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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Parallelized Carbon Oxidation and Surface Recession Model in Direct-Simulation Monte Carlo Code, SPARTA

Ablative thermal protection system (TPS) materials for spacecraft are composites that often consist of a carbon-based reinforcement and a polymeric matrix. During Earth re-entry, they endure high-temperature oxidation and surface recession. Oxidation is an important mechanism for ablation, sometimes leading to the weakening, spallation, or failure of the oxidized fibers at the surface and in the char layer. However, more details are required including accurate material properties of the fiber microstructure, whether the fibers recede homogenously or localized at pits, and the role of pyrolysis outgassing in order to evaluate the role oxidation plays in the degradation and failure mechanisms of these materials. In this work, we demonstrate a parallelizable oxidation-driven ablation model developed for detailed, large-scale simulations in the DSMC code SPARTA. We also develop robust algorithms which handle the conservation of the surface state after an ablation step. Finally, we verify our model for both simple and more complex chemistry as well as microstructures with reaction statistics, oxidation depth calculations, and detailed visualization of oxidation-induced material recession at the microscale.

V Arias↗
NASA NTRS2017

Hyperspectral Radiative Transfer Modeling to Explore the Combined Retrieval of Biophysical Parameters and Canopy Fluorescence from FLEX - Sentinel-3 Tandem Mission Multi-Sensor Data

The FLuorescence EXplorer (FLEX) satellite mission, selected as ESA's 8th Earth Explorer, has been designed forthe measurement of sun-induced fluorescence (F) spectra emitted by plants. This will be accomplished through amulti-sensor approach by placing it in a common orbit in tandem with the Sentinel-3 (S3) mission, which willhave two optical sensors on board, OLCI (Ocean and Land Colour Instrument) and SLSTR (Sea and Land SurfaceTemperature Radiometer) to complement FLEX. These S3 instruments will be used in combination with theimaging spectrometers on board FLEX to provide data useful for atmospheric correction of FLEX data. However,a fully synergetic approach, i.e. by exploiting the spectral and directional information from all tandem missioninstruments together, is an attractive alternative which is explored in this paper. By employing all combined topof-atmosphere (TOA) spectral radiance data, one can (i) characterize the relevant optical properties of the atmosphere,(ii) retrieve biophysical canopy properties including the associated reflectance anisotropy, and (iii)retrieve a more accurate and consistent canopy F.Regarding retrieval methods, Fraunhofer Line Depth (FLD) and Spectral Fitting (SF) are well-known techniquesapplied to hyperspectral data. Both methods depend on a high spectral resolution and assume aLambertian (isotropic) canopy reflectance. However, most vegetation canopies are non-Lambertian. This impliesthat, in particular when ignoring the anisotropic surface reflection, substantial retrieval errors can occur due tothe interaction between atmospheric absorption bands and surface reflectance anisotropy. In this paper, a novelmethod based on spectral radiative transfer (RT) modeling is proposed, in which coupled RT models are used tosimulate TOA radiance spectra. These are then matched with ‘measured' spectra in order to retrieve surfacefluorescence, along with a suite of biophysical parameters, by model inversion through optimization. By applyingcoupled RT models of the soil-leaf-canopy and the surface-atmosphere systems, TOA radiance spectra canbe simulated for all optical sensors of this tandem mission. In this way, complex effects due to surface reflectanceanisotropy and the spectral sampling by the various instruments, which are difficult to compensate for in the endproducts, are properly taken into account by their incorporation in the forward modeling. Next, by model inversionof TOA radiance data via optimization, the most accurate F retrievals can be achieved in a consistentmanner, along with important canopy level biophysical parameters that may help interpret the F spectrum, suchas chlorophyll content and leaf area index (LAI). The potential of this approach has been explored in a numericalexperiment, and the results are presented in this paper. We find that, with the assumed well-characterized andplausible FLEX/S3 instrument performances, the simultaneous retrieval of biophysical canopy parameters and Fspectra would be possible with a remarkable accuracy, provided the correct atmospheric characterization isavailable.

