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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Measurement of gamma-induced reactions between 10 and 19 MeV on natural zinc with potential application to 67 Cu production

As part of a broader campaign to understand gamma-induced charged particle emission with multiple materials, the cross sections of the (γ, p), and (γ, α) reactions on a natural zinc target were measured. Here, these cross sections were measured experimentally using a kinematically-complete, event-by-event methodology, using monoenergetic gamma ray beams from the High Intensity Gamma Source (HIγS) facility, ranging from 10 to 19 MeV, to bombard a natural metallic zinc target in vacuum. The measured cross sections are compared with theoretical predictions using the statistical model approach, which is important for the use of such models in real-world applications such as the production of the 67 Cu theranostic via the 68 Zn(γ, p) reaction.

Gamma-induced reactions↗
DOE OSTI2021

Kinetic, metabolic, and statistical analytics: addressing metabolic transport limitations among organelles and microbial communities

Microbial organisms engage in a variety of metabolic interactions. A crucial part of these interactions is the exchange of molecules between different organelles, cells, and the environment. The main forces mediating this metabolic exchange are transporters. This transport can be difficult to measure experimentally because several transport mechanisms remain opaque. However, theoretical calculations about the inputs and outputs of cells via metabolic exchanges have enabled the successful inference of the workings of intra-organismal and inter-organismal systems. Kinetic, metabolic, and statistical modeling approaches in combination with omics data are enhancing our knowledge and understanding about metabolic exchange and mass resource allocation. Furthermore, this model-driven analytics approach can guide effective experimental design and yield new insights into biological function and control.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Detecting regular sound changes in linguistics as events of concerted evolution

Background: Concerted evolution is normally used to describe parallel changes at different sites in a genome, but it is also observed in languages where a specific phoneme changes to the same other phoneme in many words in the lexicon—a phenomenon known as regular sound change. We develop a general statistical model that can detect concerted changes in aligned sequence data and apply it to study regular sound changes in the Turkic language family. Results: Linguistic evolution, unlike the genetic substitutional process, is dominated by events of concerted evolutionary change. Our model identified more than 70 historical events of regular sound change that occurred throughout the evolution of the Turkic language family, while simultaneously inferring a dated phylogenetic tree. Including regular sound changes yielded an approximately 4-fold improvement in the characterization of linguistic change over a simpler model of sporadic change, improved phylogenetic inference, and returned more reliable and plausible dates for events on the phylogenies. The historical timings of the concerted changes closely follow a Poisson process model, and the sound transition networks derived from our model mirror linguistic expectations. Conclusions: We demonstrate that a model with no prior knowledge of complex concerted or regular changes can nevertheless infer the historical timings and genealogical placements of events of concerted change from the signals left in contemporary data. Our model can be applied wherever discrete elements—such as genes, words, cultural trends, technologies, or morphological traits—can change in parallel within an organism or other evolving group.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Residual value analysis of plug-in vehicles in the United States

Knowledge about the value of used plug-in electric vehicles (PEVs), known as residual value, is critical for potential PEV purchasers, corporations, and governments who wish to consider the lifetime cost effectiveness of PEVs. In this study, we investigate the residual values of PEVs and compare them with those of other vehicle powertrain technologies using the “true market value” data from Edmunds.com, and considering U.S. federal incentives. We define the adjusted retention rate as the ratio between resale value and the manufacturer’s suggested retail price, subtracting incentives. We develop statistical models to quantify the effects of powertrain technologies on residual value while controlling key factors, including vehicle size, brand, and market segments. We find that the long-range high-performance Tesla Model S holds value significantly better than any other vehicle type evaluated, including internal combustion engine vehicles. Hybrid electric vehicles and plugin hybrid electric vehicles are comparable to one another. They hold slightly less value than internal combustion engine vehicles, but significantly more than short-range (<125 miles) battery electric vehicles. However, short-range battery electric vehicles have a faster improvement in 3-year adjusted retention rate than any other powertrain technology from model year 2013–2014. Finally, the other factor that significantly influences adjusted retention rate is the home country of the vehicle manufacturer (e.g., United States, Japan, or Germany).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

An overview of visualization and visual analytics applications in water resources management

