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At least 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photoassimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be upregulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm upregulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

Weitzeal, A. J.↗
DOE OSTI2023

Residual-based error correction for neural operator accelerated infinite-dimensional Bayesian inverse problems

We explore using neural operators, or neural network representations of nonlinear maps between function spaces, to accelerate infinite-dimensional Bayesian inverse problems (BIPs) with models governed by nonlinear parametric partial differential equations (PDEs). Neural operators have gained significant attention in recent years for their ability to approximate the parameter-to-solution maps defined by PDEs using as training data solutions of PDEs at a limited number of parameter samples. The computational cost of BIPs can be drastically reduced if the large number of PDE solves required for posterior characterization are replaced with evaluations of trained neural operators. However, reducing error in the resulting BIP solutions via reducing the approximation error of the neural operators in training can be challenging and unreliable. We provide an a priori error bound result that implies certain BIPs can be ill-conditioned to the approximation error of neural operators, thus leading to inaccessible accuracy requirements in training. To reliably deploy neural operators in BIPs, we consider a strategy for enhancing the performance of neural operators: correcting the prediction of a trained neural operator by solving a linear variational problem based on the PDE residual. We show that a trained neural operator with error correction can achieve a quadratic reduction of its approximation error, all while retaining substantial computational speedups of posterior sampling when models are governed by highly nonlinear PDEs. The strategy is applied to two numerical examples of BIPs based on a nonlinear reaction–diffusion problem and deformation of hyperelastic materials. We demonstrate that posterior representations of the two BIPs produced using trained neural operators are greatly and consistently enhanced by error correction.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

Evaluation of SLAR and simulated thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

Kershaw County, South Carolina was selected as the study site for analyzing simulated thematic mapper MSS data and dual-polarized X-band synthetic aperture radar (SAR) data. The impact of the improved spatial and spectral characteristics of the LANDSAT D thematic mapper data on computer aided analysis for forest cover type mapping was examined as well as the value of synthetic aperture radar data for differentiating forest and other cover types. The utility of pattern recognition techniques for analyzing SAR data was assessed. Topics covered include: (1) collection and of TMS and reference data; (2) reformatting, geometric and radiometric rectification, and spatial resolution degradation of TMS data; (3) development of training statistics and test data sets; (4) evaluation of different numbers and combinations of wavelength bands on classification performance; (5) comparison among three classification algorithms; and (6) the effectiveness of the principal component transformation in data analysis. The collection, digitization, reformatting, and geometric adjustment of SAR data are also discussed. Image interpretation results and classification results are presented.

Hoffer, R. M.↗
DOE OSTI2024

A discontinuous piecewise polynomial generalized moving least squares scheme for robust finite element analysis on arbitrary grids

A variational approach is developed with a meshless discretization to enable accurate and robust numerical simulation of partial differential equations for meshes that are of poor quality. Traditional finite element methods use the mesh to both discretize the geometric domain and to define the finite element shape functions. The latter creates a dependence between the quality of the mesh and the properties of the finite element basis that may adversely affect the accuracy of the discretized problem. Here, we propose a new approach for defining finite element shape functions that breaks this dependence and separates mesh quality from the discretization quality, which we call discontinuous piecewise polynomial generalized moving least squares (DPP-GMLS). At the core of the approach is a meshless definition of the shape functions, which limits the purpose of the mesh to representing the geometric domain and integrating the basis functions without having any role in their approximation quality. The resulting non-conforming space can be utilized within a standard discontinuous Galerkin framework, providing a rigorous foundation for solving partial differential equations on low-quality meshes. We present a collection of numerical experiments demonstrating our approach in a wide range of settings: strongly coercive elliptic problems, linear elasticity in the compressible regime, and the stationary Stokes problem. We demonstrate convergence for all problems and stability for element pairs for problems which usually require inf-sup compatibility for conforming methods, also referring to a minor modification possible through the symmetric interior penalty Galerkin framework for stabilizing element pairs that would otherwise be traditionally unstable. Mesh robustness is particularly critical for elasticity, and we provide an example that our approach provides a greater than 5 x improvement in accuracy and allows for taking an 8 x larger stable timestep for a highly deformed mesh, compared to the continuous Galerkin finite element method.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Comparative hypsometric analysis of both Earth and Venus topographic distributions

