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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Domain Wall Patterning and Giant Response Functions in Ferrimagnetic Spinels

Abstract The manipulation of mesoscale domain wall phenomena has emerged as a powerful strategy for designing ferroelectric responses in functional devices, but its full potential is not yet realized in the field of magnetism. This work shows a direct connection between magnetic response functions in mechanically strained samples of Mn 3 O 4 and MnV 2 O 4 and stripe‐like patternings of the bulk magnetization which appear below known magnetostructural transitions. Building off previous magnetic force microscopy data, a small‐angle neutron scattering is used to show that these patterns represent distinctive magnetic phenomena which extend throughout the bulk of two separate materials, and further are controllable via applied magnetic field and mechanical stress. These results are unambiguously connected to the anomalously large magnetoelastic and magnetodielectric response functions reported for these materials, by performing susceptibility measurements on the same crystals and directly correlating local and macroscopic data.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Abstract We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT–AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.). We also show that our framework provides a speed-up of $$7 \times 10^{6}$$ 7 × 10 6 times, in the best case, and $$7 \times 10^{3}$$ 7 × 10 3 times on average compared to a finite element solver. Furthermore, this BT–AE framework can operate on unstructured meshes, which provides flexibility in its application to standard numerical solvers, on-site measurements, experimental data, or a combination of these sources.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1976

New sidelobe envelopes for small aperture earth stations

The advent of domestic satellite systems and technological improvements in both space and ground equipment makes the use of small aperture earth stations economically feasible and attractive for broadcast satellite applications. With increasing use of the orbit spectrum, there is some concern that broadcast satellite systems may not be able to obtain satisfactory allocations of this orbit-spectrum resource because of interference considerations. Specifically, interference calculations based on the present envelope result in comparatively large orbit spacings for broadcast satellites. Theoretical and experimental investigations of simple sidelobe suppression techniques, plus an analysis of experimental data on small aperture antennas, indicate that much better sidelobe performance can be obtained with a very small cost or performance penalty.

Janky, J. M.↗
NASA NTRS1986

An assessment of the small-crack effect for 2024-T3 aluminum alloy

Data on small-crack behavior were obtained for a single-edge-notched tensile specimen made of 2024-T3 Al alloy and used to evaluate the capability of a semiempirical crack-growth and closure model to predict the fatigue life of notched specimens. Fatigue tests were conducted under either constant-amplitude loading (with stress ratios of 0.5, 0, -1, and -2) or spectrum loading, using a replication technique to record growth. It was found that small cracks exhibited the 'small-crack' effect in that they grew faster than large cracks when subjected to the same stress intensity factor range. Experimental small-crack growth rates agreed well with the model predictions. For making predictions of fatigue life, an initial surface defect void size of 3 x 12 x 0.4 microns was used in all calculations; predicted fatigue lives agreed well with experimentally determined values obtained in all tests. The crack-closure model indicated that the 'small-crack' effect on fatigue life was greatest in tests involving significant compressive loads.

Newman, J. C., Jr.↗
NASA NTRS1996

Technique for Extension of Small Antenna Array Mutual-Coupling Data to Larger Antenna Arrays

A technique is presented whereby the mutual interaction between a small number of elements in a planar array can be interpolated and extrapolated to accurately predict the combined interactions in a much larger array of many elements. An approximate series expression is developed, based upon knowledge of the analytical characteristic behavior of the mutual admittance between small aperture antenna elements in a conducting ground plane. This expression is utilized to analytically extend known values for a few spacings and orientations to other element configurations, thus eliminating the need to numerically integrate a large number of highly oscillating and slowly converging functions. This paper shows that the technique can predict very accurately the mutual coupling between elements in a very large planar array with a knowledge of the self-admittance of an isolated element and the coupling between only two-elements arranged in eight different pair combinations. These eight pair combinations do not necessarily have to correspond to pairs in the large array, although all of the individual elements must be identical.

