Search NASA⌕ Search

SEARCH · Search NASA

Results for “test correlation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 271 records · Page 15

Deformation and Failure Mechanisms of Shape Memory Alloys

The goal of this research was to understand the fundamental mechanics that drive the deformation and failure of shape memory alloys (SMAs). SMAs are difficult materials to characterize because of the complex phase transformations that give rise to their unique properties, including shape memory and superelasticity. These phase transformations occur across multiple length scales (one example being the martensite-austenite twinning that underlies macroscopic strain localization) and result in a large hysteresis. In order to optimize the use of this hysteretic behavior in energy storage and damping applications, we must first have a quantitative understanding of this transformation behavior. Prior results on shape memory alloys have been largely qualitative (i.e., mapping phase transformations through cracked oxide coatings or surface morphology). The PI developed and utilized new approaches to provide a quantitative, full-field characterization of phase transformation, conducting a comprehensive suite of experiments across multiple length scales and tying these results to theoretical and computational analysis. The research funded by this award utilized new combinations of scanning electron microscopy, diffraction, digital image correlation, and custom testing equipment and procedures to study phase transformation processes at a wide range of length scales, with a focus at small length scales with spatial resolution on the order of 1 nanometer. These experiments probe the basic connections between length scales during phase transformation. In addition to the insights gained on the fundamental mechanisms driving transformations in shape memory alloys, the unique experimental methodologies developed under this award are applicable to a wide range of solid-to-solid phase transformations and other strain localization mechanisms.

36 MATERIALS SCIENCE↗

High-Activity Dealloyed Catalysts

Reduction of costly Pt usage in proton exchange membrane fuel cell electrodes is one of the major challenges towards development and commercialization of fuel cell vehicles. Although few have met the initial-kinetic activity requirements in a realistic fuel cell device, no catalyst material has ever met the demanding fuel cell durability targets set by DOE. In this project, a team of 4 universities and 2 companies came together to investigate a concept that appeared promising in preliminary non-fuel cell tests then to further develop the catalyst to a mature level ready for vehicle implementation. The team consists of academia with technical leadership in their respective areas, a catalyst supplier, and a fuel cell system integrator.The tightly collaborative project enabled development of a highly active and durable catalyst with performance that significantly exceeds that of previous catalysts and meets the DOE targets for the first time (Figure 1A). The catalyst was then further evaluated in full-active-area stack in a realistic vehicle operating condition (Figure 1B). This is the first public demonstration that one can realize the performance benefit and Pt cost reduction over a conventional pure Pt catalyst in a long-term realistic PEMFC system. Furthermore, systematic analyses of a range of catalysts with different performance after fuel cell testing allowed for correlation between catalyst microstructure and its electrocatalytic activity and durability. This will in turn aid future catalyst development.

30 DIRECT ENERGY CONVERSION↗

Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud-Resolving Model Inter-comparison and Cross-Validation using Radar Observations

Evolution of precipitation structures are simulated and compared with radar observations for the November Madden-Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground-based, ship-borne, and space-borne precipitation radars and three Cloud-Resolving Models (CRMs) driven by observed large-scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0-dBZ echo-top heights, and convective organization by contiguous 17-dBZ areas. The multi-radar and multi-model framework allows for more stringent model validations. The emphasis is on testing models’ ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site-specific large-scale forcing can reproduce not only common features in cloud populations, but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo-top heights for the strongest convection within large, organized precipitation features. Cross-validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large-scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo-top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well-validated model simulations could be used to constrain uncertainties in observed echo-top heights when the low-resolution surveillance scanning strategy is used.