Previous studies have compared the global topographic distribution of both planets by means of differential hypsometric curves. For the purpose of comparison, the terrestrial oceanic load was removed, and a reference base level was acquired. It was chosen on the basis of geometric considerations and reflected the geometric shape of the mean dynamical equilibrium figure of the planetary surface in both cases. This reference level corresponds to the well-known sea level for the Earth; for Venus, given its slow rate of rotation, a sphere of radius close to the mean, median and modal values of the planetary radii distribution were considered and the radius value of 6051 km arbitrarily taken. These studies were based on the low resolution (100 x 100 sq km) coverage of Venus obtained by the Pioneer Venus altimeter and on the 1 deg x 1 deg terrestrial topography. But, apart from revealing the distinct contrast existing between the Earth's bimodal and Venus' strong unimodal topographic distribution, the choice of such a reference level is inadequate and even misleading for the comparative geophysical understanding of the planetary relief distribution. The present work reinvestigates the comparison between Earth and Venus hypsometric distribution on the basis of the high-resolution data provided, on one hand, by the recent Magellan global topographic coverage of Venus' surface, and on the other hand, by the detailed NCAR 5 x 5 ft. grid topographic database currently available for the Earth's surface.

Rosenblatt, P.↗
NASA NTRS2004

Variable Step Integration Coupled with the Method of Characteristics Solution for Water-Hammer Analysis, A Case Study

One-dimensional water-hammer modeling involves the solution of two coupled non-linear hyperbolic partial differential equations (PDEs). These equations result from applying the principles of conservation of mass and momentum to flow through a pipe, and usually the assumption that the speed at which pressure waves propagate through the pipe is constant. In order to solve these equations for the interested quantities (i.e. pressures and flow rates), they must first be converted to a system of ordinary differential equations (ODEs) by either approximating the spatial derivative terms with numerical techniques or using the Method of Characteristics (MOC). The MOC approach is ideal in that no numerical approximation errors are introduced in converting the original system of PDEs into an equivalent system of ODEs. Unfortunately this resulting system of ODEs is bound by a time step constraint so that when integrating the equations the solution can only be obtained at fixed time intervals. If the fluid system to be modeled also contains dynamic components (i.e. components that are best modeled by a system of ODEs), it may be necessary to take extremely small time steps during certain points of the model simulation in order to achieve stability and/or accuracy in the solution. Coupled together, the fixed time step constraint invoked by the MOC, and the occasional need for extremely small time steps in order to obtain stability and/or accuracy, can greatly increase simulation run times. As one solution to this problem, a method for combining variable step integration (VSI) algorithms with the MOC was developed for modeling water-hammer in systems with highly dynamic components. A case study is presented in which reverse flow through a dual-flapper check valve introduces a water-hammer event. The predicted pressure responses upstream of the check-valve are compared with test data.

Turpin, Jason B.↗
NASA NTRS2016

Microarray Data Analysis of Space Grown Arabidopsis Leaves for Genes Important in Vascular Patterning

