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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Resurgence, Painlevé equations and conformal blocks

We discuss some physical consequences of the resurgent structure of Painlevé equations and their related conformal block expansions. Here, the resurgent structure of Painlevé equations is particularly transparent when expressed in terms of physical conformal block expansions of the associated tau functions. Resurgence produces an intricate network of inter-relations; some between expansions around different critical points, others between expansions around different instanton sectors of the expansions about the same critical point, and others between different non-perturbative sectors of associated spectral problems, via the Bethe-gauge and Painlevé-gauge correspondences. Resurgence relations exist both for convergent and divergent expansions, and can be interpreted in terms of the physics of phase transitions. These general features are illustrated with three physical examples: correlators of the 2d Ising model, the partition function of the Gross–Witten–Wadia matrix model, and the full counting statistics of one dimensional fermions, associated with Painlevé VI, Painlevé III and Painlevé V, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

CHANDRA DETECTION OF SN 2010da FOUR MONTHS AFTER OUTBURST: EVIDENCE FOR A HIGH-MASS X-RAY BINARY IN NGC 300

We present the results of a 63 ks Chandra observation of the 'supernova impostor' SN 2010da four months after it was first observed on 2010 May 24. We detect an X-ray source at {approx}7{sigma} confidence coincident with the optical location of the outburst. Our imaging analysis has revealed a hard central point source, surrounded by soft diffuse emission extending {approx}8'' north of the central source. The diffuse emission has a hardness ratio ({approx}-0.4), 0.35-2 keV luminosity ({approx}6 x 10{sup 35} erg s{sup -1}), and size ({approx}70 pc) consistent with that of a supernova remnant, although the low number of counts prohibits detailed spectral modeling. The 0.5-6 keV spectrum of the central point source is well described by both a power law with {Gamma} {approx}0 and a blackbody with kT {approx} 1.8 keV, with no evidence for intrinsic absorption beyond the Galactic column. We estimate the 0.3-10 keV luminosity to be {approx}2 x 10{sup 37} erg s{sup -1}, a factor of {approx}25 decrease since the initial outburst. The high X-ray luminosity and slow fading rate is not consistent with this object being a single massive star undergoing an outburst. When combined with the optical and infrared properties of the outburst and progenitor systems, our X-ray observations suggest the SN 2010da system may be a Be X-ray binary system which experienced an extremely bright optical outburst near simultaneously with a bright, Type II X-ray outburst.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

FAINT END OF 1.3 mm NUMBER COUNTS REVEALED BY ALMA

We present the faint end of number counts at 1.3 mm (238 GHz) obtained with the Atacama Large Millimeter/submillimeter Array (ALMA). Band 6 observations were carried out targeting 20 star-forming galaxies at z ∼ 1.4 in the Subaru/XMM-Newton Deep Survey field. In the observations, we serendipitously detect 15 sources (≥3.8σ, S{sub 1.3} {sub mm} = 0.15-0.61 mJy) other than the targeted sources. We create number counts by using these ''sub-mJy sources'', which probe the faintest flux range among surveys at millimeter wavelengths. The number counts are consistent with (flux-scaled) number counts at 850 μm and 870 μm obtained with gravitational lensing clusters. The ALMA number counts agree well with model predictions, which suggest that these sub-mJy populations are more like ''normal'' star-forming galaxies than ''classical'' submillimeter galaxies with intense star-forming activity. In this flux range, ∼80% of the extragalactic background light at 1.3 mm is resolved into individual sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

HerMES: A DEFICIT IN THE SURFACE BRIGHTNESS OF THE COSMIC INFRARED BACKGROUND DUE TO GALAXY CLUSTER GRAVITATIONAL LENSING

