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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Survival of pathogenic bacteria under nutrient starvation conditions

The survival of opportunistic pathogenic microorganisms in water, under nutrient-limiting conditions, has been investigated in order to ascertain whether human pathogens can survive within a water-distribution system of the kind proposed for the NASA Space Station. Cultures of a strain of pseudomonas aeruginosa and two strains of staphylococcus aureus were incubated at 10, 25, or 37 C, and samples at 1 day, 1 week, 1 month, and six weeks. While neither of the staphylococcus strains tested were detected after 1 week of starvation, the pseudomonas strain can survive in deionized water at all three temperatures.

Boyle, Michael↗
DOE OSTI2022

UV/chlorine advanced oxidation processes for degradation of contaminants in water and wastewater: A comprehensive review

Advanced oxidation processes (AOPs) have recently gained increasing attention as promising alternatives to conventional water and wastewater treatment technologies. As an AOP, there has been a growing interest in UV/chlorine due to its multiple disinfection modes and ability to maintain chlorine residuals in drinking water distribution systems. Compared to the popular UV/H 2 O 2 AOP treatment process, UV/chlorine AOP possesses several advantages including a higher radical production efficiency and a lower power demand. The process has recently been applied for the degradation of a wide range of natural and synthetic organic as well as inorganic compounds including pharmaceutical and personal care products, natural organic matter, herbicides and insecticides, taste and odor, and different types of water and wastewaters. The focus of the present work is to review and evaluate the efficiency of the UV/chlorine process on the oxidation of these pollutants. Here a critical overview is provided of the fundamentals of UV/chlorine, controlling factors of the process performance, and a comparison with other UV-based AOPs. The formation of disinfection by-products (DBPs), one of the concerns associated with UV/chlorine treatment, is discussed and strategies to tackle this obstacle are provided for future studies and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

Olson, William S.↗
DOE OSTI2020

PETSc DMNetwork: A Library for Scalable Network PDE-Based Multiphysics Simulations

We present DMNetwork, a high-level package included in the PETSc library for the simulation of multiphysics phenomena over large-scale networked systems. The library aims at applications that have networked structures such as those in electrical, gas, and water distribution systems. DMNetwork provides data and topology management, parallelization for multiphysics systems over a network, and hierarchical and composable solvers to exploit the problem structure. DMNetwork eases the simulation development cycle by providing the necessary infrastructure through simple abstractions to define and query the network components. This article presents the design of DMNetwork, illustrates its user interface, and demonstrates its ability to solve multiphysics systems, such as an electric circuit, a network of power grid and water subnetworks, and transient hydraulic systems over large networks with more than 2 billion variables on extreme-scale computers using up to 30,000 processors.

extreme-scale computing↗
NASA NTRS2007

NIRSS Upgrades: Final Report

This year we were able to further the NIRSS program by re-writing the data ingest and display code from LabVIEW to C++ and Java. This was leveraged by a University of Colorado Computer Science Department Senior Project. The upgrade made the display more portable and upgradeable. Comparisons with research aircraft flights conducted during AIRS-2 were also done and demonstrate reasonable skill in determining cloud altitudes and liquid water distribution. Improvements can still be made to the cloud and liquid logic. The icing hazard index was not evaluated here since that represents work in progress and needs to be made compatible with the new CIP-Severity algorithm. CIP is the Current Icing Potential product that uses a combination decision tree/fuzzy logic algorithm to combine numerical weather model output with operational sensor data (NEXRAD, GOES, METARs and voice pilot reports) to produce an hourly icing diagnosis across the CONUS. The new severity algorithm seeks to diagnose liquid water production through rising, cooling air, and depletion by ice processes. The information used by CIP is very different from that ingested by NIRSS but some common ground does exist. Additionally, the role of NIRSS and the information it both needs and provides needs to be determined in context of the Next Generation Air Traffic System (NGATS). The Weather Integrated Products Team has a plan for an Initial Operating Capability (IOC) to take place in 2012. NIRSS is not explicitly a part of that IOC but should be considered as a follow-on as part of the development path to a 2025 full capability.

Politovich, Marcia K.↗
NASA NTRS1990

The composition and origin of the C, P, and D asteroids - Water as a tracer of thermal evolution in the outer belt

A telescopic and laboratory investigation of water distribution among low albedo asteroids in the outer belt, using the 3-micron reflectance absorption of molecular H2O and structural OH ions (coincident with the 3-micron spectral signature of meteorite and asteroid hydrated silicates) shows that 66 percent of the C-class asteroids in the sample have hydrated silicate surfaces. In conjunction with the apparently anhydrous P and D surfaces, this pronounced hydration difference between C-class asteroids and the more distant P and D classes points to an original outer belt asteroid composition of anhydrous silicates, water ice, and complex organic material. Early solar-wind induction heating of protoasteroids, declining in intensity with distance from the sun, is conjectured to have produced the observed diminution of hydrated silicate abundance.

