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At least 1,657 records · Page 92

Topical Report on Water Balance Model Development and Initial Application

This topical report summarizes results from developing a generic dynamic water balance tool which can be used by coal-fired power plant operators to evaluate FGD water management strategies. EPRI is using a statistical software model created on the GoldSim platform and data from coal-fired energy plants to determine the fraction of power plant water needs that can be satisfied by electrodialysis reversal treatment and, correspondingly, the discharge volume and/or byproducts that still need to be managed. The generic model is designed to accept a number of easily obtainable process variables and generate probabilities of resultant water characteristics. The model is also constructed as a universal process flow; one that can be adjusted to accommodate most major components of an FGD blowdown handling system. The generic model is dynamic and utilizes user-inputted operational variation in water quality and quantity to best provide a probabilistic representation of potential performance outcomes. In order to account for complexities of water composition and treatment, a separate chemical modeling software is used to evaluate water chemistry and unit operation performance. The thermodynamic modeling software, OLI Studio, is employed to convert ion data from laboratory analyses into balanced molecular concentrations that are classified as dissolved and suspended solids. The dynamic water model is designed to import a total of 11 species commonly found in FGD blowdown water as molecular concentrations.Water management unit operations are used in the model and categorized by either physical unit operation blocks or chemical unit operations blocks. As the name implies, the physical water treatment blocks are unit operations that are exclusively physical changes to the system (e.g., separations and volume changes). The chemical water treatment blocks are unit operations where chemical changes occur and require the use of OLI Studio to characterize subsequent streams. Water and material balances from three unique coal-fired power plants were obtained and preliminary modeling on the dynamic water balance tool was performed using the extracted data from these power plants. These three power plants were chosen due to their unique configurations and water profiles that represented a variety of operational changes. Results from using the dynamic tool with the three plant configurations are presented and discussed in the context of the existing tool and planned future capabilities.

01 COAL, LIGNITE, AND PEAT↗

Topical Report on Water Balance Model Development and Initial Application

This topical report summarizes results from developing a generic dynamic water balance tool which can be used by coal-fired power plant operators to evaluate FGD water management strategies. EPRI is using a statistical software model created on the GoldSim platform and data from coal-fired energy plants to determine the fraction of power plant water needs that can be satisfied by advanced treatment technologies and, correspondingly, the discharge volume and/or byproducts that still need to be managed. The initial evaluations presented in this report represent generic scenarios, while the final evaluations will incorporate results from advanced treatment and encapsulation studies conducted during later stages of the project.

01 COAL, LIGNITE, AND PEAT↗

Measurement of the production of (anti)nuclei in p–Pb collisions at s NN = 8.16 TeV

Measurements of (anti)proton, (anti)deuteron, and (anti)3He production in the rapidity range -1< y < 0 as a function of the transverse momentum and event multiplicity in p–Pb collisions at a center-of-mass energy per nucleon–nucleon pair $\sqrt{S_{NN}}$ = 8.16 TeV are presented. The coalescence parameters B 2 and B 3 , measured as a function of the transverse momentum per nucleon and of the mean charged-particle multiplicity density, confirm a smooth evolution from low to high multiplicity across different collision systems and energies. The ratios between (anti)deuteron and (anti) 3 He yields and those of (anti)protons are also reported as a function of the mean charged-particle multiplicity density. A comparison with the predictions of the statistical hadronization and coalescence models for different collision systems and center-of-mass energies favors the coalescence description for the deuteron-to-proton yield ratio with respect to the canonical statistical model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Stochastic simulation of predictive space–time scenarios of wind speed using observations and physical model outputs

We propose a statistical space-time model for predicting atmospheric wind speed based on deterministic numerical weather predictions and historical measurements. We consider a Gaussian multivariate space-time framework that combines multiple sources of past physical model outputs and measurements in order to produce a probabilistic wind speed forecast within the prediction window. We illustrate this strategy on wind speed forecasts during several months in 2012 for a region near the Great Lakes in the United States. The results show that the prediction is improved in the mean-squared sense relative to the numerical forecasts as well as in probabilistic scores. Moreover, the samples are shown to produce realistic wind scenarios based on sample spectra and space-time correlation structure.

54 ENVIRONMENTAL SCIENCES↗

Remote sensing of Earth terrain

Remote sensing of earth terrain is examined. The layered random medium model is used to investigate the fully polarimetric scattering of electromagnetic waves from vegetation. The model is used to interpret the measured data for vegetation fields such as rice, wheat, or soybean over water or soil. Accurate calibration of polarimetric radar systems is essential for the polarimetric remote sensing of earth terrain. A polarimetric calibration algorithm using three arbitrary in-scene reflectors is developed. In the interpretation of active and passive microwave remote sensing data from the earth terrain, the random medium model was shown to be quite successful. A multivariate K-distribution is proposed to model the statistics of fully polarimetric radar returns from earth terrain. In the terrain cover classification using the synthetic aperture radar (SAR) images, the applications of the K-distribution model will provide better performance than the conventional Gaussian classifiers. The layered random medium model is used to study the polarimetric response of sea ice. Supervised and unsupervised classification procedures are also developed and applied to synthetic aperture radar polarimetric images in order to identify their various earth terrain components for more than two classes. These classification procedures were applied to San Francisco Bay and Traverse City SAR images.