54 ENVIRONMENTAL SCIENCES↗

Develop a new integrated macro→micro←nano (MMN) multiscale modeling framework to optimize high strength aluminum alloys and processes for vehicle light-weighting​

Bending tests provide a means to study plane strain fracture performance of 6000 series aluminum alloys. Metrics from bending tests have been correlated with self-pierce riveting (SPR) performance of a high strength AA6111 automotive aluminum alloy in previous works. Using the ORNL HPC resources, this project developed an innovative macro→micro←nano (MMN) multiscale microstructure-based finite element (FE) code to further the understanding of microstructural relationship to fracture properties of high strength 6000 series alloys.

36 MATERIALS SCIENCE↗

Tribological bench and engine dynamometer tests of a low viscosity SAE 0W-16 engine oil using a combination of ionic liquid and ZDDP as anti-wear additives

We have previously reported an oil-miscible phosphonium-organophosphate ionic liquid (IL) with an effective anti-wear (AW) functionality when added to a base oil by itself or combined with a conventional zinc dialkyldithiophosphate (ZDDP) for a synergistic effect. In this research, we investigated whether this synergy manifests in formulated engine oils. An experimental SAE 0W-16 engine oil was generated containing a combination of IL and ZDDP with equal phosphorus contribution. The prototype engine oil was first evaluated using tribological bench tests: AW performance in boundary lubrication (BL) and friction behavior (Stribeck curves) in elastohydrodynamic, mixed, and BL. In addition, the forthcoming standard Sequence VIE engine dynamometer test was then conducted to demonstrate improved fuel economy. Results were benchmarked against those of another experimental engine oil with almost the same formulation except using ZDDP only without the IL (similar total phosphorus content). The IL-ZDDP formulation consistently outperforms the ZDDP-only formulation in friction reduction and wear protection, and results from the bench and engine tests are well correlated.

42 ENGINEERING↗

A Comparative study of two RVE modelling methods for chopped carbon fiber SMC

To achieve vehicle light-weighting, the chopped carbon fiber sheet molding compound (SMC) is identified as a promising material to replace metals. However, there are no effective tools and methods to predict the mechanical property of the chopped carbon fiber SMC due to the high complexity in microstructure features and the anisotropic properties. In this paper, the Representative Volume Element (RVE) approach is used to model the SMC microstructure. Two modeling methods, the Voronoi diagram-based method and the chip packing method, are developed for material RVE property prediction. The two methods are compared in terms of the predicted elastic modulus and the predicted results are validated using the Digital Image Correlation (DIC) tensile test results. Furthermore, the advantages and shortcomings of these two methods are discussed in terms of the required input information and the convenience of use in the integrated processing-microstructure-property analysis.

mesostructure reconstruction↗

Data-driven model validation for neutrino-nucleus cross section measurements

Neutrino-nucleus cross section measurements are needed to improve interaction modeling to meet the precision needs of neutrino experiments in efforts to measure oscillation parameters and search for physics beyond the Standard Model. We review the difficulties associated with modeling neutrino-nucleus interactions that lead to a dependence on event generators in oscillation analyses and cross section measurements alike. We then describe data-driven model validation techniques intended to address this model dependence. The method relies on utilizing various goodness-of-fit tests and the correlations between different observables and channels to probe the model for defects in the phase space relevant for the desired analysis. These techniques shed light on relevant mismodeling, allowing it to be detected before it begins to bias the cross section results. We compare more commonly used model validation methods which directly validate the model against alternative ones to these data-driven techniques and show their efficacy with fake data studies. These studies demonstrate that employing data-driven model validation in cross section measurements represents a reliable strategy to produce robust results that will stimulate the desired improvements to interaction modeling.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

First Season QUIET Observations: Measurements of CMB Polarization Power Spectra at 43 GHz in the Multipole Range 25 <= ell <= 475

