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

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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Coordinated Multiscale Modeling and Synthesis of Novel Nanostructured Composite Membranes for Solar Fuels Generation (Final Report)

Generation of carbon-based liquid fuels from reduction of CO 2 using solar energy requires the development of improved membranes that provide good ionic conductivity and mechanical properties while minimizing the crossover of gases and reduction products. Using closely coordinated multiscale modeling, synthesis and characterization studies we propose to investigate and develop novel nanostructured composite membranes with applications to conversion of carbon dioxide to storable chemical fuels. The envisioned proton exchange membranes (PEMs) will be based on a support of self- assembling polymer-modified nanoparticles with controllable porosity and tortuosity. The use of a nanoparticle support will provide control of transport and mechanical properties of the membranes. Tuning the copolymer modification of nanoparticles (polymer architectures, brush grafting density) will allow to optimize the ion (proton) transport via the Grotthuss mechanism through narrow hydrated channels while minimizing crossover of gases and reaction products due to the high density of the grafted brush and use of a non-ionic conducting glassy polymers to fill spaces between polymer-grafted nanoparticles. In Phase I synthesis of the copolymers and their attachment to the nanoparticle support will be guided by multiscale simulations that include atomistic molecular dynamics and continuum-level transport simulations. The former will include reactive and non-reactive atomistic simulations that will provide key insight into nanoscale polymer morphology and ion/molecular transport mechanisms need to optimize the copolymer structure. The latter will provide insight into the role of nanoparticle self-assembly on the global transport of ionic and molecular species. The proton conduction and CO 2 /methanol permeability of the membranes will be experimentally characterized as well as simulated and will be correlated with morphology and polymer structure. Prototypes of optimal membranes will be fabricated and characterized at the end of the project. Successful development of improved nanostructured composite PEMs and demonstration of the simulation-guided materials-by-design paradigm will result in our ability to design and synthesize membranes for a wide variety of solar fuels generation and related electrochemical applications.

14 SOLAR ENERGY↗
DOE OSTI2024

Skeletal Kinetics Reduction for Astrophysical Reaction Networks

A novel methodology is developed to extract accurate skeletal reaction models for nuclear combustion. Local sensitivities of isotope mass fractions with respect to reaction rates are modeled based on the forced optimally time-dependent (f-OTD) scheme. These sensitivities are then analyzed temporally to generate skeletal models. The methodology is demonstrated by conducting skeletal reduction of constant density and temperature burning of carbon and oxygen relevant to Type Ia supernovae (SNe Ia). The 495-isotopes Torch model is chosen as the detailed reaction network. A map of maximum production of 56 Ni in SNe Ia is produced for different temperatures, densities, and proton-to-neutron ratios. The f-OTD simulations and the sensitivity analyses are then performed with initial conditions from this map. A series of skeletal models are derived and their performances are assessed by comparison against currently existing skeletal models. Previous models have been constructed intuitively by assuming the dominance of α-chain reactions. The comparison of the newly generated skeletal models against previous models is based on the predicted energy release and 44 Ti and 56 Ni abundances by each model. The consequences of ye ≠ 0.5 in the initial composition are also explored where ye is the electron fraction. The simulated results show that 56 Ni production decreases by decreasing ye as expected, and that the 43 Sc is a key isotope in proton and neutron channels toward 56 Ni production. It is shown that an f-OTD skeletal model with 150 isotopes can accurately predict the 56Ni abundance in SNe Ia for ye ≲ 0.5 initial conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Bicarbonate impact on U(VI) bioreduction in a shallow alluvial aquifer