Verhoef, Wouter↗
NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗
DOE OSTI2020

Impact of Lateral Groundwater Flow and Subsurface Lower Boundary Conditions on Atmospheric Boundary Layer Development over Complex Terrain

Credible soil moisture redistribution schemes are essential to meteorological models, as lower boundary moisture influences the balance of surface turbulent fluxes and atmospheric boundary layer (ABL) development. While land surface models (LSMs) have vastly improved in their hydrologic representation, several commonly held assumptions, such as free-draining lower boundary, one-dimensional moisture flux, and lack of groundwater representation, can bias the terrestrial water balance. This study explores the impact of LSM hydrology representation on ABL development in the Weather Research and Forecasting (WRF) meteorological model. The results of summertime WRF simulations with Noah LSM, characterized by 2-m-thick soil and one-dimensional flow, are shown for a domain in the Colorado Rocky Mountain headwaters region. A reference WRF simulation is compared to 1) the same model with soil moisture initialized by the hydrologic model ParFlow; 2) a deep, free-draining simulation; and 3) WRF coupled to ParFlow, a three-dimensional, integrated groundwater-surface water model. Results show that both lateral transport of groundwater and the rate of drainage from the lower soil layer can weaken or reverse the coupling strength between evaporative fraction and ABL over a 5-month summer period. The resulting shifts in low-level moist convection in river valleys and thermally driven airflows yield strengthened anabatic upslope winds and perturbations to regional precipitation.

Forrester, Mary M.↗
DOE OSTI2025

STILGAR: Subsurface Models for Graymont Pleasant Gap Mine

The detection, location, and monitoring of underground structures are of great importance to national and global security. Tunnels and voids generate seismic signatures detectable at the surface, but using non-invasive seismic data to image near-surface presents several challenges in real-world applications. In this report, we describe the use of a dense surface seismic deployment to generate subsurface models of the Graymont Pleasant Gap mine - a single-layer mine with a complex structure embedded in a high-velocity P-wave limestone bedrock. Our approach consists of three key methods. We use P-wave arrival times from local blast events to perform a tomography inversion with the tomoTD method, constructing a P-wave velocity model of the subsurface. We model the layer above the mine using Rayleigh wave ellipticity and inversion techniques. We leverage ongoing anthropogenic activities to identify and locate noise sources both on the surface and within the subsurface. With this integrated approach we aim to overcome the challenges and enhance our ability to non-invasively characterize underground structures, contributing to improved seismic monitoring techniques.

58 GEOSCIENCES↗
NASA NTRS2009

Polarization Properties of Rotation Powered Pulsars

Polarization measurements of rotation-powered pulsars and their nebulae have unique diagnostic potential. The polarization position angle of the pulsar wind nebula, as is know for the Crab pulsar, can tell us the orientation of the spin axis. Phase-resolved polarimetry of pulsars has had enormous diagnostic capability at radio and optical wavelengths and could also be a powerful diagnostic in the X-ray range. Measurement of the polarization properties as a function of pulse phase can therefore provide a multidimensional mapping of the pulsar emission. In the 'rotating vector' model, radiation originating near a magnetic pole is expected to show a characteristic S-shaped swing of the position angle vs. pulse phase. In this case it is possible to determine the magnetic inclination and viewing angles. Radiation originating further from the poles or further above the neutron star surface will have a more complex polarization signature, as a result of relativistic effects of aberration and time-of-flight delays and may also cause depolarization of the signal. I will discuss predicted polarization properties of pulsed emission in polar cap models, where radiation originates near the neutron star surface at the magnetic poles, and in slot gap and outer gap models, where radiation originates over a range of altitudes out to the speed-of-light cylinder.

