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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Exclusive J/$\psi$ detection and physics with ECCE

The EIC Comprehensive Chromodynamics Experiment (ECCE) detector has been recommended as a reference design for the proposed Electron-Ion Collider (EIC) program. Here, this paper presents simulation studies of exclusive J/$\psi$ detection and selected physics impact results in EIC using the projected ECCE detector concept. Exclusive quarkonium photoproduction is one of the most popular processes in EIC, which has a large cross section and a simple final state. Due to the gluonic nature of the exchange Pomeron, this process can be related to the gluon distributions in the nucleus. Preliminary results estimate the excellent statistics benefited from the large cross section of J/$\psi$ photoproduction and superior performance of ECCE detector concept. The precise measurement of exclusive J/$\psi$ photoproduction at EIC will help us to more deeply understand nuclear gluon distributions, near threshold production mechanism and nucleon mass structure.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Velocity-dependent J-factors for Milky Way dwarf spheroidal analogues in cosmological simulations

We study the impact of the dark matter velocity distribution modelling on signals from velocity-dependent dark matter annihilation in Milky Way dwarf spheroidal galaxies. Using the high resolution APOSTLE simulations, we identify analogues corresponding to Milky Way dwarf spheroidal galaxies, and from these directly determine the dark matter pair-wise relative velocity distribution, and compare to best-fitting Maxwell-Boltzmann distribution models. For three velocity-dependent annihilation models, p-wave, d-wave, and the Sommerfeld model, we quantify the errors introduced when using the Maxwell-Boltzmann parameterization. We extract a simple power-law relation between the maximum circular velocity of the dwarf spheroidal analogue and the peak speed of the Maxwell-Boltzmann distribution. We show that this relation can be used to accurately calculate the dark matter relative velocity distribution, and find that it allows us to estimate the dark matter annihilation signal without the need to directly calculate the relative velocity distribution for each galaxy. The scatter in the J-factors calculated from the analogues dominates the uncertainty obtained when compared to the J-factor as determined from the observational data for each dwarf spheroidal, with the largest scatter from d-wave models and the smallest from Sommerfeld models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

PARTICLE ACCELERATION AND HEATING BY TURBULENT RECONNECTION

Turbulent flows in the solar wind, large-scale current sheets, multiple current sheets, and shock waves lead to the formation of environments in which a dense network of current sheets is established and sustains “turbulent reconnection.” We constructed a 2D grid on which a number of randomly chosen grid points are acting as scatterers (i.e., magnetic clouds or current sheets). Our goal is to examine how test particles respond inside this large-scale collection of scatterers. We study the energy gain of individual particles, the evolution of their energy distribution, and their escape time distribution. We have developed a new method to estimate the transport coefficients from the dynamics of the interaction of the particles with the scatterers. Replacing the “magnetic clouds” with current sheets, we have proven that the energization processes can be more efficient depending on the strength of the effective electric fields inside the current sheets and their statistical properties. Using the estimated transport coefficients and solving the Fokker–Planck (FP) equation, we can recover the energy distribution of the particles only for the stochastic Fermi process. We have shown that the evolution of the particles inside a turbulent reconnecting volume is not a solution of the FP equation, since the interaction of the particles with the current sheets is “anomalous,” in contrast to the case of the second-order Fermi process.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1990

Power system state estimation for a spacecraft power system

An application of the maximum likelihood state estimator to a space-based power system is presented. The state estimator uses current and voltage measurements to generate estimates of node voltages for an electrical power distribution system for the Space Shuttle. Preliminary results on the effect of noisy measurements on estimated parameters are reported. The software used in generating these results is part of an overall package being developed at Louisiana Tech University. Intended applications of this package include the analysis of power systems and real-time parallel processing on the Space Shuttle.

