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NASA NTRS2016

Satellite-Surface Perspectives of Air Quality and Aerosol-Cloud Effects on the Environment: An Overview of 7-SEAS BASELInE

The objectives of 7-SEASBASELInE (Seven SouthEast Asian Studies Biomass-burning Aerosols and Stratocumulus Environment: Lifecycles and Interactions Experiment) campaigns in spring 2013-2015 were to synergize measurements from uniquely distributed ground-based networks (e.g., AERONET (AErosol RObotic NETwork)), MPLNET ( NASA Micro-Pulse Lidar Network)) and sophisticated platforms (e.g.,SMARTLabs (Surface-based Mobile Atmospheric Research and Testbed Laboratories), regional contributing instruments), along with satellite observations retrievals and regional atmospheric transport chemical models to establish a critically needed database, and to advance our understanding of biomass-burning aerosols and trace gases in Southeast Asia (SEA). We present a satellite-surface perspective of 7-SEASBASELInE and highlight scientific findings concerning: (1) regional meteorology of moisture fields conducive to the production and maintenance of low-level stratiform clouds over land; (2) atmospheric composition in a biomass-burning environment, particularly tracers-markers to serve as important indicators for assessing the state and evolution of atmospheric constituents; (3) applications of remote sensing to air quality and impact on radiative energetics, examining the effect of diurnal variability of boundary-layer height on aerosol loading; (4) aerosol hygroscopicity and ground-based cloud radar measurements in aerosol-cloud processes by advanced cloud ensemble models; and (5) implications of air quality, in terms of toxicity of nanoparticles and trace gases, to human health. This volume is the third 7-SEAS special issue (after Atmospheric Research, vol. 122, 2013; and Atmospheric Environment, vol. 78, 2013) and includes 27 papers published, with emphasis on air quality and aerosol-cloud effects on the environment. BASELInE observations of stratiform clouds over SEA are unique, such clouds are embedded in a heavy aerosol-laden environment and feature characteristically greater stability over land than over ocean, with minimal radar surface clutter at a high vertical spatial resolution. To facilitate an improved understanding of regional aerosol-cloud effects, we envision that future BASELInE-like measurement modeling needs fall into two categories: (1) efficient yet critical in-situ profiling of the boundary layer for validating remote-sensing retrievals and for initializing regional transport chemical and cloud ensemble models; and (2) fully utilizing the high observing frequencies of geostationary satellites for resolving the diurnal cycle of the boundary layerheight as it affects the loading of biomass-burning aerosols, air quality and radiative energetics.

AERONET↗

NASA NTRSDate not supplied

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗

NASA NTRS1997

An Adaptive Flow Solver for Air-Borne Vehicles Undergoing Time-Dependent Motions/Deformations

This report describes a concurrent Euler flow solver for flows around complex 3-D bodies. The solver is based on a cell-centered finite volume methodology on 3-D unstructured tetrahedral grids. In this algorithm, spatial discretization for the inviscid convective term is accomplished using an upwind scheme. A localized reconstruction is done for flow variables which is second order accurate. Evolution in time is accomplished using an explicit three-stage Runge-Kutta method which has second order temporal accuracy. This is adapted for concurrent execution using another proven methodology based on concurrent graph abstraction. This solver operates on heterogeneous network architectures. These architectures may include a broad variety of UNIX workstations and PCs running Windows NT, symmetric multiprocessors and distributed-memory multi-computers. The unstructured grid is generated using commercial grid generation tools. The grid is automatically partitioned using a concurrent algorithm based on heat diffusion. This results in memory requirements that are inversely proportional to the number of processors. The solver uses automatic granularity control and resource management techniques both to balance load and communication requirements, and deal with differing memory constraints. These ideas are again based on heat diffusion. Results are subsequently combined for visualization and analysis using commercial CFD tools. Flow simulation results are demonstrated for a constant section wing at subsonic, transonic, and a supersonic case. These results are compared with experimental data and numerical results of other researchers. Performance results are under way for a variety of network topologies.

