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At least 883 records · Page 49

LASSO observations at McDonald and OCA/CERGA: A preliminary analysis

The Laser Synchronization from Synchronous Orbit (LASSO) observations between USA and Europe were made possible with the move of Meteosat 3/P2 toward 50 deg W. Two Lunar Laser Ranging stations participated into the observations: the MLRS at McDonald Observatory (Texas, USA) and OCA/CERGA (Grasse, France). Common sessions were performed since 30 Apr. 1992, and will be continued up to the next Meteosat 3/P2 move further West (planned for January 1993). The preliminary analysis made with the data already collected by the end of Nov. 1992 shows that the precision which can be obtained from LASSO is better than 100 ps, the accuracy depending on how well the stations maintain their time metrology, as well as on the quality of the calibration (still to be made.) For extracting such a precision from the data, the processing has been drastically changed compared to the initial LASSO data analysis. It takes into account all the measurements made, timings on board, and echoes at each station. This complete use of the data increased dramatically the confidence into the synchronization results.

Veillet, CH.↗

Biomass Compositional Analysis: NIR Rapid Methods (Fact Sheet)

NREL biomass analysis scientists use near-infrared (NIR) spectroscopy correlated with compositional data, produced using traditional wet chemical techniques, to develop rapid calibration models. These models dramatically decrease the time required for (and the cost of) routine compositional analyses. NREL has models to predict the composition of a variety of biomass types.

09 BIOMASS FUELS↗

Application of Atmospheric Infrared Sounder (AIRS) Data to Climate Research

The application of hyper spectral radiometric data to climate research requires very high absolute radiometric accuracy and stability. We use cloud-free tropical ocean data from the Atmospheric InfraRed Sounder (AIR) Calibration Data Subset (ADCS) to show that the radiometric precision and stability required climate applications has been achieved. The sea surface skin temperatures derived from the AIRS 2616cm-1 super window channel are stable relative to the RTG.SST at the better than 8 mK/year level, and the spectral calibration is stable at the 1 ppm/year level. The excellent stability and accuracy are the result of the implementation of AIRS as a grating array spectrometer, which is cooled and stabilized within 10 mK at 155 K. Analysis of daily measurements of the temperature gradient between the surface and 7 km altitude show that the AIRS Calibration Data Subset has applications which extend its original intent for calibration support to climate research. The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua satellite was launched into polar orbit in May 2002. AIRS covers the spectral region from 640 to 2700 cm-1 with 2378 independent channels and represents the first of a new generation of hyper spectral resolution sounders in support of global sounding data for weather forecasting and climate research.

infrared↗

Propulsion-Airframe Integration for Conceptual Redesign of a Low-Boom Supersonic Transport

A low-boom supersonic transport was generated in a previous low-boom multidisciplinary optimization (MDO) study that used computational fluid dynamics (CFD) off-body pressure to compute the undertrack sonic boom ground signature and calibrated low-fidelity aerodynamics analyses to compute the mission performance metrics. This low-boom aircraft, referred to as the Mach 1.7 40-PAX concept, can carry 40 passengers for a low-boom overland mission with cruise Mach 1.7 for the airport pairs over the continental US and has the potential to achieve an undertrack sonic boom ground noise level below 70 perceived level of decibels at the start of overland cruise (SOC). The engine for the Mach 1.7 40-PAX concept was designed using the Numerical Propulsion System Simulation (NPSS) for the mission analysis and modeled as a flow-through nacelle for CFD-based sonic boom analysis. To understand how the engine plume affects the undertrack ground signature, the Mach 1.7 40-PAX concept is redesigned in this paper after replacing the flow-through nacelles by CFD engines for sonic boom analysis using aeropropulsive CFD simulation. A process is developed for approximation of the NPSS engine at SOC by a CFD engine for aeropropulsive CFD simulation. The generated CFD engine has the identical nozzle boundary conditions and approximately the same mass flow and thrust as those of the NPSS engine at SOC. Then, the outer mold line of the configuration with the CFD engines is redesigned to approximately restore the low-boom characteristics of the Mach 1.7 40-PAX concept at SOC. Finally, the CFD simulation data for the redesigned concept with the CFD engines is used to calibrate the low-fidelity aerodynamic analyses for mission analysis of this concept. The cyclic dependency of the involved disciplinary analyses is resolved using an iteration method for a consistent coupling of the mission analysis, NPSS engine analysis, and low-boom redesign using the aeropropulsive CFD simulation. This low-boom redesign study is used as an example to demonstrate how the propulsion-airframe integration could be implemented for conceptual design of supersonic transports that satisfy both the low-boom and mission performance requirements.

