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DOE OSTI2013

Oak Ridge Environmental Information System (OREIS) Enhancements - 13109

Significant cleanup has been accomplished on the Oak Ridge (OR) site since it was placed on the National Priorities List (NPL) in 1989, and a final evaluation of Zone 1 at the East Tennessee Technology Park (ETTP) under the Comprehensive Environmental Response, Compensation, and Liability Act of 1988 (CERCLA) has been initiated. The Oak Ridge Environmental Information System (OREIS) is the database for storing OR site environmental characterization and monitoring data. Consideration of a final decision under CERCLA prompted several enhancements to OREIS that were designed to provide future users a clear picture of remediation progression across the OR site. The enhancements to OREIS are ongoing and fall into four categories: Geographic Information System Interface; Document Association; Remediation Status; Geo-spatial Data (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

GNF fuel technology update

In 2015, Global Nuclear Fuel (GNF) launched the GNF3 fuel design by inserting lead-use assemblies into two boiling water reactors (BWRs) in the U.S. A lead use assembly is a nuclear fuel assembly which is inserted in a reactor core to confirm its performance. A third set of GNF3 lead-use assemblies are scheduled to be inserted into another reactor in the spring of 2017. GNF3 is a robust next-generation 10*10 fuel design that will improve both fuel cycle and fuel reliability. In addition, GNF3 will be delivered in a fully assembled condition - forgoing the need to insert fuel channels over the bundles at the site. The process of shipping BWR fuel in a channeled configuration is complex and requires an understanding of the potential high-cycle and low-cycle fatigue conditions that can occur during shipping, as characterized by accelerometer data from ship tests. The key component in evaluating channeled fuel shipping is the spacer, and the GNF3 spacer fatigue performance was found to be approximately twice that of GNF2. While fuel reliability has traditionally been related to the avoidance of fuel leakers, for the past 15 years channel - control blade interference has been a close second for concern. To eliminate this problem, GNF3 will come standard with NSF (a zirconium alloy) channels that are effectively resistant to fluence gradient-induced bow and shadow corrosion-induced bow. In addition to the development of GNF3, GNF is evaluating the use of advancing 3D metal printing or additive manufacturing for manufacturing fuel bundle components. Additive manufacture offers the hope of more flexibility in design and shorter manufacturing development cycles. However, since there is little experience with this technology in the nuclear industry, GNF has been evaluating the use of additive manufacture to fabricate small scale components that are easily retrieved from the reactor for testing. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2015