Singh, Jatinder↗

NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

air traffic management↗

NASA NTRS1993

Interhemispheric comparison of the development of the stratospheric polar vortex during fall - A 3-dimensional perspective for 1991-1992

The development of the stratospheric polar vortex during fall and early winter in the Northern Hemisphere (NH) during 1991-1992, and the Southern Hemisphere (SH) during 1992 is examined using National Meteorological Center data. Compared to the NH, the polar vortex in the SH developed with less variability on short time scales, deepened more rapidly and continued to expand well into winter. Daily minimum temperatures in the lower stratosphere were lowest at equivalent seasonal dates in both hemispheres, but values below the condensation temperatures of polar stratospheric clouds occurred earlier, persisted much longer, and occupied a larger volume of air in the SH. These interhemispheric meteorological differences can account for some of the key features of the chlorine monoxide distributions observed by the Microwave Limb Sounder on the Upper Atmosphere Research Satellite.

Manney, Gloria L.↗

DOE OSTI2024

Using Machine Learning to Predict Cloud Turbulent Entrainment–Mixing Processes

Different turbulent entrainment–mixing mechanisms between clouds and environment are essential to cloud–related processes; however, accurate representation of entrainment–mixing in weather/climate models still poses a challenge. This study exploits the use of machine learning (ML) to address this challenge. Four ML (Light Gradient Boosting Machine [LGB], eXtreme Gradient Boosting, Random Forest, and Support Vector Regression) are examined and compared. It is found that LGB performs best, and thus is selected to understand the impact of entrainment–mixing on microphysics using simulation data from Explicit Mixing Parcel Model. Compared with traditional parameterizations, the trained LGB provides more accurate microphysical properties (number concentration and cloud droplet spectral dispersion). The partial dependences of predicted microphysics on features exhibit a strong alignment with physical mechanisms and expectations, as determined by the interpreting method, thus overcoming the limitations of the “black box” scheme. The underlying mechanisms are that the smaller number concentration and larger spectral dispersion correspond to more inhomogeneous entrainment–mixing. Specifically, number concentration after entrainment–mixing is positively correlated with adiabatic number concentration and liquid water content affected by entrainment–mixing, and inversely correlated with adiabatic volume mean radius. Spectral dispersion after entrainment–mixing is negatively correlated with liquid water content affected by entrainment–mixing, turbulent dissipation rate and relative humidity of entrained air. Sensitivity analysis further suggests that number concentration is mainly determined by cloud microphysical properties whereas spectral dispersion is influenced by both cloud microphysical properties and environmental variables. The results indicate that the LGB scheme has the potential to enhance the representation of entrainment–mixing in weather/climate models.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Preliminary Development of Heat Transfer Model-Based Control Algorithms of Liquid Sodium Purification System: Advanced Sensors and Instrumentation Advanced Controls

Monitoring the operation of sodium purification system is essential for efficient operation of sodium fast reactors. In this work, a heat transfer model has been developed for monitoring the plugging meter and cold trap systems at the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The model of the purification system was developed by treating the respective aspects of the cold trap purification loop and plugging meter diagnostic loop as two separate control volumes using information from the METL piping and instrumentation diagram (P&ID). A model predictive controller was designed using first order differential equations with the specified boundary conditions. The system behavior was studied with a tuned optimized procedure using the internal cold trap temperature and plugging meter outlet temperature as control variables, and the air blower temperature as an independent variable respectively. Results of computer simulations obtained in this study compared favorably with experimental data showing very good reference tracking response with negligible overshoot as both plugging meter and cold trap physical models approach the setpoint.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2005

Measurement of hydraulic characteristics of porous media used to grow plants in microgravity

Understanding the effect of gravity on hydraulic properties of plant growth medium is essential for growing plants in space. The suitability of existing models to simulate hydraulic properties of porous medium is uncertain due to limited understanding of fundamental mechanisms controlling water and air transport in microgravity. The objective of this research was to characterize saturated and unsaturated hydraulic conductivity (K) of two particle-size distributions of baked ceramic aggregate using direct measurement techniques compatible with microgravity. Steady state (Method A) and instantaneous profile measurement (Method B) methods for K were used in a single experimental unit with horizontal flow through thin sections of porous medium providing an earth-based analog to microgravity. Comparison between methods was conducted using a crossover experimental design compatible with limited resources of space flight. Satiated (natural saturation) K ranged from 0.09 to 0.12 cm s-1 and 0.5 to >1 cm s-1 for 0.25- to 1- and 1- to 2-mm media, respectively. The K at the interaggregate/intraaggregate transition was approximately 10(-4) cm s-1 for both particle-size distributions. Significant differences in log(10)K due to method and porous medium were less than one order of magnitude and were attributed to variability in air entrapment. The van Genuchten/Mualem parametric models provided an adequate prediction of K of the interaggregate pore space, using residual water content for that pore space. The instantaneous profile method covers the range of water contents relevant to plant growth using fewer resources than Method A, all advantages for space flight where mass, volume, and astronaut time are limited.

