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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Revisiting studies of the statistical property of a strong gravitational lens system and model-independent constraint on the curvature of the universe

In this paper, we use a recently compiled data set, which comprises 118 galactic-scale strong gravitational lensing (SGL) systems to constrain the statistical property of the SGL system as well as the curvature of the universe without assuming any fiducial cosmological model. Based on the singular isothermal ellipsoid (SIE) model of the SGL system, we obtain that the constrained curvature parameter Ω{sub k} is close to zero from the SGL data, which is consistent with the latest result of Planck measurement. More interestingly, we find that the parameter f in the SIE model is strongly correlated with the curvature Ω{sub k}. Neglecting this correlation in the analysis will significantly overestimate the constraining power of SGL data on the curvature. Furthermore, the obtained constraint on f is different from previous results: f=1.105±0.030 (68% confidence level [C.L.]), which means that the standard singular isothermal sphere (SIS) model (f = 1) is disfavored by the current SGL data at more than a 3σ C.L. We also divide all of the SGL data into two parts according to the centric stellar velocity dispersion σ{sub c} and find that the larger the value of σ{sub c} for the subsample, the more favored the standard SIS model is. Finally, we extend the SIE model by assuming the power-law density profiles for the total mass density, ρ=ρ{sub 0}(r/r{sub 0}){sup −α}, and luminosity density, ν=ν{sub 0}(r/r{sub 0}){sup −δ}, and obtain the constraints on the power-law indices: α=1.95±0.04 and δ=2.40±0.13 at a 68% C.L. When assuming the power-law index α=δ=γ, this scenario is totally disfavored by the current SGL data, χ{sub min,γ}{sup 2}−χ{sub min,SIE}{sup 2}≃53.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1992

Dynamic test/analysis correlation using reduced analytical models

Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

Mcgowan, Paul E.↗
NASA NTRS1987

SPAN: Ocean science

The Space Physics Analysis Network (SPAN) is a multi-mission, correlative data comparison network which links space and Earth science research and data analysis computers. It provides a common working environment for sharing computer resources, sharing computer peripherals, solving proprietary problems, and providing the potential for significant time and cost savings for correlative data analysis. This is one of a series of discipline-specific SPAN documents which are intended to complement the SPAN primer and SPAN Management documents. Their purpose is to provide the discipline scientists with a comprehensive set of documents to assist in the use of SPAN for discipline specific scientific research.

Thomas, Valerie L.↗
NASA NTRS1992

Dynamic test/analysis correlation using reduced analytical models

Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System (IRS) reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

Mcgowan, Paul E.↗
NASA NTRS2005

Energy Finite Element Analysis for Computing the High Frequency Vibration of the Aluminum Testbed Cylinder and Correlating the Results to Test Data

The Energy Finite Element Analysis (EFEA) is a finite element based computational method for high frequency vibration and acoustic analysis. The EFEA solves with finite elements governing differential equations for energy variables. These equations are developed from wave equations. Recently, an EFEA method for computing high frequency vibration of structures either in vacuum or in contact with a dense fluid has been presented. The presence of fluid loading has been considered through added mass and radiation damping. The EFEA developments were validated by comparing EFEA results to solutions obtained by very dense conventional finite element models and solutions from classical techniques such as statistical energy analysis (SEA) and the modal decomposition method for bodies of revolution. EFEA results have also been compared favorably with test data for the vibration and the radiated noise generated by a large scale submersible vehicle. The primary variable in EFEA is defined as the time averaged over a period and space averaged over a wavelength energy density. A joint matrix computed from the power transmission coefficients is utilized for coupling the energy density variables across any discontinuities, such as change of plate thickness, plate/stiffener junctions etc. When considering the high frequency vibration of a periodically stiffened plate or cylinder, the flexural wavelength is smaller than the interval length between two periodic stiffeners, therefore the stiffener stiffness can not be smeared by computing an equivalent rigidity for the plate or cylinder. The periodic stiffeners must be regarded as coupling components between periodic units. In this paper, Periodic Structure (PS) theory is utilized for computing the coupling joint matrix and for accounting for the periodicity characteristics.

