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All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Approach for Propagating Radiometric Data Uncertainties Through NASA Ocean Color Algorithms

Spectroradiometric satellite observations of the ocean are commonly referred to as “ocean color” remote sensing. NASA has continuously collected, processed, and distributed ocean color datasets since the launch of the Sea-viewing Wide-field-of-view Sensor (SeaWiFS) in 1997. While numerous ocean color algorithms have been developed in the past two decades that derive geophysical data products from sensor-observed radiometry, few papers have clearly demonstrated how to estimate measurement uncertainty in derived data products. As the uptake of ocean color data products continues to grow with the launch of new and advanced sensors, it is critical that pixel-by-pixel data product uncertainties are estimated during routine data processing. Knowledge of uncertainties can be used when studying long-term climate records, or to assist in the development and performance appraisal of bio-optical algorithms. In this method paper we provide a comprehensive overview of how to formulate first-order first-moment (FOFM) calculus for propagating radiometric uncertainties through a selection of bio-optical models. We demonstrate FOFM uncertainty formulations for the following NASA ocean color data products: chlorophyll-a pigment concentration (Chl), the diffuse attenuation coefficient at 490 nm (K(sub d,490)), particulate organic carbon (POC), normalized fluorescent line height (nflh), and inherent optical properties (IOPs). Using a quality-controlled in situ hyperspectral remote sensing reflectance (R(sub rs,i)) dataset, we show how computationally inexpensive, yet algebraically complex, FOFM calculations may be evaluated for correctness using the more computationally expensive Monte Carlo approach. We compare bio-optical product uncertainties derived using our test R(sub rs) dataset assuming spectrally-flat, uncorrelated relative uncertainties of 1, 5, and 10%. We also consider spectrally dependent, uncorrelated relative uncertainties in R(sub rs). The importance of considering spectral covariances in R(sub rs), where practicable, in the FOFM methodology is highlighted with an example SeaWiFS image. We also present a brief case study of two POC algorithms to illustrate how FOFM formulations may be used to construct measurement uncertainty budgets for ecologically-relevant data products. Such knowledge, even if rudimentary, may provide useful information to end-users when selecting data products or when developing their own algorithms.

Bio-optics↗
DOE OSTI2020

Assessment of the degree of hydration of ocular surface tissues using THz reflectometry

Using the effective medium model, the complex permittivity of the ocular surface system in the THz frequency range is considered. The penetration depth of THz radiation and the sensitivity of the reflected component to the dynamics of evaporation of the tear film are discussed. The results of in vivo experiments aimed to determine the reflection coefficient of the ocular surface using continuous THz reflectometers are well described using the developed model. (paper)

36 MATERIALS SCIENCE↗
DOE OSTI2019

Obtaining the complex optical constants n and k via quantitative absorption measurements in KBr pellets

Reflectance (emittance) spectroscopy, especially at infrared wavelengths, continues to grow in utility as an analytical technique for contact, standoff, and remote sensing. The reflectance spectra of solids, however, are complex, depending on many parameters, even for the same material. Granule or powder particle size, crystal morphology, layer thickness, and substrate material all affect the spectral distribution of reflected light. However, such phenomena can all be modeled if the optical constants n(?) and k(?) are available. If the quantitative absorption coefficient K(?) is known, the k value can be obtained via the relation k(?) = 2.303K(?)/4p?. The absorption coefficient can in turn be derived from a simple KBr-pellet infrared absorption measurement, provided the pellet mass ratio is prepared quantitatively. The method requires the pellet’s mass and diameter, along with the analyte mass fraction and density. In this paper we demonstrate the requisite experimental details in preparing the pellets, as well as methods to reduce light scattering in order to obtain more quantitative values. Theoretical methods to derive the related optical constants will also be detailed, in particular the assumptions used to obtain the scalar refractive index n. Ideally, this value is known or measured separately, but in some cases we have found that it can be approximated (first approximation) for most organic chemicals by n~1.5 at the shortest wavelength. The results are presented for a couple of species.

optical constants, solids, KBr pellet↗
NASA NTRS1989

Narrow bandgap semiconducting silicides: Intrinsic infrared detectors on a silicon chip

