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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 OSTI2015

Composition mediated serration dynamics in Zr-based bulk metallic glasses

The composition mediated serration dynamics in Zr-based bulk metallic glasses (BMGs) is investigated by statistics analyses of the elastic-energy density, and free volumes during shear-banding are beneficial to understand serrated-flow behavior. The amplitude and elastic-energy density display a gradually increasing and then decreasing trend with increasing the content of Zr. It is based on the free-volume theory describing the atomic-level structure of ternary Zr-Cu-Al BMGs. The good agreement between the molecular dynamics simulation and experimental results provides evidence for the variation of free volumes as the elementary mechanism of composition mediated serration dynamics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Multitaper Magnitude‐Squared Coherence for Time Series With Missing Data: Understanding Oscillatory Processes Traced by Multiple Observables

To explore the hypothesis of a common source of variability in two time series, observers may estimate the magnitude-squared coherence (MSC), which is a frequency-domain view of the cross correlation. For time series that do not have uniform observing cadence, MSC can be estimated using Welch's overlapping segment averaging. However, multitaper has superior statistical properties to Welch's method in terms of the tradeoff between bias, variance, and bandwidth. The classical multitaper technique has recently been extended to accommodate time series with underlying uniform observing cadence from which some observations are missing. This situation is common for solar and geomagnetic data sets, which may have gaps due to breaks in satellite coverage, instrument downtime, or poor observing conditions. We demonstrate the scientific use of missing-data multitaper magnitude-squared coherence by detecting known solar mid-term oscillations in simultaneous, missing-data time series of solar Lyman α flux and geomagnetic Disturbance Storm Time index. Due to their superior statistical properties, we recommend that multitaper methods be used for all heliospheric time series with underlying uniform observing cadence.

Astro-statistics techniques (1886)↗
DOE OSTI2023

Kernel-based global sensitivity analysis obtained from a single data set

Results from global sensitivity analysis (GSA) often guide the understanding of complicated input–output systems. Kernel-based GSA methods have recently been proposed for their capability of treating a broad scope of complex systems. In this paper, we develop a new set of kernel GSA tools when only a single set of input–output data is available. Three key advances are made: (1) A new numerical estimator is proposed that demonstrates an empirical improvement over previous procedures. (2) A computational method for generating inner statistical functions from a single data set is presented. (3) A theoretical extension is made to define conditional sensitivity indices, which reveal the degree that the inputs carry shared information about the output when inherent input–input correlations are present. Utilizing these conditional sensitivity indices, a decomposition is derived for the output uncertainty based on what is called the optimal learning sequence of the input variables, which remains consistent when correlations exist between the input variables. Further, while these advances cover a range of GSA subjects, a common single data set numerical solution is provided by a technique known as the conditional mean embedding of distributions. The new methodology is implemented on benchmark systems to demonstrate the provided insights.

42 ENGINEERING↗
DOE OSTI2026

Excited-state uncertainties in lattice-QCD calculations of multi-hadron systems

Excited-state effects lead to hard-to-quantify systematic uncertainties in lattice quantum chromodynamics (LQCD) spectroscopy calculations when computationally accessible imaginary times are smaller than inverse excitation gaps, as often arises for multi-hadron systems with signal-to-noise problems. Lanczos residual bounds address this by providing two-sided constraints on energies that do not require assumptions beyond Hermiticity, but often give very conservative systematic uncertainty estimates. Here, a more-constraining set of gap bounds is introduced for hadron spectroscopy. These bounds provide tighter constraints whose validity requires an explicit assumption about an energy gap. Exactly solvable lattice field theory correlators are used to test the utility of residual and gap bounds at finite and infinite statistics. Two-sided bounds and other analysis methods are then applied to a high-statistics LQCD calculation of nucleon-nucleon scattering at $m_π\sim 800$ MeV. Generalized eigenvalue problem (GEVP) and Lanczos energy estimators are compatible when applied to the same correlator data, but analyses including different interpolating operators show statistically significant inconsistencies. However, two-sided bounds from all operators are consistent. Under the assumption that the number of energy levels below $NΔ$ and $ΔΔ$ thresholds is the same as for non-interacting nucleons, gap bounds are sufficient to constrain nucleon-nucleon scattering amplitudes at phenomenologically relevant precision. Lanczos methods further reveal that energy-eigenstate estimates from previously studied asymmetric correlators have not converged over accessible imaginary times. Nevertheless, data-driven examples demonstrate why assumptions are required to draw conclusions about the natures of two-nucleon ground states at these masses.

