Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “data depth”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The character and amplitude of ‘discontinuous’ bottom-simulating reflections in marine seismic data

Bottom-simulating reflections (BSRs) identified in seismic data are well documented; and are commonly interpreted to indicate the presence of gas hydrates along continental margins, as well as to estimate regional volumes of gas hydrate. A BSR is defined as a reflection that sub-parallels the seafloor but is opposite in polarity and cross-cuts dipping sedimentary strata. BSRs form as a result of a strong negative acoustic impedance contrast. BSRs, however, are a diverse seismic phenomena that manifest in strikingly contrasting ways in different geological settings, and in different seismic data types. We investigate the characteristics of BSRs, using conventional and high resolution, 2D and 3D seismic data sets in three locations: the Terrebonne and Orca Basins in the Gulf of Mexico, and Blake Ridge on the US Atlantic Margin. The acquisition geometry and frequency content of the seismic data significantly impact the resultant character of BSRs, as observed with depth and amplitude maps of the BSRs. Furthermore, our amplitude maps reinforce the concept that the BSR represents a zone, over which the transition from hydrate to free gas occurs, as opposed to the conventional model of the BSR occurring at a single interface. Our results show that a BSR can be mapped in three dimensions but it is not spatially continuous, at least not at the basin scale. Rather, a BSR manifests itself as a discontinuous, or patchy, reflection and only at local scales is it continuous. We suggest the discontinuous nature of BSRs is the result of variable saturation and distribution of free gas and hydrate, acquisition geometry and frequency content of the recorded seismic data. Lastly, the commonly accepted definition of a BSR should be broadened with careful consideration of these factors, to represent the uppermost extent of enhanced amplitude at the shallowest occurrence of free gas trapped by overlying hydrate-bearing sediments.

03 NATURAL GAS↗
DOE OSTI2018

Three-dimensional migration behavior of juvenile salmonids in reservoirs and near dams

To acquire 3-D tracking data on juvenile salmonids, Juvenile Salmon Acoustic Telemetry System (JSATS) cabled hydrophone arrays were deployed in the forebays of two dams on the Snake River and at a mid-reach reservoir between the dams. The depth distributions of fish were estimated by statistical analyses performed on large 3-D tracking data sets from ~33,500 individual acoustic tagged yearling and subyearling Chinook salmon and juvenile steelhead at the two dams in 2012 and subyearling Chinook salmon at the two dams and the mid-reach reservoir in 2013. This research investigated the correlation between vertical migration behavior and passage routes. The depth distributions of fish within the forebays of the dams were significantly different from fish passing the mid-reach reservoir. Fish residing deeper in the forebay tended to pass the dam using deeper powerhouse routes. This difference in depth distributions indicated that the depth distribution of fish at the mid-reach reservoir was not related to behaviors of fish passing through certain routes of the adjacent dams. For fish that were detected deeper than 17.5 m in the forebays, the probability of powerhouse passage (i.e., turbine) increased significantly. Another important finding was the variation in depth distributions during dam passage associated with the diel period, especially the crepuscular periods.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Automated Interpretation and Extraction of Topographic Information from Time of Flight Secondary Ion Mass Spectrometry Data

Time of flight secondary ion mass spectrometry (ToF SIMS) is one of the most powerful characterization tools allowing imaging of the chemical properties of various systems and materials. It allows precise studies of the chemical composition with sub-100-nm lateral and nanometer depth spatial resolution. However, comprehensive interpretation of ToF SIMS results is challengeable, because of the data volume and its multidimensionality. Furthermore, investigation of the samples with pronounced topographical features are complicated by the spectral shift. In this work we developed approach for the comprehensive ToF SIMS data interpretation based on the data analytics and automated extraction of the sample topography based on time of flight shift. We further applied this approach to investigate correlation between biological function and chemical composition in Arabidopsis roots.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

Abstract Background Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean’s interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth. Results We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins. Conclusions Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

