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NASA NTRS2011

Effect of Inductive Coil Geometry and Current Sheet Trajectory of a Conical Theta Pinch Pulsed Inductive Plasma Accelerator

Results are presented demonstrating the e ect of inductive coil geometry and current sheet trajectory on the exhaust velocity of propellant in conical theta pinch pulsed induc- tive plasma accelerators. The electromagnetic coupling between the inductive coil of the accelerator and a plasma current sheet is simulated, substituting a conical copper frustum for the plasma. The variation of system inductance as a function of plasma position is obtained by displacing the simulated current sheet from the coil while measuring the total inductance of the coil. Four coils of differing geometries were employed, and the total inductance of each coil was measured as a function of the axial displacement of two sep- arate copper frusta both having the same cone angle and length as the coil but with one compressed to a smaller size relative to the coil. The measured relationship between total coil inductance and current sheet position closes a dynamical circuit model that is used to calculate the resulting current sheet velocity for various coil and current sheet con gura- tions. The results of this model, which neglects the pinching contribution to thrust, radial propellant con nement, and plume divergence, indicate that in a conical theta pinch ge- ometry current sheet pinching is detrimental to thruster performance, reducing the kinetic energy of the exhausting propellant by up to 50% (at the upper bound for the parameter range of the study). The decrease in exhaust velocity was larger for coils and simulated current sheets of smaller half cone angles. An upper bound for the pinching contribution to thrust is estimated for typical operating parameters. Measurements of coil inductance for three di erent current sheet pinching conditions are used to estimate the magnetic pressure as a function of current sheet radial compression. The gas-dynamic contribution to axial acceleration is also estimated and shown to not compensate for the decrease in axial electromagnetic acceleration that accompanies the radial compression of the plasma in conical theta pinches.

Hallock, Ashley K.↗

DOE OSTI2017

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data

New technologies, such as connected and automated vehicles, have attracted more and more researchers for improving the energy efficiency and environmental impact of current transportation systems. The green routing strategy instructs a vehicle to select the most fuel-efficient route before the vehicle departs. It benefits the current transportation system with fuel saving opportunity through identifying the greenest route. This paper introduces an evaluation framework for estimating benefits of green routing based on large-scale, real-world travel data. The framework has the capability to quantify fuel savings by estimating the fuel consumption of actual routes and comparing to routes procured by navigation systems. A route-based fuel consumption estimation model, considering road traffic conditions, functional class, and road grade is proposed and used in the framework. An experiment using a large-scale data set from the California Household Travel Survey global positioning system trajectory data base indicates that 31% of actual routes have fuel savings potential with a cumulative estimated fuel savings of 12%.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2015

PanFP: Pangenome-based functional profiles for microbial communities

For decades there has been increasing interest in understanding the relationships between microbial communities and ecosystem functions. Current DNA sequencing technologies allows for the exploration of microbial communities in two principle ways: targeted rRNA gene surveys and shotgun metagenomics. For large study designs, it is often still prohibitively expensive to sequence metagenomes at both the breadth and depth necessary to statistically capture the true functional diversity of a community. Although rRNA gene surveys provide no direct evidence of function, they do provide a reasonable estimation of microbial diversity, while being a very cost effective way to screen samples of interest for later shotgun metagenomic analyses. However, there is a great deal of 16S rRNA gene survey data currently available from diverse environments, and thus a need for tools to infer functional composition of environmental samples based on 16S rRNA gene survey data. As a result, we present a computational method called pangenome based functional profiles (PanFP), which infers functional profiles of microbial communities from 16S rRNA gene survey data for Bacteria and Archaea. PanFP is based on pangenome reconstruction of a 16S rRNA gene operational taxonomic unit (OTU) from known genes and genomes pooled from the OTU s taxonomic lineage. From this lineage, we derive an OTU functional profile by weighting a pangenome s functional profile with the OTUs abundance observed in a given sample. We validated our method by comparing PanFP to the functional profiles obtained from the direct shotgun metagenomic measurement of 65 diverse communities via Spearman correlation coefficients. These correlations improved with increasing sequencing depth, within the range of 0.8 0.9 for the most deeply sequenced Human Microbiome Project mock community samples. PanFP is very similar in performance to another recently released tool, PICRUSt, for almost all of survey data analysed here. But, our method is unique in that any OTU building method can be used, as opposed to being limited to closed reference OTU picking strategies against specific reference sequence databases. In conclusion, we developed an automated computational method, which derives an inferred functional profile based on the 16S rRNA gene surveys of microbial communities. The inferred functional profile provides a cost effective way to study complex ecosystems through predicted comparative functional metagenomes and metadata analysis. All PanFP source code and additional documentation are freely available online at GitHub.

