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NASA NTRS2008

Development of arrays of position-sensitive microcalorimeters for Constellation-X

We are developing arrays of position-sensitive transition-edge sensor (POST) X-ray detectors for future astronomy missions such as NASA's Constellation-X. The POST consists of multiple absorbers thermally coupled to one or more transition-edge sensor (TES). Each absorber element has a different thermal coupling to the TES. This results in a distribution of different pulse shapes and enables position discrimination between the absorber elements. POST'S are motivated by the desire to achieve the largest possible focal plane area with the fewest number of readout channels and are ideally suited to increasing the Constellation-X focal plane area, without comprising on spatial sampling. Optimizing the performance of POST'S requires careful design of key parameters such as the thermal conductances between the absorbers, TES and the heat sink. as well as the absorber heat capacities. Using recently developed signal processing algorithms we have investigated the trade-off between position-sensitivity, energy resolution and pulse decay time. based on different device design parameters for PoST's. Our new generation of PoST's utilize technology successfully developed on high resolution (approximately 2.5eV) single pixels arrays of Mo/Au TESs. also under development for Constellation-X. This includes noise mitigation features on the TES and low resistivity electroplated absorbers. We report on the first experimental results from these new one and two-channel PoST"s, consisting of all Au and composite Au/Bi absorbers, which are designed to achieve an energy resolution of < 10 eV. coupled with count-rates of 100's per pixel per second and position sensitivity over the energy range 0.3-10 keV.

Smith, S. J.↗

NASA NTRS2008

Improving Coastal Ocean Color Validation Capabilities through Application of Inherent Optical Properties (IOPs)

Understanding how the different components of seawater alter the path of incident sunlight through scattering and absorption is essential to using remotely sensed ocean color observations effectively. This is particularly apropos in coastal waters where the different optically significant components (phytoplankton, detrital material, inorganic minerals, etc.) vary widely in concentration, often independently from one another. Inherent Optical Properties (IOPs) form the link between these biogeochemical constituents and the Apparent Optical Properties (AOPs). understanding this interrelationship is at the heart of successfully carrying out inversions of satellite-measured radiance to biogeochemical properties. While sufficient covariation of seawater constituents in case I waters typically allows empirical algorithms connecting AOPs and biogeochemical parameters to behave well, these empirical algorithms normally do not hold for case I1 regimes (Carder et al. 2003). Validation in the context of ocean color remote sensing refers to in-situ measurements used to verify or characterize algorithm products or any assumption used as input to an algorithm. In this project, validation capabilities are considered those measurement capabilities, techniques, methods, models, etc. that allow effective validation. Enhancing current validation capabilities by incorporating state-of-the-art IOP measurements and optical models is the purpose of this work. Involved in this pursuit is improving core IOP measurement capabilities (spectral, angular, spatio-temporal resolutions), improving our understanding of the behavior of analytical AOP-IOP approximations in complex coastal waters, and improving the spatial and temporal resolution of biogeochemical data for validation by applying biogeochemical-IOP inversion models so that these parameters can be computed from real-time IOP sensors with high sampling rates. Research cruises supported by this project provides for collection and processing of seawater samples for biogeochemical (pigments, DOC and POC) and optical (CDOM and POM absorption coefficients) analyses to enhance our understanding of the linkages between in-water optical measurements (IOPs and AOPs) and biogeochemical constituents and to provide a more comprehensive suite of validation products.