We have observed four massive galaxy clusters with the SPIRE instrument on the Herschel Space Observatory and measure a deficit of surface brightness within their central region after removing detected sources. We simulate the effects of instrumental sensitivity and resolution, the source population, and the lensing effect of the clusters to estimate the shape and amplitude of the deficit. The amplitude of the central deficit is a strong function of the surface density and flux distribution of the background sources. We find that for the current best fitting faint end number counts, and excellent lensing models, the most likely amplitude of the central deficit is the full intensity of the cosmic infrared background (CIB). Our measurement leads to a lower limit to the integrated total intensity of the CIB of I{sub 250{mu}m}>0.69{sub -0.03}{sup +0.03}(stat.){sub -0.06}{sup +0.11}(sys.) MJy sr{sup -1}, with more CIB possible from both low-redshift sources and from sources within the target clusters. It should be possible to observe this effect in existing high angular resolution data at other wavelengths where the CIB is bright, which would allow tests of models of the faint source component of the CIB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Poisson hurdle model-based method for clustering microbiome features

Abstract Motivation High-throughput sequencing technologies have greatly facilitated microbiome research and have generated a large volume of microbiome data with the potential to answer key questions regarding microbiome assembly, structure and function. Cluster analysis aims to group features that behave similarly across treatments, and such grouping helps to highlight the functional relationships among features and may provide biological insights into microbiome networks. However, clustering microbiome data are challenging due to the sparsity and high dimensionality. Results We propose a model-based clustering method based on Poisson hurdle models for sparse microbiome count data. We describe an expectation–maximization algorithm and a modified version using simulated annealing to conduct the cluster analysis. Moreover, we provide algorithms for initialization and choosing the number of clusters. Simulation results demonstrate that our proposed methods provide better clustering results than alternative methods under a variety of settings. We also apply the proposed method to a sorghum rhizosphere microbiome dataset that results in interesting biological findings. Availability and implementation R package is freely available for download at https://cran.r-project.org/package=PHclust. Supplementary information Supplementary data are available at Bioinformatics online.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Life Cycle Analysis Data and Results for Geothermal and Other Electricity Generation Technologies

Life cycle analysis (LCA) is an environmental assessment method that quantifies the environmental performance of a product system over its entire lifetime, from cradle to grave. Based on a set of relevant metrics, the method is aptly suited for comparing the environmental performance of competing products systems. This file contains LCA data and results for electric power production including geothermal power. The LCA for electric power has been broken down into two life cycle stages, namely plant and fuel cycles. Relevant metrics include the energy ratio and greenhouse gas (GHG) ratios, where the former is the ratio of system input energy to total lifetime electrical energy out and the latter is the ratio of the sum of all incurred greenhouse gases (in CO2 equivalents) divided by the same energy output. Specific information included herein are material to power (MPR) ratios for a range of power technologies for conventional thermoelectric, renewables (including three geothermal power technologies), and coproduced natural gas/geothermal power. For the geothermal power scenarios, the MPRs include the casing, cement, diesel, and water requirements for drilling wells and topside piping. Also included herein are energy and GHG ratios for plant and fuel cycle stages for the range of considered electricity generating technologies. Some of this information are MPR data extracted directly from the literature or from models (eg. ICARUS - a subset of ASPEN models) and others (energy and GHG ratios) are results calculated using GREET models and MPR data. MPR data for wells included herein were based on the Argonne well materials model and GETEM well count results.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Algorithmic and GPU enhancements for molecular dynamics in Cabana and LAMMPS

The focus of this milestone was to implement and test new algorithms and optimizations for improved GPU performance by molecular dynamics (MD) and related particle codes. The work was done in the CoPA Cabana library, the CabanaMD mini-app which uses Cabana to implement and benchmark prototypical MD models, and the LAMMPS MD code which is used by the ECP EXAALT project as well as for materials modeling generally. Efforts included (a) implementation of new or optimized algorithms for fundamental MD kernels like neighbor-list building and FFTs which are also widely used in other particle methods, (b) performance testing of data structure layouts for both simple pairwise and computationally intense neural network potentials, (c) optimizations aimed at improving GPU performance for models with small atom counts, and (d) optimizations specific to the SNAP interatomic potential due to its importance for the EXAALT project.