GoAmazon 2014/15 Particle Sampling Field Campaign Report

As a part of the GoAmazon 2014/15 field deployments, samples of atmospheric particles were collected at the T3 field site (3° 12' 46.70" S, 60° 35' 53.0, Manacapuru, Brazil) established in the Amazonian region. The site was located downwind from Manaus and therefore, experienced clean conditions when winds were from northwest and polluted conditions when winds were from Manaus. During the second intensive operational period of GoAmazon 2014/15 (09/06/2014-10/02/2014), multiple samples of particles were collected using a cascade Multi-Orifice Uniform Deposition Impactor (MOUDI-110). Size-resolved samples by MOUDI (0.056-0.1, 0.1-0.18, 0.18-0.32, 0.32-0.56, 0.56-1.0, 1.0-1.8 μm) were collected for 6-12 hours. A variety of substrates, compatible with different spectro-microscopy methods of analysis, were arranged on the impactor stages. Collected aerosol samples are now stored pending laboratory analysis using multi-modal methods of chemical imaging. Our approach is to analyze only the samples of specific interest. We use the field campaign records and data on meteorology, as well as in situ measurements of gases and aerosols, to select the subset of samples for the in-depth laboratory analysis for selected episodes where changes in chemical composition of particles can be correlated with other data recorded at the site. Hence, we do not expect to perform detailed measurements on all samples—rather, only those samples with the greatest potential to provide scientific insight into aerosol chemistry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Model, data, and code for paper "Modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x"

The data package includes data, model, and code that support the analyses and conclusions in the paper titled “modeling of streamflow in a 30-kilometer-long reach spanning 5 years using OpenFOAM 5.x”. The primary goal of this paper is to demonstrate that key streamflow properties such as water depth, flow velocity, and dynamic pressure in a natural river at 30-kilometer scale over 5 years can be reliably and efficiently modeled using the computational framework presented in this paper. To support the paper, various data types from remote sensing, field observations, and computational models are used. Specific details are described as follows. Firstly, the river bathymetry data was obtained from a Light Detection and Ranging (LiDAR) survey. This data is then converted to a triangulated surface format, STL, for mesh generation in OpenFOAM. The STL data can be found in Model_Setups/BaseCase_2013To2015/constant/triSurface. The OpenFOAM mesh generated using this STL file can be found in constant/polyMesh. Other model setups, boundary and initial conditions can be found in /system and /0.org under folder BaseCase_2013To2015. A similar data structure can also be found in BaseCase_2018To2019 for the simulations during 2018 and 2019. Secondly, the OpenFOAM simulations need the upstream discharge and water depth information at the upstream boundary to drive the model. These data are generated from a one-dimensional hydraulic model and the data can be found under the folder Model_Setups /1D model Mass1 data. The mass1_65.csv and mass1_191.csv files include the results of the 1D model at the model inlet and outlet, respectively. The Matlab source code Mass1ToOFBC20182019.m is used to convert these data into OpenFOAM boundary condition setups.With the above OpenFOAM model, it can generate data for water surface elevation, flow velocity, and dynamic pressure. In this paper, the water surface elevation was measured at 7 locations during different periods between 2011 and 2019. The exact survey locations (see Fig1_SurveyLocations.txt) can be found in folder Fig_1. The variation of water stage over time at the 7 locations can be found in folder /Observation_WSE. The data type include .txt, .csv, .xlsx, and .mat. The .mat data can be loaded by Matlab.We also measured the flow velocities at 12 cross-sections along the river. At each cross-section, we recorded the x, y locations, depth, three velocity components u,v,w. These data are saved to a Matlab format which can be found under folder /Observation_Velocity and /Fig_1. The relative locations of velocity survey locations to the river bathymetry can be found in Figure 1c.The water stage data at the 7 locations from OpenFOAM, 1D, and 2D hydraulic models are also provided to evaluate the long-term performance of 3D models vs 1D/2D models. The water stage data for the 7 locations from OpenFOAM have been saved to .mat format and can be found in /OpenFOAM_WSE. The water stage data from the 1D model are saved in .csv format and can be found in /Mass1_WSE. The water stage from the 2D model is saved as .mat format and can be found in / Mass2_WSEIn addition, the OpenFOAM model outputs the information of hydrostatic and hydrodynamic pressure. They are saved as .mat format under folder /Fig_11/2013_1. As the files are too large, we only uploaded the data for January 2013. The area of different ratio of dynamic pressure to static pressure for all simulation range, i.e., 2013-2015, are saved to .mat format. They can be found in /Fig_11/PA. Further, the data of wall clock time versus the solution time of the OpenFOAM modeling are also saved to .mat format under folder /Fig_13/LogsMat. In summary, the data package contains seven data types, including .txt, .csv, .xlsx, .dat, .stl, .m, and .mat. The former 4 types can be directly open using a text editor or Microsoft Office. The .mat format needs to be read by Matlab. The Matlab source code .m files need to be run with Matlab. The OpenFOAM setups can be visualized in ParaView. The .stl file can be opened in ParaView or Blender. The data in subfolders Fig_1 to Fig_10 and Fig_12 are copied from the aforementioned data folders to generate specific figures for the paper. A readME.txt file is included in each subfolder to further describe how the data in each folder are generated and used to support the paper.Please use the data package's DOI to cite the data package. Please contact yunxiang.chen@pnnl.gov if you need more data related to the paper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Improving Progressive Retrieval for HPC Scientific Data using Deep Neural Network