Bailey, M. C.↗
NASA NTRSDate not supplied

Characterization of the Eugene Stansbery-Meterclass Autonomous Telescope on Ascension Island

In a focused effort to meet full operational capability for NASA’s Eugene Stansbery Meter Class Autonomous Telescope (ES-MCAT), a thorough system characterization analysis was completed. NASA’s Orbital Debris Program Office (ODPO)utilizes ES-MCAT as the primary sensor for characterizing the geosynchronous orbit (GEO)environment to acquire photometric data of small, faint debris objects in or near GEO. ES-MCAT is located on Ascension Island in the middle of the Atlantic Ocean at nearly 8° South latitude and 15° West longitude. This location provides dark skies suited for faint object observations but is also continuously subject to a harsh environment exposed to volcanic ash and salt spray. To better assess the overall system performance of the optical instrument, a historical assessment of the system’s performance was conducted. This analysis investigated all systematic and optical operational data to determine the overall performance parameters for ES-MCAT.A complete optical system throughput calculation was performed to determine the optimal filter for observing orbital debris in GEO orbits. The responses of each optical component to the solar spectrum, with atmospheric absorption, were multiplied and integrated to give ES-MCAT’s total system response for various filters. With the highest flux values, the Sloan Digital Sky Survey (SDSS) r’ and g’ were determined to be the optimal filters for ES-MCAT observations. Further analysis with known GEO debris objects enabled the selection of the r’ filter for characterization of the GEO debris population. A detailed overview of the optical system throughput, data reduction, photometric and astrometric data, and other system characteristics that define ES-MCAT will be discussed in the subsequent paper.

C. Cruz↗
NASA NTRSDate not supplied

Characterization of the Eugene Stansbery-Meter Class Autonomous Telescope on Ascension Island

In a focused effort to meet full operational capability for NASA’s Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT), a thorough system characterization analysis was completed. NASA’s Orbital Debris Program Office (ODPO) utilizes ES-MCAT as the primary sensor for characterizing the geosynchronous Earth orbit (GEO) environment to acquire photometric data of small, faint debris objects in or near GEO. ES-MCAT is located on Ascension Island in the middle of the Atlantic Ocean at nearly 8° South latitude and 14° West longitude. This location provides dark skies suited for faint object observations but is also continuously subject to a harsh environment exposed to volcanic ash and salt spray. To better assess the overall system performance of the optical instrument, a historical assessment of the system’s performance was conducted. This analysis investigated all systematic and optical operational data to determine the overall performance parameters for ES-MCAT. A complete optical system throughput calculation was performed to determine the optimal filter for observing orbital debris in GEO orbits. The responses of each optical component to the solar spectrum, with atmospheric absorption, were multiplied and integrated to give ES-MCAT’s total system response for various filters. With the highest flux values, the Sloan Digital Sky Survey (SDSS) r′ and g′ were determined to be the optimal filters for ES-MCAT observations. Further analysis with known GEO debris objects enabled the selection of the r′ filter for characterization of the GEO debris population. A detailed overview of the optical system throughput, data reduction, photometric and astrometric data, and other system characteristics that define ES-MCAT are discussed.

Corbin L Cruz↗
NASA NTRS1993

A hydrogen isotope study of CO3 type carbonaceous chondrites; comparison with type 3 ordinary chondrites

Meteorites of the Ornans type 3 carbonaceous chondrites exhibit a range in degree of equilibration, attributed to differing amounts of thermal metamorphism. These differences have been used to split the CO3 chondrites into petrologic sub-types from 3.0, least equilibrated, to 3.7, being most equilibrated. This is similar to the system of assigning the type 3 ordinary chondrites into petrologic sub-types 3.0 to 3.9 based upon thermoluminescence (TL) and other properties; however, the actual range of thermal metamorphism experienced by CO3 chondrites is much less than that of the type 3 ordinary chondrites. The least equilibrated ordinary chondrites show evidence of aqueous alteration and have high D/H ratios possibly due to a deuterium-rich organic carrier. The aim of this study was to determine whether the CO3 chondrites, which have experienced similar secondary conditions to the type 3 ordinary chondrites, also contain a similar deuterium-rich carrier. To date a total of 5 CO3 meteorites, out of a set of 11 for which carbon and nitrogen isotopic data are available, have been analyzed. Ornans has not been analyzed yet, because it does not appear to fit in with the metamorphic sequence exhibited by the other CO3 chondrites; it also has an extremely high delta-D value of +2150 percent, unusual for such a comparatively equilibrated meteorite (type 3.4). Initial results indicate that the more equilibrated CO3's tend to have lower delta-D values, analogous to the higher petrologic type ordinary chondrites. However this is complicated by the effects of terrestrial weathering and the small data-set.