16S rRNA survey↗

DOE OSTI2017

Green Routing Fuel Saving Opportunity Assessment: A Case Study on California Large-Scale Real-World Travel Data: Preprint

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1995

Adaptive noise reduction circuit for a sound reproduction system

A noise reduction circuit for a hearing aid having an adaptive filter for producing a signal which estimates the noise components present in an input signal. The circuit includes a second filter for receiving the noise-estimating signal and modifying it as a function of a user's preference or as a function of an expected noise environment. The circuit also includes a gain control for adjusting the magnitude of the modified noise-estimating signal, thereby allowing for the adjustment of the magnitude of the circuit response. The circuit also includes a signal combiner for combining the input signal with the adjusted noise-estimating signal to produce a noise reduced output signal.

Engebretson, A. Maynard↗

NASA NTRS1973

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

Carter, M. C.↗

NASA NTRS1978

Estimation of longitudinal aircraft characteristics using parameter identification techniques

This study compares the results from different parameter identification methods used to determine longitudinal aircraft characteristics from flight data. In general, these comparisons have found that the estimated short-period dynamics (natural frequency, damping, transfer functions) are only weakly affected by the type of identification method, however, the estimated aerodynamic coefficients may be strongly affected by the type of identification method. The estimated values for aerodynamic coefficients were found to depend upon the type of math model and type of test data used with each of the identification methods. The use of fairly complete math models and the use of long data lengths, combining both steady and nonsteady motion, are shown to provide aerodynamic coefficient values that compare favorably with the results from other testing methods such as steady-state flight and full-scale wind-tunnel experiments.

Wingrove, R. C.↗

DOE OSTI2014

The cosmic evolution of Fermi BL Lacertae objects

Fermi has provided the largest sample of γ-ray-selected blazars to date. In this work we use a uniformly selected set of 211 BL Lacertae (BL Lac) objects detected by Fermi during its first year of operation. We obtained redshift constraints for 206 out of the 211 BL Lac objects in our sample, making it the largest and most complete sample of BL Lac objects available in the literature. We use this sample to determine the luminosity function of BL Lac objects and its evolution with cosmic time. We find that for most BL Lac classes the evolution is positive, with a space density peaking at modest redshift (z ≈ 1.2). Low-luminosity, high-synchrotron-peaked (HSP) BL Lac objects are an exception, showing strong negative evolution, with number density increasing for z ≲ 0.5. Since this rise corresponds to a drop-off in the density of flat-spectrum radio quasars (FSRQs), a possible interpretation is that these HSPs represent an accretion-starved end state of an earlier merger-driven gas-rich phase. We additionally find that the known BL Lac correlation between luminosity and photon spectral index persists after correction for the substantial observational selection effects with implications for the so-called 'blazar sequence'. Finally, by estimating the beaming corrections to the luminosity function, we find that BL Lac objects have an average Lorentz factor of γ=6.1{sub −0.8}{sup +1.1}, and that most are seen within 10° of the jet axis.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1996

Development of a real-time transport performance optimization methodology

The practical application of real-time performance optimization is addressed (using a wide-body transport simulation) based on real-time measurements and calculation of incremental drag from forced response maneuvers. Various controller combinations can be envisioned although this study used symmetric outboard aileron and stabilizer. The approach is based on navigation instrumentation and other measurements found on state-of-the-art transports. This information is used to calculate winds and angle of attack. Thrust is estimated from a representative engine model as a function of measured variables. The lift and drag equations are then used to calculate lift and drag coefficients. An expression for drag coefficient, which is a function of parasite drag, induced drag, and aileron drag, is solved from forced excitation response data. Estimates of the parasite drag, curvature of the aileron drag variation, and minimum drag aileron position are produced. Minimum drag is then obtained by repositioning the symmetric aileron. Simulation results are also presented which evaluate the affects of measurement bias and resolution.

