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.
Probabilistic modeling and stochastic process investigations to provide measures of quality of performance and reliability for systems engineering - Chebyshev approximation
HYBRID is a modeling toolset to assess the economic viability of Nuclear-Renewable Integrated Energy Systems (N-R IES). The frameworks enabling this toolset are INL’s RAVEN, its CashFlow plugin and the Modelica language. The toolset includes sample RAVEN workflows performing economic assessments. These workflows consist of: generation of stochastic time series and application of probabilistic analysis and optimization algorithms (RAVEN); a library of Modelica models representing the physical behavior of N-R IES; and the CashFlow plugin mapping physical performance to economic performance. The toolset allows assembling existing and new models such as nuclear reactors, renewable energy sources, energy storage, gas turbines, industrial processes, etc. into an N-R IES. The toolset workflows evaluate the dynamics of the N-R IES responding to stochastic conditions (electricity demand, price, etc.) and optimize the dispatch economics as well as N-R IES capacity planning.
Star tracker error signal processor for onboard current satellite attitude control over wide range of gimbal angles
This research program will convert acid pretreated corn stover to sugars at the National Renewable Energy Laboratory (NREL) and then transfer these sugars to Honda R&D and its partner the Green Earth Institute (GEI) for conversion to ethanol via a novel fermentation organism. In phase one, NREL will adapt its pretreatment and saccharification process to the unique attributes of this organism, and Honda R&D/GEI will increase the sugar conversion rate as well as the yield and titer of the resulting ethanol. In later phases, NREL, Honda R&D, and GEI will work together at NREL to optimize and scale-up to pilot-scale the Honda R&D/GEI bioethanol production process. The final stage will be to undertake a pilot-scale test at NREL of the optimized bioethanol conversion process.
We present bhlight, a numerical scheme for solving the equations of general relativistic radiation magnetohydrodynamics using a direct Monte Carlo solution of the frequency-dependent radiative transport equation. bhlight is designed to evolve black hole accretion flows at intermediate accretion rate, in the regime between the classical radiatively efficient disk and the radiatively inefficient accretion flow (RIAF), in which global radiative effects play a sub-dominant but non-negligible role in disk dynamics. We describe the governing equations, numerical method, idiosyncrasies of our implementation, and a suite of test and convergence results. We also describe example applications to radiative Bondi accretion and to a slowly accreting Kerr black hole in axisymmetry.
The {sup 13}C(α,n){sup 16}O reaction is the neutron source of the main component of the s-process. The astrophysical S(E)-factor is dominated by the −3 keV sub-threshold resonance due to the 6.356 MeV level in {sup 17}O. Its contribution is still controversial as extrapolations, e.g., through R-matrix calculations, and indirect techniques, such as the asymptotic normalization coefficient (ANC), yield inconsistent results. Therefore, we have applied the Trojan Horse Method (THM) to the {sup 13}C({sup 6}Li,n{sup 16}O)d reaction to measure its contribution. For the first time, the ANC for the 6.356 MeV level has been deduced through the THM, allowing to attain an unprecedented accuracy. Though a larger ANC for the 6.356 MeV level is measured, our experimental S(E) factor agrees with the most recent extrapolation in the literature in the 140-230 keV energy interval, the accuracy being greatly enhanced thanks to this innovative approach, merging together two well establish indirect techniques, namely, the THM and the ANC.
Combustion process monitoring in rocket engines
The French vitrification of High Level Liquid Waste (HLLW) developed since the beginning of the 1960's led to the successive completion of four industrial vitrification facilities: PIVER facility (1969), Marcoule vitrification facility (1978), and R7 (1989) and T7 (1992) vitrification facilities on La Hague site. R and D has involved containment glass formulation and characterization of glass properties, development of modular technologies specifically tailored to be operated in shielded cells, and development of the vitrification process on full scale prototype. Industrial support has then provided by the R and D team during all phases of commissioning and operation of these industrial facilities. The initial choices of industrial facility design, as well as technologies to enhance flexibility and modularity, allowed an evolution of the vitrification process over time. Maintaining the R and D capabilities on containment glass, process and technology development at full scale size is essential to anticipate treatment of the new effluent and propose innovative industrial technologies. Fueling R and D with industrial feedback ensured the longevity of industrial vitrification facilities and development capabilities for future projects. (authors)
The presented R-matrix formalism could improve evaluations of resolved resonance nuclear cross section data by parameterizing direct reaction processes via an orthonormal channel mixing matrix and doorway state processes. Together, they can parameterize direct-semidirect capture. A formal similarity among the R-, K-, T- matrix formalisms was leveraged to parameterize direct and doorway processes. The advantage of this R-matrix parameterization is that it is easily extensible due to its application of projection operators directly upon the (H-E) on p. 6.
