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All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Deciphering the Spectra of Flowers to Map Landscape-scale Blooming Dynamics

Like leaves, floral coloration is driven by inherent optical properties, which are determined by pigments, scattering structure, and thickness. However, establishing the relative contribution of these factors to canopy spectral signals is usually limited to in-situ observations. Modeling flowering dynamics (e.g., blooming duration, spatial distribution) at the landscape scale may reveal insights into ecological processes and phenological adaptations to environmental changes. Multitemporal visible to shortwave infrared (VSWIR) imaging spectroscopy observations are especially suited for such efforts. Reflectance in this spectral range is sensitive to major flower pigments, flowering phenology traces, and biophysical differences between flowers and other plant parts. We explored how flowers contribute to spectral signals using a time series of imagery from the Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) collected as part of the SBG High-Frequency Time Series (SHIFT) campaign as a case study. Airborne data were collected weekly during the spring of 2022 across two natural reserves in California. Field spectra were gathered from blooming plots at leaf, flower, and canopy levels at two time points during the campaign. The processed data was used to investigate flowering species' spectro-temporal variation and spatial distribution using Spectral Mixture Residual, Gaussian clustering techniques, and a proposed narrow-band flowering index. Linear spectral unmixing allowed the computation of the weighted contribution of four major high-variance endmembers (leaves, flowers, soil, dark) and low-variance residual signal that comprises subtle spectral features used to track biophysical processes. The reflectance residual was projected on a low principal component basis to characterize flowering clusters' variation and spatial distribution based on the Gaussian mixture model, providing an uncertainty metric to assess the results. Mapping flowering events from modeling spectro-temporal dynamics throughout the season, from pre-blooming to post-flowering stages, allowed us to identify gradient variations in spectral features within the VSWIR spectral range linked to flowering pigments. Time series of the Mixture Residual Blooming Index and the Red-Edge Normalized Difference Vegetation Index revealed specific flowering and greenness phenophases across the two main species (Coreopsis gigantea, Artemisia californica) in the flowering areas. Overall, our approach opens opportunities for future satellite monitoring of floral cycles at broader scales.

Yoseline Angel↗
NASA NTRSDate not supplied

Synthesis Analysis of Mulit-Dimensional Ozone Lidar Measurements in Coastal Environments Toward Improving Ozone Simulation

Large surface ozone variations are frequently observed in coastal regions which makes the modeling of air quality in these regions challenging. The ability to properly model coastal regions relies heavily on the proper detailed observations. There have been three air quality studies (over Chesapeake Bay and the Long Island Sound) that focused on thorough measurements in these complex coastal regions; OWLETS 1 & 2 and LISTOS. Over the course of the campaigns, there were surface ozone observations taken from LIDAR (LIght Detection And Ranging) instruments for a total of 89 days at a high temporal rate. We developed a clustering method that characterizes the multiple timestamps of measurements into a range of ozone events that are specific to these coastal regions. We simulated coastal ozone for these cluster groups using WRF-GC and WRF-Chem to identify gaps within the model. Using the characterized ozone clusters, we were able to identify multiple coastal mechanisms that led to incorrect model simulations.

Claudia Bernier↗
NASA NTRS2015

Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics

A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.

composite materials↗
NASA NTRS1999

Formation and Levitation of Unconfined Droplet Clusters

Combustion experiments using arrays of droplets seek to provide a link between single droplet combustion phenomena and the behavior of complex spray combustion systems. Both single droplet and droplet array studies have been conducted in microgravity to better isolate the droplet interaction phenomena and eliminate or reduce the confounding effects of buoyancy-induced convection. In most experiments involving droplet arrays, the droplets are supported on fibers to keep them stationary and close together before the combustion event. The presence of the fiber, however, disturbs the combustion process by introducing a source of heat transfer and asymmetry into the configuration. As the number of drops in a droplet array increases, supporting the drops on fibers becomes less practical because of the cumulative effect of the fibers on the combustion process. The overall objective of this research is to study the combustion of well-characterized drop clusters in a microgravity environment. Direct experimental observations and measurements of the combustion of droplet clusters would fill a large gap in our current understanding of droplet and spray combustion and provide unique experimental data for the verification and improvement of spray combustion models. This paper describes current work on the design and performance of an apparatus to generate and stabilize droplet clusters using acoustic and electrostatic forces.

