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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Optimized dark matter searches in deep observations of Segue 1 with MAGIC

We present the results of stereoscopic observations of the satellite galaxy Segue 1 with the MAGIC Telescopes, carried out between 2011 and 2013. With almost 160 hours of good-quality data, this is the deepest observational campaign on any dwarf galaxy performed so far in the very high energy range of the electromagnetic spectrum. We search this large data sample for signals of dark matter particles in the mass range between 100 GeV and 20 TeV. For this we use the full likelihood analysis method, which provides optimal sensitivity to characteristic gamma-ray spectral features, like those expected from dark matter annihilation or decay. In particular, we focus our search on gamma-rays produced from different final state Standard Model particles, annihilation with internal bremsstrahlung, monochromatic lines and box-shaped signals. Our results represent the most stringent constraints to the annihilation cross-section or decay lifetime obtained from observations of satellite galaxies, for masses above few hundred GeV. In particular, our strongest limit (95% confidence level) corresponds to a ∼500 GeV dark matter particle annihilating into τ{sup +}τ{sup −}, and is of order <σ{sub ann}v>≃ 1.2×10{sup −24} cm{sup 3} s{sup −1} — a factor ∼40 above the <σ{sub ann}v>≃ thermal value.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

An inexact regularized Newton framework with a worst-case iteration complexity of $ {\mathscr O}(\varepsilon^{-3/2}) $ for nonconvex optimization

Abstract An algorithm for solving smooth nonconvex optimization problems is proposed that, in the worst-case, takes ${\mathscr O}(\varepsilon ^{-3/2})$ iterations to drive the norm of the gradient of the objective function below a prescribed positive real number $\varepsilon $ and can take ${\mathscr O}(\varepsilon ^{-3})$ iterations to drive the leftmost eigenvalue of the Hessian of the objective above $-\varepsilon $. The proposed algorithm is a general framework that covers a wide range of techniques including quadratically and cubically regularized Newton methods, such as the Adaptive Regularization using Cubics (arc) method and the recently proposed Trust-Region Algorithm with Contractions and Expansions (trace). The generality of our method is achieved through the introduction of generic conditions that each trial step is required to satisfy, which in particular allows for inexact regularized Newton steps to be used. These conditions center around a new subproblem that can be approximately solved to obtain trial steps that satisfy the conditions. A new instance of the framework, distinct from arc and trace, is described that may be viewed as a hybrid between quadratically and cubically regularized Newton methods. Numerical results demonstrate that our hybrid algorithm outperforms a cubically regularized Newton method.

Mathematics↗
DOE OSTI2020

Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or an investigation for maximizing their effectiveness. We carry out a comparison between several common machine learning methods for galaxy classification [Convolutional Neural Network (CNN), K-nearest neighbour, logistic regression, Support Vector Machine, Random Forest, and Neural Networks] by using Dark Energy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project (GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of ~2800 galaxies with visual classification from GZ1, we reach an accuracy of ~0.99 for the morphological classification of ellipticals and spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both ellipticals and spirals. We confirm that ~2.5 percent galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Enhancing strontium clock atom interferometry using quantum optimal control

Strontium clock atom interferometry is a promising new technology, with multiple experiments under development around the world to explore its potential for dark matter and gravitational wave detection. In these detectors, large momentum transfer using sequences of many laser pulses is necessary, and thus high-fidelity pulses are important since small errors become magnified. Quantum optimal control (QOC) is a framework for developing control pulse waveforms that achieve high fidelity and are robust against experimental imperfections. Resonant single-photon transitions using the narrow clock transition of strontium involve significantly different quantum dynamics than more established atom interferometry methods based on far-detuned two-photon Raman or Bragg transitions, which leads to new opportunities and challenges when applying QOC. Here, we study in simulation QOC pulses for strontium clock interferometry and demonstrate their advantage over basic square pulses (primitive pulses) and composite pulses in terms of robustness against multiple noise channels. In conclusion, this could improve the scale of large momentum transfer in Sr clock interferometers, paving the way to achieving these scientific goals.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Baseline Optimization for the Measurement of CP Violation, Mass Hierarchy, and $\theta_{23}$ Octant in a Long-Baseline Neutrino Oscillation Experiment

Next-generation long-baseline electron neutrino appearance experiments will seek to discover C P violation, determine the mass hierarchy and resolve the θ 23 octant. In light of the recent precision measurements of θ 13 , we consider the sensitivity of these measurements in a study to determine the optimal baseline, including practical considerations regarding beam and detector performance. We conclude that a detector at a baseline of at least 1000 km in a wide-band muon neutrino beam is the optimal configuration.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Use of radial symmetry for the calculation of cylindrical absorption coefficients and optimal capillary loadings