X-Ray Diffraction of Slag-Based Sodium Salt Waste Forms - 15513

Cementitious materials are used to solidify and stabilize aqueous based radioactive waste containing sodium salts. The types and proportions of cementitious ingredients used to treat aqueous radioactive waste streams containing sodium salts depend on the performance objectives for the waste forms and the compositions of the waste streams. This paper documents sample preparation and x-ray diffraction results for a series of materials made with water or highly alkaline sodium salt simulated waste water and cementitious binders. The objective of this study was to: 1) generate a base line for the evolution of the waste form as a function of time and conditions, 2) design new binders based on mineralogy of the binder, 3) understand and predict anion and cation leaching behavior of contaminants of concern, and 4) predict performance of the waste forms for which phase solubility and thermodynamic data are available. Characterization of the mineralogy is also important for understanding the buffering effects that the waste form has on infiltrating water / leachates. In summary, mixtures of Type II portland cement, Grade 100 ground granulated blast furnace slag (GGBFS) and carbon burn-out (CBO) Class F Fly ash which were hydrated with water contained hydrated phase assemblages typical of those reported in the literature. The calcium silicate hydrate phase assemblage in samples hydrated with the alkaline 4.4 M sodium salt simulated waste solution was found to be a function of the (CaO + MgO) / (SiO{sub 2} + Al{sub 2}O{sub 3}) ratio of the samples characterized. No significant differences were detected in samples cured 2 months and 14 months in sealed containers at ambient indoor temperatures. Slag and a blend of slag and cement hydrated with caustic 4.4 M Na salt solution resulted in the most crystalline matrix. In addition to poorly ordered C-S-H, these samples contained fairly well ordered C-S-H I (a precursor of 14A tobermorite) and 11 A Al-substituted tobermorite. These crystalline C-S-H phases did not form or were present in only trace amounts in slag blends containing about 45 to 62 mass percent fly ash. These slag-Class F fly ash blends had a higher silica plus alumina content relative to lime and magnesia than the blends that produced C-S-H I and Al-substituted tobermorite. The calcium silicate binder in the 10:45:45 mixture of cement: slag: fly ash was made up of poorly ordered C-S-H. The sample cured for 14 months may contain a small amount of the more crystalline calcium silicate hydrate phases. Layered double hydroxides in the hydrotalcite (magnesium-aluminum carbonate hydroxide) and hydrocalumite / AFm phases (calcium aluminum hydroxide) were present in mixtures containing slag. The specific phase(s) were not identified because these phases form solid solutions and have a considerable amount of overlap in their x-ray patterns. Sodium nitrate was the only sodium salt phase identified in x-ray diffraction patterns of the samples hydrated with salt solution. Drying during x-ray diffraction sample preparation may have resulted in precipitation of the sodium nitrate or it may have been present in the samples prior to x-ray sample preparation. Sodium sulfate, aluminate, and carbonate may have been incorporated in the structures of the layered double hydroxide (AFm) type phases. These mixed metal layered double hydroxides make up an important fraction of the matrix in the slag containing blends hydrated with caustic salt solution. They are among the few oxide-based phases that exhibit substantial, permanent anion exchange capacity [Kirkpatrick, et al. 1999, Plamer, et al., 2009, and Zhang and Reardon, 2003]. They also contribute to the structural properties of cementitious matrices [Taylor, 1997]. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2016

The Near-Earth Meteoroid Flux, Speed Distribution, and Uncertainty

Meteoroids are known to pose a threat to spacecraft; they can puncture components, disturb spacecraft attitude, and possibly create secondary electrical effects. Accurate environment models are therefore critical for mitigating meteoroid-related risks. While there are several meteoroid environment models available for assessing spacecraft risk, the uncertainties associated with these models are not well understood. Because meteoroid properties are derived from indirect observations such as meteors and impact craters, the uncertainty in the meteoroid flux is potentially quite large. We combine existing meteoroid flux measurements with new radar and optical meteor data to improve our characterization of the meteoroid flux onto the Earth and its velocity distribution. We use data extracted from the NASA all-sky network, the Canadian Automated Meteor Observatory, and the Canadian Meteor Orbit Radar. We improve our characterization of the observed meteoroid speed distribution by incorporating modern descriptions of the ionization efficiency (e.g., Thomas et al., 2016). We also present estimates of the uncertainties associated with our meteoroid flux distribution. Finally, we discuss the implications for spacecraft. Our model is constrained by the cratering rate on the space-facing surface of LDEF, and thus the risk posed to spacecraft by meteoroid-induced physical damage is the least uncertain component of our model. Other sources of risk, however, may vary. For instance, a lower average meteoroid speed would require a higher meteoroid mass flux in order to match the LDEF crater counts, leading to higher predicted rates of attitude disturbances.

Moorhead, Althea↗

NASA NTRS1997

Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

Lam, N.↗

DOE OSTI2019

The Morphology and Structure of Stellar Populations in the Fornax Dwarf Spheroidal Galaxy from Dark Energy Survey Data

Using deep wide-field photometry 3 yr data (Y3) from the Dark Energy Survey (DES), we introduce a panoramic study of the Fornax dwarf spheroidal galaxy. The data discussed here—a small subset of the full survey—uniformly cover a region of 25 deg 2 centered on the galaxy to a depth of g ~ 23.5. We use these data to study the structural properties of Fornax, overall stellar population, and its member stars in different evolutionary phases. We also search for possible signs of tidal disturbance. Fornax is found to be significantly more spatially extended than what early studies suggested. No statistically significant distortions or signs of tidal disturbances were found down to a surface brightness limit of ~32.1 mag arcsec -2 . Yet, there are hints of shell-like features located ~20'–40' from the center of Fornax that may be stellar debris from past merger events. We also find that intermediate-age and young main-sequence populations show different orientation at the galaxy center and have many substructures. The deep DES Y3 data allow us to characterize the age of those young stellar substructures with great accuracy, both those previously known and those newly identified as possible overdensities in this work, on the basis of their color–magnitude diagram morphology. We find that the youngest overdensities are all found on the eastern side of Fornax, where the Fornax field population itself is slightly younger than in the west. In summary, the high-quality DES Y3 data reveal that Fornax has many rich structures and provide insights into its complex formation history.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Best Practice for the Commercial Deployment of Carbon Dioxide Geologic Storage: Adaptive Management Approach

