a wet deposition collector. Using these measurements, we identified that wet deposition was the dominant control for black carbon lifetime, but that dry deposition was poorly constrained in models. We developed a new parameterization for particle dry deposition, and applied it to global models to demonstrate the importance of dry deposition in air pollution and radiative effect estimates.