Jones, Thomas D.↗
NASA NTRS2005

Models for Water Isotopes Constrained with Data from Crystal Face

During the year covered by this proposal we conducted work on several different topics, as reflected by our publications listed below. One major activity was to work with a group of about 10 scientists from around the country to prepare a science-planning document (Tropical Composition, Cloud and Climate Coupling Experiment (TC4)) that outlined the rationale, locations, strategy to accomplish the goals, and possible payloads for a set of three tropical missions. We also prepared background materials for various NRAs being prepared at NASA Headquarters for missions in Costa Rica, Darwin and Guam. Unfortunately budgetary constraints prevented these missions from moving forward. In conjunction with the group NASA Ames we built a new numerical model for deep convection and have applied that model to simulate the CRYSTAL isotope data. Our goal in particular has been to better understanding how convection distributes water vapor isotopes. CRYSTAL observations of water isotopes are very different from those suggested by previous workers who assumed the isotopes would obey Rayleigh fractionation. The water isotope study has several implications. First it is a check on the realism of the deep convection model. Second, the isotopes are a measure of the precipitation removal in the atmosphere. Hence they provide a constraint on a parameter that is difficult to otherwise measure. Finally it has been suggested that isotopes may be the key to unraveling the water transport into the stratosphere and upper troposphere. Such transport is critical both for the radiation balance and for stratospheric chemistry. Ours is the first model that is able to treat this transport. Our initial results are now in press in Geophys. Res. Lett. Essentially we are able to explain the vertical profiles of isotopes in the tropical tropopause transition layer. We are also able to account for stratospheric humidity ana isotope abundances with this model. The data suggest that isotopes do not provide a clear constraint on the mechanism by which water enters the stratosphere- whether by convection, or by slow ascent. Our work is relevant for the water isotope comparison experiments recently done by NASA. We are conducting numerical experiments related to this project to help understand that data.

Toon, Owen B.↗
DOE OSTI2021

Ripple-Type Control for Enhancing Resilience of Networked Physical Systems

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical infrastructures under unexpected events. Purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physical system and are allowed to communicate with peers over a “hotline” communication network. According to this protocol, agents act on local readings unless their control resources have been depleted, in which case they send a beacon for assistance to peer agents. Our ripple-type scheme triggers communication locally only for the agents with saturated resources and it is proved to converge. Moreover, under a monotonicity assumption on the underlying physical law coupling control outputs to inputs, the devised control is proved to converge to a configuration satisfying safe operational constraints. The assumption is shown to hold for voltage control in electric power systems and pressure control in water distribution networks. Numerical tests corroborate the efficacy of the novel scheme.

distributed control↗
DOE OSTI2021

Ripple-Type Control for Enhancing Resilience of Networked Physical Systems: Preprint

Distributed control agents have been advocated as an effective means for improving the resiliency of our physical in-frastructures under unexpected events. While purely local control has been shown to be insufficient, centralized optimal resource allocation approaches can be slow. In this context, we put forth a hybrid low-communication saturation-driven protocol for the coordination of control agents that are distributed over a physicalsystem and are allowed to communicate with peers over a 'hot-line' communication network. According to this protocol, agents act upon on local readings unless their control resources have been depleted, in which case they send a beacon for assistance to peer agents. Our ripple-type scheme triggers communication locally only for the agents with saturated resources, and is proved to converge. Moreover, under a monotonicity assumption on the underlying physical law coupling control outputs to inputs, the devised control is proved to converge to a configuration satisfying safe operational constraints. The assumption is shown to hold for voltage control in electric power systems and pressure control in water distribution networks. Numerical tests on both networks corroborate the efficacy of the novel scheme.

distributed control↗
DOE OSTI2023

A Decision-Relevant Factor-Fixing Framework: Application to Uncertainty Analysis of a High-Dimensional Water Quality Model