Vlahopoulos, Nickolas↗
DOE OSTI2025

A joint analysis of 3D clustering and galaxy × CMB-lensing cross-correlations with DESI DR1 galaxies

The spectroscopic data from DESI Data Release 1 (DR1) galaxies enables the analysis of 3D clustering by fitting galaxy power spectra and reconstructed correlation functions in redshift space. Given low measurements of the amplitude of structure from cosmic shear at z ∼ 1, redshift space distortions (RSD) + Baryon Acoustic Oscillation (BAO) signals from DESI galaxies combined with weak lensing can break degeneracies and provide a tight alternative constraint on the z ∼ 1 amplitude of structure. In this paper we perform joint analyses that combine full-shape + post-reconstruction information from the DESI DR1 BGS and LRG samples along with angular cross-correlations with Planck PR4 and ACT DR6 CMB lensing maps. We show that adding galaxy-lensing cross-correlations tightens clustering amplitude constraints, improving σ 8 uncertainties by 30% over RSD+BAO alone. We also include angular galaxy-galaxy and galaxy-lensing spectra using photometric samples from the DESI Legacy Survey to further improve constraints. Our headline results are σ 8 = 0.803 ± 0.017, Ω m = 0.3037 ± 0.0069, and S 8 = 0.808 ± 0.017. Given DESI's preference for higher σ 8 compared to lower values from BOSS, we perform a catalog-level comparison of LRG samples from both surveys. We test sensitivity to dark energy assumptions by relaxing our ΛCDM prior and allowing for evolving dark energy via the w 0 - w a parameterization. We find our S 8 constraints to be relatively unchanged despite a 3.5σ tension with the cosmological constant model when combining with the Union3 supernova likelihood. Finally we test general relativity (GR) by allowing the gravitational slip parameter (γ) to vary, and find γ = 1.17 ± 0.11 in mild (∼ 1.5σ) tension with the GR value of 1.0.

cosmological parameters from LSS↗
NASA NTRS1995

Quantitative analysis of volatile organic compounds using ion mobility spectra and cascade correlation neural networks

Ion Mobility Spectrometry (IMS) is a powerful technique for trace organic analysis in the gas phase. Quantitative measurements are difficult, because IMS has a limited linear range. Factors that may affect the instrument response are pressure, temperature, and humidity. Nonlinear calibration methods, such as neural networks, may be ideally suited for IMS. Neural networks have the capability of modeling complex systems. Many neural networks suffer from long training times and overfitting. Cascade correlation neural networks train at very fast rates. They also build their own topology, that is a number of layers and number of units in each layer. By controlling the decay parameter in training neural networks, reproducible and general models may be obtained.

Harrington, Peter DEB.↗
NASA NTRS2000

The Correlation Between Atmospheric Dust Deposition to the Surface Ocean and SeaWiFS Ocean Color: A Global Satellite-Based Analysis

Since the atmospheric deposition of iron has been linked to primary productivity in various oceanic regions, we have conducted an objective study of the correlation of dust deposition and satellite remotely sensed surface ocean chlorophyll concentrations. We present a global analysis of the correlation between atmospheric dust deposition derived from a satellite-based 3-D atmospheric transport model and SeaWiFs estimates of ocean color. We use the monthly mean dust deposition fields of Ginoux et al. which are based on a global model of dust generation and transport. This model is driven by atmospheric circulation from the Data Assimilation Office (DAO) for the period 1995-1998. This global dust model is constrained by several satellite estimates of standard circulation characteristics. We then perform an analysis of the correlation between the dust deposition and the 1998 SeaWIFS ocean color data for each 2.0 deg x 2.5 deg lat/long grid point, for each month of the year. The results are surprisingly robust. The region between 40 S and 60 S has correlation coefficients from 0.6 to 0.95, statistically significant at the 0.05 level. There are swaths of high correlation at the edges of some major ocean current systems. We interpret these correlations as reflecting areas that have shear related turbulence bringing nitrogen and phosphorus from depth into the surface ocean, and the atmospheric supply of iron provides the limiting nutrient and the correlation between iron deposition and surface ocean chlorophyll is high. There is a region in the western North Pacific with high correlation, reflecting the input of Asian dust to that region. The southern hemisphere has an average correlation coefficient of 0.72 compared that in the northern hemisphere of 0.42 consistent with present conceptual models of where atmospheric iron deposition may play a role in surface ocean biogeochemical cycles. The spatial structure of the correlation fields will be discussed within the context of guiding the design of field programs.

