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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2016

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

aerosols above clouds↗
DOE OSTI2025

Emulation of the calculations of final r -process abundance patterns with a neural network

This work explores the construction of a fast emulator for the calculation of the final pattern of nucleosynthesis in the rapid neutron capture process (the r-process). An emulator is built using a feed-forward artificial neural network (ANN). We train the ANN with nuclear data and relative abundance patterns. We take as input the β-decay half-lives and the one-neutron separation energy of the nuclei in the rare-earth region. The output is the final isotopic abundance pattern. In this work, we focus on the nuclear data and abundance patterns in the rare-earth region to reduce the dimension of the input and output space. We show that the ANN can capture the effect of the changes in the nuclear physics inputs on the final r-process abundance pattern in the adopted astrophysical conditions. We employ the deep ensemble method to quantify the prediction uncertainty of the neural network emulator. The emulator achieves a speed-up by a factor of about 20 000 in obtaining a final abundance pattern in the rare-earth region. The emulator may be utilized in statistical analyses such as uncertainty quantification, inverse problems, and sensitivity analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2011

Exploring the Possible Use of Information Barriers for future Biological Weapons Verification Regimes

This report describes a path forward for implementing information barriers in a future generic biological arms-control verification regime. Information barriers have become a staple of discussion in the area of arms control verification approaches for nuclear weapons and components. Information barriers when used with a measurement system allow for the determination that an item has sensitive characteristics without releasing any of the sensitive information. Over the last 15 years the United States (with the Russian Federation) has led on the development of information barriers in the area of the verification of nuclear weapons and nuclear components. The work of the US and the Russian Federation has prompted other states (e.g., UK and Norway) to consider the merits of information barriers for possible verification regimes. In the context of a biological weapons control verification regime, the dual-use nature of the biotechnology will require protection of sensitive information while allowing for the verification of treaty commitments. A major question that has arisen is whether - in a biological weapons verification regime - the presence or absence of a weapon pathogen can be determined without revealing any information about possible sensitive or proprietary information contained in the genetic materials being declared under a verification regime. This study indicates that a verification regime could be constructed using a small number of pathogens that spans the range of known biological weapons agents. Since the number of possible pathogens is small it is possible and prudent to treat these pathogens as analogies to attributes in a nuclear verification regime. This study has determined that there may be some information that needs to be protected in a biological weapons control verification regime. To protect this information, the study concludes that the Lawrence Livermore Microbial Detection Array may be a suitable technology for the detection of the genetic information associated with the various pathogens. In addition, it has been determined that a suitable information barrier could be applied to this technology when the verification regime has been defined. Finally, the report posits a path forward for additional development of information barriers in a biological weapons verification regime. This path forward has shown that a new analysis approach coined as Information Loss Analysis might need to be pursued so that a numerical understanding of how information can be lost in specific measurement systems can be achieved.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Al capping layers for nondestructive x-ray photoelectron spectroscopy analyses of transition-metal nitride thin films

X-ray photoelectron spectroscopy (XPS) compositional analyses of materials that have been air exposed typically require ion etching in order to remove contaminated surface layers. However, the etching step can lead to changes in sample surface and near-surface compositions due to preferential elemental sputter ejection and forward recoil implantation; this is a particular problem for metal/gas compounds and alloys such as nitrides and oxides. Here, the authors use TiN as a model system and compare XPS analysis results from three sets of polycrystalline TiN/Si(001) films deposited by reactive magnetron sputtering in a separate vacuum chamber. The films are either (1) air-exposed for ≤10 min prior to insertion into the ultrahigh-vacuum (UHV) XPS system; (2) air-exposed and subject to ion etching, using different ion energies and beam incidence angles, in the XPS chamber prior to analysis; or (3) Al-capped in-situ in the deposition system prior to air-exposure and loading into the XPS instrument. The authors show that thin, 1.5–6.0 nm, Al capping layers provide effective barriers to oxidation and contamination of TiN surfaces, thus allowing nondestructive acquisition of high-resolution core-level spectra representative of clean samples, and, hence, correct bonding assignments. The Ti 2p and N 1s satellite features, which are sensitive to ion bombardment, exhibit high intensities comparable to those obtained from single-crystal TiN/MgO(001) films grown and analyzed in-situ in a UHV XPS system and there is no indication of Al/TiN interfacial reactions. XPS-determined N/Ti concentrations acquired from Al/TiN samples agree very well with Rutherford backscattering and elastic recoil analysis results while ion-etched air-exposed samples exhibit strong N loss due to preferential resputtering. The intensities and shapes of the Ti 2p and N 1s core level signals from Al/TiN/Si(001) samples do not change following long-term (up to 70 days) exposure to ambient conditions, indicating that the thin Al capping layers provide stable surface passivation without spallation.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Using the VAHIRR Radar Algorithm to Investigate Lightning Cessation