The Q/U Imaging ExperimenT (QUIET) employs coherent receivers at 43GHz and 95GHz, operating on the Chajnantor plateau in the Atacama Desert in Chile, to measure the anisotropy in the polarization of the CMB. QUIET primarily targets the B modes from primordial gravitational waves. The combination of these frequencies gives sensitivity to foreground contributions from diffuse Galactic synchrotron radiation. Between 2008 October and 2010 December, over 10,000 hours of data were collected, first with the 19-element 43-GHz array (3458 hours) and then with the 90-element 95-GHz array. Each array observes the same four fields, selected for low foregrounds, together covering {approx} 1000 square degrees. This paper reports initial results from the 43-GHz receiver which has an array sensitivity to CMB fluctuations of 69 {mu}K{radical}s. The data were extensively studied with a large suite of null tests before the power spectra, determined with two independent pipelines, were examined. Analysis choices, including data selection, were modified until the null tests passed. Cross correlating maps with different telescope pointings is used to eliminate a bias. This paper reports the EE, BB, and EB power spectra in the multipole range {ell} = 25-475. With the exception of the lowest multipole bin for one of the fields, where a polarized foreground, consistent with Galactic synchrotron radiation, is detected with 3-{sigma} significance, the E-mode spectrum is consistent with the {Lambda}CDM model, confirming the only previous detection of the first acoustic peak. The B-mode spectrum is consistent with zero, leading to a measurement of the tensor-to-scalar ratio of r = 0.35{sub -0.87}{sup +1.06}. The combination of a new time-stream 'double-demodulation' technique, Mizuguchi-Dragone optics, natural sky rotation, and frequent boresight rotation leads to the lowest level of systematic contamination in the B-mode power so far reported, below the level of r = 0.1.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Diagnosing Undersampling in Monte Carlo Eigenvalue and Flux Tally Estimates

This study explored the impact of undersampling on the accuracy of tally estimates in Monte Carlo (MC) calculations. Steady-state MC simulations were performed for models of several critical systems with varying degrees of spatial and isotopic complexity, and the impact of undersampling on eigenvalue and fuel pin flux/fission estimates was examined. This study observed biases in MC eigenvalue estimates as large as several percent and biases in fuel pin flux/fission tally estimates that exceeded tens, and in some cases hundreds, of percent. This study also investigated five statistical metrics for predicting the occurrence of undersampling biases in MC simulations. Three of the metrics (the Heidelberger-Welch RHW, the Geweke Z-Score, and the Gelman-Rubin diagnostics) are commonly used for diagnosing the convergence of Markov chains, and two of the methods (the Contributing Particles per Generation and Tally Entropy) are new convergence metrics developed in the course of this study. These metrics were implemented in the KENO MC code within the SCALE code system and were evaluated for their reliability at predicting the onset and magnitude of undersampling biases in MC eigenvalue and flux tally estimates in two of the critical models. Of the five methods investigated, the Heidelberger-Welch RHW, the Gelman-Rubin diagnostics, and Tally Entropy produced test metrics that correlated strongly to the size of the observed undersampling biases, indicating their potential to effectively predict the size and prevalence of undersampling biases in MC simulations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Diagnosing undersampling in Monte Carlo eigenvalue and flux tally estimates - 14515

This study explored the impact of undersampling on the accuracy of tally estimates in Monte Carlo (MC) calculations. Steady-state MC simulations were performed for models of several critical systems with varying degrees of spatial and isotopic complexity, and the impact of undersampling on eigenvalue and fuel pin flux/fission estimates was examined. This study observed biases in MC eigenvalue estimates as large as several percent and biases in fuel pin flux/fission tally estimates that exceeded tens, and in some cases hundreds, of percent. This study also investigated five statistical metrics for predicting the occurrence of undersampling biases in MC simulations. Three of the metrics (the Heidelberger-Welch RHW, the Geweke Z-Score, and the Gelman-Rubin diagnostics) are commonly used for diagnosing the convergence of Markov chains, and two of the methods (the Contributing Particles per Generation and Tally Entropy) are new convergence metrics developed in the course of this study. These metrics were implemented in the KENO MC code within the SCALE code system and were evaluated for their reliability at predicting the onset and magnitude of undersampling biases in MC eigenvalue and flux tally estimates in two of the critical models. Of the five methods investigated, the Heidelberger-Welch RHW, the Gelman-Rubin diagnostics, and Tally Entropy produced test metrics that correlated strongly to the size of the observed undersampling biases, indicating their potential to effectively predict the size and prevalence of undersampling biases in MC simulations. (authors)