Gilyard, Glenn↗

DOE OSTI2016

Planck 2015 results: XVII. Constraints on primordial non-Gaussianity

We report that the Planck full mission cosmic microwave background (CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity (NG). Using three classes of optimal bispectrum estimators – separable template-fitting (KSW), binned, and modal – we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result from temperature alone ƒ local NL = 2.5 ± 5.7, ƒ equil NL = -16 ± 70, , and ƒ ortho NL = -34 ± 32 (68% CL, statistical). Combining temperature and polarization data we obtain ƒ local NL = 0.8 ± 5.0, ƒ equil NL = -4 ± 43, and ƒ ortho NL = -26 ± 21 (68% CL, statistical). The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are consistent with estimators based on measuring the Minkowski functionals of the CMB. The effect of time-domain de-glitching systematics on the bispectrum is negligible. In spite of these test outcomes we conservatively label the results including polarization data as preliminary, owing to a known mismatch of the noise model in simulations and the data. Beyond estimates of individual shape amplitudes, we present model-independent, three-dimensional reconstructions of the Planck CMB bispectrum and derive constraints on early universe scenarios that generate primordial NG, including general single-field models of inflation, axion inflation, initial state modifications, models producing parity-violating tensor bispectra, and directionally dependent vector models. We present a wide survey of scale-dependent feature and resonance models, accounting for the “look elsewhere” effect in estimating the statistical significance of features. We also look for isocurvature NG, and find no signal, but we obtain constraints that improve significantly with the inclusion of polarization. The primordial trispectrum amplitude in the local model is constrained to be g local NL = (-0.9 ± 7.7 ) X 10 4 (68% CL statistical), and we perform an analysis of trispectrum shapes beyond the local case. The global picture that emerges is one of consistency with the premises of the ΛCDM cosmology, namely that the structure we observe today was sourced by adiabatic, passive, Gaussian, and primordial seed perturbations.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

FRONTIER FIELDS: HIGH-REDSHIFT PREDICTIONS AND EARLY RESULTS

The Frontier Fields program is obtaining deep Hubble and Spitzer Space Telescope images of new ''blank'' fields and nearby fields gravitationally lensed by massive galaxy clusters. The Hubble images of the lensed fields are revealing nJy sources (AB mag > 31), the faintest galaxies yet observed. The full program will transform our understanding of galaxy evolution in the first 600 million years (z > 9). Previous programs have yielded a dozen or so z > 9 candidates, including perhaps fewer than expected in the Ultra Deep Field and more than expected in shallower Hubble images. In this paper, we present high-redshift (z > 6) number count predictions for the Frontier Fields and candidates in three of the first Hubble images. We show the full Frontier Fields program may yield up to ∼70 z > 9 candidates (∼6 per field). We base this estimate on an extrapolation of luminosity functions observed between 4 < z < 8 and gravitational lensing models submitted by the community. However, in the first two deep infrared Hubble images obtained to date, we find z ∼ 8 candidates but no strong candidates at z > 9. We defer quantitative analysis of the z > 9 deficit (including detection completeness estimates) to future work including additional data. At these redshifts, cosmic variance (field-to-field variation) is expected to be significant (greater than ±50%) and include clustering of early galaxies formed in overdensities. The full Frontier Fields program will significantly mitigate this uncertainty by observing six independent sightlines each with a lensing cluster and nearby blank field.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1988

A method for modeling bias in a person's estimates of likelihoods of events

It is of practical importance in decision situations involving risk to train individuals to transform uncertainties into subjective probability estimates that are both accurate and unbiased. We have found that in decision situations involving risk, people often introduce subjective bias in their estimation of the likelihoods of events depending on whether the possible outcomes are perceived as being good or bad. Until now, however, the successful measurement of individual differences in the magnitude of such biases has not been attempted. In this paper we illustrate a modification of a procedure originally outlined by Davidson, Suppes, and Siegel (3) to allow for a quantitatively-based methodology for simultaneously estimating an individual's subjective utility and subjective probability functions. The procedure is now an interactive computer-based algorithm, DSS, that allows for the measurement of biases in probability estimation by obtaining independent measures of two subjective probability functions (S+ and S-) for winning (i.e., good outcomes) and for losing (i.e., bad outcomes) respectively for each individual, and for different experimental conditions within individuals. The algorithm and some recent empirical data are described.

