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At least 883 records · Page 49

A31N-03: Lower-Tropospheric CO2 from Near-Infrared ACOS-GOSAT Observations

We present two new products from near-infrared GOSAT observations: lower tropospheric (LMT, from 0-2.5 km) and upper tropospheric/stratospheric (U, above 2.5 km) carbon dioxide partial columns. We compare these new products to aircraft profiles and remote surface flask measurements and find that the seasonal and year-to-year variations in the new partial columns significantly improve over the ACOS-GOSAT initial guess/a priori, with distinct patterns in the LMT and U seasonal cycles which match validation data. For land monthly averages, we find errors of 1.9, 0.7, and 0.8 ppm for retrieved GOSAT LMT, U, and XCO2; for ocean monthly averages, we find errors of 0.7, 0.5, and 0.5 ppm for retrieved GOSAT LMT, U, and XCO2. In the southern hemisphere biomass burning season, the new partial columns show similar patterns to MODIS fire maps and MOPITT multispectral CO for both vertical levels, despite a flat ACOS-GOSAT prior, and CO/CO2 emission factor consistent with published values. The difference of LMT and U, useful for evaluation of model transport error, has also been validated with monthly average error of 0.8 (1.4) ppm for ocean (land). The new LMT partial column is more locally influenced than the U partial column, meaning that local fluxes can now be separated from CO2 transported from far away.

Kulawik, Susan S.↗

Extracting strength from high pressure ramp-release experiments

Unloading from a plastically deformed state has long been recognized as a sensitive measure of a material's deviatoric response. In the case of a ramp compression and unload, time resolved particle velocity measurements of a sample/window interface may be used to gain insight into the sample material's strength. Unfortunately, measurements of this type are often highly perturbed by wave interactions associated with impedance mismatches. Additionally, wave attenuation, the finite pressure range over which the material elastically unloads, and rate effects further complicate the analysis. Here, we present a methodology that overcomes these shortcomings to accurately calculate a mean shear stress near peak compression for experiments of this type. A new interpretation of the self-consistent strength analysis is presented and then validated through the analysis of synthetic data sets on tantalum to 250 GPa. The synthetic analyses suggest that the calculated shear stresses are within 3% of the simulated values obtained using both rate-dependent and rate-independent constitutive models. Window effects are addressed by a new technique referred to as the transfer function approach, where numerical simulations are used to define a mapping to transform the experimental measurements to in situ velocities. The transfer function represents a robust methodology to account for complex wave interactions and a dramatic improvement over the incremental impedance matching methods traditionally used. The technique is validated using experiments performed on both lithium fluoride and tantalum ramp compressed to peak stresses of 10 and 15 GPa, respectively. In each case, various windows of different shock impedance are used to ensure consistency within the transfer function analysis. The data are found to be independent of the window used and in good agreement with previous results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Automated Grain Boundary (GB) Segmentation and Microstructural Analysis in 347H Stainless Steel Using Deep Learning and Multimodal Microscopy

Austenitic 347H stainless steel offers superior mechanical properties and corrosion resistance required for extreme operating conditions such as high temperature. The change in microstructure due to composition and process variations is expected to impact material properties. Identifying microstructural features such as grain boundaries thus becomes an important task in the process-microstructure-properties loop. Applying convolutional neural network (CNN)-based deep learning models is a powerful technique to detect features from material micrographs in an automated manner. In contrast to microstructural classification, supervised CNN models for segmentation tasks require pixel-wise annotation labels. However, manual labeling of the images for the segmentation task poses a major bottleneck for generating training data and labels in a reliable and reproducible way within a reasonable timeframe. Microstructural characterization especially needs to be expedited for faster material discovery by changing alloy compositions. Here, in this study, we attempt to overcome such limitations by utilizing multimodal microscopy to generate labels directly instead of manual labeling. We combine scanning electron microscopy images of 347H stainless steel as training data and electron backscatter diffraction micrographs as pixel-wise labels for grain boundary detection as a semantic segmentation task. The viability of our method is evaluated by considering a set of deep CNN architectures. We demonstrate that despite producing instrumentation drift during data collection between two modes of microscopy, this method performs comparably to similar segmentation tasks that used manual labeling. Additionally, we find that naïve pixel-wise segmentation results in small gaps and missing boundaries in the predicted grain boundary map. By incorporating topological information during model training, the connectivity of the grain boundary network and segmentation performance is improved. Finally, our approach is validated by accurate computation on downstream tasks of predicting the underlying grain morphology distributions which are the ultimate quantities of interest for microstructural characterization.