As the disparity between compute and I/O on high-performance computing systems has continued to widen, it has become increasingly difficult to perform post-hoc data analytics on full-resolution scientific simulation data due to the high I/O cost. Error-bounded data decomposition and progressive data retrieval framework has recently been developed to address such a challenge by performing data decomposition before storage and reading only part of the decomposed data when necessary. However, the performance of the progressive retrieval framework has been suffering from the over-pessimistic error control theory, such that the achieved maximum error of recomposed data is significantly lower than the required error. Therefore, more data than required is fetched for recomposition, incurring additional I/O overhead. In order to tackle this issue, we propose a DNN-based progressive retrieval framework that can better identify the minimum amount of data to be retrieved. Our contributions are as follows: 1) We provide an in-depth investigation of the recently developed progressive retrieval framework; 2) We propose two designs of prediction models (named D-MGARD and E-MGARD) to estimate the amount of retrieved data size based on error bounds. 3) We evaluate our proposed solutions using scientific datasets generated by real-world simulations from two domains. Evaluation results demonstrate the effectiveness of our solution in accurately predicting the amount of retrieval data size, as well as the advantages of our solution over the traditional approach to reducing the I/O overhead. Based on our evaluation, our solution is shown to read significantly less data (5% - 40% with D-MGARD, 20% - 80% with E-MGARD).

Wang, Jinzhen↗
DOE OSTI2016

Rising plant-mediated methane emissions from arctic wetlands

Plant-mediated CH 4 flux is an important pathway for land–atmosphere CH 4 emissions, but the magnitude, timing, and environmental controls, spanning scales of space and time, remain poorly understood in arctic tundra wetlands, particularly under the long-term effects of climate change. CH 4 fluxes were measured in situ during peak growing season for the dominant aquatic emergent plants in the Alaskan arctic coastal plain, Carex aquatilis and Arctophila fulva, to assess the magnitude and species-specific controls on CH 4 flux. Plant biomass was a strong predictor of A. fulva CH 4 flux while water depth and thaw depth were copredictors for C. aquatilis CH 4 flux. Here, we used plant and environmental data from 1971 to 1972 from the historic International Biological Program (IBP) research site near Barrow, Alaska, which we resampled in 2010–2013, to quantify changes in plant biomass and thaw depth, and used these to estimate species-specific decadal-scale changes in CH 4 fluxes. A ~60% increase in CH 4 flux was estimated from the observed plant biomass and thaw depth increases in tundra ponds over the past 40 years. In spite of our covering only ~5% of the landscape, we estimate that aquatic C. aquatilis and A. fulva account for two-thirds of the total regional CH 4 flux of the Barrow Peninsula. The regionally observed increases in plant biomass and active layer thickening over the past 40 years not only have major implications for energy and water balance, but also have significantly altered land–atmosphere CH 4 emissions for this region, potentially acting as a positive feedback to climate warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Evaluating Corrosion in SAVY Containers using Non-Destructive Techniques