Explore the source record for details and available documents.
Vertical transport by moist sub-grid scale processes such as deep convection is a well-known source of uncertainty in CO2 source/sink inversion. However, a dynamical link between vertical transport, satellite based retrievals of column mole fractions of CO2, and source/sink inversion has not yet been established. By using the same offline transport model with meteorological fields from slightly different data assimilation systems, we examine sensitivity of frontal CO2 transport and retrieved fluxes to different parameterizations of sub-grid vertical transport. We find that frontal transport feeds off background vertical CO2 gradients, which are modulated by sub-grid vertical transport. The implication for source/sink estimation is two-fold. First, CO2 variations contained in moist poleward moving air masses are systematically different from variations in dry equatorward moving air. Moist poleward transport is hidden from orbital sensors on satellites, causing a sampling bias, which leads directly to small but systematic flux retrieval errors in northern mid-latitudes. Second, differences in the representation of moist sub-grid vertical transport in GEOS-4 and GEOS-5 meteorological fields cause differences in vertical gradients of CO2, which leads to systematic differences in moist poleward and dry equatorward CO2 transport and therefore the fraction of CO2 variations hidden in moist air from satellites. As a result, sampling biases are amplified and regional scale flux errors enhanced, most notably in Europe (0.43+/-0.35 PgC /yr). These results, cast from the perspective of moist frontal transport processes, support previous arguments that the vertical gradient of CO2 is a major source of uncertainty in source/sink inversion.
A comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework consists of three major phases: Phase 1—Preliminary raw data sets exploration, including time formatting and combining datasets of different lengths and different time intervals; Phase 2—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme values; and Phase 3—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado) were analyzed. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.The files that are in this data package include one excel file, converted to CSV format (Billy_Barr_raw_qaqc.csv) that contains the raw meteorological data, i.e., input data used for the QA/QC analysis. The second CSV file (Billy_Barr_1hr.csv) is the QA/QC and flagged meteorological data, i.e., output data from the QA/QC analysis. The last file (QAQC_Billy_Barr_2021-03-22.R) is a script written in R that implements the QA/QC and flagging process. The purpose of the CSV data files included in this package is to provide input and output files implemented in the R script.
Combined Algal Processing for the Synthesis of Liquid Oleofuels and Products (CAPSLOC) aims to develop a biorefinery concept that is composition-agnostic and enables economically, environmentally, and socially viable biofuel production by maximizing the value from each fraction. To achieve this, we have employed an iterative approach between R&D and TEA/LCA to establish process targets and quantify improvements in the minimum fuel selling price (MFSP), reduce carbon intensity, and support the state of technology (SOT). We have surveyed various methods for biomass pretreatment and successfully demonstrated pre-pilot scale pretreatment in batch mode. Using techniques such as lipid modification, fermentation, mild oxidative treatment (MOT), and carbonization, we have developed biofuel precursors and a range of value-added co-products. Our project has demonstrated significant improvements in key aspects of algae processing, particularly in pretreatment technologies suitable for variable composition, co-products available from lipid and extracted solid streams, conditioning and fermenting high-protein hydrolysates, and recovering nitrogen (N) and phosphorus (P) nutrients for recycling to cultivation ponds. The success of this project will support the commercialization of a sustainable microalgal biorefinery industry.