Field-scale biostimulation and desorption tracer experiments conducted in a uranium (U) contaminated, shallow alluvial aquifer have provided insight into the coupling of microbiology, biogeochemistry, and hydrogeology that control U mobility in the subsurface. Initial experiments successfully tested the concept that Fe-reducing bacteria such as Geobacter sp. could enzymatically reduce soluble U(VI) to insoluble U(IV) during in situ electron donor amendment (Anderson et al., 2003; Williams et al., 2011). In parallel, in situ desorption tracer tests using bicarbonate amendment demonstrated rate-limited U(VI) desorption (Fox et al., 2012). These results and prior laboratory studies underscored the importance of enzymatic U(VI)-reduction and suggested the ability to combine desorption and bioreduction of U(VI). Here in this paper we report the results of a new field experiment in which bicarbonate-promoted uranium desorption and acetate amendment were combined and compared to an acetate amendment-only experiment in the same experimental plot. Results confirm that bicarbonate amendment to alluvial aquifer sediments desorbs U(VI) and increases the abundance of Ca-uranyl-carbonato complexes. At the same time, the rate of acetate-promoted enzymatic U(VI) reduction was greater in the presence of added bicarbonate in spite of the increased dominance of Ca-uranyl-carbonato aqueous complexes. A model-simulated peak rate of U(VI) reduction was ~3.8 times higher during acetate-bicarbonate treatment than under acetate-only conditions. Lack of consistent differences in microbial community structure between acetate-bicarbonate and acetate-only treatments suggest that a significantly higher rate of U(VI) reduction in the bicarbonate-impacted sediment may be due to a higher intrinsic rate of microbial reduction induced by elevated concentrations of the bicarbonate oxyanion. The findings indicate that bicarbonate amendment may be useful in improving the engineered bioremediation of uranium in aquifers.

58 GEOSCIENCES↗
NASA NTRS1992

Water reclamation technology development for future long range missions

This paper covers the development of computer simulation models of the Vapor Compression Distillation (VCD) process, the Super Critical Water Oxidation (SCWO) process, and two versions of a Vapor Phase Catalytic Ammonia Reduction (VPCAR) process. These process level models have combined into two Integrated Water Reclamation Systems (IWRS). Results from these integrated models, in conjunction with other data sources, have been used to develop a preliminary comparison of the two systems. Also discussed in this paper is the development of a Vapor Phase Catalytic Ammonia Reduction teststand and the development of a new urine analog for use with the teststand and computer models.

Flynn, Michael T.↗
DOE OSTI2022

Establishing the Role of Operating Potential and Mass Transfer in Multicarbon Product Generation for Photoelectrochemical CO 2 Reduction Cells Using a Cu Catalyst

There is increasing interest in the possibility of photoelectrochemical (PEC) reduction of CO 2 to C 2+ products; however, the criteria for maximizing PEC solar-to-C 2+ (STC 2+ ) rates are not well understood. We report here a continuum-scale model of PEC CO 2 reduction (CO 2 R) on Cu in 0.1 M CsHCO 3 and use it to optimize the design and operating conditions for generating C 2+ products. Furthermore, we demonstrate that the potential-dependent product distribution of CO 2 R on Cu requires operating near the potential that maximizes C 2+ generation rates ($V$ id ), unlike PEC water splitting, which desires operation at the maximum photocurrent density. Because of this requirement, the criterion for a high STC 2+ rate includes high-photocurrent semiconductors with photovoltages near $V$ id and low series resistance. The STC 2+ rate in these systems is enhanced by optimal CO 2 transport and exhibits low sensitivity to dirunal solar irradiance variations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2004

Risk-Based Prioritization of Research for Aviation Security Using Logic-Evolved Decision Analysis

The National Aeronautics and Space Administration is developing advanced technologies to reduce terrorist risk for the air transportation system. Decision support tools are needed to help allocate assets to the most promising research. An approach to rank ordering technologies (using logic-evolved decision analysis), with risk reduction as the metric, is presented. The development of a spanning set of scenarios using a logic-gate tree is described. Baseline risk for these scenarios is evaluated with an approximate reasoning model. Illustrative risk and risk reduction results are presented.

Eisenhawer, S. W.↗
DOE OSTI2015

Pathways to Mexico’s climate change mitigation targets: A multi-model analysis

Mexico’s climate policy sets ambitious national greenhouse gas (GHG) emission reduction targets—30% versus a business-as-usual baseline by 2020, 50% versus 2000 by 2050. However, these goals are at odds with recent energy and emission trends in the country. Both energy use and GHG emissions in Mexico have grown substantially over the last two decades. Here, we investigate how Mexico might reverse current trends and reach its mitigation targets by exploring results from energy system and economic models involved in the CLIMACAP-LAMP project. To meet Mexico’s emission reduction targets, all modeling groups agree that decarbonization of electricity is needed, along with changes in the transport sector, either to more efficient vehicles or a combination of more efficient vehicles and lower carbon fuels. These measures reduce GHG emissions as well as emissions of other air pollutants. The models find different energy supply pathways, with some solutions based on renewable energy and others relying on biomass or fossil fuels with carbon capture and storage. The economy-wide costs of deep mitigation could range from 2% to 4% of GDP in 2030, and from 7% to 15% of GDP in 2050. Our results suggest that Mexico has some flexibility in designing deep mitigation strategies, and that technological options could allow Mexico to achieve its emission reduction targets, albeit at a cost to the country.

