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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Occupation Time of a Randomly Accelerated Particle on the Positive Half Axis: Results for the First Five Moments

In the random acceleration process a point particle is accelerated by Gaussian white noise with zero mean. Although several fundamental statistical properties of the motion have been analyzed in detail, the statistics of occupation times is still not well understood. We consider the occupation or residence time T{sub +} on the positive x axis of a particle which is randomly accelerated on the unbounded x axis for a time t. The first two moments of T{sub +} were recently derived by Ouandji Boutcheng et al. (J Stat Mech 053213:1–10, 2016). With an alternate approach utilizing basis functions which have proved useful in other studies of randomly accelerated motion, results for the first five moments are obtained in this paper.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Toroidal regularization of the guiding center Lagrangian

In the Lagrangian theory of guiding center motion, an effective magnetic field B* = B+ (m/e)v ∥ ∇ x b appears prominently in the equations of motion. Because the parallel component of this field can vanish, there is a range of parallel velocities where the Lagrangian guiding center equations of motion are either ill-defined or very badly behaved. Moreover, the velocity dependence of B* greatly complicates the identification of canonical variables and therefore the formulation of symplectic integrators for guiding center dynamics. Here, this letter introduces a simple coordinate transformation that alleviates both these problems simultaneously. In the new coordinates, the Liouville volume element is equal to the toroidal contravariant component of the magnetic field. Consequently, the large-velocity singularity is completely eliminated. Moreover, passing from the new coordinate system to canonical coordinates is extremely simple, even if the magnetic field is devoid of flux surfaces. We demonstrate the utility of this approach in regularizing the guiding center Lagrangian by presenting a new and stable one-step variational integrator for guiding centers moving in arbitrary time-dependent electromagnetic fields.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

From individual leaves to forest stands: importance of niche, distance decay, and stochasticity vary by ecosystem type and functional group for fungal community composition

Abstract Community assembly is influenced by environmental niche processes as well as stochastic processes that can be spatially dependent (e.g. dispersal limitation) or independent (e.g. priority effects). Here, we sampled senesced tree leaves as unit habitats to investigate fungal community assembly at two spatial scales: (i) small neighborhoods of overlapping leaves from differing tree species and (ii) forest stands of differing ecosystem types. Among forest stands, ecosystem type explained the most variation in community composition. Among adjacent leaves within stands, variability in fungal composition was surprisingly high. Leaf type was more important in stands with high soil fertility and dominated by differing tree mycorrhizal types (sugar maple vs. basswood or red oak), whereas distance decay was more important in oak-dominated forest stands with low soil fertility. Abundance of functional groups was explained by environmental factors, but predictors of taxonomic composition within differing functional groups were highly variable. These results suggest that fungal community assembly processes are clearest for functional group abundances and large spatial scales. Understanding fungal community assembly at smaller spatial scales will benefit from further study focusing on differences in drivers for different ecosystems and functional groups, as well as the importance of spatially independent factors such as priority effects.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Scalable and Memory-Efficient Algorithms for Controlling Networked Epidemic Processes Using Multiplicative Weights Update Method

We study the problem of designing scalable algorithms to find effective intervention strategies for controlling stochastic epidemic processes on networks. This is a common problem arising in agent based models for epidemic spread. Previous approaches to this problem focus on either heuristics with no guarantees or approximation algorithms that scale only to networks corresponding to county-sized populations, typically, with less than a million nodes. In particular, the mathematical-programming based approaches need to solve the Linear Program (LP) relaxation of the problem using an LP solver, which restricts the scalability of this approach. In this work, we overcome this restriction by designing an algorithm that adapts the multiplicative weights update (MWU) framework, along with the sample average approximation (SAA) technique, to approximately solve the linear program (LP) relaxation for the problem. To scale this approach further, we provide a memory-efficient algorithm that enables scaling to large networks, corresponding to country-size populations, with over 300 million nodes and 30 billion edges. Furthermore, we show that this approach provides near-optimal solutions to the LP in practice.