Mannino, Antonio↗

NASA NTRS2005

Improved Compression of Wavelet-Transformed Images

A recently developed data-compression method is an adaptive technique for coding quantized wavelet-transformed data, nominally as part of a complete image-data compressor. Unlike some other approaches, this method admits a simple implementation and does not rely on the use of large code tables. A common data compression approach, particularly for images, is to perform a wavelet transform on the input data, and then losslessly compress a quantized version of the wavelet-transformed data. Under this compression approach, it is common for the quantized data to include long sequences, or runs, of zeros. The new coding method uses prefixfree codes for the nonnegative integers as part of an adaptive algorithm for compressing the quantized wavelet-transformed data by run-length coding. In the form of run-length coding used here, the data sequence to be encoded is parsed into strings consisting of some number (possibly 0) of zeros, followed by a nonzero value. The nonzero value and the length of the run of zeros are encoded. For a data stream that contains a sufficiently high frequency of zeros, this method is known to be more effective than using a single variable length code to encode each symbol. The specific prefix-free codes used are from two classes of variable-length codes: a class known as Golomb codes, and a class known as exponential-Golomb codes. The codes within each class are indexed by a single integer parameter. The present method uses exponential-Golomb codes for the lengths of the runs of zeros, and Golomb codes for the nonzero values. The code parameters within each code class are determined adaptively on the fly as compression proceeds, on the basis of statistics from previously encoded values. In particular, a simple adaptive method has been devised to select the parameter identifying the particular exponential-Golomb code to use. The method tracks the average number of bits used to encode recent runlengths, and takes the difference between this average length and the code parameter. When this difference falls outside a fixed range, the code parameter is updated (increased or decreased). The Golomb code parameter is selected based on the average magnitude of recently encoded nonzero samples. The coding method requires no floating- point operations, and more readily adapts to local statistics than other methods. The method can also accommodate arbitrarily large input values and arbitrarily long runs of zeros. In practice, this means that changes in the dynamic range or size of the input data set would not require a change to the compressor. The algorithm has been tested in computational experiments on test images. A comparison with a previously developed algorithm that uses large code tables (generated via Huffman coding on training data) suggests that the data-compression effectiveness of the present algorithm is comparable to the best performance achievable by the previously developed algorithm.

Kiely, Aaron↗

NASA NTRS2004

Experimentally Determined Plasma Parameters in a 30 cm Ion Engine

Single planar Langmuir probes and fiber optic probes are used to concurrently measure the plasma properties and neutral density variation in a 30cm diameter ion engine discharge chamber, from the immediate vicinity of the keeper to the near grid plasma region. The fiber optic probe consists of a collimated optical fiber recessed into a double bore ceramic tube fitted with a stainless steel light-limiting window. The optical fiber probe is used to measure the emission intensity of excited neutral xenon for a small volume of plasma, at various radial and axial locations. The single Langmuir probes, are used to generate current-voltage characteristics at a total of 140 spatial locations inside the discharge chamber. Assuming a maxwellian distribution for the electron population, the Langmuir probe traces provide spatially resolved measurements of plasma potential, electron temperature, and plasma density. Data reduction for the NSTAR TH8 and TH15 throttle points indicates an electron temperature range of 1 to 7.9 eV and an electron density range of 4e10 to le13 cm(sup -3), throughout the discharge chamber, consistent with the results in the literature. Plasma potential estimates, computed from the first derivative of the probe characteristic, indicate potential from 0.5V to 11V above the discharge voltage along the thruster centerline. These values are believed to be excessively high due to the sampling of the primary electron population along the thruster centerline. Relative neutral density profiles are also obtained with a fiber optic probe sampling photon flux from the 823.1 nm excited to ground state transition. Plasma parameter measurements and neutral density profiles will be presented as a function of probe location and engine discharge conditions. A discussion of the measured electron energy distribution function will also be presented, with regards to variation from pure maxwellian. It has been found that there is a distinct primary population found along the thruster centerline, which causes estimates of electron temperature, electron density, and plasma potential, to err on the high side, due this energetic population. Computation of the energy distribution fimction of the plasma clearly indicates the presence of primaries, whose presence become less obvious with radial distance from the main discharge plume.

near grid plasma↗

NASA NTRS2018

Characterization and Analysis of Phoca Vitulina, Zalophus Californianus and Mirounga Angustirostris Vibrissae

Vibrissae of Phoca Vitulina (harbor seal) and Mirounga Angustirostris (elephant seal) possess undulations along their length. Harbor seal vibrissae have shown potential to reduce vortex induced vibrations and reduce drag compared to cylinders and ellipses. The exact geometry of the whiskers has not been well documented and the parameters that are responsible for the reduction in drag and vortex induced vibrations have not been characterized. Samples of six harbor seal vibrissae, six elephant seal vibrissae and six California sea lion (Zalophus californianus) vibrissae were collected from the Marine Mammal Center in California. The objectives of this study were to (1) Compare measurement techniques for digitizing and extracting parameters of the seal whiskers for the PeTaL (Periodic Table of Life) database. CT scanning, microscopy and 3D scanning techniques were compared. (2) Compare aerodynamic characteristics of a representative harbor seal whisker, elephant seal whisker, California sea lion whisker and ellipse at Re = 12000 and Re = 23000 based on major axis and free stream velocity. The data (in appendices) is available to compare CFD models or for further experimental validation, (3) Show close up images of whiskers and look for surface roughness effects. Variations in the seven parameters of the seal whisker were observed that may either be a feature of the vibration reduction mechanism or a result of natural variation. It is hypothesized that six parameters are sufficient to characterize seal whiskers based on analytic fitting. The drag coefficient of harbor seal whiskers examined in this study were found to be 25 percent lower than that of an ellipse with comparable major and minor axis lengths at Reynolds number of 12000. The dissipation length scale was found to be larger for seal whiskers. Potential applications of seal whisker morphology for aerospace are discussed. Roughness is not thought to play a factor in seal hydrodynamics.

