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NASA NTRS2013

Unique Testing Capabilities of the NASA Langley Transonic Dynamics Tunnel, an Exercise in Aeroelastic Scaling

NASA Langley Research Center's Transonic Dynamics Tunnel (TDT) is the world's most capable aeroelastic test facility. Its large size, transonic speed range, variable pressure capability, and use of either air or R-134a heavy gas as a test medium enable unparalleled manipulation of flow-dependent scaling quantities. Matching these scaling quantities enables dynamic similitude of a full-scale vehicle with a sub-scale model, a requirement for proper characterization of any dynamic phenomenon, and many static elastic phenomena. Select scaling parameters are presented in order to quantify the scaling advantages of TDT and the consequence of testing in other facilities. In addition to dynamic testing, the TDT is uniquely well-suited for high risk testing or for those tests that require unusual model mount or support systems. Examples of recently conducted dynamic tests requiring unusual model support are presented. In addition to its unique dynamic test capabilities, the TDT is also evaluated in its capability to conduct aerodynamic performance tests as a result of its flow quality. Results of flow quality studies and a comparison to a many other transonic facilities are presented. Finally, the ability of the TDT to support future NASA research thrusts and likely vehicle designs is discussed.

Ivanco, Thomas G.↗

NASA NTRS2015

Optimization of a Wcl6 CVD System to Coat UO2 Powder with Tungsten

In order to achieve deep space exploration via Nuclear Thermal Propulsion (NTP), Marshall Space Flight Center (MSFC) is developing W-UO2 CERMET fuel elements, with focus on fabrication, testing, and process optimization. A risk of fuel loss is present due to the CTE mismatch between tungsten and UO2 in the W-60vol%UO2 fuel element, leading to high thermal stresses. This fuel loss can be reduced by coating the spherical UO2 particles with tungsten via H2/WCl6 reduction in a fluidized bed CVD system. Since the latest incarnation of the inverted reactor was completed, various minor modifications to the system design were completed, including an inverted frit sublimer. In order to optimize the parameters to achieve the desired tungsten coating thickness, a number of trials using surrogate HfO2 powder were performed. The furnace temperature was varied between 930 C and 1000degC, and the sublimer temperature was varied between 140 C and 200 C. Each trial lasted 73-82 minutes, with one lasting 205 minutes. A total of 13 trials were performed over the course of three months, two of which were re-coatings of previous trials. The powder samples were weighed before and after coating to roughly determine mass gain, and Scanning Electron Microscope (SEM) data was also obtained. Initial mass results indicated that the rate of layer deposition was lower than desired in all of the trials. SEM confirmed that while a uniform coating was obtained, the average coating thickness was 9.1% of the goal. The two re-coating trials did increase the thickness of the tungsten layer, but only to an average 14.3% of the goal. Therefore, the number of CVD runs required to fully coat one batch of material with the current configuration is not feasible for high production rates. Therefore, the system will be modified to operate with a negative pressure environment. This will allow for better gas mixing and more efficient heating of the substrate material, yielding greater tungsten coating per trial.

Belancik, Grace A.↗

NASA NTRS2016

Phase-Retrieval Uncertainty Estimation and Algorithm Comparison for the JWST-ISIM Test Campaign

Phase retrieval, the process of determining the exitpupil wavefront of an optical instrument from image-plane intensity measurements, is the baseline methodology for characterizing the wavefront for the suite of science instruments (SIs) in the Integrated Science Instrument Module (ISIM) for the James Webb Space Telescope (JWST). JWST is a large, infrared space telescope with a 6.5-meter diameter primary mirror. JWST is currently NASA's flagship mission and will be the premier space observatory of the next decade. ISIM contains four optical benches with nine unique instruments, including redundancies. ISIM was characterized at the Goddard Space Flight Center (GSFC) in Greenbelt, MD in a series of cryogenic vacuum tests using a telescope simulator. During these tests, phase-retrieval algorithms were used to characterize the instruments. The objective of this paper is to describe the Monte-Carlo simulations that were used to establish uncertainties (i.e., error bars) for the wavefronts of the various instruments in ISIM. Multiple retrieval algorithms were used in the analysis of ISIM phase-retrieval focus-sweep data, including an iterativetransform algorithm and a nonlinear optimization algorithm. These algorithms emphasize the recovery of numerous optical parameters, including low-order wavefront composition described by Zernike polynomial terms and high-order wavefront described by a point-by-point map, location of instrument best focus, focal ratio, exit-pupil amplitude, the morphology of any extended object, and optical jitter. The secondary objective of this paper is to report on the relative accuracies of these algorithms for the ISIM instrument tests, and a comparison of their computational complexity and their performance on central and graphical processing unit clusters. From a phase-retrieval perspective, the ISIM test campaign includes a variety of source illumination bandwidths, various image-plane sampling criteria above and below the Nyquist- Shannon critical sampling value, various extended object sizes, and several other impactful effects.