36 MATERIALS SCIENCE↗
DOE OSTI2016

AN EMPIRICAL METHOD FOR IMPROVING THE QUALITY OF RXTE HEXTE SPECTRA

We have developed a correction tool to improve the quality of Rossi X-ray Timing Explorer (RXTE) High Energy X-ray Timing Experiment (HEXTE) spectra by employing the same method we used earlier to improve the quality of RXTE Proportional Counter Array (PCA) spectra. We fit all of the hundreds of HEXTE spectra of the Crab individually to a simple power-law model, some 37 million counts in total for Cluster A and 39 million counts for Cluster B, and we create for each cluster a combined spectrum of residuals. We find that the residual spectrum of Cluster A is free of instrumental artifacts while that of Cluster B contains significant features with amplitudes ∼1%; the most prominent is in the energy range 30–50 keV, which coincides with the iodine K edge. Starting with the residual spectrum for Cluster B, via an iterative procedure we created the calibration tool hexBcorr for correcting any Cluster B spectrum of interest. We demonstrate the efficacy of the tool by applying it to Cluster B spectra of two bright black holes, which contain several million counts apiece. For these spectra, application of the tool significantly improves the goodness of fit, while affecting only slightly the broadband fit parameters. The tool may be important for the study of spectral features, such as cyclotron lines, a topic that is beyond the scope of this paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Two-Tower Quantum Matrix Chain Multiplication: Trading Qubits for Depth

Matrix chain multiplication -- computing $\mathcal{W} = M^{(0)}\cdots M^{(K-1)}$ where $M^{(k)} \in \mathbb{R}^{P_k \times P_{k+1}}$-- arises in scientific computing, machine learning, and graph analysis. Despite the importance of this problem, for chains of distinct matrices, the classical number of operations grows linearly with the chain length $K$ and polynomially in the matrix dimensions. We present \emph{Two-Tower Matrix Multiplication}, a quantum subroutine that encodes the product $\mathcal{W}$ of the $K$ matrices into a quantum state in circuit depth $\mathcal{O}(\max_{k} \mathrm{polylog} (P_k P_{k+1}))$, which is independent of~$K$ within the QRAM-based state-preparation model, whereas the qubit count is $\mathcal{O}\bigl(\sum_{k} \log P_k \bigr)$; the total gate count remains linear in $K$, so the gain is in the circuit depth. The construction interleaves state-preparation operators across two layers; within each layer, all operators act on disjoint registers and execute in parallel. This subroutine can be specialized for the chain-vector case, which computes the product of $K-1$ matrices applied to a vector. We prove the correctness of the subroutine for all $K$ and provide two implementations using the Qiskit and QCLAB frameworks. The subroutine is applicable to any downstream quantum algorithm that operates on a matrix encoded in the statevector, including norm estimation, graph-matrix powers, linear system solving, and quantum machine learning kernels.

Antonioli, Giacomo [Pisa U.] (ORCID:00090000668703↗
DOE OSTI2026

Allometric and Mobile Terrestrial LiDAR Modeling of Aboveground Woody Biomass of Populus in Coppice Production

Poplars ( Populus spp.) and their hybrids are increasingly being grown in coppice production to generate bioenergy feedstocks at frequent intervals. Allometric equations are re-quired to predict aboveground biomass (AGB) of coppiced individuals with minimal field measurements. Likewise, remote sensing tools like LiDAR (light detection and ranging) can be used if models are available to predict AGB from point cloud data. Therefore, this study sought to develop equations to predict dry woody AGB from field measurements and LiDAR data from coppiced poplar field trials containing eastern cottonwood ( P. del-toides ) and hybrid poplar taxa. We found that taxa-specific allometric models containing the summed basal area of the three largest stems in the coppice provided the best predictive model, with stem height and stem count failing to provide additional explanatory power. The best predictive LiDAR-based model was independent of taxa but had slightly lower adjusted R 2 and higher RMSE than the allometric model. It contained four parameters including crown volume, leaf area index, variance of height returns, and the top point density (i.e., density metric 9 or the proportion of points in the highest point interval when the point cloud is evenly divided into ten vertical intervals). In total, these models can be used to quickly and efficiently estimate dry woody AGB of Populus coppice systems for bioenergy feedstock production.

