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An energy analyzer has been constructed that is appropriate for measuring the energy profile and charge state distribution of the exhaust plume of a xenon-driven Hall thruster.
This paper describes the kernel of a distributed operating system called ADAPT. The system runs on top of existing single host operating systems that are networked together. It's purpose is to transform this network of individual systems into a single system that will be easier for application programmers to use. This single system need not be monolithic; ADAPT facilitates the construction of both integrated and modular distributed systems.
Simultaneous broadband spectral and temporal studies of blazars are an important tool for investigating active galactic nuclei (AGN) jet physics. Aims. Here, we study the spectral evolution between quiescent and flaring periods of 22 radio-loud AGN through multiepoch, quasi-simultaneous broadband spectra. For many of these sources these are the first broadband studies. We also use a Bayesian block analysis of Fermi/LAT light curves to determine time ranges of constant flux for constructing quasi-simultaneous spectral energy distributions (SEDs). The shapes of the resulting 81 SEDs are described by two logarithmic parabolas and a blackbody spectrum where needed. The peak frequencies and luminosities agree well with the blazar sequence for low states with higher luminosity implying lower peak frequencies. This is not true for sources in high states. The γ-ray photon index in Fermi/LAT correlates with the synchrotron peak frequency in low and intermediate states. No correlation is present in high states. The black hole mass cannot be determined from the SEDs. Surprisingly, the thermal excess often found in FSRQs at optical/UV wavelengths can be described by blackbody emission and not an accretion disk spectrum. The so-called harder-when-brighter trend, typically seen in X-ray spectra of flaring blazars, is visible in the blazar sequence. Furthermore, our results for low and intermediate states, as well as the Compton dominance, are in agreement with previous results. Black hole mass estimates using recently published parameters are in agreement with some of the more direct measurements. For two sources, estimates disagree by more than four orders of magnitude, possibly owing to boosting effects. The shapes of the thermal excess seen predominantly in flat spectrum radio quasars are inconsistent with a direct accretion disk origin.
Distributed memory architectures offer high levels of performance and flexibility, but have proven awkard to program. Current languages for nonshared memory architectures provide a relatively low level programming environment, and are poorly suited to modular programming, and to the construction of libraries. A set of language primitives designed to allow the specification of parallel numerical algorithms at a higher level is described. Tensor product array computations are focused on along with a simple but important class of numerical algorithms. The problem of programming 1-D kernal routines is focused on first, such as parallel tridiagonal solvers, and then how such parallel kernels can be combined to form parallel tensor product algorithms is examined.
A new diagnostic for the quantification of Sauter Mean Diameter (SMD) in high-pressure fuel sprays has been recently developed using combined optical and x-ray measurements at the Georgia Institute of Technology and Argonne National Laboratory, respectively. This diagnostic utilizes liquid scattering extinction measurements from diffuse back-illumination imaging, conducted at Georgia Tech, and liquid absorption measurements from x-ray radiography, conducted at Argonne’s Advanced Photon Source. The new diagnostic, entitled the Scattering Absorption Measurement Ratio (SAMR), quantifies two-dimensional distributions of path integrated SMD, enabling construction of the spatial history of drop size development within practical fuel sprays. This technique offers unique benefits over conventional drop-sizing methods in that it can be more robust in optically dense regions of the spray, while also providing high spatial and temporal resolution of the corresponding droplet field. The methodology for quantification of SMD distributions using the SAMR technique has been previously introduced and demonstrated in diesel sprays using the Engine Combustion Network Spray D injector, however a more detailed treatment of measurement uncertainties has been needed. In the current work, we present a summary of the various sources of measurement uncertainty in the SAMR diagnostic, like those due to the experimental setup, data processing methods, and theoretical assumptions, and assess how these sources of uncertainty affect the quantified SMD. The spatially-resolved SMD measurements that result from the SAMR diagnostic will be especially valuable to the engine modeling community for the quantitative validation of spray submodels in engine CFD codes. Careful evaluation and quantification of measurement uncertainties is important to support accurate model validation and to ensure the development of more predictive spray models.
Here, we present a pseudoreversible normalizing flow method for efficiently generating samples of the state of a stochastic differential equation (SDE) with various initial distributions. The primary objective is to construct an accurate and efficient sampler that can be used as a surrogate model for computationally expensive numerical integration of SDEs, such as those employed in particle simulation. After training, the normalizing flow model can directly generate samples of the SDE’s final state without simulating trajectories. The existing normalizing flow model for SDEs depends on the initial distribution, meaning the model needs to be retrained when the initial distribution changes. The main novelty of our normalizing flow model is that it can learn the conditional distribution of the state, i.e., the distribution of the final state conditional on any initial state, such that the model only needs to be trained once and the trained model can be used to handle various initial distributions. This feature can provide a significant computational saving in studies of how the final state varies with the initial distribution. Additionally, we propose to use a pseudoreversible network architecture to define the normalizing flow model, which has sufficient expressive power and training efficiency for a variety of SDEs in science and engineering, e.g., in particle physics. We provide a rigorous convergence analysis of the pseudoreversible normalizing flow model to the target probability density function in the Kullback–Leibler divergence metric. Numerical experiments are provided to demonstrate the effectiveness of the proposed normalizing flow model.