09 BIOMASS FUELS↗
NASA NTRS1991

Springtime soil moisture, natural climatic variability, and North American drought as simulated by the NCAR Community Climate Model 1

Previous results concerning the role that summertime soil moisture reductions can play in amplifying or maintaining North American droughts are extended to include the role of springtime soil moisture reductions and the role that natural climatic variability, as expressed in soil moisture, can play. General circulation model (GCM) simulations with the NCAR Community Climate Model have been made with initial desert-like soil moisture anomalies imposed on 1 May and on 1 March. The May simulation maintained the imposed anomaly throughout the summer, while in the March simulation the anomaly was ameliorated within one month. Thus, the timing of soil moisture reductions may be crucial. A 10-year model control integration with prescribed sea surface temperatures yielded 1 year with late spring and summer soil moisture values similar to those of the 1 May anomaly simulation. This suggests that occasional widespread North American droughts may be an inherent feature of at least the GCM employed for this study. The results also demonstrate the important role played by moisture transport from the Gulf of Mexico in modulating or ameliorating drought conditions for much of the south-central United States, a topic that requires considerable further investigation.

Oglesby, Robert J.↗
DOE OSTI2019

Accelerating the Deployment of Advanced Energy Communities: The Oakland EcoBlock A Zero Net Energy, Low Water Use Retrofit Neighborhood Demonstration Project

This report describes the design development process and recommendations of a Community-Scale Zero Net Energy Master Plan for a residential block in Oakland, the Oakland EcoBlock. The recommended master plan includes an integrated system of energy efficiency retrofits, a direct current solar/storage/electric vehicle microgrid, alternating/direct current houses, and water efficiency retrofits with rainwater capture. The recommended master plan is projected to be close to zero-net energy (95 percent) for homes, reduce carbon emissions by 65 percent at the block scale (including transportation), and reduce water use 60–70 percent. The integrated system of energy efficiency and a direct current solar/storage/electric vehicle (EV) charging microgrid is the first of its kind at the residential block scale. This breakthrough because the deep energy efficiency retrofit savings free up enough capacity in the solar supply and storage to enable residents to switch from natural gas to electricity for heating and domestic hot water and to provide EV charging for 33 percent of vehicle miles traveled. The savings in household transportation costs are a game changer because when combined with savings in the electric and water utility bills, the total cash flow savings are projected to fund the capital improvements of the proposed systems. This project’s benefits include lower and more predictable utility bills; greater resiliency because the system can operate during outages, and vastly improved indoor air quality by reducing natural gas consumption. The local energy storage reduces peak demand for the utility. California benefits from a model that exceeds the targets for reductions in energy consumption and carbon emissions and the reductions in water use address California’s severe water challenges. The Oakland EcoBlock is a transformative model for accelerating the rapid deployment of advanced energy communities.

decarbonization codes↗
NASA NTRS2012

Integrated Path Differential Absorption Lidar Optimizations Based on Pre-Analyzed Atmospheric Data for ASCENDS Mission Applications

In this paper a modeling method based on data reductions is investigated which includes pre analyzed MERRA atmospheric fields for quantitative estimates of uncertainties introduced in the integrated path differential absorption methods for the sensing of various molecules including CO2. This approach represents the extension of our existing lidar modeling framework previously developed and allows effective on- and offline wavelength optimizations and weighting function analysis to minimize the interference effects such as those due to temperature sensitivity and water vapor absorption. The new simulation methodology is different from the previous implementation in that it allows analysis of atmospheric effects over annual spans and the entire Earth coverage which was achieved due to the data reduction methods employed. The effectiveness of the proposed simulation approach is demonstrated with application to the mixing ratio retrievals for the future ASCENDS mission. Independent analysis of multiple accuracy limiting factors including the temperature, water vapor interferences, and selected system parameters is further used to identify favorable spectral regions as well as wavelength combinations facilitating the reduction in total errors in the retrieved XCO2 values.