Detmold, William [MIT, Cambridge, CTP]↗
DOE OSTI2016

Warm dark matter via ultra-violet freeze-in: reheating temperature and non-thermal distribution for fermionic Higgs portal dark matter

Warm dark matter (WDM) of order keV mass may be able to resolve the disagreement between structure formation in cold dark matter simulations and observations. The detailed properties of WDM will depend upon its energy distribution, in particular how it deviates from the thermal distribution usually assumed in WDM simulations. Here we focus on WDM production via the Ultra-Violet (UV) freeze-in mechanism, for the case of fermionic Higgs portal dark matter ψ produced via the portal interaction ψ-barψH{sup †}H/Λ. We introduce a new method to simplify the computation of the non-thermal energy distribution of dark matter from freeze-in. We show that the non-thermal energy distribution from UV freeze-in is hotter than the corresponding thermal distribution and has the form of a Bose-Einstein distribution with a non-thermal normalization. The resulting range of dark matter fermion mass consistent with observations is 5–7 keV. The reheating temperature must satisfy T{sub R}≳120 GeV in order to account for the observed dark matter density when m{sub ψ}≈5 keV, where the lower bound on T{sub R} corresponds to the limit where the fermion mass is entirely due to electroweak symmetry breaking via the portal interaction. The corresponding bound on the interaction scale is Λ≳6.0×10{sup 9} GeV.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2013

U.S. residential consumer product information: Validation of methods for post-stratification weighting of Amazon Mechanical Turk surveys

We present two post-stratification weighting methods to validate survey data collected using Amazon Mechanical Turk (AMT). Two surveys focused on appliance and consumer electronics devices were administered in the spring and summer of 2012 to each of approximately 3,000 U.S. households. Specifically, the surveys asked questions about residential refrigeration products, televisions (TVs) and set-top boxes (STBs). Filtered data were assigned weights using each of two weighting methods, termed “sequential” and “simultaneous,” by examining up to eight demographic variables (income, education, gender, race, Hispanic origin, number of occupants, ages of occupants, and geographic region) in comparison to reference U.S. demographic data from the 2009 Residential Energy Consumption Survey (RECS). Five key questions from the surveys (number of refrigerators, number of freezers, number of TVs, number of STBs and primary service provider) were evaluated with a set of statistical tests to determine whether either method improved the agreement of AMT with reference data, and if so, which method was better. The statistical tests used were: differences in proportions, distributions of proportions (using Pearson’s chi-squared test), and differences in average numbers of devices as functions of all demographic variables. The results indicated that both methods generally improved the agreement between AMT and reference data, sometimes greatly, but that the simultaneous method was usually superior to the sequential method. Some differences in sample populations were found between the AMT and reference data. Differences in the proportion of STBs reflected large changes in the STB market since the time our reference data was acquired in 2009. Differences in the proportions of some primary service providers suggested real sample bias, with the possible explanation that AMT user are more likely to subscribe to providers who also provide home internet service. Differences in other variables, while statistically significant in some cases, were nonetheless considered to be minor. Depending on the intended purpose of the data collected using AMT, these biases may or may not be important; to correct them, additional questions and/or further post-survey adjustments could be employed. In general, based on the analysis methods and the sample datasets used in this study, AMT surveys appeared to provide useful data on appliance and consumer electronics devices.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Performance Analysis Tool for HPC and Big Data Applications on Scientific Clusters

Big data is prevalent in HPC computing. Many HPC projects rely on complex workflows to analyze terabytes or petabytes of data. These workflows often require running over thousands of CPU cores and performing simultaneous data accesses, data movements, and computation. It is challenging to analyze the performance involving terabytes or petabytes of workflow data or measurement data of the executions, from complex workflows over a large number of nodes and multiple parallel task executions. To help identify performance bottlenecks or debug the performance issues in large-scale scientific applications and scientific clusters, we have developed a performance analysis framework, using state-ofthe- art open-source big data processing tools. Our tool can ingest system logs and application performance measurements to extract key performance features, and apply the most sophisticated statistical tools and data mining methods on the performance data. It utilizes an efficient data processing engine to allow users to interactively analyze a large amount of different types of logs and measurements. To illustrate the functionality of the big data analysis framework, we conduct case studies on the workflows from an astronomy project known as the Palomar Transient Factory (PTF) and the job logs from the genome analysis scientific cluster. Our study processed many terabytes of system logs and application performance measurements collected on the HPC systems at NERSC. The implementation of our tool is generic enough to be used for analyzing the performance of other HPC systems and Big Data workows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Bayesian Model Averaging for Ensemble-Based Estimates of Solvation Free Energies