A control problem for stochastically forced nonlinear continuous-time systems is considered. We propose a method for construction of the regulator that provides a preassigned probabilistic distribution of random states in stochastic equilibrium. Geometric criteria of the controllability are obtained. Constructive technique for the specification of attainability sets is suggested.
In this study, six deep convective systems (DCSs) with a total of 5589 five-second samples and a range of temperatures from -41°C to 0°C during the Midlatitude Continental Convective Clouds Experiment (MC3E) were selected to investigate the ice cloud microphysical properties of DCSs over the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site. The ice cloud measurements of the DCS cases were made by the University of North Dakota Citation II research aircraft, and the ice cloud properties were derived through the following processes. First, the instances of supercooled liquid water in the ice-dominated cloud layers of DCSs have been eliminated using multisensor detection, including the Rosemount Icing Detector, King and Cloud Droplet Probes, as well as 2DC and Cloud Imaging Probe images. Then the Nevzorov-measured ice water contents (IWCs) at maximum diameter D max < 4000 µm are used as the best estimation to determine a new mass-dimensional relationship. Finally, the newly derived mass-dimensional relationship (a = 0.00365, b = 2.1) has been applied to a full spectrum of particle size distributions (PSDs, 120–30,000 µm) constructed from both 2DC and High-Volume Precipitation Spectrometer measurements to calculate the best-estimated IWCs of DCSs during MC3E. The averages of the total number concentrations (N t ), median mass diameter (D m ), maximum diameter (D max ), and IWC from six selected cases are 0.035 cm -3 , 1666 µm, 8841 µm, and 0.45 g m -3 , respectively. The gamma-type-size distributions are then generated matching the observed PSDs (120–30,000 µm), and the fitted gamma parameters are compared with the observed PSDs through multimoment assessments including first moment (D m ), third moment (IWC), and sixth moment (equivalent radar reflectivity, Z e ). Lastly, for application of observed PSDs to the remote sensing community, a series of empirical relationships between fitted parameters and Z e values has been derived, and the bullet rosette ice crystal backscattering relationship has been suggested for ground-based remote sensing.
Quantitative assessment of gas-particle partitioning of individual components within complex atmospheric organic aerosols (OA) mixtures is critical for predicting and comprehending the formation and evolution of OA particles in the atmosphere. This investigation leverages previously documented data obtained through a temperature programmed desorption - direct analysis in real time – high resolution mass spectrometry (TPD-DART-HRMS) platform. This methodology facilitates the bottom-up construction of volatility basis set (VBS) distributions for constituents found in three biogenic secondary organic aerosol (SOA) mixtures produced through the ozonolysis of a-pinene, limonene, and ocimene. The apparent enthalpies (ΔH*, kJ mol -1 ) and saturated vapor mass concentrations (C T *, µg∙m -3 ) of individual SOA components, determined as a function of temperature (T, K), facilitated an assessment of changes in VBS distributions and gas-particle partitioning with respect to T and atmospheric total organic mass loadings (tOM, µg∙m -3 ). Further, the VBS distributions reveal distinct differences in volatilities among monomers, dimers, and trimers, enabling their categorization into separate volatility bins. At the ambient temperature of T = 298 K, only monomers efficiently partition between gas and particle phases across a broad range of atmospherically relevant total organic mass loadings (tOM) values of 1–100 µg∙m -3 . Partitioning of dimers and trimers becomes notable only at T > 360 K and T > 420 K, respectively. The viscosity of SOA mixtures is assessed using a bottom-up calculation approach, incorporating the input of elemental formulas, ΔH*, C T *, and particle-phase mass fractions of the SOA components. Through this approach, we are able to accurately estimate the variations in SOA viscosity that result from the evaporation of its components. These variations are, in turn, influenced by atmospherically relevant changes in tOM and T. Comparison of the calculated SOA viscosity and diffusivity values with literature reported experimental results shows close agreement, thereby validating the employed calculation approach. These findings underscore the significant potential for TPD-DART-HRMS measurements in enabling the untargeted analysis of organic molecules within OA mixtures. This approach facilitates quantitative assessment of their gas-particle partitioning and allows for the estimation of their viscosity and condensed-phase diffusion, thereby contributing valuable insights to atmospheric models.
