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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hierarchical deep reinforcement learning reveals a modular mechanism of cell movement

Time-lapse images of cells and tissues contain rich information about dynamic cell behaviours, which reflect the underlying processes of proliferation, differentiation and morphogenesis. However, we lack computational tools for effective inference. Here we exploit deep reinforcement learning (DRL) to infer cell–cell interactions and collective cell behaviours in tissue morphogenesis from three-dimensional (3D) time-lapse images. We use hierarchical DRL (HDRL), known for multiscale learning and data efficiency, to examine cell migrations based on images with a ubiquitous nuclear label and simple rules formulated from empirical statistics of the images. When applied to Caenorhabditis elegans embryogenesis, HDRL reveals a multiphase, modular organization of cell movement. Imaging with additional cellular markers confirms the modular organization as a novel migration mechanism, which we term sequential rosettes. Furthermore, HDRL forms a transferable model that successfully differentiates sequential rosettes-based migration from others. Our study demonstrates a powerful approach to infer the underlying biology from time-lapse imaging without prior knowledge.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

PiCAM: A Raspberry Pi-based open-source, low-power camera system for monitoring plant phenology in Arctic environments

Time-lapse cameras have been widely used as a tool to monitor the timing of seasonal vegetation growth. These simple, relatively inexpensive systems can provide high-frequency observations of leaf development and demography which are critical data sets needed to characterize plant phenology from species to landscapes. This is important for understanding how plants are responding to global changes, as well as for validating satellite-derived phenology products. However, in remote regions including the high-latitude Arctic, deploying time-lapse cameras could be challenging. The remoteness and lack of widespread power and telecommunications infrastructure limit options for the installation, maintenance and retrieval of data and equipment, and make it difficult for cameras to survive in extreme weather (e.g. long cold winters). To improve our understanding of Arctic phenology, new technologies are required to address these challenges. Here, we present a novel, low-power, compact, lightweight time-lapse camera system, called power-interval camera automation module (PiCAM). The PiCAM was designed with explicit consideration to simplify deployment (i.e. without a need for external power supplies) of camera systems and to address the challenges of camera survival in harsh Arctic environments. In this paper, we describe the design, setup and technical details of the PiCAM and provide a roadmap for how to build and operate these systems. As proof of concept, we deployed 26 PiCAMs at three low-Arctic tundra sites on the Seward Peninsula, Alaska in early August 2021 for characterizing Arctic plant phenology. Of the 26 PiCAMs, 70% remained active at the point of our revisit in late July 2022 despite the extreme winter temperatures they experienced (< –30°C, heavy snow cover). We extracted key plant phenology metrics from the PiCAMs and captured strong differences across key Arctic plant species. We showed that the PiCAM has the potential to be widely used for monitoring plant phenology across the broader Arctic region, addressing the need for ground-based understanding of Arctic phenological diversity to develop knowledge of plant response to climate change and to validate remote sensing products.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Final report of a scalable, automated, semipermanent seismic array (SASSA) method for detecting CO 2 extent during geologic CO 2 injection