Morse, A. D.↗
DOE OSTI2024

Phase Diagrams of Alloys and Their Hydrides via On-Lattice Graph Neural Networks and Limited Training Data

Efficient prediction of sampling-intensive thermodynamic properties is needed to evaluate material performance and permit high-throughput materials modeling for a diverse array of technology applications. To alleviate the prohibitive computational expense of high-throughput configurational sampling with density functional theory (DFT), surrogate modeling strategies like cluster expansion are many orders of magnitude more efficient but can be difficult to construct in systems with high compositional complexity. We therefore employ minimal-complexity graph neural network models that accurately predict and can even extrapolate to out-of-train distribution formation energies of DFT-relaxed structures from an ideal (unrelaxed) crystallographic representation. This enables the large-scale sampling necessary for various thermodynamic property predictions that may otherwise be intractable and can be achieved with small training data sets. Two exemplars, optimizing the thermodynamic stability of low-density high-entropy alloys and modulating the plateau pressure of hydrogen in metal alloys, demonstrate the power of this approach, which can be extended to a variety of materials discovery and modeling problems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1947

An Investigation of the Low-speed Stability and Control Characteristics of Swept-forward and Swept-back Wing in the Ames 40- by 80-foot Wind Tunnel

An investigation has been made at large scale of the characteristics of highly swept wings. Data were obtained at several angles of sideslip on wings having angles of sweep of plus or minus 45 degrees, plus or minus 30 degrees, and 0 degrees. The airfoil sections of the wings varied from approximately NACA 0015 at the root to NACA 23009 at the tip. Each wing was investigated with flaps under flection, partial-span split flaps deflected 60 degrees, full-span split flaps defected 60 degrees and split-flap-type ailerons deflected plus or minus 15 degrees. Values of maximum lift were obtained at Reynolds numbers raging from 5.7 to 9.2 times 10 to the 6th power. In this report the summarized results are compared with the predictions made by use of the simplified theory for the effect of sweep and with existing small-scale data. The basic wind-tunnel results from which these summary data were taken are included in an appendix. The primary problems accompanying the use of weep as revealed by this investigation are the loss in maximum lift, the high effective dihedral, and the sharp reduction in lateral-control effectiveness. In general, simple theory enables good predictions to be made of the gross effects of sweep but further refinements are necessary to obtain the accuracy required for design purposes. In cases where comparisons can be made, the indications are that, as sweep increases, scale effects diminish and large-scale results approach small-scale results.

Mccormack, Gerald M↗
NASA NTRS1996

Study of the velocity gradient tensor in turbulent flow

The behavior of the velocity gradient tensor, A(ij)=delta u(i)/delta x(j), was studied using three turbulent flows obtained from direct numerical simulation The flows studies were: an inviscid calculation of the interaction between two vortex tubes, a homogeneous isotropic flow, and a temporally evolving planar wake. Self-similar behavior for each flow was obtained when A(ij) was normalized with the mean strain rate. The case of the interaction between two vortex tubes revealed a finite sized coherent structure with topological characteristics predictable by a restricted Euler model. This structure was found to evolve with the peak vorticity as the flow approached singularity. Invariants of A(ij) within this structure followed a straight line relationship of the form: gamma(sup 3)+gammaQ+R=0, where Q and R are the second and third invariants of A(ij), and the eigenvalue gamma is nearly constant over the volume of this structure. Data within this structure have local strain topology of unstable-node/saddle/saddle. The characteristics of the velocity gradient tensor and the anisotropic part of a related acceleration gradient tensor H(ij) were also studied for a homogeneous isotropic flow and a temporally evolving planar wake. It was found that the intermediate principal eigenvalue of the rate-of-strain tensor of H(ij) tended to be negative, with local strain topology of the type stable-node/saddle/saddle. There was also a preferential eigenvalue direction. The magnitude of H(ij) in the wake flow was found to be very small when data were conditioned at high local dissipation regions. This result was not observed in the relatively low Reynolds number simulation of homogeneous isotropic flow. A restricted Euler model of the evolution of A(ij) was found to reproduce many of the topological features identified in the simulations.