Design Analysis↗

NASA NTRS2017

The Value of Data and Metadata Standardization for Interoperability in Giovanni Or: Why Your Product's Metadata Causes Us Headaches!

Giovanni is a data exploration and visualization tool at the NASA Goddard Earth Sciences Data Information Services Center (GES DISC). It has been around in one form or another for more than 15 years. Giovanni calculates simple statistics and produces 22 different visualizations for more than 1600 geophysical parameters from more than 90 satellite and model products. Giovanni relies on external data format standards to ensure interoperability, including the NetCDF CF Metadata Conventions. Unfortunately, these standards were insufficient to make Giovanni's internal data representation truly simple to use. Finding and working with dimensions can be convoluted with the CF Conventions. Furthermore, the CF Conventions are silent on machine-friendly descriptive metadata such as the parameter's source product and product version. In order to simplify analyzing disparate earth science data parameters in a unified way, we developed Giovanni's internal standard. First, the format standardizes parameter dimensions and variables so they can be easily found. Second, the format adds all the machine-friendly metadata Giovanni needs to present our parameters to users in a consistent and clear manner. At a glance, users can grasp all the pertinent information about parameters both during parameter selection and after visualization.

interoperability↗

NASA NTRS1994

Optical and Electrical Properties of Reactively Sputtered TiN, ZrN, and HfN Thin Films

Thin films of titanium, zirconium, and hafnium nitride are prepared by DC magnetron reactive sputtering at room temperature on fused silica, optical glass, and silicon substrates. Deposition parameters are investigated in order to obtain stoichiometric films. The optical and electrical properties of the films as a function of nitrogen partial pressure are determined. The results show that an inverse correlation exists between the optical reflectance and the electrical resistivity of the films. Ellipsometer data for all three films show that their refractive index in the visible spectrum is decreased by increasing the film thickness while the extinction coefficient is unchanged. Thin films of TiN have the lowest room temperature resistivity relative to ZrN and HfN thin films.

Reactive↗

NASA NTRS2020

Streaming Instability with Multiple Dust Species – I. Favourable Conditions for the Linear Growth

A recent study suggests that the streaming instability, one of the leading mechanisms for driving the formation of planetesimals, may not be as efficient as previously thought. Under some disc conditions, the growth time-scale of the instability can be longer than the disc lifetime when multiple dust species are considered. To further explore this finding, we use both linear analysis and direct numerical simulations with gas fluid and dust particles tomutually validate and study the unstablemodes of the instability in more detail.We extend the previously studied parameter space by one order of magnitude in both the range of the dust-size distribution [Ts, min, Ts, max] and the total solid-to-gas mass ratio ε and introduce a third dimension with the slope q of the size distribution. We find that the fast-growth regime and the slow-growth regime are distinctly separated in the ε–Ts, max space, while this boundary is not appreciably sensitive to q or Ts, min.With a wide range of dust sizes present in the disc (e.g. Ts, min 10−3), the growth rate in the slow-growth regime decreases as more dust species are considered.With a narrow range of dust sizes (e.g. Ts, max/Ts, min = 5), on the other hand, the growth rate in most of the ε–Ts, max space is converged with increasing dust species, but the fast and the slow growth regimes remain clearly separated. Moreover, it is not necessary that the largest dust species dominate the growth of the unstable modes, and the smaller dust species can affect the growth rate in a complicated way. In any case, we find that the fast-growth regime is bounded by ε 1 or Ts, max 1, which may represent the favourable conditions for planetesimal formation.

Zhaohuan Zhu↗

NASA NTRS2019

Isotopologue Consistency of Semi-Empirically Computed InfraRed Line Lists and Further Improvement for Rare Isotopologues: CO2 and SO2 Case Studies.