Venation patterning in leaves is a major determinant of photosynthesis efficiency because of its dependency on vascular transport of photo-assimilates, water, and minerals. Arabidopsis thaliana grown in microgravity show delayed growth and leaf maturation. Gene expression data from the roots, hypocotyl, and leaves of A. thaliana grown during spaceflight vs. ground control analyzed by Affymetrix microarray are available through NASA's GeneLab (GLDS-7). We analyzed the data for differential expression of genes in leaves resulting from the effects of spaceflight on vascular patterning. Two genes were found by preliminary analysis to be up-regulated during spaceflight that may be related to vascular formation. The genes are responsible for coding an ARGOS (Auxin-Regulated Gene Involved in Organ Size)-like protein (potentially affecting cell elongation in the leaves), and an F-box/kelch-repeat protein (possibly contributing to protoxylem specification). Further analysis that will focus on raw data quality assessment and a moderated t-test may further confirm up-regulation of the two genes and/or identify other gene candidates. Plants defective in these genes will then be assessed for phenotype by the mapping and quantification of leaf vascular patterning by NASA's VESsel GENeration (VESGEN) software to model specific vascular differences of plants grown in spaceflight.

venation↗
DOE OSTI2024

HIGH BURNUP FUEL-COOLANT INTERACTION ANALYSIS SUPPORTING FUEL SAFETY TESTING AT IDAHO NATIONAL LABORATORY

In the near future, experiments on HBu fuel under loss-of-coolant accident (LOCA) and reactivity-initiated accident (RIA) conditions will be performed within the Transient Reactor Test Facility (TREAT) at Idaho National Laboratory (INL). These experiments will be performed using the Transient Water Irradiation System for TREAT (TWIST) experiment vehicle. To support these experiments, analysis of fuel-coolant interaction (FCI) energetics is underway. This paper discusses FCIs in the context of light water reactor (LWR) safety, differentiating between the severe accident focus of commercial reactors and experimental RIA test programs where FCIs have occurred. However, it is highlighted that as the nuclear industry aims for increased burnup limits, the FCI events observed in RIA test programs may become relevant to commercial LWR safety analysis. The paper then presents developments to the UW-FCI computer program to enable simulation of FCIs initiated by solid fuel particles dispersing into the coolant during RIAs.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Probing putative orbital differentiation effects via Eu 2+ spin dynamics in Sr 1-x Eu x Fe 2 As 2

Here, in this work, we report x-ray powder diffraction, elemental analysis, electrical resistivity, magnetic susceptibility, specific heat, and electron spin resonance (ESR) in single crystals of Sr 1-x Eu x Fe 2 As 2 . We observed a breakdown of the previously reported scaling between the Eu 2+ Korringa relaxation rate obtained from ESR and the spin density wave temperature evolution for Sr-rich samples. This result suggests a distinct evolution of the orbital differentiation of the Fe 3d bands along the Sr-based series when compared to the Ba counterpart. We argue that this difference is related to a larger splitting between the structural (tetragonal-to-orthorhombic) and the Fe-driven spin density wave transitions induced by Eu doping in this series. In fact, our results indicate that the two transitions follow an opposite x-Eu dependence for Sr-concentrated samples. Our work shows that Sr 1-x Eu x Fe 2 As 2 series and the comparison with their Ba-based counterparts are exciting platforms to be explored for understanding the interplay among orbital differentiation, magnetism, and structural distortions in the iron pnictides

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1981

Design and analysis of a torsion braid pendulum displacement transducer

The dynamic properties at various temperatures of braids impregnated with polymer can be measured by using the braid as the suspension of a torsion pendulum. This report describes the electronic and mechanical design of a torsional braid pendulum displacement transducer which is an advance in the state of the art. The transducer uses a unique optical design consisting of refracting quartz windows used in conjunction with a differential photocell to produce a null signal. The release mechanism for initiating free torsional oscillation of the pendulum has also been improved. Analysis of the precision and accuracy of the transducer indicated that the maximum relative error in measuring torsional amplitude was approximately 0. A serious problem inherent in all instruments which use a torsional suspension was analyzed: misalignment of the physical and torsional axes of the torsional member which results in modulation of the amplitude of the free oscillation.

