Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Oklahoma”

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

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

At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

ARM Mobile Facility Leaving Alaska for U.S. Southeast

The Atmospheric Radiation Measurement (ARM) user facility will soon begin the process of moving its third mobile facility (AMF3) from Alaska to the Southeastern United States. A workshop in August 2018 identified the Southeast as a priority region of interest for further study by ARM. The Southeast is a region with abundant atmospheric convection, yet the land surface, boundary layer, vegetation, and aerosol properties are markedly different from those seen at ARM’s fixed observatory in Oklahoma, allowing opportunities to explore new research questions. To maximize the scientific value of the new site, DOE’s Biological and Environmental Research program selected a site science team that will help guide the move of AMF3. Brookhaven National Laboratory (BNL) in New York will lead the AMF3 relocation effort. Supported by ARM and DOE’s Atmospheric System Research (ASR), the multi-institutional team is responsible for developing a science plan and initial research project for the Southeastern U.S. deployment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Examining the Ice-Nucleating Particles from the Southern Great Plains Field Campaign Report

The recent U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility field campaign, named Examining the Ice-Nucleating Particles from Southern Great Plains (ExINP-SGP), targeted experimentally characterizing abundance and other properties of ambient ice-nucleating particles (INPs) at the SGP site in Oklahoma (36° 36' 18" N, 97° 29' 6" W) during the period of October 1 to November 14, 2019. This campaign was funded through the DOE Office of Science Early Career Research Program (DE-SC0018979) as one of three major campaigns to be conducted at three ARM observatories, including the Eastern North Atlantic (ENA) station in 2020–2021 and North Slope of Alaska (NSA) site in 2021–2023, besides SGP. Different INP episodes were assessed to develop an SGP-relevant ice nucleation parameterization that would help understand convective and mixed-phase cloud systems typically observed in this region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) southern great plains (SGP) site at Oklahoma, USA has become a reference research site for meteorological studies. Due to an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, SGP instrumentations, the site and some site-specific atmospheric conditions which potentially effect wind turbines within the region. As the atmospheric boundary layer is bounded and influenced by the surface, observations of surface radiation components and heat fluxes are crucial in understanding land-atmosphere interactions. The entrainment of air, updrafts, downdrafts and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both surface in-situ and remote sensing observations at SGP provide an overall climatology and their interactions from surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at SGP central facility were analyzed. All the measurements were generally within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in-situ and remote sensing instrumentation used in the report; provides mathematical equations to analyze fluxes, turbulence and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory; an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site specific atmospheric conditions, such as nocturnal low-level jets. Diurnal, seasonal and yearly variations of surface, sub-surface and boundary layer quantities, such as wind speed, direction, temperature, atmospheric stability, soil temperature, and various atmospheric fluxes at SGP showed distinct trends useful for focused modeling studies. The applicability of surface similarity theory on ARM SGP data is also evaluated, which showed northerly flows are aligned with MO theory estimates compared to southerly flows. Boundary layer winds and direction profiles for several years from a Doppler lidar shows a consistent presence of a nocturnal low-level jet and predominant southerly wind directions through the boundary layer at SGP. The inter-annual variability at SGP is low (<3.5%), with a mean annual wind speed of approximately 7 m s -1 at 100 m above ground level. Boundary layer turbulence and moisture transport from Doppler and Raman lidars are evaluated, which provides evidence of increased water vapor mass flux into the great plains during nocturnal low-level jets. The moisture flux from nocturnal low-level jets is observed to be maximum during summer periods. A novel machine learning algorithm is implemented to accurately estimate the planetary boundary layer height, providing further insights into growth and destruction of the convective boundary layer height during various seasons and land-atmosphere conditions. The high frequency of low-level clouds during winter, spring and fall seasons is validated using the multi-sensor array and satellite estimates of cloud top height. Satellite vegetative fraction data provides insight into seasonal surface roughness and vegetation variability around SGP site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Boundary Layer Climatology at ARM Southern Great Plains