Polycrystalline thin films of CrSi2, LaSi2, and ReSi2 were grown on silicon substrates. Normal incidence optical transmittance and reflectance measurements were made as a function of wavelength. It was demonstrated that LaSi2 is a metallic conductor, but that CrSi2 and ReSi2 are, in fact, narrow bandgap semiconductors. For CrSi2, the complex index of refraction was determined by computer analysis of the optical data. From the imaginary part, the optical absorption coefficient was determined as a function of photon energy. It was shown that CrSi2 possesses an indirect forbidden energy gap of slightly less than 0.31 eV, and yet it is a very strong absorber of light above the absorption edge. On the other hand, the ReSi2 films exhibit an absorption edge in the vicinity of 0.2 eV. Measurements of the thermal activation energy of resistivity for ReSi2 indicate a bandgap of 0.18 eV. It is concluded that the semiconducting silicides merit further investigation for development as new silicon-compatible infrared detector materials.

Mahan, John E.↗
DOE OSTI2026

Generation of random geological models using multi-randomization for machine learning

Generating high-fidelity geological models is essential for advancing machine learning (ML) methods in automated seismic interpretation. For instance, seismic images paired with corresponding fault labels are foundational for ML-based fault detection from seismic migration sections. While several open-access datasets of random geological models exist, open-source tools specifically designed to produce large volumes of such models for ML applications remain scarce. To address this gap, we present RGM (Random Geological Model), an open-source software package for efficiently generating 2D and 3D synthetic geological models tailored for ML workflows. RGM supports the creation of diverse model components, including medium property distributions (P-/S-wave velocities and density), seismic reflectivity images (i.e., synthetic migration sections), relative geological time, and discrete fault attributes such as probability, dip, strike, rake, and displacement. It also accommodates the creation of complex geological features such as salt bodies and unconformities. The model generation algorithm employs a multi-randomization strategy, yielding an effectively infinite-dimensional model space that encompasses a wide range of geological scenarios and associated seismic features. Furthermore, RGM incorporates a method to generate synthetic elastic migration images using analytical elastic reflection coefficients combined with frequency-dependent scaling. This functionality enables the creation of training datasets for ML models that leverage elastic seismic images. RGM is implemented in modern object-oriented Fortran, allowing users to flexibly control statistical parameters governing model variability. We demonstrate the capability, performance, and geological realism of the package through comprehensive 2D and 3D examples.

58 GEOSCIENCES↗
DOE OSTI2017

Structural Emergence in Particle Dispersions

Particle dispersions, such as pigment-based inks, comprise weakly bound, milled nanoparticles. The properties of these pigments depend on both their chemical composition and a rather complex structural hierarchy which emerges from these dispersions. The emergence of structure under semidilute conditions is related to the structure of the dilute particles, the particle spacing (mesh size), processing history, and the interaction potential. Kinetic simulations could predict such emergence using these input parameters. In this paper, organic pigments are studied as an example of the importance of emergent structure to predict properties such as brilliance and opacity. Organic pigments are used to impart color to commercial inks, plastics, coatings, and cosmetics. In many cases, dilute pigments are mass fractal structures consisting of aggregated nanoparticles held together by weak van der Waals forces. In water, surfactant is added to create a pigment dispersion (an ink). The final properties of a pigment emerge from a complex interplay between aggregation and dispersion of aggregates as a function of concentration. Samples of the organic pigment yellow 14, PY14, were milled to four primary particle sizes to study the effect on structural emergence. The interaction between surfactant-stabilized PY14 aggregates in an aqueous medium was quantified by the second virial coefficient, A 2 , which reflects long-range interactions. The degree of aggregation is associated with short-range attractive interactions between primary particles. In this series of pigments, the degree of aggregation increases dramatically with reduction in primary particle size. Concurrently, the second-order virial coefficient, A 2 , increases reflecting stronger long-range repulsive interactions with particle size. Structural emergence can be understood through the percolation concentration and the filler mesh size. A 2 is translated into a repulsive interaction potential for use in dissipative particle dynamics simulations to enable predictive modeling. Furthermore, this description of the interactions between dispersed pigment aggregates allows for a more scientific and predictive approach to understand structural emergence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Spread Spectrum Time Domain Reflectometry (SSTDR) Digital Twin Simulation of Photovoltaic Systems for Fault Detection and Location