Rind, E.↗
NASA NTRSDate not supplied

Transcriptomic Analysis of ISS Crewmembers’ Peripheral Blood Mononuclear Cells Reveals Homeostatic Regulations in Space

The impact of spaceflight on the immune system has been investigated for decades. Studies conducted in cell models, animals and humans suggest that the spaceflight environment affects the innate and acquired immune systems, as the ability to recognize antigens, defend against foreign invaders, and orchestrate repair is significantly hindered. However, the molecular mechanisms behind spaceflight-induced immune dysregulations are still unclear. In this study, blood from eleven (11) International Space Station (ISS) crewmembers was collected before, during and after long duration space missions, as well as from 11 matched ground control subjects. Transcriptomic analysis was performed in isolated peripheral blood mononuclear cells (PBMCs) using the RNA-sequencing technique. In comparison to the blood samples collected from the crewmembers pre-flight, a total of ~1000 genes were found to be upregulated and ~1000 genes downregulated in PBMC collected between 4 and 6 months after they were in space. The most significantly DEGs (differentially expressed genes) include activation of RUBCNL which is an autophagy enhancer and inhibition of GRASP which regulates cell trafficking. Genes involved in cell adhesion, cell cycle progression and other functions were also dysregulated. Pathway analysis of the DEGs indicates mitochondria dysfunction, particularly reduced ATP production in the electron transport chain. Other pathways impacted by spaceflight include glycolysis, autophagy and inflammatory response. Our results suggest that, in space, blood cells may have also experienced energy depletion and reduced metabolism. Consequently, the cells may become autophagic, which is a known homeostatic mechanism for blood cells to become quiescent, but to stay alive. Further analysis of the data shows recovery of the crewmembers after mission and potential differential responses between genders to the space environment. Our data potentially explains some of the physiological changes that have been observed in space such as mitochondria dysfunction, inhibition of T cell activation and telomere lengthening. Comparison of our results with other transcriptomics studies of ISS crewmembers’ blood cells will also be presented.

Maria Moreno Villanueva↗
NASA NTRS1994

Operations for Learning with Graphical Models

This paper is a multidisciplinary review of empirical, statistical learning from a graphical model perspective. Well-known examples of graphical models include Bayesian net- works, directed graphs representing a Markov chain, and undirected networks representing a Markov field. These graphical models are extended to model data analysis and empirical learning using the notation of plates. Graphical operations for simplifying and manipulating a problem are provided including decomposition, differentiation, and the manipulation of probability models from the exponential family. These operations adapt existing techniques from statistics and automatic differentiation to graphs. Two standard algorithm schemes for learning are reviewed in a graphical framework: Gibbs sampling and the expectation maximization algorithm. Some algorithms are developed in this graphical framework including a generalized version of linear regression, techniques for feed-forward networks, and learning Gaussian and discrete Bayesian networks from data. The paper concludes by sketching some implications for data analysis and summarizing some popular algorithms that fall within the framework presented. The main original contributions here are the decomposition techniques and the demonstration that graphical models provide a framework for understanding and developing complex learning algorithms.

Buntine, Wray L.↗
NASA NTRS1973

Normal mode analysis of a rotating group of lashed turbine blades by substructures

A group of 5 lashed identical stream turbine blades is studied through the use of single level substructuring using NASTRAN level 15.1. An altered version, similar to DMAP Program Number 3 of the NASTRAN Newsletter, of Rigid Format 13.0 was used. Steady-state displacements and stresses due to centrifugal loads are obtained both without and with consideration of differential stiffness. The normal mode calculations were performed for blades at rest and at operating speed. Substructuring lowered the computation costs of the analysis by a factor of four.

