Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distributed Estimation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,639 records · Page 91
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Radio jet feedback and star formation in heavily obscured, hyperluminous quasars at redshifts ∼ 0.5–3. I. ALMA observations

We present Atacama Large Millimeter/submillimeter Array (ALMA) 870 μm (345 GHz) data for 49 high-redshift (0.47 < z < 2.85), luminous (11.7<log(L{sub bol}/L{sub ⊙})<14.2) radio-powerful active galactic nuclei (AGNs), obtained to constrain cool dust emission from starbursts concurrent with highly obscured radiative-mode black hole (BH) accretion in massive galaxies that possess a small radio jet. The sample was selected from the Wide-field Infrared Survey Explorer with extremely steep (red) mid-infrared colors and with compact radio emission from NVSS/FIRST. Twenty-six sources are detected at 870 μm, and we find that the sample has large mid- to far-infrared luminosity ratios, consistent with a dominant and highly obscured quasar. The rest-frame 3 GHz radio powers are 24.7<log(P{sub 3.0 GHz}/W Hz{sup −1})<27.3, and all sources are radio-intermediate or radio-loud. BH mass estimates are 7.7 < log(M{sub BH}/M{sub ⊙}) < 10.2. The rest-frame 1–5 μm spectral energy distributions are very similar to the “Hot DOGs” (hot dust-obscured galaxies), and steeper (redder) than almost any other known extragalactic sources. ISM masses estimated for the ALMA-detected sources are 9.9 < log (M{sub ISM}/M{sub ⊙}) < 11.75 assuming a dust temperature of 30 K. The cool dust emission is consistent with star formation rates reaching several thousand M{sub ⊙} yr{sup −1}, depending on the assumed dust temperature, but we cannot rule out the alternative that the AGN powers all the emission in some cases. Our best constrained source has radiative transfer solutions with approximately equal contributions from an obscured AGN and a young (10–15 Myr) compact starburst.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A mathematical model of extremely low frequency ocean induced electromagnetic noise

Magnetic Anomaly Detection (MAD) system uses the principle that ferromagnetic objects disturb the magnetic lines of force of the earth. These lines of force are able to pass through both water and air in similar manners. A MAD system, usually mounted on an aerial vehicle, is thus often employed to confirm the detection and accomplish localization of large ferromagnetic objects submerged in a sea-water environment. However, the total magnetic signal encountered by a MAD system includes contributions from a myriad of low to Extremely Low Frequency (ELF) sources. The goal of the MAD system is to detect small anomaly signals in the midst of these low-frequency interfering signals. Both the Range of Detection (R{sub d}) and the Probability of Detection (P{sub d}) are limited by the ratio of anomaly signal strength to the interfering magnetic noise. In this paper, we report a generic mathematical model to estimate the signal-to-noise ratio or SNR. Since time-variant electro-magnetic signals are affected by conduction losses due to sea-water conductivity and the presence of air-water interface, we employ the general formulation of dipole induced electromagnetic field propagation in stratified media [1]. As a first step we employ a volumetric distribution of isolated elementary magnetic dipoles, each having its own dipole strength and orientation, to estimate the magnetic noise observed by a MAD system. Numerical results are presented for a few realizations out of an ensemble of possible realizations of elementary dipole source distributions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Pulse height model for deuterated scintillation detectors

This work includes the theoretical calculation of pulse height distribution and elaborate measurement at Ohio University using deuterated organic scintillation detector, which allows us to thoroughly investigate the light output spectrum induced by fast neutrons and convincingly compensate the pulse deficiency due to application of threshold to minimize noises either from electronics or environmental background. Specifically, a complete and self-contained analytic model of pulse height distribution for EJ-315 is created. In the model, considering impacts of detector geometry on light output and neutron leakage, a non-uniform angular distribution is also taken into account. An energy range of incident neutron from 1 MeV to 10 MeV is investigated. In return, based on the Peierls-formula, the completed calculation exhibits quantitative probability of fast neutron slowing down history due to stochastic collisions with carbon or deuterium nuclei. The quantitative collision probability conjoining with light output function, which was measured and corrected in view of detector response to several gamma rays, for continuous neutron flux generated by the tandem Van De Graaff Generator gives the light output for various collisions. Furthermore, the individual collision structure of the light pulse spectrum is analyzed and compared to the corresponding pulse height distribution from experimental measurement. Lastly, the resulting light pulse height distribution generated in this model offers intriguing advantages for identifying or characterizing nuclear materials and estimating potentials of various fast recoil detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