Kong, Jin AU↗

Fractal fluctuations in cardiac time series

Human heart rate, controlled by complex feedback mechanisms, is a vital index of systematic circulation. However, it has been shown that beat-to-beat values of heart rate fluctuate continually over a wide range of time scales. Herein we use the relative dispersion, the ratio of the standard deviation to the mean, to show, by systematically aggregating the data, that the correlation in the beat-to-beat cardiac time series is a modulated inverse power law. This scaling property indicates the existence of long-time memory in the underlying cardiac control process and supports the conclusion that heart rate variability is a temporal fractal. We argue that the cardiac control system has allometric properties that enable it to respond to a dynamical environment through scaling.

NASA Discipline Cardiopulmonary↗

Broadband Spectral Investigations of SGR J1550-5418 Bursts

We present the results of our broadband spectral analysis of 42 SGR J1550−5418 bursts simultaneously detected with the Swift/X-ray Telescope (XRT) and the Fermi/Gamma-ray Burst Monitor (GBM), during the 2009 January active episode of the source. The unique spectral and temporal capabilities of the XRT windowed timing mode have allowed us to extend the GBM spectral coverage for these events down to the X-ray domain (0.5-10 keV). Our earlier analysis of the GBM data found that the SGR J1550−5418 burst spectra were described equally well with either a Comptonized model or with two blackbody functions; the two models were statistically indistinguishable. Our new broadband (0.5-200 keV) spectral fits show that, on average, the burst spectra are better described with two blackbody functions than with the Comptonized model. Thus, our joint XRT-GBM analysis clearly shows for the first time that the SGR J1550−5418 burst spectra might naturally be expected to exhibit a more truly thermalized character, such as a two-blackbody or even a multi-blackbody signal. Using the Swift and RXTE timing ephemeris for SGR J1550−5418 we construct the distribution of the XRT burst counts with spin phase and find that it is not correlated with the persistent X-ray emission pulse phase from SGR J1550−5418. These results indicate that the burst emitting sites on the neutron star need not to be co-located with hot spots emitting the bulk of the persistent X-ray emission. Finally, we show that there is a significant pulse phase dependence of the XRT burst counts, likely demonstrating that the surface magnetic field of SGR J1550−5418 is not uniform over the emission zones, since it is anticipated that regions with stronger surface magnetic field could trigger bursts more efficiently.

bursts↗

Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios

Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.

crop yield projections↗

Bayesian characterization of explosive sources using infrasonic signals

In this paper, a Bayesian approach is applied to the estimation of source characteristics for above ground explosive events using infrasonic observations at propagation distances of hundreds of kilometers. Propagation-based, stochastic path geometry models have previously been investigated for infrasonic source localization with promising results; here, statistical transmission loss models are investigated using archived atmospheric specifications and propagation simulation tools to demonstrate that such an approach is applicable to source characterization. The resulting transmission loss models models are utilized in estimating near-source spectral characteristics for explosive events from infrasonic observations at regional distances of several hundred kilometers or more using a Bayesian framework to compute a combined estimate. The near-source spectral characterization can be used along with a simplistic explosive source model to compute an estimate of explosive yield with quantifiable uncertainty. Finally, the yield estimation framework is evaluated using above-ground explosive events from the western US during the fall of 2012 with promising results.

58 GEOSCIENCES↗

Wireless Channel Characterization: Modeling the 5 GHz Microwave Landing System Extension Band for Future Airport Surface Communications

We describe a recently completed wideband wireless channel characterization project for the 5 GHz Microwave Landing System (MLS) extension band, for airport surface areas. This work included mobile measurements at large and small airports, and fixed point-to-point measurements. Mobile measurements were made via transmission from the air traffic control tower (ATCT), or from an airport field site (AFS), to a receiving ground vehicle on the airport surface. The point-to-point measurements were between ATCT and AFSs. Detailed statistical channel models were developed from all these measurements. Measured quantities include propagation path loss and power delay profiles, from which we obtain delay spreads, frequency domain correlation (coherence bandwidths), fading amplitude statistics, and channel parameter correlations. In this paper we review the project motivation, measurement coordination, and illustrate measurement results. Example channel modeling results for several propagation conditions are also provided, highlighting new findings.