The scalable, automated, semipermanent seismic array (SASSA) project led and managed by the Energy & Environmental Research Center (EERC) was designed as a 3-year proof-of-concept study to evaluate and demonstrate an innovative application of the seismic method. The concept was to use a sparse surface array of 96 nodal seismic sensors paired with a single, remotely operated active seismic source at a fixed location to monitor for CO 2 saturation changes in a subsurface reservoir by processing the data for time-lapse changes at individual, strategically chosen reservoir reflection points. The combination of autonomous equipment and modern processing algorithms was used to apply the seismic method in a manner different from the normal paradigm of collecting a spatially dense data set to produce an image. It was used instead to monitor individual, strategically chosen reservoir reflection points for detectable signal character changes that could be attributed to the passing of a CO 2 saturation front or, possibly, changes in reservoir pressure. Data collection occurred over the course of 1 year at an oil field undergoing CO 2 injection for enhanced oil recovery (EOR) and focused on four overlapping “five-spot” EOR injector–producer patterns. Selection, procurement, configuration, installation, and testing of project equipment and collection of five baseline data sets were completed in advance of CO 2 injection within the study area. Weekly remote data collection produced 41 incremental time-lapse records for each of the 96 nodes. Validation was provided by two methods: 1) a conventional 2-D seismic line acquired through the center of the study area before injection started and again after the project ended and processed in a time-lapse manner and 2) by CO 2 saturation maps created from reservoir simulations based on injection and production history matching. Interpreted results were encouraging but mixed, with indications of changes likely due to the presence of CO 2 on some node reflection points where and when effects would be expected and noneffects where no CO 2 was expected, while results at some locations where simulation outputs suggested CO 2 should be present were ambiguous. Acquisition noise impacted interpretation of data at several locations. Many lessons learned were generated by the study to inform and improve results on a follow-up study. The ultimate aim of the project was to evaluate whether deployment of a SASSA technology can provide a useful and cost-effective monitoring solution for future CO 2 injection projects. The answer appears to be affirmative, with the expectation that lessons learned applied to future iterations, together with technology advances, will likely result in significant improvements.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluation of Electrical Resistivity Tomography to Monitor the Transport of Past Releases Beneath Tank Farms

Underground storage tanks at the Hanford Site, in southeastern Washington State, hold radioactive waste generated from four decades of plutonium production. The 149 single-shell tanks and the 28 double-shell tanks have all exceeded their initial design life of approximately 25 years. At least 67 tanks are assumed to have leaked in the past, resulting in radioactive releases into the vadose zone. Gamma ray logging within dry monitoring wells is currently the primary method for tracking the migration of leaked tank waste through the vadose zone. While this approach provides an accurate assessment of radioactive contamination, that information is only provided near (within ~1m) the borehole, leaving most of the vadose zone unmonitored, particularly the important region directly beneath the tank. This report describes a numerical study that investigates the feasibility and performance of time-lapse 3D electrical resistivity tomography (ERT) for long-term monitoring of a hypothetical tank waste location and migration through the vadose zone. ERT is a method of remotely imaging the bulk electrical conductivity (EC) of the subsurface, which is significantly impacted by the presence of conductive solid and liquid tank waste. The release of liquid tank wastes increases subsurface fluid conductivity and saturation over time, creating a target to use time-lapse ERT for long-term monitoring. Although the presence of metallic infrastructure can cause ERT interference, recent advancements in ERT data processing enable the deleterious effects of buried metallic infrastructure (e.g. pipes, wellbore casings, tanks) to be removed to better determine the liquid tank waste migration over time. Three hypothetical realistic scenarios were simulated in the ERT evaluation. The first two scenarios assume the same leak amount and rate (i.e., between 1/1/1951 and 12/31/1951 at the rate of 347 m 3 per year) but different leaky tanks. Scenario 1 assumes leaks under tank B-102, which is located on the edge of the B-tank farm and surrounded by a few metallic infrastructure including cased pipes/wells/tanks. Scenario 2 assumes leaks under tank B-108, which is located near the center of the B-tank farm and surrounded by larger amount of metallic infrastructure than B-102. Scenario 3 assumes the same metallic infrastructure as B-102, with a more recent contaminant leak that was simulated to have occurred between 1/1/2018 and 12/31/2023 at a rate of 1.89 m 3 per year. The leak time in Scenarios 1 and 2 corresponds to a historical overfill event in 1951 and Scenario 3 corresponds to a recent found tank leak in 2019. In each scenario, a “true” bulk EC model vs. time reflecting contaminant migration was generated. ERT data was simulated from these “true” bulk EC models and a time-lapse ERT inversion produced “imaged” bulk EC vs. time. Three electrode configurations in two, four and eight boreholes surrounding the leak tank were used in the ERT simulations in each scenario. These borehole configurations were considered logistically feasible and cost-effective for monitoring. The hypothetical ERT boreholes are assumed to have non-metallic casing. By comparing the “imaged” bulk EC with the “true” bulk EC, it was demonstrated that the three configurations of wells used (two, four, and eight wells) were able to successfully monitor the migration of tank leaks through the vadose zone, with bulk EC resolution increasing with the number of down borehole ERT arrays for all scenarios. Therefore, the use of eight boreholes to perform ERT monitoring beneath the tanks provided the best spatiotemporal information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Robust Carbon Dioxide Plume Imaging Using Joint Tomographic Inversion of Seismic Onset Time and Distributed Pressure and Temperature Measurements (Final Report)