Recent advances in information, communication, and environmental monitoring technologies have increased the availability, spatiotemporal resolution, and quality of water-related data, thereby leading to the emergence of many innovative big data applications. Among these applications, visualization and visual analytics, also known as the visual computing techniques, empower the synergy of computational methods (e.g., machine learning and statistical models) with human reasoning to improve the understanding and solution toward complex science and engineering problems. These approaches are frequently integrated with geographic information systems and cyberinfrastructure to provide new opportunities and methods for enhancing water resources management. Here, we present a comprehensive review of recent hydroinformatics applications that employ visual computing techniques to (1) support complex data-driven research problems, and (2) support the communication and decision-makings in the water resources management sector. Then, we conduct a technical review of the state-of-the-art web-based visualization technologies and libraries to share our experiences on developing shareable, adaptive, and interactive visualizations and visual interfaces for water resources management applications. We close with a vision that applies the emerging visual computing technologies and paradigms to develop the next generation of hydroinformatics applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Indirectly probing the structural change in ion-irradiated Zr-Based metallic glasses from small scale mechanical tests

Ion irradiation was applied to tailor the structural heterogeneities in Zr-based metallic glasses at room temperature. Experimental methods of X-ray diffraction, nanoindentation, and micropillar compression were conducted to examine the irradiation effects on their structural and mechanical property changes. It is found that the irradiated materials retained amorphous structure after room-temperature Ni ion irradiation. The reduction of elastic modulus and hardness measured by nanoindentation indicated the irradiation-induced mechanical degradation. A unified statistic model was employed to quantitatively predict the density and strength of irradiation defects, although their specific structural and physical nature is not explicitly included in this model. The transition of non-intersecting shear bands to multiple intersecting shear bands was observed on compression tests of irradiated micropillars with the increase of irradiation dose. Furthermore, the analysis of the displacement excursion of micropillar compression tests indicated a different deformation mode from the unirradiated state. These results from nanoindentation pop-in and micro-pillar compression tests suggested that irradiation eventually leads to a new state with different types and characteristics of structural heterogeneities from violent displacement cascades and non-equilibrium energy deposition/dissipation processes, which also proves ion irradiation as an effective method to tune the structure and mechanical properties of metallic glasses.

36 MATERIALS SCIENCE↗
DOE OSTI2017

In Vivo Brain Plaque and Tangle Burden Mediates the Association Between Diastolic Blood Pressure and Cognitive Functioning in Nondemented Adults

OBJECTIVE Growing evidence supports an association among increased blood pressure and: (a) poor cognitive performance in older adults, and (b) various biomarkers of increased Alzheimer's disease (AD) neuropathology. The objective of this study was to determine whether systolic blood pressure (SBP) and diastolic blood pressure (DBP) were significantly associated with cognitive functioning in non-demented adults, and to examine in vivo AD pathology as a possible mediator of this association. METHODS Positron emission tomography (PET) scans with 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile (FDDNP) provide in vivo measurements of plaque and tangle burden. A total of 101 non-demented older subjects with blood pressure data and FDDNP-PET scans were drawn from a larger study of predictors of cognitive decline. A neuropsychological test battery was used to compute "global cognitive scores" (averaged across five key domains), which served as an index of general cognitive functioning. RESULTS Higher DBP (but not SBP) was significantly associated with lower cognitive scores, controlling for age, sex, antihypertensive medication use, and ApoE genotype (η2 = 0.06). However, this relationship was no longer significant after introducing FDDNP-PET binding as an additional covariate in the statistical models. In vivo plaque and tangle burden accounted for over 30% of the observed association between higher DBP and poorer cognitive performance. CONCLUSIONS By indicating a mediation of the relationship between DBP and cognitive functioning by FDDNP-PET binding, this study advances our understanding of some potential predictors of cognitive decline in non-demented adults, and underscores the importance of devising early multimodal interventions to more effectively combat degenerative brain disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A probabilistic drought forecasting framework: A combined dynamical and statistical approach