42 ENGINEERING↗

Galaxy Clusters Selected via the Sunyaev-Zel'dovich Effect in 5 year data from the SPT-3G Main Survey

We report a new galaxy cluster catalog, selected using the thermal Sunyaev-Zel'dovich (SZ) effect, from 5 years of observations of the SPT-3G Main field. Drawn from arcminute-resolution data with white noise levels of 3.2, 2.5, and 8.9 $μ$K-arcmin at 95, 150, and 220 GHz, respectively, the sample consists of 8,892 cluster candidates detected above significance $ξ=4$, with an expected purity of $>82\%$ (4,480 at $ξ\ge5$ with purity $>99\%$). Using optical and infrared data we have confirmed 7,190 candidates as clusters. The sample spans a mass range $7.9 \times 10^{13}M_\odot/h_{70}< M_\textrm{500c} < 1.6 \times 10^{15}M_\odot/h_{70}$ with a median mass of $1.65 \times 10^{14}M_\odot/h_{70}$, and a redshift range of $0.0371$ and 271 at $z>1.5$. Compared to previous SZ cluster samples from South Pole Telescope and Atacama Cosmology Telescope data, the SPT-3G sample is highly consistent in mass and redshift but is significantly deeper, with per-cluster detection signal-to-noise 2-4 times higher and a cluster density of 4.5 confirmed clusters/deg$^2$. We cross match with eRASS1 cluster and point source catalogs, finding 1,279 and 1,319 matches, respectively. The SPT and eROSITA cluster mass estimates are in relatively good agreement. We perform a series of validation checks using both internal data splits and comparisons to external samples. These tests show increasing correlated (dusty) emission with redshift, with a $\sim17\times$ larger 220 GHz temperature increment for clusters at $z\sim1.5$ than $z\sim0.25$, but only weak evidence for correlated synchrotron emission. Finally, a number of clusters are flagged as candidate strong gravitational lenses.

Bleem, L. E. [Argonne (main); Chicago U., KICP; Ch↗

Joint analysis of Dark Energy Survey Year 3 data and CMB lensing from SPT and Planck . III. Combined cosmological constraints

Here we present cosmological constraints from the analysis of two-point correlation functions between galaxy positions and galaxy lensing measured in Dark Energy Survey (DES) Year 3 data and measurements of cosmic microwave background (CMB) lensing from the South Pole Telescope (SPT) and Planck. When jointly analyzing the DES-only two-point functions and the DES cross-correlations with SPT+Planck CMB lensing, we find Ω m = 0.344 ± 0.030 and S 8 ≡ σ 8 (Ω m /0.3) 0.5 = 0.773 ± 0.016, assuming ΛCDM. When additionally combining with measurements of the CMB lensing autospectrum, we find Ω m = 0.306$^{+0.018}_{-0.021}$ and S 8 = 0.792 ± 0.012. The high signal-to-noise of the CMB lensing cross-correlations enables several powerful consistency tests of these results, including comparisons with constraints derived from cross-correlations only, and comparisons designed to test the robustness of the galaxy lensing and clustering measurements from DES. Applying these tests to our measurements, we find no evidence of significant biases in the baseline cosmological constraints from the DES-only analyses or from the joint analyses with CMB lensing cross-correlations. However, the CMB lensing cross-correlations suggest possible problems with the correlation function measurements using alternative lens galaxy samples, in particular the redMaGiC galaxies and high-redshift MagLim galaxies, consistent with the findings of previous studies. We use the CMB lensing cross-correlations to identify directions for further investigating these problems.