Sambaturu, Prathyush↗
DOE OSTI2016

REST-UV ABSORPTION LINES AS METALLICITY ESTIMATOR: THE METAL CONTENT OF STAR-FORMING GALAXIES AT z ∼ 5

We measure a relation between the depth of four prominent rest-UV absorption complexes and metallicity for local galaxies and verify it up to z∼3. We then apply this relation to a sample of 224 galaxies at 3.5 9 is characterized by 0.3–0.4 dex (in units of 12+log(O/H)) lower metallicities than at z ∼ 2, but comparable to z∼3.5. We find galaxies with weak or no Lyα emission to have metallicities comparable to z ∼ 2 galaxies and therefore may represent an evolved subpopulation of z∼5 galaxies. We find a correlation between metallicity and dust in good agreement with local galaxies and an inverse trend between metallicity and star-formation rate consistent with observations at z ∼ 2. The relation between stellar mass and metallicity (MZ relation) is similar to z∼3.5, but there are indications of it being slightly shallower, in particular for the young, Lyα-emitting galaxies. We show that, within a “bathtub” approach, a shallower MZ relation is expected in the case of a fast (exponential) build-up of stellar mass with an e-folding time of 100–200 Myr. Because of this fast evolution, the process of dust production and metal enrichment as a function of mass could be more stochastic in the first billion years of galaxy formation compared to later times.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Studying the effect of meteorological factors on the SO2 and PM10 pollution levels with refined versions of the SARIMA model

Numerous time series methods are used in environmental sciences allowing the detailed investigation of air pollution processes. The goal of this study is to present the empirical analysis of various aspects of stochastic modeling and in particular the ARIMA/SARIMA methods. The subject of investigation is air pollution in the town of Kardzhali, Bulgaria with 2 problematic pollutants – sulfur dioxide (SO2) and particulate matter (PM10). Various SARIMA Transfer Function models are built taking into account meteorological factors, data transformations and the use of different horizons selected to predict future levels of concentrations of the pollutants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

The relationship between anatomic noise and volumetric breast density for digital mammography

Purpose: The appearance of parenchymal/stromal patterns in mammography have been characterized as having a Wiener power spectrum with an inverse power-law shape described by the exponential parameter, {beta}. The amount of fibroglandular tissue, which can be quantified in terms of volumetric breast density (VBD), influences the texture and appearance of the patterns formed in a mammogram. Here, a large study is performed to investigate the variations in {beta} in a clinical population and to indicate the relationship between {beta} and breast density. Methods: From a set of 2686 cranio-caudal normal screening mammograms, the parameter {beta} was extracted from log-log fits to the Wiener spectrum over the range 0.15-1 mm{sup -1}. The Wiener spectrum was calculated from regions of interest in the compression paddle contact region of the breast. An in-house computer program, Cumulus V, was used to extract the volumetric breast density and identify the compression paddle contact regions of the breast. The Wiener spectra were calculated with and without modulation transfer function (MTF) correction to determine the impact of VBD on the intrinsic anatomic noise. Results: The mean volumetric breast density was 25.5% ({+-}12.6%) over all images. The mean {beta} following a MTF correction which decreased the {beta} slightly ( Almost-Equal-To -0.08) was found to be 2.87. Varying the maximum of the spatial frequency range of the fits from 0.7 to 1.0, 1.25 or 1.5 mm{sup -1} showing small decreases in the result, although the effect of the quantum noise power component on reducing {beta} was clearly observed at 1.5 mm{sup -1}. Conclusions: The texture parameter, {beta}, was found to increase with VBD at low volumetric breast densities with an apparent leveling off at higher densities. The relationship between {beta} and VBD measured here can be used to create probabilistic models for computer simulations of detectability. As breast density is a known risk predictor for breast cancer, the correlation between {beta} and VBD suggests that {beta} may provide predictive information and this will be investigated in the future.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

Toward in vivo lung's tissue incompressibility characterization for tumor motion modeling in radiation therapy

