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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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26 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Enhanced Boiling on Micro-Configured Composite Surfaces Under Microgravity Conditions

In order to accommodate the growing thermal management needs of future space platforms, several two-phase active thermal control systems (ATCSs) have evolved and were included in the designs of space stations. Compared to the pumped single-phase liquid loops used in the conventional Space Transportation System and Spacelab, ATCSs offer significant benefits that may be realized by adopting a two-phase fluid-loop system. Alternately, dynamic power systems (DPSs), based on the Rankine cycle, seem inevitably to be required to supply the electrical power requirements of expanding space activities. Boiling heat transfer is one of the key technologies for both ATCSs and DPSs. Nucleate boiling near critical heat flux (CHF) can transport very large thermal loads with much smaller device size and much lower pumping power. However, boiling performance deteriorates in a reduced gravity environment and operation in the CHF regime is precarious because any slight overload will cause the heat transfer to suddenly move to the film boiling regime, which in turn, will result in burnout of the heat transfer surfaces. New materials, such as micro-configured metal-graphite composites, can provide a solution for boiling enhancement. It has been shown experimentally that this type of material manifests outstanding boiling heat transfer performance and their CHF is also extended to higher values. Due to the high thermal conductivity of graphite fiber (up to 1,200 W/m-K in the fiber direction), the composite surfaces are non-isothermal during the boiling process. The composite surfaces are believed to have a much wider safe operating region (a more uniform boiling curve in the CHF regime) because non-isothermal surfaces have been found to be less sensitive to variations of wall superheat in the CHF regime. The thermocapillary forces formed by the temperature difference between the fiber tips and the metal matrix play a more important role than the buoyancy in the bubble detachment, for the bubble detachment manifests itself by a necking process which should not be weakened by reduced gravity. In addition, the composite surfaces introduce no extra pressure drop, no fouling and do not impose significant primary or maintenance costs. All of these suggest that this type of composite is an ideal material for the challenge of accounting for both reliability and economy of the relevant components applied in the ATCSs, the DPSs and other devices in future space missions. The aim of the proposed work is to experimentally investigate high nucleate pool boiling performance on a micro-configured metal-graphite composite surface and to determine the mechanisms of the nucleate boiling heat transfer both experimentally and theoretically. Freon-113 and water will be used as the test liquids to investigate wettability effects on boiling characteristics. The Cu-Gr and Al-Gr composites with various volume fractions of graphite fibers will be tested to obtain the heat transfer characteristic data in the nucleate boiling region and in the CHF regime. In the experiments, the bubble emission and coalescence processes will be recorded by a video camera with a magnifying borescope probe immersed in the working fluid. The temperature profile in the thermal boundary layer on the composite surfaces will be measured by a group of micro thermocouples consisting of four ultra fine micro thermocouples. This instrument was developed and successfully used to measure the temperature profile of evaporating liquid thin layers by the proposers in a study performed at the NASA/Lewis Research Center. A two tier model to explain the nucleate boiling process and the performance enhancement on the composite surfaces has been suggested by the authors. According to the model, the thicknesses of the microlayer and the macrolayer underneath the bubbles and mushrooms, can be estimated by the geometry of the composite surface. The experimental results will be compared to the predictions from the model, and in turn, to revise and improve it.

Zhang, Nengli↗
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↗
DOE OSTI2022

Disentangling the Relative Drivers of Seasonal Evapotranspiration Across a Continental-Scale Aridity Gradient

Evapotranspiration (ET) is a significant ecosystem flux, governing the partitioning of energy at the land surface. Understanding the seasonal pattern and magnitude of ET is critical for anticipating a range of ecosystem impacts, including drought, heat-wave events, and plant mortality. Here, in this study, we identified the relative controls of seasonal variability in ET, and how these controls vary among ecosystems. We used overlapping AmeriFlux and PhenoCam time series at a daily timestep from 20 sites to explore these linkages (# site-years >100), and our study area covered a broad climatological aridity gradient in the U.S. and Canada. We focused on disentangling the most important controls of bulk surface conductance (G s ) and evaporative fraction (EF = LE/[H + LE]), where LE and H represent latent and sensible heat fluxes, respectively. Specifically, we investigated how vegetation phenology varied in importance relative to meteorological variables (vapor pressure deficit and antecedent precipitation) as a driver of G s and EF using path analysis, a framework for quantifying and comparing the causal linkages among multiple response and explanatory variables. Our results revealed that the drivers of G s and EF seasonality varied significantly between energy- and water-limited ecosystems. Specifically, precipitation had a much higher effect in water-limited ecosystems, while seasonal patterns in canopy greenness emerged as a stronger control in energy-limited ecosystems. Given that phenology is expected to shift under future climate, our findings provide key information for understanding and predicting how phenology may impact 21st-century hydroclimate regimes and the surface-energy balance.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

