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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 469 records · Page 26

Mapping Surface Cover Parameters Using Aggregation Rules and Remotely Sensed Cover Classes

A coupled model, which combines the Biosphere-Atmosphere Transfer Scheme (BATS) with an advanced atmospheric boundary-layer model, was used to validate hypothetical aggregation rules for BATS-specific surface cover parameters. The model was initialized and tested with observations from the Anglo-Brazilian Amazonian Climate Observational Study and used to simulate surface fluxes for rain forest and pasture mixes at a site near Manaus in Brazil. The aggregation rules are shown to estimate parameters which give area-average surface fluxes similar to those calculated with explicit representation of forest and pasture patches for a range of meteorological and surface conditions relevant to this site, but the agreement deteriorates somewhat when there are large patch-to-patch differences in soil moisture. The aggregation rules, validated as above, were then applied to remotely sensed 1 km land cover data set to obtain grid-average values of BATS vegetation parameters for 2.8 deg x 2.8 deg and 1 deg x 1 deg grids within the conterminous United States. There are significant differences in key vegetation parameters (aerodynamic roughness length, albedo, leaf area index, and stomatal resistance) when aggregate parameters are compared to parameters for the single, dominant cover within the grid. However, the surface energy fluxes calculated by stand-alone BATS with the 2-year forcing, data from the International Satellite Land Surface Climatology Project (ISLSCP) CDROM were reasonably similar using aggregate-vegetation parameters and dominant-cover parameters, but there were some significant differences, particularly in the western USA.

Arain, Altaf M.↗

Finite Element Model Development For Aircraft Fuselage Structures

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results.

Buehrle, Ralph D.↗

Finite Element Model Development and Validation for Aircraft Fuselage Structures

The ability to extend the valid frequency range for finite element based structural dynamic predictions using detailed models of the structural components and attachment interfaces is examined for several stiffened aircraft fuselage structures. This extended dynamic prediction capability is needed for the integration of mid-frequency noise control technology. Beam, plate and solid element models of the stiffener components are evaluated. Attachment models between the stiffener and panel skin range from a line along the rivets of the physical structure to a constraint over the entire contact surface. The finite element models are validated using experimental modal analysis results. The increased frequency range results in a corresponding increase in the number of modes, modal density and spatial resolution requirements. In this study, conventional modal tests using accelerometers are complemented with Scanning Laser Doppler Velocimetry and Electro-Optic Holography measurements to further resolve the spatial response characteristics. Whenever possible, component and subassembly modal tests are used to validate the finite element models at lower levels of assembly. Normal mode predictions for different finite element representations of components and assemblies are compared with experimental results to assess the most accurate techniques for modeling aircraft fuselage type structures.

Buehrle, Ralph D.↗

Tailoring the Stiffness of Large Mirrors to Reduce Specific Optical Aberrations

Presented is a method that tailors the geometry of a mirror’s core structure as well as the mounting interface such that a desired set of aberrations is reduced. It will be shown that targeting specific aberrations as opposed to reducing overall surface figure error (SFE) is a valid method to reduce weight or improve performance. Analyzed first is the self-weight deflection of a thin circular plate of uniform thickness continuously supported along its outer edge. The Kirchhoff-Love plate bending equations are related to the radially symmetric Zernike polynomials of piston, defocus, and primary spherical aberration. Next, the mirror’s radial thickness is optimized to eliminate primary and secondary spherical aberrations when the outer edge is simply supported. As an example, the method is demonstrated using a 2-meter diameter aluminum mirror where surface deflections can have an appreciable effect at mid-to-near infrared wavelengths

mirror stiffness optimization↗

Assessment of climate variability of the Greenland Ice Sheet: Integration of in situ and satellite data