Shyam, Vikram↗

NASA NTRSDate not supplied

Particle Size Distribution Parameters from SAGE III/ISS Extinction Spectra

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on the relative abundance of different sized particles within the sample volume, often referred to as the particle size distribution (PSD). If the PSD is accurately known then other key modeling parameters (e.g., surface area density and effective radius) can be derived. Historically, occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts routinely failed to account for measurement uncertainty and lacked a rigorous estimate of the inferred PSD uncertainty. We carried out a series of simulations to evaluate the accuracy of these inferences and, for every valid SAGE III/ISS extinction spectrum, determined the range of PSD parameters that fell withing the bounds of the extinction error bars. Special application of this method was applied to estimate the impact of the 2022 Hunga Tonga eruption had on particle size distributions.

Travis N Knepp↗

NASA NTRSDate not supplied

Sage III/ISS Stratospheric Aerosols and Gas Experiment An Earth Science Mission on the International Space Station

Stratospheric aerosols play key roles in the chemistry and radiation balance of the atmosphere and are a key input parameter for global chemistry and climate models. The degree to which aerosols impact chemistry and radiation balance depends primarily on the relative abundance of different sized particles within the sample volume, often referred to as the particle size distribution (PSD). If the PSD is accurately known then other key modeling parameters (e.g., surface area density and effective radius) can be derived. Historically, occultation observations from orbital instruments such as SAGE III/ISS have been used to infer these PSD parameters by inverting the extinction coefficient spectra. However, past efforts routinely failed to account for measurement uncertainty and lacked a rigorous estimate of the inferred PSD uncertainty. We developed a PSD solution algorithm that infers single mode and bimodal distribution parameters and applied this algorithm to the SAGE II and SAGE III/ISS data record. Herein we describe the algorithm, evaluate its performance, and show results from the 2022 Hunga Tonga eruption.

Travis N. Knepp↗

NASA NTRS1974

Selection of sampling rate for digital control of aircrafts

The considerations in selecting the sample rates for digital control of aircrafts are identified and evaluated using the optimal discrete method. A high performance aircraft model which includes a bending mode and wind gusts was studied. The following factors which influence the selection of the sampling rates were identified: (1) the time and roughness response to control inputs; (2) the response to external disturbances; and (3) the sensitivity to variations of parameters. It was found that the time response to a control input and the response to external disturbances limit the selection of the sampling rate. The optimal discrete regulator, the steady state Kalman filter, and the mean response to external disturbances are calculated.

Katz, P.↗

NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗

NASA NTRS1976

LACIE performance predictor final operational capability program description, volume 1

The program EPHEMS computes the orbital parameters for up to two vehicles orbiting the earth for up to 549 days. The data represents a continuous swath about the earth, producing tables which can be used to determine when and if certain land segments will be covered. The program GRID processes NASA's climatology tape to obtain the weather indices along with associated latitudes and longitudes. The program LUMP takes substrata historical data and sample segment ID, crop window, crop window error and statistical data, checks for valid input parameters and generates the segment ID file, crop window file and the substrata historical file. Finally, the System Error Executive (SEE) Program checks YES error and truth data, CAMS error data, and signature extension data for validity and missing elements. A message is printed for each error found.