Liu, S.↗
NASA NTRS2001

Combustion of Unconfined Droplet Clusters in Microgravity

Combustion experiments using arrays of droplets seek to provide a link between single droplet combustion phenomena and the behavior of complex spray combustion systems. Both single droplet and droplet array studies have been conducted in microgravity to better isolate the droplet interaction phenomena and eliminate or reduce the confounding effects of buoyancy-induced convection. In most experiments involving droplet arrays, the droplets are supported on fibers to keep them stationary and close together before the combustion event. The presence of the fiber, however, disturbs the combustion process by introducing a source of heat transfer and asymmetry into the configuration. As the number of drops in a droplet array increases, supporting the drops on fibers becomes less practical because of the cumulative effect of the fibers on the combustion process. To eliminate the effect of the fiber, several researchers have conducted microgravity experiments using unsupported droplets. Jackson and Avedisian investigated single, unsupported drops while Nomura et al. studied droplet clouds formed by a condensation technique. The overall objective of this research is to extend the study of unsupported drops by investigating the combustion of well-characterized drop clusters in a microgravity environment. Direct experimental observations and measurements of the combustion of droplet clusters would fill a large gap in our current understanding of droplet and spray combustion and provide unique experimental data for the verification and improvement of spray combustion models. In this work, the formation of drop clusters is precisely controlled using an acoustic levitation system so that dilute, as well as dense clusters can be created and stabilized before combustion in microgravity is begun. This paper describes the design and performance of the 1-g experimental apparatus, some preliminary 1-g results, and plans for testing in microgravity.

Ruff, G. A.↗
NASA NTRS2000

Characterization of Acousto-Electric Cluster and Array Levitation and its Application to Evaporation

An acousto-electric levitator has been developed to study the behavior of liquid drop and solid particle clusters and arrays. Unlike an ordinary acoustic levitator that uses only a standing acoustic wave to levitate a single drop or particle, this device uses an extra electric static field and the acoustic field simultaneously to generate and levitate charged drops in two-dimensional arrays in air without any contact to a solid surface. This cluster and array generation (CAG) instrument enables us to steadily position drops and arrays to study the behavior of multiple drop and particle systems such as spray and aerosol systems relevant to the energy, environmental, and material sciences.

Robert E. Apfel↗
NASA NTRS1995

Characterization of silicon-carbon clusters by infrared laser spectroscopy. The nu 1 band of SiC4

The nu 1 fundamental vibration of linear SiC4 has been observed by infrared diode laser spectroscopy of a supersonic cluster beam. Twenty-four rovibrational transitions were measured in the spectral region of 2094.6 to 2097.1 cm-1, the rotational temperature was 10 K. A combined least-squares fit of these transitions with previously reported microwave data yielded the following molecular constants: nu 1 = 2095.45806(37) cm-1, B" = 0.051161131(52) cm-1, and B' = 0.0509157(96) cm-1. These results are compared to vibrational spectroscopy measurements of SiC4 trapped in a solid Ar matrix and to ab initio calculations.

NASA Discipline Exobiology↗
NASA NTRS1994

Characterization of silicon-carbon clusters by infrared laser spectroscopy: the nu 3(sigma u) band of linear Si2C3

The nu 3(sigma u) fundamental vibration of 1 sigma g+ Si2C3 has been observed using a laser vaporization-supersonic cluster beam-diode laser spectrometer. Forty rovibrational transitions were measured in the range of 1965.8 to 1970.9 cm-1 with a rotational temperature of 10-15 K. A least-squares fit of these transitions yielded the following molecular constants: nu 3(sigma u)=1968.188 31(18) cm-1, B"=0.031 575 1(60) cm-1, and B'=0.031 437 4(57) cm-1. These results are in excellent agreement with recent Fourier transform infrared (FTIR) measurements of Si2C3 trapped in a solid Ar matrix [J. Chem. Phys. 100, 181(1994)] and with ab initio calculations [J. Chem. Phys. 100, 175 (1994)] which suggest cumulenic-like bonding for Si2C3, analogous to the isovalent C5 carbon cluster.

Non-NASA Center↗
NASA NTRS1990

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

Advanced oxide thermal barrier coatings have been developed by incorporating multi- component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma- sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia-yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging fiom 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Zhu, Dongming↗
NASA NTRS2003

Defect Clustering and Nano-Phase Structure Characterization of Multi-Component Rare Earth Oxide Doped Zirconia-Yttria Thermal Barrier Coatings

Advanced oxide thermal barrier coatings have been developed by incorporating multi-component rare earth oxide dopants into zirconia-yttria to effectively promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nano-scale phases within the coating systems. The presence of these nano-sized defect clusters has found to significantly reduce the coating intrinsic thermal conductivity, improve sintering resistance, and maintain long-term high temperature stability. In this paper, the defect clusters and nano-structured phases, which were created by the addition of multi-component rare earth dopants to the plasma-sprayed and electron-beam physical vapor deposited thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The defect cluster size, distribution, crystallographic and compositional information were investigated using high-resolution TEM lattice imaging, selected area diffraction (SAD), electron energy-loss spectroscopy (EELS) and energy dispersive spectroscopy (EDS) analysis techniques. The results showed that substantial defect clusters were formed in the advanced multi-component rare earth oxide doped zirconia- yttria systems. The size of the oxide defect clusters and the cluster dopant segregation was typically ranging from 5 to 50 nm. These multi-component dopant induced defect clusters are an important factor for the coating long-term high temperature stability and excellent performance.