Nygren, Thomas E.↗

DOE OSTI2024

Neural Networks to Find the Optimal Forcing for Offsetting the Anthropogenic Climate Change Effects

Abstract Of great relevance to climate engineering is the systematic relationship between the radiative forcing to the climate system and the response of the system, a relationship often represented by the linear response function (LRF) of the system. However, estimating the LRF often becomes an ill-posed inverse problem due to high-dimensionality and nonunique relationships between the forcing and response. Recent advances in machine learning make it possible to address the ill-posed inverse problem through regularization and sparse system fitting. Here, we develop a convolutional neural network (CNN) for regularized inversion. The CNN is trained using the surface temperature responses from a set of Green’s function perturbation experiments as imagery input data together with data sample densification. The resulting CNN model can infer the forcing pattern responsible for the temperature response from out-of-sample forcing scenarios. This promising proof of concept suggests a possible strategy for estimating the optimal forcing to negate certain undesirable effects of climate change. The limited success of this effort underscores the challenges of solving an inverse problem for a climate system with inherent nonlinearity. Significance Statement Predicting the climate response for a given climate forcing is a direct problem, while inferring the forcing for a given desired climate response is often an inverse, ill-posed, problem, posing a new challenge to the climate community. This study makes the first attempt to infer the radiative forcing for a given target pattern of global surface temperature response using a deep learning approach. The resulting deeply trained convolutional neural network inversion model shows promise in capturing the forcing pattern corresponding to a given surface temperature response, with a significant implication on the design of an optimal solar radiation management strategy for curbing global warming. This study also highlights the technical challenges that future research should prioritize in seeking feasible solutions to the inverse climate problem.

Ren, Huiying↗

DOE OSTI2015

Convergence of statistical moments of particle density time series in scrape-off layer plasmas

Particle density fluctuations in the scrape-off layer of magnetically confined plasmas, as measured by gas-puff imaging or Langmuir probes, are modeled as the realization of a stochastic process in which a superposition of pulses with a fixed shape, an exponential distribution of waiting times, and amplitudes represents the radial motion of blob-like structures. With an analytic formulation of the process at hand, we derive expressions for the mean squared error on estimators of sample mean and sample variance as a function of sample length, sampling frequency, and the parameters of the stochastic process. Employing that the probability distribution function of a particularly relevant stochastic process is given by the gamma distribution, we derive estimators for sample skewness and kurtosis and expressions for the mean squared error on these estimators. Numerically, generated synthetic time series are used to verify the proposed estimators, the sample length dependency of their mean squared errors, and their performance. We find that estimators for sample skewness and kurtosis based on the gamma distribution are more precise and more accurate than common estimators based on the method of moments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2026

Optimization performance, fidelity, and cost: SIAM VQE

This dataset contains files storing results from classically-simulated quantum subroutines within a dynamical mean-field theory workflow, and jupyter notebooks processing the data in these files to generate plots. The files store: (1) Results from variational quantum eigensolver (VQE) simulations searching for optimal parameters allowing parametrized quantum circuits to prepare approximations to ground states of different Anderson impurity models (AIMs) (2) Results from simulations of a quantum Lanczos algorithm (QLA) estimating the Lanczos coefficients defining the continued-fraction representation of an (AIM) Green’s function Description: Any file named vqe_gs_results* stores approximations to the ground state and energy of a given AIM estimated using three different methods: (1) Numerical diagonalization (2) Ideal VQE simulation (3) VQE simulation with sampling noise For each VQE simulations metadata about the optimization (optimization results plus number of quantum circuits that would have been executed on real hardware) is also stored. Any file named qla_dos_results* estimations for the Lanczos coefficients defining the Green’s function of an AIM. The stored estimations are achieved using different methods: (1) Numerical Lanczos algorithm from initial states obtained from numerical diagonalization (2) Simulated quantum Lanczos algorithm from initial states prepared from parametrized quantum circuits yielded by corresponding ideal and noisy VQE subroutines. The dataset is used and described in M. Karabin et al., "Quantum solver for single-impurity Anderson models with particle-hole symmetry", Phys. Rev. Research 8, 033066 (2026). DOI: https://doi.org/10.1103/7ys3-tl4l

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2014

Plasma polychlorinated biphenyl concentrations and immune function in postmenopausal women