We develop and demonstrate rapid and cost-effective methodologies for spatiotemporal tracking of CO2 plumes during geologic sequestration using joint inversion of seismic data and distributed pressure and temperature measurements. Key elements of our methodology are: (a) a computationally efficient approach to pressure and temperature propagation, (b) analysis of time lapse seismic data using a novel ‘seismic onset time’ approach to detect fluid front propagation, and (c) data assimilation and uncertainty assessment via joint inversion of pressure, temperature and time lapse seismic data, and (d) validating the numerical tomographic inversion using a CO2 injection demonstration projects, specifically data collected from the from the Petra Nova Parish Holdings CCUS project in the West Ranch Field, Texas and the Chester-16 reef CO2 injection site in Northern Michigan which is part of the DOE Midwestern Carbon Sequestration Project. The research team is led by Texas A&M University and includes Battelle as a subcontractor with support from Shell, Anadarko, Chevron and JX Nippon. A carbon dioxide (CO2) water-alternating-gas (WAG) pilot was conducted to gain insights into tertiary oil recovery potential via CO2 flood in the West Ranch Field as part of the Petra Nova project, the world’s largest post-combustion CO2 capture and utilization initiative. With a fluvial formation geology and large contrasts in permeability, this is a challenging and novel application of CO2 enhanced oil recovery (EOR). We build a predictive dynamic model of the subsurface that incorporates the multiphase and compositional data acquired during the pilot operation. The calibrated model is used for the carbon dioxide plume imaging. The study began with an initialization of the pilot sector model extracted from a calibrated full-field model. The pilot model calibration follows a two-step hierarchical workflow. First, we performed a large-scale update of the permeability distribution by integrating available bottomhole pressure and multiphase production data. In the second step, local permeability field is fine-tuned using a streamline-based method to match CO2 breakthrough times at the producers. The predictive capability of the calibrated model was verified through two blind validation tests: (1) the model showed good agreement with saturation logs acquired at two observation wells; and (2) the model reproduced the CO2 recovery as a fraction of the injected CO2. The use of seismic onset times has shown great promise for integrating near-continuous seismic surveys for updating geologic models. In this study, we analyze the impact of seismic survey frequency on the onset time approach aiming to extend the application of onset time to infrequent seismic surveys. In addition, we quantitatively examine the nonlinearity of the onset time method and compare it to the commonly used amplitude inversion method. We carry out a sensitivity analysis of seismic survey frequency based on the complete seismic survey data (over 175 surveys) of steam injection in a heavy oil reservoir (Peace River Unit) in Canada. Our results show that an adequate onset time map can be obtained from the infrequent seismic surveys by interpolation between seismic surveys as long as there is no change in the dominant underlying physics between the successive surveys. The study also shows that nonlinearity of the onset time method can be -smaller than that of the amplitude inversion method by several orders of magnitude. Application to the Brugge benchmark case shows that the onset time method obtains comparable permeability update as the traditional seismic amplitude inversion method with faster computation and improved convergence characteristics. We extend the streamline-based data integration approach to incorporate distributed temperature sensor (DTS) data using the concept of thermal tracer travel time. Then, a hierarchical workflow composed of evolutionary and streamline methods is employed to jointly history match the DTS and pressure data. Finally, CO2 saturation and streamline maps are used to visualize the CO2 plume movement during the sequestration process. The hierarchical workflow is applied to a carbon sequestration project in a carbonate reef reservoir within the Northern Niagaran Pinnacle Reef Trend in Michigan, USA. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at the injection well and a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. The history matching results indicate that the CO2 movement is mostly restricted to the intended zones of injection which is consistent with an independent warm-back analysis of the temperature data. In addition to employing simulation models and inverse methods for CO2 plume imaging, we also initialized a data-driven technology for detecting inter-well connectivity based on production and pressure data. Our machine-learning framework is built on the statistical recurrent unit (SRU) model and interprets well-based injection/production data into inter-well connectivity without relying on a geologic model. We test it on synthetic and field-scale CO2 EOR projects utilizing the water-alternating-gas (WAG) process. The validation of the proposed data-driven inter-well connectivity assessment is performed using synthetic data from simulation models where inter-well connectivity can be easily measured using the streamline-based flux allocation. The SRU model is shown to offer excellent prediction performance on the synthetic case. Despite significant measurement noise and frequent well shut-ins imposed in the field-scale case, the SRU model offers good prediction accuracy, the overall relative error of the phase production rates at most producers ranges from 10% to 30%. It is shown that the dominant connections identified by the data-driven method and streamline method are in close agreement. Texas A&M University, the lead organization in the project, was primarily responsible for the development of tomographic approaches for CO2 plume mapping in conjunction with distributed pressure, temperature and seismic onset time data. Battelle, as a subcontractor, was primarily responsible for the development of analytical and empirical methods for analyzing transient injection rate and pressure data from point/line sources such as injection and monitoring wells. An additional area of emphasis for Battelle was the use of machine learning for such tasks as inferring reservoir connectivity information from injection-production data, and identifying variable importance for machine learning-based proxy models developed from full-physics simulations. The two organizations also collaborated on the application of the tomographic inversion methodology for a field data set.