Accurately determining the threat posed by lightning is a major area for improved operational forecasts. Most efforts have focused on the initiation of lightning within a storm, with far less effort spent investigating lightning cessation. Understanding both components, initiation and cessation, are vital to improving lightning safety. Few organizations actively forecast lightning onset or cessation. One such organization is the 45th Weather Squadron (45WS) for the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45WS has identified that charged anvil clouds remain a major threat of continued lightning and can greatly extend the window of a potential lightning strike. Furthermore, no discernable trend of total lightning activity has been observed consistently for all storms. This highlights the need for more research to find a robust method of knowing when a storm will cease producing lightning. Previous lightning cessation work has primarily focused on forecasting the cessation of cloud-to -ground lightning only. A more recent, statistical study involved total lightning (both cloud-to-ground and intracloud). Each of these previous works has helped the 45WS take steps forward in creating improved and ultimately safer lightning cessation forecasts. Each study has either relied on radar data or recommended increased use of radar data to improve cessation forecasts. The reasoning is that radar data is able to either directly or by proxy infer more about dynamical environment leading to cloud electrification and eventually lightning cessation. The authors of this project are focusing on a two ]step approach to better incorporate radar data and total lightning to improve cessation forecasts. This project will utilize the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) algorithm originally developed during the Airborne Field Mill II (ABFM II) research project. During the project, the VAHIRR product showed a trend of increasing values with increases in the electric field magnitude above 3 kV/m. An extreme value analysis showed that VAHIRR values less than or equal to 10 dBZ-km showed that the probability of having an electric field magnitude larger than 3 kV/m was less than one in ten thousand. VAHIRR also was found to be sensitive at indicating anvil clouds that posed a threat of initiating a lightning flash. This project seeks to use VAHIRR to analyze its utility as a lightning cessation tool, particularly dealing with the threat posed by detached anvils. The results from this project will serve as a baseline effectiveness of radar ]based lightning cessation algorithms. This baseline will be used in the second, and concurrent work by the co ]author fs who are developing a lightning cessation algorithm based on dual ]polarimetric radar data. Ultimately, an accurate method for identifying lightning cessation can save money on lost manpower time as well as greatly improve lightning safety.

Stano, Geoffrey T.↗
DOE OSTI2014

Brachial artery vasomotion and transducer pressure effect on measurements by active contour segmentation on ultrasound

Purpose: To use feed-forward active contours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward active contour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

New Constraints on IGM Thermal Evolution from the Ly α Forest Power Spectrum

We observe the thermal evolution of the intergalactic medium (IGM) over 3 Gyr of cosmic time $1.8\lt z\lt 5.4$ by comparing measurements of the Lyα forest power spectrum to a suite of ~70 hydrodynamical simulations. We conduct Bayesian inference of IGM thermal parameters using an end-to-end forward modeling framework whereby mock spectra generated from our simulation grid are used to build a custom emulator that interpolates the power spectrum between thermal grid points. The temperature at mean density T 0 rises steadily from ${T}_{0}\sim 6000\,{\rm{K}}$ at z = 5.4, peaks at 14,000 K for z ~ 3.4, and decreases at lower redshift, reaching T 0 ~ 7000 K by z ~ 1.8. This evolution provides conclusive evidence for photoionization heating resulting from the reionization of $\mathrm{He}\,{\rm{II}}$, as well as the subsequent cooling of the IGM due to the expansion of the universe after all reionization events are complete. Our findings are broadly consistent with previous measurements of thermal evolution based on a variety of approaches, but the sensitivity of the power spectrum, the combination of high-precision measurements of large-scale modes ($k\lesssim 0.02\,{\rm{s}}\ {\mathrm{km}}^{-1}$) from the Baryon Oscillation Spectroscopic Survey with our recent determination of the small-scale power, our large grid of models, and our careful statistical analysis enable us to break the well-known degeneracy between the temperature at mean density T 0 and the slope of the temperature–density relation γ that has plagued previous analyses. At the highest redshifts, z ≥ 5, we infer lower temperatures than expected from the standard picture of IGM thermal evolution leaving little room for additional smoothing of the Lyα forest by free streaming of warm dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Investigation of Hydrometeor Distributions in Continental and Maritime Storm Systems: Application of Cloud-Resolving Simulations, a Polarimetric Scanning Radar Simulator and Polarimetric Radar Observations