Low-boom supersonic transport↗

Columnar data analysis with ATLAS analysis formats

Future analysis of ATLAS data will involve new small-sized analysis formats to cope with the increased storage needs. The smallest of these, named DAOD_PHYSLITE, has calibrations already applied to allow fast downstream analysis and avoid the need for further analysis-specific intermediate formats. This allows for application of the "columnar analysis" paradigm where operations are applied on a per-array instead of a per-event basis. We will present methods to read the data into memory, using Uproot, and also discuss I/O aspects of columnar data and alternatives to the ROOT data format. Furthermore, we will show a representation of the event data model using the Awkward Array package and present proof of concept for a simple analysis application.

97 MATHEMATICS AND COMPUTING↗

Predicting Switchgrass Biomass Yields Using a Spectral Vegetation Index Derived from Multispectral Satellite Imagery

Successful scaling of perennial bioenergy crop production requires a landscape design that optimizes the benefits of finite lands for people, communities, and environments. Utilizing marginal areas is the key to sustainable bioenergy crop production (Ssegane et al., 2015, 2016). Marginal areas are often small-sized lands and unevenly distributed across the agricultural landscape (Ssegane et al., 2016); thus, a systematic, semi-automated remote sensing method is needed as an effective means of estimating bioenergy crop yields across landscapes. Argonne National Laboratory (Argonne) is currently developing a tool, Scaling Up Perennial Bioenergy Economics and Ecosystem Services Tool (SUPERBEEST), to identify marginal agricultural lands and quantify environmental and economic effects of perennial bioenergy crop production systems. The tool aims to provide users a path to foster the sustainable and productive integration of bioenergy crops in the Midwestern agricultural landscape. Reliable, cost-effective, and timely estimation of bioenergy crop yields using remote sensing would help calculate and track the success of integrated bioenergy crops in the landscape for those communities. Argonne previously conducted feasibility studies for estimating biomass yields for bioenergy feedstock, corn and perennial grass using spectral vegetation indices (SVIs)1 derived from optical imagery (Hamada et al., 2015, 2021). In both studies, SVIs, more specifically those sensitive to plant chlorophyll or nitrogen contents, showed potential for estimating or predicting biomass yields with a correlation of determination (R2) ranging from 0.54 to 0.96, indicating a value for further investigation as a viable means of quantifying bioenergy feedstock production across large landscapes. Thus, the goal of this study is to evaluate the feasibility of use of SVIs as a means of estimating or predicting switchgrass biomass yields at harvest using publicly available multispectral satellite imagery. The feasibility analysis was performed using four study areas of mature switchgrass located in Virginia. Objectives are to (1) examine the SVIs and establish their relationships with switchgrass biomass yields at harvest, (2) develop a parsimonious image processing model for predicting at-harvest yields by applying the relationships with the most promising spectral index and (3) map switchgrass yields predicted by the image processing model across the study sites. The calibration to field data will rely on switchgrass biomass yields determined by the baling method, representing a potential challenge to the analysis but an important practical aspect for future applications. With this research design, the study aimed to gain insights into enabling remote sensing-based estimation of bioenergy crop yields in a reliable, cost- effective, and timely manner across large, heterogeneous landscapes.