02 PETROLEUM↗
DOE OSTI2022

Geophysical Characterization and Monitoring of the 200 Area Treated Effluent Disposal Facility to Support Permit Renewal; TEDF Geophysical Monitoring

The Treated Effluent Disposal Facility (TEDF), located in the 200 East Area of the Hanford Site, is a site where non-hazardous and non-radioactive liquid wastes are disposed into two state-permitted infiltration basins. In 2016, the Washington State Department of Ecology denied a permit renewal request for TEDF due to the inability to adequately assess the impact of TEDF discharge water on the underlying groundwater quality. TEDF overlies the relatively impermeable Ringold Lower Mud (RLM) unit, whose upper contact lies in the vadose zone approximately 30 m below ground surface and approximately 10 m above the water table boundary. The RLM is assumed to isolate TEDF discharge water from the natural groundwater aquifer, which is monitored using wellbores screened below the RLM. Therefore, samples collected from monitoring wells near TEDF are not considered representative of TEDF discharge water. Rather, TEDF discharge water is assumed to mound on top of the RLM to form a perched aquifer. To support permitting of the TEDF, a new monitoring well is required that can be used to sample water from the presumed perched water aquifer above the RLM. Ideally, the screened section of the well would be located at the peak of the perched water mound(s), which presumably occurs at the point of maximum vertical flux from TEDF to the RLM, or equivalently where the dominant infiltration flow paths reach the RLM. This report describes how time-lapse 3D electrical resistivity tomography (ERT) was used in conjunction with nominal TEDF discharge operations to image the dominant flow paths from each pond to the RLM. Results are summarized in Figure ES.1. Figure ES.1A shows a satellite image of the TEDF overlain by an array of surface ERT electrodes. The solid and dashed black circles denote the zones of maximum vertical flux at the RLM within the south and north ponds, respectively, and presumably the regions where perched water peaks during discharge. Figure ES.1B shows time-lapse difference imaging results approximately 15 days after switching discharge from the south pond to the north pond. Blue iso-surfaces beneath the north pond denote regions of increasing bulk electrical conductivity caused by increasing saturation due to infiltrating water. Red iso-surfaces beneath the south pond denote regions that were previously saturated during the south pond discharge and are now de-saturating, causing a decrease in bulk electrical conductivity. In both cases, the zones of maximum change mark the dominant flow paths to the RLM. Figure ES.1C shows time-lapse imaging results approximately 15 days after switching discharge from the north pond to the south pond. In this case, blue iso-surfaces mark the dominant flow paths to the RLM from the south pond. The red iso-surfaces mark the dominant flow paths that existed during discharge to the north pond. The regions of maximum change in bulk conductivity (due to saturation or desaturation) that mark the primary flow paths are equivalent in both cases and denoted by the dashed solid and black circles. If a perched water zone forms on the RLM, it is likely to mound within or near the dashed circle during discharge to the north pond, and in the solid circle during discharge to the south pond. In other words, if perched water mounding occurs, the circles mark the optimum locations suggested by the ERT imaging for monitoring boreholes to be placed, enabling samples to be collected that are representative of TEDF discharge impacts on groundwater quality.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Deep Vadose Zone Monitoring Test Bed (FY23 Status Report)