Utilizing spread spectrum time domain reflectometry (SSTDR) to detect, locate, and characterize faults in photovoltaic (PV) systems is examined in this paper. We present a method to obtain the model parameters that are needed to produce digital twin SSTDR responses for PV systems. The digital twin SSTDR responses could be used to predict faults within the PV systems. Here, the model parameters are the reflection and transmission coefficients at each impedance discontinuity in the PV system along with the propagation coefficients across each PV cable segment. We obtain model parameter by applying inverse modeling techniques to experimental SSTDR data associated with PV systems. Our model parameters can be used in any digital twin simulation method for modeling reflectometry in frequency-dependent and complex loads. For validation, we used the model parameters in a graph network simulation engine and adapted it to be used for SSTDR digital twin simulations in PV systems. We produced simulations for 0 to 10 PV modules connected in series. We also simulated SSTDR responses for open circuit disconnections in a PV setup containing 10 PV modules in series. Results show that all but one simulated disconnect locations match experimental disconnection locations of the same setup with an error of less than 5%.

14 SOLAR ENERGY↗
NASA NTRS1999

Development of Analysis Methods for Designing with Composites

The project involved the development of new analysis methods to achieve efficient design of composite structures. We developed a complex variational formulation to analyze the in-plane and bending coupling response of an unsymmetrically laminated plate with an elliptical cutout subjected to arbitrary edge loading as shown in Figure 1. This formulation utilizes four independent complex potentials that satisfy the coupled in-plane and bending equilibrium equations, thus eliminating the area integrals from the strain energy expression. The solution to a finite geometry laminate under arbitrary loading is obtained by minimizing the total potential energy function and solving for the unknown coefficients of the complex potentials. The validity of this approach is demonstrated by comparison with finite element analysis predictions for a laminate with an inclined elliptical cutout under bi-axial loading.The geometry and loading of this laminate with a lay-up of [-45/45] are shown in Figure 2. The deformed configuration shown in Figure 3 reflects the presence of bending-stretching coupling. The validity of the present method is established by comparing the out-of-plane deflections along the boundary of the elliptical cutout from the present approach with those of the finite element method. The comparison shown in Figure 4 indicates remarkable agreement. The details of this method are described in a manuscript by Madenci et al. (1998).

Madenci, E.↗
NASA NTRS2015

Further Research on the Electrification of Pyrocumulus Clouds

Past research on pyrocumulus electrification has demonstrated that a variety of lightning types can occur, including cloud‐to‐ground (CG) flashes, sometimes of dominant positive polarity, as well as small intra‐cloud (IC) discharges in the upper levels of the pyro‐cloud. In Colorado during summer 2012, the first combined polarimetric radar, multi‐Doppler radar, and three‐dimensional lightning mapping array (LMA) observations of lightning‐producing pyrocumulus were obtained. These observations suggested that the National Lightning Detection Network (NLDN) was not sensitive enough to detect the small IC flashes that appear to be the dominant mode of lightning in these clouds. However, after an upgrade to the network in late 2012, the NLDN began detecting some of this pyrocumulus lightning. Multiple pyrocumulus clouds documented by the University of Wisconsin for various fires in 2013 and 2014 (including over the Rim, West Fork Complex, Yarnell Hill, Hardluck, and several other incidents) are examined and reported on here. This study exploits the increased‐sensitivity NLDN as well as the new nationwide U.S. network of polarimetric Next‐generation Radars (NEXRADs). These observations document the common occurrence of a polarimetric "dirty ice" signature ‐ modest reflectivities (20‐40+ dBZ), near‐zero differential reflectivity, and reduced correlation coefficient (less than 0.9) ‐ prior to the production of lightning. This signature is indicative of a mixture of ash and ice particles in the upper levels of the pyro‐cloud (less than ‐20 C), with the ice interpreted as being necessary for pyro‐cloud electrification. Pseudo‐Geostationary Lightning Mapper (GLM) data will be produced from the 2012 LMA observations, and the ability of GLM to detect small pyrocumulus ICs will be assessed. The utility of lightning and polarimetric radar for documenting rapid wildfire growth, as well as for documenting pyrocumulus impacts on the composition of the upper troposphere/lower stratosphere (UTLS), will be discussed.

Lang, Timothy J.↗
NASA NTRS1974

Electromagnetic diffraction efficiencies for plane reflection diffraction gratings

The theory and computer programs, based on electromagnetic theory, for the analysis and design of echelle gratings were developed. The gratings are designed for instruments that operate in the ultraviolet portion of the spectrum. The theory was developed so that the resulting computer programs will be able to analyze deep (up to 30 wavelengths) gratings by including as many as 100 real or homogeneous diffraction orders. The program calculates the complex amplitude coefficient for each of the diffracted orders. A check on the numerical method used to solve the integral equations is provided by a conservation of energy calculation.