Source record↗

NASA NTRS2012

The Validity Chlorophyll-a Estimation by Sun Induced Fluorescence in Estuarine Waters: An Analysis of Long-term (2003-2011) Water Quality Data from Tampa Bay, Florida (USA)

Satellite observation of phytoplankton concentration or chlorophyll-a is an important characteristic, critically integral to monitoring coastal water quality. However, the optical properties of estuarine and coastal waters are highly variable and complex and pose a great challenge for accurate analysis. Constituents such as suspended solids and dissolved organic matter and the overlapping and uncorrelated absorptions in the blue region of the spectrum renders the blue-green ratio algorithms for estimating chlorophyll-a inaccurate. Measurement of sun-induced chlorophyll fluorescence, on the other hand, which utilizes the near infrared portion of the electromagnetic spectrum, may provide a better estimate of phytoplankton concentrations. While modelling and laboratory studies have illustrated both the utility and limitations of satellite baseline algorithms based on the sun induced chlorophyll fluorescence signal, few have examined the empirical validity of these algorithms using a comprehensive long term in situ data set. In an unprecedented analysis of a long term (2003-2011) in situ monitoring data from Tampa Bay, Florida (USA), we assess the validity of the FLH product from the Moderate Resolution Imaging Spectrometer (MODIS) against chlorophyll ]a and a suite of water quality parameters taken in a variety of conditions throughout a large optically complex estuarine system. A systematic analysis of sampling sites throughout the bay is undertaken to understand how the relationship between FLH and in situ chlorophyll-a responds to varying conditions within the estuary including water depth, distance from shore and structures and eight water quality parameters. From the 39 station for which data was derived, 22 stations showed significant correlations when the FLH product was matched with in situ chlorophyll-alpha data. The correlations (r2) for individual stations within Tampa Bay ranged between 0.67 (n=28, pless than 0.01) and-0.457 (n=12, p=.016), indicating that for some areas within the Bay, FLH can be a good predictor of chlorophyll-alpha concentration and hence a useful tool for the analysis of water quality. Overall, the results show a 106% increase in the validity of chlorophyll -a concentration estimates using FLH over the standard the blue-green OC3M algorithm. This analysis also illustrates that the correlations between FLH and in situ chlorophyll -a measurements increases with increasing water depth and distance of the monitoring sites from both the shore and structures. However, due to confounding factors related to the complexity of the estuarine system, a linear improvement in the FLH to chlorophyll ]a relationship was not clearly noted with increasing depth and distance from shore alone. Correlations of FLH with turbidity, nutrients (total nitrogen and total phosphorous) biological oxygen demand, salinity, sea surface temperature correlated positively with FLH concentrations, while dissolved oxygen and pH showed negative correlations. Principle component analyses are employed to further describe the relationships between the multivariate water quality parameters and the FLH product. The majority of sites with higher and very significant correlations (pless than 0.01) also showed high correlation values for nutrients, turbidity and biological oxygen demand. These sites were on average in greater than seven meters of water and over five kilometers from shore. A thorough understanding of the relationship between the MODIS FLH product and in situ water quality parameters will enhance our understanding of the accuracy MODIS fs global FLH algorithm and assist in optimizing its calibration for use in monitoring the quality of estuarine and coastal waters worldwide.

Moreno-Madrinan, Max Jacobo↗

NASA NTRS1986

Pervasive small-scale structure in molecular clouds

An unbiased CO survey of molecular cloud cores was completed, and the profiles were analyzed within the context of a model for emission from clumpy clouds. It was found that all sources observed contain a significant amount of structure that is not resolved with our 2.3-arcmin beam, and that the parameters which describe the degree of clumping span a remarkably narrow range of the possible values. We studied two separate samples of cloud cores: a large sample of warm cores from the Massachusetts-Stony Brook 12CO survey of the first galactic quadrant, and a sample of cool cores in the Taurus dark clouds chosen primarily on the basis of H2CO emission. We observed all sources in the 1-0 transition of 12CO and 13CO with the 5-m telescope of the Millimeter Wave Observatory. The 12CO/13CO ratios can be explained if there is unresolved structure giving rise to significant variations of opacity across the beam. Our model cloud consists of a large number of identical clumps distributed randomly in the beam. These clumps have velocity widths v small compared to the width of the observed profile, which is determined by the relative motion of the clumps. The entire cloud is isothermal and in local thermodynamic equilibrium. With these assumptions the intensity and linewidth ratios depend on three parameters: the abundance ratio; the peak 13CO opacity through a single clump, tau(0); and the average number of clumps on a line of sight N. Small tau(0) and large N correspond to the microturbulent limit, which is indistinguishable from a uniform gas distribution. In the other extreme, large tau(0) and snall N, at a given velocity at most one clump contributes to the profile on each line of sight. A figure is presented which shows the model parameters which reproduce the measured intensity and linewidth ratios for the sample of warm cores, assuming an abundance ratio of 75.