This paper applies the Bayesian Model Averaging (BMA) statistical ensemble technique to estimate small molecule solvation free energies. There is a wide range methods for predicting solvation free energies, ranging from empirical statistical models to {\it ab initio} quantum mechanical approaches. Each of these methods are based on a set of conceptual assumptions that can affect a method's predictive accuracy and transferability. Using an iterative statistical process, we have selected and combined solvation energy estimates using an ensemble of 17 diverse methods from the SAMPL4 blind prediction study to form a single, aggregated solvation energy estimate. The ensemble design process evaluates the statistical information in each individual method as well as the performance of the aggregate estimate obtained from the ensemble as a whole. Methods that possess minimal or redundant information are pruned from the ensemble and the evaluation process repeats until aggregate predictive performance can no longer be improved. We show that this process results in a final aggregate estimate that outperforms all individual methods by reducing estimate errors by as much as 91% to 1.2 kcal/mol accuracy. We also compare our iterative refinement approach to other statistical ensemble approaches and demonstrate that this iterative process reduces estimate errors by as much as 61%. This work provides a new approach for accurate solvation free energy prediction and lays the foundation for future work on aggregate models that can balance computational cost with predictive accuracy.

solvation, Bayesian model averaging, Electrostatic↗
DOE OSTI2019

Solvent Hold Tank Sample Results for MCU-19-2-3-4 (January 2019), MCU-19-83-84-85 (February 2019), MCU-19-208-209-210 (March 2019) and MCU-19-138-139-140 (March special trim): Quarterly Report

A trend summary of three sets of Solvent Hold Tank (SHT) monthly samples (MCU-19-2-3-4, MCU-19-83-84-85, MCU-19-208-209-210); and a set from a special trim (MCU-19-138-139-140) are reported. Most of the conclusions are based on the March SHT sample (MCU-18-208-209-210). Analyses of the March SHT sample (MCU-19-208-209-210) indicated that the Modifier (Cs-7SB) and the Extractant (MaxCalix) concentrations were below their nominal recommended concentrations (169,000 mg/L and 46,900 mg/L, respectively) by 3% and 6%, respectively. The Suppressor (N,N’,N”–tris(3,7-dimethyloctyl)guanidine or TiDG) concentration has increased since the January 2019 measurement to 1141 mg/L, which is above the minimum recommended concentration (479 mg/L). These new concentrations are consistent with the concentrations observed when MCU was fully operational in 2016. The Semi-Volatile Organic Analysis (SVOA) did not detect any impurities. However, the Fourier Transform Hydrogen Nuclear Magnetic Resonance (FT-HNMR) analysis detected presence of phthalates at a few ppm. The impurity concentration was highest in the January sample and consistently detected in the February and March samples (but always registered as a few ppm or less). Another impurity observed in the samples was mercury. Based on the March SHT sample, up to 25 ± 5 micrograms of mercury per mL of solvent was detected (as the average of the Direct Mercury Analysis (DMA) and X-Ray Fluorescence (XRF) methods). The higher mercury concentration in the solvent (as determined in the last three-monthly samples) is possibly due to the higher mercury concentration in Salt Batches 9 and 10. The gamma concentration (~2.55E5 dpm/mL) measured in the March 2019 SHT samples was consistent with previous values observed when MCU was operating continuously (for example, between December 2016 and January 2017). Statistical analysis of the different analytical methods detected a bias (a statistical difference at 5% level) between the FT-HNMR and HPLC methods when measuring the MaxCalix and Modifier concentration; the FT-HNMR gave a higher concentration possibly due to peak overlapping in the measured data. A bias was also detected when measuring total mercury by the DMA method versus the XRF method with the XRF method reported higher mercury concentrations. The laboratory will continue to monitor the quality of the solvent for any new impurities or degradation of the solvent components.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2013

Mechanism-based Representative Volume Elements (RVEs) for Predicting Property Degradations in Multiphase Materials