Detailed observations from DOE ARM field campaigns were used to evaluate and improve microphysical and dynamic fields simulated by 3D Cloud Resolving Models (CRMs), employing both bulk and size-resolved bin microphysics. One of the main challenges in bridging the gap between observations and models is placing the analysis in a common framework. To address this, a polarimetric radar simulator was built, consisting of a forward operator to calculate model-consistent polarimetric radar fields, and an analysis package to calculate microphysical and dynamic fields from radar data in a self-consistent manner. The assumptions required for the transformation from model output to radar parameters were carefully considered and tested. It was found that although rain is fairly well captured by the forward model, ice characteristics are difficult to constrain. This polarimetric radar simulator, POLArimetric Radar Retrieval and Instrument Simulator (POLARRIS), was then applied to WRF simulations and polarimetric C-band radar observations from Darwin, Australia and the SGP site in Oklahoma. These two locations contrast maritime and mid-latitude continental convection respectively. POLARRIS was used with NASA Unified WRF simulations of the same storms in order to compare the observed land and ocean contrasts in microphysics and dynamics. An improved model framework for dynamic downscaling of large-scale aerosol products was also developed and applied to the NASA Unified WRF (NU-WRF) cloud resolving model. This improved framework was used to explore the effects of thermodynamic and aerosol invigoration in deep land and ocean convection through a series of sensitivity studies by perturbating aerosol (CCN) and convective available potential energy (CAPE). It was found that increases in aerosol concentrations yielded increases in low-density graupel in the maritime case and high-density hail in the continental case through riming by increased supercooled water. This result implies that native differences in aerosol concentrations may enhance the inherent contrast in riming effects between deep convective systems in the maritime and continental conditions. Formal publications were generated describing this research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

MnEdgeNet for accurate decomposition of mixed oxidation states for Mn XAS and EELS L2,3 edges without reference and calibration

Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer and redox centers for electronic, and electrocatalytic and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XAS) measurements of the Mn L2,3 edges are widely used for this purpose. To date, although the measurements of the Mn L2,3 edges are straightforward given the sample is prepared properly, an accurate decomposition of the mix valence states of Mn remains non-trivial. For both EELS and XAS, 2+, 3+, and 4+ reference spectra need to be taken on the same instrument/beamline and preferably in the same experimental session because the instrumental resolution and the energy axis offset could vary from one session to another. To circumvent this hurdle, in this study, we adopted a deep learning approach and developed a calibration-free and reference-free method to decompose the oxidation state of Mn L2,3 edges for both EELS and XAS. A deep learning regression model is trained to accurately predict the composition of the mix valence state of Mn. To synthesize physics-informed and ground-truth labeled training datasets, we created a forward model that takes into account plural scattering, instrumentation broadening, noise, and energy axis offset. With that, we created a 1.2 million-spectrum database with 1-by-3 oxidation state composition ground truth vectors. The library includes a sufficient variety of data including both EELS and XAS spectra. By training on this large database, our convolutional neural network achieves 85% accuracy on the validation dataset. We tested the model and found it is robust against noise (down to PSNR of 10) and plural scattering (up to t/λ = 1). We further validated the model against spectral data that were not used in training. In particular, the model shows high accuracy and high sensitivity for the decomposition of Mn 3 O 4 , MnO, Mn 2 O 3 , and MnO 2 . The accurate decomposition of Mn 3 O 4 experimental data shows the model is quantitatively correct and can be deployed for real experimental data. Our model will not only be a valuable tool to researchers and material scientists but also can assist experienced electron microscopists and synchrotron scientists in the automated analysis of Mn L edge data.