A cloudiness transition in a marine boundary layer

Boundary layer cloudiness plays several important roles in the energy budget of the earth. Low level stratocumulus are highly reflective clouds which reduce the net incoming shortwave radiation at the earth's surface. Climatically, the transition to a small area fraction of scattered cumulus clouds occurs as the air flows over warmer water. Although these clouds reflect less sunlight, they still play an important role in the boundary layer equilibrium by transporting water vapor upwards, and enhancing the surface evaporation. The First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) included a marine stratocumulus experiment off the southern California coast from June 29 to July 19, 1987. The objectives of this experiment were to study the controls on fractional cloudiness, and to assess the role of cloud-top entrainment instability (CTEI) and mesoscale structure in determining cloud type. The focus is one research day, July 7, 1987, when coordinated aircraft missions were flown by four research aircraft, centered on a LANDSAT scene at 1830 UTC. The remarkable feature of this LANDSAT scene is the transition from a clear sky in the west through broken cumulus to solid stratocumulus in the east. The dynamic and thermodynamic structure of this transition in cloudiness is analyzed using data from the NCAR Electra. By averaging the aircraft data, the internal structure of the different cloud regimes is documented, and it is shown that the transition between broken cumulus and stratocumulus is associated with a change in structure with respect to the CTEI condition. However, this results not from sea surface temperature changes, but mostly from a transition in the air above the inversion, and the breakup appears to be at a structure on the unstable side of the wet virtual adiabat.

Betts, Alan K.↗
NASA NTRS2016

Comparison of Simultaneous PIV and Hydroxyl Tagging Velocimetry in Low Velocity Flows

Hydroxyl tagging velocimetry (HTV) is a molecular tagging velocimetry (MTV) technique that relies on the photo- dissociation of water vapor into OH radicals and their subsequent tracking using laser-induced fluorescence. At ambient temperature in air, the OH species lifetime is about 50 micro-s. The feasibility of using HTV for probing low- speed flows (a few m/s) is investigated by using an inert, heated gas as a means to increase the OH species lifetime. Unlike particle-based techniques, MTV does not suffer from tracer settling, which is particularly problematic at low speeds. Furthermore, the flow needs to be seeded with only a small mole fraction of water vapor, making it safer for both the user and facilities than other MTV techniques based on corrosive or toxic chemical tracers. HTV is demonstrated on a steam-seeded nitrogen jet at approximately 75 C in the laminar (Umean=3.31 m/s, Re=1,540), transitional (Umean=4.48 m/s, Re=2,039), and turbulent (Umean=6.91 m/s, Re=3,016) regimes at atmospheric pressure. The measured velocity profiles are compared with particle image velocimetry (PIV) measurements performed simultaneously with a second imager. Seeding for the PIV is achieved by introducing micron-sized water droplets into the flow with the steam; the same laser sheet is used for PIV and HTV to guarantee spatial and temporal overlap of the data. Optimizing each of these methods, however, requires conflicting operating conditions: higher temperatures benefit the HTV signals but reduce the available seed density for the PIV through evaporation. Nevertheless, data are found to agree within 10% for the instantaneous velocity profiles and within 5% for the mean profiles and demonstrate the feasibility of HTV for low-speed flows at moderate to high temperatures.

Andre, Matthieu A.↗
NASA NTRS2018

Towards an Enhanced Droplet Activation Scheme for Multi-Moment Bulk Microphysics Schemes

