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NASA NTRSDate not supplied

NASA’s Quiet Electric ENgines (QUEEN): Summary of the Acoustic Tests of the QUEEN V1

Noise produced by an electric ducted fan system was measured in tests at the NASA Glenn Research Center Acoustical Testing Laboratory. Main components of the system include a Commercial-Off-the-Shelf fan, shroud, motor, and Electronic Speed Controller, plus a custom-designed inlet bellmouth, and four experimental inlet duct acoustic liners. Fan speed and noise were measured in this static ground test of the propulsor. This propulsor prototype is one of NASA’s Quiet Electric ENgines (QUEENs) and is designated the ‘QUEEN V1.’ The Quiet Electric Engines are being developed for the 25% scale model of the Subsonic Aft Engine (SUSAN) Flight Research Vehicle and are intended to explore the potential of distributed electric propulsion for large single-aisle aircraft. Results indicated that inlet duct acoustic liners reduced tone and broadband noise as compared to a hardwall inlet duct. Predicted performance of the honeycomb liner compared well with measurements from an array of far field microphones. Inlet acoustic liners are just one method for mitigating noise for electric ducted fans for aircraft propulsion systems. Lessons learned will be used to guide development of future QUEEN prototypes. Results of a thermal test of the Electronic Speed Controller are presented in a separate report.

Aircraft propulsion and power↗

NASA NTRSDate not supplied

NASA’s Quiet Electric ENgines (QUEEN): Summary of the Acoustic Tests of the QUEEN V1

Aircraft propulsion and power↗

NASA NTRSDate not supplied

Supersonic Traveling Crossflow Wave Characteristics in Ground and Flight Tests

This paper continues analysis of data acquired in a series of supersonic crossflow transition experiments on a 65° swept- wing model tested in both wind tunnel and flight. Flow visualization data are summarized to provide context for the swept-wing instability mechanisms of interest. Unsteady pressure measurements obtained near the wing model leading edge (LE) are studied using 2nd- and 3rd-order statistical methods to extract traveling crossflow wave characteristics from these data. Comparisons between tunnel and flight data with boundary-layer (BL) Linear Stability Theory (LST) predictions provide insights into BL transition phenomena similarities and differences observed in tests using the same swept-wing model configurations. Comparisons of unsteady pressure data results for wing LE configurations with and without distributed-roughness-element (DRE) patterns installed, suggest traveling crossflow disturbance growth is reduced when this type of flow control is applied. A brief stud y of different background surface roughness levels on the wing LE suggests the potential for another flow control approach to promote laminar flow on swept wings using streamwise-biased surface finishes.

Lewis R Owens↗

NASA NTRS2015

CFD Modeling of the Multipurpose Hydrogen Test Bed (MHTB) Self-Pressurization and Spray Bar Mixing Experiments in Normal Gravity: Effect of the Accommodation Coefficient on the Tank Pressure

A CFD model for simulating the self-pressurization of a large scale liquid hydrogen storage tank is utilized in this paper to model the MHTB self-pressurization experiment. The kinetics-based Schrage equation is used to account for the evaporative and condensi ng interfacial mass flows in this model. The effect of the accommodation coefficient for calculating the interfacial mass transfer rate on the tank pressure during tank selfpressurization is studied. The values of the accommodation coefficient which were considered in this study vary from 1.0e-3 to 1.0e-1 for the explicit VOF model and from 1.0e-4 to 1.0e-3 for the implicit VOF model. The ullage pressure evolutions are compared against experimental data. A CFD model for controlling pressure in cryogenic storage tanks by spraying cold liquid into the ullage is also presented. The Euler-Lagrange approach is utilized for tracking the spray droplets and for modeling the interaction between the droplets and the continuous phase (ullage). The spray model is coupled with the VOF model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. Droplet-ullage heat and mass transfer are modeled. The flow, temperature, and interfacial mass flux, as well as droplets trajectories, size distribution and temperatures predicted by the model are presented. The ul lage pressure and vapor temperature evolutions are compared with experimental data obtained from the MHTB spray bar mixing experiment. The effect of the accommodation coefficient for calculating the interfacial and droplet mass transfer rates on the tank pressure during mixing of the vapor using spray is studied. The values used for the accommodation coefficient at the interface vary from 1.0e-5 to 1.0e-2. The droplet accommodation coefficient values vary from 2.0e-6 to 1.0e-4.