09 BIOMASS FUELS↗

SkICAT: A cataloging and analysis tool for wide field imaging surveys

We describe an integrated system, SkICAT (Sky Image Cataloging and Analysis Tool), for the automated reduction and analysis of the Palomar Observatory-ST ScI Digitized Sky Survey. The Survey will consist of the complete digitization of the photographic Second Palomar Observatory Sky Survey (POSS-II) in three bands, comprising nearly three Terabytes of pixel data. SkICAT applies a combination of existing packages, including FOCAS for basic image detection and measurement and SAS for database management, as well as custom software, to the task of managing this wealth of data. One of the most novel aspects of the system is its method of object classification. Using state-of-theart machine learning classification techniques (GID3* and O-BTree), we have developed a powerful method for automatically distinguishing point sources from non-point sources and artifacts, achieving comparably accurate discrimination a full magnitude fainter than in previous Schmidt plate surveys. The learning algorithms produce decision trees for classification by examining instances of objects classified by eye on both plate and higher quality CCD data. The same techniques will be applied to perform higher-level object classification (e.g., of galaxy morphology) in the near future. Another key feature of the system is the facility to integrate the catalogs from multiple plates (and portions thereof) to construct a single catalog of uniform calibration and quality down to the faintest limits of the survey. SkICAT also provides a variety of data analysis and exploration tools for the scientific utilization of the resulting catalogs. We include initial results of applying this system to measure the counts and distribution of galaxies in two bands down to Bj is approximately 21 mag over an approximate 70 square degree multi-plate field from POSS-II. SkICAT is constructed in a modular and general fashion and should be readily adaptable to other large-scale imaging surveys.

Weir, N.↗

Scattered light in the echelle modes of the Goddard High Resolution Spectrograph aboard the Hubble Space Telescope. II - Analysis of in-flight spectroscopic observations

We report on an analysis of observations made with the GHRS aboard the HST for the purpose of calibrating the effects of scattered light. The data were obtained during the first 2 years of flight operations as part of the Science Verification, Science Assessment Observations, and Guaranteed Time Observations programs. Both the general level of background light near the spectra and the filling-in of the cores of saturated interstellar absorption lines have been determined as functions of grating, order, wavelength, and aperture. The behavior is in accordance with our detailed analysis of prelaunch laboratory data and validates both the observing procedures and the data reduction developed on the basis of that experience. We present and discuss the use of a background (scattered light) removal algorithm designed to produce net spectra properly corrected for the effects of grating scattered light. The coefficients of the scattered light removal algorithm have been determined, and recommended numerical values are presented.

Cardelli, Jason A.↗

Regression Model Optimization for the Analysis of Experimental Data

A candidate math model search algorithm was developed at Ames Research Center that determines a recommended math model for the multivariate regression analysis of experimental data. The search algorithm is applicable to classical regression analysis problems as well as wind tunnel strain gage balance calibration analysis applications. The algorithm compares the predictive capability of different regression models using the standard deviation of the PRESS residuals of the responses as a search metric. This search metric is minimized during the search. Singular value decomposition is used during the search to reject math models that lead to a singular solution of the regression analysis problem. Two threshold dependent constraints are also applied. The first constraint rejects math models with insignificant terms. The second constraint rejects math models with near-linear dependencies between terms. The math term hierarchy rule may also be applied as an optional constraint during or after the candidate math model search. The final term selection of the recommended math model depends on the regressor and response values of the data set, the user s function class combination choice, the user s constraint selections, and the result of the search metric minimization. A frequently used regression analysis example from the literature is used to illustrate the application of the search algorithm to experimental data.