Pliutau, Denis↗
DOE OSTI2018

Fe and Ni Dopants Facilitating Ammonia Synthesis on Mn 4 N and Mechanistic Insights from First-Principles Methods

Cyclic step-catalysis enables intermittent, atmospheric ammonia production, and can be integrated with sustainable and renewable energy sources. By employing metal (e.g., Mn) nitride, a nitrogen carrier, the rate-limiting N 2 activation step is bypassed. In this work, molecular-level pathways, describing the reduction of Mn 4 N by dissociatively adsorbed hydrogen, were investigated using periodic density functional theory (DFT). The established mechanism confirmed that Fe and Ni doped in the nitride sublayer and top layer can disturb local electronic structures and be exploited to tune the ammonia production activity. The strength of N–M (M = Mn, Fe, Ni) and H–M bonds both determine the overall reduction thermochemistry. DFT-based modeling further showed that the low concentration of Fe or Ni in the Mn 4 N sublayer facilitates N diffusion by lowering the diffusion energy barrier. Also, these heteroatom dopant species, particularly Ni, decrease the reduction endergonicity, thanks to the strong hydrogen binding with the surface Ni dopant. The Brønsted–Evans–Polanyi relationship and linear scaling relationships have been developed to reveal ammonia evolution kinetic and energetic trends for a series of idealized Fe- and Ni-doped Mn 4 N. Finally, deviations from the linear scaling relationship have been observed for certain doped systems, indicating potentially more complex behaviors of metal nitrides and intriguing promises for greater ammonia synthesis materials design opportunities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2024

Revised estimates of NO 2 reductions during the COVID-19 lockdowns using updated TROPOMI NO 2 retrievals and model simulations

The TROPOspheric Monitoring Instrument (TROPOMI) observed unprecedented declines in NO 2 vertical column densities (VCD) over the world's most densely populated cities during the 2020 COVID-19 lockdowns. These favorable changes in NO 2 air quality were correlated with sharp reductions in traffic volume and economic activity during the lockdowns. In this comprehensive global study, we provide revised estimates of the declines in anthropogenic emissions for 36 megacities using a novel methodology for disentangling the anthropogenic emissions from the meteorological transport and natural variability. We further quantify the uncertainty associated with changes in the a priori profile shape information during the lockdowns due to reduced emissions. Satellite NO 2 retrieval techniques calculate an air mass factor that requires a priori NO 2 profile shape information representative of the local atmosphere. This information, which is typically obtained from a chemical transport model (CTM), was not available for the early studies. This study also accounts for the satellite sampling errors resulting from the selective sampling of non-cloudy scenes during the study period. For our analysis, we used CTM simulations that were generated with and without COVID-impacted emissions. We perform retrievals of tropospheric NO 2 columns with the NASA NO 2 algorithm, and then use observed and simulated data to disentangle the meteorological transport from the contribution due anthropogenic emissions. We found that the meteorological transport was most significant source of variability ranging between −35% and 22% of the change total tropospheric VCD. We also find that not accounting for changes in the a priori NO 2 profile shape information during the lockdowns resulted in systematic retrieval errors that were up to 12% of the estimated decline, and the elimination of cloud contaminated scenes resulted in sampling errors that in general ranged between varied ±15%.

NO2↗
DOE OSTI2018

Effect of Wear on Surface Crack Propagation in Rail–Wheel Wet Contact

The interaction between wear and rolling contact fatigue in wet contact was investigated by means of experiments on a two-disk test bench. Specimens of various railway wheel steels were coupled with specimens of the same rail steel, subjected to rolling and sliding wet contact with varying sliding/rolling ratio. Some tests with a dry rolling–sliding contact phase preceding wet contact were carried out as well (dry–wet tests). The pressurization of the fluid entrapped in the surface cracks was the cause of a rapid and severe damage in the dry–wet tests, due to the nucleation of surface cracks by ratcheting in the dry phase, which subsequently propagate in the wet phase. In the wet tests, the fluid pressurization effect was much mitigated due to the absence of initial surface cracks; the specimens subjected to higher sliding/rolling ratio showed the best performance against rolling contact fatigue, due to the effect of wear in reducing the length of surface cracks. A model for assessing the interaction between wear and rolling contact fatigue was proposed, based on the correction of the classical Paris law for crack propagation by taking into account the effect of wear on crack length reduction. The application of the model to the experimental tests allowed finding a correlation between the model predictions and the occurrence of fatigue failure.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Optimal experimental design for prediction based on push-forward probability measures