Powerpoint presentation on Ultrasonic and Eddy Current NDT; UT Theory; Eddy current (ECA): How it works; Controlled Corrosion at NM Tech; Results – HCl Corrosion; Waveform Data for 10M HCl; Accuracy Statistics; Results – FeCl 3 Pitting; Waveforms for Anhydrous FeCl 3 ; Analyzing Corroded Stainless Steel 316L Plates; 316L Plate to Imitate Pitting; ECA Pit Depth Calibration Curve; C Scan Imaging; UT Pit Detection; SST Containers: Ultrasonic (UT) vs. CMM; UT Data Analysis; UT Conclusions and Observations; ECA Conclusions; Automated System Vision.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Square Kilometre Array Science Data Challenge 1: analysis and results

ABSTRACT As the largest radio telescope in the world, the Square Kilometre Array (SKA) will lead the next generation of radio astronomy. The feats of engineering required to construct the telescope array will be matched only by the techniques developed to exploit the rich scientific value of the data. To drive forward the development of efficient and accurate analysis methods, we are designing a series of data challenges that will provide the scientific community with high-quality data sets for testing and evaluating new techniques. In this paper, we present a description and results from the first such Science Data Challenge 1 (SDC1). Based on SKA MID continuum simulated observations and covering three frequencies (560, 1400, and 9200 MHz) at three depths (8, 100, and 1000 h), SDC1 asked participants to apply source detection, characterization, and classification methods to simulated data. The challenge opened in 2018 November, with nine teams submitting results by the deadline of 2019 April. In this work, we analyse the results for eight of those teams, showcasing the variety of approaches that can be successfully used to find, characterize, and classify sources in a deep, crowded field. The results also demonstrate the importance of building domain knowledge and expertise on this kind of analysis to obtain the best performance. As high-resolution observations begin revealing the true complexity of the sky, one of the outstanding challenges emerging from this analysis is the ability to deal with highly resolved and complex sources as effectively as the unresolved source population.

Bonaldi, A.↗
DOE OSTI2015

A physical approach to the identification of high-Z mergers: Morphological classification in the stellar mass domain

At z ≳ 1, the distinction between merging and “normal” star-forming galaxies based on single band morphology is often hampered by the presence of large clumps which result in a disturbed, merger-like appearance even in rotationally supported disks. In this paper we discuss how a classification based on canonical, non-parametric structural indices measured on resolved stellar mass maps, rather than on single-band images, reduces the misclassification of clumpy but not merging galaxies. We calibrate the mass-based selection of mergers using the MIRAGE hydrodynamical numerical simulations of isolated and merging galaxies which span a stellar mass range of 10{sup 9.8}–10{sup 10.6} M{sub ⊙} and merger ratios between 1:1–1:6.3. These simulations are processed to reproduce the typical depth and spatial resolution of observed Hubble Ultra Deep Field (HUDF) data. We test our approach on a sample of real z≃2 galaxies with kinematic classification into disks or mergers and on ∼100 galaxies in the HUDF field with photometric/spectroscopic redshift between 1.5 ≤ z ≤ 3 and M > 10{sup 9.4} M{sub ⊙}. We find that a combination of the asymmetry A{sub MASS} and M{sub 20, MASS} indices measured on the stellar mass maps can efficiently identify real (major) mergers with ≲20% contamination from clumpy disks in the merger sample. This mass-based classification cannot be reproduced in star-forming galaxies by H-band measurements alone, which instead result in a contamination from clumpy galaxies which can be as high as 50%. Moreover, we find that the mass-based classification always results in a lower contamination from clumpy galaxies than an H-band classification, regardless of the depth of the imaging used (e.g., CANDELS versus HUDF).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2010