Zhu, Dongming↗
NASA NTRS2004

Defect Clustering and Nano-phase Structure Characterization of Multicomponent Rare Earth-Oxide-Doped Zirconia-Yttria Thermal Barrier Coatings

Advanced thermal barrier coatings (TBCs) have been developed by incorporating multicomponent rare earth oxide dopants into zirconia-based thermal barrier coatings to promote the creation of the thermodynamically stable, immobile oxide defect clusters and/or nanophases within the coating systems. In this paper, the defect clusters, induced by Nd, Gd, and Yb rare earth dopants in the zirconia-yttria thermal barrier coatings, were characterized by high-resolution transmission electron microscopy (TEM). The TEM lattice imaging, selected area diffraction (SAD), and electron energy-loss spectroscopy (EELS) analyses demonstrated that the extensive nanoscale rare earth dopant segregation exists in the plasma-sprayed and electron-physical-vapor-deposited (EB PVD) thermal barrier coatings. The nanoscale concentration heterogeneity and the resulting large lattice distortion promoted the formation of parallel and rotational defective lattice clusters in the coating systems. The presence of the 5-to 100-nm-sized defect clusters and nanophases is believed to be responsible for the significant reduction of thermal conductivity, improved sintering resistance, and long-term high temperature stability of the advanced thermal barrier coating systems.

Zhu, Dongming↗
NASA NTRS2005

Small-Scale Drop Size Variability: Impact on Estimation of Cloud Optical Properties

Most cloud radiation models and conventional data processing techniques assume that the mean number of drops of a given radius is proportional to volume. The analysis of microphysical data on liquid water drop sizes shows that, for sufficiently small volumes, this proportionality breaks down; the number of cloud drops of a given radius is instead proportional to the volume raised to a drop size-dependent nonunit power. The coefficient of proportionality, a generalized drop concentration, is a function of the drop size. For abundant small drops the power is unity as assumed in the conventional approach. However, for rarer large drops, it falls increasingly below unity. This empirical fact leads to drop clustering, with the larger drops exhibiting a greater degree of clustering. The generalized drop concentration shows the mean number of drops per cluster, while the power characterizes the occurrence frequency of clusters. With a fixed total number of drops in a cloud, a decrease in frequency of clusters is accompanied by a corresponding increase in the generalized concentration. This initiates a competing process missed in the conventional models: an increase in the number of drops per cluster enhances the impact of rarer large drops on cloud radiation while a decrease in the frequency suppresses it. Because of the nonlinear relationship between the number of clustered drops and the volume, these two opposite tendencies do not necessarily compensate each other. The data analysis suggests that clustered drops likely have a stronger radiative impact compared to their unclustered counterpart; ignoring it results in underestimation of the contribution from large drops to cloud horizontal optical path.

Knyazikhin, Y.↗
NASA NTRS2004

Using Fuzzy Clustering for Real-time Space Flight Safety

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Lee, Charles↗
NASA NTRS1999

Characterizing the Small Scale Structure in Clusters of Galaxies

We have applied a wavelet transform analysis to quantify the small-scale (less than a few arcminutes) X-ray structure of clusters of galaxies to several clusters. Three of these clusters show interesting structure. In addition to the small scale structure in surface brightness, we have searched for temperature structure using Advanced Satellite for Cosmology and Astrophysics (ASCA) observations. For A754, we find a filamentary structure, similar to that previously detected in A85. For A119, we find small scale structure associated with both cool and hot regions with a hot filament extending to the northeast. For A1750, one of the first clusters to show substructure from Einstein, we have a rederived the substructure from the ROSAT observations. The ASCA observations show a hot region between the two small scale features - sub-clusters. The hot region shows that the two subclusters are merging and producing a shock wave at the leading edge of the interaction. This analysis had been applied to a sample of 17 clusters to determine the radial distribution of substructure in a sample. The number of detected substructures was rather small and it was decided to select a different cluster sample at larger redshift. This provided a larger radial range over which substructure could be detected. This new cluster sample also includes about 20 clusters and is being analyzed. Finally, we are considering how to compare the substructure parameters of nearby clusters with a more distant sample to see if one can extract cosmological information. Since substructure frequency should depend on the cosmological density parameter, it may be possible to derive new constraints by comparing nearby and distant clusters.