Cheng, Wei-Ping↗
NASA NTRS1995

Dust in the small Magellanic Cloud. 2: Dust models from interstellar polarization and extinction data

We study the dust in the Small Magellanic Cloud using our polarization and extinction data (Paper 1) and existing dust models. The data suggest that the monotonic SMC extinction curve is related to values of lambda(sub max), the wavelength of maximum polarization, which are on the average smaller than the mean for the Galaxy. On the other hand, AZV 456, a star with an extinction similar to that for the Galaxy, shows a value of lambda(sub max) similar to the mean for the Galaxy. We discuss simultaneous dust model fits to extinction and polarization. Fits to the wavelength dependent polarization data are possible for stars with small lambda(sub max). In general, they imply dust size distributions which are narrower and have smaller mean sizes compared to typical size distributions for the Galaxy. However, stars with lambda(sub max) close to the Galactic norm, which also have a narrower polarization curve, cannot be fit adequately. This holds true for all of the dust models considered. The best fits to the extinction curves are obtained with a power law size distribution by assuming that the cylindrical and spherical silicate grains have a volume distribution which is continuous from the smaller spheres to the larger cylinders. The size distribution for the cylinders is taken from the fit to the polarization. The 'typical', monotonic SMC extinction curve can be fit well with graphite and silicate grains if a small fraction of the SMC carbon is locked up in the grain. However, amorphous carbon and silicate grains also fit the data well. AZV456, which has an extinction curve similar to that for the Galaxy, has a UV bump which is too blue to be fit by spherical graphite grains.

Rodrigues, C. V.↗
NASA NTRS2003

Superalloy Disk With Dual-Grain Structure Spin Tested

Advanced nickel-base disk alloys for future gas turbine engines will require greater temperature capability than current alloys, but they must also continue to deliver safe, reliable operation. An advanced, nickel-base disk alloy, designated Alloy 10, was selected for evaluation in NASA s Ultra Safe Propulsion Project. Early studies on small test specimens showed that heat treatments that produced a fine grain microstructure promoted high strength and long fatigue life in the bore of a disk, whereas heat treatments that produced a coarse grain microstructure promoted optimal creep and crack growth resistance in the rim of a disk. On the basis of these results, the optimal combination of performance and safety might be achieved by utilizing a heat-treatment technology that could produce a fine grain bore and coarse grain rim in a nickel-base disk. Alloy 10 disks that were given a dual microstructure heat treatment (DMHT) were obtained from NASA s Ultra-Efficient Engine Technology (UEET) Program for preliminary evaluation. Data on small test specimens machined from a DMHT disk were encouraging. However, the benefit of the dual grain structure on the performance and reliability of the entire disk still needed to be demonstrated. For this reason, a high temperature spin test of a DMHT disk was run at 20 000 rpm and 1500 F at the Balancing Company of Dayton, Ohio, under the direction of NASA Glenn Research Center personnel. The results of that test showed that the DMHT disk exhibited significantly lower crack growth than a disk with a fine grain microstructure. In addition, the results of these tests could be accurately predicted using a two-dimensional, axisymmetric finite element analysis of the DMHT disk. Although the first spin test demonstrated a significant performance advantage associated with the DMHT technology, a second spin test on the DMHT disk was run to determine burst margin. The disk burst in the web at a very high speed, over 39 000 rpm, in line with the predicted location and speed. Furthermore, significant growth of the disk was observed before failure, in line with predictions, clearly demonstrating the reliability and safety of the DMHT technology. Although successful spin testing in Ultra Safe's Nickel Disk Program represents a significant milestone for DMHT technology, realistic engine operation will require repeated loading of a DMHT nickel disk. For this reason, a cyclic spin test study of DMHT nickel disk technology has been proposed to start in fiscal year 2003 under NASA's Aviation Safety Program. The goal of this program will be to determine the fatigue failure mechanism in DMHT nickel disks, thereby demonstrating the reliability and safety of DMHT technology under repetitive loading conditions encountered in realistic engine operation.