79 ASTRONOMY AND ASTROPHYSICS↗

Hypothesis tests for the detection of constant speed radiation moving sources

Radiation Portal Monitors are deployed in linear network to detect radiological material in motion. As a complement to single and multichannel detection algorithms, inefficient under too low signal to noise ratios, temporal correlation algorithms have been introduced. Test hypothesis methods based on empirically estimated mean and variance of the signals delivered by the different channels have shown significant gain in terms of a tradeoff between detection sensitivity and false alarm probability. This paper discloses the concept of a new hypothesis test for temporal correlation detection methods, taking advantage of the Poisson nature of the registered counting signals, and establishes a benchmark between this test and its empirical counterpart. The simulation study validates that in the four relevant configurations of a pedestrian source carrier under respectively high and low count rate radioactive background, and a vehicle source carrier under the same respectively high and low count rate radioactive background, the newly introduced hypothesis test ensures a significantly improved compromise between sensitivity and false alarm, while guaranteeing the stability of its optimization parameter regardless of signal to noise ratio variations between 2 to 0.8. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Evaluation of getters for methane and ammonia decomposition

Getters are used in many tritium purification systems for impurity removal. One getter material, SAES® ST909, can be used to decompose various impurities (methane, carbon oxides, ammonia and others), and release the hydrogen bound in these compounds for further processing. Because, ST909 absorbs eight to nine percent of its initial weight in nitrogen, alternate materials may provide greater operational flexibility to accommodate variable operating carrier gases. The gettering capability of ST909 is related to the tri-metallic alloy (zirconium, manganese, and iron) composition. However, simply using a material with the same composition may not provide similar methane and ammonia decomposition conversion efficiency. For this testing, alternative materials to ST909 are compared to track methane and ammonia decomposition performance. Bench scale tests were performed at elevated temperature using various gas mixtures. Changes in methane and ammonia decomposition performance were tracked using RGA analysis during bench scale testing. Analytical comparisons of chemically equivalent materials to ST909 were also performed and correlated to bench scale test results. Characterization testing performed to evaluate chemically equivalent materials included: X-ray fluorescence, X-ray diffraction, and inductively coupled plasma-mass spectrometry (ICP-MS). Results are expounded upon and differences in gettering capability of alternate materials are highlighted.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effective thermal conductivity of insulation materials for cryogenic LH 2 storage tanks: A review

An accurate estimation of the effective thermal conductivity of various insulation materials is essential in the evaluation of heat leak and boil-off rate from liquid hydrogen storage tanks. In this work, we review the existing experimental data and various proposed correlations for predicting the effective conductivity of insulation systems consisting of powders, foams, fibrous materials, and multilayer systems. We also propose a first principles-based correlation that may be used to estimate the dependence of the effective conductivity as a function of temperature, interstitial gas composition, pressure, and structural properties of the material. We validate the proposed correlation using available experimental data for some common insulation materials. Further improvements and testing of the proposed correlation using laboratory scale data obtained using potential LH 2 tank insulation materials are also discussed.

08 HYDROGEN↗

Microbial Community Dynamics and Activity Link to Indigo Production from Indole in Bioaugmented Activated Sludge Systems