Operational since 1992, the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, USA, has become a reference research site for meteorological studies. Because of an open data policy the ARM data are used by researchers all over the world. In this report, we review the long-term climatology of the atmospheric boundary layer, the SGP instrumentation, the site and some site-specific atmospheric conditions, which potentially affect wind turbines in the region. Because the atmospheric boundary layer is bounded and influenced by the land surface, observations of surface radiation components and heat fluxes are crucial to understanding land–atmosphere interactions. The entrainment of air, updrafts, downdrafts, and boundary layer height characteristics is needed for understanding the structure and growth of the atmospheric boundary layer. Therefore, measurements from both ground surface in situ and remote-sensing observations at the SGP site provide an overall climatology and their interactions from ground surface up to the boundary layer. Measurements from a 60 m meteorological tower, surface flux stations, disdrometers, soil temperature and moisture flux plates, coherent Doppler lidar, Raman lidar, radiosondes, and satellite data at the SGP central facility were analyzed. All the measurements were generally made within a few square kilometers of each other at the central facility. This report focuses on data from January 2010 to June 2020 at the SGP central facility. The various sections describe the ARM SGP site and surrounding wind turbines; in situ and remotesensing instrumentation used in the report; mathematical equations to analyze fluxes, turbulence, and other boundary layer parameters; a climatological analysis of surface winds, fluxes and thermodynamic parameters for several years; an analysis of observed winds in the framework of Monin-Obukhov Similarity Theory (MOST); an analysis of the boundary layer winds and direction from a Doppler lidar; multi-year turbulence estimates through the boundary layer from a Doppler lidar; atmospheric boundary layer water vapor and relative humidity profiles from Raman lidar; cloud base height and boundary layer height from multiple sensors and satellite data; and finally site-specific atmospheric conditions, such as nocturnal low-level jets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lifting Condensation Level Height (LCL Height) Value-Added Product Report

The lifting condensation level height (LCL, m) is determined from continuous surface-air observations of relative humidity and temperature as the altitude where the surface-air moisture equals saturation following a dry-adiabatic ascent. Values are computed from surface meteorological observations for 16 facilities belonging to the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) atmospheric observatory and for 133 Oklahoma Mesonet (OKM) stations. The LCL Height Value-Added Product (VAP) was developed for use by the Large-Eddy Simulation (LES) ARM Symbiotic Simulation and Observation (LASSO) project (Gustafson et al. 2016, 2017, 2018, 2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Computed Tomography Scanning and Geophysical Measurements of the Caney Shale Formation from the Tomaney #1-35-34-27 Well

Evaluation of reservoir samples can support resource estimation and determination of effective extraction methodologies. While it is common for commercial entities to perform these characterizations, the resources necessary to conduct these analyses are not always available to the broader interest base, such as state agencies, universities, and research-based consortiums. To meet the growing need for comprehensive and high-quality lithologic data for collaborative research initiatives, the U.S. Department of Energy’s (DOE) National Energy Technology Laboratory (NETL) has used available resources in conjunction with previous techniques and new, innovative methodologies to develop a systematic approach for the evaluation of cores. This report focuses on the Tomaney #1-35-34-27 well. Tomaney #1-35-34-27 was drilled in southwestern Stephens County, Oklahoma within section 35, township 2S, and range 4W. The Tomaney #1-35-34-27 was drilled in January/February of 2020 and targeted the Devonian Woodford Shale Formation and cored the Mississippian Caney Shale formation within the Ardmore Basin.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2021

Developing and Testing a Novel Stochastic Ice Microphysics Parameterization for Cloud and Climate Models Using ARM Field Campaign Data (Final Progress Report)

The major goals of this project were: 1) to use field campaign measurements from DOE’s Atmospheric Radiation Measurement (ARM) program to characterize variability of important parameters describing properties of ice particles in the atmosphere; 2) based on this observational analysis, to develop a parameterization scheme for weather and climate models that stochastically varies these parameters, and implement the new scheme into a weather model called the Weather Research and Forecasting model (WRF); 3) to use WRF coupled with the new stochastic scheme to simulate ARM field campaign thunderstorm cases and analyze how accounting for this parameter variability affects the model simulations. This work was performed jointly between the National Center for Atmospheric Research, University of Oklahoma, and University of Utah. To accomplish these goals, we extended an approach previously developed to characterize the variability in the size distribution of ice particles to parameters that are explicitly represented in models (i.e., relationships between ice particle mass and size, and between particle fall velocity and size). Our project was, to our knowledge, the first to apply observationally-constrained estimates of this parameter variability describing mass-size and fall velocity-size in a modeling framework. Our results showed efficacy of the approach, evaluated using ARM observations. Similarly, to our knowledge, work in this project was the first to propose and evaluate in detail a stochastic approach for unresolved turbulent mixing in high-resolution model simulations against detailed, benchmark large eddy simulations and ARM observations. Results showed some promising behavior, particularly with increased mixing and dilution of air in thunderstorm cores with surrounding environmental air, bringing the stochastic simulations closer to the benchmark large eddy simulations; however, results were somewhat degraded using stochastic mixing compared to observations from the AMIE/DYNAMO field campaign. This project also further refined and applied a modeling methodology called “piggybacking” that can robustly separate dynamical and thermodynamic impacts of model changes, and comparison studies of different models based on cases developed from ARM observations. Finally, this project directly supported three graduate students who completed their PhDs as well as a postdoctoral research fellow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Paths Forward for Nuclear Energy: Using a Nationwide Post-Stratified Hierarchical Model to Facilitate Matching of New Nuclear Technologies to Receptive Host Communities