In order to improve drought forecasting skill, this study develops a probabilistic drought forecasting framework comprised of dynamical and statistical modeling components. The novelty of this study is to seek the use of data assimilation to quantify initial condition uncertainty with the Monte Carlo ensemble members, rather than relying entirely on the hydrologic model or land surface model to generate a single deterministic initial condition, as currently implemented in the operational drought forecasting systems. Next, the initial condition uncertainty is quantified through data assimilation and coupled with a newly developed probabilistic drought forecasting model using a copula function. The initial condition at each forecast start date are sampled from the data assimilation ensembles for forecast initialization. Finally, seasonal drought forecasting products are generated with the updated initial conditions. This study introduces the theory behind the proposed drought forecasting system, with an application in Columbia River Basin, Pacific Northwest, United States. Results from both synthetic and real case studies suggest that the proposed drought forecasting system significantly improves the seasonal drought forecasting skills and can facilitate the state drought preparation and declaration, at least three months before the official state drought declaration.

data assimilation↗
DOE OSTI2016

A likelihood ratio anomaly detector for identifying within-perimeter computer network attacks

The rapid detection of attackers within firewalls of enterprise computer networks is of paramount importance. Anomaly detectors address this problem by quantifying deviations from baseline statistical models of normal network behavior and signaling an intrusion when the observed data deviates significantly from the baseline model. But, many anomaly detectors do not take into account plausible attacker behavior. As a result, anomaly detectors are prone to a large number of false positives due to unusual but benign activity. Our paper first introduces a stochastic model of attacker behavior which is motivated by real world attacker traversal. Then, we develop a likelihood ratio detector that compares the probability of observed network behavior under normal conditions against the case when an attacker has possibly compromised a subset of hosts within the network. Since the likelihood ratio detector requires integrating over the time each host becomes compromised, we illustrate how to use Monte Carlo methods to compute the requisite integral. We then present Receiver Operating Characteristic (ROC) curves for various network parameterizations that show for any rate of true positives, the rate of false positives for the likelihood ratio detector is no higher than that of a simple anomaly detector and is often lower. Finally, we demonstrate the superiority of the proposed likelihood ratio detector when the network topologies and parameterizations are extracted from real-world networks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Hydrogen and deuterium permeation in Hastelloy N

Hastelloy N was chosen as the fluoride salt-contacting structural material for the Molten Salt Reactor Experiment due to its excellent compatibility with the fuel salt FLiBe. FLiBe is currently investigated for several advanced fusion and fission reactor concepts where tritium generation in the FLiBe is anticipated. Knowledge of hydrogen transport properties through Hastelloy N is important to understand how tritium would permeate through this material and result in an unintentional release. In this study, the hydrogen and deuterium permeability, diffusivity, and solubility were measured from 500 to 700 °C at a primary-side pressure of 10 kPa in a well-characterized sample of Hastelloy N. The prepared polycrystalline Hastelloy N had C and O impurities present on the surface. These impurities were investigated using Auger Emission Spectroscopy and Ar depth profiling. Here, the adventitious C was removed upon the first Ar sputter cycle whereas O persisted deeper into the sample. For permeation experiments, applied deuterium pressures ranged from 13 Pa to 100 kPa and deuterium transport remained in the diffusion-limited regime (J ∝ P 0.5 ) throughout the pressure range examined. Two methods are employed to measure the effective hydrogen and deuterium diffusivity: rise and decline. The decline method produced improved statistical model fits for calculating the effective diffusion coefficient compared to the rise method. The resultant transport properties compared well to published values for other nickel alloys.

08 HYDROGEN↗
DOE OSTI2015

Effect of Composition on the Voltage Fade Phenomenon in Lithium-, Manganese-Rich xLiMnO 3 •(1-x)LiNi a Mn b Co c O 2 : A Combinatorial Synthesis Approach

The effect of composition on the voltage fade phenomenon was probed using combinatorial synthesis methods. In compositions that have the general formula, (Li 2 MnO 3 ) a (LiNiO 2 ) b (LiMnO 2 ) c (LiCoO 2 ) d , where 0 ≤ a≤0.83, 0.15 ≤ b ≤ 0.42, 0 ≤ c ≤ 0.85, and 0 ≤ d ≤ 0.30 (a + b + c + d = 1), the dependence of features in the x-ray diffraction pattern and of voltage fade on composition were identified and mapped. The observed values of voltage fade indicated that it displayed some sensitivity to composition, but that the sensitivity was not large. The values of voltage fade were found to be amenable to statistical modeling. The model indicated that it may be possible to lower the value of voltage fade below 0.01% by adjusting the composition of the system; however, the composition is not expected to have the layered–layered structure.

