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At least 919 records · Page 51

Atomic isotropic hyperfine properties for first row elements (B–F) revisited

Benchmark quality isotropic hyperfine properties have been obtained for first row elements (B–F) using a systematic composite approach consisting of a sequence of core/valence correlation consistent basis sets, up through aug-cc-pCV8Z, along with configuration interaction and coupled cluster theory methods. The best nonrelativistic final values (in MHz) are 10.64 (B), 20.22 (C), 10.59 (N), –31.74 (O), and 318.30 (F) and are in very good agreement with available experimental values for these difficult-to-describe properties. Agreement is especially close in the case of N, which has the most accurate experimental value. The spin densities derived from the best composite level of theory were found to closely follow a simple quadratic scaling with the atomic number, Z. Finally, observed convergence rates in the 1-particle and n-particle expansions obtained here may be useful in judging likely accuracy that can be expected in studies of molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Climate Benchmark Missions: CLARREO

CLARREO (Climate Absolute Radiance and Refractivity Observatory) is one of the four Tier 1 missions recommended by the recent NRC decadal survey report on Earth Science and Applications from Space (NRC, 2007). The CLARREO mission addresses the need to rigorously observe climate change on decade time scales and to use decadal change observations as the most critical method to determine the accuracy of climate change projections such as those used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4). A rigorously known accuracy of both decadal change observations as well as climate projections is critical in order to enable sound policy decisions. The CLARREO mission accomplishes this critical objective through highly accurate and SI traceable decadal change observations sensitive to many of the key uncertainties in climate radiative forcings, responses, and feedbacks that in turn drive uncertainty in current climate model projections. The same uncertainties also lead to uncertainty in attribution of climate change to anthropogenic forcing. The CLARREO breakthrough in decadal climate change observations is to achieve the required levels of accuracy and traceability to SI standards for a set of observations sensitive to a wide range of key decadal change variables. These accuracy levels are determined both by the projected decadal changes as well as by the background natural variability that such signals must be detected against. The accuracy for decadal change traceability to SI standards includes uncertainties of calibration, sampling, and analysis methods. Unlike most other missions, all of the CLARREO requirements are judged not by instantaneous accuracy, but instead by accuracy in large time/space scale average decadal changes. Given the focus on decadal climate change, the NRC Decadal Survey concluded that the single most critical issue for decadal change observations was their lack of accuracy and low confidence in observing the small but critical climate change signals. CLARREO is the recommended attack on this challenge, and builds on the last decade of climate observation advances in the Earth Observing System as well as metrological advances at NIST (National Institute of Standards and Technology) and other standards laboratories.

Wielicki, Bruce A.↗

Radial Compressors with Advanced Secondary Flow Paths for Extended Operating Range

Adequate range is a critical criterion in determining the proper compressor for a given application. In industries centering on turbochargers, range is often the dominant concern. Many times, significant sacrifices in performance are made at the design point in order to obtain enough range of the machine for the duty required. Active controls, the most common being inlet guide vanes (IGVs), can provide sufficient range extension while generating minimal degradation of performance at the design point. Such devices, however, add significant cost and complexity to the machine as they require an active control mechanism. Other devices, such as recirculating casing treatment (RCT), have the advantage of both cost and simplicity by virtue of their passive nature. They’ve seen widespread adoption in the turbocharger industry, though they are generally less effective than IGVs in extending range. A novel approach to extend compressor range through a passive method is proposed here. The method takes some inspiration from classical RCT applications in that it prompts recirculation at low flow rates and corresponding higher back pressures. This recirculation then occupies a portion of the primary cross-sectional passage area and confines the rest of the non-recirculating flow to a smaller area. This restriction forces a higher meridional velocity and a more favorable incidence angle at the impeller blade leading edge. The recirculation is accomplished by laying out an expanded secondary flow path at the rear of the impeller leading back to the inlet hub region. Vanes on the rear of the impeller disk provide just enough pressure rise to counter the induced pressure from the primary flow at the design point. This yields very low mass flow in the secondary path, a condition known as “shutoff” in the pump industry. At lower primary flow levels, and higher back pressures, the secondary flow is induced back to the impeller inlet setting up the recirculation region and pinching the primary flow. Various vane configurations and layouts in the secondary region are explained, and advantages and disadvantages of each are covered. The range extensions made possible by this method and the corresponding impact on performance is discussed.