Initial droplet spectra produced upon activation impact the ensuing chain of microphysical processes andtherefore play a crucial role in cloud evolution. This work re-examines dependencies of newly formed clouddroplet size distribution (CDSD) characteristics on environmental and aerosol properties via parcel model simulationsthat serve as the basis for a multi-moment bulk microphysics droplet activation scheme suitable for acloud-resolving model (CRM). It is found that applying a fixed size threshold to define activated droplets versusemploying physical considerations can lead to erroneous activation and overly broad CDSDs for high aerosolconcentration and weak updraft conditions. Aerosol distributions characterized by larger median sizes and/orincreased solubility can result in greater activated droplet numbers, whereas impacts of these parameters onCDSD spectral width depend on both aerosol number concentration and updraft velocity. An expansion of theactivation scheme to include CDSD spectral width is proposed to aid efforts to extend high-order momentprediction to cloud droplet categories in CRMs as well as better represent variability in the activation process onthe cloud scale.simulations to investigate the regime dependence of the relative dispersion(d)1 of newly activated CDSDs, where d is the ratio of dropletradius standard deviation (σ) to the mean radius (r ). C16 demonstratedthat increasing Na resulted in increasing (decreasing) d values via reducedcondensational narrowing (spectral broadening) rates within theAL (UL) regime, with d values peaking in the TR regime. Their findingssuggest a similar regime dependence for d as R09 noted for Nc and helpexplain reportedly conflicting relationships between Na and CDSDspectral characteristics (cf. Hudson and Noble, 2014; Liu et al., 2014),although the applicability of these results within bulk microphysicalschemes was not addressed.Simulating aerosol-cloud interactions with CRMs employing bulkmicrophysics requires that the scheme minimally predict two CDSDparameters, namely mass and number concentrations, and represent thedroplet activation process. Various activation schemes aim to determineNc from aerosol and environmental properties and include analyticalexpressions (e.g., Abdul-Razzak et al., 1998; Morrison et al., 2005) aswell as lookup tables (LUTs) based on detailed parcel model calculations(e.g., Saleeby and Cotton, 2004, hereafter SC04; Segal and Khain,2006; Thompson and Eidhammer, 2014). Expressions to diagnose CDSDspectral width from Nc (Grabowski, 1998; Liu et al., 2006; Morrison andGrabowski, 2007) or cloud water content (Geoffroy et al., 2010) havealso been developed, although more robust methods to obtain CDSDspectral width upon activation are presently lacking. This latter point isrelevant for triple-moment (3 M) bulk microphysics that aim to predictdistribution spectral width alongside number and mass concentrations(e.g., Loftus et al., 2014; Milbrandt and Yau, 2005).The current work extends the findings of C16 to the current LUTbasedaerosol activation scheme used in the Regional AtmosphericModeling System (RAMS) (Cotton et al., 2003; SC04; Saleeby and vanden Heever, 2013, hereafter SvdH13) and additionally examinesaerosol size and solubility impacts on newly activated CDSD properties.Because early cloud development processes such as condensationalgrowth, evaporation, and droplet self-collection depend on and impactCDSD spectral width (Hudson and Yum, 1997; Seifert and Beheng 2001;Lu and Seinfeld, 2006; Igel and van den Heever, 2017), an expansion ofthe activation LUTs to include CDSD spectral width is proposed as apreliminary step for extending 3M prediction to CDSDs in CRMs forimproved simulations of aerosol-cloud interactions.2. MethodologyThe current RAMS two-moment microphysics module determinesthe fractional number of aerosol particles that activate to cloud dropletsfrom five-dimensional LUTs based on model predicted air temperature(T), w, Na, and the geometric median radius (rg) and soluble fraction (ε)of the aerosol size distribution (SvdH13). These LUTs are created offlineusing a one-dimensional Lagrangian adiabatic parcel model (Feingoldand Heymsfield, 1992; Heymsfield and Sabin, 1989; SC04) to simulateexplicit droplet activation and initial CDSD growth for a range of ambientatmospheric conditions [T, w] and binned lognormal aerosol sizedistributions given by= ⎡⎣ ⎢− ⎤⎦ ⎥N r Nr π σr rσ( )2 lnexp[ln( / )]2(ln )aggg22 (1)where r is the dry aerosol particle bin radius and σg is the geometricstandard deviation of the distribution. As the parcel model simulationsfocus on the activation process, other processes such as coalescence,sedimentation, and mixing are not considered. Details of the parcelmodel can be found in SC04 and SvdH13, and only a brief description isprovided here. At the onset of parcel model calculations, the initiallydry aerosol particles in all bins first deliquesce and reach theirequilibrium diameters in a sub-saturated environment based on theKöhler equation for solution droplets. The parcel is then lifted at a fixedupward velocity w, and particle growth by vapor diffusion, along withconcurrent changes in the ambient environment, are iteratively computedusing the Variable-coefficient Ordinary Differential Equation(VODE) solver (Brown et al., 1989). The time resolution of these calculationsis determined within the VODE solver, and the frequency atwhich the solver is called is controlled by a longer model time stepbased on fixed upward parcel displacement increments (Δz) at thespecified w (Δt=Δz/w). Model calculations proceed until the parcelreaches a height 50m beyond the level of maximum saturation ratio(Smax) or total parcel displacement exceeds 2 km. Upon model termination,Smax and the fractional number of aerosols (factv) resulting innewly formed cloud droplets, defined as particles having diameters of atleast 2 μm, are cataloged in the LUTs according to the specified T, w, Na,rg, and ε parameter values.A critical point regarding the creation of these LUTs is the use of afixed minimum diameter (Dmin) to define cloud droplets in the parcelmodel, which can produce erroneous CDSD characteristics, particularlywithin the UL regime. For aerosol distributions with large rg valuesunder low SS conditions, for example, deliquesced aerosols within thelarge tail of the distribution can exceed 2 μm in diameter yet remainunactivated as ‘haze’ particles (Levin and Cotton, 2009; McFigganset al., 2006). For this study, aerosol particles activate to cloud dropletsbased on the critical diameter Dcrit as a function of parcel supersaturationratio (Sr) as in R09:D = σ MS RTρ83 ln( ) critsol wr w (2)where σsol is the surface tension of a solution droplet, Mw and ρw are themolar mass and density of liquid water, respectively, and R is theuniversal gas constant. Additionally, at relatively large w values withinthe AL regime, Nc stabilizes shortly after reaching supersaturation.However, parcel ascent and condensational growth continue beyondthe level of Smax, potentially causing additional narrowing of the CDSD.In the current work, model calculations terminate upon reaching Smaxas changes in Nc are negligible with continued ascent (Peng et al., 2007;R09).Parcel model simulations are performed to examine the sensitivitiesof CDSD characteristics to w, Na, rg, and ε, with the ranges for theseparameters listed in Table 1. Aerosols are assumed to be a mix of solubleand insoluble material of equal density, specified by ε, where fullysoluble aerosols correspond to ammonium sulfate with hygroscopicityparameter κ=0.61 (Petters and Kreidenweis, 2007). FollowingSvdH13, aerosol geometric standard deviation is fixed at σg=1.8, andaerosol distributions (Eq. 1) are partitioned into 100 logarithmicallyspacedbins spanning a size range specific to each rg value. For all simulations,Δz=1 m, and initial values of relative humidity, air temperatureand pressure are set to RH=0.99, T=10 °C and p=900 hPa,respectively.