A subsurface air injection at the Hanford Site’s Deep Vadose Zone Monitoring Test Bed was completed to realize a change in subsurface hydrologic conditions in accordance with a soil desiccation remedy. The injection mimicked a previous injection at the site that was performed in accordance with a vadose zone treatability study. Unlike the previous test which relied on electrical methods only, the change in hydrologic conditions during the recent test was also monitored using cross-hole seismic sensing methods to assess the ability of the seismic methods to evaluate changes in moisture conditions of desiccated sediment at the field scale. Data from in situ neutron probes indicates a reduction of soil moisture in the vicinity of the injection well due to the air injection. Similar changes were observed in the time-lapse electrical resistivity and seismic data, which indicates a loss of soil moisture over time. Tomographic inversions of the time-lapse geophysical data illustrate the 2D and 3D features of the soil moisture distribution over time. Time-lapse electrical resistivity tomography (ERT) results show a reduction in the electrical conductivity of the subsurface in the vicinity of the injection well, with most changes occurring within the screened interval. Similar patterns are observed in the seismic tomography results, with both methods illustrating two lobe-shaped features of reduced soil moisture. Use of seismic and ERT technologies in tandem takes advantage of two complementary geophysical monitoring technologies, providing increased sensitivity to specific hydrologic conditions. The multiphysics approach, therefore, has the potential to improve the ability to estimate subsurface moisture conditions from sensor-based and remotely sensed geophysical data that will ultimately improve the ability of remediation contractors to evaluate remedy performance.

58 GEOSCIENCES↗
DOE OSTI2020

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1977

The effects of cockpit environment on long-term pilot performance

A fixed-base helicopter simulator was used to examine pilot performance as influenced by noise, vibration, and fatigue. Subjects flew the simulator for periods ranging between three and eight hours while exposed to vibrations (at 17 Hz) ranging from 0.1 to 0.3 g, and noise stimuli varying between 74 (ambient) and 100 dB. Despite reports of extreme fatigue on these long flights, subject performance did not degrade. Within the limits of this study, performance tended to improve as environmental stress increased. However, subjects did suffer from lapses resulting in abnormally poor performance. These lapses are probably of short duration (seconds) and occur at unpredictable times. If such lapses occur in actual flight, they could provide an explanation for many so-called 'pilot error' accidents.

Stave, A. M.↗
NASA NTRS1981

Climate sensitivity of a one-dimensional radiative-convective model with cloud feedback

The potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included is illustrated. This is done by studying the behavior of a one-dimensional radiative-convective model with two types of cloud variation: (1) variable cloud cover with constant optical thickness and (2) variable optical thickness with constant cloud cover. The variable parameter is calculated on the assumption that a correlation exists between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, the sensitivity of the results to two different critical lapse rates is examined. These are a constant 6.5 K/km lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are also examined. The model results reveal that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover.

Wang, W.-C.↗
NASA NTRS2008

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Dong, Xiquan↗
NASA NTRS2016

Perceived Noise Analysis for Offset Jets Applied to Commercial Supersonic Aircraft

