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

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Reservoir Modeling by Data Integration via Intermediate Spaces and Artificial Intelligence Tools in MPS Simulation Frameworks

Conditioning stochastic simulations are very important in many geostatistical applications that call for the introduction of nonlinear and multiple-point data in reservoir modeling. Here, a new methodology is proposed for the incorporation of different data types into multiple-point statistics (MPS) simulation frameworks. Unlike the previous techniques that call for an approximate forward model (filter) for integration of secondary data into geologically constructed models, the proposed approach develops an intermediate space where all the primary and secondary data are easily mapped onto. Definition of the intermediate space, as may be achieved via application of artificial intelligence tools like neural networks and fuzzy inference systems, eliminates the need for using filters as in previous techniques. The applicability of the proposed approach in conditioning MPS simulations to static and geologic data is verified by modeling a real example of discrete fracture networks using conventional well-log data. The training patterns are well reproduced in the realizations, while the model is also consistent with the map of secondary data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

INL Fleet Vehicle Characterization Study for the U.S. Department of Navy

Battelle Energy Alliance, LLC, managing and operating contractor for the U.S. Department of Energy’s Idaho National Laboratory, is the lead laboratory for U.S. Department of Energy Advanced Vehicle Testing. Battelle Energy Alliance, LLC collected and evaluated data on federal fleet operations as part of the Advanced Vehicle Testing Activity’s Federal Fleet Vehicle Data Logging and Characterization Study. The Advanced Vehicle Testing Activity’s study seeks to collect and evaluate data to validate use of advanced plug-in electric vehicle (PEV) transportation. This report focuses on US Department of Navy's fleet to identify daily operational characteristics of select vehicles and report findings on vehicle and mission characterizations to support the successful introduction of PEVs into the agency’s fleets. Individual observations of these selected vehicles provide the basis for recommendations related to electric vehicle adoption and whether a battery electric vehicle or plug-in hybrid electric vehicle (collectively referred to as PEVs) can fulfill the mission requirements.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2021

Leaf gas exchange measurements on Carex aquatilis Wahlenb. following a single season warming treatment. Data were collected in 2021 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2017

Leaf gas exchange measurements on Petasites frigidus (L.) Fr. following a single season warming treatment. Data were collected in 2017 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5-25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017-2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2018

Leaf gas exchange measurements on Arctagrostis latifolia (R. Br.) Griseb. following a single season warming treatment. Data were collected in 2018 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vegetation Warming Experiment: Plant Physiology, Utqiagvik (Barrow), Alaska, 2019

Leaf gas exchange measurements on Eriophorum angustifolium Honck. following a single season warming treatment. Data were collected in 2019 from 5 treatment warming chambers and paired control plots located on the Barrow Environmental Observatory (BEO), Utqiagvik, Alaska. Data include CO2 response (ACi) curves, light response (AQ) curves, and dark-adapted respiration (Rdark) logged data measured at controlled leaf temperatures from 5–25 °C. The data package includes 4 data files in .csv format,, and include 4 data files, 10 metadata files and the complete instrument output for all measurements. These data were collected as part of an experiment using Zero Power Warming (ZPW) chambers that delivered a single season warming treatment of ~4 °C above ambient air temperature. Four different plant species were targeted over four experimental years from 2017–2021. See related data packages for processed gas exchange data, leaf trait data (leaf mass per area, leaf nitrogen concentration), ambient and chamber environmental conditions, phenocamera images, thaw depth and GPS locations of chambers. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗
DOE OSTI2020

Radiation Mapping UAV [Poster]

The NuMI (Neutrinos at the Main Injector) target system delivers a high-energy flux of muon-neutrinos towards a detector more than 800 km away with the goal of better understanding the origin of the universe and its evolution. The target system becomes radioactive because it is irradiated by a sub-Mega-Watt power proton beam. Radiological hazard is one of critical issues for a radiological worker which limits the iractivities near the target system; however, they often need to quantify the radiation level of the target system manually. Thus, the objective of this project is to reduce their exposure to radiation while improving the accuracy of the measurements. A quadcopter UAV fitted with a radiation dosimeter is ideal to traverse the irradiated environment as it can be deployed in any space and requires minimal hardware integration to the test room. Due to the lack of indoor GPS signal, this UAV utilizes a series of ultrasonic beacons that release several varied-frequency pulses simultaneously in order to localize the drone. The flight controller returns a 3D coordinate tied to the radiation data to understand precisely where radiation spikes are being emitted from the horn. The flight controller stores log data that can be processed into an easily interpretable map of radiation intensities. The radiation map serves as one of the primary references for planning the transportation of the NuMI horn.