25 ENERGY STORAGE↗
DOE OSTI2013

Applying uncertainty quantification to multiphase flow computational fluid dynamics

Multiphase computational fluid dynamics plays a major role in design and optimization of fossil fuel based reactors. There is a growing interest in accounting for the influence of uncertainties associated with physical systems to increase the reliability of computational simulation based engineering analysis. The U.S. Department of Energy's National Energy Technology Laboratory (NETL) has recently undertaken an initiative to characterize uncertainties associated with computer simulation of reacting multiphase flows encountered in energy producing systems such as a coal gasifier. The current work presents the preliminary results in applying non-intrusive parametric uncertainty quantification and propagation techniques with NETL's open-source multiphase computational fluid dynamics software MFIX. For this purpose an open-source uncertainty quantification toolkit, PSUADE developed at the Lawrence Livermore National Laboratory (LLNL) has been interfaced with MFIX software. In this study, the sources of uncertainty associated with numerical approximation and model form have been neglected, and only the model input parametric uncertainty with forward propagation has been investigated by constructing a surrogate model based on data-fitted response surface for a multiphase flow demonstration problem. Monte Carlo simulation was employed for forward propagation of the aleatory type input uncertainties. Several insights gained based on the outcome of these simulations are presented such as how inadequate characterization of uncertainties can affect the reliability of the prediction results. Also a global sensitivity study using Sobol' indices was performed to better understand the contribution of input parameters to the variability observed in response variable.

42 ENGINEERING↗
DOE OSTI2015

New opportunities in h → 4ℓ

The Higgs decay h → 4ℓ has played an important role in discovering the Higgs and measuring its mass thanks to low background and excellent resolution. Current cuts in this channel have been optimized for Higgs discovery via the dominant tree level ZZ contribution arising from electroweak symmetry breaking. Going forward, one of the primary objectives of this sensitive channel will be to probe other Higgs couplings and search for new physics on top of the tree level ZZ ‘background’. Thanks to interference between these small couplings and the large tree level contribution to ZZ, the h → 4ℓ decay is uniquely capable of probing the magnitude and CP phases of the Higgs couplings to γγ and Zγ as well as, to a lesser extent, ZZ couplings arising from higher dimensional operators. With this in mind we examine how much relaxing current cuts can enhance the sensitivity while also accounting for the dominant non-Higgs continuum \( q\overline{q}\to 4\ell \) background. We find the largest enhancement in sensitivity for the hZγ couplings (≳100%) followed by hγγ (≳40%) and less so for the higher dimensional hZZ couplings (a few percent). With these enhancements, we show that couplings of order Standard Model values for hγγ may optimistically be probed by end of Run-II at the LHC while for hZγ perhaps towards the end of a high luminosity LHC. In addition, an appropriately optimized h → 4ℓ analysis can complement direct decays of the Higgs to on-shell γγ and Zγ pairs giving a unique opportunity to directly access the CP properties of these couplings.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Laser Atmospheric Wind Sounder (LAWS) phase 1. Volume 2

This report summarizes and documents the results of the 12-month phase 1 work effort. The objective of phase 1 was to establish the conceptional definition of the laser atmospheric wind sounder (LAWS) sensor system, including accommodations analyses to ensure compatibility with the Space Station Freedom (SSF) and the Earth Observing System (EOS) Polar Orbiting Platform (POP). Various concepts were investigated with trade studies performed to select the configuration to be carried forward to the phase 2 Preliminary Design Definition. A summary of the LAWS system and subsystem trade studies that were performed leading to the baseline design configuration is presented in the appendix. The overall objective of the LAWS Project is to define, design, and implement an operational space based facility, LAWS, for accurate measurement of Earth wind profiles. Phase 1 addressed three major areas: (1) requirements definition; (2) instrument concepts and configurations; and (3) performance analysis. For the LAWS instrument concepts and configurations, the issues which press the technological state of the art are reliable detector lifetime and laser performance and lifetime. Lag angle compensation, pointing accuracy, satellite navigation, and telescope design are significant technical issues, but they are considered to be currently state of the art. The primary issues for performance analysis concern interaction with the atmosphere in terms of backscatter and attenuation, wind variance, and cloud blockage. The phase 1 tasks were formulated to address these significant technical issues and demonstrate the technical feasibility of the LAWS concept. Primary emphasis was placed on analysis/trade and identification of candidate concepts. Promising configurations were evaluated for performance, sensitivities, risks, and budgetary costs. Lockheed's baseline LAWS configuration is presented.