compressors, extended operating range↗

Properties of Linear Contrails Detected in 2012 Northern Hemisphere MODIS Imagery

Observation of linear contrail cirrus coverage and retrieval of their optical properties are valuable data for validating atmospheric climate models that represent contrail formation explicitly. These data can reduce our uncertainty of the regional effects of contrail-generated cirrus on global radiative forcing, and thus improve our estimation of the impact of commercial aviation on climate change. We use an automated contrail detection algorithm (CDA) to determine the coverage of linear persistent contrails over the Northern Hemisphere during 2012. The contrail detection algorithm is a modified form of the Mannstein et al. (1999) method, and uses several channels from thermal infrared MODIS data to reduce the occurrence of false positive detections. A set of contrail masks of varying sensitivity is produced to define the potential range of uncertainty in contrail coverage estimated by the CDA. Global aircraft emissions waypoint data provided by FAA allow comparison of detected contrails with commercial aircraft flight tracks. A pixel-level product based on the advected flight tracks defined by the waypoint data and U-V wind component profiles from the NASA GMAO GEOS-4 reanalysis has been developed to assign a confidence of contrail detection for the contrail mask. To account for possible contrail cirrus missed by the CDA, a post-processing method based on the assumption that pixels adjacent to detected linear contrails will have radiative signatures similar to those of the detected contrails is applied to the Northern Hemisphere data. Results from several months of MODIS observations during 2012 will be presented, representing a near-global climatology of contrail coverage. Linear contrail coverage will be compared with coverage estimates determined previously from 2006 MODIS data.

Duda, David P.↗

Towards an Improved Understanding of the Antarctic Coastal Zone and Its Contribution to Future Global Sea Level

Understanding the coastal zone of the Antarctic Ice Sheet (AIS), where it interacts with the Southern Ocean and warmer air masses, is crucial for predicting Antarctica's influence on the global climate and sea level. This region has multiple tipping mechanisms that could trigger large, rapid, and potentially irreversible changes in the AIS, the Southern Ocean and their global connections in the coming centuries. The AIS remains the largest source of uncertainty in future sea-level projections. Bed topography beneath the ice shelves and the coastal ice sheet is not yet well documented, and is a major source of this uncertainty. This review assesses current knowledge of the coastal zone and highlights methods to investigate it, including aerogeophysical surveys, ground- and ship-based measurements, satellite observations, and computer modeling. An ensemble analysis of published bed topography data sets identifies significant data gaps and their regional distribution, framed in the context of current ice-sheet behavior and potential instability. We propose scientific priorities and guidelines for future aerogeophysical surveys, advocating for a comprehensive, coordinated international effort to build a next-generation data set of Antarctic bed properties. Such an initiative would significantly advance understanding of the role of coastal processes in ice-sheet dynamics, reducing uncertainties in sea-level rise projections and improving predictions of future ocean and climate changes.

Kenichi Matsuoka↗

Fully ab-initio all-electron calculation of dark matter-electron scattering in crystals with evaluation of systematic uncertainties

We calculate target-material responses for dark matter–electron scattering at the all-electron level using atom-centered Gaussian basis sets. The all-electron effects enhance the material response at high momentum transfers from dark matter to electrons, q ≳ O ( 10 α m e ) , compared to calculations using conventional plane wave methods, including those used in ; this enhances the expected event rates at energy transfers E ≳ 10 eV , especially when scattering through heavy mediators. We carefully test a range of systematic uncertainties in the theory calculation, including those arising from the choice of basis set, exchange-correlation functional, number of unit cells in the Bloch sum, k -mesh, and neglect of scatters with very high momentum transfers. We provide state-of-the-art crystal form factors, focusing on silicon and germanium. Our code and results are made publicly available as a new tool, called (“”). Published by the American Physical Society 2024