The Plains CO 2 Reduction (PCOR) Partnership is one of seven regional partnerships formed as part of the U.S. Department of Energy’s National Energy Technology Laboratory Regional Carbon Sequestration Partnerships (RCSP) Initiative. The RCSP Initiative is focused on the safe and long-term storage of CO 2 to support the commercial deployment of carbon capture and storage (CCS). To that end, the PCOR Partnership has spent over 10 years developing, testing, and validating the best methods and technologies to conduct the geologic storage of CO 2 (hereafter referred to as CO 2 storage). Through this effort, the PCOR Partnership has formalized an adaptive management approach (AMA) for the commercial development of CO 2 storage projects. The use of this approach, which draws upon the collective experience and lessons learned from the PCOR Partnership, represents best practice for advancing CO 2 storage projects toward commercial deployment. At the heart of the AMA are four technical elements necessary for any successful CO 2 storage project: 1) site characterization; 2) modeling and simulation; 3) risk assessment; and 4) monitoring, verification, and accounting (MVA). Each of these elements plays a key role in gathering and assessing site-specific data that provide a fundamental understanding of the storage complex and its performance. While each of the four technical elements can provide useful data independently, integrating them through the AMA yields a streamlined, fit-for-purpose strategy for the commercial deployment of CO 2 storage. Key to this integration and resulting best practice are feedback loops that allow the results of each element to serve as inputs to the others. Each iteration of the AMA creates an improved understanding of the storage complex and thus more targeted and efficient applications of the technical elements. For the purpose of establishing an adaptive management framework, hard lines have been drawn between the technical elements of the AMA. However, in practice, the rapid and seamless interaction between the elements can blur these lines. For example, to aid in the analysis and interpretation of site characterization data, a static geocellular model is often required. While this model development is part of the technical element, modeling and simulation, it is an integral part of the site characterization effort. Likewise, much of the monitoring data collected as part of the MVA technical element can be used to inform site characterization. This back-and-forth flow of data and use of models between the technical elements continues throughout the project.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Infrared spectroscopy data- and physics-driven machine learning for characterizing surface microstructure of complex materials

There is a need to characterize complex materials and their dynamics under reaction conditions to accelerate materials design. Adsorbate vibrational excitations are selective to adsorbate/surface interactions and infrared (IR) spectra associated with activating adsorbate vibrational modes are accurate, capture details of most modes, and can be obtained operando. Current interpretation depends on heuristic peak assignments for simple spectra, precluding the possibility of obtaining detailed structural information. Here, we combine data-based approaches with chemistry-dependent problem formulation to develop physics-driven surrogate models that generate synthetic IR spectra from first-principles calculations. Using synthetic IR spectra of carbon monoxide on platinum, we implement multinomial regression via neural network ensembles to learn probability distributions functions (pdfs) that describe adsorption sites and quantify uncertainty. We use these pdfs to infer detailed surface microstructure from experimental spectra and extend this methodology to other systems as a first step towards characterizing complex interfaces and closing the materials gap.

Science & Technology - Other Topics↗

DOE OSTI2016

Segmentation of nanotomographic cortical bone images for quantitative characterization of the osteoctyte lacuno-canalicular network

A newly developed data processing method able to characterize the osteocytes lacuno-canalicular network (LCN) is presented. Osteocytes are the most abundant cells in the bone, living in spaces called lacunae embedded inside the bone matrix and connected to each other with an extensive network of canals that allows for the exchange of nutrients and for mechanotransduction functions. The geometrical three-dimensional (3D) architecture is increasingly thought to be related to the macroscopic strength or failure of the bone and it is becoming the focus for investigating widely spread diseases such as osteoporosis. To obtain 3D LCN images non-destructively has been out of reach until recently, since tens-of-nanometers scale resolution is required. Ptychographic tomography was validated for bone imaging in [1], showing clearly the LCN. The method presented here was applied to 3D ptychographic tomographic images in order to extract morphological and geometrical parameters of the lacuno-canalicular structures.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2017