Source record↗
DOE OSTI2013

Estimating Bacteria Emissions from Inversion of Atmospheric Transport: Sensitivity to Modelled Particle Characteristics

Model-simulated transport of atmospheric trace components can be combined with observed concentrations to obtain estimates of ground-based sources using various inversion techniques. These approaches have been applied in the past primarily to obtain source estimates for long-lived trace gases such as CO2. We consider the application of similar techniques to source estimation for atmospheric aerosols, by using as a case study the estimation of bacteria emissions from different ecosystem regions in the global atmospheric chemistry and climate model ECHAM5/MESSy-Atmospheric Chemistry (EMAC). Simulated particle concentrations in the tropopause region and at high latitudes, as well as transport of particles to tundra and land ice regions are shown to be highly sensitive to scavenging in mixed-phase clouds, which is poorly characterized in most global climate models. This may be a critical uncertainty in correctly simulating the transport of aerosol particles to the Arctic. Source estimation via Monte Carlo Markov Chain is applied to a suite of sensitivity simulations and the global mean emissions are estimated. We present an analysis of the partitioning of uncertainties in the global mean emissions that are attributable to particle size, CCN activity, the ice nucleation scavenging ratios for mixed-phase and cold clouds, and measurement error. Uncertainty due to CCN activity or to a 1 um error in particle size is typically between 10% and 40% of the uncertainty due to data uncertainty, as measured by the 5%-ile to 95%-ile range of the Monte Carlo ensemble. Uncertainty attributable to the ice nucleation scavenging ratio in mized-phase clouds is as high as 10% to 20% of the data uncertainty. Taken together, the four model 20 parameters examined contribute about half as much to the uncertainty in the estimated emissions as do the measurements. This was a surprisingly large contribution from model uncertainty in light of the substantial data uncertainty, which ranges from 81% to 870% for each of ten ecosystems for this case study. The effects of these and other model parameters in contributing to the uncertainties in the transport of atmospheric aerosol particles should be treated explicitly and systematically in both forward and inverse modelling studies.

characteristics↗
NASA NTRS2015

A Researcher's Perspective on Function Allocation and Its Application to Air Traffic Management

Functional Allocation is an important research area for NASA going forward, and aims at exploring a range of potential options for future ATM (Air Traffic Management) operation concepts. The goal of this work is to gain some insight into the relative strengths and limitations of a range of different concepts, and to identify the important variables as well as any critical or threshold values for those variables for each of those concepts. This information will be captured in a form that can be easily referenced, and can then be used by decision makers to chose which concept or concepts best suit the needs of the US NAS (National Airspace System). The work presented here is one researcher's perspective on this process. A brief overview of Functional Allocation will be followed by more detailed discussion about two of the topics being currently investigated, as well as why and how this work differs from the way we have done ATM research in the past. More specifically, the goal of the analysis work is to understand the reasons for any differences in our metrics (such as delay) when adjusting input variables rather than trying to analyze the raw numbers themselves. In other words, finding which variables different concepts are sensitive to is important for this work, while finding a best or recommended operational concept is not. This will be followed by some examples of this process using results from our current studies. Finally, there will be a discussion on where we are in the process as well as our next steps.

Air-Ground Studies↗
DOE OSTI2016

Isotope ratio characteristics and sensitivity for uranium determinations using a liquid sampling-atmospheric pressure glow discharge ion source coupled to an Orbitrap mass analyzer

Abstract The continued development of the liquid sampling-atmospheric pressure glow discharge (LS-APGD) microplasma as an ion source for diverse, elemental/isotopic analysis applications continues. To this end, characterization of the capabilities in performing precise and accurate isotope ratio (IR) determinations is essential. Based on past experience with the Thermo Exactive Orbitrap mass analyzer, the LS-APGD was interfaced with this instrument for these tests. While the Orbitrap platform has demonstrated excellent mass resolution and accuracy in “organic” mass spectrometry (MS) applications, work using an Orbitrap for IR analysis is very sparse. These efforts build off previous work in this coupling, where the importance of a few of the LS-APGD discharge parameters and Orbitrap data acquisition methods on IR precision and accuracy were probed. Presented here are the results of a study that evaluated the analytical precision for natural uranium sample (assumed 235U/238U = 0.0072) determinations. The instrumental parameters evaluated include the number of microscans and scans making up a data acquisition set, uranium concentration/signal level, sample make-up, and Fourier transform digitization window. Ultimately, a precision of 0.41% relative standard deviation (RSD) can be achieved for a single determination, with a reproducibility of 1.63 %RSD over 10 separate analytical measurements. A preliminary study of matrix effects on IR measurements of U is presented, highlighting the importance of pre-mass selection before injection into the Orbitrap. The analytical system sensitivity is suggested with the ability to produce a calibration function having an R2 value of >0.99 over a range of 4 orders of magnitude of concentration (~1 – 1000 ng mL-1). These efforts demonstrate the very promising pairing of the LS-APGD ionization source and the Orbitrap, pointing as well to definitive paths forward to better utilize both components in high quality isotope ratio mass spectrometry (IRMS).