AGB↗
DOE OSTI2022

Model-Based Reconstruction for Collimated Beam Ultrasound Systems

Collimated beam ultrasound systems are a novel technology for imaging inside multi-layered structures such as geothermal wells. Such systems include a transmitter and multiple receivers to capture reflected signals. Common algorithms for ultrasound reconstruction use delay-and-sum (DAS) approaches; these have low computational complexity but produce inaccurate images in the presence of complex structures and specialized geometries such as collimated beams.In this paper, we propose a multi-layer, ultrasonic, model-based iterative reconstruction algorithm designed for collimated beam systems. We introduce a physics-based forward model to accurately ac-count for the propagation of a collimated ultrasonic beam in multi-layer media and describe an efficient implementation using binary search. We model direct arrival signals, detector noise, and a spatially varying image prior, then cast the reconstruction as a maximum a posteriori estimation problem. Using simulated and experimental data we obtain significantly fewer artifacts relative to DAS while running in near real time using commodity compute resources.

Alanazi, Abdulrahman M.↗
DOE OSTI2024

Tensor decompositions for count data that leverage stochastic and deterministic optimization

There is growing interest to extend low-rank matrix decompositions to multi-way arrays, or tensors. One fundamental low-rank tensor decomposition is the canonical polyadic decomposition (CPD). The challenge of fitting a low-rank, nonnegative CPD model to Poisson-distributed count data is of particular interest. Several popular algorithms use local search methods to approximate the maximum likelihood estimator (MLE) of the Poisson CPD model. Here, this work presents two new algorithms that extend state-of-the-art local methods for Poisson CPD. Hybrid GCP-CPAPR combines Generalized Canonical Decomposition (GCP) with stochastic optimization and CP Alternating Poisson Regression (CPAPR), a deterministic algorithm, to increase the probability of converging to the MLE over either method used alone. Restarted CPAPR with SVDrop uses a heuristic based on the singular values of the CPD model unfoldings to identify convergence toward optimizers that are not the MLE and restarts within the feasible domain of the optimization problem, thus reducing overall computational cost when using a multi-start strategy. We provide empirical evidence that indicates our approaches outperform existing methods with respect to converging to the Poisson CPD MLE.

CPAPR↗
DOE OSTI2021

Sizing Energy Storage System for Energy Arbitrage in Extreme Fast Charging Station

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. The proposed model is formulated and solved using AIMMS. Finally, a thorough sensitivity analysis is performed to offer insights into how different input parameters impact the ESS sizing and savings from the energy arbitrage perspective.

25 ENERGY STORAGE↗
DOE OSTI2016

Revisiting the NVSS number count dipole

We present a realistic modeling of the dipole component of the projected sky distribution of NVSS radio galaxies. The modeling relies on mock catalogs generated within the context of ΛCDM cosmology, in the linear regime of structure formation. After removing the contribution from the solar motion, the mocks show that the remaining observed signal is mostly (70%) due to structures within z ∼< 0.1. The amplitude of the model signal depends on the bias factor b of the NVSS mock galaxies. For sources with flux density, S > 15 mJy, the bias recipe inferred from higher order moments is consistent with the observed dipole signal at 2.12σ. Flux thresholds above 20 mJy yield a disagreement close to the 3σ level. A constant high bias, b = 3 is needed to mitigate the tension to the ∼ 2.3σ level.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Methane Exhaust Measurements at Gathering Compressor Stations in the United States