Gayda, John↗
DOE OSTI2022

SAXS-guided unbiased coarse-grained Monte Carlo simulation for identification of self-assembly nanostructures and dimensions

Recent studies have shown that solvated amphiphiles can form nanostructured self-assemblies called dynamic binary complexes (DBCs) in the presence of ions. Since the nanostructures of DBCs are directly related to their viscoelastic properties, it is important to understand how the nanostructures change under different solution conditions. However, it is challenging to obtain a three-dimensional molecular description of these nanostructures by utilizing conventional experimental characterization techniques or thermodynamic models. To this end, we combined the structural data from small angle X-ray scattering (SAXS) experiments and thermodynamic knowledge from coarse-grained Monte Carlo (CGMC) simulations to identify the detailed three-dimensional nanostructure of DBCs. Specifically, unbiased CGMC simulations are performed with SAXS-guided initial conditions, which aids us to sample accurate nanostructures in a computationally efficient fashion. As a result, an elliptical bilayer nanostructure is obtained as the most probable nanostructure of DBCs whose dimensions are validated by scanning electron microscope (SEM) images. Then, utilizing the obtained molecular model of DBCs, here we could also explain the pH tunability of the system. Overall, our results from SAXS-guided unbiased CGMC simulations highlight that using potential energy combined with SAXS data, we can distinguish otherwise degenerate nanostructures resulting from the inherent ambiguity of SAXS patterns.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Plasma image classification using cosine similarity constrained convolutional neural network

Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei and young stellar objects commonly emit plasma jets in various forms. With the availability of data from plasma jet experiments resembling astrophysical plasma jets, classification of such data would potentially aid in not only investigating the underlying physics of the experiments but also the study of astrophysical jets. In this work we use deep learning to process all of the laboratory plasma images from the Caltech Spheromak Experiment spanning two decades. We found that cosine similarity can aid in feature selection, classify images through comparison of feature vector direction and be used as a loss function for the training of AlexNet for plasma image classification. We also develop a simple vector direction comparison algorithm for binary and multi-class classification. Using our algorithm we demonstrate 93 % accurate binary classification to distinguish unstable columns from stable columns and 92 % accurate five-way classification of a small, labelled data set which includes three classes corresponding to varying levels of kink instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Measurement Uncertainty in One-Of-A-Kind Event Data Analysis

A golden standard in science is to repeat an experiment a statistically significant number of times, recording data using the same set of detectors and the same data analysis methodology. In such case experimental error includes both the range of true values generated by repetitions of the experiment, and measurement uncertainty caused by the detector. They are independent. It is a huge and too frequently used simplification, to assume that one can measure multiple repetitions of an identical experiment, resulting in identical true experimental value. Repetitions, as similar is it is experimentally achievable, have unavoidable built-in differences resulting in a range of the true values rather than in a single value. When modern, very sensitive and well calibrated measurement systems are used, this range is not negligible, and sometimes dominates over the measurement uncertainty. Range of true values depends on built-in differences in physics of the experiment. Stochastic physical processes result typically in a broader range of true values than non-stochastic processes do. Measurement uncertainty depends on a measurement method (properties of the detector not of the experiment). Modern measurement methods, including digital ones, frequently make the measurement uncertainty very small. When data from one–of –a kind experiment are analyzed, only the measurement uncertainty is reported. It provides no information about the range of true experimental values, neither about reliability of a reported data point. Reliability of a data point is in general independent from its measurement uncertainty. However, in practice reliable measurement methods frequently have high measurement uncertainty, while low reliability methods are applied to limit measurement uncertainty. Comparison of reliable data with high measurement uncertainty to not so reliable data measured with low uncertainty is discussed – in different scenarios different data analysis methods are applicable. Methods for data analysis from an experiment repeated statistically significant number of times are very well developed. They do not require a detailed expertise in physics of an experiment, nor in the properties of the measurement system used, and meaning of the reported uncertainty is well understood in any scientific community. It all changes when data from one-of-a-kind experiment is analyzed. Analyst’s expertise is required both in the physics of the experiment and in all aspects of the measurement system, all possible malfunctions. Data users must remember that only measurement uncertainty is reported from any one-of-a-kind experiment. Theory with simulations may provide estimation of expected built-in differences in the experiment, and by this of expected range of true values for a given experiment; yet measurement uncertainty can never be used in place of the range of true experimental values.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRSDate not supplied

