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NASA NTRS1984

Analysis and Interpretation of Synthetic Time Strings of Oscillation Data

Artificial strings of solar oscillation data with gaps and noise, corresponding to the output of different spatial filter functions, were analyzed. Peaks in the power spectrum are identified for values of the degree l from 0 to 18, and rotational splitting is estimated. The filters prove effective in facilitating identification of essentially all the real peaks in the power spectrum. Estimates of peak frequencies and amplitudes and rotational splitting frequencies are in reasonably good agreement with the input values. Spurious peaks in autocorrelation spectra correspond to the frequency spacing between power peaks with the same order n, differing by one or two in the degree l.

Mihalas, B. W.↗

NASA NTRS2000

BOREAS HYD-1 Soil Hydraulic Properties

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-1 team coordinated a program of data collection to measure and monitor soil properties in collaboration with other science team measurement needs. This data set contains soil hydraulic properties determined at the Northern Study Area (NSA) and Southern Study Area (SSA) flux tower sites based on analysis of in situ tension infiltrometer tests and laboratory-determined water retention from soil cores collected during the 1994-95 field campaigns. Results from this analysis are saturated hydraulic conductivity, and fitting parameters for the van Genuchten-Mualem soil hydraulic conductivity and water retention function at flux tower sites. The data are contained in tabular ASCII files. The HYD-01 soil hydraulic properties data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Hall, Forrest G.↗

NASA NTRS1995

SAVS: A Space and Atmospheric Visualization Science system

The research environment faced by space and atmospheric scientists in the 1990s is characterized by unprecedented volumes of new data, by ever-increasing repositories of unexploited mission files, and by the widespread use of empirical and large-scale computational models needed for the synthesis of understanding across data sets and discipline boundaries. The effective analysis and interpretation of such massive amounts of information have become the subjects of legitimate concern. With SAVS (a Space and Atmospheric Visualization Science System), we address these issues by creating a 'push-button' software environment that mimics the logical scientific processes in data acquisition, reduction, and analysis without requiring a detailed understanding of the methods, networks, and modules that link the tools and effectively execute the functions. SAVS provides (1) a customizable framework for accessing a powerful set of visualization tools based on the popular AVS visualization software with hooks to PV-Wave and access to Khoros modules, (2) a set of mathematical and statistical tools, (3) an extensible library of discipline-specific functions and models (e.g., MSIS, IRI, Feldstein Oval, IGRF, satellite tracking with CADRE-3, etc.), and (4) capabilities for local and remote data base access. The system treats scalar, vector, and image data, and runs on most common Unix workstations. We present a description of SAVS and its components, followed by several applications based on generic research interests in interplanetary and magnetospheric physics (IMP/ISTP), active experiments in space (CRRES), and mission planning focused on the Earth's thermospheric, ionospheric, and mesospheric domains (TIMED).

Szuszczewicz, E. P.↗

NASA NTRSDate not supplied

NESC GN&C TDT Workshop on 2D Image Motion Optical Transfer Functions, Pointing Performance Analysis, and Requirements

What You Will Learn: The focus is on payload imaging performance due to pointing motion. Some historical background on pointing performance analysis is given. The Optical Transfer Function (OTF) and Modulation Transfer Function (MTF) are defined. The imaging performance due to pointing motion is measured by image motion optical transfer functions (IM OTF). IM OTFs are defined for displacement, smear, and jitter motions, which are all rigorously defined. Deterministic and Statistical IM OTFs are briefly derived and graphically illustrated and compared. The IM OTFs are parameterized by pointing error metrics(PEM), which are means and covariances of displacement, smear, and jitter. Emphasis is on procedures and algorithms to evaluate the image motion optical transfer functions and pointing error metrics. Three procedures are covered, which depend on whether the pointing error data is from time-domain simulation, frequency-domain analysis, or stochastic modeling. A method to evaluate the relative contribution of disturbance sources and to identify the most significant contributors is presented. The presentation includes pertinent discussion of flexible structures and control-structure interaction. No single book can adequately cover this subject, so a book is not required for the course. A list of selected articles, reports, documents, and books is provided for reference and further study. Mathis kept to the minimum necessary to convey principles; lengthy derivations are left to the reference material. Graphics are used to illustrate concepts. As with any such learning endeavor, the knowledge gained will be retained and strengthened through actual practice.c©2019–2021 Mark E. Pittelkau— 5