43 PARTICLE ACCELERATORS↗
DOE OSTI2023

Utah FORGE 2439: Well 16B(78)-32 Field-Test Data from Mini-Frac Tests

This submittal includes the field-test data collected during stress tests conducted in the Utah FORGE 16B(78)-32 wellbore to measure/characterize the stresses in the geothermal reservoir. The type of stress test performed is referred to as a mini-frac test or a micro-frac test. The test is a hydraulic fracture test that involves injecting a small volume of water into a short interval of the reservoir that is isolated by a straddle packer to create a fracture. The test provides information about the minimum and maximum horizontal stress at the test depths. A total of seven mini-frac tests were performed within the upper (vertical or nearly vertical) section of the 9-5/8-inch diameter uncased wellbore, between depths of 5,202 ft MD [5,202 ft TVD] and 5,980 ft MD [5966.18 ft TVD]. Two types of data were generated as part of the mini-frac tests. The first type of data is time-series data for each mini-frac test (e.g., injection-rate, test-interval pressure), and are contained in the "Mini-Frac Test Data.zip" file below. The second type is geophysical log data, attached below in the "Geophysical Logs.zip" file. Here, two types of image logs and acoustic logs were obtained before and after the mini-frac tests to examine each test depth for visual evidence of induced fracture(s) and to measure the azimuth (orientation) of any observed fractures. The attached Readme file includes the test depth information and contents of each data file included here. Analysis of the field-test data was conducted and is documented in the attached report below.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Characterization of throughput on the AXI DMA bus for burst data transfer over Ethernet

cThe Xilinx AXI Direct Memory Access (AXI DMA) module is an efficient solution for medium-speed data transfer in Xilinx SoC FPGAs, supporting data rates greater than 1000 Gbps even in very suboptimal operating modes. It facilitates direct transfer of AXI stream data into processor memory without constant software intervention, which reduces overhead and ensures consistent data logging. By utilizing the FPGA's available memory, large circular buffers (1-5 GiB) are used to buffer data and accommodate network limitations, enabling high-rate data bursts. In this study, we measured the performance of AXI DMA under conditions simulating its lowest practical data transfer speeds. The Arbitrary Length Data Sender was used to transmit AXI stream packets at 32-bit width and 100 MHz frequency, a narrow width and slow speed. Results show that the AXI DMA can transfer up to 3192.76 Mbps with large packet sizes but experiences reduced performance for smaller packets, as low as 2.6 Mbps for 4-byte packets. For Ethernet-limited applications, packet sizes between 8,000 and 16,000 bytes provided optimal transfer speeds of 874 to 1600 Mbps. These findings suggest that the AXI DMA is not the limiting factor in systems where packet sizes exceed 8,000 bytes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2018

Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection

Automated analysis methods are crucial aids for monitoring and defending a network to protect the sensitive or confidential data it hosts. This work introduces a flexible, powerful, and unsupervised approach to detecting anomalous behavior in computer and network logs; one that largely eliminates domain-dependent feature engineering employed by existing methods. By treating system logs as threads of interleaved ``sentences'' (event log lines) to train online unsupervised neural network language models, our approach provides an adaptive model of normal network behavior. We compare the effectiveness of both standard and bidirectional recurrent neural network language models at detecting malicious activity within network log data. Extending these models, we introduce a tiered recurrent architecture, which provides context by modeling sequences of users' actions over time. Compared to isolation forests and Principal Components Analysis (PCA), two popular anomaly detection algorithms, we observe superior performance on the Los Alamos National Laboratory Cyber Security dataset. For log-line-level predictions, our best performing character-based model provides test set anomaly scores ranking red team events in the 98th percentile on average, and yields 0.97 area under the receiver operator characteristic curve, demonstrating the strong fine-grained anomaly detection performance of this approach on open vocabulary logging sources.

Cyber Analysis, Deep Learning, language analysis, ↗
DOE OSTI2016

Utah FORGE: Milford Digitized Geophysical Logs from Acord 1

This submission includes digitalized versions of the following: McCulloch Geothermal Corp Acord 1-26 Cover Letter McCulloch Geothermal Corp Acord 1-26 Drilling Plan McCulloch Geothermal Corp Acord 1-26 Bond Documents Division of Water Rights Permission to Drill Drillers Log Geothermal Data (Mud) Log Compensated Densilog - Neutron Log Dual Induction Focused Log BHC Acoustilog Differential Temperature Log Dual Induction Focused Log Gamma Ray Neutron Log Temperature Log Caliper Temperature Log (Run 3) Densilog Gamma Ray Neutron Log Temperature Log (Run 4) Compensated Densilog Sample Log (Page 1 of 2) Report of Well Driller Stratigraphic Report (J.E. Welsh) Photographs and Negatives of Acord 1-26 Well Site (7) Petrography Report (M.J. Sweeney) Cuttings Samples (21 Boxes at Utah Core Research Center)

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Oil & Natural Gas Technology A new approach to understanding the occurrence and volume of natural gas hydrate in the northern Gulf of Mexico using petroleum industry well logs

The northern Gulf of Mexico has been the target for the petroleum industry for exploration of conventional energy resource for decades. We have used the rich existing petroleum industry well logs to find the occurrences of natural gas hydrate in the northern Gulf of Mexico. We have identified 798 wells with well log data within the gas hydrate stability zone. Out of those 798 wells, we have found evidence of gas hydrate in well logs in 124 wells (15% of wells). We have built a dataset of gas hydrate providing information such as location, interval of hydrate occurrence (if any) and the overall quality of probable gas hydrate. Our dataset provides a wide, new perspective on the overall distribution of gas hydrate in the northern Gulf of Mexico and will be the key to future gas hydrate research and prospecting in the area.