Quantitative understanding of the evolving thermal-mechanical properties of a multi-phase material hinges upon the availability of quantitative statistically representative microstructure descriptions. Questions then arise as to whether a two-dimensional (2D) or a three-dimensional (3D) representative volume element (RVE) should be considered as the statistically representative microstructure. Although 3D models are more representative than 2D models in general, they are usually computationally expensive and difficult to be reconstructed. In this paper, we evaluate the accuracy of a 2D RVE in predicting the property degradations induced by different degradation mechanisms with the multiphase solid oxide fuel cell (SOFC) anode material as an example. Both 2D and 3D microstructure RVEs of the anodes are adopted to quantify the effects of two different degradation mechanisms: humidity-induced electrochemical degradation and phosphorus poisoning induced structural degradation. The predictions of the 2D model are then compared with the available experimental measurements and the results from the 3D model. It is found that the 2D model, limited by its inability of reproducing the realistic electrical percolation, is unable to accurately predict the degradation of thermo-electrical properties. On the other hand, for the phosphorus poisoning induced structural degradation, both 2D and 3D microstructures yield similar results, indicating that the 2D model is capable of providing computationally efficient yet accurate results for studying the structural degradation within the anodes.

degradation mechanisms↗
DOE OSTI2013

A NEW METHOD OF PULSE-WISE SPECTRAL ANALYSIS OF GAMMA-RAY BURSTS

Time-resolved spectral analysis, though a very promising method to understand the emission mechanism of gamma-ray bursts (GRBs), is difficult to implement in practice because of poor statistics. We present a new method for pulse-wise time-resolved spectral study of the individual pulses of GRBs, using the fact that many spectral parameters are either constants or smooth functions of time. We use this method for the two pulses of GRB 081221, the brightest GRB with separable pulses. We choose, from the literature, a set of possible models that includes the Band model, blackbody with a power law (BBPL), and a collection of blackbodies with a smoothly varying temperature profile, along with a power law (mBBPL), and two blackbodies with a power law (2BBPL). First, we perform a time-resolved study to confirm the spectral parameter variations, and then we construct the new model to perform a joint spectral fit. We find that any photospheric emission in terms of blackbodies is required mainly in the rising parts of the pulses and the falling part can be adequately explained in terms of the Band model, with the low-energy photon index within the regime of synchrotron model. Interestingly, we find that 2BBPL is comparable or sometimes even better, though marginally, than the Band model, in all episodes. Consistent results are also obtained for the brightest GRB of Fermi era-GRB 090618. We point out that the method is generic enough to test any spectral model with well-defined parameter variations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

The nature and energetics of AGN-driven perturbations in the hot gas in the Perseus Cluster

In this paper, cores of relaxed galaxy clusters are often disturbed by AGN. Their Chandra observations revealed a wealth of structures induced by shocks, subsonic gas motions, bubbles of relativistic plasma, etc. In this paper, we determine the nature and energy content of gas fluctuations in the Perseus core by probing statistical properties of emissivity fluctuations imprinted in the soft- and hard-band X-ray images. About 80 per cent of the total variance of perturbations on ~8–70 kpc scales in the core have an isobaric nature, i.e. are consistent with subsonic displacements of the gas in pressure equilibrium with the ambient medium. The observed variance translates to the ratio of energy in perturbations to thermal energy of ~13 per cent. In the region dominated by weak ‘ripples’, about half of the total variance is associated with isobaric perturbations on scales of a few tens of kpc. If these isobaric perturbations are induced by buoyantly rising bubbles, then these results suggest that most of the AGN-injected energy should first go into bubbles rather than into shocks. Using simulations of a shock propagating through the Perseus atmosphere, we found that models reproducing the observed features of a central shock have more than 50 per cent of the AGN-injected energy associated with the bubble enthalpy and only about 20 per cent is carried away with the shock. Such energy partition is consistent with the AGN-feedback model, mediated by bubbles of relativistic plasma, and supports the importance of turbulence in the cooling–heating balance.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Phonons of metallic hydrogen with quantum Monte Carlo

Here, we describe a simple scheme to perform phonon calculations with quantum Monte Carlo (QMC) methods and demonstrate it on metallic hydrogen. Because of the energy and length scales of metallic hydrogen and the statistical noise inherent to QMC methods, the conventional manner of calculating force constants is prohibitively expensive. We show that our alternate approach is nearly 100 times more efficient in resolving the force constants needed to calculate the phonon spectrum in the harmonic approximation. This requires only the calculation of atomic forces, as in the conventional approach, and otherwise little or no programmatic modification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Comparison of two culture methods for the enumeration of Legionella pneumophila from potable water samples