Ulbrich, N.↗

Performance of Thermal Mass Flow Meters in a Variable Gravitational Environment

The performance of five thermal mass flow meters, MKS Instruments 179A and 258C, Unit Instruments UFM-8100, Sierra Instruments 830L, and Hastings Instruments HFM-200, were tested on the KC-135 Reduced Gravity Aircraft in orthogonal, coparallel, and counterparallel orientations relative to gravity. Data was taken throughout the parabolic trajectory where the g-level varied from 0.01 to 1.8 times normal gravity. Each meter was calibrated in normal gravity in the orthogonal position prior to flight followed by ground testing at seven different flow conditions to establish a baseline operation. During the tests, the actual flow rate was measured independently using choked-flow orifices. Gravitational acceleration and attitude had a unique effect on the performance of each meter. All meters operated within acceptable limits at all gravity levels in the calibrated orthogonal position. However, when operated in other orientations, the deviations from the reference flow became substantial for several of the flow meters. Data analysis indicated that the greatest source of error was the effect of orientation, followed by the gravity level. This work emphasized that when operating thermal flow meters in a variable gravity environment, it is critical to orient the meter in the same direction relative to gravity in which it was calibrated. Unfortunately, there was no test in normal gravity that could predict the performance of a meter in reduced gravity. When operating in reduced gravity, all meters indicated within 5 percent of the full scale reading at all flow conditions and orientations.

Brooker, John E.↗

Quantitative analysis of time-resolved microwave conductivity data

Flash-photolysis time-resolved microwave conductivity (fp-TRMC) is a versatile, highly sensitive technique for studying the complex photoconductivity of solution, solid, and gas-phase samples. The purpose of this paper is to provide a standard reference work for experimentalists interested in using microwave conductivity methods to study functional electronic materials, describing how to conduct and calibrate these experiments in order to obtain quantitative results. The main focus of the paper is on calculating the calibration factor, K, which is used to connect the measured change in microwave power absorption to the conductance of the sample. We describe the standard analytical formulae that have been used in the past, and compare them to numerical simulations. This comparison shows that the most widely used analytical analysis of fp-TRMC data systematically under-estimates the transient conductivity by ~60%. We suggest a more accurate semi-empirical way of calibrating these experiments. However, we emphasize that the full numerical calculation is necessary to quantify both transient and steady-state conductance for arbitrary sample properties and geometry.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Cluster Cosmology Constraints from the 2500 deg 2 SPT-SZ Survey: Inclusion of Weak Gravitational Lensing Data from Magellan and the Hubble Space Telescope

We derive cosmological constraints using a galaxy cluster sample selected from the 2500 deg 2 SPT-SZ survey. The sample spans the redshift range 0.25 < z < 1.75 and contains 343 clusters with SZ detection significance ξ > 5. The sample is supplemented with optical weak gravitational lensing measurements of 32 clusters with 0.29 < z < 1.13 (from Magellan and Hubble Space Telescope ) and X-ray measurements of 89 clusters with 0.25 < z < 1.75 (from Chandra). We rely on minimal modeling assumptions: (i) weak lensing provides an accurate means of measuring halo masses, (ii) the mean SZ and X-ray observables are related to the true halo mass through power-law relations in mass and dimensionless Hubble parameter E(z) with a priori unknown parameters, and (iii) there is (correlated, lognormal) intrinsic scatter and measurement noise relating these observables to their mean relations. We simultaneously fit for these astrophysical modeling parameters and for cosmology. Assuming a flat νΛCDM model, in which the sum of neutrino masses is a free parameter, we measure Ω m = 0.276 ± 0.047, σ 8 = 0.781 ± 0.037, and σ 8 (Ω m /0.3) 0.2 = 0.766 ±0.025. The redshift evolutions of the X-ray Y X –mass and M gas –mass relations are both consistent with self-similar evolution to within 1σ. The mass slope of the Y X –mass relation shows a 2.3σ deviation from self-similarity. Similarly, the mass slope of the M gas –mass relation is steeper than self-similarity at the 2.5σ level. In a νwCDM cosmology, we measure the dark energy equation-of-state parameter w = -1.55 ± 0.41 from the cluster data. Here, we perform a measurement of the growth of structure since redshift z ~ 1.7 and find no evidence for tension with the prediction from general relativity. This is the first analysis of the SPT cluster sample that uses direct weak-lensing mass calibration and is a step toward using the much larger weak-lensing data set from DES. We provide updated redshift and mass estimates for the SPT sample.