Assessment of the Idaho National Laboratory Remote Handled Low Level Waste Disposal Facility Hydraulic Performance

This document provides a summary of the expected hydraulic performance of the vault drainage system installed at Idaho National Laboratory’s Remote Handled Low-Level Waste disposal facility. Hydraulic performance was assessed through analysis of the mechanical properties of the drainage system and backfill materials, including material gradation and proctor data; laboratory data, including bulk density, porosity, unsaturated hydraulic conductivity, moisture-retention data, and van Genuchten parameters; and field-data collected using in-situ instrumentation with data collected during a vault-scale infiltration characterization test. Hydraulic performance of the vault drainage system was designed to promote a greater than 500-year vault concrete longevity. The predicted hydraulic performance is, in part, a function of the materials used in construction, sequencing of the hydraulic drainage materials, and the as-built condition of the materials following compaction necessary to ensure vault stability. Specifying specific as-built hydraulic properties is exceedingly difficult at the facility specification/design phase. Instead, material mechanical properties were specified and confirmed early during the construction process. As the drainage materials were installed, samples were sent to a laboratory for hydraulic property testing and, after drainage system installation was complete around the performance assessment vaults, a field-scale infiltration test was conducted with data collection to verify the as-built hydraulic performance. This report provides summary data for the measured mechanical properties, laboratory data, and field infiltration characterization test data. Mechanical data have relatively little variability because of the sieve system used when the materials were crushed onsite. Laboratory data were obtained for a relatively small number of material samples, but the data obtained for each sample are extensive. However, laboratory data provide the moisture retention relationships and relative hydraulic conductivity-moisture content relationships for uninstalled materials. Conducting field-scale infiltration tests with collection of moisture retention data and wetting front propagation data allows extension of laboratory data to the as-installed conditions of the vault drainage system. These combined data types are integrated using a numerical simulation of the infiltration characterization test to refine model parameters. The infiltration characterization model will be used to support the hydraulic and concrete performance of the vault system provided in the facility performance assessment.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

An advanced joint inversion system for CO 2 storage modeling with large date sets for characterization and real-time monitoring-enhancing storage performance and reducing failure risks under uncertainties

As large-scale, commercial storage projects become operational, the problem of utilizing information from diverse sources becomes more critically important. In this project, we developed, tested, and applied an advanced joint data inversion system for CO 2 storage modeling with large data sets for use in site characterization and real-time monitoring. Emphasis was on the development of advanced and efficient computational algorithms for joint inversion of hydro-geophysical data, coupled with state-of-the-art forward process simulations. The developed system consists of (1) inversion tools using characterization data, such as 3D seismic survey (amplitude images), borehole log and core data, as well as hydraulic, tracer and thermal tests before CO 2 injection, (2) joint inversion tools for updating the geologic model with the distribution of rock properties, thus reducing uncertainty, using hydro-geophysical monitoring data, and (3) highly efficient algorithms for directly solving the dense or sparse linear algebra systems derived from the joint inversion. The system combines methods from stochastic analysis, fast linear algebra, and high performance computing. The developed joint inversion tools have been tested through synthetic CO 2 storage examples.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2021

Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin - Task 2 Topical Report

This attachment A is a detailed Topical Report for Task 2 (Advanced Field Characterization and Machine Learning Based Data Integration) under the project "Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin." The overall project activity and finding, including the field pilot testing of CO 2 injection are summarized in the companion Final Technical Report The Advanced Field Characterization and Machine Learning Based Data Integration task (Task 2) involved a systematic geologic characterization of the Trenton-Black River (TBR) play in the SMB which included the development of comprehensive datasets, advanced data analytics, risk assessment, and piggyback field characterization. These activities aimed to address the complex carbonate systems by evaluating the extent of fractures, dolomitization, facies, and reservoir properties with the primary objective of informing the static and dynamic modeling, field injection test, and providing input into the development strategy plan. The task was divided into four subtasks: • Subtask 2.1 – Data compilation, review, and analysis • Subtask 2.2 – Risk Assessment • Subtask 2.3 – Advanced Field Characterization • Subtask 2.4 – Integrated Physics-Based Machine Learning and Advanced Data Analytics