36 MATERIALS SCIENCE↗

Quantifying thermal barrier coating delamination through luminescence modeling

Thermal barrier coatings (TBCs) are widely used in the hot sections of gas turbine systems as they are remarkably efficient in insulating the underlying superalloys, leading to higher operating temperatures and therefore enhancing the performance of the engines. However, this benefit is only possible if the integrity of the TBC under aggressive thermo-mechanical environments is ensured. Delamination is a common but hard to detect failure mode. We present, in this work, supported by experimentation, the implementation of a modeling approach applying the Kubelka-Munk theory to provide numerical quantification of luminescence contrast and intensity due to top coat delamination in TBCs. The method relies on the drastic change in reflectivity when a delamination forms, exploiting it for high-contrast luminescence mapping. Two distinct TBC configurations containing an erbium-doped yttria-stabilized zirconia (YSZ:Er 3+ ) layer for delamination sensing were used to validate this model. A delamination zone induced by Rockwell indentation was successfully tracked by measuring an increase of the intensity of the erbium emission line at 562 nm. Luminescence-based methods for delamination detection can provide a revolutionary non-invasive technique, with potential for both off-line and on-line engine monitoring.

36 MATERIALS SCIENCE↗

Analytical model for drag reduction on liquid-infused structured non-wetting surfaces

Liquid-infused structured non-wetting surfaces provide alternating no-slip and partial slip boundary conditions to the fluid flow, resulting in reduced friction at the interface. In this paper, an analytical model is developed for the evaluation of effective slip and, in turn, friction factor and drag reduction on liquid-infused structured non-wetting surfaces. By considering the entire range of anisotropy and heterogeneity of the surface structures as well as the full range of partial slip offered by the infusion liquid, the present model eliminates empirical fitting or correlations that are inherent in previous studies. Based on the effective slip length, drag reduction and skin friction coefficient values for Newtonian flow between two infinite parallel plates and flow in round tubes are presented. Extension of Moody charts for non-wetting surfaces and design maps of surface meso/micro/nano texturing for achieving desired drag reduction are presented for a broad range of engineering applications. The paper further presents independent validation of the model across experimental and computational data from the literature and brings together several previous studies in a unified manner.

36 MATERIALS SCIENCE↗

Measurement of pulsed-power-driven magnetic fields via proton deflectometry

Measuring magnetic field and current distribution in Z-pinch plasma systems is crucial to the validation of Z-pinch theory. In this letter, the demonstration of proton deflectometry to pulsed-power-driven loads at the mega-amp scale is presented, which is capable of making more detailed field maps in high-density regions of plasmas. In this method, a laser-driven, broad-spectrum, MeV-energy proton beam is directed through a pulsed-power-driven plasma system, and the resulting deflections are measured to examine configuration of magnetic fields and to infer the currents that support them. The technique was first demonstrated on simple short-circuit loads, and the results are in excellent agreement with numerical simulations providing reliable estimates of the field and current configurations. It was then applied to a more complex—radial foil—plasma load. The measurements show unexpected proton deflections that exhibit the complexity of the plasma load and that with further analysis will reveal details about the current and magnetic field topology in this complex configuration.