Purpose: A novel technique is proposed to characterize lung tissue incompressibility variation during respiration. Estimating lung tissue incompressibility parameter variations resulting from air content variation throughout respiration is critical for computer assisted tumor motion tracking. Continuous tumor motion is a major challenge in lung cancer radiotherapy, especially with external beam radiotherapy. If not accounted for, this motion may lead to areas of radiation overdosage for normal tissue. Given the unavailability of imaging modality that can be used effectively for real-time lung tumor tracking, computer assisted approach based on tissue deformation estimation can be a good alternative. This approach involves lung biomechanical model where its fidelity depends on input tissue properties. This investigation shows that considering variable tissue incompressibility parameter is very important for predicting tumor motion accurately, hence improving the lung radiotherapy outcome. Methods: First, an in silico lung phantom study was conducted to demonstrate the importance of employing variable Poisson's ratio for tumor motion predication. After it was established that modeling this variability is critical for accurate tumor motion prediction, an optimization based technique was developed to estimate lung tissue Poisson's ratio as a function of respiration cycle time. In this technique, the Poisson's ratio and lung pressure value were varied systematically until optimal values were obtained, leading to maximum similarity between acquired and simulated 4D CT lung images. This technique was applied in an ex vivo porcine lung study where simulated images were constructed using the end exhale CT image and deformation fields obtained from the lung's FE modeling of each respiration time increment. To model the tissue, linear elastic and Marlow hyperelastic material models in conjunction with variable Poisson's ratio were used. Results: The phantom study showed that the tumor motion trajectory and its final locations obtained from simulations with and without considering tissue incompressibility variation were very different. For example, tumor displacements in the z direction were -11.23 and -38.10 mm obtained with the Marlow hyperelastic material model in conjunction with constant and variable Poisson's ratio, respectively. By comparing the acquired 4D-CT image sequence of the porcine lung with their image sequence counterparts obtained from the hyperelastic model with constant and variable Poisson's ratio, it was shown that using variable tissue incompressibility reduced errors significantly in tumor motion prediction. Conclusions: This investigation demonstrates the importance of incompressibility variation estimation and utilization for accurate tumor tracking in computer assisted lung external beam radiation therapy. An optimization framework was developed to estimate a Poisson's ratio function in terms of respiration cycle time using experimental image data of the lung. Utilizing this function along with respiratory system FE modeling may lead to more effective tumor targeting, hence potentially improving the outcome of lung external beam radiation therapy techniques. This is particularly true for stereotactic body radiation therapy where only one or a few fraction treatments are applied, precluding the possibility of averaging out dosimetric deviations introduced by the respiratory motion.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Laboratory Strategies for Hydrate Formation in Fine‐Grained Sediments

Abstract Fine‐grained sediments limit hydrate nucleation, shift the phase boundary, and hinder gas supply. Laboratory experiments in this study explore different strategies to overcome these challenges, including the use of a more soluble guest molecule rather than methane, grain‐scale gas‐storage within porous diatoms, ice‐to‐hydrate transformation to grow lenses at predefined locations, forced gas injection into water saturated sediments, and long‐term guest molecule transport. Tomographic images and thermal and pressure data provide rich information on hydrate formation and morphology. Results show that hydrate formation is inherently displacive in fine‐grained sediments; lenses are thicker and closer to each other in compressible, high specific surface area sediments subjected to low effective stress. Temperature and pressure trajectories follow a shifted phase boundary that is consistent with capillary effects. Exo‐pore growth results in freshly formed hydrate with a striped and porous structure; this open structure becomes an effective pathway for gas transport to the growing hydrate front. Ice‐to‐hydrate transformation goes through a liquid stage at premelt temperatures; then, capillarity and cryogenic suction compete, and some water becomes imbibed into the sediment faster than hydrate reformation. The geometry of hydrate lenses and the internal hydrate structure continue evolving long after the exothermal response to hydrate formation has completely decayed. Multiple time‐dependent processes occur during hydrate formation, including gas, water and heat transport, sediment compressibility, reaction rate, and the stochastic nucleation process. Hydrate formation strategies conceived for this study highlight the inherent difficulties in emulating hydrate formation in fine‐grained sediments within the relatively short time scale available for laboratory experiments.