Matolak, D. W.↗

Light (anti)nuclei production in Pb-Pb collisions at s N N = 5.02 TeV

The measurement of the production of deuterons, tritons and 3 He and their antiparticles in Pb-Pb collisions at $\sqrt{s_{NN}}$= 5.02 TeV is presented in this article. The measurements are carried out at midrapidity (|y| < 0.5) as a function of collision centrality using the ALICE detector. The p T -integrated yields, the coalescence parameters and the ratios to protons and antiprotons are reported and compared with nucleosynthesis models. The comparison of these results in different collision systems at different center-of-mass collision energies reveals a suppression of nucleus production in small systems. In the Statistical Hadronisation Model framework, this can be explained by a small correlation volume where the baryon number is conserved, as already shown in previous fluctuation analyses. However, a different size of the correlation volume is required to describe the proton yields in the same data sets. The coalescence model can describe this suppression by the fact that the wave functions of the nuclei are large and the fireball size starts to become comparable and even much smaller than the actual nucleus at low multiplicities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

Here, the LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived from ${1.4}\times 10^{4}\;\mathrm{kg\,days}$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Towards a data-driven model of hadronization using normalizing flows

We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A Systems Approach to Increasing Carbon Flux to Seed Oil for Biofuels and Bioproducts Production in Camelina sativa (Final Report)

To combat climate change and alleviate the dependency of the United States on fossil fuels, the transition to biofuel crops has long been proposed as a crucial part of the long-term solution. Camelina sativa has emerged as one of the leading commercially viable options for biofuel and bioproduct production for the U.S. Camelina has the advantages of low agronomic inputs and natural resistance to diverse biotic and abiotic stresses relative to other oilseed crops, and Camelina oil-based blends have been tested and approved as liquid transportation fuels. A major limitation in the widespread adoption of Camelina as a viable industrial oilseed crop is its modest oil yields. This project directly investigated possible paths towards increasing oil, by employing tissue-specific and whole plant systems approaches to identify major regulatory bottlenecks. We developed a new high-throughput method for the identification of multi-gene transformants in polyploid species like Camelina sativa and used this to determine that, contrary to what mathematical models suggested, introduction of the microbial Entner-Doudoroff (ED) pathway into Camelina sativa did not result in significant seed oil increases. We developed flux maps providing accurate and statistically robust models of central carbon metabolism in Camelina, including of cultured Camelina embryos. This knowledge was used in the capacitation of a number of junior researchers in gaining knowledge on approaches used for quantitative flux map analyses. We identified several novel Camelina transcription factor genes regulating fatty acid biosynthesis that showed variable effects on seed oil accumulation in transgenic plants. Among a number of community resources, we also developed a knowledge base web resource (CamRegBase) to integrate Camelina gene regulatory information. Together, research outcomes from this project have contributed to a much better understanding of the regulation and bottlenecks to engineer seed oil production in Camelina.

09 BIOMASS FUELS↗

E3SM simulation results and associated python analysis scripts

This archive contains E3SM Land Model simulation results associated with the Journal of Advances in Modeling Earth Systems (JAMES) article titled "More Realistic Intermediate Depth Dry Firn Densification in the Energy Exascale Earth System Model (E3SM)," by Adam M. Schneider, Charles S. Zender, and Stephen F. Price. Also included in the archive are python scripts used to analyze associated data and an offline, statistical firn model.

54 ENVIRONMENTAL SCIENCES↗

Modeling and parameterization of horizontally inhomogeneous cloud radiative properties

One of the fundamental difficulties in modeling cloud fields is the large variability of cloud optical properties (liquid water content, reflectance, emissivity). The stratocumulus and cirrus clouds, under special consideration for FIRE, exhibit spatial variability on scales of 1 km or less. While it is impractical to model individual cloud elements, the research direction is to model a statistical ensembles of cloud elements with mean-cloud properties specified. The major areas of this investigation are: (1) analysis of cloud field properties; (2) intercomparison of cloud radiative model results with satellite observations; (3) radiative parameterization of cloud fields; and (4) development of improved cloud classification algorithms.

Welch, R. M.↗

Structure of chalcogen overlayers on Au(111): Density functional theory and lattice-gas modeling

Ordering of different chalcogens, S, Se, and Te, on Au(111) exhibit broad similarities but also some distinct features, which must reflect subtle differences in relative values of the long-range pair and many-body lateral interactions between adatoms. We develop lattice-gas (LG) models within a cluster expansion framework, which includes about 50 interaction parameters. These LG models are developed based on density functional theory (DFT) analysis of the energetics of key adlayer configurations in combination with the Monte Carlo (MC) simulation of the LG models to identify statistically relevant adlayer motifs, i.e., model development is based entirely on theoretical considerations. The MC simulation guides additional DFT analysis and iterative model refinement. Given their complexity, development of optimal models is also aided by strategies from supervised machine learning. The model for S successfully captures ordering motifs over a broader range of coverage than achieved by previous models, and models for Se and Te capture the features of ordering, which are distinct from those for S. More specifically, the modeling for all three chalcogens successfully explains the linear adatom rows (also subtle differences between them) observed at low coverages of ~0.1 monolayer. The model for S also leads to a new possible explanation for the experimentally observed phase with a (5 × 5)-type low energy electron diffraction (LEED) pattern at 0.28 ML and to predictions for LEED patterns that would be observed with Se and Te at this coverage.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