Incorporating experimental data is essential for increasing the credibility of simulation-aided decision making and design. This paper presents a method which uses a computational model to guide the optimal acquisition of experimental data to produce data-informed predictions of quantities of interest (QoI). Many strategies for optimal experimental design (OED) select data that maximize some utility that measures the reduction in uncertainty of uncertain model parameters, for example the expected information gain between prior and posterior distributions of these parameters. In this paper, we seek to maximize the expected information gained from the pushforward of an initial (prior) density to the push-forward of the updated (posterior) density through the parameter-to-prediction map. The formulation presented is based upon the solution of a specific class of stochastic inverse problems which seeks a probability density that is consistent with the model and the data in the sense that the push-forward of this density through the parameter-to-observable map matches a target density on the observable data. While this stochastic inverse problem forms the mathematical basis for our approach, we develop a one-step algorithm, focused on push-forward probability measures, that leverages inference-for-prediction to bypass constructing the solution to the stochastic inverse problem. A number of numerical results are presented to demonstrate the utility of this optimal experimental design for prediction and facilitate comparison of our approach with traditional OED.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1993

Long Duration Exposure Facility (LDEF) experiment M0003 meteoroid and debris survey

A survey of the meteoroid and space debris impacts on LDEF experiment M0003 was performed. The purpose of this survey was to document significant impact phenomenology and to obtain impact crater data for comparison to current space debris and micrometeoroid models. The survey consists of the following: photomicrographs of significant impacts in a variety of material types; accurate measurements of impact crater coordinates and dimensions for selected experiment surfaces; and databasing of the crater data for reduction, manipulation, and comparison to models. Large area surfaces that were studied include the experiment power and data system (EPDS) sunshields, environment exposure control canister (EECC) sunshields, and the M0003 signal conditioning unit (SCU) covers. Crater diameters down to 25 microns were measured and cataloged. Both leading (D8) and trailing (D4) edge surfaces were studied and compared. The EPDS sunshields are aluminum panels painted with Chemglaze A-276 white thermal control paint, the EECC sunshields are chromic acid-anodized aluminum, and the SCU covers are aluminum painted with S13GLO white thermal control paint. Typical materials that have documented impacts are metals, glasses and ceramics, composites, polymers, electronic materials, and paints. The results of this survey demonstrate the different response of materials to hypervelocity impacts. Comparison of the survey data to curves derived from the Kessler debris model and the Cour-Palais micrometeoroid model indicates that these models overpredict small impacts (less than 100 micron) and may underpredict large impacts (greater than 1000 micron) while having fair to good agreement for the intermediate impacts. Comparison of the impact distributions among the various surfaces indicates significant variations, which may be a function of material response effects, or in some cases surface roughness. Representative photographs and summary graphs of the impact data are presented.

Meshishnek, M. J.↗
DOE OSTI2019

First study of reionization in tilted flat and untilted non-flat dynamical dark energy inflation models

We examine the effects of dark energy dynamics and spatial curvature on cosmic reionization by studying reionization in tilted spatially flat and untilted non-flat XCDM and $\phi$CDM dynamical dark energy inflation models that best fit the Planck 2015 cosmic microwave background (CMB) anisotropy and a large compilation of non-CMB data. We carry out a detailed statistical study, based on a principal component analysis and a Markov chain Monte Carlo analysis of a compilation of lower-redshift reionization data to estimate the uncertainties in the cosmological model reionization histories. We find that, irrespective of the nature of dark energy, there are significant differences between the reionization histories of the spatially flat and non-flat models. Although both the flat and non-flat models can accurately match the low-redshift ( z ≲ 6) reionization observations, there is a clear discrepancy between high-redshift ( z > 7) Lyman-α emitter data and the predictions from non-flat models. This is solely due to the fact that the non-flat models have a significantly larger electron scattering optical depth, τ el , compared to the flat models, which requires an extended and much earlier reionization scenario supported by more high-redshift ionizing sources in the non-flat models. Non-flat models also require strong redshift evolution in the photon escape fraction, which can become unrealistically high (≳1) at some redshifts. However, τ el is about 0.9-σ lower in the tilted flat ΛCDM model when the new Planck 2018 data are used and this reduction will partially alleviate the tension between the non-flat model predictions and the data.

Astronomy & Astrophysics↗