Berry, F. C.↗
DOE OSTI2019

Attack Identification and Correction for PMU GPS Spoofing in Unbalanced Distribution Systems

Due to the vulnerability of civilian global positioning system (GPS) signals, the accuracy of phasor measurement units (PMUs) can be greatly compromised by GPS spoofing attacks (GSAs), which introduce phase shifts into true phase angle measurements. Focusing on simultaneous GSAs for multiple PMU locations, this paper proposes a novel identification and correction algorithm in distribution systems. A sensitivity analysis of state estimation residuals on a single GSA phase angle is firstly implemented. An identification algorithm using a probing technique is proposed to determine the locations of spoofed PMUs and the ranges of GSA phase shifts. Based on the identification results, these GSA phase shifts are determined via an estimation algorithm that minimizes the mismatch between measurements and system states. Finally, with the attacked PMU data corrected, the system states are recovered. Simulations in unbalanced IEEE 34-bus and 123-bus distribution systems demonstrates the efficiency and accuracy of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Size Selectivity of Sampling Gears Used to Sample Kokanee

Abstract Kokanee Oncorhynchus nerka provide valued recreational fisheries and also serve as a prey resource for economically, socially, and ecologically important fishes. As such, management of kokanee is a major focus of natural resource agencies. Kokanee are typically monitored using midwater trawls, but the interpretation of data collected using midwater trawls is difficult due to the unknown size selectivity of the gear. We sought to assess the length selectivity of midwater trawls by comparing estimates obtained from midwater trawls with estimates obtained from gill nets adjusted for size selectivity. Experimental curtain gill nets and midwater trawls were used in conjunction to sample kokanee in seven lentic systems in Idaho. The size selectivity of gill nets was estimated by accounting for the probability of encounter and the probability of retention. Estimates of size selectivity were then used to adjust the length distribution of fish sampled in gill nets. The adjusted length distribution of fish sampled in gill nets was compared with estimates obtained from midwater trawls to identify potential size selectivity of midwater trawls. A pattern of size selectivity was apparent for both sampling techniques. The average length of kokanee sampled with midwater trawls was 111 mm; whereas, kokanee sampled with gill nets had a mean length of 235 mm. Our results suggest experimental gill nets are useful for common sampling of kokanee (e.g., trend monitoring) because the gear is less size selective than midwater trawls and is adjustable for size selectivity. However, midwater trawls are likely the best gear for addressing questions associated with early life history. Overall, our results provide a better understanding of gill-net and midwater trawl selectivity and ultimately improve the ability to sample and manage the species.

Klein, Zachary B.↗
DOE OSTI2016

Nitrate vulnerability projections from Bayesian inference of multiple groundwater age tracers

Nitrate is a major source of contamination of groundwater in the United States and around the world. We tested the applicability of multiple groundwater age tracers ( 3 H, 3 He, 4 He, 14 C, 13 C, and 85 Kr) in projecting future trends of nitrate concentration in 9 long-screened, public drinking water wells in Turlock, California, where nitrate concentrations are increasing toward the regulatory limit. Very low 85 Kr concentrations and apparent 3 H/ 3 He ages point to a relatively old modern fraction (40–50 years), diluted with pre-modern groundwater, corroborated by the onset and slope of increasing nitrate concentrations. An inverse Gaussian–Dirac model was chosen to represent the age distribution of the sampled groundwater at each well. Model parameters were estimated using a Bayesian inference, resulting in the posterior probability distribution – including the associated uncertainty – of the parameters and projected nitrate concentrations. Three scenarios were considered, including combined historic nitrate and age tracer data, the sole use of nitrate and the sole use of age tracer data. Each scenario was evaluated based on the ability of the model to reproduce the data and the level of reliability of the nitrate projections. The tracer-only scenario closely reproduced tracer concentrations, but not observed trends in the nitrate concentration. Both cases that included nitrate data resulted in good agreement with historical nitrate trends. Use of combined tracers and nitrate data resulted in a narrower range of projections of future nitrate levels. However, use of combined tracer and nitrate resulted in a larger discrepancy between modeled and measured tracers for some of the tracers. In conclusion, despite nitrate trend slopes between 0.56 and 1.73 mg/L/year in 7 of the 9 wells, the probability that concentrations will increase to levels above the MCL by 2040 are over 95% for only two of the wells, and below 15% in the other wells, due to a leveling off of reconstructed historical nitrate loadings to groundwater since about 1990.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Autonomous Unmanned Aerial Vehicles for Examining Current and Evolving Distribution of Contamination from the FDNPP Accident - 17020