Harding Alice K.↗
NASA NTRS1998

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.↗
NASA NTRS2016

The Impact of Truth Surrogate Variance on Quality Assessment/Assurance in Wind Tunnel Testing

Minimum data volume requirements for wind tunnel testing are reviewed and shown to depend on error tolerance, response model complexity, random error variance in the measurement environment, and maximum acceptable levels of inference error risk. Distinctions are made between such related concepts as quality assurance and quality assessment in response surface modeling, as well as between precision and accuracy. Earlier research on the scaling of wind tunnel tests is extended to account for variance in the truth surrogates used at confirmation sites in the design space to validate proposed response models. A model adequacy metric is presented that represents the fraction of the design space within which model predictions can be expected to satisfy prescribed quality specifications. The impact of inference error on the assessment of response model residuals is reviewed. The number of sites where reasonably well-fitted response models actually predict inadequately is shown to be considerably less than the number of sites where residuals are out of tolerance. The significance of such inference error effects on common response model assessment strategies is examined.

DeLoach, Richard↗
DOE OSTI2022

Tracking snowmelt during hydrological surface processes using a distributed hydrological model in a mesoscale basin on the Tibetan Plateau

We report that mountain snowpack is an important water resource for the high altitude and latitude regions where the terrain is complex. However, the snowmelt pathway and its actual contribution to streamflow and soil moisture are rarely reported and remain unclear in such regions. To fill in this knowledge gap, we incorporate a snowmelt pathway tracking algorithm to a high-resolution physics-based distributed-hydrology-soil-vegetation model (DHSVM), to track snowmelt movement and quantify snowmelt contributions in the surface hydrologic processes. A simple reservoir operation scheme is also incorporated in the model. The modified model is applied to a dammed meso-scale watershed in the northeast Tibetan Plateau, China to study the snow and reservoir effects. The results show that annual snow contribution to soil moisture (SC-SM) and snow contribution to streamflow (SC-S) significantly decrease over 1965-2019. At a monthly scale, SC-SM has the largest amplitude at the top soil layer and its peak in the deeper layer lags behind the upper layer, and mean monthly SC-S at all stations show bimodal distributions corresponding to snowfall season. Reservoir regulation has subtle impacts (≤2.0%) on SC-S. If the current climate change rate continues, monthly and annual streamflow at the outlet will decrease primarily due to snowpack reduction. To mitigate climate change impacts, better water resource management is needed in this watershed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

The Formation of Charon's Red Poles from Seasonally Cold-Trapped Volatiles

A unique feature of Plutos large satellite Charon is its dark red northern polar cap. Similar colours on Plutos surface have been attributed to tholin-like organic macromolecules produced by energetic radiation processing of hydrocarbons. The polar location on Charon implicates the temperature extremes that result from Charons high obliquity and long seasons in the production of this material. The escape of Pluto's atmosphere provides a potential feedstock for a complex chemistry. Gas from Pluto that is transiently cold-trapped and processed at Charon's winter pole was proposed as an explanation for the dark coloration on the basis of an image of Charon's northern hemisphere, but not modelled quantitatively. Here we report images of the southern hemisphere illuminated by Pluto-shine and also images taken during the approach phase that show the northern polar cap over a range of longitudes. We model the surface thermal environment on Charon and the supply and temporary cold-trapping of material escaping from Pluto, as well as the photolytic processing of this material into more complex and less volatile molecules while cold-trapped. The model results are consistent with the proposed mechanism for producing the observed colour pattern on Charon.

Grundy, W. M.↗
NASA NTRSDate not supplied

Response of the QBO to Abrupt Increases in CO2 Using Three Atmospheric Chemistry Configurations