The semi-empirical molecular rovibrational IR line lists, such as ExoMol, TheoReTs, and Ames, combine the experimental accuracy and theoretical power to reach better than 0.1 cm-1 accuracy for line positions and better than 80-90% agreement for line intensities. The quality of these existing semi-empirical IR lists allows further improvements of intensity and line positions for those unobserved minor isotopologues. This paper presents our new BTRHE (Best Theory + Reliable High-resolution Experiment) strategy implementation. For line intensity, the isotopologue consistency and the patterns of mass dependence in the Ames-296K SO2 and CO2 IR lists are quantitatively presented along the mass-inverse coordinates. The consistency and patterns are better than those in existing experimental data. The methodology proposed here can be used to identify inconsistencies, outliers, and mistakes in intensities, and help improve Effective Dipole Model (EDM) and molecular IR databases. We call for an experimental study on the 50006 and 60007 bands of CO2 628. For line position predictions, a simple approach combining the variational IR line lists with Effective Hamiltonian (EH) model may refine the effective rotational constants A0/B0/C0 and quartic centrifugal distortion constants of minor isotopologues. The prediction accuracy may be improved by two orders of magnitude, i.e. reaching 0-5 MHz prediction accuracy in the range of J<20-30, Ka<10-20, and 0.01-0.02 MHz accuracy for A0/B0/C0. Several important factors have been systematically investigated and discussed, e.g. convergence, uncertainties, higher order terms, fixing EH parameters, mass coordinates, etc. Amicrowave (MW) line set consisting of 644,636 strong transitions for all 30 isotopologues and corresponding refined EH(Ames) parameters are reported in the supplementary material. This approach may be easily extended to rovibrational bands, hot bands, and other molecular systems.

Xinchuan Huang↗

NASA NTRS2023

Plasma Activated Water: A Technology for Acid Generation and Space Crop Production

As humanity returns to the moon and onward to Mars, sustainable space travel becomes essential for cost and independence from Earth. Astronaut activities in low Earth orbit resupply consumable materials and can require alternative technologies if transportation of chemicals is deemed hazardous. Plasma technology and applications are able to generate commodities that assist in achieving Earth independence. Plasma interaction with water generates acid in-situ using on-board resources of electricity and breathable air without the need for large infrastructure. At Kennedy Space Center, researchers have shown that plasma is able to produce nitric acid, and therefore nitrates, in a plant-usable form in water. In this report, the team presents results on acid generation in g/kW-hr as well as provides results on plasma activated water for plant growth assistance. Plasma was generated utilizing DC, AC, and pulsed power supplies in order to determine optimizing parameters for generation of this useful commodity.

Plasma↗

NASA NTRSDate not supplied

Mass Spectrometer Observing Lunar Operations (MSoLo)

Introduction: In 2019, the National Aeronautics and Space Administration (NASA) announced that it would seek to have humans return to the moon by 2024 in the hopes of establishing a more sustainable lunar presence by 2028. This goal comes with many challenges, one of upmost importance will be to utilize resources that can be found on the moon. Water, which has been identified in the lunar Polar Regions, will be a key resource for in-situ resource utilization (ISRU), as it is capable of being processed for vehicular fuel, as well as life support systems materials such as oxygen. Upcoming Commercial Lunar Payload Services (CLPS) missions will be critical for these resource assessments. Methods: A modified commercial off-the-shelf (COTS) mass spectrometer developed at Kennedy Space Center known as MSolo, consisting of a quadrupole mass filter and space rated electronics undergoes testing and modifications in order to study operational parameters to unconventional approaches needed in flight situations. In general, MSolo operates in the 0-100 m/z range with the ability to detect with a faraday cup (FC) or an electron multiplier (EM) for enhanced detection. A crossbeam (XB) ionization source is used. Preliminary Data: Prior to construction, little information was available on how the MSolo system would perform at lunar like environments, factors such as temperatures (possible fluctuations from 70 to -45 °C), vibrations from launch and their side effects, the general ability to operate while the entire system (hardware and electronic components) were in a vacuum environment, were factors that while know to flight instruments, were something new to a modified COTS system. As components start to warm up, temperature becomes a key factor (ie. heat can no longer escape the electronics as no atmosphere is present), therefore it becomes crucial to find new ways to maintain stable signals and keep the instrument tuned. Calibration itself becomes an important parameter that needs to be performed while maintaining all flight like characteristics. Even the structure itself of MSolo’s sensor needed to be changed to survive the verification parameters needed to be approved for flight. Most important, all the modifications made to the COTS system have to keep the instrument working at the same specifications of the standard commercial systems. Novel Aspect: Results gathered provide key parameters that will assist to the unconventional mass spectrometry approaches of the upcoming CLPS missions to which MSolo has been selected to.