Estimates as well as subsequent measurements of the radiation released following the events at the Fukushima Daiichi Nuclear Power Plant in March 2011 place the incident as the second greatest nuclear event to have ever occurred - duly rated at the maximum of Level 7 on the INES Event Scale. The releases of radioactivity from the plant were detected worldwide, however the multi-reactor nature of the events at the FDNPP has complicated the understanding of the radionuclide release inventory and the subsequent distribution of the material. As a result of this highly-complex release scenario, it is important to understand the current and evolving state of contamination within the rapidly evolving, topographically extreme and frequently typhoon impacted environment on Japan's eastern coast. Existing systems rely either on high-altitude manned aircraft to perform such contamination surveys, correcting results to ground-level, or, on humans manually measuring the dose-rate on foot. In order to overcome the shortcomings of both methods, a low-altitude unmanned aerial vehicle (UAV) has been developed at the University of Bristol and successfully deployed to the affected areas surrounding the FDNPP. In contrast to these other methods; the use of low-altitude UAVs provides a spatial resolution previously achievable only through the deployment of humans on the ground, with the potential for significant radiation exposure. This high-resolution monitoring allows for subsequent modelling to inform our understanding of the behaviour and long-term stability of the fallout material. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1993

A study of the earth's free core nutation using international deployment of accelerometers gravity data

In this study we consider the influence of the earth's free core nutation (FCN) on diurnal tidal admittance estimates for 11 stations of the globally distributed International Deployment of Accelerometers network. The FCN causes a resonant enhancement of the diurnal admittances which can be used to estimate some properties of the FCN. Estimations of the parameters describing the FCN (period, Q, and resonance strength) are made using data from individual stations and many stations simultaneously. These yield a result for the period of 423-452 sidereal days, which is shorter than theory predicts but is in agreement with many previous studies and suggests that the dynamical ellipticity of the core may be greater than its hydrostatic value.

Cummins, Phil R.↗
NASA NTRS2011

Multiple Damage Progression Paths in Model-Based Prognostics

Model-based prognostics approaches employ domain knowledge about a system, its components, and how they fail through the use of physics-based models. Component wear is driven by several different degradation phenomena, each resulting in their own damage progression path, overlapping to contribute to the overall degradation of the component. We develop a model-based prognostics methodology using particle filters, in which the problem of characterizing multiple damage progression paths is cast as a joint state-parameter estimation problem. The estimate is represented as a probability distribution, allowing the prediction of end of life and remaining useful life within a probabilistic framework that supports uncertainty management. We also develop a novel variance control mechanism that maintains an uncertainty bound around the hidden parameters to limit the amount of estimation uncertainty and, consequently, reduce prediction uncertainty. We construct a detailed physics-based model of a centrifugal pump, to which we apply our model-based prognostics algorithms. We illustrate the operation of the prognostic solution with a number of simulation-based experiments and demonstrate the performance of the chosen approach when multiple damage mechanisms are active

Daigle, Matthew↗
NASA NTRS1978

A global model for rain attenuation prediction

A model was developed for the prediction of rain attenuation statistics for 8 rain rate climate regions spanning all land regions from the equator to the poles. The model uses empirically determined rain rate distributions for each climate region and an empirical model to estimate path averaged rain rate for given values of point rain rate. Attenuation distribution observations were compared with model predictions. Good agreement was obtained for earth-space paths at 0.1 percent of the year. At the extremes, 0.01 and 1 percent of the year the observations were generally within the model estimate bounds but the agreement is not as good as at 0.1 percent of the year. The discrepancies are attributed to the limited duration of the attenuation observations and to the limited number of rain rate distribution observations.

Crane, R. K.↗
DOE OSTI2021

Rare Events via Cross-Entropy Population Monte Carlo

Rare events are events that happen with very low frequency. Estimating rare event probabilities using Monte Carlo techniques is computationally expensive, often to the point of intractability, and special methods are required. Importance sampling (IS) is a well known technique that uses a proposal distribution in place of a target distribution to lower the variance of the estimator. Key to the success of IS methods is the choice of a proposal distribution, or the parameters governing the distribution. Adaptive importance sampling improves the parameters of a family or population of proposal distributions iteratively through trials. We present a novel cross-entropy population Monte Carlo algorithm, which adapts the parameters of proposals through the cross-entropy method. The proposed method stands apart from previous work in that we are not optimizing a mixture distribution. Instead, we leverage deterministic mixture weights and optimize the distributions individually through a reinterpretation of the typical derivation of the cross-entropy method. Demonstrations on rare event examples show that the algorithm can outperform existing resampling based population Monte Carlo methods, especially for higher-dimensional problems. Finally, we also demonstrate efficacy on a conjunction analysis problem.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2019