ARPA-E PNDIODES "PN Junctions by Ion Implantation" Project (Final Report)

Electricity accounts for nearly 40% of the energy generated in the United States, of which 65% is lost to electrical system inefficiency before reaching end-use sectors. Power electronics will play a growing role in this distribution and end-use, with up to 80% of electricity estimated to pass through power electronics from generation to consumption by 2030. This gives technical improvements in power electronics enormous potential to drive efficiency gains throughout the U.S. economy. Current Si-based power architectures including MOSFETs and IGBTs are limited by high losses, low switching frequency, and poor high-temperature performance. Given the material properties of GaN, devices can exhibit a given turn-on resistance and breakdown voltage with a minute fraction of the area of a Si device—all with higher switching speeds. While n-type doping of III-nitrides has reached a high level of maturity and integration into commercialized products, p-type doping presents distinct challenges that requires continued research. The success of the next generation of GaN-based power devices depends in large part on the ability to form selective-area p-type regions, which can be accomplished by ion implantation of the prevailing acceptor dopant, Mg. This approach is relatively inexpensive and is a fab-ready processing step for creation of current-generation power electronic devices including BJTs, IGBTs, and diode rectifiers. However, ion implantation induces lattice damage and creates point defects within the material, which negatively impacts dopant activation annealing. These forms of damage may be removed by high-temperature annealing, however short annealing time and higher pressures are required to prevent decomposition of the material. We approach this challenge through an innovative combination of approaches toward obtaining high-conductivity p-type GaN. By the novel employment of a gyrotron, a microwave source that can be shaped into a highly localized beam to dissipate very high power in a semiconductor target, a wafer of GaN can be annealed in short (<2 s) ‘pulses’ at temperatures of 1450 °C (2640 °F) to achieve p-type activation without appreciable surface degradation. The p-type activation of Mg-implanted GaN can be further aided by co-implantation with N, believed to enhance the removal of point defects that compensate the acceptors dopant. Elevation to such high temperatures for even a short time induces degradation of GaN-to overcome, we have implemented additional measures to retain high-quality crystalline GaN while removing implant damage and activating Mg dopant. A bilayer cap of AlN is deposited by a combination of chemical and physical vapor deposition to protect the GaN surface. To prevent decomposition of GaN loss of N during annealing, a custom vessel—to contain pressurized N while allowing injection of microwave energy—is employed. By detailed study of the interaction of various measures that are implemented to protect the sample surface (GaN), activate the implanted dopants, and mitigate damage of the lattice heating damage during annealing, we are able to achieve p-type GaN and observe recovery of the crystal and removal of substantial density of defects created during the implantation process.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Conservative Estimation of Tail Probabilities from Limited Sample Data

Several sparse-sample uncertainty quantification (UQ) methods are compared for conservative but not overly conservative estimation of small tail probabilities involving responses that lay beyond specified thresholds in the tails of probability distributions. Sixteen very differently shaped distributions (or probability density functions, PDFs) and tail probability magnitudes ranging from 10 -5 to 10 -1 are considered in order for the study to be relevant to a wide range of risk analysis and quantification of margins and uncertainty (QMU) problems. The emphasis of the study is on limited data regimes ranging from N = 2 to 20 samples, reflective of most experimental and some expensive computational situations. Relatively simple sparse-sample UQ methods tested for this regime involve statistical tolerance interval "Equivalent Normal and related "Ensemble of Normals" and "Superdistribution (SD) approaches. (The independently derived SD is effectively equivalent to the Bayesian posterior predictive distribution given the assumptions of the derivation.) The performance of the methods was generally improved for N ≥ 5 samples with a generalized Jackknife resampling technique, which determines a tail probability estimate by averaging estimates from smaller sub-samples. Several quantitative metrics for method conservatism and accuracy of tail probability estimation are used to assess and rank the methods' performance over many random trials for each test PDF and probability magnitude. A variant of Bootstrap resampling was also tried, but did not significantly improve tail probability estimates in most cases. Detailed results are presented from over 100-million tests over the above factors that provide useful granular information on which methods or combination of methods perform best in various areas of the factor space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Optimization of tomographic reconstruction workflows on geographically distributed resources