02 PETROLEUM↗

DOE OSTI2016

Scalable subsurface inverse modeling of huge data sets with an application to tracer concentration breakthrough data from magnetic resonance imaging

When characterizing subsurface properties is crucial for reliable and cost-effective groundwater supply management and contaminant remediation. With recent advances in sensor technology, large volumes of hydro-geophysical and geochemical data can be obtained to achieve high-resolution images of subsurface properties. However, characterization with such a large amount of information requires prohibitive computational costs associated with “big data” processing and numerous large-scale numerical simulations. To tackle such difficulties, the Principal Component Geostatistical Approach (PCGA) has been proposed as a “Jacobian-free” inversion method that requires much smaller forward simulation runs for each iteration than the number of unknown parameters and measurements needed in the traditional inversion methods. PCGA can be conveniently linked to any multi-physics simulation software with independent parallel executions. In our paper, we extend PCGA to handle a large number of measurements (e.g. 106 or more) by constructing a fast preconditioner whose computational cost scales linearly with the data size. For illustration, we characterize the heterogeneous hydraulic conductivity (K) distribution in a laboratory-scale 3-D sand box using about 6 million transient tracer concentration measurements obtained using magnetic resonance imaging. Since each individual observation has little information on the K distribution, the data was compressed by the zero-th temporal moment of breakthrough curves, which is equivalent to the mean travel time under the experimental setting. Moreover, only about 2,000 forward simulations in total were required to obtain the best estimate with corresponding estimation uncertainty, and the estimated K field captured key patterns of the original packing design, showing the efficiency and effectiveness of the proposed method. This article is protected by copyright. All rights reserved.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS2014

Software Suite to Support In-Flight Characterization of Remote Sensing Systems

A characterization software suite was developed to facilitate NASA's in-flight characterization of commercial remote sensing systems. Characterization of aerial and satellite systems requires knowledge of ground characteristics, or ground truth. This information is typically obtained with instruments taking measurements prior to or during a remote sensing system overpass. Acquired ground-truth data, which can consist of hundreds of measurements with different data formats, must be processed before it can be used in the characterization. Accurate in-flight characterization of remote sensing systems relies on multiple field data acquisitions that are efficiently processed, with minimal error. To address the need for timely, reproducible ground-truth data, a characterization software suite was developed to automate the data processing methods. The characterization software suite is engineering code, requiring some prior knowledge and expertise to run. The suite consists of component scripts for each of the three main in-flight characterization types: radiometric, geometric, and spatial. The component scripts for the radiometric characterization operate primarily by reading the raw data acquired by the field instruments, combining it with other applicable information, and then reducing it to a format that is appropriate for input into MODTRAN (MODerate resolution atmospheric TRANsmission), an Air Force Research Laboratory-developed radiative transport code used to predict at-sensor measurements. The geometric scripts operate by comparing identified target locations from the remote sensing image to known target locations, producing circular error statistics defined by the Federal Geographic Data Committee Standards. The spatial scripts analyze a target edge within the image, and produce estimates of Relative Edge Response and the value of the Modulation Transfer Function at the Nyquist frequency. The software suite enables rapid, efficient, automated processing of ground truth data, which has been used to provide reproducible characterizations on a number of commercial remote sensing systems. Overall, this characterization software suite improves the reliability of ground-truth data processing techniques that are required for remote sensing system in-flight characterizations.