Long-term projections of the Quasi-Biennial Oscillation (QBO) remain highly uncertain. This is partly due to the paucity of models which are able to properly simulate that phenomenon. Only 5 of the 47 CMIP5 models are capable of spontaneously generating a realistic QBO (Butchart et al., 2018), and even those models exhibit large biases in key QBO characteristics (e.g. amplitude, period, vertical extent) when compared with observations. Furthermore, only 1 of these 5 employed interactive atmospheric chemistry, which is known to modulate QBO dynamics. We here investigate the QBO response to increased greenhouse gases using the NASA Goddard Institute for Space Studies Middle Atmosphere Model E2.2. Compared to lower vertical resolution versions of Model E, version 2.2 has a higher model top (0.002 hPa), and additional interactive non-orographic gravity wave drag sources from convection and shear, which produce a sufficiently realistic QBO, thus rendering it suitable for use in climate change studies. Steady-state responses to doubled and quadrupled CO2 from a pre-industrial control are analyzed, as well as the transient response to a 1% per year CO2 increase. In addition, we systematically explore the impact of interactive chemistry in modulating the QBO response to increased CO2 by contrasting interactive, prescribed, and linearized ozone chemistry configurations of the model. Overall, in response to increase CO2 concentrations the QBO is seen to increase in frequency and weaken in amplitude, consistent with previous results, but the memory of the tropical stratosphere may complicate assessments of trends in chemistry and surface impacts. We also discuss implications for the trade-off between ensemble size and the complexity of the chemistry scheme in the model.

Quasi-Biennial Oscillation (QBO)↗
DOE OSTI2025

ClimGen: Learning the Forcing-Response Relationship in Climate System

Solar Radiation Management (SRM) is emerging as a potential geoengineering strategy to address the anthropogenic impact on climate, but its effective implementation requires an iterative and large ensemble of highly accurate and efficient climate projections. Traditional climate projections rely on executing computationally demanding and time-consuming numerical climate models. Recent advances in machine learning (ML) aim to enhance these approaches by emulating traditional methods. In this work, we propose a novel framework for directly learning the relationship between solar radiation flux at the top of the atmosphere and the corresponding surface temperature response. To evaluate the feasibility of this direct ML-based projection, we developed a dataset using an intermediate complexity model, incorporating a comprehensive suite of different forcing patterns and evaluation metrics to rigorously assess the ML model’s performance. We introduce a Conditional Denoising Diffusion Probabilistic Model (cDDPM) for this task, which demonstrates encouraging skill in representing climate statistics under previously unseen forcing patterns. This approach provides a promising pathway for direct climate projections by accurately learning the forcing-response relationship, with a wide range of applications in impact mitigation, emissions policy design, and SRM strategies.

Chen, Tse-Chun [BATTELLE (PACIFIC NW LAB)] (ORCID:↗
DOE OSTI2025

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗
DOE OSTI2025

Density functional theory-based surrogate kinetic models for heterogeneous reactions of hydrocarbon intermediates on silicon carbide

The increasing demand for high-performance materials in advanced technologies highlights the importance of achieving a fundamental understanding and potential control of silicon carbide (SiC) deposition processes. However, existing models often lack sufficient theoretical detail, relying heavily on empirical data and offering limited predictive capability. In particular, the complex surface chemistry governing SiC growth remains poorly understood. This study addresses these challenges by employing density functional theory (DFT) to investigate key heterogeneous reactions involving hydrocarbon intermediates on SiC surfaces, including dehydrogenation, hydrogenation, and carbon deposition. Transition state searches were conducted to identify reaction pathways and energy barriers. While first-principles calculations offer high accuracy, they are computationally intensive. To extend the utility of these first-principles results, vibrational analyses were performed using phonon-based statistical thermochemistry to compute temperature-dependent reaction rates which were used to develop Arrhenius-type surrogate kinetic models. Furthermore, the resulting framework provides a more rigorous, physically grounded basis for integrating atomistic insights into continuum-scale modeling, ultimately enabling improved prediction and optimization of SiC film growth in high-performance material systems.