This project was a collaboration between the University of Oklahoma (OU) and the University of Michigan (UMich). The overall objective of the project was to address a critical problem facing the siting of nuclear facilities, where there is no mechanism for incorporating public attitudes at a state and local level into decision-making. Utilizing recent advances in data modeling over local spatial scales, the research team created a state and county level map of public attitudes towards nuclear energy. Current estimates for public acceptance of nuclear technologies primarily exists on a national level, and sub-national estimates of public opinion about reactor siting, research facilities, transport routes, or storage and disposal facilities are very scarce. Model results from this project provide a systematic basis for technology developers to evaluate public acceptance across alternative siting options as a critical component for weighing potential benefit-cost tradeoffs for alternative paths to deploy new nuclear facilities. The project utilized data from the largest database of nuclear attitudes in the US, coupled with Census and elections-related data as well as data on social vulnerability and proximity to current nuclear facilities. In addition to modeling public support, the team also developed an interactive map to showcase results, using an online tool called Public and Local Attitudes about Nuclear Energy Technologies (PLANET). The tool allows technology developers and stakeholders to interact with the model results and better understand variation in support for nuclear facility siting on a state and county level. The interactive nature of the tool also allows users to analyze results in a targeted way, by comparing levels of support across different states and/or counties as desired.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Using Machine Learning to Identify Optimum Prospects for Offshore Geologic CO 2 Storage and Enhanced Oil Recovery in the Gulf of Mexico

The SECARB Offshore Partnership is a government-industry partnership focused on assembling the knowledge base required for secure, long-term, large-scale CO 2 subsea storage in saline formations and mature oil reservoirs. The SECARB Offshore Partnership is evaluating potential storage opportunities in the Central and Eastern planning areas of the outer continental shelf (OCS) of the Gulf of Mexico. The evaluation focuses on active and depleted oil and gas fields and potentially associated CO 2 -enhanced oil recovery (CO 2 -EOR), as well as, deep saline storage resources. As part of Subtask 3.0 (Offshore Storage Resources Characterization) and Subtask 4.0 (Risk Assessment, Simulation, and Modeling), Oklahoma State University (OSU) is developing a machine learning system that employs the SAS Institute’s Viya platform with visual data mining and machine learning to identify and characterize optimum prospects for enhanced oil recovery and stacked storage in saline reservoirs. This report summarizes this effort to date and discusses the many variables that can be used to characterize these storage objectives, as well as, the design vision of the Viya machine learning system.

02 PETROLEUM↗
DOE OSTI2022

Examining the Ice-Nucleating Particles from the Eastern North Atlantic (ExINP-ENA) (Field Campaign Report)

The Examining the Ice-Nucleating Particles from the Eastern North Atlantic (ExINP-ENA) field campaign was conducted at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility’s Eastern North Atlantic (ENA) observatory on Graciosa Island, Azores (39.0916° N, 28.0257° W). The ExINP-ENA campaign began on October 1, 2020, and collected data until March 28, 2021, for a total of 179 days of data generated, with a 45-day intensive operational period (IOP) from October 10 to November 24. This campaign was funded by the DOE Office of Science Early Career Research Program through grant DE-SC001879. This grant contains funding for three field campaigns. The previous field campaign at the Southern Great Plains (SGP) site in Oklahoma, ExINP-SGP, was completed in 2020 (36.6073° N, 97.4876° W), and the upcoming field campaign at the North Slope of Alaska (NSA), ExINP-NSA, will take place from October 2021 at the National Oceanic and Atmospheric Administration (NOAA) Barrow Atmospheric Baseline Observatory (71.3230° N, 156.6114° W).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Research Introduction [Slides]

In the topic of Reverse Time Imaging, we proposed a new IC to reduce computation cost but reserve image resolution for distributed sensor networks. For Induced Seismicity in Oklahoma, we analyzed fault stress state analysis at state scale, and we applied machine learning techniques to polarity picking and seismicity rate forecasting. The results provide better understanding of fault properties, stress field, and the relationships among fault, stress state, injections, and potential seismic hazards. Lastly, for Microseismic Monitoring, we detected and located 770 low-frequency events (5-50 Hz): (1) Shallow events are highly clustered, consistent with the pathway from injection well 13-10A to monitoring well; moment tensor inversion shows dominant tensile cracking; (2) Deep events are scattered and show migration pattern to the basement; moment tensors show that most events are shear cracks.