The proposed research involves the application of multispectral satellite data in combination with ground truth measurements to monitor surface properties of the Greenland Ice Sheet which are essential for describing the energy and mass of the ice sheet. Several key components of the energy balance are parameterized using satellite data and in situ measurements. The analysis will be done for a ten year time period in order to get statistics on the seasonal and interannual variations of the surface processes and the climatology. Our goal is to investigate to what accuracy and over what geographic areas large scale snow properties and radiative fluxes can be derived based upon a combination of available remote sensing and meteorological data sets. Operational satellite sensors are calibrated based on ground measurements and atmospheric modeling prior to large scale analysis to ensure the quality of the satellite data. Further, several satellite sensors of different spatial and spectral resolution are intercompared to access the parameter accuracy. Proposed parameterization schemes to derive key component of the energy balance from satellite data are validated. For the understanding of the surface processes a field program was designed to collect information on spectral albedo, specular reflectance, soot content, grain size and the physical properties of different snow types. Further, the radiative and turbulent fluxes at the ice/snow surface are monitored for the parameterization and interpretation of the satellite data. The expected results include several baseline data sets of albedo, surface temperature, radiative fluxes, and different snow types of the entire Greenland Ice Sheet. These climatological data sets will be of potential use for climate sensitivity studies in the context of future climate change.

Steffen, K.↗

Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing

We demonstrate a multi-fidelity (MF) machine learning ensemble framework for the inverse design of photonic surfaces, trained on a dataset of 11,759 samples that we fabricate using high throughput femtosecond laser processing. The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. The combined MF ensemble can generate multiple disparate sets of laser-processing parameters that can each produce the same target input spectral emissivity with high accuracy (root mean squared errors < 2%). SHapley Additive exPlanations analysis shows transparent model interpretability of the complex relationship between laser parameters and spectral emissivity. Finally, the MF ensemble is experimentally validated by fabricating and evaluating photonic surface designs that it generates for improved efficiency energy harvesting devices. Our approach provides a powerful tool for advancing the inverse design of photonic surfaces in energy harvesting applications.

97 MATHEMATICS AND COMPUTING↗

An Assessment of the Influence of Uncertainty in Temporally Evolving Streamflow Forecasts on Riverine Inundation Modeling

Continental-scale river forecasting platforms forecast streamflow at reaches that can be used as boundary conditions to drive a local-scale flood inundation model. Uncertainty accumulated during this process stems not only from any part of the forecasting chain but can also be caused by the daily variations in weather forcing that keeps evolving as the event advances. This work aims to examine the influence of the evolving forecast streamflow on predicting the maximum inundation for extreme floods. A diagnostic case study was made on the basis of a hindcast of Hurricane Matthew striking the eastern U.S. in 2016. The U.S. National Water Model was one-way coupled to a hydrodynamic inundation model through a developed automated workflow. Although the river forcing has significantly mismatched hydrographs versus observations, the simulated peak water surface elevations and maximum extents were validated to be comparable with the observations, which indicates that the inundation model may not be sensitive to the inherited uncertainty from the weather forcing. Moreover, the uncertainty of the forecast streamflow time series caused only one order of magnitude fewer variations in inundation prediction; this dampening effect may become clearer for extreme events with large areas inundated. In addition, the forecast total volume of stream discharge appears to be an important metric for assessing the performance of river forcing for inundation mapping, as a linear correlation between the total volume and the accuracy of the predicted peak water surface elevation and maximum extent was found, with the coefficients of determination all above 0.8. Extra best-practice experience of running similar operational tasks demonstrated the tradeoff between the cost and accuracy gain.

flood, national water model, RIFT↗

Modeling of the Earth's gravity field using the New Global Earth Model (NEWGEM)