New technological advancements in synchrotron light sources enable data acquisitions at unprecedented levels. This emergent trend affects not only the size of the generated data but also the need for larger computational resources. Although beamline scientists and users have access to local computational resources, these are typically limited and can result in extended execution times. Applications that are based on iterative processing as in tomographic reconstruction methods require high-performance compute clusters for timely analysis of data. Here, time-sensitive analysis and processing of Advanced Photon Source data on geographically distributed resources are focused on. Two main challenges are considered: (i) modeling of the performance of tomographic reconstruction workflows and (ii) transparent execution of these workflows on distributed resources. For the former, three main stages are considered: (i) data transfer between storage and computational resources, (i) wait/queue time of reconstruction jobs at compute resources, and (iii) computation of reconstruction tasks. These performance models allow evaluation and estimation of the execution time of any given iterative tomographic reconstruction workflow that runs on geographically distributed resources. For the latter challenge, a workflow management system is built, which can automate the execution of workflows and minimize the user interaction with the underlying infrastructure. The system utilizes Globus to perform secure and efficient data transfer operations. The proposed models and the workflow management system are evaluated by using three high-performance computing and two storage resources, all of which are geographically distributed. Workflows were created with different computational requirements using two compute-intensive tomographic reconstruction algorithms. Experimental evaluation shows that the proposed models and system can be used for selecting the optimum resources, which in turn can provide up to 3.13× speedup (on experimented resources). Furthermore, the error rates of the models range between 2.1 and 23.3% (considering workflow execution times), where the accuracy of the model estimations increases with higher computational demands in reconstruction tasks.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Remote Sensing of Sea Salt Aerosol below Trade Wind Clouds

Abstract Sea salt aerosol in the boundary layer below shallow cumulus clouds is remotely observed with a Ka-band cloud radar at the Barbados Cloud Observatory and is detected in 76% of the measurements over 1 year. Carried by convection, sea salt particles with a diameter larger than 500 nm show an upward motion of 0.2 m s−1 below shallow cumulus clouds for a 2-day case study. Caused by an increasing relative humidity with increasing altitude, the sea salt particles become larger as they move closer to the cloud base. By using combined measurements of a Ka-band cloud radar and a Raman lidar, the retrieved equivolumetric diameter of the hygroscopically grown sea salt particles is found to be between 6 and 11 μm with a total number concentration of 20 cm−3 near cloud base. Assuming a fixed shape parameter, a size distribution of sea salt particles under high-relative-humidity conditions below cloud base is estimated and agrees with measurements taken by a dry-deposition sampler and online aerosol observations. The methods outlined in this paper can be used in future studies to get a better understanding of the vertical and temporal sea salt distribution in the boundary layer and sea salt aerosol–cloud interaction processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Effect of moisture content and distribution on radiation transport in concrete - 14426