Lei, L.↗
DOE OSTI2013

Acquisition of material properties in production for sheet metal forming processes

In past work a measurement system for the in-line acquisition of material properties was developed at IVP. This system is based on the non-destructive eddy-current principle. Using this system, a 100% control of material properties of the processed material is possible. The system can be used for ferromagnetic materials like standard steels as well as paramagnetic materials like Aluminum and stainless steel. Used as an in-line measurement system, it can be configured as a stand-alone system to control material properties and sort out inapplicable material or as part of a control system of the forming process. In both cases, the acquired data can be used as input data for numerical simulations, e.g. stochastic simulations based on real world data.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Accurate numerical simulations of open quantum systems using spectral tensor trains

Decoherence between qubits is a major bottleneck in quantum computations. Decoherence results from intrinsic quantum and thermal fluctuations as well as noise in the external fields that perform the measurement and preparation processes. With prescribed colored noise spectra for intrinsic and extrinsic noise, we present a numerical method, Quantum Accelerated Stochastic Propagator Evaluation (Q-ASPEN), to solve the time-dependent noise-averaged reduced density matrix in the presence of intrinsic and extrinsic noise. Q-ASPEN is arbitrarily accurate and can be applied to provide estimates for the resources needed to error-correct quantum computations. We employ spectral tensor trains, which combine the advantages of tensor networks and pseudospectral methods, as a variational ansatz to the quantum relaxation problem and optimize the ansatz using methods typically used to train neural networks. Here, the spectral tensor trains in Q-ASPEN make accurate calculations with tens of quantum levels feasible. We present benchmarks for Q-ASPEN on the spin-boson model in the presence of intrinsic noise and on a quantum chain of up to 32 sites in the presence of extrinsic noise. In our benchmark, the memory cost of Q-ASPEN scales as a low-order polynomial in the size of the system once the number of system states surpasses the number of basis functions used in the spectral expansion.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Deep learning categorization of infrasound array data

Here we develop a deep learning-based infrasonic detection and categorization methodology that uses convolutional neural networks with self-attention layers to identify stationary and non-stationary signals in infrasound array processing results. Using features extracted from the coherence and direction-of-arrival information from beamforming at different infrasound arrays, our model more reliably detects signals compared with raw waveform data. Using three infrasound stations maintained as part of the International Monitoring System, we construct an analyst-reviewed data set for model training and evaluation. We construct models using a 4-category framework, a generalized noise vs non-noise detection scheme, and a signal-of-interest (SOI) categorization framework that merges short duration stationary and non-stationary categories into a single SOI category. We evaluate these models using a combination of k-fold cross-validation, comparison with an existing “state-of-the-art” detector, and a transportability analysis. Although results are mixed in distinguishing stationary and non-stationary short duration signals, f-scores for the noise vs non-noise and SOI analyses are consistently above 0.96, implying that deep learning-based infrasonic categorization is a highly accurate means of identifying signals-of-interest in infrasonic data records.

47 OTHER INSTRUMENTATION↗
NASA NTRS1972

Earth-based navigation capabilities for outer planet missions.

The role of new Earth-based radio metric data types and of advanced estimation algorithms in navigating an outer planet spacecraft in the vicinity of Saturn has been analyzed. The data types included in the study consist of conventional range and range-rate measurements taken from a single station and simultaneous and nearly simultaneous measurements obtained from pairs of stations during overlapping viewing periods. The utility of a third data set that is produced by explicitly differencing the simultaneous points has also been investigated. The data was processed with a conventional least squares batch filter and with a sequential filter that estimated parameters describing small stochastic accelerations (process noise) acting on the spacecraft. It was found that process noise can produce large errors in the estimates obtained from batch filtering conventional and simultaneous data, and that the only batch filtered estimates that were reliable were those obtained from differenced data. The performance of the simultaneous data in the presence of process noise is greatly improved by sequential filtering.

Hildebrand, C. E.↗
NASA NTRS1972

Receiver processing for direct-detection optical communication systems.