Dreyer, Cyrus E.↗

Multiorbital Quantum Impurity Solver for General Interactions and Hybridizations

Here we present a numerically exact inchworm Monte Carlo method for equilibrium multiorbital quantum impurity problems with general interactions and hybridizations. We show that the method, originally developed to overcome the dynamical sign problem in certain real-time propagation problems, can also overcome the sign problem as a function of temperature for equilibrium quantum impurity models. This is shown in several cases where the current method of choice, the continuous-time hybridization expansion, fails due to the sign problem. Our method therefore enables simulations of impurity problems as they appear in embedding theories without further approximations, such as the truncation of the hybridization or interaction structure or a discretization of the impurity bath with a set of discrete energy levels, and eliminates a crucial bottleneck in the simulation of ab initio embedding problems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Discrete-Direct Model Calibration and Uncertainty Propagation Method Confirmed on Multi-Parameter Plasticity Model Calibrated to Sparse Random Field Data

A discrete direct (DD) model calibration and uncertainty propagation approach is explained and demonstrated on a 4-parameter Johnson-Cook (J-C) strain-rate dependent material strength model for an aluminum alloy. The methodology's performance is characterized in many trials involving four random realizations of strain-rate dependent material-test data curves per trial, drawn from a large synthetic population. The J-C model is calibrated to particular combinations of the data curves to obtain calibration parameter sets which are then propagated to “Can Crush” structural model predictions to produce samples of predicted response variability. These are processed with appropriate sparse-sample uncertainty quantification (UQ) methods to estimate various statistics of response with an appropriate level of conservatism. This is tested on 16 output quantities (von Mises stresses and equivalent plastic strains) and it is shown that important statistics of the true variabilities of the 16 quantities are bounded with a high success rate that is reasonably predictable and controllable. The DD approach has several advantages over other calibration-UQ approaches like Bayesian inference for capturing and utilizing the information obtained from typically small numbers of replicate experiments in model calibration situations—especially when sparse replicate functional data are involved like force–displacement curves from material tests. The DD methodology is straightforward and efficient for calibration and propagation problems involving aleatory and epistemic uncertainties in calibration experiments, models, and procedures.

42 ENGINEERING↗

TU-H-CAMPUS-JeP1-04: Deformable Image Registration Performances in Pelvis Patients: Impact of CBCT Image Quality

Purpose: To investigate the accuracy and robustness, against image noise and artifacts (typical of CBCT images), of a commercial algorithm for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on real prostate patient images. Methods: The Anaconda DIR algorithm, implemented in RayStation was tested. Two specific Deformation Vector Fields (DVFs) were applied to the reference data set (CTref) using the ImSimQA software, obtaining two deformed CTs. For each dataset twenty-four different level of noise and/or capping artifacts were applied to simulate CBCT images. DIR was performed between CTref and each deformed CTs and CBCTs. In order to investigate the relationship between image quality parameters and the DIR results (expressed by a logit transform of the Dice Index) a bilinear regression was defined. Results: More than 550 DIR-mapped ROIs were analyzed. The Statistical analysis states that deformation strenght and artifacts were significant prognostic factors of DIR performances, while noise appeared to have a minor role in DIR process as implemented in RayStation as expected by the image similarity metric built in the registration algorithm. Capping artifacts reveals a determinant role for the accuracy of DIR results. Two optimal values for capping artifacts were found to obtain acceptable DIR results (DICE> 075/ 0.85). Various clinical CBCT acquisition protocol were reported to evaluate the significance of the study. Conclusion: This work illustrates the impact of image quality on DIR performance. Clinical issues like Adaptive Radiation Therapy (ART) and Dose Accumulation need accurate and robust DIR software. The RayStation DIR algorithm resulted robust against noise, but sensitive to image artifacts. This result highlights the need of robustness quality assurance against image noise and artifacts in the commissioning of a DIR commercial system and underlines the importance to adopt optimized protocols for CBCT image acquisitions in ART clinical implementation.

60 APPLIED LIFE SCIENCES↗

Millimeter-wave spectral line radiation from a powerful explosion

Millimeter-wave spectral line radiation from a powerful air explosion accompanied by neutron, X-ray, and gamma emission is considered. It is shown that the main contribution to the line radiation in the frequency window of air near the wavelength of 2.3 mm is made by nitric oxide molecules. The set of kinetic equations for a partially ionized plasma near the explosion is solved by the Runge-Kutta method. It is shown that the density of nitrogen oxide molecules increases in time to a certain steady-state level. The spectral power of radiation in the NO lines is estimated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

IPET and FETR: Experimental Approach for Studying Molecular Structure Dynamics by Cryo-Electron Tomography of a Single-Molecule Structure