CHARACTERIZING THE THERMOSPHERE OF HD209458b WITH UV TRANSIT OBSERVATIONS

Transmission spectroscopy at UV wavelengths is a rich and largely unexplored source of information about the upper atmospheres of extrasolar planets. So far, UV transit observations have led to the detection of atomic hydrogen, oxygen, and ionized carbon in the upper atmosphere of HD209458b. The interpretation of these observations is controversial-it is not clear if the absorption arises from an escaping atmosphere interacting with the stellar radiation and stellar wind, or from the thermosphere inside the Roche lobe. In this paper, we introduce an empirical model that can be used to analyze UV transit depths of extrasolar planets. We use this model to interpret the transits of HD209458b in the H I 1216 and the O I 1304 triplet emission lines. The results indicate that the mean temperature of the thermosphere is T = 8000-11,000 K and that the H{sub 2}/H dissociation front is located at pressures between p = 0.1 and 1 {mu}bar, which correspond to a distance r{approx} 1.1 R{sub p} from the center of the planet. The upper boundary of the model thermosphere is located at r = 2.7-3 R{sub p} , above which the atmosphere is mostly ionized. We find that the H I transit depth in the wings of the H Ly{alpha} line reflects the optical depth of the thermosphere, but that the atmosphere also overflows the Roche lobe. By assuming a solar mixing ratio of oxygen, we obtain an O I transit depth that is statistically consistent with the observations. An O I transit depth comparable to the H I transit depth is possible if the atmosphere is undergoing fast hydrodynamic escape, the O/H ratio is supersolar, or if a significant quantity of neutral oxygen is found outside the Roche lobe. We find that the observations can be explained solely by absorption in the upper atmosphere and extended clouds of energetic neutral atoms or atoms strongly perturbed by radiation pressure are not required. Due to the large uncertainty in the data, repeated observations are necessary to better constrain the O I transit depths and thus the composition of the thermosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Superconductivity and phase diagrams of CaK(Fe 1- x Mn x ) 4 As 4 single crystals

In order to study the effects of Mn substitution on the superconducting and magnetic ground state of CaKFe 4 As 4 (T c = 35 K), members of the CaK (Fe 1–x Mn x ) 4 As 4 series have been synthesized by high-temperature solution growth in single-crystalline form and characterized by elemental analysis, thermodynamic, and transport measurements. These measurements show that the superconducting transition temperature decreases monotonically and is finally suppressed below 1.8 K as x is increased from 0 to 0.036. For x values greater than 0.016, signatures of a magnetic transition can be detected in both thermodynamic and transport measurements in which kinklike features allow for the determination of the transition temperature T* that increases as Mn substitution increases. Here, a temperature-composition (T–x) phase diagram is constructed, revealing a half-dome of superconductivity with the magnetic transition temperature T* appearing near 26 K for x ~ 0.017 and rising slowly up to 33 K for x ~ 0.036. In addition to the creation of the T–x phase diagram for CaK(Fe 1–x Mn x ) 4 As 4 , specific-heat data are used to track the jump in specific heat at T c ; the CaK(Fe 1–x Mn x ) 4 As 4 data do not follow the scaling of ΔC p with $T$$^{3}_{c}$ as many of the other Fe-based superconducting systems do. These data suggest that, as magnetic pair breaking is present, the jump in C p for a given T c is reduced. Elastoresistivity coefficients 2m 66 and m 11 – m 12 as a function of temperature are also measured. 2m 66 and m 11 – m 12 are qualitatively similar to CaK(Fe 1–x Ni x ) 4 As 4 . This may indicate that the magnetic order in Mn-substituted system may be still the same as CaK(Fe 1–x Mn x ) 4 As 4 . Superconductivity of CaK(Fe 1–x Mn x ) 4 As 4 is also studied as a function of magnetic field. A clear change in H' c2 (T)/T c , where H' c2 (T) is dH' c2 (T)/dT, at x ~ 0.015 is observed and probably is related to change of the Fermi surface due to magnetic order. Coherence lengths and the London penetration depths are also calculated based on H c1 and H c2 data. Coherence lengths as the function of x also show the changes near x = 0.015, again consistent with Fermi-surface changes associated with the magnetic ordering seen for higher-x values.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2012

Detection and Characterization of Underground Facilities by Stochastic Inversion and Modeling of Data from the New Generation of Synthetic Aperture Satellites (Final Report)