Biosynthesis of the popular dyestuff indigo from indole has been comprehensively studied using pure cultures, but less has been done to characterize the indigo production by microbial communities. In our previous studies, a wild strain Comamonas sp. MQ was isolated from activated sludge and the recombinant Escherichia coli nagAc carrying the naphthalene dioxygenase gene (nag) from strain MQ was constructed, both of which were capable of producing indigo from indole. Herein, three activated sludge systems, G1 (non-augmented control), G2 (augmented with Comamonas sp. MQ), and G3 (augmented with recombinant E. coli nagAc), were constructed to investigate indigo production. After 132-day operation, G3 produced the highest yields of indigo (99.5 ± 3.0 mg/l), followed by G2 (27.3 ± 1.3 mg/l) and G1 (19.2 ± 1.2 mg/l). The microbial community dynamics and activities associated with indigo production were analyzed by Illumina Miseq sequencing of 16S rRNA gene amplicons. The inoculated strain MQ survived for at least 30 days, whereas E. coli nagAc was undetectable shortly after inoculation. Quantitative real-time PCR analysis suggested the abundance of naphthalene dioxygenase gene (nagAc) from both inoculated strains was strongly correlated with indigo yields in early stages (0–30 days) (P < 0.001) but not in later stages (30–132 days) (P > 0.10) of operation. Based on detrended correspondence analysis (DCA) and dissimilarity test results, the communities underwent a noticeable shift during the operation. Among the four major genera (> 1% on average), the commonly reported indigo-producing populations Comamonas and Pseudomonas showed no positive relationship with indigo yields (P > 0.05) based on Pearson correlation test, while Alcaligenes and Aquamicrobium, rarely reported for indigo production, were positively correlated with indigo yields (P < 0.05). This study should provide new insights into our understanding of indigo bio-production by microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

Unveiling damage mechanisms of chromium-coated zirconium-based fuel claddings at LWR operating temperature by in-situ digital image correlation

Here, we investigate the coupled thermomechanical fracture mechanisms of coated nuclear fuel claddings at Light Water Reactor (LWR) operating temperatures. These coated claddings are a highly attractive, near-term solution, which addresses the demands for accident-tolerant fuel systems and provide greater oxidation resistance. However, the fracture mechanisms of these coatings, which may create channels for oxidation ingression, must be fully understood prior to implementation. Thus, high-temperature expanding plug experiments were conducted on coated cladding specimens at a temperature of 315 °C, consistent with the operating environment of LWRs. Furthermore, in-situ thermomechanical deformation was measured with stereo digital image correlation during heating and mechanical testing to separately resolve contributions of thermal and mechanical strain. Digital image correlation, supported by acoustic emissions (AE) detection, was also leveraged to track cracking activity during loading. Coating fracture was found to initiate at total hoop strains of 0.34%. The thermal deformation of the coated claddings was investigated via finite element simulations, revealing a bidirectional stress-state within the coating with axial and circumferential strains of 0.026 and 0.031%. This bidirectional stress-state was attributed with the generation of off-axis fracture pattern within the coating as identified via post-experiment scanning electron microscopy. Thus, this study unveiled critical, coupled thermomechanical mechanisms governing the coating fracture of coated claddings at LWR temperatures.

36 MATERIALS SCIENCE↗

A free association semantic task for fNIRS-based perinatal depression assessment

Perinatal depression (PD) is a highly prevalent psychological disorder that has a detrimental effect on infant and maternal physical and mental health, but effective and objective assessment of PD is still insufficient. In recent years, the functional near-infrared spectroscopy (fNIRS) has been acknowledged as an effective non-invasive tool for clinical assessment of depression. This study proposed a free association semantic task (FAST) paradigm for fNIRS-based assessment of PD. To better address the emotion characteristics of PD, the participants are required to generate a dynamic concept chain based on positive, negative or neutral seed words, while 48-channel fNIRS recordings over frontal and bilateral temporal regions. Results from twenty-two late-pregnant women revealed that, the oxyhemoglobin (oxy-Hb) changes during the FAST with the positive and negative seed words over the frontal region were correlated with PD severity, which was different from the correlation patterns in the FAST with neutral seed word and the classical verbal fluency test (VFT). Furthermore, distinct correlation patterns were also observed in the FAST with the positive and negative seed words, manifested in fNIRS channels corresponding to the right dorsolateral prefrontal cortex (DLPFC) and right inferior frontal gyrus (IFG), respectively. Moreover, regression analyses showed that the FAST with positive and negative seed words can well explain the severity of PD. Our findings suggest the proposed FAST paradigm as a promising approach for PD assessment.

Chen, Danni↗