cryogenic fluid storage↗

NASA NTRS1981

The Mars water cycle

A model has been developed to test the hypothesis that the observed seasonal and latitudinal distribution of water on Mars is controlled by the sublimation and condensation of surface ice deposits in the Arctic and Antarctic, and the meridional transport of water vapor. Besides reproducing the observed water vapor distribution, the model correctly reproduces the presence of a large permanent ice cap in the Arctic and not in the Antarctic. No permanent ice reservoirs are predicted in the temperate or equatorial zones. Wintertime ice deposits in the Arctic are shown to be the source of the large water vapor abundances observed in the Arctic summertime, and the moderate water vapor abundances in the northern temperate region. Model calculations suggest that a year without dust storms results in very little change in the water vapor distribution. The current water distribution appears to be the equilibrium distribution for present atmospheric conditions.

Davies, D. W.↗

NASA NTRS2001

GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden

We describe the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea-salt that is used to estimate the aerosol indirect effect. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows us to predict aerosol effects on cloud optical thickness and microphysical process rates. We calculate the aerosol indirect effect by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day vs. pre-industrial emissions. Both the first (radiative) and second (microphysical) indirect effects are explored. We test the sensitivity of our results to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden. The global mean aerosol indirect effect for all three aerosol types ranges from -1.55 to -4.36 W/sq m in our simulations. The results are quite sensitive to the pre-industrial background aerosol burden, with low pre-industrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

Menon, Surabi↗

NASA NTRS2001

GCM Simulations of the Aerosol Indirect Effect: Sensitivity to Cloud Parameterization and Aerosol Burden

We describe the coupling of the Goddard Institute for Space Studies (GISS) general circulation model (GCM) to an online sulfur chemistry model and source models for organic matter and sea-salt that is used to estimate the aerosol indirect effect. The cloud droplet number concentration is diagnosed empirically from field experiment datasets over land and ocean that observe droplet number and all three aerosol types simultaneously; corrections are made for implied variations in cloud turbulence levels. The resulting cloud droplet number is used to calculate variations in droplet effective radius, which in turn allows us to predict aerosol effects on cloud optical thickness and microphysical process rates. We calculate the aerosol indirect effect by differencing the top-of-the-atmosphere net cloud radiative forcing for simulations with present-day vs. pre-industrial emissions. Both the first (radiative) and second (microphysical) indirect effects are explored. We test the sensitivity of our results to cloud parameterization assumptions that control the vertical distribution of cloud occurrence, the autoconversion rate, and the aerosol scavenging rate, each of which feeds back significantly on the model aerosol burden. The global mean aerosol indirect effect for all three aerosol types ranges from -1.55 to -4.36 W m(exp -2) in our simulations. The results are quite sensitive to the pre-industrial background aerosol burden, with low pre-industrial burdens giving strong indirect effects, and to a lesser extent to the anthropogenic aerosol burden, with large burdens giving somewhat larger indirect effects. Because of this dependence on the background aerosol, model diagnostics such as albedo-particle size correlations and column cloud susceptibility, for which satellite validation products are available, are not good predictors of the resulting indirect effect.