Martin, B.↗

NASA NTRS1980

Effective optical constants of anisotropic materials

The applicability of a technique for determining the optical constants of soil or aerosol components on the basis of measurements of the reflectance or transmittance of inhomogeneous samples of component material is investigated. Optical constants for a sample of very pure quartzite were obtained by a specular reflection technique and line parameters were calculated by classical dispersion theory. Predictions of the reflectance of powdered quartz were then derived from optical constants measured for the anisotropic quartz and for pure quartz crystals, and compared with experimental measurements. The calculated spectra are found to resemble each other moderately well in shape, however the reflectance level calculated from the psuedo-optical constants (quartzite) is consistently below that calculated from quartz values. The spectrum calculated from the quartz optical constants is also shown to represent the experimental nonrestrahlen features more accurately. It is thus concluded that although optical constants derived from inhomogeneous materials may represent the spectral features of a powdered sample qualitatively a quantitative fit to observed data is not likely.

Aronson, J. R.↗

NASA NTRS2023

Surface Biology and Geology Imaging Spectrometer: A Case Study to Optimize the Mission Design Using Intrinsic Dimensionality

The information content that can be derived from spectroscopic imagery tends to increase with finer ground sampling distance, finer spectral sampling, more frequent revisit, and higher signal-to-noise ratios (SNRs). However, these parameters are not independent, and it is thus impossible to design a space-borne imaging spectrometer to maximize all of them simultaneously. We present an instrument model and simulation environment that enable us to find the optimal combination of these four mission design parameters, using intrinsic dimensionality (ID) as the metric. ID is the size of the signal subspace – the maximum degrees of freedom when noise can be disregarded – and is a metric that is independent of any one particular algorithm or application area. This study is important for upcoming missions such as NASA's Earth System Observatory mission to study the Earth's Surface Biology and Geology (SBG), which will comprise a visible to shortwave infrared spectrometer in addition to a multi-channel thermal radiometer on a separate platform. When evaluating a desert site and a tropical forested site, we find that spectral resolution drives information content, with a significant drop in normalized ID (15–45% decrease) when simulating 15 nm spectral sampling as opposed to 10 nm spectral sampling. However, there was some variation between sites, with the forested site benefiting from 5 nm spectral sampling, whereas the desert site had poorer results at this resolution, due to the impact on noise. At 10 nm spectral sampling, ground sampling distances in the range 30–50 m provided the optimal balance between spatial resolution and SNR, although more frequent revisit, potentially by combining data from multiple missions, would maximize total information content.

Mission design↗

NASA NTRS2007

Colorimetric-Solid Phase Extraction Technology for Water Quality Monitoring: Evaluation of C-SPE and Debubbling Methods in Microgravity

Colorimetric-solid phase extraction (C-SPE) is being developed as a method for in-flight monitoring of spacecraft water quality. C-SPE is based on measuring the change in the diffuse reflectance spectrum of indicator disks following exposure to a water sample. Previous microgravity testing has shown that air bubbles suspended in water samples can cause uncertainty in the volume of liquid passed through the disks, leading to errors in the determination of water quality parameter concentrations. We report here the results of a recent series of C-9 microgravity experiments designed to evaluate manual manipulation as a means to collect bubble-free water samples of specified volumes from water sample bags containing up to 47% air. The effectiveness of manual manipulation was verified by comparing the results from C-SPE analyses of silver(I) and iodine performed in-flight using samples collected and debubbled in microgravity to those performed on-ground using bubble-free samples. The ground and flight results showed excellent agreement, demonstrating that manual manipulation is an effective means for collecting bubble-free water samples in microgravity.