Optimizing a Small RNAseq Analysis Pipeline for NASA GeneLab Using Open-Source Tools and Libraries

Small RNA sequencing (small RNAseq) is a powerful tool for studying the regulation of gene expression in various organisms. Small RNAseq has been leveraged in space biology research to study how expression of small RNAs, e.g. micro RNAs (miRNAs), small interfering RNAs (siRNAs), and piwi-interacting RNAs (piRNAs), change upon exposure to the space environment. NASA GeneLab currently hosts small RNAseq raw data derived from space-relevant experiments on the Open Science Data Repository (OSDR). To maximize the accessibility of these data to the scientific community, in addition to hosting raw data, which is only interpretable by bioinformaticians, GeneLab plans to process all small RNAseq datasets and make those processed data available to the scientific community via the OSDR. In this study, we present the development of the GeneLab standardized pipeline for processing small RNAseq datasets. Using human, plant, and synthetic small RNAseq datasets, we interrogate various open-source software and publicly available databases to evaluate their accuracy and reproducibility in each step of the pipeline. For quality control and adapter detection and trimming, we evaluated TrimGalore!, FASTX, SeqKit, and DNApi methods to optimize alignment to reference genomes. We compared BWA, Bowtie, and Bowtie2 to determine the optimal alignment tool. For each alignment tool we also assessed various reference databases, including Ensembl reference genomes and different types of small RNA reference databases, including genome, hairpin, and miRNA references from the miRbase and MirGeneDB databases. To quantify the aligned data, we compared SAMtools, HTSeq, and RSEM for counting alignment events from each alignment tool used. Finally, we evaluated various tools, including DESeq2 and EdgeR, for data normalization and subsequent differential expression analysis. We will present the results from our comparative analyses for each pipeline step and propose a consensus pipeline for processing small RNAseq data derived from various organisms exposed to the space environment.

SmallRNAseq, NASA GeneLab, quality control, adapte↗
NASA NTRS2015

Physical Models of Layered Polar Firn Brightness Temperatures from 0.5 to 2 GHz

We investigate physical effects influencing 0.5-2 GHz brightness temperatures of layered polar firn to support the Ultra Wide Band Software Defined Radiometer (UWBRAD) experiment to be conducted in Greenland and in Antarctica. We find that because ice particle grain sizes are very small compared to the 0.5-2 GHz wavelengths, volume scattering effects are small. Variations in firn density over cm- to m-length scales, however, cause significant effects. Both incoherent and coherent models are used to examine these effects. Incoherent models include a 'cloud model' that neglects any reflections internal to the ice sheet, and the DMRT-ML and MEMLS radiative transfer codes that are publicly available. The coherent model is based on the layered medium implementation of the fluctuation dissipation theorem for thermal microwave radiation from a medium having a nonuniform temperature. Density profiles are modeled using a stochastic approach, and model predictions are averaged over a large number of realizations to take into account an averaging over the radiometer footprint. Density profiles are described by combining a smooth average density profile with a spatially correlated random process to model density fluctuations. It is shown that coherent model results after ensemble averaging depend on the correlation lengths of the vertical density fluctuations. If the correlation length is moderate or long compared with the wavelength (approximately 0.6x longer or greater for Gaussian correlation function without regard for layer thinning due to compaction), coherent and incoherent model results are similar (within approximately 1 K). However, when the correlation length is short compared to the wavelength, coherent model results are significantly different from the incoherent model by several tens of kelvins. For a 10-cm correlation length, the differences are significant between 0.5 and 1.1 GHz, and less for 1.1-2 GHz. Model results are shown to be able to match the v-pol SMOS data closely and predict the h-pol data for small observation angles.

layered polar firn emission↗