Erickson, D. J., III↗
DOE OSTI2019

Application of the ESMACS Binding Free Energy Protocol to a Multi-Binding Site Lactate Dehydogenase A Ligand Dataset

Over the past two decades, the use of fragment-based lead generation has become a common, mature approach to identify tractable starting points in chemical space for the drug discovery process. This approach naturally involves the study of the binding properties of highly heterogeneous ligands. Such datasets challenge computational techniques to provide comparable binding free energy estimates from different binding modes. The performance of a range of statistically robust ensemble-based binding free energy calculation protocols, called ESMACS (enhanced sampling of molecular dynamics with approximation of continuum solvent), is evaluated. Ligands designed to target two binding pockets in the lactate dehydogenase, a target protein, which vary in size, charge, and binding mode, are studied. When compared to experimental results, excellent statistical rankings are obtained across this highly diverse set of ligands. In addition, three approaches to account for entropic contributions are investigated: 1) normal mode analysis, 2) weighted solvent accessible surface area (WSAS), and 3) variational entropy. Normal mode analysis and WSAS correlate strongly with each other—although the latter is computationally far cheaper—but do not improve rankings. Variational entropy corrects exaggerated discrimination of ligands bound in different pockets but creates three outliers which reduce the quality of the overall ranking.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Multimodal Nanoscale Tomographic Imaging for Battery Electrodes

Accurate representations of the 3D structure within a lithium-ion battery are key to understanding performance limitations. However, obtaining exact reconstructions of electrodes, where the active particles, the carbon black and polymeric binder domain, and the pore space are visualized is challenging. In this work, it is shown that multimodal imaging can be used to overcome this challenge. High-resolution ptychographic X-ray computed tomography are combined with lower resolution but higher contrast transmission X-ray tomographic microscopy to obtain 3D reconstructions of pristine and cycled graphite-silicon composite electrodes. This cross-correlation enables quantitative analysis of the surface of active particles, including the heterogeneity of carbon-black and binder domain and solid-electrolyte interphase coverage. Capturing the active particles as well as the carbon black-binder domain allows using these segmented structures for electrochemical simulations to highlight the influence of the particle embedding on local state of charge heterogeneities.

25 ENERGY STORAGE↗
DOE OSTI2023

The Role of Transition Metals on Chemo-Mechanical Instabilities in Prussian Blue Analogues For K-Ion Batteries: The Case Study on KNHCF Versus KMHCF

Prussian blue analogues (PBAs) cathodes can host diverse monovalent and multivalent metal ions due to their tunable structure. However, their electrochemical performance suffers from poor cycle life associated with chemo-mechanical instabilities. This study investigates the driving forces behind chemo-mechanical instabilities in Ni- and Mn-based PBAs cathodes for K-ion batteries by combining electrochemical analysis, digital image correlation, and spectroscopy techniques. Capacity retention in Ni-based PBA is 96% whereas it is 91.5% for Mn-based PBA after 100 cycles at C/5 rate. During charge, the potassium nickel hexacyanoferrate (KNHCF) electrode experiences a positive strain generation whereas the potassium manganese hexacyanoferrate (KMHCF) electrode undergoes initially positive strain generation followed by a reduction in strains at a higher state of charge. Overall, both cathodes undergo similar reversible electrochemical strains in each charge–discharge cycle. There is ~0.80% irreversible strain generation in both cathodes after 5 cycles. XPS studies indicated richer organic layer compounds in the cathode-electrolyte interface (CEI) layer formed on KMHCF cathodes compared to the KNHCF ones. Faster capacity fades in Mn-based PBA, compared to Ni-based ones, is attributed to the formation of richer organic compounds in CEI layers, rather than mechanical deformations. In conclusion, understanding the driving forces behind instabilities provides a guideline to develop material-based strategies for better electrochemical performance.

25 ENERGY STORAGE↗
DOE OSTI2024

In‐mold rheology and automated process control for injection molding of recycled polypropylene

Abstract Manufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock. Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.