Traditionally, the global gravity field was described by representations based on the spherical harmonics (SH) expansion of the geopotential. The SH expansion coefficients were determined by fitting the Earth's gravity data as measured by many different methods including the use of artificial satellites. As gravity data have accumulated with increasingly better accuracies, more of the higher order SH expansion coefficients were determined. The SH representation is useful for describing the gravity field exterior to the Earth but is theoretically invalid on the Earth's surface and in the Earth's interior. A new global Earth model (NEWGEM) (KIM, 1987 and 1988a) was recently proposed to provide a unified description of the Earth's gravity field inside, on, and outside the Earth's surface using the Earth's mass density profile as deduced from seismic studies, elevation and bathymetric information, and local and global gravity data. Using NEWGEM, it is possible to determine the constraints on the mass distribution of the Earth imposed by gravity, topography, and seismic data. NEWGEM is useful in investigating a variety of geophysical phenomena. It is currently being utilized to develop a geophysical interpretation of Kaula's rule. The zeroth order NEWGEM is being used to numerically integrate spherical harmonic expansion coefficients and simultaneously determine the contribution of each layer in the model to a given coefficient. The numerically determined SH expansion coefficients are also being used to test the validity of SH expansions at the surface of the Earth by comparing the resulting SH expansion gravity model with exact calculations of the gravity at the Earth's surface.

Kim, Yeong E.↗

Lattice Boltzmann Modeling of Drying of Porous Media Considering Contact Angle Hysteresis

Drying of porous media is governed by a combination of evaporation and movement of the liquid phase within the porous structure. Contact angle hysteresis induced by surface roughness is shown to influence multi-phase flows, such as contact line motion of droplet, phase distribution during drainage and coffee ring formed after droplet drying in constant contact radius mode. However, the influence of contact angle hysteresis on liquid drying in porous media is still an unanswered question. Lattice Boltzmann model (LBM) is an advanced numerical approach increasingly used to study phase change problems including drying. In this paper, based on a geometric formulation scheme to prescribe contact angle, we implement a contact angle hysteresis model within the framework of a two-phase pseudopotential LBM. The capability and accuracy of prescribing and automatically measuring contact angles over a large range are tested and validated by simulating droplets sitting on flat and curved surfaces. Afterward, the proposed contact angle hysteresis model is validated by modeling droplet drying on flat and curved surfaces. Then, drying of two connected capillary tubes is studied, considering the influence of different contact angle hysteresis ranges on drying dynamics. Finally, the model is applied to study drying of a dual-porosity porous medium, where phase distribution and drying rate are compared with and without contact angle hysteresis. The proposed model is shown to be capable of dealing with different contact angle hysteresis ranges accurately and of capturing the physical mechanisms during drying in different porous media including flat and curved geometries.

36 MATERIALS SCIENCE↗

Intercomparison Between in situ and AVHRR Polar Pathfinder-Derived Surface Albedo over Greenland

The Advanced Very High Resolution (AVHRR) Polar Pathfinder Data (APP) provides the first long time series of consistent, calibrated surface albedo and surface temperature data for the polar regions. Validations of these products have consisted of individual studies that analyzed algorithm performance for limited regions and or time periods. This paper reports on comparisons made between the APP-derived surface albedo and that measured at fourteen automatic weather stations (AWS) around the Greenland ice sheet from January 1997 to August 1998. Results show that satellite-derived surface albedo values are on average 10% less than those measured by the AWS stations. However, the station measurements tend to be biased high by about 4% and thus the differences in absolute albedo may be less (e.g. 6%). In regions of the ice sheet where the albedo variability is small, such as the dry snow facies, the APP albedo uncertainty exceeds the natural variability. Further work is needed to improve the absolute accuracy of the APP-derived surface albedo. Even so, the data provide temporally and spatially consistent estimates of the Greenland ice sheet albedo.