NASA Center JSC↗

NASA NTRS1985

Particle generation experience in Langley's 16-foot transonic tunnel

The Langley 16-Foot Transonic Tunnel is a single-return, continuous-flow, atmospheric tunnel which uses air exchange for cooling. The tunnel speed is continuously variable from Mach 0 to 1.30. The test section is a regular octagon in cross-section with slots at the corners of the octagon. The laser velocimeter optics, laser, photomultipliers, etc. are mounted in the test section plenum chamber which surrounds the test section. The test volume is approximately a 1-meter cube about the tunnel center line centered on tunnel station 40.84 meters. The seeding system particle generators are mounted on the upstream side of the fourth set of turning vanes approximately 49 meters upstream of the test volume. At this point the tunnel has a diameter of 17.68 meters which meant that installation of the generators was a difficult procedure. It might be noted that particle generation had to be continuous as when the generators were turned off the data rate rapidly deteriorated to zero.

Reubush, D. E.↗

NASA NTRS1991

Liquid atomization by coaxial rocket injectors

The atomization characteristics of a scaled-down version of a coaxial rocket injector was investigated using a phase Doppler particle analyzer (PDPA). The injector was operated in the conventional mode with liquid being injected through its inner orifice and gas being injected through its outer annulus. The shearing action occurring at the liquid-gas interface causes the liquid jet to atomize. In this study, two different liquid-air systems, namely a water-air system and a liquid nitrogen-gaseous nitrogen system, were chosen for detailed investigation. This paper discusses the performance characteristics of the coaxial injector under different flow and geometric conditions. Specifically, the effects of injection gas pressure and the injector cavity size on variables such as the mean particle diameter, Sauter mean diameter, number density, volume flux, and velocity have been presented.

Sankar, S. V.↗

NASA NTRS1985

Three-dimensional unsteady Euler equations solutions on dynamic grids

A method is presented for solving the three-dimensional unsteady Euler equations on dynamic grids based on flux vector splitting. The equations are cast in curvilinear coordinates and a finite volume discretization is used for handling arbitrary geometries. The discretized equations are solved using an explicit upwind second-order predictor corrector scheme that is stable for a CFL of 2. Characteristic variable boundary conditions are developed and used for unsteady impermeable surfaces and for the far-field boundary. Dynamic-grid results are presented for an oscillating air-foil and for a store separating from a reflection plate. For the cases considered of stores separating from a reflection plate, the unsteady aerodynamic forces on the store are significantly different from forces obtained by steady-state aerodynamics with the body inclination angle changed to account for plunge velocity.

Belk, D. M.↗

NASA NTRS1991

Addition of equilibrium air to an upwind Navier-Stokes code and other first steps toward a more generalized flow solver

An upwind three-dimensional volume Navier-Stokes code is modified to facilitate modeling of complex geometries and flow fields represented by proposed National Aerospace Plane concepts. Code enhancements include an equilibrium air model, a generalized equilibrium gas model and several schemes to simplify treatment of complex geometric configurations. The code is also restructured for inclusion of an arbitrary number of independent and dependent variables. This latter capability is intended for eventual use to incorporate nonequilibrium/chemistry gas models, more sophisticated turbulence and transition models, or other physical phenomena which will require inclusion of additional variables and/or governing equations. Comparisons of computed results with experimental data and results obtained using other methods are presented for code validation purposes. Good correlation is obtained for all of the test cases considered, indicating the success of the current effort.