Krantz, Joshua↗
DOE OSTI2020

Spectral fluctuations in the Sachdev-Ye-Kitaev model

We present a detailed quantitative analysis of spectral correlations in the Sachdev-Ye-Kitaev (SYK) model. We find that the deviations from universal Random Matrix Theory (RMT) behavior are due to a small number of long-wavelength fluctuations (of the order of the number of Majorana fermions N ) from one realization of the ensemble to the next one. These modes can be parameterized effectively in terms of Q-Hermite orthogonal polynomials, the main contribution being due to scale fluctuations for which we give a simple analytical estimate. Our numerical results for N = 32 show that only the lowest eight polynomials are needed to eliminate the nonuniversal part of the spectral fluctuations. The covariance matrix of the coefficients of this expansion can be obtained analytically from low-order double-trace moments. We evaluate the covariance matrix of the first six moments and find that it agrees with the numerics. We also analyze the spectral correlations in terms of a nonlinear σ-model, which is derived through a Fierz transformation, and evaluate the one and two-point spectral correlation functions to two-loop order. The wide correlator is given by the sum of the universal RMT result and corrections whose lowest-order term corresponds to scale fluctuations. However, the loop expansion of the σ-model results in an ill-behaved expansion of the resolvent, and it gives universal RMT fluctuations not only for q= 4 or higher even q-body interactions, but also for the q= 2 SYK model albeit with a much smaller Thouless energy while the correct result in this case should have been Poisson statistics. In our numerical studies we analyze the number variance and spectral form factor for N = 32 and q = 4. We show that the quadratic deviation of the number variance for large energies appears as a peak for small times in the spectral form factor. After eliminating the long-wavelength fluctuations, we find quantitative agreement with RMT up to an exponentially large number of level spacings for the number variance or exponentially short times in the case of the spectral form factor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Creep Behavior and Phase Equilibria in Model Precipitate Strengthened Alumina-Forming Austenitic Alloys

Abstract Creep-rupture behavior and microstructural response in alumina-forming austenitic (AFA) alloys with two different precipitation strengthening mechanisms, “Laves-phase + M 23 C 6 carbide” and “coherent L1 2 γ′-Ni 3 (Al,Ti),” were explored as “model” cases of multi-phase, multi-scale heat-resistant AFA alloys for 650–750°C use. These alloys will be used to guide and verify computational alloy design and life-prediction modeling under an on-going eXtremeMAT project through the Office of Fossil Energy and Carbon Management, US Department of Energy. Computational thermodynamics were used to design and predict the amounts of strengthening and deteriorating secondary phases at 750°C. Creep-rupture lives of the alloys tested at 750°C and 100 MPa were in a range of 4000–9000 h, and the microstructure at the gage/grip after creep-rupture testing was compared with isothermally aged alloys for 1500 h, as well as the calculated phases. Detailed microstructure characterization includes phase identification, volume fraction measurement, and compositional analysis, which were correlated with the creep-rupture properties. High-temperature oxidation resistance was also screened and compared with commercial, chromia-forming heat-resistant steels. These model alloys also provide the basis for further design and optimization of next generation AFA alloys with improved creep resistance.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Quantification of grain rotation in bulk nanostructured copper via in situ heating white beam synchrotron X-ray diffraction

Grain rotation during microstructural relaxation under heating is conventionally studied extensively through transmission electron microscopy and simulations. However, there is a shortage in examining grain rotations at larger length and volume scales in bulk materials. It is critical to understand the thermal stability of bulk nanostructured metals, since those enhanced mechanical properties have been well recognized. Here, this study aimed to employ a white beam microdiffraction X-ray technique under in situ heating from 300 K to 1073 K at 12 K/min on a nanostructured copper processed by high-pressure torsion, yielding an initial grain size of ∼260 nm before the heating. Evaluation across a wide range of temperatures reveals transition temperatures associated with microstructural relaxation processes. By tracking separate Laue diffraction peaks stemming from individual grains, changes in their orientations can be estimated and quantified. This approach becomes particularly effective when the number of grains within the probed volume is reasonably small. At temperatures above 940 K, about 7.5 % of Cu grains are rotating at speeds of ∼2 × 10 –3 °/s. The radial direction of the disk specimen is found to be the preferred direction of grain rotation, with the rotation axis along the shear direction. Further analysis found no correlation between peak intensity and peak size, related to grain sizes and deviatoric strain, respectively, with rotation conditions or speed. These findings demonstrate that the diffraction technique utilizing white beam X-rays is a complementary and novel characterization tool for understanding microstructural evolution, especially in grain rotations, of bulk crystalline materials.