Stroeve, Julienne C.↗

In-Flight Validation of Mid and Thermal Infrared Remotely Sensed Data Using the Lake Tahoe and Salton Sea Automated Validation Sites

The presentation includes an introduction, Lake Tahoe site layout and measurements, Salton Sea site layout and measurements, field instrument calibration and cross-calculations, data reduction methodology and error budgets, and example results for MODIS. Summary and conclusions are: 1) Lake Tahoe CA/NV automated validation site was established in 1999 to assess radiometric accuracy of satellite and airborne mid and thermal infrared data and products. Water surface temperatures range from 4-25C.2) Salton Sea CA automated validation site was established in 2008 to broaden range of available water surface temperatures and atmospheric water vapor test cases. Water surface temperatures range from 15-35C. 3) Sites provide all information necessary for validation every 2 mins (bulk temperature, skin temperature, air temperature, wind speed, wind direction, net radiation, relative humidity). 4) Sites have been used to validate mid and thermal infrared data and products from: ASTER, AATSR, ATSR2, MODIS-Terra, MODIS-Aqua, Landsat 5, Landsat 7, MTI, TES, MASTER, MAS. 5) Approximately 10 years of data available to help validate AVHRR.

Lake Tahoe↗

Experimental Investigation of Charging Properties of Interstellar Type Silica Dust Grains by Secondary Electron Emissions

The dust charging by electron impact is an important dust charging processes in astrophysical and planetary environments. Incident low energy electrons are reflected or stick to the grains charging the dust grains negatively. At sufficiently high energies electrons penetrate the grains, leading to excitation and emission of electrons referred to as secondary electron emission (SEE). Available classical theoretical models for calculations of SEE yields are generally applicable for neutral, planar, or bulk surfaces. These models, however, are not valid for calculations of the electron impact charging properties of electrostatically charged micron/submicron-size dust grains in astrophysical environments. Rigorous quantum mechanical models are not yet available, and the SEE yields have to be determined experimentally for development of more accurate models for charging of individual dust grains. At the present time, very limited experimental data are available for charging of individual micron-size dust grains, particularly for low energy electron impact. The experimental results on individual, positively charged, micron-size lunar dust grains levitated carried out by us in a unique facility at NASA-MSFC, based on an electrodynamic balance, indicate that the SEE by electron impact is a complex process. The electron impact may lead to charging or discharging of dust grains depending upon the grain size, surface potential, electron energy, electron flux, grain composition, and configuration (Abbas et al, 2010, 2012). In this paper, we discuss SEE charging properties of individual micron-size silica microspheres that are believed to be analogs of a class of interstellar dust grains. The measurements indicate charging of the 0.2m silica particles when exposed to 25 eV electron beams and discharging when exposed to higher energy electron beams. Relatively large size silica particles (5.2-6.82m) generally discharge to lower equilibrium potentials at both electron energies. These measurements conducted on silica microspheres are qualitatively similar in nature to our previous SEE measurements on lunar Apollo missions dust samples.

Tankosic, D.↗

Enhanced Characterization of Microorganisms in the Spacecraft Environment

Spacecraft such as the International Space Station (ISS) and the space shuttles are enclosed environments where crewmembers may spend long periods of time. Currently, crewmembers spend approximately a period of 6 months in the ISS. It is known that these prolonged stays in space may result in weakening of the immune system. Therefore, exposure to opportunistic pathogens or high concentrations of environmental microorganisms may compromise the health of the crew. The detection of biocontaminants in spacecraft environments utilizes culture-based methodology, omitting greater than 90% of all microorganisms including pathogens such as Legionella and Cryptosporidium. Culturable bacteria and fungi have been the only allergens studied; the more potent allergens, such as those from dust mites, have never been tested for in spacecraft environments. In addition, no attempts have been made to monitor microbial toxins in spacecrafts. The present study utilized quantitative polymerase chain reaction (QPCR) as a novel approach for monitoring microorganisms in the spacecraft environment. QPCR is a molecular biology technique that does not rely on the physiological state of the organisms for identification, thereby enabling detection of both culturable and non-culturable organisms. In this project, specific molecular primers and probes were utilized for the detection and quantitation of two fungi of concern in indoor environments, Aspergillus fumigatus and Stachybotrys chartarum. These organisms were selected because of the availability of PCR primers and probes, and to establish the sample processing and analysis methodology that may be employed with additional organisms. Purification methods and QPCR assays were optimized for the detection of these organisms in air, surface, and water; and sample processing and analysis protocols were developed. Preliminary validation of these protocols was conducted in the laboratory with air, surface, and water samples seeded with known concentrations of the target organisms. Additional studies were conducted with bulk materials (HEPA filter pleats and particulate found on the filter screen) obtained from the ISS.