Many clandestine development and production activities can be conducted underground to evade surveillance. The purpose of the study reported here was to develop a technique to detect underground facilities by broad-area search and then to characterize the facilities by inversion of the collected data. This would enable constraints to be placed on the types of activities that would be feasible at each underground site, providing a basis the design of targeted surveillance and analysis for more complete characterization. Excavation of underground cavities causes deformation in the host material and overburden that produces displacements at the ground surface. Such displacements are often measurable by a variety of surveying or geodetic techniques. One measurement technique, Interferometric Synthetic Aperture Radar (InSAR), uses data from satellite-borne (or airborne) synthetic aperture radars (SARs) and so is ideal for detecting and measuring surface displacements in denied access regions. Depending on the radar frequency and the acquisition mode and the surface conditions, displacement maps derived from SAR interferograms can provide millimeter- to centimeter-level measurement accuracy on regional and local scales at spatial resolution of {approx}1-10 m. Relatively low-resolution ({approx}20 m, say) maps covering large regions can be used for broad-area detection, while finer resolutions ({approx}1 m) can be used to image details of displacement fields over targeted small areas. Surface displacements are generally expected to be largest during or a relatively short time after active excavation, but, depending on the material properties, measurable displacement may continue at a decreasing rate for a considerable time after completion. For a given excavated volume in a given geological setting, the amplitude of the surface displacements decreases as the depth of excavation increases, while the area of the discernable displacement pattern increases. Therefore, the ability to detect evidence for an underground facility using InSAR depends on the displacement sensitivity and spatial resolution of the interferogram, as well as on the size and depth of the facility and the time since its completion. The methodology development described in this report focuses on the exploitation of synthetic aperture radar data that are available commercially from a number of satellite missions. Development of the method involves three components: (1) Evaluation of the capability of InSAR to detect and characterize underground facilities ; (2) inversion of InSAR data to infer the location, depth, shape and volume of a subsurface facility; and (3) evaluation and selection of suitable geomechanical forward models to use in the inversion. We adapted LLNL's general-purpose Bayesian Markov Chain-Monte Carlo procedure, the 'Stochastic Engine' (SE), to carry out inversions to characterize subsurface void geometries. The SE performs forward simulations for a large number of trial source models to identify the set of models that are consistent with the observations and prior constraints. The inverse solution produced by this kind of stochastic method is a posterior probability density function (pdf) over alternative models, which forms an appropriate input to risk-based decision analyses to evaluate subsequent response strategies. One major advantage of a stochastic inversion approach is its ability to deal with complex, non-linear forward models employing empirical, analytical or numerical methods. However, while a geomechanical model must incorporate adequate physics to enable sufficiently accurate prediction of surface displacements, it must also be computationally fast enough to render the large number of forward realizations needed in stochastic inversion feasible. This latter requirement prompted us first to investigate computationally efficient empirical relations and closed-form analytical solutions. However, our evaluation revealed severe limitations in the ability of existing empirical and analytical forms to predict deformations from underground cavities with an accuracy consistent with the potential resolution and precision of InSAR data. We followed two approaches to overcoming these limitations. The first was to develop a new analytical solution for a 3D cavity excavated in an elastic half-space. The second was to adapt a fast parallelized finite element method to the SE and evaluate the feasibility of using in the stochastic inversion. To date we have demonstrated the ability of InSAR to detect underground facilities and measure the associated surface displacements by mapping surface deformations that track the excavation of the Los Angeles Metro system. The Stochastic Engine implementation has been completed and undergone functional testing.

58 GEOSCIENCES↗
DOE OSTI2022

Improved limits on the tensor-to-scalar ratio using BICEP and P l a n c k data

In this study, we present constraints on the tensor-to-scalar ratio r using a combination of BICEP/Keck 2018 (BK18) and Planck PR4 data allowing us to fit for r consistently with the six parameters of the Λ CDM model. We discuss the sensitivity of constraints on r to uncertainties in the Λ CDM parameters as defined by the Planck data. In particular, we are able to derive a constraint on the reionization optical depth τ and thus propagate its uncertainty into the posterior distribution for r . While Planck sensitivity to r is slightly lower than the current ground-based measurements, the combination of Planck with BK18 and baryon-acoustic-oscillation data yields results consistent with r = 0 and tightens the constraint to r < 0.032 at 95% confidence.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Transport and Retention of Particulate Organic Matter in Sand: Lab Experiments and Modelling