A model that is sufficiently general to describe the predominant statistical characteristics of the output of many real optical detectors is formulated. This model is used to study the optimum receiver processing for direct-detection optical communication systems. In particular, the structures of detectors and estimators for filtered doubly stochastic Poisson processes (DSPP) observed in additive white Gaussian noise are considered. Representations for the posterior statistics of a vector Markov process that modulates the intensity of the DSPP are obtained.

Hoversten, E. V.↗
DOE OSTI2014

ENSO regimes and the late 1970's climate shift: The role of synoptic weather and South Pacific ocean spiciness

South Pacific subtropical density compensated temperature and salinity (spiciness) anomalies are known to be associated with decadal equatorial variability, however, the mechanisms by which such disturbances are generated, advect and the degree to which they modulate the equatorial thermocline remains controversial. During the late 1970's a climate regime transition preceded a period of strong and sustained El Nino events. Using an ocean general circulation model forced by the constituent mechanical and thermodynamic components of the reanalysed atmosphere we show that the late 1970's transition coincided with the arrival of a large-scale, subsurface cold and fresh water anomaly in the central tropical Pacific. An ocean reanalysis for the period 1990–2007 that assimilates subsurface Argo, XBT and CTD data, reveals that disturbances occur due to the subduction of negative surface salinity anomalies from near 30° S, 100° W which are advected along the σ=25–26 kgm{sup −3} isopycnal surfaces. These anomalies take, on average, seven years to reach the central equatorial Pacific where they may substantially perturb the thermocline before the remnants ultimately ventilate in the region of the western Pacific warm pool. Positive (warm–salty) disturbances, known to occur due to late winter diapycnal mixing and isopycnal outcropping, arise due to both subduction of subtropical mode waters and subsurface injection. On reaching the equatorial band (10° S–0° S) these disturbances tend to deepen the thermocline reducing the model's ENSO. In contrast the emergence of negative (cold–fresh) disturbances at the equator are associated with a shoaling of the thermocline and El Nino events. Process studies are used to show that the generation and advection of anomalous density compensated thermocline disturbances critically depend on stochastic forcing of the intrinsic ocean by weather. We further show that in the absence of the inter-annual component of the atmosphere forcing Central Pacific El Nino events are manifest.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

TU-AB-303-01: A Feasibility Study for Dynamic Adaptive Therapy of Non-Small Cell Lung Cancer

Purpose: To compare plans for NSCLC optimized using Dynamic Adaptive Therapy (DAT) with conventional IMRT optimization. DAT adapts plans based on changes in the target volume by using dynamic programing techniques to consider expected changes into the optimization process. Information gathered during treatment, e.g. from CBCT, is incorporated into the optimization. Methods and materials: DAT is formulated using stochastic control formalism, which minimizes the total expected number of tumor cells at the end of a treatment course subject to uncertainty inherent in the tumor response and organs-at-risk (OAR) dose constraints. This formulation allows for non-stationary dose distribution as well as non-stationary fractional dose as needed to achieve a series of optimal plans that are conformal to tumor over time. Sixteen phantom cases with various sizes and locations of tumors, and OAR geometries were generated. Each case was planned with DAT and conventional IMRT (60Gy/30fx). Tumor volume change over time was obtained by using, daily MVCT-based, two-level cell population model. Monte Carlo simulations have been performed for each treatment course to account for uncertainty in tumor response. Same OAR dose constraints were applied for both methods. The frequency of plan modification was varied to 1, 2, 5 (weekly), and 29 (daily). The final average tumor dose and OAR doses have been compared to quantify the potential benefit of DAT. Results: The average tumor max, min, mean, and D95 resulted from DAT were 124.0–125.2%, 102.1–114.7%, 113.7–123.4%, and 102.0–115.9% (range dependent on the frequency of plan modification) of those from conventional IMRT. Cord max, esophagus max, lung mean, heart mean, and unspecified tissue D05 resulted from AT were 84–102.4%, 99.8–106.9%, 66.9–85.6%, 58.2–78.8%, and 85.2–94.0% of those from conventional IMRT. Conclusions: Significant tumor dose increase and OAR dose reduction, especially with parallel OAR with mean or dose-volume constraints, can be achieved using DAT.

60 APPLIED LIFE SCIENCES↗