The problem of numerically evaluating absorption correction factors for cylindrical samples has been revisited using a treatment that fully takes advantage of the sample symmetry. It is shown that the path lengths for all points within the sample at all possible diffraction angles can be trivially determined once the angle-dependent distance distribution for a single line of points is calculated. This provides advantages in both computational efficiency and in gaining an intuitive understanding of the effects of absorption on diffraction data. A matrix of absorption coefficients calculated for µR products between 0 and 20 for diffraction angles θ D of 0° to 90° were used to examine the influence of (1) capillary diameter and of (2) sample density on the overall scattered intensity as a function of diffraction angle, where µ is the linear absorption coefficient for the sample and R is the capillary radius. Based on this analysis, the optimal sample loading for a capillary experiment to maximize diffraction at angles of 0 – 50° is in general expected to be achieved when the maximum radius capillary compatible with the beam is used, and when the sample density is adjusted to be 3/(4µR) of its original density.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Energy optimization of a regular macromolecular crystallography beamline for ultra-high-resolution crystallography

A practical method for operating existing undulator synchrotron beamlines at photon energies considerably higher than their standard operating range is described and applied at beamline 19-ID of the Structural Biology Center at the Advanced Photon Source enabling operation at 30 keV. Adjustments to the undulator spectrum were critical to enhance the 30 keV flux while reducing the lower- and higher-energy harmonic contamination. A Pd-coated mirror and Al attenuators acted as effective low- and high-bandpass filters. The resulting flux at 30 keV, although significantly lower than with X-ray optics designed and optimized for this energy, allowed for accurate data collection on crystals of the small protein crambin to 0.38 Å resolution.

Rosenbaum, Gerd↗
DOE OSTI2023

Optimization and Comparison of Modern Offshore Wind Turbine Generators Using GeneratorSE 2.0

As the offshore wind industry keeps growing at a rapid pace, developers are bracing themselves for a huge demand in critical rare earth metals which will threaten an already vulnerable supply chain. The wind energy industry is addressing this problem by investing in modern generator technologies that employ magnets with reduced rare earth content and high-field magnets enabled by rare-earth-free superconductors. In this paper we introduce the National Renewable Energy Laboratory's newly advanced GeneratorSE 2.0, which is a design and optimization tool that was developed to investigate the feasibility of such modern generators. Two direct-drive generator topologies with different magnet materials and mounting arrangements are investigated: an outer-rotor, V-shaped interior permanent magnet generator, and an inner-rotor normally conducting armature, paired with a low-temperature superconducting field with race-track coils. These technologies were evaluated for a range of power ratings between 15 and 25 MW, which represent the next generation of offshore wind turbines for both fixed-bottom and floating applications. The analyses indicate a new trend favoring the low-temperature superconducting technology for the direct-drive system.

direct-drive generators↗
DOE OSTI2023

The Empirical Effect of Fleet Optimization on Synchronization and Rebound Effects in Heat Pump Water Heaters

Demand response is a growing concept in light of the internet of things and an increasing need for grid flexibility. Water heaters are one of the preferred devices for providing demand response for grid services and peak management due to their capability to store energy. The efficient use of water heaters for demand response requires consideration of the associated load effects such as synchronization of device schedules and rebound effect. These effects present a significant challenge. Despite the importance of the mentioned effects for water heater queuing and scheduling, there has been no effort to quantify and empirically validate their impact. This study attempts to address this gap by offering two methods - Ward clustering and Euclidean K-means - to evaluate the extent of synchronization in a fleet of 42 water heaters in Atlanta, GA. Using the aforementioned methods on the measured data, we find evidence of convergence of water heater loads as a result of optimization compared to an idle period and analyzed their impact.

demand response↗
DOE OSTI2014

SSD-optimized workload placement with adaptive learning and classification in HPC environments

In recent years, non-volatile memory devices such as SSD drives have emerged as a viable storage solution due to their increasing capacity and decreasing cost. Due to the unique capability and capacity requirements in large scale HPC (High Performance Computing) storage environment, a hybrid configuration (SSD and HDD) may represent one of the most available and balanced solutions considering the cost and performance. Under this setting, effective data placement as well as movement with controlled overhead become a pressing challenge. In this paper, we propose an integrated object placement and movement framework and adaptive learning algorithms to address these issues. Specifically, we present a method that shuffle data objects across storage tiers to optimize the data access performance. The method also integrates an adaptive learning algorithm where realtime classification is employed to predict the popularity of data object accesses, so that they can be placed on, or migrate between SSD or HDD drives in the most efficient manner. We discuss preliminary results based on this approach using a simulator we developed to show that the proposed methods can dynamically adapt storage placements and access pattern as workloads evolve to achieve the best system level performance such as throughput.