Menon, Surabi↗

NASA NTRS2001

Global Bathymetric Prediction For Ocean Modeling and Marine Geophysics

We proposed to construct a complete bathymetric map of the oceans at a 3-10 km resolution by combining all of the available depth soundings collected over the past 30 years with high resolution marine gravity information provided by the Geosat, ERS-1/2, and Topex/Poseidon altimeters. Detailed bathymetry is essential for understanding physical oceanography and marine geophysics. Currents and tides are controlled by the overall shapes of the ocean basins as well as the smaller sharp ocean ridges and seamounts. Because erosion rates are low in the deep oceans, detailed bathymetry reveals the mantle convection patterns, the plate boundaries, the cooling/subsidence of the oceanic lithosphere, the oceanic plateaus, and the distribution of off-ridge volcanoes. We proposed to: (1) Accumulate all available depth soundings collected over the past 30 years; (2) Use the short wavelength (< 160 km) satellite gravity information to interpolate between sparse ship soundings; (3) Improve the resolution of the marine gravity field using enhanced estimates along repeat altimeter profiles together with the dense altimeter measurements; (4) Refine/improve bathymetric predictions using the improved resolution gravity field and also by investigating computer-intensive methods for bathymetric prediction such as inverse theory; and (5) Produce a 'Globe of the Earth' similar to the globe of Venus prepared by the NASA Magellan investigation. This will also include the best available digital land data.

Sandwell, David T.↗

NASA NTRS2003

Monitoring of Observation Errors in the Assimilation of Satellite Ozone Data

The stratospheric ozone layer protects life on Earth from the harmful effects of solar ultravioiet radiation. The ozone layer is currently in a fragile state because of depletion caused by man-made chemicals, especially chlorofluorocarbons. The state of the ozone layer is being monitored and evaluated by scientific experts around the world, in order to help policy makers assess the impacts of international protocols that control the production and release of ozone depleting chemicals. Scientists use a variety ozone measurements and models in order to form a comprehensive picture about the current state of the ozone layer, and to predict the future behavior (expected to be a recovery, as the abundance of the depleting chemicals decreases). Among the data sets used, those from satellite-borne instruments have the advantage of providing a wealth of information about the ozone distribution over most of the globe. Several instruments onboard American and international satellites make measurements of the properties of the atmosphere, from which atmospheric ozone amounts are estimated; long-term measurement programs enable monitoring of trends in ozone. However, the characteristics of satellite instruments change in time. For example, the instrument lenses through which measurements are made may deteriorate over time, or the satellite orbit may drift so that measurements over each location are made later and later in the day. These changes may increase the errors in the retrieved ozone amounts, and degrade the quality of estimated ozone amounts and of their variability. Our work focuses on combining the satellite ozone data with global models that capture atmospheric motion and ozone chemistry, using advanced statistical techniques: this is known as data assimilation. Our method provides a three-dimensional global ozone distribution that is consistent with both the satellite measurements and with our understanding of processes (described in the models) that control ozone distribution. Through the monitoring of statistical properties of the agreement between the data and the model, this approach also enables us to detect changes in the quality of ozone data retrieved from satellite-borne instrument measurements. This paper demonstrates that calculations of the changes in satellite data quality, and the impact these changes on the estimates of the global ozone distribution, can assist in maintaining the uniform quality of the satellite ozone data throughout the lifetime of these instruments, thus contributing to our understanding of long-term ozone change.

Stajner, Ivanka↗

NASA NTRS2016

Modeling Droplet Heat and Mass Transfer during Spray Bar Pressure Control of the Multipurpose Hydrogen Test Bed (MHTB) Tank in Normal Gravity

A CFD model for simulating pressure control in cryogenic storage tanks through the injection of a subcooled liquid into the ullage is presented and applied to the 1g MHTB spray bar cooling experiments. An Eulerian-Lagrangian approach is utilized to track the spray droplets and capture the interaction between the discrete droplets and the continuous ullage phase. The spray model is coupled with the VOF model by performing particle tracking in the ullage, removing particles from the ullage when they reach the interface, and then adding their contributions to the liquid. A new model for calculating the droplet-ullage heat and mass transfer is developed. In this model, a droplet is allowed to warm up to the saturation temperature corresponding to the ullage vapor pressure, after which it evaporates while remaining at the saturation temperature. The droplet model is validated against the results of the MHTB spray-bar cooling experiments with 50% and 90% tank fill ratios. The predictions of the present T-sat based model are compared with those of a previously developed kinetic-based droplet mass transfer model. The predictions of the two models regarding the evolving tank pressure and temperature distributions, as well as the droplets' trajectories and temperatures, are examined and compared in detail. Finally, the ullage pressure and local vapor and liquid temperature evolutions are validated against the corresponding data provided by the MHTB spray bar mixing experiment.