Legionella infections have steadily increased in the United States over the last 20 years, and most of these infections have been attributed to contaminated water. The gold standard for confirmation of Legionella presence in water is culturing with Buffered Charcoal Yeast Extract (BCYE) agar. Following many modifications, this method is still time-consuming, expensive, and can take longer than 10 days for full confirmation. The Legiolert is a newer and simpler culture product that is claimed to be able to quantify Legionella pneumophila in 7 days with high sensitivity and specificity and does not need further confirmation for the presence of L. pneumophila. This study compared the culturability of L. pneumophila occurring in a simulated home plumbing system using both Legiolert and BCYE agar methods. Out of 185 water samples, Legiolert and BCYE method detected L. pneumophila in 83 and 85% of the samples, respectively. The two methods were determined to be statistically equivalent for culturability of L. pneumophila, though the detected levels by Legiolert were slightly higher than the BCYE method. The molecular confirmation of positive (n = 254) and negative wells (n = 82) with Legiolert also showed a high specificity of 96.5% (i.e., 3.5% false positives (9/254) and 0% false negatives (0/82)).

Boczek, Laura A.↗
DOE OSTI2026

Improving statistical precision in Monte Carlo samples with negative weights via reweighting and uncertainty quantification

High statistical precision is critical for Monte Carlo (MC) samples in high energy physics and is degraded by negatively weighted events. This paper investigates a procedure to learn the relationship between the negative and positive weight distributions of any sample, allowing the reduction of statistical uncertainty by reweighting kinematically equivalent events with the same sign. A robust uncertainty quantification method is required for the practical application of such method. Two methods for the estimation of the reweighting uncertainty are developed: one at the event and another one at the final observable level. The latter method is strongly favored. The gains in statistical precision are then quantified. The method is demonstrated on Sherpa vector boson plus jets samples when using all generated events and when restricted to the signal region of a mock analysis. It is demonstrated to significantly reduce stochastic behavior in sparse MC samples while decreasing the overall uncertainty with a sufficiently well-known reweighting function.

Monte Carlo methods↗
DOE OSTI2022

Observational process data analytics using causal inference

Voluminous process data are available with the paradigm shift toward smart manufacturing. However, most historical data are observational, containing noncausal correlations due to confounders and mediators. Estimating causal effects from observational data remains a bottleneck in leveraging them for active applications such as optimization and control. Further, this work aims to introduce a causal modeling framework for analyzing observational process data and extracting quantitative causal information. We demonstrate a real-world application in steel manufacturing where causal inference is used to analyze observational production data and improve the steelmaking process. Additionally, we propose a novel formulation for identifying critical process parameters from observational data, where causal inference is combined with variance-based methods to estimate corresponding risks of interventions to the manufacturing system. The proposed methods are compared with statistical ones to illustrate that causally interpreting statistical correlation leads to problematic results, while the provided workflow generates satisfactory strategies for process improvement.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Comparison of Endovascular and Open Carotid Artery Treatment in Germany: A Retrospective Analysis from 2010 to 2015

Introduction: We analyzed trends in carotid artery stenting (CAS) and carotid endarterectomy (CEA) in hospitalized cases in Germany in the years 2010–2015. Methods: Data from national statistics (DRG statistics) published by the Federal Statistical Office in Germany describing the number of hospitalized patients treated with CEA and CAS were used. In addition, numbers of patients hospitalized with the principal diagnosis stroke associated with precerebral lesions (ICD code I63), transitory cerebral ischemic attacks (G45) and precerebral carotid artery stenosis (I65) treated by CEA and CAS were analyzed for the year 2015. Results: Total number of CEA decreased by 4.0% from 24.067 (2010) to 23.104 (2015) and CAS increased by 5.1% from 5.703 to 5.992. In 2015, 79.4% of all procedures coded concerning the internal carotid artery were CEA and 21.6% CAS. From 27.798 cases hospitalized with the principal diagnosis stroke associated with precerebral lesions, CEA was performed in 3.921 (14.1%) and in 2.132 (7.7%) CAS was documented, with CAS making up one-third of all treatments within the stroke group. In 28.273 cases hospitalized with a TIA, CEA was specified in 853 (3.0%) and CAS in 255 (0.9%) cases. In 27.553 cases with an occlusion and stenosis of precerebral arteries, not resulting in cerebral infarction, 17.036 (61.8%) had a CEA and 3.156 (11.5%) a CAS procedure. Conclusion: CEA is still the primary treatment of extracranial artery stenosis. The impact of CAS becomes mainly apparent in cases presenting with acute strokes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