The dynamic personalities and structural heterogeneity of proteins are essential for proper functioning. Structural determination of dynamic/heterogeneous proteins is limited by conventional approaches of X-ray and electron microscopy (EM) of single-particle reconstruction that require an average from thousands to millions different molecules. Cryo-electron tomography (cryoET) is an approach to determine three-dimensional (3D) reconstruction of a single and unique biological object such as bacteria and cells, by imaging the object from a series of tilting angles. However, cconventional reconstruction methods use large-size whole-micrographs that are limited by reconstruction resolution (lower than 20 Å), especially for small and low-symmetric molecule (,400 kDa). In this study, we demonstrated the adverse effects from image distortion and the measuring tilt-errors (including tilt-axis and tilt-angle errors) both play a major role in limiting the reconstruction resolution. Therefore, we developed a ‘‘focused electron tomography reconstruction’’ (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance protein. FETR can tolerate certain levels of image-distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. To describe this method, a set of simulated cryoET images was employed; to validate this approach, the real experimental images from negative-staining and cryoET were used. Since this approach can obtain the structure of a single-instance molecule/particle, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single ‘‘snapshot’’ molecule structure determination. Thus, FETR/IPET provides a completely new opportunity for a single-molecule structure determination, and could be used to study the dynamic character and equilibrium fluctuation of macromolecules.

59 BASIC BIOLOGICAL SCIENCES↗

Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the diversity of potential impacts that can occur at different times of year. However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1-second resolution is often required, which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled. This computational burden is a clear limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solutions run in less than 5 minutes within an acceptable error.

24 POWER TRANSMISSION AND DISTRIBUTION↗

The Theoretical Transition Probabilities Between the B(sup 3)Pi(sub g) and the A(sup 3)Sigma(Sup +, sub u), W(sup 3)Delta(sub u), B'(sup 3)Sigma(sup -, sub u) States of N2

The electronic transition moment functions between the B(sup 3)Pi(sub g) and the A(sup 3)Sigma(sup +, sub u), W(sup 3)Delta(sub u), B'(sup 3)Sigma(sup -, sub u) states of N2 are studied using the internally contracted multireference configuration interaction (ICMRCI) method based upon complete active space SCF (CASSCF) reference wave-functions. The dependence of the moments on both the one and n-particle basis sets has been investigated in detail. The calculated radiative lifetimes for the vibrational levels of B(sup 3)Pi(sub g) are in excellent agreement with the most recent measurement of Euler and Pipkin (1983)

Thuemmel, Helmar T.↗

Flightspeed Integral Image Analysis Toolkit

The Flightspeed Integral Image Analysis Toolkit (FIIAT) is a C library that provides image analysis functions in a single, portable package. It provides basic low-level filtering, texture analysis, and subwindow descriptor for applications dealing with image interpretation and object recognition. Designed with spaceflight in mind, it addresses: Ease of integration (minimal external dependencies) Fast, real-time operation using integer arithmetic where possible (useful for platforms lacking a dedicated floatingpoint processor) Written entirely in C (easily modified) Mostly static memory allocation 8-bit image data The basic goal of the FIIAT library is to compute meaningful numerical descriptors for images or rectangular image regions. These n-vectors can then be used directly for novelty detection or pattern recognition, or as a feature space for higher-level pattern recognition tasks. The library provides routines for leveraging training data to derive descriptors that are most useful for a specific data set. Its runtime algorithms exploit a structure known as the "integral image." This is a caching method that permits fast summation of values within rectangular regions of an image. This integral frame facilitates a wide range of fast image-processing functions. This toolkit has applicability to a wide range of autonomous image analysis tasks in the space-flight domain, including novelty detection, object and scene classification, target detection for autonomous instrument placement, and science analysis of geomorphology. It makes real-time texture and pattern recognition possible for platforms with severe computational restraints. The software provides an order of magnitude speed increase over alternative software libraries currently in use by the research community. FIIAT can commercially support intelligent video cameras used in intelligent surveillance. It is also useful for object recognition by robots or other autonomous vehicles

Thompson, David R.↗

A Study on the Potential Applications of Satellite Data in Air Quality Monitoring and Forecasting