mass transfer↗

NASA NTRS1989

An evaluative model of system performance in manned teleoperational systems

Manned teleoperational systems are used in aerospace operations in which humans must interact with machines remotely. Manual guidance of remotely piloted vehicles, controling a wind tunnel, carrying out a scientific procedure remotely are examples of teleoperations. A four input parameter throughput (Tp) model is presented which can be used to evaluate complex, manned, teleoperations-based systems and make critical comparisons among candidate control systems. The first two parameters of this model deal with nominal (A) and off-nominal (B) predicted events while the last two focus on measured events of two types, human performance (C) and system performance (D). Digital simulations showed that the expression A(1-B)/C+D) produced the greatest homogeneity of variance and distribution symmetry. Results from a recently completed manned life science telescience experiment will be used to further validate the model. Complex, interacting teleoperational systems may be systematically evaluated using this expression much like a computer benchmark is used.

Haines, Richard F.↗

NASA NTRSDate not supplied

System Identification for eVTOL Aircraft Using Simulated Flight Data

This paper describes a system identification method for electric vertical takeoff and landing (eVTOL) aircraft. The approach merges fixed-wing and rotary-wing modeling techniques with new strategies to develop a modeling method for eVTOL vehicles using flight test data. The eVTOL aircraft system identification approach is demonstrated through application to the NASA LA-8 tandem tilt-wing, distributed electric propulsion aircraft using a high-fidelity flight dynamics simulation. Orthogonal phase-optimized multisine inputs are applied to each control surface and propulsor at numerous flight conditions throughout the flight envelope to collect informative flight data. An aero-propulsive model is identified at each flight condition using the equation-error method in the frequency domain. The local model parameters are then blended to create a global model across the nominal flight envelope. Parameter estimation results are shown to provide a good fit to modeling data and have good prediction capability. The methodology is developed with a discussion of unique eVTOL vehicle aerodynamic characteristics and practical strategies intended to inform future flight-based system identification efforts for eVTOL aircraft.

system identification↗

NASA NTRS1988

Hub loads analysis of the SA349/2 helicopter

The forces and moments at the rotor hub of an Aerospatiale SA349/2 helicopter were investigated. The study included three main topics. First, measured hub forces and moments for a range of level flight conditions (mu = 0.14 to 0.37) were compared with predictions from a comprehensive rotorcraft analysis to examine the influence of the wake model on the correlations. Second, the effect of changing the blade mass distribution and blade chordwise center of gravity location on the 3/rev nonrotating frame hub loads was studied for a high-speed flight condition (mu = 0.37). Third, the use of higher harmonic control to reduce nonrotating frame 3/rev hub shear forces was investigated. The last two topics were theoretical studies only.

Heffernan, R. M.↗

NASA NTRS1990

Hub loads analysis of the SA349/2 helicopter

Heffernan, Ruth M.↗

NASA NTRS2009

Electric Field Effects on Fiber Alignment Using an Auxiliary Electrode During Electrospinning

Control of electrospun fiber placement and distribution was investigated by examining the effect of electric field parameters on the electrospinning of fibers. The experimental set-up used in this study eliminated the bending instability and whipping, allowing the jet to be modeled as a stable trajectory. Coupling of experimental and computational results suggests the potential for predicting aligned fiber distribution in electrospun mats.