Flow-through reactor (FTR) experiments were conducted at three different downward vertical flow rates to study the transport and retention of particulate organic matter (Chlorella powder) in riverbed sediments. This data package includes data files (.csv) regarding effluent collected from the FTRs during the experiments (time, duration, volume of each sample collection; concentration of nonreactive bromide tracer; concentration of suspended Chlorella determined by absorbance measurements) and sediment (sand) slices collected from the FTRs after the experiments (mass of Chlorella retained in 1 cm depth intervals determined by loss-on-ignition method). More detailed descriptions of data are provided in the data dictionary, and detailed methods are available in the associated MSc thesis listed in ‘Related References.’ The data dictionary and file level meta data (FLMD) are included in the data package as both .csv and .xlsx files. This data package also includes timelapse videos (.mp4) of the experiments, and modelling scripts associated with the experiments. The modelling scripts are included as MATLAB ‘live scripts’ (.mlx, which can be run using MATLAB), and are also included as .pdf and .html files with output plots included (which can be viewed without a MATLAB license and installation). The data files and modelling scripts are organized into a .zip folder for each of the three FTR experiments (three flow rates).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Depth and elevation of floodplain fine sediment along the East River near Crested Butte, Colorado measured in 2016 and 2017

The depth of floodplain fine sediment was measured at 1,601 points along the East River near Crested Butte, Colorado spanning a study reach approximately 800 m in length in 2016 and 2017. These depths are being used to estimate the volume of floodplain sediment present along the study reach, converted into mass of sediment using bulk density measurements, and finally used to estimate the mass of organic carbon stored in the floodplain based on elemental analysis of percent organic carbon content. Recorded depths include a minimum of 1 cm, a median of 56 cm, a maximum of 175 cm, and a mean with standard deviation of 61 ± 34 cm. This data include a csv file of the coordinates for each point in NAD 83 UTM zone 13, measured sediment depths, distance from the river channel active during 2015 measured using geographic information systems, the elevation of the floodplain surface derived from 0.5-m resolution lidar, and the elevation of the underlying gravel/bedrock surface, and in some cases the distance from the active channel measured in the field along the sampling transect. Also included is an ESRI ArcMap shapefile of the measurement points complete with the data listed above.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

CuAl{sub x}Ga{sub 1−x}Se{sub 2} thin films for photovoltaic applications: Optical and compositional analysis

Highlights: ► Wide band gap CAGS thin films have been obtained by selenization of evaporated metallic precursors. ► Direct nonlinear dependence of the band gap energy with the Al/(Al + Ga) ratio is found. ► The bowing parameter decreases when the CAGS film thickness increases. ► The Cu at% remains constant in depth, together with some Al, Ga and Se gradients. ► Surface is strongly oxidized but the oxidation is relatively low in bulk. - Abstract: Wide-band gap chalcopyrite semiconductors have a great interest due to their potential application in multi-junction thin film solar cells or as window layers. Polycrystalline CuAl{sub x}Ga{sub 1−x}Se{sub 2} (CAGS) thin films have been prepared by selenization of evaporated metallic precursor layers on bare and Mo-coated soda lime glass substrates. The optical properties of CAGS films of 2 thicknesses have been analyzed by spectrophotometry in the visible-infrared (VIS-IR) and the compositional characteristics have been studied by energy dispersive analysis of X-rays (EDAX) and X-ray photoelectron spectroscopy (XPS). The optical transmission increases and the band gap energy shifts toward higher values as the Al content increases, which indicates the partial substitution of Ga by Al. The dependence of the band gap with the composition has resulted to be nonlinear and a bowing parameter of b = 0.62 and b = 0.54 for 0.6 μm and 1.1 μm-CAGS samples, respectively, has been obtained. XPS data have shown an Al, Ga and Se composition gradient in depth and a surface strongly oxidized. However, XPS reveals that the Cu composition remains constant in depth and the oxidation is relatively low in bulk increasing slightly in the interface with Mo/SLG. Moreover, samples with high Al content reveal a higher contribution of CuO in depth.

36 MATERIALS SCIENCE↗