Cruz, Patricia↗

Benefits of Using a Mars Forward Strategy for Lunar Surface Systems

This paper identifies potential risk reduction, cost savings and programmatic procurement benefits of a Mars Forward Lunar Surface System architecture that provides commonality or evolutionary development paths for lunar surface system elements applicable to Mars surface systems. The objective of this paper is to identify the potential benefits for incorporating a Mars Forward development strategy into the planned Project Constellation Lunar Surface System Architecture. The benefits include cost savings, technology readiness, and design validation of systems that would be applicable to lunar and Mars surface systems. The paper presents a survey of previous lunar and Mars surface systems design concepts and provides an assessment of previous conclusions concerning those systems in light of the current Project Constellation Exploration Architectures. The operational requirements for current Project Constellation lunar and Mars surface system elements are compared and evaluated to identify the potential risk reduction strategies that build on lunar surface systems to reduce the technical and programmatic risks for Mars exploration. Risk reduction for rapidly evolving technologies is achieved through systematic evolution of technologies and components based on Moore's Law superimposed on the typical NASA systems engineering project development "V-cycle" described in NASA NPR 7120.5. Risk reduction for established or slowly evolving technologies is achieved through a process called the Mars-Ready Platform strategy in which incremental improvements lead from the initial lunar surface system components to Mars-Ready technologies. The potential programmatic benefits of the Mars Forward strategy are provided in terms of the transition from the lunar exploration campaign to the Mars exploration campaign. By utilizing a sequential combined procurement strategy for lunar and Mars exploration surface systems, the overall budget wedges for exploration systems are reduced and the costly technological development gap between the lunar and Mars programs can be eliminated. This provides a sustained level of technological competitiveness as well as maintaining a stable engineering and manufacturing capability throughout the entire duration of Project Constellation.

Mulqueen, Jack↗

Cell Population–resolved Multiomics Atlas of the Developing Lung

The lung is a vital organ that undergoes extensive morphological and functional changes during postnatal development. To disambiguate how different cell populations contribute to organ development, we performed proteomic and transcriptomic analyses of four sorted cell populations from the lung of human subjects aged 0 to 8 years-old with a focus on early life. The cell populations analyzed included epithelial, endothelial, mesenchymal, and immune cells. Our results revealed distinct molecular signatures for each of the sorted cell populations that enable the description of molecular shifts occurring in these populations during post-natal development. Here, we confirmed that the proteome of the different cell populations was distinct regardless of age and identified functions specific to each population. We identified a series of cell population protein markers, including those located at the cell surface, that show differential expression and distribution on RNA in situ hybridization and immunofluorescence imaging. We validated the spatial distribution of AT1 and endothelial cell surface markers. Temporal analyses of the proteome of each of the four populations revealed processes modulated during postnatal development and disambiguating results obtained on whole tissue proteome. Finally, the proteome was compared to a transcriptomics survey performed on the same lung samples to evaluate processes under post-transcriptional control.