In this study we explore the potential applications of MODIS (Moderate Resolution Imaging Spectroradiometer) -like satellite sensors in air quality research for some Asian regions. The MODIS aerosol optical thickness (AOT), NCEP global reanalysis meteorological data, and daily surface PM(sub 10) concentrations over China and Thailand from 2001 to 2009 were analyzed using simple and multiple regression models. The AOT-PM(sub 10) correlation demonstrates substantial seasonal and regional difference, likely reflecting variations in aerosol composition and atmospheric conditions, Meteorological factors, particularly relative humidity, were found to influence the AOT-PM(sub 10) relationship. Their inclusion in regression models leads to more accurate assessment of PM(sub 10) from space borne observations. We further introduced a simple method for employing the satellite data to empirically forecast surface particulate pollution, In general, AOT from the previous day (day 0) is used as a predicator variable, along with the forecasted meteorology for the following day (day 1), to predict the PM(sub 10) level for day 1. The contribution of regional transport is represented by backward trajectories combined with AOT. This method was evaluated through PM(sub 10) hindcasts for 2008-2009, using ohservations from 2005 to 2007 as a training data set to obtain model coefficients. For five big Chinese cities, over 50% of the hindcasts have percentage error less than or equal to 30%. Similar performance was achieved for cities in northern Thailand. The MODIS AOT data are responsible for at least part of the demonstrated forecasting skill. This method can be easily adapted for other regions, but is probably most useful for those having sparse ground monitoring networks or no access to sophisticated deterministic models. We also highlight several existing issues, including some inherent to a regression-based approach as exemplified by a case study for Beijing, Further studies will be necessa1Y before satellite data can see more extensive applications in the operational air quality monitoring and forecasting.

Li, Can↗

P50/P90 Analysis for Solar Energy Systems Using the System Advisor Model: Preprint

To secure competitive financing for a solar energy generation project, the economic risk associated with interannual solar resource variability must be quantified. One way to quantify this risk is to calculate exceedance probabilities representing the amount of energy expected to be produced by a plant. Many years of solar radiation and metereological data are required to determine these values,often called P50 or P90 values for the level of certainty they represent. This paper describes the two methods implemented in the National Renewable Energy Laboratory's System Advisor Model (SAM) to calculate P50 and P90 exceedance probabilities for solar energy projects. The methodology and supporting data sets are applicable to photovoltaic, solar water heating, and concentrating solar power(CSP) systems.

14 SOLAR ENERGY↗

How Bayesian methods can improve R -matrix analyses of data: The example of the d t reaction

The 3 H(d, n) 4 He reaction is of significant interest in nuclear astrophysics and nuclear applications. It is an important, early step in big-bang nucleosynthesis and a key process in nuclear fusion reactors. We use one- and two-level R-matrix approximations to analyze data on the cross section for this reaction at center-of-mass energies below 215 keV. We critically examine the data sets using a Bayesian statistical model that allows for both common-mode and additional point-to-point un- certainties. We use Markov Chain Monte Carlo sampling to evaluate this R-matrix-plus-statistical model and find two-level R-matrix results that are stable with respect to variations in the channel radii. The S factor at 40 keV evaluates to 25.36(19) MeV b (68% credibility interval). We discuss our Bayesian analysis in detail and provide guidance for future applications of Bayesian methods to R-matrix analyses. We also discuss possible paths to further reduction of the S-factor uncertainty.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

A sharp interface model for deterministic simulation of dendrite growth

A high order level set model is developed for deterministic simulation of dendritic growth in unstable solidifying systems. The model captures motion of the front implicitly on a structured finite difference grid, enables calculation of its geometric properties and also applies boundary conditions on the immersed interface. Interfacial capillary effect is incorporated in the model through the Gibbs-Thomson condition. Canonical problems for evaluating grid convergence of the numerical method and validation tests for stability of a growing nucleus in the presence of isotropic surface tension are presented. The growth morphology of solidifying nuclei in undercooled metallic melts is quantitatively analyzed. Effects of crystal anisotropy and melt undercooling on the front geometry, propagation speed and formation of branched dendritic structures are examined. In conclusion, the complex morphological changes, such as remelting of secondary perturbations under specific conditions of undercooling, are also captured during the quantitative analysis.

36 MATERIALS SCIENCE↗