Marathay, A. S.↗
DOE OSTI2015

The role of nanoparticle rigidity on the diffusion of linear polystyrene in a polymer nanocomposite

The impact of the inclusion of a nanoparticle in a polymer matrix on the dynamics of the polymer chains is an area of recent interest. In this article, we describe the role of nanoparticle rigidity or softness on the impact of the presence of that nanoparticle on the diffusive behavior of linear polymer chains. The neutron reflectivity results clearly show that the inclusion of 10 nm soft nanoparticles in a polymer matrix (R g ~ 20 nm) increases the diffusion coefficient of the linear polymer chain. Surprisingly, thermal analysis shows that these nanocomposites exhibit an increase in their glass transition temperature, which is incommensurate with an increase in free volume. Therefore, it appears that this effect is more complex than a simple plasticizing effect. Results from small-angle neutron scattering of the nanoparticles in solution show a structure that consists of a gel like core with a corona of free chain ends and loops. Furthermore, the increase in linear polymer diffusion may be related to an increase in constraint release mechanisms in the reptation of the polymer chain, in a similar manner to that which has been reported for the diffusion of linear polymer chains in the presence of star polymers.

36 MATERIALS SCIENCE↗
NASA NTRS1972

The interaction of moderately strong shock waves with thick perforated walls of low porosity

A theoretical prediction is given of the flow through thick perforated walls of low porosity resulting from the impingement of a moderately strong traveling shock wave. The model was a flat plate positioned normal to the direction of the flow. Holes bored in the plate parallel to the direction of the flow provided nominal hole length-to-diameter ratios of 10:1 and an axial porosity of 25 percent of the flow channel cross section. The flow field behind the reflected shock wave was assumed to behave as a reservoir producing a quasi-steady duct flow through the model. Rayleigh and Fanno duct flow theoretical computations for each of three possible auxiliary wave patterns that can be associated with the transmitted shock (to satisfy contact surface compatibility) were used to provide bounding solutions as an alternative to the more complex influence coefficients method. Qualitative and quantitative behavior was verified in a 1.5- by 2.0-in. helium shock tube. High speed Schlieren photography, piezoelectric pressure-time histories, and electronic-counter wave speed measurements were used to assess the extent of correlation with the theoretical flow models. Reduced data indicated the adequacy of the bounding theory approach to predict wave phenomena and quantitative response.

Grant, D. J.↗
NASA NTRS1974

Dielectric properties of soils as a function of moisture content

Soil dielectric constant measurements are reviewed and the dependence of the dielectric constant on various soil parameters is determined. Moisture content is given special attention because of its practical significance in remote sensing and because it represents the single most influential parameter as far as soil dielectric properties are concerned. Relative complex dielectric constant curves are derived as a function of volumetric soil water content at three frequencies (1.3 GHz, 4.0 GHz, and 10.0 GHz) for each of three soil textures (sand, loam, and clay). These curves, presented in both tabular and graphical form, were chosen as representative of the reported experimental data. Calculations based on these curves showed that the power reflection coefficient and emissivity, unlike skin depth, vary only slightly as a function of frequency and soil texture.

Cihlar, J.↗
NASA NTRS1983

Sound radiation from annular ducts/nozzles using modal decomposition of in-duct acoustic power

Using a refined acoustic impulse technique, an experimental program was carried out to determine the proper procedure for measuring the acoustic power for both incident and reflected sound fields for annular ducts with and without nozzles at various flow conditions. Several radial and azimuthal pressure measurements were made, and using these complex pressure data, the modal content of the pressure field was determined. A mathematical approach for the modal decomposition of annular duct acoustic power was developed. The acoustic power due to each individual mode and also their total sum were derived. The acoustic characteristics of annular duct-nozzle systems were studied at various flow conditions. The results derived from the experiments include the termination reflection coefficient, the normalized transmission coefficients, the power transfer functions and the power imbalance.