Factor Fixing (FF) is a common method for reducing the number of model parameters to lower computational cost. FF typically starts with distinguishing the insensitive parameters from the sensitive and pursues uncertainty quantification (UQ) on the resulting reduced-order model, fixing each insensitive parameter at a fixed value. There is a need, however, to expand such a common approach to consider the effects of decision choices in the FF-UQ procedure on metrics of interest. Therefore, to guide the use of FF and increase confidence in the resulting dimension-reduced model, we propose a new adaptive framework consisting of four principles: (a) re-parameterize the model first to reduce obvious non-identifiable parameter combinations, (b) focus on decision relevance especially with respect to errors in quantities of interest (QoI), (c) conduct adaptive evaluation and robustness assessment of errors in the QoI across FF choices as sample size increases, and (d) reconsider whether fixing is warranted. The framework is demonstrated on a spatially-distributed water quality model. The error in estimates of QoI caused by FF can be estimated using a Polynomial Chaos Expansion (PCE) surrogate model. Built with 70 model runs, the surrogate is computationally inexpensive to evaluate and can provide global sensitivity indices for free. For the selected catchment, just two factors may provide an acceptably accurate estimate of model uncertainty in the average annual load of Total Suspended Solids (TSS), suggesting that reducing the uncertainty in these two parameters is a priority for future work before undertaking further formal uncertainty quantification.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗
DOE OSTI2022

Hydrological Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science

Hydrologic sciences depend on data monitoring, analyses, and simulations of hydrologic processes to ensure safe, sufficient, and equal water distribution. These hydrologic data come from but are not limited to primary (lab, plot, and field experiments) and secondary sources (remote sensing, UAVs, hydrologic models) that typically follow FAIR Principles (Findable, Accessible, Interoperable, and Reusable: (go-fair.org)). Easy availability of FAIR data has become possible because the hydrology-oriented organizations have pushed the community to increase coordination of the protocols for generating data and sharing model platforms. In addition, networking at all levels has emerged with an invigorated effort to activate community science efforts that complement conventional data collection methods. However, it has become difficult to decipher various complex hydrologic processes with increasing data. Machine learning, a branch of artificial intelligence, provide more accurate and faster alternatives to better understand different hydrological processes. The Integrated, Coordinated, Open, Networked (ICON) framework provides a pathway for water users to include and respect diversity, equity, and inclusivity. In addition, ICONs support the integration of peoples with historically marginalized identities into this professional discipline of water sciences. This article comprises three independent commentaries about the state of ICON principles in hydrology and discusses the opportunities and challenges of adopting them.

(ICON) principles to address↗
NASA NTRS1970

Linear geologic structure and magic rock discrimination as determined from infrared data

Color infrared photographs of the Beartooth Mountains, Montana show the distribution of mafic dikes and amphibolite bodies. Lineaments that cross grassy plateaus can be identified as dikes by the marked constrast between the dark rocks and the red vegetation. Some amphibolite bodies in granitic terrain can also be detected by infrared photography and their contacts can be accurately drawn due to enchanced contrast of the two types of rock in the near infrared. Reflectance measurements made in the field for amphibolite and granite show that the granite is 25% to 50% more reflective in the near infrared than in the visible region. Further enhancement is due to less atmospheric scattering than in the visible region. Thermal infrared images of the Mill Creek, Oklahoma test site provided information on geologic faults and fracture systems not obtainable from photographs. Subtle stripes that cross outcrop and intervening soil areas and which probably record water distribution are also shown on infrared photographs.

Offield, T. W.↗
DOE OSTI2024

Cellulose acetate membranes exhibit exceptional monovalent to divalent cation selectivities

Salt transport properties of cellulose acetate membranes are reported for a series of chloride salts with mono- valent and divalent cations (LiCl, NaCl, MgCl 2 , CaCl 2 ). Measurements include salt permeability and sorption, with diffusivity values calculated from the permeability and sorption results. We report an exceptionally high LiCl/MgCl 2 selectivity of 750:1. Salts with similar valence (LiCl and NaCl; MgCl 2 and CaCl 2 ) have similar transport properties. The high monovalent/divalent selectivity arises from differences in both sorption and diffusion, with a LiCl/MgCl 2 solubility selectivity of about 11 and a diffusivity selectivity of about 70. Atomistic molecular dynamics simulations show that ions tend to reside in isolated clusters of water. Increasing ion charge strengthens ion–water interactions relative to ion–polymer interactions, explaining the reduced sorption of divalent ions. Diffusion of ions through the membrane occurs via hop-like motion between water clusters. Lithium diffuses faster than magnesium due to weaker ion–water coordination for lithium, which allows for greater mobility within water clusters and more frequent hopping. Altogether, our atomistic simulations suggest that the high LiCl/MgCl 2 selectivity is linked to cellulose acetate’s high water/salt selectivity and is a consequence of low water content and relatively uniform water distribution.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding the Effect of Single Atom Cationic Defect Sites in an Al 2 O 3 (012) Surface on Altering Selenate and Sulfate Adsorption: An Ab Initio Study