Mariscal, D.↗

Overcoming time and complexity limitations in molecular dynamics investigations of equilibrium melting

Abstract A hybrid Monte-Carlo molecular-dynamics method for determining solidus and liquidus compositions in multicomponent systems is presented that overcomes both the time limitations in conventional molecular dynamics that prevent the evolution of distinct solid and liquid compositions via diffusion and the complexity challenge that prevents use of thermodynamic assessment in systems of many components. This hybrid method is validated in the Cu–Ni system against an independent assessment of solidus and liquidus compositions based on the regular solution model. Strategies for efficient mapping of different phase diagrams, based on the thermodynamic parameter T 0 , the temperature at which two phases of the composition X 0 have equal free energies, are presented and then demonstrated for the copper-nickel fully miscible system and the gold–silicon eutectic system. A calculation of the solidus and liquidus sampled during the equilibrium melting of equiatomic CrMnFeCoNi is performed, indicating that this method has potential to be extended to the study of many component alloys.

Au-Si↗

Dosimetric accuracy of a deterministic radiation transport based {sup 192}Ir brachytherapy treatment planning system. Part III. Comparison to Monte Carlo simulation in voxelized anatomical computational models

Purpose: To compare TG43-based and Acuros deterministic radiation transport-based calculations of the BrachyVision treatment planning system (TPS) with corresponding Monte Carlo (MC) simulation results in heterogeneous patient geometries, in order to validate Acuros and quantify the accuracy improvement it marks relative to TG43. Methods: Dosimetric comparisons in the form of isodose lines, percentage dose difference maps, and dose volume histogram results were performed for two voxelized mathematical models resembling an esophageal and a breast brachytherapy patient, as well as an actual breast brachytherapy patient model. The mathematical models were converted to digital imaging and communications in medicine (DICOM) image series for input to the TPS. The MCNP5 v.1.40 general-purpose simulation code input files for each model were prepared using information derived from the corresponding DICOM RT exports from the TPS. Results: Comparisons of MC and TG43 results in all models showed significant differences, as reported previously in the literature and expected from the inability of the TG43 based algorithm to account for heterogeneities and model specific scatter conditions. A close agreement was observed between MC and Acuros results in all models except for a limited number of points that lay in the penumbra of perfectly shaped structures in the esophageal model, or at distances very close to the catheters in all models. Conclusions: Acuros marks a significant dosimetry improvement relative to TG43. The assessment of the clinical significance of this accuracy improvement requires further work. Mathematical patient equivalent models and models prepared from actual patient CT series are useful complementary tools in the methodology outlined in this series of works for the benchmarking of any advanced dose calculation algorithm beyond TG43.

60 APPLIED LIFE SCIENCES↗

SU-E-T-49: Automatic Beam Angle Determination for Lung IMRT Planning Using a Beam Configuration Atlas

Purpose: To present a technique to automatically determine beam angle configurations for lung IMRT planning based on the patient-specific anatomy and tumor geometry. Methods: The relationship between individual patient anatomy and proper beam configurations was learned from high quality clinical plans in three steps. First, a beam configuration atlas was obtained by classifying 60 lung IMRT plans into 6 beam configuration clusters based on a dissimilarity measure defined between different beam configurations. A beam configuration template was extracted from each cluster to form an atlas. Second, a beam efficiency index map (EI map) was constructed to characterize the geometry of the tumor relative to the lungs, the body and other OARs along each candidate beam direction. Finally, the EI maps of the clinical cases and the cluster assignments of their beam configurations were paired to train a Bayesian classification model. This technique was validated by leave-one-out cross validation with 16 cases randomly selected from the original dataset. An IMRT plan (autobeam plan) for each test case was generated using the beam configuration template according to the cluster assignment given by the model and was compared with the corresponding clinical plan. Results: The dosimetric parameters (mean±S.D. in percentage of prescription dose) in the auto-beam plans and in the clinical plans, respectively, and the p-values by a paired ttest (in parenthesis) are: lung Dmean: 16.3±9.3, 18.6±7.4 (0.48), esophagus Dmean: 28.4±18, 30.7±19.3 (0.02), Heart Dmean: 21.5±17.5,21.1±17.2 (0.76), Spinal Cord D2%: 48±23, 51.2±21.8 (0.01), PTV dose homogeneity (D2%–D99%): 22±27.4, 20.4±12.8 (0.10).The dose reductions by the autobeam plans in esophagus Dmean and cord D02 are statistically significant but the differences (<4%) may not be clinically significant. The other dosimetric parameters are not statistically different. Conclusion: Plans generated by the automatic beam angle determination method can achieve dosimetric quality equivalent to that of clinical plans. Partially supported by NIH/NCI under grant #R21CA161389 and a master research grant by Varian Medical System.