Background: Polychlorinated biphenyl (PCB) exposure has been associated with non-Hodgkin lymphoma in several studies, and the immune system is a potential mediator. Objectives: We analyzed associations of plasma PCBs with immune function measures. We hypothesized that higher plasma PCB concentrations are associated with lower immune function cross-sectionally, and that increases in PCB concentrations over a one year period are associated with decreases in immune function. Methods: Plasma PCB concentrations and immune function [natural killer (NK) cell cytotoxicity and PHA-induced T-lymphocyte proliferation (PHA-TLP)] were measured at baseline and one year in 109 postmenopausal overweight women participating in an exercise intervention study in the Seattle, Washington (USA) area. Mixed models, with adjustment for body mass index and other potential confounders, were used to estimate associations of PCBs with immune function cross-sectionally and longitudinally. Results: Associations of PCBs with immune function measures differed across groups of PCBs (e.g., medium- and high-chlorinated and dioxin-like [mono-ortho-substituted]) and by the time frame for the comparison (cross-sectional vs. longitudinal). Higher concentrations of medium- and high-chlorinated PCBs were associated with higher PHA-TLP cross-sectionally but not longitudinally. The mean decrease in 0.5 µg/mL PHA-TLP/50.0 pmol/g-lipid increase in dioxin-like PCBs over one year was 51.6 (95% confidence interval 2.7, 100.5; P=0.039). There was no association between plasma PCBs and NK cytotoxicity. Conclusions: These results do not provide strong evidence of impaired cellular immunity from PCB exposure. Larger longitudinal studies with greater variability in PCB exposures are needed to further examine temporal associations of PCBs with immune function. - Highlights: • Plasma PCBs and immune function were measured in 109 women at baseline and one year. • Immune measures included T lymphocyte proliferation (TLP) and NK cell cytotoxicity. • Higher-chlorinated PCBs were positively associated with TLP in cross-section. • An increase in dioxin-like PCBs was associated with a decrease in TLP over one year. • We did not find strong evidence of impaired cellular immunity from PCB exposure.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Change-point Detection and Image Segmentation for Time Series of Astrophysical Images

Many astrophysical phenomena are time-varying, in the sense that their intensity, energy spectrum, and/or the spatial distribution of the emission suddenly change. This paper develops a method for modeling a time series of images. Under the assumption that the arrival times of the photons follow a Poisson process, the data are binned into 4D grids of voxels (time, energy band, and x-y coordinates), and viewed as a time series of non-homogeneous Poisson images. The method assumes that at each time point, the corresponding multiband image stack is an unknown 3D piecewise constant function including Poisson noise. It also assumes that all image stacks between any two adjacent change points (in time domain) share the same unknown piecewise constant function. The proposed method is designed to estimate the number and the locations of all of the change points (in time domain), as well as all of the unknown piecewise constant functions between any pairs of the change points. The method applies the minimum description length principle to perform this task. A practical algorithm is also developed to solve the corresponding complicated optimization problem. Simulation experiments and applications to real data sets show that the proposed method enjoys very promising empirical properties. Applications to two real data sets, the XMM observation of a flaring star and an emerging solar coronal loop, illustrate the usage of the proposed method and the scientific insight gained from it.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1992

Trends in column ozone based on TOMS data - Dependence on month, latitude, and longitude

On the basis of the TOMS satellite column ozone data in latitudes 70 deg S-70 deg N from November 1978 to May 1990, a statistical model is used to estimate the trends in ozone as a function of latitude, longitude, and month. The trends in the TOMS ozone data are highly seasonal and dependent on location. Near the equator, the estimated monthly trends are not significantly different from zero. For high latitudes, most of the estimated monthly trends are negative. In January, February, and March, there are some positive trend estimates in the western hemisphere around latitude 60 deg N. The most negative trends for these three months also appear in the high latitudes of the northern hemisphere. Starting in June, more negative trends appear in the latitudes 50 deg S-70 deg S than the trends in the rest of the world considered. A large depletion develops during the spring time (September to November) in the southern high-latitude region, and the area of peak ozone decline is moving eastward during the period. The largest negative trends (about -29 percent per decade) for the area considered in this study appear in October around the latitude 70 deg S and longitudes 20 deg W-100 deg W region. For the northern hemisphere, the year-round trend estimates for latitudes 30 deg N-70 deg N range from -0.96 percent to -7.43 percent per decade. In the latitudes 30 deg N-50 deg N, the winter trend estimates are more negative than those for the summer and the fall. However, this pattern did not hold for latitudes 50 deg N-70 deg N.

Niu, Xufeng↗