Criticality Emergency Planning (CEP) requires a detailed knowledge of the Facility design and construction in order to undertake radiation transport studies in support of criticality consequence calculations. Such calculations are used at AWE to determine mitigated doses, CEP exclusion zones and in support of Criticality Warning Systems (CWS) detector head placement studies. At AWE, such calculations have traditionally been performed by assuming that structural concrete has a fixed and evenly distributed moisture profile. In order to validate this assumption, work has been undertaken using the finite element analysis tool Femmasse to simulate moisture movement within the concrete and calculate moisture distributions in a 65 cm thick concrete wall as a function of aging and specific environmental conditions. This work identified that considerable variation in the moisture profile may arise, with an equilibrium condition being reached after circa 20 years, where the overall moisture content is reduced to a minimum. Furthermore, the calculations identified that the overall moisture content used in extant CEP assessments was considerably lower than that estimated in this work. In order to determine the effect of the moisture distribution profiles, the Monte Carlo transport code MCNP5 was used to study the transmission of radiation through aged concrete and thus assess its performance as a radiation shield in the event of a criticality. Various moisture distributions were assessed based on the findings of the Femmasse calculations and were compared with that assessed using traditional assumptions. Results were obtained for neutron and photon doses. The paper provides an overview of the findings and makes recommendations on the suitability of using evenly distributed moisture profiles in concrete in support of mitigated doses, CEP and CWS detector head placement studies. (authors)

36 MATERIALS SCIENCE↗
DOE OSTI2024

Neural simulation-based inference of the neutron star equation of state directly from telescope spectra

Neutron stars provide a unique opportunity to study strongly interacting matter under extreme density conditions. The intricacies of matter inside neutron stars and their equation of state are not directly visible, but determine bulk properties, such as mass and radius, which affect the star's thermal X-ray emissions. However, the telescope spectra of these emissions are also affected by the stellar distance, hydrogen column, and effective surface temperature, which are not always well-constrained. Uncertainties on these nuisance parameters must be accounted for when making a robust estimation of the equation of state. In this study, we develop a novel methodology that, for the first time, can infer the full posterior distribution of both the equation of state and nuisance parameters directly from telescope observations. This method relies on the use of neural likelihood estimation, in which normalizing flows use samples of simulated telescope data to learn the likelihood of the neutron star spectra as a function of these parameters, coupled with Hamiltonian Monte Carlo methods to efficiently sample from the corresponding posterior distribution. Our approach surpasses the accuracy of previous methods, improves the interpretability of the results by providing access to the full posterior distribution, and naturally scales to a growing number of neutron star observations expected in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Entanglement Throughput Measurements and Capacity Estimates for Aerial-Inground Fiber

The throughput of entangled qubit pairs per second (eqps) is a basic performance metric of quantum networks that provide the entanglement distribution capability. Over fiber connections, it is measured using specialized instruments, including photonic entanglement sources and single-photon detectors. Extensive theory has been developed to estimate the capacity of a generic quantum channel, which in turn is applied to estimate the maximum achievable eqps over a fiber connection. However, there is a gap in relating these two performance metrics, in part due to their disparate nature, namely, mathematical formulae of the channel capacity and specialized instrumentation for eqps measurements. We describe eqps measurements collected over testbed connections composed of aerial and inground fiber of lengths up to 45 km. We estimate the normalized capacity using the transmissivity parameter derived from single photon detector measurements. These estimates are then converted to capacity bounds on the connection's eqps using the source eqps rate derived from co-located detector measurements. The results indicate a consistency between eqps measurements and their capacity estimates, and provide insights into relating the parameters of analytic capacity estimates to physical measurements.

Rao, Nageswara [ORNL] (ORCID:0000000234085941)↗
DOE OSTI2023

Description of the multinucleon transfer mechanism for Ca 48 + Pu 244 and Kr 86 + Pt 198 reactions in a quantal transport approach