60 APPLIED LIFE SCIENCES↗

SU-E-J-241: Wavelet-Based Temporal Feature Extraction From DCE-MRI to Identify Sub-Volumes of Low Blood Volume in Head-And-Neck Cancer

Purpose: A previous study showed that large sub-volumes of tumor with low blood volume (BV) (poorly perfused) in head-and-neck (HN) cancers are significantly associated with local-regional failure (LRF) after chemoradiation therapy, and could be targeted with intensified radiation doses. This study aimed to develop an automated and scalable model to extract voxel-wise contrast-enhanced temporal features of dynamic contrastenhanced (DCE) MRI in HN cancers for predicting LRF. Methods: Our model development consists of training and testing stages. The training stage includes preprocessing of individual-voxel DCE curves from tumors for intensity normalization and temporal alignment, temporal feature extraction from the curves, feature selection, and training classifiers. For feature extraction, multiresolution Haar discrete wavelet transformation is applied to each DCE curve to capture temporal contrast-enhanced features. The wavelet coefficients as feature vectors are selected. Support vector machine classifiers are trained to classify tumor voxels having either low or high BV, for which a BV threshold of 7.6% is previously established and used as ground truth. The model is tested by a new dataset. The voxel-wise DCE curves for training and testing were from 14 and 8 patients, respectively. A posterior probability map of the low BV class was created to examine the tumor sub-volume classification. Voxel-wise classification accuracy was computed to evaluate performance of the model. Results: Average classification accuracies were 87.2% for training (10-fold crossvalidation) and 82.5% for testing. The lowest and highest accuracies (patient-wise) were 68.7% and 96.4%, respectively. Posterior probability maps of the low BV class showed the sub-volumes extracted by our model similar to ones defined by the BV maps with most misclassifications occurred near the sub-volume boundaries. Conclusion: This model could be valuable to support adaptive clinical trials with further validation. The framework could be extendable and scalable to extract temporal contrastenhanced features of DCE-MRI in other tumors. We would like to acknowledge NIH for funding support: UO1 CA183848.

60 APPLIED LIFE SCIENCES↗

An integrated Imaging and Modeling Toolbox for Accelerated Development of Root-focused Crops at Field Scales

This project, led by Yuxin Wu at the LBNL, was proposed to develop an integrated imaging-modeling toolbox allowing for accelerated development of root-focused crops at field scales. Our approach is based on a novel root phenotyping method we termed Tomographic Electrical Rhizosphere Imaging (TERI), which provides advanced phenotyping of key root traits by sensing the electrical impedance response of roots and soil to external electrical excitations, and mapping these responses to root and soil properties. The role of Noble Research Institute in this project is to assist TERI model establishment and validation by collecting various above- and below-ground traits data from container- and field-grown plants (mainly wheat). Over the last three years, Noble Research Institute has conducted 3 phases of experiments as proposed including: (Phase 1) greenhouse and hoop-house experiments in wheat and pecan plants grown under controlled container-grown conditions; (Phase 2) space-planted individual plant field experiment using different wheat varieties; and (Phase 3) small-plot planted field experiment using different wheat varieties, as well as using different small grains species including wheat, rye, triticale, oat and barley for increasing plant variation.

60 APPLIED LIFE SCIENCES↗

First Principles Model of Electric Cable Braid Penetration with Dielectrics

In this study, we report the formulation to account for dielectrics in a first principles multipole-based cable braid electromagnetic penetration model. To validate our first principles model, we consider a one-dimensional array of wires, which can be modeled analytically with a multipole-conformal mapping expansion for the wire charges; however, the first principles model can be readily applied to realistic cable geometries. We compare the elastance (i.e. the inverse of the capacitance) results from the first principles cable braid electromagnetic penetration model to those obtained using the analytical model. The results are found in good agreement up to a radius to half spacing ratio of 0.5-0.6, depending on the permittivity of the dielectric used, within the characteristics of many commercial cables. We observe that for typical relative permittivities encountered in braided cables, the transfer elastance values are essentially the same as those of free space; the self-elastance values are also approximated by the free space solution as long as the dielectric discontinuity is taken into account for the planar mode.