59 BASIC BIOLOGICAL SCIENCES↗

Validation of LOCA2 and STAR-ESDM Statistically Downscaled Products

The National Climate Assessment (NCA) is the preeminent national report examining current and future risks posed by climate change. Countless agencies, policymakers, stakeholders and other end-users rely upon guidance from the NCA to plan for an uncertain future. These groups all depend on modern curated data, provided alongside the NCA, to quantify the impact of climate change on metrics of relevance for their decision processes. In its fifth iteration (NCA5), two statistically downscaled ensemble products, each providing data at grid spacing of approximately 5km over the contiguous United States, were selected to accompany the report. These include LOCalized Analogs version 2 (LOCA2) and Seasonal Trends and Analysis of Residuals Empirical-Statistical Downscaling Model (STAR-ESDM). Both data products are produced through a process known as statistical downscaling, where relatively coarse Global Climate Model (GCM) data is refined to locally relevant scales through the application of scientifically-supported empirical and algorithmic relationships. In support of the NCA effort, this report provides an independent validation of these two products against historical observations, with a focus on precipitation and near-surface temperature variables. Based on the results of this validation, several recommendations are provided related to the use of these data products. The structure of this report is as follows: In section 2, we review three gridded observational products that are used as part of our intercomparison. In section 3, we describe the two statistical downscaling techniques and their corresponding datasets that are the focus of this study. In section 4, the methodology we employ for validation is described. Section 5 provides results of the validation, which in turn motivate our recommendations on the use of these data products. A brief summary is provided in section 6.

54 ENVIRONMENTAL SCIENCES↗

Monitoring CO2 sources and sinks from space : the Orbiting Carbon Observatory (OCO) Mission

NASA's Orbiting Carbon Observatory (OCO) will make the first space-based measurements of atmospheric carbon dioxide (CO2) with the precision, resolution, and coverage needed to characterize the geographic distribution of CO2 sources and sinks and quantify their variability over the seasonal cycle. OCO is currently scheduled for launch in 2008. The observatory will carry a single instrument that incorporates three high-resolution grating spectrometers designed to measure the near-infrared absorption by CO2 and molecular oxygen (O2) in reflected sunlight. OCO will fly 12 minutes ahead of the EOS Aqua platform in the Earth Observing System (EOS) Afternoon Constellation (A-Train). The in-strument will collect 12 to 24 soundings per second as the Observatory moves along its orbit track on the day side of the Earth. A small sampling footprint (<3 km2 at nadir) was adopted to reduce biases in each sounding associated with clouds and aerosols and spatial variations in surface topography. A comprehensive ground-based validation program will be used to assess random errors and biases in the XCO2 product on regional to continental scales. Measurements collected by OCO will be assimilated with other environmental measurements to retrieve surface sources and sinks of CO2. This information could play an important role in monitoring the integrity of large scale CO2 sequestration projects.

carbon dioxide sources and sinks↗

Data for A Hybrid Biophysical-Machine Learning Framework for Diurnal Surface Energy Flux Estimation Using Proximal Sensing

Thermal infrared-based remote sensing of surface energy fluxes has traditionally relied on high spatial resolution satellite data with revisit frequencies on the order of weeks. In this study, we evaluate a biophysics-based analytical surface energy balance model for predicting latent energy (LE) and sensible heat (H) fluxes using proximal sensing observations. The Surface Temperature Initiated Closure (STIC1.2) model has been extensively validated across a wide range of spatial and temporal scales using various satellite-derived thermal infrared data sets. Here we extend this validation by applying STIC at sub-hourly temporal resolution over multiple growing seasons for four distinct agricultural systems. We further develop and evaluate novel STIC variants that incorporate machine learning (ML) techniques to eliminate the need for surface energy balance observations, specifically net radiation and soil heat flux, thereby enhancing model applicability in data-sparse settings. The integration of a ML component to estimate surface available energy is shown to have strong predictive performance for both LE (R2 = 0.81–0.94) and H (R2 = 0.46–0.72) across all agricultural systems examined here, demonstrating the potential of hybrid biophysical-machine learning approaches for surface energy balance modeling with minimal data requirements. This study concludes with a novel application of explainable machine learning (exML) to diagnose sources of model error. This exML framework attributes residual prediction errors to both model input variables and environmental drivers not explicitly included in the simulation experiments. This approach provides a new pathway for improving model design and integrating previously overlooked yet influential variables into future model iterations.

AI/ML↗