Multinucleon transfer (MNT) reactions involving heavy projectile and target combinations stand as a promising method for synthesizing new neutron-rich exotic nuclei, which may not be possible using hot or cold fusion reactions or fragmentation. Exploring the mechanisms behind MNT reactions is essential and it requires a comprehensive theoretical framework that can explain the physical observables in these reactions. This work aims to show that the quantal diffusion approach based on the stochastic mean-field (SMF) theory is capable of explaining the reaction dynamics observed in MNT reactions. Primary product mass distributions in 48 Ca + 244 Pu reaction at E c.m. = 203.2 MeV and 86 Kr + 198 Pt reaction at E c.m. = 324.2 MeV are calculated and compared with the available experimental data. In this work, we utilize the time-dependent Hartree-Fock (TDHF) calculations to analyze the mean-field reaction dynamics computationally in the reactions 48 Ca + 244 Pu and 86 Kr + 198 Pt for a broad range of initial angular momenta. Quantal transport description based on the SMF approach is used to calculate quantal diffusion coefficients and mass variances in 48 Ca + 244 Pu and 86 Kr + 198 Pt systems. The primary products arising from quasifission reactions are described by joint probability distribution in the SMF approach and those arising from fusion-fission are estimated by using the statistical deexcitation code gemini + +. Mean values of charge and mass numbers, scattering angles of the primary reaction products, and the total kinetic energies after the collision are calculated within the TDHF framework for a broad range of initial angular momenta. Throughout all the collisions, drift toward the mass symmetry and large mass dispersion associated with this drift are observed. Here, the calculated primary fragment and mass distributions using the SMF approach successfully explain experimental observations for the 48 Ca + 244 Pu and 86 Kr + 198 Pt systems. The primary mass distributions, mean values of binary products, and mass dispersions are determined and results are compared with the available experimental data. The observed agreement between the experimental data and SMF results highlights the effectiveness of the quantal diffusion mechanism based on the SMF approach, which does not include any adjustable parameters other than standard parameters of Skyrme energy density functional.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

High-Throughput Computation and the Applicability of Monte Carlo Integration in Fatigue Load Estimation of Floating Offshore Wind Turbines

Long-term fatigue loads for floating offshore wind turbines are hard to estimate because they require the evaluation of the integral of a highly nonlinear function over a wide variety of wind and wave conditions. Current design standards involve scanning over a uniform rectangular grid of metocean inputs (e.g., wind speed and direction and wave height and period), which becomes intractable in high dimensions as the number of required evaluations grows exponentially with dimension. Monte Carlo integration offers a potentially efficient alternative because it has theoretical convergence proportional to the inverse of the square root of the number of samples, which is independent of dimension. In this paper, we first report on the integration of the aeroelastic code FAST into NREL's systems engineering tool, WISDEM, and the development of a high-throughput pipeline capable of sampling from arbitrary distributions, running FAST on a large scale, and postprocessing the results into estimates of fatigue loads. Second, we use this tool to run a variety of studies aimed at comparing grid-based and Monte Carlo-based approaches with calculating long-term fatigue loads. We observe that for more than a few dimensions, the Monte Carlo approach can represent a large improvement in computational efficiency, but that as nonlinearity increases, the effectiveness of Monte Carlo is correspondingly reduced. The present work sets the stage for future research focusing on using advanced statistical methods for analysis of wind turbine fatigue as well as extreme loads.

17 WIND ENERGY↗
DOE OSTI2023

Inclusive photon production at forward rapidities in pp and p–Pb collisions at $\sqrt{{{s}}_{\textrm{NN}}}={5.02}$ TeV

A study of multiplicity and pseudorapidity distributions of inclusive photons measured in pp and p–Pb collisions at a center-of-mass energy per nucleon–nucleon collision of $\sqrt{s_{NN}}$ = 5.02 TeV using the ALICE detector in the forward pseudorapidity region 2.3 < η lab < 3.9 is presented. Measurements in p–Pb collisions are reported for two beam configurations in which the directions of the proton and lead ion beam were reversed. The pseudorapidity distributions in p–Pb collisions are obtained for seven centrality classes which are defined based on different event activity estimators, i.e., the charged-particle multiplicity measured at midrapidity as well as the energy deposited in a calorimeter at beam rapidity. The inclusive photon multiplicity distributions for both pp and p–Pb collisions are described by double negative binomial distributions. The pseudorapidity distributions of inclusive photons are compared to those of charged particles at midrapidity in pp collisions and for different centrality classes in p–Pb collisions. The results are compared to predictions from various Monte Carlo event generators. None of the generators considered in this paper reproduces the inclusive photon multiplicity distributions in the reported multiplicity range. The pseudorapidity distributions are, however, better described by the same generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Modeling the impact of high thermal conductivity paper on the performance and life of power transformers