Salikuddin, M.↗
NASA NTRS1989

State-of-the-art fiber optics for short distance frequency reference distribution

A number of recently developed fiber-optic components that hold the promise of unprecedented stability for passively stabilized frequency distribution links are characterized. These components include a fiber-optic transmitter, an optical isolator, and a new type of fiber-optic cable. A novel laser transmitter exhibits extremely low sensitivity to intensity and polarization changes of reflected light due to cable flexure. This virtually eliminates one of the shortcomings in previous laser transmitters. A high-isolation, low-loss optical isolator has been developed which also virtually eliminates laser sensitivity to changes in intensity and polarization of reflected light. A newly developed fiber has been tested. This fiber has a thermal coefficient of delay of less than 0.5 parts per million per deg C, nearly 20 times lower than the best coaxial hardline cable and 10 times lower than any previous fiber-optic cable. These components are highly suitable for distribution systems with short extent, such as within a Deep Space Communications Complex. Here, these new components are described and the test results presented.

Lutes, G. F.↗
DOE OSTI2024

Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model

The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. Determining if and how the features of these exogenous variables (e.g., sound frequency, reach angle) are reflected in population neural activity is important for understanding how the brain operates. Often, high-dimensional neural population activity is confined to low-dimensional latent spaces. However, many current methods fail to extract latent spaces that are clearly structured by exogenous variables. This has contributed to a debate about whether or not brains should be thought of as dynamical systems or representational systems. Here, we developed a new latent process Bayesian regression framework, the orthogonal stochastic linear mixing model (OSLMM) which introduces an orthogonality constraint amongst time-varying mixture coefficients, and provide Markov chain Monte Carlo inference procedures. We demonstrate superior performance of OSLMM on latent trajectory recovery in synthetic experiments and show superior computational efficiency and prediction performance on several real-world benchmark data sets. We primarily focus on demonstrating the utility of OSLMM in two neural data sets: μ ECoG recordings from rat auditory cortex during presentation of pure tones and multi-single unit recordings form monkey motor cortex during complex arm reaching. We show that OSLMM achieves superior or comparable predictive accuracy of neural data and decoding of external variables (e.g., reach velocity). Most importantly, in both experimental contexts, we demonstrate that OSLMM latent trajectories directly reflect features of the sounds and reaches, demonstrating that neural dynamics are structured by neural representations. Together, these results demonstrate that OSLMM will be useful for the analysis of diverse, large-scale biological time-series datasets.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1996

Numerical Analysis of the Sea State Bias for Satellite Altimetry

Theoretical understanding of the dependence of sea state bias (SSB) on wind wave conditions has been achieved only for the case of a unidirectional wind-driven sea. Recent analysis of Geosat and TOPEX altimeter data showed that additional factors, such as swell, ocean currents, and complex directional properties of realistic wave fields, may influence SSB behavior. Here we investigate effects of two-dimensional multimodal wave spectra using a numerical model of radar reflection from a random, non-Gaussian surface. A recently proposed ocean wave spectrum is employed to describe sea surface statistics. The following findings appear to be of particular interest: (1) Sea swell has an appreciable effect in reducing the SSB coefficient compared with the pure wind sea case but has less effect on the actual SSB owing to the corresponding increase in significant wave height. (2) Hidden multimodal structure (the two-dimensional wavenumber spectrum contains separate peaks, for swell and wind seas, while the frequency spectrum looks unimodal) results in an appreciable change of SSB. (3) For unimodal, purely wind-driven seas, the influence of the angular spectral width is relatively unimportant; that is, a unidirectional sea provides a good qualitative model for SSB if the swell is absent. (4) The pseudo wave age is generally much better fo parametrization the SSB coefficient than the actual wave age (which is ill-defined for a multimodal sea) or wind speed. (5) SSB can be as high as 5% of the significant wave height, which is significantly greater than predicted by present empirical model functions tuned on global data sets. (6) Parameterization of SSB in terms of wind speed is likely to lead to errors due to the dependence on the (in practice, unknown) fetch.

Glazman, R. E.↗
NASA NTRS1985

Contrasts among bidirectional reflectance of leaves, canopies, and soils

Simple models are presented for predicting the bidirectional reflectance distribution functions (BRDFs) for soils and plant canopies viewed from various directions. BRDFs are predicted for bare soil, individual leaves, and plant canopies, and the results are compared with measurements and a three coefficient empirical equation. BRDF measurements for corn and soybean leaves are presented to contrast with canopy and soil distributions. Estimates of the soil, canopy, and leaf BRDFs are combined into a model called Cupid to predict BRDFs for complex natural surfaces.

Norman, J. M.↗