79 ASTRONOMY AND ASTROPHYSICS↗

Neutron Monitoring Systems for the Characterisation of Nuclear Fuel and Waste - Methodology and Applications - 12055

The most characteristic behaviour of nuclear fuel or waste contaminated by fission material or isotopes resulting from fissile processes is the emission of neutrons. At the same time because of the high penetration of the material by neutrons, they are an ideal probe for measurement by non-destructive assay. The detection and data analysis in this case is quite different compared to methods using gamma measuring techniques. Neutron detection monitors have been in routine operation for a long time, showing their excellent detection capabilities. The neutron monitors designed for different applications have demonstrated their capabilities during daily operation in the field of burned up fuel elements and for nuclear waste with alpha activity. Lately the data analysis was refined and the quality of the results was improved by using MCNP calculations. Last but not least the layout and the calibration of neutron monitors are nowadays unfeasible without support by MCNP simulations. In the field of non-destructive assay the neutron monitors are undisputed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Monitoring MRK 509: The Origin of the Reprocessor and Broad Band X-ray Spectrum of Narrow Line Seyfert 1 AKN 564

The ten monitoring observations of Mrk 509 were made successfully between October 20 and November 26 last year. These observations were simultaneously with RXTE observations. A preliminary analysis of the RXTE observations has been done, and the light curve is shown in figure 1. Our aim in this experiment is to determine the location of the emission region of the reflection component by reverberation mapping. This component could be emitted from the accretion disk, within 100 Scwartzschild radii (R(sub s)) from the source. Note that the monitoring interval of 2.5 days corresponds to 100 R(sub s) for a 2 x 10(exp 8) solar mass black hole, which may be appropriate for this luminous object. In that case, we would expect the reflected component to vary along the direct flux, and there should be no spectral variability between observations. Alternatively, the reflected emission could come from the molecular torus, several parsecs from the nucleus. In that case, the reflection component flux should not vary. The light curve in figure 1 shows that during the monitoring period, the target varied in an ideal way, since significant variability was observed between observations and yet the most rapid variability is apparently sampled. The analysis of this data is not yet completed. The measurement of the reflection component in the combined ASCa and RXTE spectra depends critically on the RXTE background subtraction and calibration, but these have not yet progressed to the point where the analysis can be done.

Halpern, Jules P.↗

Physics-Informed and Data-Driven Prediction of Residual Stress in Three-Dimensional Machining

Efficient and reliable prediction of machining-induced residual stress (RS) is a key requirement for truly integrated computational materials engineering (ICME). Currently available process modeling approaches, including empirical, analytical, and numerical methodologies lack predictive power and require substantial calibration and validation data. Moreover, most model-based approaches consider only two-dimensional (2D) (i.e., orthogonal), cutting processes. Meanwhile, industrial processes such as milling, turning, and drilling are inherently three-dimensional (3D). The present work attempts to bridge the gap between 2D and 3D through careful consideration of the process physics, including geometric, kinematic, and size-effect constraints to realize robust prediction of how RS develops in 3D machining. Using a novel in-situ experimental technique and digital image correlation (DIC) to determine equivalent Hertzian contact widths, contact pressures, and friction coefficients, the proposed methodology leverages a discretized conversion algorithm that includes multi-pass shakedown effects. This paper presents a semi-analytical model to predict machining-induced RS in 3D turning operations, which are used representatively for 3D processes more generally. Rather than follow a ‘brute force’ 3D FEM approach or conduct countless experiments to train a purely data-driven machine learning algorithm, the proposed approach builds on previous 2D modeling work. Through careful consideration of the process physics, including complex geometry/kinematic considerations of 3D turning, the authors demonstrated an experimentally calibrated approach, as well as validation based on published RS data. Model predictions and previously published measurement data of RS depth profiles for turning of Inconel 718 were compared for a range of process parameters. Correlation between the proposed 3D model and validation data was found to be within the margin of experimental error for most conditions. The proposed model appears to capture the overall behavior of 3D RS depth profiles with acceptable accuracy, particularly the key metrics of near-surface stress, peak stress magnitude and location, as well as overall stress profile depth. This report presents a physics-informed, data-driven approach for efficient calibration of a 2D model for machining-induced RS through DIC analysis of in-situ characterized subsurface displacement fields.