Loftus, Adrian M.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11084-DND

The solar radiation must be considered as the primary factor when we study the climatic system because it provides almost all energy that drives the climatic system and most atmospheric phenomena. The solar radiation at the TOA is partially transferred, transformed into other forms of energy that are eventually dissipated by the general circulation of the atmosphere and oceans, and partially used in chemical and biological processes. The absorption of solar energy in the atmosphere (Acol) plays a key role in the climate system, not only because it affects the amount of solar energy absorbed by the Earth system, but also because it changes the vertical distribution of absorbed energy, which in turn impacts surface evaporation, atmospheric convection and precipitation. To investigate Acol, we have collected the collocated satellite-surface observations over the 35 selected BSRN surface sites during the period 2000-2004. The surface radiation budgets are averaged from the BSRN Shortwave (SW) observations over a 1-hour interval centered at the time of the NASA Terra and Aqua satellites overpass, and the TOA radiation budgets are averaged from the closest FOV satellite data to the BSRN stations. Then the atmospheric column SW absorption will be inferred from the satellite TOA albedo and BSRN surface absorption (through the estimated surface albedo). Monthly means of Acol, TOA albedo, and surface absorption have been calculated under both clear- and all-sky conditions over the 35 selected BSRN sites which represent different climate regimes. To evaluate the GCM simulations, we have collected the ECHAM5-HAM simulated surface, TOA and atmospheric radiation budgets by researchers at ETH Zurich and compared those simulations with observations. The preliminary comparisons have shown that the ECHAM5 simulated clear-sky surface absorption, TOA albedo, and ACOL agree very well (1-3%) with observations. Under all-sky conditions, they have strong correlations with CERES-derived cloud fraction. The simulated surface absorption is lower and TOA albedo is higher than those under clear skies, but ACOL does not increase too much. However, there are relatively large differences over some regions and months. A further study is needed.

X. Dong↗
DOE OSTI2020

Dynamics of Subsiding Shells in Actively Growing Clouds with Vertical Updrafts

The dynamics of a subsiding shell at the edges of actively growing shallow cumulus clouds with updrafts is analyzed using direct numerical simulation. The actively growing clouds have a fixed in-cloud buoyancy and velocity. Turbulent mixing and evaporative cooling at the cloud edges generate a subsiding shell that grows with time. A self-similar regime is observed for first- and second-order moments when normalized with respective maximum values. Internal scales derived from integral properties of the flow problem are identified. A self-similarity analysis using these scales reveals that contrary to classical self-similar flows, the turbulent kinetic energy budget terms and velocity moments scale according to the buoyancy and not with the mean velocity. The shell thickness is observed to increase linearly with time. The buoyancy scale remains time invariant and is set by the initial cloud–environment thermodynamics. The shell accelerates ballistically with a magnitude set by the saturation value of the buoyancy of the cloud–environment mixture. In this regime, the shell is buoyancy driven and independent of the in-cloud velocity. Relations are obtained for predicting the shell thickness and minimum velocities by linking the internal scales with external flow parameters. The values thus calculated are consistent with the thickness and velocities observed in typical shallow cumulus clouds. The entrainment coefficient is a function of the initial state of the cloud and the environment, and is shown to be on the same order of magnitude as fractional entrainment rates calculated for large-scale models.

54 ENVIRONMENTAL SCIENCES↗