Hazen-Bosveld, April↗

NASA NTRS2002

Maximizing Macromolecule Crystal Size for Neutron Diffraction Experiments

A challenge in neutron diffraction experiments is growing large (greater than 1 cu mm) macromolecule crystals. In taking up this challenge we have used statistical experiment design techniques to quickly identify crystallization conditions under which the largest crystals grow. These techniques provide the maximum information for minimal experimental effort, allowing optimal screening of crystallization variables in a simple experimental matrix, using the minimum amount of sample. Analysis of the results quickly tells the investigator what conditions are the most important for the crystallization. These can then be used to maximize the crystallization results in terms of reducing crystal numbers and providing large crystals of suitable habit. We have used these techniques to grow large crystals of Glucose isomerase. Glucose isomerase is an industrial enzyme used extensively in the food industry for the conversion of glucose to fructose. The aim of this study is the elucidation of the enzymatic mechanism at the molecular level. The accurate determination of hydrogen positions, which is critical for this, is a requirement that neutron diffraction is uniquely suited for. Preliminary neutron diffraction experiments with these crystals conducted at the Institute Laue-Langevin (Grenoble, France) reveal diffraction to beyond 2.5 angstrom. Macromolecular crystal growth is a process involving many parameters, and statistical experimental design is naturally suited to this field. These techniques are sample independent and provide an experimental strategy to maximize crystal volume and habit for neutron diffraction studies.

Judge, R. A.↗

NASA NTRS2016

Weak-Lensing Mass Calibration of the Atacama Cosmology Telescope Equatorial Sunyaev-Zeldovich Cluster Sample with the Canada-France-Hawaii Telescope Stripe 82 Survey

Mass calibration uncertainty is the largest systematic effect for using clustersof galaxies to constrain cosmological parameters. We present weak lensing mass measurements from the Canada-France-Hawaii Telescope Stripe 82 Survey for galaxy clusters selected through their high signal-to-noise thermal Sunyaev-Zeldovich (tSZ) signal measured with the Atacama Cosmology Telescope (ACT). For a sample of 9 ACT clusters with a tSZ signal-to-noise greater than five, the average weak lensing mass is (4.8 plus or minus 0.8) times 10 (sup 14) solar mass, consistent with the tSZ mass estimate of (4.7 plus or minus 1.0) times 10 (sup 14) solar mass, which assumes a universal pressure profile for the cluster gas. Our results are consistent with previous weak-lensing measurements of tSZ-detected clusters from the Planck satellite. When comparing our results, we estimate the Eddington bias correction for the sample intersection of Planck and weak-lensing clusters which was previously excluded.

Battaglia, N.↗

NASA NTRS2003

Structural Reliability Using Probability Density Estimation Methods Within NESSUS

A reliability analysis studies a mathematical model of a physical system taking into account uncertainties of design variables and common results are estimations of a response density, which also implies estimations of its parameters. Some common density parameters include the mean value, the standard deviation, and specific percentile(s) of the response, which are measures of central tendency, variation, and probability regions, respectively. Reliability analyses are important since the results can lead to different designs by calculating the probability of observing safe responses in each of the proposed designs. All of this is done at the expense of added computational time as compared to a single deterministic analysis which will result in one value of the response out of many that make up the density of the response. Sampling methods, such as monte carlo (MC) and latin hypercube sampling (LHS), can be used to perform reliability analyses and can compute nonlinear response density parameters even if the response is dependent on many random variables. Hence, both methods are very robust; however, they are computationally expensive to use in the estimation of the response density parameters. Both methods are 2 of 13 stochastic methods that are contained within the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) program. NESSUS is a probabilistic finite element analysis (FEA) program that was developed through funding from NASA Glenn Research Center (GRC). It has the additional capability of being linked to other analysis programs; therefore, probabilistic fluid dynamics, fracture mechanics, and heat transfer are only a few of what is possible with this software. The LHS method is the newest addition to the stochastic methods within NESSUS. Part of this work was to enhance NESSUS with the LHS method. The new LHS module is complete, has been successfully integrated with NESSUS, and been used to study four different test cases that have been proposed by the Society of Automotive Engineers (SAE). The test cases compare different probabilistic methods within NESSUS because it is important that a user can have confidence that estimates of stochastic parameters of a response will be within an acceptable error limit. For each response, the mean, standard deviation, and 0.99 percentile, are repeatedly estimated which allows confidence statements to be made for each parameter estimated, and for each method. Thus, the ability of several stochastic methods to efficiently and accurately estimate density parameters is compared using four valid test cases. While all of the reliability methods used performed quite well, for the new LHS module within NESSUS it was found that it had a lower estimation error than MC when they were used to estimate the mean, standard deviation, and 0.99 percentile of the four different stochastic responses. Also, LHS required a smaller amount of calculations to obtain low error answers with a high amount of confidence than MC. It can therefore be stated that NESSUS is an important reliability tool that has a variety of sound probabilistic methods a user can employ and the newest LHS module is a valuable new enhancement of the program.

Chamis, Chrisos C.↗