42 ENGINEERING↗

FY2017 Report on NISC Measurements and Detector Simulations

FY17 work focused on automation, both of the measurement analysis and comparison of simulations. The experimental apparatus was relocated and weeks of continuous measurements of the spontaneous fission source 252 Cf was performed. Programs were developed to automate the conversion of measurements into ROOT data framework files with a simple terminal input. The complete analysis of the measurement (which includes energy calibration and the identification of correlated counts) can now be completed with a documented process which involves one simple execution line as well. Finally, the hurdles of slow MCNP simulations resulting in low simulation statistics have been overcome with the generation of multi-run suites which make use of the highperformance computing resources at LANL. Preliminary comparisons of measurements and simulations have been performed and will be the focus of FY18 work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Assessing Nutrient and Carbon Responses to Agricultural Conservation Practices in Two Midwest Watersheds

The United States is undertaking efforts to transition to a low-carbon economy in response to the heightened impacts of climate change, which are largely attributed to decades of carbon-intensive development. A concerted effort by the energy sector to achieve net-zero carbon emissions is aimed at strategically reducing the carbon footprint of the energy supply chain, particularly in the production of feedstocks for biofuels. The production of biofuels relies heavily on land use and management practices in biomass cultivation. Among other factors, soil organic carbon (SOC) plays a crucial role in the biofuel carbon cycle, impacting land productivity, greenhouse gas emissions, and water quality. The process of carbon drawdown during plant growth and storage helps to mitigate the release of carbon dioxide (CO 2 ) into the atmosphere. Another key parameter is the release of nitrous oxide (N 2 O) — a potent greenhouse gas with a global warming potential 273 times that of CO 2 — from soil. While prioritizing low-carbon production, sustainable bioenergy also necessitates improved water quality and ecosystem services. Agricultural conservation practices can contribute to enhanced soil health and reduce nutrient and sediment loss into streams. However, studies that explore the broader impact of these practices on soil carbon storage and N 2 O emissions at a watershed scale are limited. Specifically, our understanding of how low-carbon feedstock production and management affect nutrient cycle dynamics is incomplete. This study assesses watershed responses to land management practices in two agriculturally dominant watersheds: the Raccoon River watershed and the Southfork of Iowa River watershed. The study focuses on carbon and nutrient dynamics, characterizing spatial and temporal variations in SOC, N 2 O, and nutrient loadings to examine the relationship between nutrient and carbon responses and agricultural conservation practices. The study employs the newly developed Soil Water Analysis Tool for Carbon (SWAT-C) model, calibrated using 20 years’ of climate and water monitoring data, to simulate and evaluate two agricultural conservation practices: no-till and crop residue harvest with cover crop planting. We compared the calibrated SWAT-C model with a historical baseline model, which allowed us to analyze various aspects of the watershed, including stream flow, suspended sediments, nitrogen, phosphorus, organic carbon, SOC at different depths, and N 2 O emissions from topsoil. Our SWAT-C modeling results indicate that, compared with results from the historical baseline model, no-till practices are positively correlated with SOC accumulation, reduced N 2 O emissions, and decreased soil loss. We also observed no change or slightly increased nitrogen and phosphorus loss to water bodies in the watersheds compared with the baseline. Conversely, crop residue harvest with cover crop planting improved water quality by reducing nutrient and soil losses but also increased N 2 O emissions. This SWAT-C modeling study establishes the groundwork for further smaller-scale and/or sub-basin-level assessments of nitrogen, phosphorus, and carbon cycles. It provides valuable science-based insights to inform policy decisions — particularly in the context of transitioning to biofuel feedstock production in these watersheds — by addressing concerns about nutrient exports to local water bodies and, ultimately, the Mississippi River.

54 ENVIRONMENTAL SCIENCES↗