Unburned methane entrained in exhaust from natural gas-fired compressor engines (“combustion slip”) can account for a substantial portion of station-level methane emissions. A novel in-stack, tracer gas method was coupled with Fourier transform infrared (FTIR) species measurements to quantify combustion slip from natural gas compressor engines at 67 gathering and boosting stations owned or managed by nine “study partner” operators in 11 U.S. states. The mean methane emission rate from 63 four-stroke, lean-burn (4SLB) compressor engines was 5.62 kg/h (95% CI = 5.15–6.17 kg/h) and ranged from 0.3 to 12.6 kg/h. The mean methane emission rate from 39 fourstroke, rich-burn (4SRB) compressor engines was 0.40 kg/h (95% CI = 0.37– 0.42 kg/h) and ranged from 0.01 to 4.5 kg/h. Study results for 4SLB engines were lower than both the U.S. EPA compilation of air pollutant emission factors (AP-42) and Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) by 8 and 9%, respectively. Study results for 4SRB engines were 43% of the AP-42 emission factor and 8% of the GHGI emission factor, the latter of which does not distinguish between engine types. Total annual combustion slip from the U.S. natural gas gathering and boosting sector was modeled using measured emission rates and compressor unit counts from the U.S. EPA Greenhouse Gas Reporting Program. Modeled results [328 Gg/y (95% CI = 235–436 Gg/y) of unburned methane] would account for 24% (95% CI = 17–31%) of the 1391 Gg of methane emissions for “Gathering and Boosting Stations”, or 6% of the net emissions for “Natural Gas Systems” (5598 Gg) as reported in the 2020 U.S. EPA GHGI. In conclusion, gathering and boosting combustion slip emissions reported in the 2020 GHGI (374 Gg) fall within the uncertainty of this model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Neutrons in MINERvA and the Antineutrino Multi-Neutron Production Cross Section

Neutrinos are among a handful of particles in the Standard Model of particle physics whose properties have not yet been fully measured. Neutrino oscillations, discovered in the late 1990s, still have yet to be fully characterized. Early evidence suggests that neutrinos and antineutrinos may undergo neutrino oscillations differently. So, multiple collaborations are building and operating kTon-scale particle detectors to try to measure this CP violation in the neutrino sector of the Standard Model. Measuring neutrino and antineutrino energies is essential to characterizing oscillation phenomena. But neutrons interfere with (anti)neutrino energy measurements because they are hard to detect in (anti)neutrino detectors. Furthermore, there are very few measurements of neutrons produced by (anti)neutrinos in the energy range of interest to accelerator-based oscillation experiments. The MINERvA collaboration initially tried to fill this gap by measuring the rate of neutron-induced activity i n plastic. The data deviated significantly from leading model predictions, but it could not be determined which models needed to be tuned. MINERvA’s first neutron counting result also cannot be compared to future models because it was not suitable for unsmearing. This thesis first expands upon MINERvA’s first foray into neutron detection at higher antineutrino energy. Neutron detection efficiency is enhanced by advances in analysis algorithms. Then, an unsmeared cross section for producing two or more neutrons is measured. Existing antineutrino interaction models again over-predict the rate of neutron production by antineutrinos. Preliminary neutron production rate measurements in MINERvA’s iron and lead targets suggest that models are also over-predicting neutron production in heavier nuclei.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Effect of photon counting shot noise on total internal reflection microscopy

Total internal reflection microscopy (TIRM) measures changes in the distance between a colloidal particle and a transparent substrate by measuring the scattering intensity of the particle illuminated by an evanescent wave. From the distribution of the recorded separation distances, the height-dependent effective potential φ(z) between the colloidal particle and the substrate can be measured. In this work, we show that spatial resolution with which TIRM can measure φ(z) is limited by the photon counting statistics of the scattered laser light. Here, we develop a model to evaluate the effect of photon counting statistics on different potential profiles using Brownian dynamics simulations and experiments. Our results show that the effect of photon counting statistics depends on spatial gradients ∂φ/∂z of the potential, with the result that sharp features tend to be significantly blurred. We further establish the critical role of photon counting statistics and the intensity integration time τ in TIRM measurements, which is a trade-off between narrowing the width of the photon counting distribution and capturing the instantaneous position of the probe particle.

47 OTHER INSTRUMENTATION↗