Filstrup, A. W.↗
NASA NTRS2019

Revolutionizing our Understanding of the Solar System via Sample Return from Mercury

Data from Mariner 10, MESSENGER, and ground-based telescopic observations have facilitated great advancements towards understanding the geochemistry, geology, internal structure, exosphere, and magnetosphere of Mercury. However, there are critical science questions that can be only addressed via examination of a sample in Earth-based laboratories, where numerous highly sensitive analytical measurements are possible. Collecting a sample from the surface of Mercury and bringing it to Earth for in-depth analysis would allow for transformative Solar System science to be conducted, examining aspects of our Solar System such as the evolution of the protoplanetary disk, space weathering on airless bodies, the geochemical behavior of elements at extreme conditions, and the origin and distribution of volatiles across the terrestrial planets. Furthermore, our knowledge of Mercury’s differentiation and geochemical processes, chronology and geologic evolution, tectonism and geomechanical properties, and past and ongoing magnetism would be greatly advanced via analysis of a sample from Mercury. Although there are ample challenges and knowledge gaps associated with sample return from Mercury in terms of both spacecraft requirements and material requirements for curatorial facilities, a sample from the planet would be an invaluable scientific resource for generations to come, enabling the most sophisticated measurements to be brought to bear for decades and helping to truly unlock the mysteries of our Solar System.

Vander Kaaden, Kathleen E.↗
NASA NTRS2026

Measure sea level air pressure from space to improve knowledge and forecasting of the atmospheric state

Modern numerical weather prediction (NWP) and analysis models require globally-observed meteorological data including sea-level pressure (SLP) for accurate operations. Up until now, SLP has only been measured by in situ instruments from ships, buoys, and ocean platforms. These measurements are sparse with large gaps, leaving models starved of this critical information to constrain the atmospheric state. Recent advancements in differential absorption radar (DAR) provide a path to close this critical observation gap through spaceborne observations in the coming decade, improving the analysis models relied upon for atmospheric research and the weather forecasts depended upon daily for public safety and commerce.

Matthew L Walker McLinden↗
DOE OSTI2021

Double-differential Measurements of Mesonless Charged-current Muon Neutrino Interactions on Argon with Final-State Protons using the MicroBooNE Detector

This note reports the first double-differential measurements of charged-current $ν_µ$ scattering on argon leading to final states containing zero mesons and one or more protons. This event topology (hereafter abbreviated as CC0$πNp$) is the most common at the neutrino energies typically produced by the Fermilab Booster Neutrino Beam. A detailed understanding of neutrino-argon scattering in the CC0$πNp$ channel is therefore crucial for the success of the precision neutrino oscillation analyses planned for the Short-Baseline Neutrino (SBN) program. This remains true for the upcoming Deep Underground Neutrino Experiment (DUNE), but the higher mean neutrino energy used there will ensure that more inelastic reaction modes, such as single pion production, will also play a major role. The analysis described in this note builds on a previous MicroBooNE study of the CC0$πNp$ channel which obtained the first single-differential cross-section measurements on an argon target. Since that foundational work, significant improvements have been made to MicroBooNE’s simulation software, event reconstruction algorithms, and procedure for calculating systematic uncertainties. When combined with a larger dataset (corresponding to a beam exposure of 6.79 × 10 20 protons-on-target versus 1.60 × 10 20 in Ref. [3]), these enhancements allow the important CC0$πNp$ channel to be studied in more detail. This note begins with a description of the data and simulation samples used as input to the analysis. Section 3 then defines the CC0$πNp$ signal event topology, and Section 4 describes a set of selection criteria designed to identify these events in MicroBooNE data. Binning schemes are then defined in Section 5 for two double-differential measurements of event rates. The first of these considers the momentum and scattering cosine of the outgoing muon, while the second reports the same observables for the leading proton, i.e., the final-state proton with the largest momentum. After a discussion of systematic uncertainties in Section 6, the note concludes by comparing the predictions of MicroBooNE Monte Carlo (MC) simulations to the measured double-differential distributions. These results will form the basis for a future extraction of flux-averaged double-differential CC0$πNp$ cross sections that will be immediately comparable to the theoretical predictions of multiple neutrino event generators. The selection described herein may also be used to study various other observables in CC0$πNp$ events, including those which are sensitive to correlations between leptonic and hadronic kinematics in the final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