42 ENGINEERING↗

Mars Observer: Applications to atmospheric transport

The Pressure Modulator Infrared Radiometer (PMIRR) is an atmospheric sounder designed to observe temporal and spatial variations of water vapor and of dust suspended in the Mars atmosphere, to characterize the planetary-scale thermal structure and circulation of the atmosphere, and to quantify the polar radiative balance. These measurements are fundamental to understanding the seasonal cycles of dust, of water, and of CO2 on Mars and, in particular, to determining the role of atmospheric transport. Using measurements in eight narrow-band infrared spectral regions and one broadband visible channel, the PMIRR investigation teams at JPL and Oxford University will derive vertical profiles of atmospheric temperature, extinction due to suspended dust, and water vapor concentration, as well as locations of CO2 and H2O ice clouds. These data will be used in a variety of ways to address issues of atmospheric dynamics and transport. Three topics will be emphasized here: (1) the expected precision of the retrieved profiles of temperature, dust extinction, and water vapor, including plans for validating the profiles; (2) the observation strategy, designed to best use PMIRR's two-axis scan mirror, as deployed in the Mars Observer mapping orbit; and (3) approaches to mapping the atmospheric fields globally and the derivation of key meteorological fields related to estimating atmospheric transport.

Zurek, Richard W.↗

Quantifying Errors in TRMM-Based Multi-Sensor QPE Products Over Land in Preparation for GPM

Determining uncertainties in satellite-based multi-sensor quantitative precipitation estimates over land of fundamental importance to both data producers and hydro climatological applications. ,Evaluating TRMM-era products also lays the groundwork and sets the direction for algorithm and applications development for future missions including GPM. QPE uncertainties result mostly from the interplay of systematic errors and random errors. In this work, we will synthesize our recent results quantifying the error characteristics of satellite-based precipitation estimates. Both systematic errors and total uncertainties have been analyzed for six different TRMM-era precipitation products (3B42, 3B42RT, CMORPH, PERSIANN, NRL and GSMap). For systematic errors, we devised an error decomposition scheme to separate errors in precipitation estimates into three independent components, hit biases, missed precipitation and false precipitation. This decomposition scheme reveals hydroclimatologically-relevant error features and provides a better link to the error sources than conventional analysis, because in the latter these error components tend to cancel one another when aggregated or averaged in space or time. For the random errors, we calculated the measurement spread from the ensemble of these six quasi-independent products, and thus produced a global map of measurement uncertainties. The map yields a global view of the error characteristics and their regional and seasonal variations, reveals many undocumented error features over areas with no validation data available, and provides better guidance to global assimilation of satellite-based precipitation data. Insights gained from these results and how they could help with GPM will be highlighted.

Peters-Lidard, Christa D.↗

An Integrated Model of Models for Global Flood Alerting

A dramatic increase in frequency of minor to major flooding since 2000 has caused significant damage to infrastructure and economic losses across the world. To mitigate and recover from these losses, actions have been taken to build resilient communities and infrastructures. Situational awareness in near real-time is essential to ensure community resilience and enhance response and recovery efforts. Several hydrologic and hydraulic flood models are available at various spatial and temporal resolutions at regional to global scale. Given the global coverage of two operational flood models - GloFAS (Global Flood Awareness System) and GFMS (Global Flood Monitoring System), the first component of this project first focuses on integrating the outputs from these two models to classify flood severity and send alerts based on potential for impacts similar to the USGS PAGER (used for severity alerting and impact analysis for earthquakes). The second component of the project focuses on using flood outputs derived from earth observation data to validate, update and add additional exposure and impact products to flood alerts. The flood impacts and severity information will be disseminated as alerts and maps through the DisasterAWARE platform, operated by the Pacific Disaster Center (PDC), that provides global multi-hazard alerting and Situational Awareness information to the emergency management community and public. In this presentation, the following objectives will be covered: (i) the effective integration of the flood models, (ii) accuracy of the flood model outputs (flood extent and depth) for specific flood events both in the United States and globally in comparison with each other and earth observation data.