Degradation of insulation paper is a key contributor to the failure of power transformers. Insulation degradation accelerates at elevated temperatures, which highlights the potential for better thermal management to prolong life. While several studies have analyzed the benefits of high thermal conductivity oil for reducing temperatures inside a transformer, this study is an initial assessment of the benefits of high thermal conductivity paper on transformer life. Blending particulates with cellulosic fibers offers a pathway for high thermal conductivity paper (with good dielectric properties), which can reduce internal temperatures. Presently, life extensions that can be achieved by the use of such thermally conducting papers were estimated, with the thermal conductivity of the paper being the key parameter under study. The analytical-numerical thermal model used in this study was validated against experimental measurements in a distribution transformer, adding confidence to the utility of the model. This model was then used to provide estimates of hot-spot temperature reduction resulting from the use of papers with higher thermal conductivity than baseline. Transformer life was predicted conventionally by tracking the degree of polymerization of paper over time, based on an Arrhenius model. Results indicate that increasing the thermal conductivity of paper from 0.2 W/mK (baseline) to 1W/mK reduces the hot spot temperature by 10°C. While degradation significantly depends on the moisture and oxygen content, the model shows that such a temperature reduction can increase life for all conditions, by as much as a factor of three.

42 ENGINEERING↗
DOE OSTI2015

Black carbon aerosol-induced Northern Hemisphere tropical expansion

Global climate models (GCMs) underestimate the observed trend in tropical expansion. Recent studies partly attribute it to black carbon (BC) aerosols, which are poorly represented in GCMs. In this paper, we conduct a suite of idealized experiments with the Community Atmosphere Model version 4 coupled to a slab ocean model forced with increasing BC concentrations covering a large swath of the estimated range of current BC radiative forcing while maintaining their spatial distribution. The Northern Hemisphere (NH) tropics expand poleward nearly linearly as BC radiative forcing increases (0.7° W -1 m 2 ), indicating that a realistic representation of BC could reduce GCM biases. We find support for the mechanism where BC-induced midlatitude tropospheric heating shifts the maximum meridional tropospheric temperature gradient poleward resulting in tropical expansion. Finally, we also find that the NH poleward tropical edge is nearly linearly correlated with the location of the Intertropical Convergence Zone, which shifts northward in response to increasing BC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The scaling economics of small unit operations

We present a correlation that represents the capital costs of the components of even very small modular facilities. Conversion of distributed feedstocks (eg, associated natural gas, biomass, and carbonaceous wastes) could provide a small fraction of the liquid fuels now used for transportation in the U.S. (~6%),or nearly half of the chemical products now made from petroleum. However, those resources tend to be available at small geographically distributed sites, and they are difficult or expensive to transport to a distant processing center. Modular, and likely intensified, processes that can be numbered up promise to enable utilizing such distributed resources. Early stage economics evaluation of those processes requires cost estimates for the components, which are likely smaller in scale than can be accommodated by the 0.6 power law typically used in chemical engineering

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Forecasting Multi-Wave Epidemics Through Bayesian Inference

We present a simple, near-real-time Bayesian method to infer and forecast a multiwave outbreak, and demonstrate it on the COVID-19 pandemic. The approach uses timely epidemiological data that has been widely available for COVID-19. It provides short-term forecasts of the outbreak’s evolution, which can then be used for medical resource planning. The method postulates one- and multiwave infection models, which are convolved with the incubation-period distribution to yield competing disease models. The disease models’ parameters are estimated via Markov chain Monte Carlo sampling and information-theoretic criteria are used to select between them for use in forecasting. The method is demonstrated on two- and three-wave COVID-19 outbreaks in California, New Mexico and Florida, as observed during Summer-Winter 2020. We find that the method is robust to noise, provides useful forecasts (along with uncertainty bounds) and that it reliably detected when the initial single-wave COVID-19 outbreaks transformed into successive surges as containment efforts in these states failed by the end of Spring 2020.

59 BASIC BIOLOGICAL SCIENCES↗