NASA Engineering and Safety Center (NESC)↗

DOE OSTI2020

Leveraging Actinide Hydrolysis Chemistry for Targeted Th and U Separations using Amidoxime-Functionalized Poly(HIPE)s

Polymerized high internal phase emulsions (poly(HIPE)s) are porous polymer monoliths whose synthesis can easily be tailored to allow incorporation of functional units. In this work, nitrile containing poly(HIPE)s have been prepared with either acrylonitrile (AN) or 4-cyanostyrene (4CS) comonomers. Post-synthetic modification of these nitrile-containing poly(HIPE)s yields their corresponding amidoximated analogues, which were studied for actinide uptake. These amidoxime-functionalized, porous polymers were shown to adsorb 95 % Th4+ species from aqueous solution within 30 minutes. In contrast to other amidoxime containing polymers the uptake of UO22+ in these poly(HIPE)s is lower under similar conditions. A critical analysis of actinide separations and high-energy X-ray scattering data provides insight into the polymers’ selectivity, enabled by the uptake of multinuclear Th clusters.

actinides↗

DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗

NASA NTRS2011

A Comparison of Methods for Assessing Space Suit Joint Ranges of Motion

Through the Advanced Exploration Systems Program, NASA is attempting to use the vast collection of space suit mobility data from 50 years worth of space suit testing to build predictive analysis tools to aid in early architecture decisions for future missions and exploration programs. However, the design engineers must first understand if and how data generated by different methodologies can be compared directly and used in an essentially interchangeable manner. To address this question, the isolated joint range of motion data from two different test series were compared. Both data sets were generated from participants wearing the Mark III Space Suit Technology Demonstrator (MK-III), Waist Entry I-suit (WEI), and minimal clothing. Additionally the two tests shared a common test subject that allowed for within subject comparisons of the methods that greatly reduced the number of variables in play. The tests varied in their methodologies: the Space Suit Comparative Technologies Evaluation used 2D photogrammetry to analyze isolated ranges of motion while the Constellation space suit benchmarking and requirements development used 3D motion capture to evaluate both isolated and functional joint ranges of motion. The isolated data from both test series were compared graphically, as percent differences, and by simple statistical analysis. The results indicated that while the methods generate results that are statistically the same (significance level p= 0.01), the differences are significant enough in the practical sense to make direct comparisons ill advised. The concluding recommendations propose direction for how to bridge the data gaps and address future mobility data collection to allow for backward compatibility.

Aitchison, Lindsay↗

DOE OSTI2022

Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning

Characterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.

36 MATERIALS SCIENCE↗

NASA NTRS2012

A Comparison of Methods for Assessing Space Suit Joint Ranges of Motion

Through the Advanced Exploration Systems (AES) Program, NASA is attempting to use the vast collection of space suit mobility data from 50 years worth of space suit testing to build predictive analysis tools to aid in early architecture decisions for future missions and exploration programs. However, the design engineers must first understand if and how data generated by different methodologies can be compared directly and used in an essentially interchangeable manner. To address this question, the isolated joint range of motion data from two different test series were compared. Both data sets were generated from participants wearing the Mark III Space Suit Technology Demonstrator (MK-III), Waist Entry I-suit (WEI), and minimal clothing. Additionally the two tests shared a common test subject that allowed for within subject comparisons of the methods that greatly reduced the number of variables in play. The tests varied in their methodologies: the Space Suit Comparative Technologies Evaluation used 2-D photogrammetry to analyze isolated ranges of motion while the Constellation space suit benchmarking and requirements development used 3-D motion capture to evaluate both isolated and functional joint ranges of motion. The isolated data from both test series were compared graphically, as percent differences, and by simple statistical analysis. The results indicated that while the methods generate results that are statistically the same (significance level p= 0.01), the differences are significant enough in the practical sense to make direct comparisons ill advised. The concluding recommendations propose direction for how to bridge the data gaps and address future mobility data collection to allow for backward compatibility.

Aitchison, Lindsay T.↗

NASA NTRS2011

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(TradeMark)(MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many countries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its real strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbox. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using symbolic operations. MatLab in its interpreter programming language form (command interface) is similar with well known programming languages such as C/C++, support data structures and cell arrays to define classes in object oriented programming. As such, MatLab is equipped with most of the essential constructs of a higher programming language. MatLab is packaged with an editor and debugging functionality useful to perform analysis of large MatLab programs and find errors. We believe there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and analysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applications. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientific problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabular format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed.