Characterizing the System Impulse Response Function from Photon-Counting LiDAR Data

NASA's Multiple Altimeter Beam Experimental LiDAR (MABEL) is an aircraft-based photon-counting laser altimeter designed as a simulator to test measurement techniques and algorithms for Advanced Topographic Laser Altimeter System (ATLAS), the sole instrument on NASA's Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. By measuring the time of flight, pointing angle, and absolute position for individual photons, ICESat-2 provides detailed elevation measurements of earth's surface. Calculating accurate and precise elevations requires an understanding of how photons interact with surfaces, and characterization of the photon distribution after returning from surfaces. Neither MABEL nor ATLAS records the transmitted laser pulse shape, relying instead on aggregating several pulses worth of photons, often using histograms, to characterize the pulse shape. In this paper, we assess the limitations of using histograms and propose a more robust method to describe MABEL's system impulse-response function using an exponentially modified Gaussian distribution. We also provide standard error estimates for the arithmetic mean and standard deviation calculations, and for exponentially modified Gaussian parameters using a Monte Carlo sensitivity analysis. We apply this method to photon returns from a sea ice lead and from a dry salt lake bed as case studies for estimating the standard error associated with sample size for the arithmetic mean and standard deviation, and for the exponentially modified Gaussian parameters. We use these standard errors to calculate the minimum number of photons required to find both Gaussian and exponentially modified Gaussian distribution parameters within 3 cm of their parent population values.

photoncounting↗
NASA NTRS2013

Temporal Fluctuations in a 100-A LaB6 Hollow Cathode

The temporal fluctuations in the near plume of a 100-Amperes LaB6 (Lanthanum hexaboride) hollow cathode are experimentally investigated. At high currents, turbulent oscillations may contribute to two of the anomalous processes of hollow cathode operation - anomalous resistivity and the production of energetic ions. A detailed study of the properties of the oscillations in a high current cathode is necessary to determine the impact of the fluctuation spectrum on these two effects. In this investigation, a probe array is employed to measure the amplitude and dispersion of axial modes in the plume while a retarding potential analyzer yields estimates of the radial ion energy distribution. The onset of the ion acoustic turbulence (IAT) is observed at high current values, and the character of the turbulent spectrum is shown to agree with weak turbulent theory: the amplitude of the spectrum decreases with flow rate but increases with discharge current. Estimates of the anomalous collision frequency based on experimental observations indicate that the IAT collision frequency can exceed the classical collision frequency at sufficiently high discharge current densities. Additionally, the onset of the IAT is shown to be correlated with the appearance of a high energy ion tail and that the energy in this tail is comparable to the energy in the experimentally-observed IAT.

production of ions↗
NASA NTRS1994

Characteristics of the vertical profiles of dual-frequency, dual-polarization radar data in stratiform rain

Airborne dual-wavelength and dual-polarization radar data are analyzed for measurements taken in stratiform rain in the western Pacific during September 1990. The focus of the paper is on the vertical profiles of the linear depolarization ratio, LDR (10 GHz); the reflectivity factor, dBZ (10 GHz); and the dual-frequency ratio, DFR (10, 34.45 GHz). Statistical characterizations of the maxima of these quantities and the relative locations at which they occur suggest that the eccentricity of the melting particles is fairly large and that the shape and size of the particles are correlated. To try to explain these features, two types of simulation are presented. In the first, a set of measured drop size distributions is used in the context of a standard model of the melting layer. Variations in snow density, as well as shape, size, and orientation distributions are used to study the relationship between these parameters and the radar measurements. To reduce the amount of ambiguity in the estimation, a second type of simulation is described in which the size distribution of the snow is estimated. Comparisons between the simulated and measured profiles indicate that radar measurements can be used to derive certain characteristics of the particle size and shape distributions in the melting layer.