Wan, Lipeng↗
DOE OSTI2017

Capturing provenance as a diagnostic tool for workflow performance evaluation and optimization

In extreme-scale computing environments such as the DOE Leadership Computing Facilities scientific workflows are routinely used to coordinate software processes for the execution of complex, computational applications that perform in-silico experiments. Monitoring the performance of workflows without also simultaneously tracking provenance is not sufficient to understand variations between runs, configurations, versions of a code, and between changes in an implemented stack, and systems, i.e. the variability of performance metrics data in their historical context. We take a provenance-based approach and demonstrate that provenance is useful as a tool for evaluating and optimizing workflow performance in extreme-scale HPC environments. We present Chimbuko, a framework for the analysis and visualization of the provenance of performance. Chimbuko implements a method for the evaluation of workflow performance from multiple components that enables the exploration of performance metrics data at scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Test of Optimized 120-mm LARP Nb 3 Sn Quadrupole Coil Using Magnetic Mirror Structure

The U.S. Large Hadron Collider accelerator research program is developing a new generation of large-aperture high-field quadrupoles based on Nb 3 Sn conductor for the high-luminosity upgrade of the Large Hadron Collider. Tests of the first series of 120-mm-aperture high-gradient quadrupole (HQ) coils revealed the necessity for further optimization of the coil design and fabrication process. Modifications in coil design were gradually implemented in two HQ coils previously tested at Fermi National Accelerator Laboratory using a magnetic mirror structure (HQM01 and HQM02). This paper describes the construction and test of an HQ mirror model with a coil of optimized design and with an interlayer resistive core in the conductor. The cable for this coil was made of a smaller diameter strand, providing more room for coil expansion during reaction. The 0.8-mm strand, used in all previous HQ coils, was replaced with a 0.778-mm Nb 3 Sn strand of RRP 108/127 subelement design. The coil was instrumented with voltage taps, heaters, and strain gauges to monitor mechanical and thermal properties and quench performance of the coil

43 PARTICLE ACCELERATORS↗
DOE OSTI2015

Solar Power Ramp Events Detection Using an Optimized Swinging Door Algorithm: Preprint

Solar power ramp events (SPREs) are those that significantly influence the integration of solar power on non-clear days and threaten the reliable and economic operation of power systems. Accurately extracting solar power ramps becomes more important with increasing levels of solar power penetrations in power systems. In this paper, we develop an optimized swinging door algorithm (OpSDA) to detection. First, the swinging door algorithm (SDA) is utilized to segregate measured solar power generation into consecutive segments in a piecewise linear fashion. Then we use a dynamic programming approach to combine adjacent segments into significant ramps when the decision thresholds are met. In addition, the expected SPREs occurring in clear-sky solar power conditions are removed. Measured solar power data from Tucson Electric Power is used to assess the performance of the proposed methodology. OpSDA is compared to two other ramp detection methods: the SDA and the L1-Ramp Detect with Sliding Window (L1-SW) method. The statistical results show the validity and effectiveness of the proposed method. OpSDA can significantly improve the performance of the SDA, and it can perform as well as or better than L1-SW with substantially less computation time.

14 SOLAR ENERGY↗
DOE OSTI2024

Readout optimization of multi-amplifier sensing charge-coupled devices for single-quantum measurement

The non-destructive readout capability of the Skipper Charge Coupled Device (CCD) has been demonstrated to reduce the noise limitation of conventional silicon devices to levels that allow single-photon or single-electron counting. The noise reduction is achieved by taking multiple measurements of the charge in each pixel. These multiple measurements come at the cost of extra readout time, which has been a limitation for the broader adoption of this technology in particle physics, quantum imaging, and astronomy applications. This work presents recent results of a novel sensor architecture that uses multiple non-destructive floating-gate amplifiers in series to achieve sub-electron readout noise in a thick, fully-depleted silicon detector to overcome the readout time overhead of the Skipper-CCD. This sensor is called the Multiple-Amplifier Sensing Charge-Coupled Device (MAS-CCD) can perform multiple independent charge measurements with each amplifier, and the measurements from multiple amplifiers can be combined to further reduce the readout noise. We will show results obtained for sensors with 8 and 16 amplifiers per readout stage in new readout operations modes to optimize its readout speed. The noise reduction capability of the new techniques will be demonstrated in terms of its ability to reduce the noise by combining the information from the different amplifiers, and to resolve signals in the order of a single photon per pixel. The first readout operation explored here avoids the extra readout time needed in the MAS-CCD to read a line of the sensor associated with the extra extent of the serial register. The second technique explore the capability of the MAS-CCD device to perform a region of interest readout increasing the number of multiple samples per amplifier in a targeted region of the active area of the device.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