Sen, Syamal K.↗

NASA NTRS1976

Data analysis and noise prediction for the QF-1B experimental fan stage

The results of a fan noise data analysis and prediction effort using experimental data obtained from tests on the QF-1B research fan are described. Surface pressure measurements were made with flush mounted sensors installed on selected rotor blades and stator vanes and noise measurements were made by microphones located at the far field. Power spectral density analysis, time history studies, and calculation of coherence functions were made. The emphasis of these studies was on the characteristics of tones in the spectra. The amplitude behavior of spectral tones was found to have a large, often predominant, random component, suggesting that turbulent processes play an important role in the generation of tonal as well as broadband noise. Inputs from the data analysis were used in a prediction method which assumes that acoustic dipoles, produced by unsteady blade and van forces, are the important source of fan noise.

Bliss, D. B.↗

NASA NTRS2004

Removing Activity-Related Radial Velocity Noise to Improve Extrasolar Planet Searches

We have made significant progress towards the proposal goals of understanding the causes and effects of magnetic activity-induced radial velocity (v_r) jitter and developing methods for correcting it. In the process, we have also made some significant discoveries in the fields of planet-induced stellar activity, planet detection methods, M dwarf convection, starspot properties, and magnetic dynamo cycles. We have obtained super high resolution (R approximately 200,000), high S / N (greater than 300) echelle study of joint line bisector and radial velocity variations using the McDonald 2-D coude. A long observing run in October 2002 in particular was quite successful (8 clear nights). We now have close to three years of data, which begins to sample a good fraction of the magnetic cycle timescales for some of our targets (e.g., kappa Ceti; P_cyc = 5.6 yrs). This will be very helpful in unraveling the complex relationships between plage and radial velocity (v-r) changes which we have uncovered. Preliminary analysis (Saar et al. 2003) of the data in hand, reveals correlations between median line bisector displacement and v_r. The correlation appears to be specific the the particular star being considered, probably since it is a function of both spectral type and rotation rate. Further analysis and interpretation will be in the context of evolving plage models and is in progress.

Saar, Steven↗

DOE OSTI2023

Acute stress reduces population-level metabolic and proteomic variation

Abstract Background Variation in omics data due to intrinsic biological stochasticity is often viewed as a challenging and undesirable feature of complex systems analyses. In fact, numerous statistical methods are utilized to minimize the variation among biological replicates. Results We demonstrate that the common statistics relative standard deviation (RSD) and coefficient of variation (CV), which are often used for quality control or part of a larger pipeline in omics analyses, can also be used as a metric of a physiological stress response. Using an approach we term Replicate Variation Analysis (RVA), we demonstrate that acute physiological stress leads to feature-wide canalization of CV profiles of metabolomes and proteomes across biological replicates. Canalization is the repression of variation between replicates, which increases phenotypic similarity. Multiple in-house mass spectrometry omics datasets in addition to publicly available data were analyzed to assess changes in CV profiles in plants, animals, and microorganisms. In addition, proteomics data sets were evaluated utilizing RVA to identify functionality of reduced CV proteins. Conclusions RVA provides a foundation for understanding omics level shifts that occur in response to cellular stress. This approach to data analysis helps characterize stress response and recovery, and could be deployed to detect populations under stress, monitor health status, and conduct environmental monitoring.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1993

Superposed epoch analysis of pressure and magnetic field configuration changes in the plasma sheet

Using data from 41 substorm events in the near-Earth magnetotail, we have combined plasma, energetic ion, and magnetic field data from the AMPTE/IRM spacecraft to perform a superposed epoch analysis of changes in the total pressure and in the magnetic field configuration as a function of time relative to substorm onset. Unloading is evident in the total pressure profile; the pressure decreases by about 20 percent. Pressure changes during the growth phase are not as uniform for the different substorms as the pressure changes during the expansion phase. To study changes in the magnetic field configuration, we have determined the development of the plasma pressure profiles in z for an average of data from 15 to 19 R(E). At substorm onset, the field line dipolarization begins on the innermost field lines and then progresses to the outer field lines. The field lines map the closest to the Earth about 45 min after substorm onset, and then begin to stretch out again during the recovery phase of the substorm.