Density Functional Theory↗
NASA NTRS2020

Hybrid AFP/Hand Layup Optimized Blades to Enhance Wind Tunnel Capability Summary of PREDICT 2018 Efforts

A project spanning four-months in 2018 was conducted at the NASA Langley Research Center (LaRC) to advance the state of the art in Automated Fiber Placement (AFP) fabrication of complex carbon fiber wind tunnel blades for NASA wind tunnels. This effort was the first step in developing a methodology for fabricating these complex parts. An AFP robotic system was used to explore whether manufacturing time and cost for production of wind tunnel blades could be reduced. Computer aided design models of the blade surfaces were created, and AFP process planning and programming was employed to study the manufacturability of the shapes. A manufacturing demonstration unit was fabricated to demonstrate a methodology to fabricate a complex shape representative of a wind tunnel blade. The present study revealed that the heater configuration on the LaRC AFP robotic system was the primary constraint that limited its ability to use AFP for wind tunnel blade manufacturing.

carbon-epoxy↗
DOE OSTI2025

A conserved chaperone protein is required for the formation of a noncanonical type VI secretion system spike tip complex

Type VI secretion systems (T6SSs) are dynamic protein nanomachines found in Gram-negative bacteria that deliver toxic effector proteins into target cells in a contact-dependent manner. Prior to secretion, many T6SS effector proteins require chaperones and/or accessory proteins for proper loading onto the structural components of the T6SS apparatus. However, despite their established importance, the precise molecular function of several T6SS accessory protein families remains unclear. In this study, we set out to characterize the DUF2169 family of T6SS accessory proteins. Using gene co-occurrence analyses, we find that DUF2169-encoding genes strictly co-occur with genes encoding T6SS spike complexes formed by valine-glycine repeat protein G (VgrG) and DUF4150 domains. Although structurally similar to Pro-Ala-Ala-Arg (PAAR) domains, “PAAR-like” DUF4150 domains lack PAAR motifs and instead contain a conserved PIPY motif, leading us to designate them PIPY domains. Next, we present both genetic and biochemical evidence that PIPY domains require a cognate DUF2169 protein to form a functional T6SS spike complex with VgrG. This contrasts with canonical PAAR proteins, which bind VgrG on their own to form functional spike complexes. By solving the first crystal structure of a DUF2169 protein, we show that this T6SS accessory protein adopts a novel protein fold. Furthermore, biophysical and structural modeling data suggest that DUF2169 contains a dynamic loop that physically interacts with a hydrophobic patch on the surface of its cognate PIPY domain. Based on these findings, we propose a model whereby DUF2169 proteins function as molecular chaperones that maintain VgrG–PIPY spike complexes in a secretion-competent state prior to their export by the T6SS apparatus.

DUF2169↗
DOE OSTI2024

A windowed mean trajectory approximation for condensed phase dynamics

We propose a trajectory-based quasi-classical method for approximating dynamics in condensed phase systems. Building upon the previously developed optimized mean trajectory approximation that has been used to compute linear and nonlinear spectra, we borrow some ideas from filtering trajectory methods to obtain a novel semiclassical method for the dynamical propagation of density matrices. This new approximation is tested rigorously against standard multistate electronic models, spin-boson models, and models of the Fenna–Matthews–Olson complex. For dissipative systems, the current method is significantly better or as good as many other semiclassical methods available, especially at low temperatures and for off-diagonal density matrix elements, whereas for scattering models, the current method bears similar limitations as mean-field propagation schemes. All results are tested against the numerically exact hierarchical equations of motion method. In conclusion, the new method shows excellent agreement across various parameter regimes with numerically exact results, highlighting the robustness and accuracy of our approach.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1978

Comparison between infrared Martian disk spectra and optical properties of terrestrial analogs

Medium spectral resolution (20 kaysers) infrared measurements of the Martian disk made between 2900 and 5600 kaysers from the NASA Lear Airborne Observatory have been successfully compared with predictions derived from a model of the Martian soil and atmosphere. Modeling of the Martian atmosphere permitted the extraction of Martian soil reflectance in the CO2 bands centered at 3657 kaysers. Three Martian soil analogs previously considered acceptable - limonite, montmorillonite, and basalt - were analyzed to determine the optical complex indices of refraction in the same range as the airborne observations, for mathematical modeling. A characteristic surface particle size approximately 1 to 3 microns diameter is indicated. It is concluded that the Martian soil surface near-infrared optical properties are consistent with a soil composition similar to montmorillonite or limonite, mixed with a basalt.

Egan, W. G.↗