A systems analysis was performed with experimental jet noise data, engine/aircraft performance codes and aircraft noise prediction codes to assess takeoff noise levels and mission range for conceptual supersonic commercial aircraft. A parametric study was done to identify viable engine cycles that meet NASAs N+2 goals for noise and performance. Model scale data from offset jets was used as input to the aircraft noise prediction code to determine the expected sound levels for the lateral certification point where jet noise dominates over all other noise sources. The noise predictions were used to determine the optimal orientation of the offset nozzles to minimize the noise at the lateral microphone location. An alternative takeoff procedure called programmed lapse rate was evaluated for noise reduction benefits. Results show there are two types of engines that provide acceptable range performance; one is a standard mixed-flow turbofan with a single-stage fan, and the other is a three-stream variable-cycle engine with a multi-stage fan. The engine with a single-stage fan has a lower specific thrust and is 8 to 10 EPNdB quieter for takeoff. Offset nozzles reduce the noise directed toward the thicker side of the outer flow stream, but have less benefit as the core nozzle pressure ratio is reduced and the bypass-to-core area ratio increases. At the systems level for a three-engine N+2 aircraft with full throttle takeoff, there is a 1.4 EPNdB margin to Chapter 3 noise regulations predicted for the lateral certification point (assuming jet noise dominates). With a 10 reduction in thrust just after takeoff rotation, the margin increases to 5.5 EPNdB. Margins to Chapter 4 and Chapter 14 levels will depend on the cumulative split between the three certification points, but it appears that low specific thrust engines with a 10 reduction in thrust (programmed lapse rate) can come close to meeting Chapter 14 noise levels. Further noise reduction is possible with additional reduction in takeoff thrust using programmed lapse rate, but studies are needed to investigate the practical limits for safety and takeoff regulations.

Turbofans↗
NASA NTRS2019

Perceived Noise Analysis for Offset Jets Applied to Commercial Supersonic Aircraft

A systems analysis was performed with experimental jet noise data, engineaircraft performance codes and aircraft noise prediction codes to assess takeoff noise levels and mission range for conceptual supersonic commercial aircraft. A parametric study was done to identify viable engine cycles that meet NASAs N+2 goals for noise and performance. Model scale data from offset jets was used as input to the aircraft noise prediction code to determine the expected sound levels for the lateral certification point where jet noise dominates over all other noise sources. The noise predictions were used to determine the optimal orientation of the offset nozzles to minimize the noise at the lateral microphone location. An alternative takeoff procedure called programmed lapse rate was evaluated for noise reduction benefits. Results show there are two types of engines that provide acceptable range performance; one is a standard mixed-flow turbofan with a single-stage fan, and the other is a three-stream variable-cycle engine with a multi-stage fan. The engine with a single-stage fan has a lower specific thrust and is 8 to 10 EPNdB quieter for takeoff. Offset nozzles reduce the noise directed toward the thicker side of the outer flow stream, but have less benefit as the core nozzle pressure ratio is reduced and the bypass-to-core area ratio increases. At the systems level for a three-engine N+2 aircraft with full throttle takeoff, there is a 1.4 EPNdB margin to Chapter 3 noise regulations predicted for the lateral certification point (assuming jet noise dominates). With a 10 reduction in thrust just after takeoff rotation, the margin increases to 5.5 EPNdB. Margins to Chapter 4 and Chapter 14 levels will depend on the cumulative split between the three certification points, but it appears that low specific thrust engines with a 10 reduction in thrust (programmed lapse rate) can come close to meeting Chapter 14 noise levels. Further noise reduction is possible with additional reduction in takeoff thrust using programmed lapse rate, but studies are needed to investigate the practical limits for safety and takeoff regulations.

Jet Noise↗
NASA NTRSDate not supplied

Changes in Alertness and Performance Over Time During Long-Haul Flying Across Multiple Time Zones