Economic competitiveness and national security depend increasingly on the insightful analysis of large data sets. The diversity of real-world data sources and analytic workflows impose challenging hardware and software requirements for parallel graph platforms. The irregular nature of graph methods is not supported well by the deep memory hierarchies of conventional distributed systems, requiring new processor and runtime system designs to tolerate memory and synchronization latencies. Moreover, the efficiency of relational table operations and matrix computations are not attainable when data is stored in common graph data structures. In this paper, we present HAGGLE, a high-performance, scalable data analytics platform. The platform’s hybrid data model supports a variety of distributed, thread-safe data structures, parallel programming constructs, and persistent and streaming data. An abstract runtime layer enables us to map the stack to conventional, distributed computer systems with accelerators. The runtime uses multithreading, active messages, and data aggregation to hide memory and synchronization latencies on large-scale systems.
During an airborne multi-sensor remote sensing experiment at the Virginia Coast Reserve (VCR) Long Term Ecological Research (LTER) site in June 2011 (VCR '11), first measurements were taken with the new NRL Goniometer for Outdoor Portable Hyperspectral Earth Reflectance (GOPHER). GOPHER measures the angular distribution of hyperspectral reflectance. GOPHER was constructed for NRL by Spectra Vista Corporation (SVC) and the University of Lethbridge through a capital equipment purchase in 2010. The GOPHER spectrometer is an SVC HR -1024, which measures hyperspectral reflectance over the range from 350 -2500 nm, the visible, near infrared, and short-wave infrared. During measurements, the spectrometer travels along a zenith quarter -arc track that can rotate in azimuth, allowing for measurement of the bi-directional reflectance distribution function (BRDF) over the whole hemisphere. The zenith arc has a radius of approximately 2m, and the spectrometer scan pattern can be programmed on the fly during calibration and validation efforts. The spectrometer and zenith arc assembly can be raised and lowered along a mast to allow for measurement of uneven terrain or vegetation canopies of moderate height. Hydraulics on the chassis allow for leveling of the instrument in the field. At just over 400 lbs, GOPHER is a field portable instrument and can be transformed into a compact trailer assembly for movement over long distances in the field.
Change detection from satellite sensor vegetation indices (VIs) presents an opportunity to monitor trends and disturbances at the regional scale for southern California's Mojave and Lower Colorado Deserts. Renewable energy sites are being constructed in this region on public lands under the Bureau of Land Management (BLM). We have developed a framework for VI change detection over the past two decades, with initial focus on three sites, Joshua Tree National Park, Mojave National Preserve, and a proximal group of Development Focus Areas (DFAs), for comparison between protected and development-targeted lands. Three Terra MODIS VIs (normalized difference [NDVI], enhanced [EVI], soil-adjusted [SAVI]) were evaluated in the Breaks for Additive Season and Trend (BFAST) setting for the regional MODIS 250-m resolution grid to estimate significant time series shifts (breakpoints) from February 2000 to May 2018. All three VIs tended to detect the maximum number of breakpoints at a grid location, but cross-correlations with precipitation and comparison with timing of wildfire burns near the study sites for breakpoint density (proportion of area with a breakpoint) showed that NDVI had the strongest response to these major disturbances, supporting its use for subsequent analysis. Time series of NDVI breakpoint change densities for individual solar energy sites did not have a consistent vegetation response following construction. Bootstrapping showed that the DFAs had significantly larger kurtosis and variance in the positive NDVI breakpoint distribution than did the protected sites, but there was no significant difference in the negative distribution for all three sites. The inconsistent post-construction NDVI signal and the large number of breakpoints overall suggested that the largest changes in vegetation cover density were tied to seasonal precipitation amounts. The distributional results indicated that existing site-specific conditions were the main control on VI responses, given the history of human disturbances in the DFAs. Although the results do not support persistent VI disturbances resulting from recent solar energy development, continued monitoring and examination of other ecological variables and surface temperatures will be vital to the long-term protection of this desert environment.