The Japanese government is supporting development work implemented jointly by Veolia subsidiaries Kurion Japan, K.K., Veolia Nuclear Solutions (VNS), Inc., and Veolia Nuclear Solutions Federal Services, LLC for treating radioactive waste generated from Fukushima Daiichi Nuclear Power Station (NPS) water treatment using the GeoMelt{sup TM} In-Container Vitrification (ICV){sup TM} technology. The initial work consisted of glass formulation and engineering-scale testing which was completed in 2018, in the frame of an IRID (International Research Institute for Nuclear Decommissioning) program as part of a project subsidized by Japan's Ministry of Economy, Trade and Industry (METI). The Fukushima Daiichi NPS Mid- and Long-Term Road-map requires investigation of methods to stabilize solid wastes (and to immobilize radioisotopes in the wastes) generated as a result of emergency response and decommissioning activities. Cooling water treatment has resulted in a significant amount of solid and slurry secondary wastes (mostly adsorbents and ion-exchange materials) which will require processing at some point. GeoMelt{sup R} ICV{sup TM} is a joule-heated melter technology which uses a refractory-lined single-use container combining the melter and disposal container. There is no pouring required nor concerns with refractory corrosion which allows the process to accommodate a wide range of waste chemistries and high waste loadings. The testing described here consisted of three engineering-scale melts, each processing between 212 kg and 240 kg of waste simulants, glass formers, and non-radioactive cesium (Cs) and strontium (Sr) tracers. Continuous isokinetic stack sampling of off-gas emissions was performed for each test in order to calculate Cs and Sr retention in the glass wasteform. Single-pass retention of Cs in the final glass wasteform ranged from 91.46 to 99.30%, and single-pass retention of Sr ranged from 99.76 to 100%. Planned particulate recycle will increase these retention levels. Melt 1 processed a mixture of KUR-EH (a zeolite-based ion-exchange material), simulated Advanced Liquid Processing System (ALPS) Carbonate and Iron Slurries, and glass additives. Melt 2 processed a mixture of KUR-EH, KUR-TSG (a titanate-based adsorbent), and glass additives. Melt 3 processed a mixture of KUR-EH, simulated barium sulfate/iron ferrocyanide sludge (AREVA sludge), and glass additives. Waste loadings for these melts ranged from 70 weight percent (wt%) to 82 wt%. Vitrification produces a waste form much denser than the stored water treatment secondary waste wastes, resulting in significant volume reduction. Volume reductions for the three tests ranged from 74 to 79 vol%. Vitrification produces a chemically durable wasteform. Pacific Northwest National Laboratory (PNNL) tested three glass samples from each engineering-scale melt) by the Materials Characterization Center 1 (MCC-1) test, an international standard leach test of the chemical durability of nuclear waste glasses. PNNL also obtained one U.S. reference glass (EA Glass) and two Japan reference glasses P0798) and tested these under the same MCC-1 conditions (90 deg. C, 10 m-1, DIW, and 7, 14, 28-day) as the GeoMelt{sup R} ICV{sup TM} glasses. The GeoMelt{sup R} ICV{sup TM} glasses exhibited lower total normalized releases and 14- to 28-day normalized release rates than the three reference glasses. These results suggest that the GeoMelt{sup R} ICV{sup TM} glasses have durabilities on par with high-level waste glasses under standard test conditions. Post-melt process sampling and analysis indicated no Cs migration into the melter refractory materials and very little deposition of Cs or Sr onto the melter hood or off-gas piping internals. The results of the testing indicated good Cs retention in the glass, high volume reduction and waste loadings, and excellent chemical durability. These factors are important to minimize treatment costs and to protect workers and the environment. (authors)
The present work analyzes the various conditions in which there can be a bouncing universe solution in f(R) gravity. In the article an interesting method, to analyze the bouncing FRW solutions in a spatially flat universe using f(R) gravity models using an effective Einstein frame description of the process, is presented. The analysis shows that a cosmological bounce in the f(R) theory need not be described by an equivalent bounce in the Einstein frame description of the process where actually there may be no bounce at all. Nevertheless the Einstein frame description of the bouncing phenomena turns out to be immensely important as the dynamics of the bounce becomes amenable to logic based on general relativistic intuition. The theory of scalar cosmological perturbations in the bouncing universe models in f(R) theories has also been worked out in the Einstein frame.
Not Available
In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.