BACKGROUND: Long-haul pilots experience high levels of fatigue and circadian disruptions due to long work hours and flying over multiple time zones. The aim of this study was to describe changes in alertness and performance among flight crews during long-haul flights crossing multiple time zones. METHODS: All pilots flying long-haul operations from a single airline were eligible to participate. All participants collected data for ~2 weeks of their normal work schedule within airline operations, with at least two long-haul rotations, including rest days and layovers. Participants wore an Actiwach throughout the entire study period and completed a sleep diary (at bedtime, upon waking up and after each nap). Each participant completed a 5-min Psychomotor Vigilance Task (PVT) and a Karolinska Sleepiness Scale (KSS) pre-flight, on top-of-descent (TOD; inflight) and at the end of each flight (post-flight). Response speed (1/RT x 1000), lapses (RT > 500 ms), and alertness were assessed over time pre-flight, TOD, post-flight, using mixed-effects models with participant as a random factor. Linear models were assumed for response speed and alertness, while a negative binomial distribution was specified for lapses due to overdispersion. RESULTS: Forty-four long-haul pilots participated in the study (5 female; mean age 44.25 ± 10.06 yrs; mean flight hours 9834.3; ± 5334.1 hrs). Lapses increased post-flight relative to pre-flight (F(2, 665) = 3.67, p < 0.05). There was a main effect of response speed (F(2, 665) = 21.45, p < 0.001) with slower speed inflight and postflight compared to preflight (p < 0.001). The KSS increased over time from M = 4.02 (± 1.35) preflight to M = 5.15 (± 1.58) inflight, to M = 6.7 (± 1.51) postflight (F(2, 701) = 182.63, p < 0.001). DISCUSSION: Our preliminary analyses showed that both performance and subjective alertness worsened from the beginning to the end of a flight. Additional analyses will be conducted to investigate the changes in alertness and performance by direction of travel, sleep history, and flight timing and duration.

long-haul↗
DOE OSTI2011

Carbon sequestration monitoring with acoustic double-difference waveform inversion: A case study on SACROC walkaway VSP data

Geological carbon sequestration involves large-scale injection of carbon dioxide into underground geologic formations and is considered as a potential approach for mitigating global warming. Changes in reservoir properties resulting from the CO{sub 2} injection and migration can be characterized using waveform inversions of time-lapse seismic data. The conventional approach for analysis using waveform tomography is to take the difference of the images obtained using baseline and subsequent time-lapse datasets that are inverted independently. By contrast, double-difference waveform inversion uses timelapse seismic datasets to jointly invert for reservoir changes. We apply this method to a field time-lapse walkaway VSP data set acquired in 2008 and 2009 for monitoring CO{sub 2} injection at an enhanced oil recovery field at SACROC, Texas. The double-difference waveform inversion gives a cleaner and more easily interpreted image of reservoir changes, as compared to that obtained with the conventional scheme. Our results from the applicatoin of acoustic double-difference waveform tomography shows some zones with decreased P-wave velocity within the reservoir due to CO{sub 2} injection and migration.

ACOUSTICS↗
DOE OSTI2021

System and method for optimizing hydrocarbon production from subsurface reservoirs

A method is described for subsurface hydrocarbon reservoir characterization including receiving a time-lapse electromagnetic (EM) dataset and a flow dataset; inverting the time-lapse EM dataset using a parametric inversion that models steel well casings to determine a volume of fluid-changed reservoir; inverting the time-lapse EM dataset and the flow dataset using a joint inversion that honors the volume of the fluid-changed reservoir to determine relative permeability and capillary pressure; and characterizing flow characteristics in the volume of the fluid-changed reservoir. The method may be executed by a computer system.