Adsorption is a promising under-the-sink selenate remediation technique for distributed water systems. Recently it was shown that adsorption induced water network rearrangement control adsorption energetics on the α-Al 2 O 3 (012) surface. Here, we aim to elucidate the relative importance of the water network effects and surface cation identity on controlling selenate and sulfate adsorption energy using density functional theory calculations. Density functional theory (DFT) calculations predicted the adsorption energies of selenate and sulfate on nine transition metal cations (Sc–Cu) and two alkali metal cations (Ga and In) in the α-Al 2 O 3 (012) surface under simulated acidic and neutral pH conditions. We find that the water network effects had a larger impact on the adsorption energy than the cationic identity. However, cation identity secondarily controlled adsorption. Most cations decreased the adsorption energy, weakening the overall performance, the larger Sc and In cations enabled inner-sphere adsorption in acidic conditions because they relaxed outward from the surface, providing more space for adsorption. Additionally, only Ti induced Se selectivity over S by reducing the adsorbing selenate to selenite but not reducing the sulfate. Altogether, this study indicates that tuning water network structure will likely have a larger impact than tuning cation–selenate interactions for increasing adsorbate effectiveness.

Adsorption↗
DOE OSTI2020

A Positive Charge in the Outer Coordination Sphere of an Artificial Enzyme Increases CO 2 Hydrogenation

The protein scaffold around the active site of enzymes is known to influence catalytic activity, but specific scaffold features responsible for favorable influences are often not known. This study focuses on using an artificial metalloenzyme to probe one specific feature of the scaffold, the position of a positive charge in the outer coordination sphere around the active site. Previous work showed that a small molecular complex, [Rh(P Et 2 N glycine P Et 2 )2 ] – , immobilized covalently within a protein scaffold was activated for CO 2 hydrogenation. In this work, using an iterative design where the effect of arginine, histidine, or lysine residues placed in the outer coordination sphere of the catalytic active site were evaluated, we tested the hypothesis that positively charged groups facilitate CO 2 hydrogenation with seven unique constructs. Single-, double-, and triple-point mutations were introduced to directly compare catalytic activity, as monitored by turnover frequencies (TOFs) measured in real time with 1 H NMR spectroscopy, and evaluate related structural and electronic properties. Two of the seven constructs showed a 2- and 3-fold increase relative to the wild type, with overall rates ranging from 0.2 to 0.7 h –1 , and a crystal structure of the fastest of these shows the positive charge positioned next to the active site. A crystal structure of the arginine-containing complex shows that the arginines are positioned near the metal. Molecular dynamics (MD) studies also suggest that the positive charge is oriented next to the active site in the two constructs with faster rates but not in the others and that the positive charge near the active site holds the CO 2 near the metal, all consistent with a positive charge appropriately positioned in the scaffold benefiting catalysis. The MD studies also suggest that changes in the water distribution around the active site may contribute to catalytic activity, while modest structural changes and movement of the complex within the scaffold do not.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On the Existence of Steady-State Solutions to the Equations Governing Fluid Flow in Networks

The steady-state solution of fluid flow in pipeline infrastructure networks driven by junction/node potentials is a crucial ingredient in various decision-support tools for system design and operation. While the nonlinear system is known to have a unique solution (when one exists), the absence of a definite result on the existence of solutions hobbles the development of computational algorithms, for it is not possible to distinguish between algorithm failure and non-existence of a solution. In this letter, we show that for any fluid whose equation of state is a scaled monomial, a unique solution exists for such nonlinear systems if the term solution is interpreted in terms of potentials and flows rather than pressures and flows. However, for gases following the CNGA equation of state, while the question of existence remains open, we construct an alternative system that always has a unique solution and show that the solution to this system is a good approximant of the true solution. Further, the existence result for flow of natural gas in networks also applies to other fluid flow networks such as water distribution networks or networks that transport carbon dioxide in carbon capture and sequestration. Most importantly, our result enables correct diagnosis of algorithmic failure, problem stiffness, and non-convergence in computational algorithms.

42 ENGINEERING↗
DOE OSTI2020

WaterModelsAnalytics.jl

WaterModelsAnalytics.jl is an analytics package for visualizing water distribution networks in Julia.

Stickel, Jonathan↗