combinatorial synthesis↗
DOE OSTI2015

Performance characterization of irregular I/O at the extreme scale

Here, this paper reports our experience with irregular I/O and describes lessons learned when running applications with such I/O on supercomputers at the extreme scale. Specifically, we study how irregularities in I/O patterns (i.e., irregular amount of data written per process at each I/O step) in scientific simulations can cause increasing I/O times and substantial loss in scalability. To this end, we quantify the impact of irregular I/O patterns on the I/O performance of scientific applications at the extreme scale by statistically modeling the irregular I/O behavior of two scientific applications: the Monte Carlo application QMCPack and the adaptive mesh refinement application ENZO. For our testing, we feed our model into I/O kernels of two well-known I/O data models (i.e., ADIOS and HDF) to measure the performance of the two applications’ I/O under different I/O settings. Empirically, we show how the growing data sizes and the irregular I/O patterns in these applications are both relevant factors impacting performance.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Novel ammonia recovery from anaerobic digestion by integrating biogas stripping and gypsum absorption

Recovering ammonia from anaerobic digestion (AD) effluent offers the opportunity to produce a renewablefertilizer and reduce environmental impact. A novel process developed for such an application was evaluatedduring this study. The feature of the process is integrating biogas stripping and gypsum (CaSO 4 •2H 2 O) absorption. The result revealed that the lower CO 2 content and the absorption temperature contributed the higherefficiency of ammonia recovery. The gypsum solution recovered around 95% of the stripped ammonia when thestripping gas contained 10% CO 2 and it rose to 100% when the gas contained more than 30% CO 2 . Furthermore,a statistical model and genetic algorithm were applied to estimate the total ammonia recovery and optimize theoperating parameters. The experimental and modeling results indicated that integrating biogas stripping withgypsum absorption can effectively harvest ammonia nitrogen and reduce CO 2 emissions while producing(NH 4 ) 2 SO 4 fertilizer from AD effluent.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Exploiting OMI NO 2 satellite observations to infer fossil-fuel CO 2 emissions from U.S. megacities

Fossil-fuel CO 2 emissions and their trends in eight U.S. megacities during 2006–2017 are inferred by combining satellite-derived NO X emissions with bottom-up city-specific NO X -to-CO 2 emission ratios. A statistical model is fit to a collection NO 2 plumes observed from the Ozone Monitoring Instrument (OMI), and is used to calculate top-down NO X emissions. Decreases in OMI-derived NO X emissions are observed across the eight cities from 2006 to 2017 (-17% in Miami to -58% in Los Angeles), and are generally consistent with long-term trends of bottom-up inventories (-25% in Miami to -49% in Los Angeles), but there are some interannual discrepancies. City-specific NO X -to-CO 2 emission ratios, used to calculate inferred CO 2 , are estimated through annual bottom-up inventories of NO X and CO 2 emissions disaggregated to 1 × 1 km 2 resolution. Over the study period, NO X -to-CO 2 emission ratios have decreased by ~40% nationwide (-24% to -51% for our studied cities), which is attributed to a faster reduction in NO X when compared to CO 2 due to policy regulations and fuel type shifts. Combining top-down NO X emissions and bottom-up NO X -to-CO 2 emission ratios, annual fossil-fuel CO 2 emissions are derived. Inferred OMI-based top-down CO 2 emissions trends vary between +7% in Dallas to -31% in Phoenix. For 2017, we report annual fossil-fuel CO 2 emissions to be: Los Angeles 113 ± 49 Tg/yr; New York City 144 ± 62 Tg/yr; and Chicago 55 ± 24 Tg/yr. A study in the Los Angeles area, using independent methods, reported a 2013–2016 average CO 2 emissions rate of 104 Tg/yr and 120 Tg/yr, which suggests that the CO 2 emissions from our method are in good agreement with other studies' top-down estimates. Lastly, we anticipate future remote sensing instruments – with better spatial and temporal resolution – will better constrain the NO X -to-CO 2 ratio and reduce the uncertainty in our method.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A flexible class of priors for orthonormal matrices with basis function-specific structure