03 NATURAL GAS↗
DOE OSTI2020

A Visual Analytics Framework for Reviewing Streaming Performance Data

Understanding and tuning the performance of extreme-scale parallel computing systems demands a streaming approach due to the computational cost of applying offline algorithms to vast amounts of performance log data. Analyzing large streaming data is challenging because the rate of receiving data and limited time to comprehend data make it difficult for the analysts to sufficiently examine the data without missing important changes or patterns. To support streaming data analysis, we introduce a visual analytic framework comprising of three modules: data management, analysis, and interactive visualization. The data management module collects various computing and communication performance metrics from the monitored system using streaming data processing techniques and feeds the data to the other two modules. The analysis module automatically identifies important changes and patterns at the required latency. In particular, we introduce a set of online and progressive analysis methods for not only controlling the computational costs but also helping analysts better follow the critical aspects of the analysis results. Finally, the interactive visualization module provides the analysts with a coherent view of the changes and patterns in the continuously captured performance data. Through a multi-faceted case study on performance analysis of parallel discrete-event simulation, we demonstrate the effectiveness of our framework for identifying bottlenecks and locating outliers.

Human-centered computing↗
DOE OSTI2015

Quantifying socio-economic indicators in developing countries from mobile phone communication data: applications to Côte d’Ivoire

The widespread adoption of mobile devices that record the communications, social relations, and movements of billions of individuals in great detail presents unique opportunities for the study of social structures and human dynamics at very large scales. This is particularly the case for developing countries where social and economic data can be hard to obtain and is often too sparse for real-time analytics. In this paper, we leverage mobile call log data from Côte d’Ivoire to analyze the relations between its nation-wide communications network and the socio-economic dynamics of its regional economies. We introduce the CallRank indicator to quantify the relative importance of an area on the basis of call records, and show that a region’s ratio of in- and out-going calls can predict its income level. We detect a communication divide between rich and poor regions of Côte d’Ivoire, which corresponds to existing socio-economic data. Our results demonstrate the potential of mobile communication data to monitor the economic development and social dynamics of low-income developing countries in the absence of extensive econometric and social data. Finally, our work may support efforts to stimulate sustainable economic development and to reduce poverty and inequality.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Model Package Report: Geoframework Model of the Hanford Site 100 Area

The purpose of the 100 Area Geoframework Model (GFM) is to provide a reasonable, consistent, and defensible three dimensional representation of the hydrostratigraphic units below the River Corridor at the Hanford Site to support contaminant fate and transport models. The GFM is a three dimensional representation of the subsurface geologic structure. From this, three dimensional geologic model-exported results, in the form of points or surfaces, are used as inputs to populate and assemble the various numerical model architectures. The objective of this report is to define the process used to produce a hydrostratigraphic model for the hydrostratigraphic units beneath the Hanford Site 100 Area. The GFM may support several other CH2M HILL Plateau Remediation Company project needs and objectives, including providing geologic information to support remedial investigations and actions and as a tool to present River Corridor geology and contaminant extents. The GFM was constructed based on information through 2019 available in the Integrated Data Management System, Hanford Environmental Information System, and the Hanford Site geologic contacts (GeoContacts) datasets. Revisions to the 100 Area GFM may occur to incorporate new data and information. Each version will be maintained in configuration control using date stamps for identifying supporting databases, figures, and interpretations. Supporting data include the final three dimensional geoframework surfaces, two dimensional structure and isopach maps, and all the geologic contact inputs and interpreted geologic log data. These final products provide a supporting set of geologic information that together allow the creation of the GFM. This information is managed, updated, and maintained via CH2M HILL Plateau Remediation Company under the Environmental Model Management Archive.

58 GEOSCIENCES↗
DOE OSTI2015

Fort Bliss Geothermal Area Data: Temperature profile, logs, schematic model and cross section

This dataset contains a variety of data about the Fort Bliss geothermal area, part of the southern portion of the Tularosa Basin, New Mexico. The dataset contains schematic models for the McGregor Geothermal System, a shallow temperature survey of the Fort Bliss geothermal area. The dataset also contains Century OH logs, a full temperature profile, and complete logs from well RMI 56-5, including resistivity and porosity data, drill logs with drill rate, depth, lithology, mineralogy, fractures, temperature, pit total, gases, and descriptions among other measurements as well as CDL, CNL, DIL, GR Caliper and Temperature files. A shallow (2 meter depth) temperature survey of the Fort Bliss geothermal area with 63 data points is also included. Two cross sections through the Fort Bliss area, also included, show well position and depth. The surface map included shows faults and well spatial distribution. Inferred and observed fault distributions from gravity surveys around the Fort Bliss geothermal area.

15 GEOTHERMAL ENERGY↗
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↗