Grain orientation↗
DOE OSTI2015

Efficient and dynamic nuclear localization of green fluorescent protein via RNA binding

Classical nuclear localization signal (NLS) sequences have been used for artificial localization of green fluorescent protein (GFP) in the nucleus as a positioning marker or for measurement of the nuclear-cytoplasmic shuttling rate in living cells. However, the detailed mechanism of nuclear retention of GFP-NLS remains unclear. Here, we show that a candidate mechanism for the strong nuclear retention of GFP-NLS is via the RNA-binding ability of the NLS sequence. GFP tagged with a classical NLS derived from Simian virus 40 (GFP-NLS{sup SV40}) localized not only in the nucleoplasm, but also to the nucleolus, the nuclear subdomain in which ribosome biogenesis takes place. GFP-NLS{sup SV40} in the nucleolus was mobile, and intriguingly, the diffusion coefficient, which indicates the speed of diffusing molecules, was 1.5-fold slower than in the nucleoplasm. Fluorescence correlation spectroscopy (FCS) analysis showed that GFP-NLS{sup SV40} formed oligomers via RNA binding, the estimated molecular weight of which was larger than the limit for passive nuclear export into the cytoplasm. These findings suggest that the nuclear localization of GFP-NLS{sup SV40} likely results from oligomerization mediated via RNA binding. The analytical technique used here can be applied for elucidating the details of other nuclear localization mechanisms, including those of several types of nuclear proteins. In addition, GFP-NLS{sup SV40} can be used as an excellent marker for studying both the nucleoplasm and nucleolus in living cells. - Highlights: • Nuclear localization signal-tagged GFP (GFP-NLS) showed clear nuclear localization. • The GFP-NLS dynamically localized not only in the nucleoplasm, but also to the nucleolus. • The nuclear localization of GFP-NLS results from transient oligomerization mediated via RNA binding. • Our NLS-tagging procedure is ideal for use in artificial sequestration of proteins in the nucleus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

PDGF family function and prognostic value in tumor biology

Highlights: • Large scale transcriptomic data analysis reveals tumor-specific roles of PDGF signaling. • Functional gene sets associated with PDGF expression are conserved between PDGF family members. • PDGF related gene signatures have increased prognostic value over each single gene. The development and progression of a tumor depends on the close interaction of malignant cells and the supportive and suppressive tumor microenvironment. Paracrine signaling enables tumor cells to shape the surrounding tissue in order to decrease recognition by the immune system, attract blood vessels to fuel growth, change metabolic programs, and induce wound healing programs. In this study, we investigate the role of the platelet-derived growth factor (PDGF) family members PDGFA, PDGFB, PDGFC and PDGFD and their cognate tyrosine kinase receptors PDGFRA and PDGFRB, using publicly available data from The Cancer Genome Atlas and the Human Protein Atlas. Large scale analysis of expression correlation in RNA sequencing data from 7616 samples derived from 16 tumor types, revealed conserved functional programs in PDGF signaling in the majority of solid tumor types. Besides the well-known effects of PDGF signaling in mesenchymal cells, our analyses revealed a potential role of PDGF signaling in the composition of the immune microenvironment. We furthermore derived gene signatures with increased prognostic value for each PDGF family member. This study emphasizes the potential to impinge on specific paracrine signaling events to interfere with the crosstalk between malignant cells and their microenvironment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Artificial Transmembrane Channel Constructed from Shape-Persistent Covalent Organic Molecular Cages Capable of Ion and Small Molecule Transport

Shape-persistent arylene ethynylene molecular cages have been investigated as transmembrane channels for ions and small molecules. The molecular cages were obtained starting from tetrayne monomers through alkyne metathesis cyclooligomerization. We found these porphyrin-based rigid molecular cages can insert into the lipid bilayer and efficiently transport ions and small molecules (e.g., calcein). Our study reveals longer hydrophobic alkyl chains on the cage molecule promote the channeling efficiency, while shorter and/or more polar side chains impair such activity. Kinetic analysis shows linear correlation between the rate of proton transport and the concentration of the cage, suggesting the active species is likely a monomeric cage. We found that C70-encapsulated cages are nearly inactive for transmembrane ion transportation, indicating that ions are likely transported through the internal cavity of the cage. Discrete shape-persistent organic cages represent highly stable synthetic ion channels or pores, which could have interesting applications in biomimetic signaling and drug delivery.

alkyne metathesis↗