Stanley, Thomas↗

DOE OSTI2026

Raw Lidar and Camera Data Synchronized with Precipitation and Present Weather Data

As part of the sensor characterization task of the SMART 2.0 project, this dataset includes raw data from three spinning lidars ([Ouster OS2-128](https://ouster.com/products/scanning-lidar/os2-sensor/), [Velodyne Puck (VLP-16)](https://velodynelidar.com/products/puck/), and [Velodyne Ultra Puck (VLP-32)](https://velodynelidar.com/products/ultra-puck/)), one camera ([Mako G-319](https://www.alliedvision.com/en/camera-selector/detail/mako/g-319/)), and one present weather sensor ([Vaisala FD-70](https://www.vaisala.com/en/products/weather-environmental-sensors/forward-scatter-fd70)). All data were synchronized, with the log start time indicated in the file name (HHMMSS). The data can be filtered by date, log time (HHMMSS), sensor, frame ID, and weather classification. These data were gathered statically at the Argonne Testbed for Multiscale Observational Science (ATMOS). Two target stop signs were placed in view of the sensors to contribute a target for comparing sensor data under different conditions. The weather data for each day are stored in netCDF “.nc” files. The lidar data contain the X, Y, Z, intensity, reflectivity, and ring from Ouster OS2-128 rev6, Velodyne VLP-16, and Velodyne VLP-32 lidars. ![raw lidar image](LiDAR_pointcloud_ATMOS.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Moisture Monitoring at Area G, Technical Area 54, Los Alamos National Laboratory

Hydrological characterization and moisture monitoring activities provide data required for evaluating the transport of subsurface contaminants in the unsaturated and saturated zones beneath Area G, and for the Area G Performance Assessment and Composite Analysis. These activities have been ongoing at Area G, Technical Area 54 of the Los Alamos National Laboratory since waste disposal operations began in 1957. This report summarizes the hydrological characterization and moisture monitoring activities conducted at Area G. It includes moisture monitoring data collected from 1986 through 2014 from numerous boreholes and access tubes with neutron moisture meters, as well as data collected by automated dataloggers for water content measurement sensors installed in a waste disposal pit cover, and buried beneath the floor of a waste disposal pit. This report is an update of the Jennings and French (2009) moisture monitoring report and includes all data from Jennings and French (2009) and the Draft 2010 Addendum moisture monitoring report (Jennings and French, 2010). For this updated report, all neutron logging data, including neutron probe calibrations, were investigated for quality and pedigree. Some data have been recalculated using more defensible calibration data. Therefore, some water content profiles are different from those in the Jennings and French (2009) report. Monitoring and characterization data generally indicate that some areas of the Area G vadose zone are consistent with undisturbed conditions, with water contents of less than five percent by volume in the top two layers of the Bandelier tuff at Area G. These data also indicate that other areas of the vadose zone are affected by waste disposal activities that have been ongoing at Area G since 1957, a period of nearly 60 years. In some areas, water content profiles indicate increases in water content to depths of tens of meters, especially in areas covered by asphalt and structures.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Genome-Scale Transcription-Translation Mapping Reveals Features of Zymomonas mobilis Transcription Units and Promoters

Efforts to rationally engineer synthetic pathways in Zymomonas mobilis are impeded by a lack of knowledge and tools for predictable and quantitative programming of gene regulation at the transcriptional, posttranscriptional, and posttranslational levels. With the detailed functional characterization of the Z. mobilis genome presented in this work, we provide crucial knowledge for the development of synthetic genetic parts tailored to Z. mobilis . This information is vital as researchers continue to develop Z. mobilis for synthetic biology applications. Our methods and statistical analyses also provide ways to rapidly advance the understanding of poorly characterized bacteria via empirical data that enable the experimental validation of sequence-based prediction for genome characterization and annotation.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1981

Aircraft subfloor response to crash loadings

Results are presented of an experimental and analytical study of the dynamic response to crash loadings of five different load-limiting subfloors for general aviation aircraft. These subfloors provide a high-strength structural floor platform to retain the seats and a crushable zone to absorb energy and limit vertical loads. Experimental static load-deflection data and dynamic deceleration response data for the five subfloors indicated that the high-strength floor platform performed well in that structural integrity and residual strength was maintained throughout the loading cycle. The data also indicated that some of the subfloor crush zones were more effective than others in providing nearly constant load for a range of displacement. The analytical data was generated by characterizing the nonlinear crush zones of the subfloor with static load-deflection data and using the DYCAST nonlinear finite element computer program. Comparisons between experimental and analytical data showed good correlation for the subfloors in which the static deformation mode closely approximated the dynamic deformation mode.

Carden, H. D.↗