Carnell, Lisa S.↗

NASA NTRS1989

Conjugate (solid/fluid) computational fluid dynamics analysis of the space shuttle solid rocket motor nozzle/case and case field joints

Three-dimensional, conjugate (solid/fluid) heat transfer analyses of new designs of the Solid Rocket Motor (SRM) nozzle/case and case field joints are described. The main focus was to predict the consequences of multiple rips (or debonds) in the ambient cure adhesive packed between the nozzle/case joint surfaces and the bond line between the mating field joint surfaces. The models calculate the transient temperature responses of the various materials neighboring postulated flow/leakpaths into, past, and out from the nozzle/case primary O-ring cavity and case field capture O-ring cavity. These results were used to assess if the design was failsafe (i.e., no potential O-ring erosion) and reusable (i.e., no excessive steel temperatures). The models are adaptions and extensions of the general purpose PHOENICS fluid dynamics code. A non-orthogonal coordinate system was employed and 11,592 control cells for the nozzle/case and 20,088 for the case field joints are used with non-uniform distribution. Physical properties of both fluid and solids are temperature dependent. A number of parametric studies were run for both joints with results showing temperature limits for reuse for the steel case on the nozzle joint being exceeded while the steel case temperatures for the field joint were not. O-ring temperatures for the nozzle joint predicted erosion while for the field joint they did not.

Doran, D.↗

NASA NTRS2010

Toward Malaria Risk Prediction in Afghanistan Using Remote Sensing

Malaria causes more than one million deaths every year worldwide, with most of the mortality in Sub-Saharan Africa. It is also a significant public health concern in Afghanistan, with approximately 60% of the population, or nearly 14 million people, living in a malaria-endemic area. Malaria transmission has been shown to be dependent on a number of environmental and meteorological variables. For countries in the tropics and the subtropics, rainfall is normally the most important variable, except for regions with high altitude where temperature may also be important. Afghanistan s diverse landscape contributes to the heterogeneous malaria distribution. Understanding the environmental effects on malaria transmission is essential to the effective control of malaria in Afghanistan. Provincial malaria data gathered by Health Posts in 23 provinces during 2004-2007 are used in this study. Remotely sensed geophysical parameters, including precipitation from TRMM, and surface temperature and vegetation index from MODIS are used to derive the empirical relationship between malaria cases and these geophysical parameters. Both neural network methods and regression analyses are used to examine the environmental dependency of malaria transmission. And the trained models are used for predicting future transmission. While neural network methods are intrinsically more adaptive for nonlinear relationship, the regression approach lends itself in providing statistical significance measures. Our results indicate that NDVI is the strongest predictor. This reflects the role of irrigation, instead of precipitation, in Afghanistan for agricultural production. The second strongest prediction is surface temperature. Precipitation is not shown as a significant predictor, contrary to other malarious countries in the tropics or subtropics. With the regression approach, the malaria time series are modelled well, with average R2 of 0.845. For cumulative 6-month prediction of malaria cases, the average provincial accuracy reaches 91%. The developed predictive and early warning capabilities support the Third Strategic Approach of the WHO EMRO Malaria Control and Elimination Plan.

Safi, N.↗

NASA NTRS2005

Biomimetic Models for An Ecological Approach to Massively-Deployed Sensor Networks

Promises of ubiquitous control of the physical environment by massively-deployed wireless sensor networks open avenues for new applications that will redefine the way we live and work. Due to small size and low cost of sensor devices, visionaries promise systems enabled by deployment of massive numbers of sensors ubiquitous throughout our environment working in concert. Recent research has concentrated on developing techniques for performing relatively simple tasks with minimal energy expense, assuming some form of centralized control. Unfortunately, centralized control is not conducive to parallel activities and does not scale to massive size networks. Execution of simple tasks in sparse networks will not lead to the sophisticated applications predicted. We propose a new way of looking at massively-deployed sensor networks, motivated by lessons learned from the way biological ecosystems are organized. We demonstrate that in such a model, fully distributed data aggregation can be performed in a scalable fashion in massively deployed sensor networks, where motes operate on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects. We show that such architectures may be used to facilitate communication and synchronization in a fault-tolerant manner, while balancing workload and required energy expenditure throughout the network.

Jones, Kennie H.↗