Rosen, Bruce S.↗

NASA NTRS2001

Space Station Biological Research Project Habitat: Incubator

Developed as part of the suite of Space Station Biological Research Project (SSBRP) hardware to support research aboard the International Space Station (ISS), the Incubator is a temperature-controlled chamber, for conducting life science research with small animal, plant and microbial specimens. The Incubator is designed for use only on the ISS and is transported to/from the ISS, unpowered and without specimens, in the Multi-Purpose Logistics Module (MPLM) of the Shuttle. The Incubator interfaces with the three SSBRP Host Systems; the Habitat Holding Racks (HHR), the Life Sciences Glovebox (LSG) and the 2.5 m Centrifuge Rotor (CR), providing investigators with the ability to conduct research in microgravity and at variable gravity levels of up to 2-g. The temperature within the Specimen Chamber can be controlled between 4 and 45 C. Cabin air is recirculated within the Specimen Chamber and can be exchanged with the ISS cabin at a rate of approximately equal 50 cc/min. The humidity of the Specimen Chamber is monitored. The Specimen Chamber has a usable volume of approximately equal 19 liters and contains two (2) connectors at 28v dc, (60W) for science equipment; 5 dedicated thermometers for science; ports to support analog and digital signals from experiment unique sensors or other equipment; an Ethernet port; and a video port. It is currently manifested for UF-3 and will be launched integrated within the first SSBRP Habitat Holding Rack.

Nakamura, G. J.↗

DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗

NASA NTRSDate not supplied

TPSAS-NF1676L-20321-DND

NASA has conducted airborne tropospheric chemistry studies for about three decades. These field campaigns have generated a great wealth of observations, including a wide range of the trace gases and aerosol properties. Even though the spatial and temporal coverage is limited, the aircraft data offer high resolution and comprehensive simultaneous coverage of many variables, e.g. ozone precursors, intermediate photochemical species, and photochemical products. The recent NASA Earth Venture Program has generated an unprecedented amount of aircraft observations in terms of the sheer number of measurements and data volume. The ASDC Toolset for Airborne Data (TAD) is being designed to meet the user community needs for aircraft data for scientific research on climate change and air quality relevant issues.

Aubrey Beach↗

NASA NTRS2002

Bubble Detachment in Variable Gravity Under the Influence of Electric Fields

The objective of the research is to investigate the behavior of individual air bubbles injected through an orifice into an electrically insulating liquid under the influence of a static electric field. Situations were considered with both uniform and nonuniform electric fields. Bubble formation and detachment were visualized in terrestrial gravity as well as for several levels of reduced gravity (lunar, martian and microgravity) using a high-speed video camera. Bubble volume, dimensions and contact angles at detachment were measured. In addition to the experimental studies, a simple model, predicting bubble characteristics at detachment in an initially uniform electric field was developed. The model, based on thermodynamic considerations, accounts for the level of gravity as well as the magnitude of the uniform electric field. The results of the study indicate that the level of gravity and the electric field magnitude significantly affect bubble behavior as well as shape, volume and dimensions.

Herman, Cila↗

NASA NTRS1983

The effect of microstructure on 650 C fatigue crack growth in P/M Astroloy

The effect of microstructure on fatigue crack propagation at 650 C has been studied in a P/M nickel-base superalloy, Astroloy. Crack propagation data were obtained in air and vacuum at 20 cpm with a modified compact tension specimen. The rate of crack growth, da/dn, was correlated with the stress intensity range. Key microstructural variables examined were grain size and the distribution and size of the strengthening gamma prime phase. A fine grain size less than 20 microns always promoted rapid, intergranular failure, while a large grain size promoted slower, transgranular failure which decreased as the size and volume fraction of aging gamma prime was manipulated so as to increase alloy strength. The rapid, intergranular mode of failure of the fine grain microstructures was suppressed in vacuum.

Gayda, J.↗

NASA NTRS1989

Water vapor and methane in the upper stratosphere - An examination of some of the Nimbus 7 measurements

The zonal mean volume mixing ratios of water vapor and methane from January to May, 1979, derived from the Nimbus-7 limb IR monitor of the stratosphere and from stratosphere and mesosphere sounder experiments are investigated. The water vapor mixing ratio of air that enters the stratosphere from the troposphere and the yield of water vapor from photochemical oxidation of methane in the stratosphere are examined. The water vapor yield averaged between 1.5 and 2.0, although variability with time and level was relatively large. It is suggested that water vapor yield increases with height in the 16- to 3-mbar range. The average water vapor mixing ratio fo air entering the stratosphere during the study period was about 3.25 X 10 to the -6th.

Hansen, Anthony R.↗