Purpose: Past efforts to improve the therapeutic ratio have focused on a spatial approach where highly conformal radiation dose is given to tumors while minimizing dose to normal tissues, e.g., IMRT, VMAT, and IGRT. However, the fractionation schedule, i.e., a temporal approach to radiotherapy, has been largely overlooked so far in maximizing the therapeutic ratio. We establish a rigorous mathematical spatio-temporal approach to systematically investigate the feasibility and potential benefits of simultaneously optimizing radiation dose distribution in space and time. Methods: Stochastic control formalism is constructed to maximize the average tumor BED by choosing an optimal radiation dose distribution for an optimal number of fractions subject to normal tissue BED constraints. Three separate simulations are run on two groups of phantom cases; 5 cases with prostate cancer and 5 cases with head-and-neck cancer. (1) Conventional IMRT with 70Gy/35fx for head-and-neck, and 81Gy/45fx for prostate, (2) IMRT is done independently from the fractionation schedule optimization (S-model), (3) integrated spatio-temporal approach (I-model) where radiation intensities are simultaneously optimized for the first time ever in space and time. Final tumor BEDs from the three trials are compared in prostate and head-and-neck cases. Results: Numerical simulations show that final tumor BED from I-model is 20–90% larger than conventional IMRT, and 20-50% larger than S-model for head-and-neck cancer with α/β=10 and Tdouble=2–50 days. Final tumor BED from I-model is also 90–140% larger than conventional IMRT, and 20–30% larger than S-model for prostate cancer with α/β=2 and Tdouble=5–80 days. Conclusion: Our spatio-temporal optimization of radiotherapy allows an expansion of search space for the optimal treatment plans to include the temporal distribution of radiation dose in addition to the spatial distribution. Such spatio-temporal approach shows great potential to improve the therapeutic ratio, particularly with fast growing, aggressive tumors with short doubling time and/or low α/β.
Statistical analyses are compared for two published hot spot data sets, one minimal set of 42 and another larger set of 117, using three different approaches. First, the earths surface is divided into 16 equal-area fractions and the observed distribution of hot spots among them is analyzed using chi-square tests. Second, cumulative distributions about the principal axes of the hot spot inertia tensor are used to describe hot spot distribution. Finally, a hot spot density function is constructed for each of the two hot spot data sets. The methods all indicate that hot spots have a nonuniform distribution, even when statistical fluctuations are considered. To the first order, hot spots are concentrated on one half of of the earth's surface area; within that portion, the distribution is consistent with a uniform distribution. The observed hot spot densities for neither data set are explained solely by plate speed.
We propose a method to measure the ellipticities of dark matter halos using the lens-shear-shear 3-point correlation function. This method is immune to effects of galaxy-halo misalignments that can potentially limit 2-point galaxy-galaxy lensing measurements of halo anisotropy. Using a simple model for the projected mass distributions of dark matter halos, we construct an ellipticity estimator that sums over all possible triangular configurations of the 3-point function. By applying our estimator to halos from N-body simulations, we find that systematic errors in the recovered ellipticity will be at the ∼< 5% fractional level. We estimate that future imaging surveys like LSST will have sufficient statistics to detect halo ellipticities using 3-point lensing.
A laminar vortex ring with swirl, which has the meridional velocity component inside the vortex core, was experimentally generated by the brief fluid ejection from a rotating outlet. The evolution of the vortex ring was investigated with flow visualizations and particle image velocimetry measurements in order to find the influence of swirling flow in particular upon the transition to turbulence. Immediately after the formation of a vortex ring with swirl, a columnar strong vortex along the symmetric axis is observed in all cases of the present experiment. Then the characteristic fluid discharging from a vortex ring with swirl referred to as “peeling off” appears. The amount of discharging fluid due to the “peeling off” increases with the angular velocity of the rotating outlet. We conjectured that the mechanism generating the “peeling off” is related to the columnar strong vortex by close observations of the spatio-temporal development of the vorticity distribution and the cutting 3D images constructed from the successive cross sections of a vortex ring. While a laminar vortex ring without swirl may develop azimuthal waves around its circumference at some later time and the ring structure subsequently breaks, the swirling flow in a vortex ring core reduces the amplification rate of the azimuthal wavy deformation and preserved its ring structure. Then the traveling distance of a vortex ring can be extended using the swirl flow under certain conditions.
The creation of an entirely soldered ozone electrode component is proposed and implemented for the first time by the authors. Electrode construction with a ribbed plate insert within it is the most perfect heat exchange device from the point of view of effective heat exchange and uniform distribution of liquid flow through its section. Stages are considered for electrode preparation for soldering and a standard heating cycle is proposed for soldering and electrode with eutectic silumin. It is shown that as a result of the soldering thermal cycle metal structure becomes coarse-grained and favorable for subsequent electrochemical formation of a nanostructured anodic oxide coating 50–60 μm thick.
Engineering studies for an International Energy Agency project for the design and construction of a 500 kW solar thermal electric power generation system of the distributed collector system (DCS) type are reviewed. The DCS system design consists of a mixed field of parabolic trough type solar collectors which are used to heat a thermal heat transfer oil. Heated oil is delivered to a thermocline storage tank from which heat is extracted and delivered to a boiler by a second heat transfer loop using the same heat transfer oil. Steam is generated in the boiler, expanded through a steam turbine, and recirculated through a condenser system cooled by a wet cooling tower.