Kistler, L. M.↗

DOE OSTI2022

Systematic study of projection biases in weak lensing analysis

We present a systematic study of projection biases in the weak lensing analysis of the first year of data from the Dark Energy Survey (DES) experiment. In the analysis we used a $\Lambda$CDM model and three two-point correlation functions. We show that these biases are a consequence of projecting, or marginalizing, over parameters like $h$, $\Omega_b$, $n_s$ and $\Omega_\nu h^2$ that are both poorly constrained and correlated with the parameters of interest like $\Omega_m$, $\sigma_8$ and $S_8$. Covering the relevant parameter space we show that the projection biases are a function of where the true values of the poorly constrained parameters lie with respect to the parameter priors. For example, biases in the position of the posteriors can exceed the 1.5$\sigma$ level if the true values of $h$ and $n_s$ are close to the top of the prior's range and the true values of $\Omega_b$ and $\Omega_\nu h^2$ are close to the bottom of the range of their priors. We also show that in some cases the 1D credible intervals can be over-specified by as much as 30% and coverage can be as low as 27%. Finally we estimate these projection biases for the analysis of three and six years worth of DES data.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2018

Reliability Analysis in the Presence of Aleatory Uncertainty

This paper proposes a method for modeling a system’s response using data. In contrast to approaches that identify a limit state function, we focus on the case in which not all uncertain parameters affecting the response are observable and the measured response is corrupted by noise. To this end, the system response is not characterized by a limit state function but instead by a Random Predictor Model (RPM) having a nonparametric structure. Consequently, the resulting failure probability is not a scalar but a random variable. This variable accounts for the aleatory contributions of the model-form uncertainty and the measurement noise into the response. Furthermore, we propose a framework that enables trading off the predicted range of failure probabilities resulting from such an analysis with a measure of risk. In this context, risk is the percentage of all predicted outcomes the analyst is willing to ignore. The reliability analysis of an aeroelastic structure subject to flutter is used to illustrate the ideas proposed.

Crespo, L. G.↗

NASA NTRS1990

Systems engineering and integration: Cost estimation and benefits analysis

Space Transportation Avionics hardware and software cost has traditionally been estimated in Phase A and B using cost techniques which predict cost as a function of various cost predictive variables such as weight, lines of code, functions to be performed, quantities of test hardware, quantities of flight hardware, design and development heritage, complexity, etc. The output of such analyses has been life cycle costs, economic benefits and related data. The major objectives of Cost Estimation and Benefits analysis are twofold: (1) to play a role in the evaluation of potential new space transportation avionics technologies, and (2) to benefit from emerging technological innovations. Both aspects of cost estimation and technology are discussed here. The role of cost analysis in the evaluation of potential technologies should be one of offering additional quantitative and qualitative information to aid decision-making. The cost analyses process needs to be fully integrated into the design process in such a way that cost trades, optimizations and sensitivities are understood. Current hardware cost models tend to primarily use weights, functional specifications, quantities, design heritage and complexity as metrics to predict cost. Software models mostly use functionality, volume of code, heritage and complexity as cost descriptive variables. Basic research needs to be initiated to develop metrics more responsive to the trades which are required for future launch vehicle avionics systems. These would include cost estimating capabilities that are sensitive to technological innovations such as improved materials and fabrication processes, computer aided design and manufacturing, self checkout and many others. In addition to basic cost estimating improvements, the process must be sensitive to the fact that no cost estimate can be quoted without also quoting a confidence associated with the estimate. In order to achieve this, better cost risk evaluation techniques are needed as well as improved usage of risk data by decision-makers. More and better ways to display and communicate cost and cost risk to management are required.

Dean, ED↗

NASA NTRS2021

VESIcal Part I: An open-source thermodynamic model engine for mixed volatile (H2O-CO2) solubility in silicate melts

Thermodynamics has been fundamental to the interpretation of geologic data and modeling of geologic systems for decades. However, more recent advancements in computational capabilities and a marked increase in researchers’ accessibility to computing tools has outpaced the functionality and extensibility of currently available modeling tools. Here we present VESIcal (Volatile Equilibria and Saturation Identification calculator): the first comprehensive modeling tool for H 2 O, CO 2 , and mixed (H 2 O-CO 2 ) solubility in silicate melts that: a) allows users access to seven commonly used models, plus easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an excel spreadsheet for simple post-modeling analysis; e) integrates advanced plotting capabilities directly within the tool; and f) provides all of these within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python. The tool is presented within this manuscript, which is a Jupyter notebook containing worked examples accessible to python users with a range of skill levels. The basic functions of VESIcal can also be access via a web app (https://vesical.anvil.app). The VESIcal python library is open-source and available for download at https://github.com/kaylai/VESIcal.

K. Iacovino↗