MSolo↗

NASA NTRSDate not supplied

Plasma Activated Water: A Technology for Acid Generation and Space Crop Production

Plasma↗

NASA NTRS2023

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗

DOE OSTI2021

Economic and Environmental Assessment of Biological Conversions of Agile BioFoundry (ABF) Bio-Derived Chemicals

Bio-derived chemicals are an essential part of the growing bioeconomy. They possess the potential to boost a new domestic bioproduct industry, improve the sustainability of integrated biomanufacturing, and reduce U.S. dependence on fossil energy. The Agile BioFoundry (ABF) consortium, a Department of Energy (DOE)-sponsored collaboration, is investigating biobased pathways to produce advantaged products including advanced biofuels, fuel intermediates, and bioproducts. ABF is integrating advanced computational tools for biological engineering, process design and data analysis, and economic/sustainability modeling tools into a comprehensive and dynamic platform for biomanufacturing of microbes and using them to produce key metabolic intermediates or beachhead molecules which may be derivatized into several distinct bioproducts of industrial interest. In this presentation, we first discuss a methodology to select a single exemplar product molecule to represent each beachhead pathway based on similarities with other end-molecule options (yields/titers/rates, fermentation operation mode, oxygen requirements, general separations challenges, etc.), in order to maintain a reasonable number of cases for rigorous process simulation. We then use techno-economic analysis (TEA) and life-cycle analysis (LCA) to highlight sensitivities and trends around economic performance and environmental footprint, reflecting examples for two selected ABF technology pathways to bio-derived chemicals: 1) adipic acid production via muconic acid fermentation from mixed sugars with Pseudomonas putida and 2) cineole via geranyl diphosphate with Rhodosporidium toruloides. We present multi-variable scan plots highlighting key drivers on costs and greenhouse gas emissions in order to identify the parameter space in which each pathway could ultimately achieve economic and environmental sustainability meeting or exceeding commodity product benchmarks, thus prioritizing future R&D focus areas.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

ZEM: Integrated Framework for Real-Time Data and Model Analyses for Robust Environmental Management Decision Making - 16438

Typically environmental management (EM) problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly analysis, assimilation and integration into a series of models with different complexity for various types of model-based analyses. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions). To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian-Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is predominantly coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org) and incorporates the MADS computational tools (Model Analysis and Decision Support; http://mads.lanl.gov). We demonstrate the application of ZEM for data and model analyses at the LANL Chromium site. The ZEM framework will be released as open-source code and can be applied to any environmental management site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Consistency relation and non-Gaussianity in a Galileon inflation

We study a particular Galileon inflation in the light of Planck2015 observational data in order to constraint the model parameter space. We study the spectrum of the primordial modes of the density perturbations by expanding the action up to the second order in perturbations. Then we pursue by expanding the action up to the third order and find the three point correlation functions to find the amplitude of the non-Gaussianity of the primordial perturbations in this setup. We study the amplitude of the non-Gaussianity both in equilateral and orthogonal configurations and test the model with recent observational data. Our analysis shows that for some ranges of the non-minimal coupling parameter, the model is consistent with observation and it is also possible to have large non-Gaussianity which would be observable by future improvements in experiments. Moreover, we obtain the tilt of the tensor power spectrum and test the standard inflationary consistency relation ( r = −8 n {sub T} ) against the latest bounds from the Planck2015 dataset. We find a slight deviation from the standard consistency relation in this setup. Nevertheless, such a deviation seems not to be sufficiently remarkable to be detected confidently.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

An improved iterative HDG approach for partial differential equations

Here we propose and analyze an iterative high-order hybridized discontinuous Galerkin (iHDG) discretization for linear partial differential equations. We improve our previous work [45] in several directions: 1) the improved iHDG approach converges in a finite number of iterations for the scalar transport equation; 2) it is unconditionally convergent for both the linearized shallow water system and the convection–diffusion equation; 3) it has improved stability and convergence rates; 4) we uncover a relationship between the number of iterations and time stepsize, solution order, meshsize and the equation parameters. This allows us to choose the time stepsize such that the number of iterations is approximately independent of the solution order and the meshsize; and 5) we provide both strong and weak scalings of the improved iHDG approach up to 16,384 cores. A connection between iHDG and time integration methods such as parareal and implicit/explicit methods are discussed. Extensive numerical results for linear (and nonlinear) PDEs are presented to verify the theoretical findings.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Dynamics of modulated beams in spectral domain