Forman, William R.↗
NASA NTRS2001

Characterizing the Small Scale Structure in Clusters of Galaxies

We studied galaxy clusters Abell 119, Abell 754, and Abell 1750, using data from the ASCA and ROSAT satellites. In addition, we completed the paper "Merging Binary Clusters". In this paper we study three prominent bi-modal X-ray clusters: A3528, A1750 and A3395. Since the sub-clusters in these systems have projected separations of 0.93, 1.00 and 0.67 Mpc respectively, we examine their X-ray and optical observations to investigate the dynamics and possible merging of these sub-clusters. Using data taken with ROSAT and ASCA, we analyze the temperature and surface brightness distributions. We also analyze the velocity distributions of the three clusters using new measurements supplemented with previously published data. We examined both the overall cluster properties as well as the two sub-cluster elements in each. These results were then applied to the determination of the overall cluster masses, that demonstrate excellent consistency between the various methods used. While the characteristic parameters of the sub-clusters are typical of isolated objects, our temperature results for the regions between the two sub-clusters clearly confirm the presence of merger activity that is suggested by the surface brightness distributions. These three clusters represent a progression of equal-sized sub-cluster mergers, starting from initial contact to immediately before first core passage.

Forman, William R.↗
NASA NTRS1981

Einstein imaging observations of clusters with a bimodal mass distribution

Einstein imaging observations of four X-ray clusters of galaxies characterized by a double X-ray surface brightness and thus mass distribution are presented. The clusters A98, A115, A1750 and SC 0627-54 were found to exhibit two enhancements in their X-ray surface brightness distributions in observations made with the Einstein Imaging Proportional Counter. Calculations of the probability that the clusters represent chance superpositions indicate that the double clusters are physically associated. The radial distributions of the components are inconsistent with those of single point sources, and have been used to derive cluster luminosities which are typical of rich clusters. Masses of the subclusters are also found to be typical of bound and virialized clusters with gas contributing 10%. Within the framework of the hierarchical theory of galactic clustering, the double clusters are suggested to represent an intermediate evolutionary stage before the merger of subclusters into a relaxed Coma-type cluster.

Forman, W.↗
NASA NTRSDate not supplied

Artificial Generation of 2-D Fiber Reinforced Composite Microstructures with Statistically Equivalent Features

Fiber reinforced composites are used widely for their high strength and low weight advantages in various aerospace and automotive applications. While their use may be sought after, modeling of these material requires increasing fidelity at the lower scales to capture accurate material behavior under loading. The first steps in creating statistically equivalent models to real life cases is developing a method of rapid evaluation and artificial microstructure generation. The outlined work is capable of tracking microscale fiber positions and determining regions of localized volume fraction extrema (high and low end). Groupings of high and low volume fraction regions are called clusters and their geometry is used to characterize the microstructure. These cluster features can be evaluated for both artificial models and actual scans, allowing correlation to be established which can ultimately be used to regenerate statistically equivalent models. The results of this work show that if one feature is to be correlated, a model can be generated which matches almost exactly. But once more features are equally taken into account, the regeneration loses accuracy.

micromechanics↗
NASA NTRS2019

Seasonal- and Beta-Angle-Dependent Latitude Bias Variations in Natural Decays

Prior work has demonstrated pronounced statistical clustering of natural decays of medium-to-high-inclination orbital objects peaking approximately 30 degrees in Argument of Latitude ahead of nodal crossings. This effect is caused by the physical bulge in the Earth and the overlying atmosphere, that cyclically modifies effective altitude (and therefore density) faster than the trajectory's decay itself. While prior work has averaged seasonal and RAAN effects over all non-uniform atmosphere possibilities to support long-term characterization of the clustering of final entries in generating a pre-mission Expectation of Casualty, the current study characterizes seasonal and beta angle effects as potential influences on the near-term statistical risks of specific tactical decay scenarios, relative to the average. Such effects on the density profile along an orbit may be important considerations in any scenario where small orbital adjustments are used to optimize the timing and location of final entry trajectories. I.E., two identical spacecraft entering in different seasons and/or beta angles may have different minimum-risk scenarios for identical control capabilities and space weather conditions. Further, the early heating history of shallow trajectories is explored, examining the influence of dramatically different density profiles over the final orbit as the spacecraft either skims over or dives into the atmosphere.

Bacon, John B.↗