Meneghini, R.↗
DOE OSTI2016

The Chandra cosmos legacy survey: clustering of X-ray-selected AGNs at 2.9 ≤ z ≤ 5.5 using photometric redshift probability distribution functions

We present the measurement of the projected and redshift-space two-point correlation function (2pcf) of the new catalog of Chandra COSMOS-Legacy active galactic nucleus (AGN) at 2.9 ≤ z ≤ 5.5 (〈L{sub bol}〉 ∼ 10{sup 46} erg s{sup −1}) using the generalized clustering estimator based on phot-z probability distribution functions in addition to any available spec-z. We model the projected 2pcf, estimated using π {sub max} = 200 h{sup −1} Mpc with the two-halo term and we derive a bias at z ∼ 3.4 equal to b = 6.6{sub −0.55}{sup +0.60}, which corresponds to a typical mass of the hosting halos of log M {sub h} = 12.83{sub −0.11}{sup +0.12} h{sup −1} M {sub ⊙}. A similar bias is derived using the redshift-space 2pcf, modeled including the typical phot-z error σ {sub z} = 0.052 of our sample at z ≥ 2.9. Once we integrate the projected 2pcf up to π {sub max} = 200 h{sup −1} Mpc, the bias of XMM and Chandra COSMOS at z = 2.8 used in Allevato et al. is consistent with our results at higher redshifts. The results suggest only a slight increase of the bias factor of COSMOS AGNs at z ≳ 3 with the typical hosting halo mass of moderate-luminosity AGNs almost constant with redshift and equal to log M {sub h} = 12.92{sub −0.18}{sup +0.13} at z = 2.8 and log M {sub h} = 12.83{sub −0.11}{sup +0.12} at z ∼ 3.4, respectively. The observed redshift evolution of the bias of COSMOS AGNs implies that moderate-luminosity AGNs still inhabit group-sized halos at z ≳ 3, but slightly less massive than observed in different independent studies using X-ray AGNs at z ≤ 2.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Satellite-Derived Distributions, Inventories and Fluxes of Dissolved and Particulate Organic Matter Along the Northeastern U.S. Continental Margin

Estuaries and the coastal ocean experience a high degree of variability in the composition and concentration of particulate and dissolved organic matter (DOM) as a consequence of riverine and estuarine fluxes of terrigenous DOM, sediments, detritus and nutrients into coastal waters and associated phytoplankton blooms. Our approach integrates biogeochemical measurements, optical properties and remote sensing to examine the distributions and inventories of organic carbon in the U.S. Middle Atlantic Bight and Gulf of Maine. Algorithms developed to retrieve colored DOM (CDOM), Dissolved (DOC) and Particulate Organic Carbon (POC) from NASA's MODIS-Aqua and SeaWiFS satellite sensors are applied to quantify the distributions and inventories of DOC and POC. Horizontal fluxes of DOC and POC from the continental margin to the open ocean are estimated from SeaWiFS and MODIS-Aqua distributions of DOC and POC and horizontal divergence fluxes obtained from the Northeastern North Atlantic ROMS model. SeaWiFS and MODIS imagery reveal the importance of estuarine outflow to the export of CDOM and DOC to the coastal ocean and a net community production of DOC on the shelf.

Mannino, A.↗
DOE OSTI2018

Clusterdv: a simple density-based clustering method that is robust, general and automatic

Abstract Motivation How to partition a dataset into a set of distinct clusters is a ubiquitous and challenging problem. The fact that data vary widely in features such as cluster shape, cluster number, density distribution, background noise, outliers and degree of overlap, makes it difficult to find a single algorithm that can be broadly applied. One recent method, clusterdp, based on search of density peaks, can be applied successfully to cluster many kinds of data, but it is not fully automatic, and fails on some simple data distributions. Results We propose an alternative approach, clusterdv, which estimates density dips between points, and allows robust determination of cluster number and distribution across a wide range of data, without any manual parameter adjustment. We show that this method is able to solve a range of synthetic and experimental datasets, where the underlying structure is known, and identifies consistent and meaningful clusters in new behavioral data. Availability and implementation The clusterdv is implemented in Matlab. Its source code, together with example datasets are available on: https://github.com/jcbmarques/clusterdv. Supplementary information Supplementary data are available at Bioinformatics online.

Marques, João C.↗