Environmental Molecular Sciences Laboratory↗
DOE OSTI2016

Mapping Cheatgrass Across the Range of the Greater Sage-Grouse: Linking Biophysical, Climate and Remote Sensing Data to Predict Cheatgrass Occurrence

Increasing spread of invasive annual grasses, such as Bromus tectorum (cheatgrass), can contribute to increased fire frequency and hinder the reestablishment of native sagebrush, forbs, and grasses in subsequent years. Knowledge of the current distribution of cheatgrass on the landscape is a key component in planning and executing strategies to protect sagebrush ecosystems and sensitive wildlife species such as the Greater sage-grouse (Centrocercus urophasianus). Pacific Northwest National Laboratory (PNNL) worked with US Fish and Wildlife Service (FWS) to assemble and derive information to map cheatgrass occurrence across the historic range of sage-grouse. The information and map products described in this report can help land managers prioritize conservation efforts at the species’ range scale. We constructed an ecological model based on a suite of climatic and biophysical variables and satellite measures of peak NDVI (normalized difference vegetation index) – an index of vegetation greenness – to predict cheatgrass occurrence across the historic range of sage-grouse in the United States. More than 24,000 field measurements of cheatgrass cover across the study area were acquired from various agencies and research groups and reviewed for use in the modeling efforts. A subset of 6650 field measurement points were identified and verified for use in statistical analyses. For each measurement location we derived a suite of 50 biophysical and NDVI variables correlated with cheatgrass occurrence. Pairwise correlation of variables was examined to remove highly-correlated variables from the model. A total of 13 variables were retained for use in forward-stepping discriminant analysis and modeling. Discriminant scores were used to determine probability of cheatgrass occurrence, which was broken into two relative cover classes: 0% to 2% cover and > 2% cheatgrass cover. This report describes the data and methods used to develop the model and the cheatgrass occurrence map. We provide a brief discussion of the accuracy of classification, and describe the appropriate scale of use for map results. The range-wide map of occurrence will be made available online for FWS and partner agencies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Standalone BISON Fuel Performance Results for Watts Bar Unit 1, Cycles 1-3

The Consortium for Advanced Simulation of Light Water Reactors (CASL) is moving forward with more complex multiphysics simulations and increased focus on incorporating fuel performance analysis methods. The coupled neutronics/thermal-hydraulics capabilities within the Virtual Environment for Reactor Applications Core Simulator (VERA-CS) have become relatively stable, and major advances have been made in analysis efforts, including the simulation of twelve cycles of Watts Bar Nuclear Unit 1 (WBN1) operation. While this is a major achievement, the VERA-CS approaches for treating fuel pin heat transfer have well-known limitations that could be eliminated through better integration with the BISON fuel performance code. Several approaches are being implemented to consider fuel performance, including a more direct multiway coupling with Tiamat, as well as a more loosely coupled one-way approach with standalone BISON cases. Fuel performance typically undergoes an independent analysis using a standalone fuel performance code with manually specified input defined from an independent core simulator solution or set of assumptions. This report summarizes the improvements made since the initial milestone to execute BISON from VERA-CS output. Many of these improvements were prompted through tighter collaboration with the BISON development team at Idaho National Laboratory (INL). A brief description of WBN1 and some of the VERA-CS data used to simulate it are presented. Data from a small mesh sensitivity study are shown, which helps justify the mesh parameters used in this work. The multi-cycle results are presented, followed by the results for the first three cycles of WBN1 operation, particularly the parameters of interest to pellet-clad interaction (PCI) screening (fuel-clad gap closure, maximum centerline fuel temperature, maximum/minimum clad hoop stress, and cumulative damage index). Once the mechanics of this capability are functioning, future work will target cycles with known or suspected PCI failures to determine how well they can be estimated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