Statistical modeling of high-dimensional matrix-valued data motivates the use of a low-rank representation that simultaneously summarizes key characteristics of the data and enables dimension reduction. Low-rank representations commonly factor the original data into the product of orthonormal basis functions and weights, where each basis function represents an independent feature of the data. However, the basis functions in these factorizations are typically computed using algorithmic methods that cannot quantify uncertainty or account for basis function correlation structure a priori. While there exist Bayesian methods that allow for a common correlation structure across basis functions, empirical examples motivate the need for basis function-specific dependence structure. We propose a prior distribution for orthonormal matrices that can explicitly model basis function-specific structure. The prior is used within a general probabilistic model for singular value decomposition to conduct posterior inference on the basis functions while accounting for measurement error and fixed effects. We discuss how the prior specification can be used for various scenarios and demonstrate favorable model properties through synthetic data examples. Finally, we apply our method to two-meter air temperature data from the Pacific Northwest, enhancing our understanding of the Earth system’s internal variability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Persistent activation of DNA damage signaling in response to complex mixtures of PAHs in air particulate matter

Complex mixtures of polycyclic aromatic hydrocarbons (PAHs) are present in air particulate matter (PM) and have been associated with many adverse human health effects including cancer and respiratory disease. However, due to their complexity, the risk of exposure to mixtures is difficult to estimate. In the present study the effects of binary mixtures of benzo[a]pyrene (BP) and dibenzo[a,l]pyrene (DBP) and complex mixtures of PAHs in urban air PM extracts on DNA damage signaling was investigated. Applying a statistical model to the data we observed a more than additive response for binary mixtures of BP and DBP on activation of DNA damage signaling. Persistent activation of checkpoint kinase 1 (Chk1) was observed at significantly lower BP equivalent concentrations in air PM extracts than BP alone. Activation of DNA damage signaling was also more persistent in air PM fractions containing PAHs with more than four aromatic rings suggesting larger PAHs contribute a greater risk to human health. Altogether our data suggests that human health risk assessment based on additivity such as toxicity equivalency factor scales may significantly underestimate the risk of exposure to complex mixtures of PAHs. The data confirms our previous findings with PAH-contaminated soil (Niziolek-Kierecka et al., 2012) and suggests a possible role for Chk1 Ser317 phosphorylation as a biological marker for future analyses of complex mixtures of PAHs. -- Highlights: ► Benzo[a]pyrene (BP), dibenzo[a,l]pyrene (DBP) and air PM PAH extracts were compared. ► Binary mixture of BP and DBP induced a more than additive DNA damage response. ► Air PM PAH extracts were more potent than toxicity equivalency factor estimates. ► Larger PAHs (> 4 rings) contribute more to the genotoxicity of PAHs in air PM. ► Chk1 is a sensitive marker for persistent activation of DNA damage signaling from PAH mixtures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Elasto-viscoplastic fast Fourier transform modeling framework for assessing microstructural effects on stress intensity factors characterizing fracture toughness

A large-strain elasto-viscoplastic fast Fourier transform (LS-EVPFFT) model with non-periodic (NP) velocity-based boundary conditions is adapted to simulate the sensitivity of stress intensity factors on microstructure for 304L stainless steel. The material was characterized via electron backscattered diffraction (EBSD) serial-sectioning to obtain a measured 3-D microstructural cell to perform simulations. The NP-LS-EVPFFT model, including the simulation setup and boundary conditions, was verified using a crystal plasticity finite element (CPFE) model. To this end, the generation of meshes of notched specimens was developed, which involved creating Python scripts for mesh “cutting” in Abaqus, and Sculpt scripts in Cubit for meshing of the measured microstructural cell processed with DREAM.3D. The complexity of the mesh preparation highlighted the advantages of the FFT-based model, which circumvents the mesh generation process. Given the efficiency of the FFT-based model, statistical distribution of stress intensity factors in function of crystal orientation at the crack tip, grain structure, and crystallographic texture surrounding the crack tip were predicted. Further, the distributions reveal about 10% variation of stress intensity factors with microstructure with the most significant sensitivity found to be the crystal orientation at the crack tip. The methodology developed in this work is discussed as a practical simulation tool for predicting the sensitivity of stress intensity factors on microstructural variability in metallic materials.

36 MATERIALS SCIENCE↗