General formalism for describing dynamics of modulated beams along linear beamlines is developed. We describe modulated beams with spectral distribution function which represents Fourier transform of the conventional beam distribution function in the 6-dimensional phase space. The introduced spectral distribution function is localized in some region of the spectral domain for nearly monochromatic modulations. It can be characterized with a small number of typical parameters such as the lowest order moments of the spectral distribution. We study evolution of the modulated beams in linear beamlines and find that characteristic spectral parameters transform linearly. The developed approach significantly simplifies analysis of various schemes proposed for seeding X-ray free electron lasers. We use this approach to study several recently proposed schemes and find the bandwidth of the output bunching in each case.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Improving superconductivity in BaFe 2 As 2 -based crystals by cobalt clustering and electronic uniformity

Quantum materials such as antiferromagnets or superconductors are complex in that chemical, electronic, and spin phenomena at atomic scales can manifest in their collective properties. Although there are some clues for designing such materials, they remain mainly unpredictable. In this work, we find that enhancement of transition temperatures in BaFe 2 As 2 -based crystals are caused by removing local-lattice strain and electronic-structure disorder by thermal annealing. While annealing improves Neel-ordering temperature in BaFe 2 As 2 crystal (T N =132K to 136K) by improving in-plane electronic defects and reducing overall a-lattice parameter, it increases superconducting-ordering temperature in optimally cobalt-doped BaFe 2 As 2 crystal (T c =23 to 25K) by precipitating-out the cobalt dopants and giving larger overall a-lattice parameter. And while annealing improves local chemical and electronic uniformity resulting in higher T N in the parent, it also promotes nanoscale phase separation in the superconductor resulting in lower disparity and strong superconducting band gaps in the dominant crystal regions, which lead to both higher overall T c and critical-current-density, J c

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Kinetic corrections from analytic non-Maxwellian distribution functions in magnetized plasmas

In magnetized plasma physics, almost all developed analytic theories assume a Maxwellian distribution function (MDF) and in some cases small deviations are described using the perturbation theory. The deviations with respect to the Maxwellian equilibrium, called kinetic effects, are required to be taken into account especially for fusion reactor plasmas. Generally, because the perturbation theory is not consistent with observed steady-state non-Maxwellians, these kinetic effects are numerically evaluated by very central processing unit (CPU)-expensive codes, avoiding the analytic complexity of velocity phase space integrals. We develop here a new method based on analytic non-Maxwellian distribution functions constructed from non-orthogonal basis sets in order to (i) use as few parameters as possible, (ii) increase the efficiency to model numerical and experimental non-Maxwellians, (iii) help to understand unsolved problems such as diagnostics discrepancies from the physical interpretation of the parameters, and (iv) obtain analytic corrections due to kinetic effects given by a small number of terms and removing the numerical error of the evaluation of velocity phase space integrals. This work does not attempt to derive new physical effects even if it could be possible to discover one from the better understandings of some unsolved problems, but here we focus on the analytic prediction of kinetic corrections from analytic non-Maxwellians. As applications, examples of analytic kinetic corrections are shown for the secondary electron emission, the Langmuir probe characteristic curve, and the entropy. This is done by using three analytic representations of the distribution function: the Kappa distribution function, the bi-modal or a new interpreted non-Maxwellian distribution function (INMDF). The existence of INMDFs is proved by new understandings of the experimental discrepancy of the measured electron temperature between two diagnostics in JET. As main results, it is shown that (i) the empirical formula for the secondary electron emission is not consistent with a MDF due to the presence of super-thermal particles, (ii) the super-thermal particles can replace a diffusion parameter in the Langmuir probe current formula, and (iii) the entropy can explicitly decrease in presence of sources only for the introduced INMDF without violating the second law of thermodynamics. Moreover, the first order entropy of an infinite number of super-thermal tails stays the same as the entropy of a MDF. The latter demystifies the Maxwell's demon by statistically describing non-isolated systems.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