Hoversten, Gary Michael↗
DOE OSTI2024

SUBTASK 1.6 – BASIN ELECTRIC CARBON STORAGE RESEARCH PROJECT: NOVEL MONITORING TECHNIQUES

The Energy & Environmental Research Center (EERC) conducted baseline activities associated with an applied research project at Basin Electric Power Cooperative’s (Basin’s) carbon capture and storage (CCS) site in Beulah, North Dakota, to establish novel carbon storage-monitoring techniques as commercial methods under Cooperative Agreement No. DE-FE0024233, Subtask 1.6. The following report summarizes the baseline activities performed and briefly describes the subsequent (operational monitoring) activities that have been proposed to the U.S. Department of Energy (DOE) as part of the overall project to develop and demonstrate novel monitoring techniques at North America’s largest permitted CCS operation. Dakota Gasification Company (DGC), a wholly owned subsidiary of Basin, owns and operates the Great Plains Synfuels Plant (GPSP) approximately 5 miles northwest of the town of Beulah, North Dakota (Figure 1). In 2023, DGC received approval from the North Dakota Industrial Commission (NDIC) to develop a storage facility on-site for injecting a stream of carbon dioxide (CO2) captured from GPSP. DGC will transport the captured CO2 stream with approximately 6.8 miles of transmission lines that extend north of GPSP and inject >1 million tonnes (MMt) of CO2 annually (>1 MMt/yr) over a 12-year period with up to six underground injection control (UIC) Class VI-compliant injection wells completed in the Broom Creek Formation, a predominantly sandstone reservoir and saline aquifer underlying GPSP. The Broom Creek Formation lies approximately 5900 feet (ft) below ground surface (bgs) at GPSP. The commercial scale (i.e., >1 MMt/yr) of DGC’s permitted carbon storage project is ideal for developing and testing the novel monitoring techniques included within Subtask 1.6. The goals of this project are to demonstrate 1) the cost-effectiveness of novel monitoring technologies included as part of this research, 2) technology capability for tracking the CO2 plume and/or associated pressure response in the subsurface and monitoring out-of-zone migration, and 3) compliance with UIC Class VI program requirements. The research activities proposed for the overall project include 1) design of an automated, integrated, modular (AIM) monitoring station; 2) time-lapse electromagnetic (EM) field surveys; 3) drone-based surveillance studies; 4) time-lapse monitoring with seismic methods; 5) advanced wellbore-monitoring methods; 6) deployment of an AIM monitoring network; 7) EM monitoring of CO2 with real-time data processing; 8) continued seasonal drone-based surveillance studies; 9) seismic monitoring with passive and active surveys; and 10) wellbore monitoring with nuclear magnetic resonance (NMR) for near-surface characterization. Completion of Activities 1.0–5.0 (baseline activities) are described in this report. Upon authorization of funding by DOE, the EERC will initiate Activities 6.0– 10.0 (operational monitoring activities). Current state-of-the-art (SOA) carbon storage-monitoring techniques require countless labor hours dedicated to the acquisition of data. Once data are gathered, these SOA techniques often rely on commercial facilities to process raw data from the field. However, it is anticipated that next-generation monitoring techniques, such as those being demonstrated, will lower acquisition footprints, be less operationally intensive, and improve data acquisition efficiencies. These new techniques are more conducive to the application of machine learning, artificial intelligence, and automation, thus providing a pathway for integration into active control systems, informing site operability, and improving the integration of data for future CCS projects across the United States. Additionally, reclaimed and active mining lands are present within the project site, creating a unique opportunity to demonstrate the effectiveness of remote sensing and surface-based geophysics monitoring techniques at similar project sites that may include disturbed, unconsolidated, or actively excavated near-surface environments. The efforts included in the overall project will produce necessary designs, learnings, and data acquired during the baseline and operational monitoring periods that are necessary for time-lapse demonstration and validation of the described monitoring techniques. In addition, it is anticipated that the monitoring technologies included in this study will be compliant with UIC Class VI requirements to enable the potential for implementation at other CCS sites across the United States.

42 ENGINEERING↗
DOE OSTI2021

4D Proxy Imaging of Fracture Dilation and Stress Shadowing Using Electrical Resistivity Tomography During High Pressure Injections into a Dense Rock Formation

Fluid flow through fractured rock systems is governed in large part by the distribution, interconnectivity, and size of fracture apertures. In-situ stress is one of the primary factors controlling fracture aperture, and one that is altered significantly during high-pressure fluid injections or extractions. Interactions between stress, pore pressure, aperture, and fluid flow can result in complex and evolving poroelastic behavior with significant implications regarding the predictability and risk of developing and managing deep subsurface reservoirs (geothermal, fossil energy, and geologic carbon sequestration). In saturated crystalline rocks, bulk electrical conductivity is highly sensitive to porosity, and therefore to fracture aperture size and distribution. We demonstrate the use of time-lapse 3D electrical resistivity tomography for remotely monitoring stress induced changes in aperture distribution during high pressure injections into a fractured rock system at a scale of tens of meters. Results reveal a complex and continuously evolving stress field involving aperture dilations in the natural fracture system and aperture contractions in adjacent zones of shadow stress. Results provide information about the spatiotemporal changes in the system behavior and point to the potential of electrical imaging for autonomously and remotely monitoring evolving stress conditions by proxy through changes in bulk electrical conductivity.

electrical resisitivity tomography, stress, 4D Tim↗