Glasscoe, Margaret↗

4D Characterization of Metals by 3DXRD

The status of 3DXRD microscopy is reviewed, with a special view to applications in metallurgy. Various approaches are compared in terms of performance. In addition several recent advances are presented, such as a 3D grain map with an unprecedented spatial resolution of 500 nm, first results from the commissioning of a novel 3D detector set-up and a validation of the box-scan procedure. Three-Dimensional X-Ray Diffraction (3DXRD) is a novel technique, aiming at a fast and nondestructive characterization of the individual crystalline elements within mm-sized polycrystalline specimens. It is based on two principles: the use of highly penetrating hard X-rays from a synchrotron source (x-ray energies in the range 20-100 keV) and the application of 'tomographic' reconstruction algorithms for the analysis of the diffraction data. In favourable cases, the position, morphology, phase, and crystallographic orientation can be derived for hundreds of elements simultaneously as well as their elastic strains. Furthermore, the dynamics of the individual elements can be monitored during typical processes such as deformation or annealing. Hence, for the first time information on the interaction between elements can be obtained directly. The provision of such data is vital in order to extend beyond state-of-art structural models.

36 MATERIALS SCIENCE↗

The Integrated Cloud-based Environmental Data Management System at Los Alamos National Laboratory - 13391

In today's world, instant access to information is taken for granted. The national labs are no exception; our data users expect immediate access to their data. Los Alamos National Laboratory (LANL) has collected over ten million records, and the data needs to be accessible to scientists as well as the public. The data span a wide range of media, analytes, time periods, formats, and quality and have traditionally existed in scattered databases, making comprehensive work with the data impossible. Recently, LANL has successfully integrated all their environmental data into a single, cloud-based, web-accessible data management system. The system combines data transparency to the public with immediate access required by the technical staff. The use of automatic electronic data validation has been critical to immediate data access while saving millions of dollars and increasing data consistency and quality. The system includes a Google Maps based GIS tool that is simple enough for people to locate potentially contaminated sites near their home or workplace, and complex enough to allow scientists to plot and trend their data at the surface and at depth as well as over time. A variety of formatted reports can be run at any desired frequency to report the most current data available in the data base. The advanced user can also run free form queries of the data base. This data management system has saved LANL time and money, an increasingly important accomplishment during periods of budget cuts with increasing demand for immediate electronic services. (authors)

54 ENVIRONMENTAL SCIENCES↗

SU-E-QI-06: Design and Initial Validation of a Precise Capillary Phantom to Test Perfusion Systems

Purpose: To design a precise perfusion phantom mimicking capillaries of the brain vasculature which could be used to test various perfusion protocols and algorithms which generate perfusion maps. Methods: A perfusion phantom was designed in Solidworks and built using additive manufacturing. The phantom was an overall cylindrical shape of diameter and height 20mm and containing capillaries of 200μm or 300μm which were parallel and in contact making up the inside volume where flow was allowed. We created a flow loop using a peristaltic pump and contrast agent was injected manually. Digital Subtraction Angiographic images and low contrast images with cone beam CT were acquired after the contrast was injected. These images were analyzed by our own code in LabVIEW software and Time-Density Curve, MTT and TTP was calculated. Results: Perfused area was visible in the cone beam CT images; however, individual capillaries were not distinguishable. The Time-Density Curve acquired was accurate, sensitive and repeatable. The parameters MTT, and TTP offered by the phantom were very sensitive to slight changes in the TDC shape. Conclusion: We have created a robust calibrating model for evaluation of existing perfusion data analysis systems. This approach is extremely sensitive to changes in the flow due to the high temporal resolution and could be used as a golden standard to assist developers in calibrating and testing of imaging perfusion systems and software algorithms. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