58 GEOSCIENCES↗
DOE OSTI2022

SECARB-USA: Preliminary Regional Commercialization Plan (Task 4.4.a)

The SECARB-USA region refers to the states in the southeastern portion of the United States including Alabama, Arkansas, Florida, Georgia, Kentucky, Louisiana, Mississippi, Missouri, North Carolina, eastern Oklahoma, South Carolina, Tennessee, eastern Texas, Virginia, and West Virginia. This region is a hub for economic activity and accordingly emits almost 1 Gtpa of CO 2 which is the motivation for the development of Carbon Capture and Storage (CCS). This preliminary commercialization plan reviews the status of commercialization of CCS within the region, outlines the infrastructure buildout to achieve CO 2 reduction goals by 2050 described by the Los Alamos National Lab in Task 4.1.b (see the Task 4.1.b “Technoeconomic Analysis of Infrastructure Buildout Scenarios” report), and provides an early estimate of the economic activity and employment creation resulting from the increase in CCS activity. Additionally, this report addresses the challenges associated with commercializing CCS within the region at a large scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Initial Risk Inventory for Commercial Scale Storage Sites

The “Southeast Regional CO 2 Utilization and Storage Acceleration Partnership” (SECARB-USA) project supports the U.S. Department of Energy (DOE) Office of Fossil Energy's (FE) mission to help the United States meet its need for secure, affordable, and environmentally sound fossil energy supplies by utilizing the advancements made since 2003 by the Regional Carbon Sequestration Partnership (RCSP) Initiative to continue to identify and address knowledge gaps. The SECARB-USA regional initiative encompasses the states of Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and portions of Kentucky, Missouri, Oklahoma, Texas, and West Virginia. The primary objective of the project is to identify and address regional onshore storage and transport challenges facing commercial deployment of carbon dioxide (CO 2 ) capture, utilization, and storage (CCUS) technologies. This document provides an overview of risks relevant to commercial CCUS projects.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Agricultural Ice Nuclei at Southern Great Plains (AGINSGP) Field Campaign Report

The Agricultural Ice Nuclei at Southern Great Plains (AGINSGP) field campaign was conducted from April 4 to April 29, 2022, at the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) SGP site in Oklahoma. The goal of this campaign was to improve understanding of the sources and variability of ice-nucleating particles (INPs) at the SGP site. To this end, the key objectives of the campaign were (1) to produce a high-quality data set including measurements of atmospheric INP concentrations and aerosol particle properties relevant to the sources of INPs; and (2) to conduct a residual characterization experiment including offline and online analysis of the physical and chemical characteristics of INPs sampled in ambient air at SGP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Physics-based Induced Earthquake Forecasting: Process Understanding, and Hazards Mitigation

Disposal of saltwater co-produced with oil and gas is linked to elevated seismicity in the Central and Midwest US. There is a concern that these events may lead to widespread damage and an overall increase in seismicity. Thus an improved understanding of the spatially and temporally variable deformation and stress field associated with fluid injection operation is critically necessary for evaluating time-varying seismic hazards. Despite the improvements in seismic monitoring capacity and the resulting decrease in the magnitude detection threshold, estimates of induced earthquake probability remain elusive due to insufficient models incapable of accounting for the complex physics governing the process of induced seismicity. The proposed research effort will comprehensively analyze, integrate, and interpret geodetic, injection, and seismic data in the vicinity of the injection sites in Oklahoma to resolve the 4-dimensional distribution of pore pressure and stress in the shallow crust. This project, in particular, is focused on exploring the statistical relation between injection operation and increased earthquake hazard. The amplitude of and the extent to which pore pressure changes are determined by some factors, in particular, the hydrogeological properties of the rocks, such as diffusivity. Thus the available deformation data will be used to constrain hydrogeological properties of the medium, to accurately resolve the evolution of crustal stresses due to fluid injection. Having the time-varying models of stress changes, a statistical framework will be implemented to estimate the time-dependent probability of large earthquakes on the nearby fault systems. These data and models help to improve seismic hazard estimates and aid in constructing operational-induced earthquake forecast models. This information can also be integrated into the updated U.S. National Seismic Hazard Map, which local communities and authorities use in their earthquake risk estimates and mitigation efforts.

58 GEOSCIENCES↗
DOE OSTI2023

Cross-Scale Land-Atmosphere Experiment (CSLAEX) (Final Report)

It is now well recognized that land-atmosphere interactions play an important role in both weather and climate. These interactions take place over a wide range of spatial and temporal scales. Most of the current formulations of the momentum, heat and moisture transport laws are informed by observations with a limited temporal or spatial scale, and hence may have limited applicability. The objective of this work is to improve the multi-scale representation of the near-surface heat transfer in the ground and in the atmosphere using a combination of modeling and field observations. Our knowledge and predictive capacity in land-atmosphere coupling is limited by our capacity to observe the full-scale spectrum at play. In order to bridge this fundamental gap in our observation capacity I will work to: create the first long-term Integrated Cross-Scale land-Atmosphere Experiment (CSLAEX) since I will work to: measure the components of the surface energy balance at a spatial scale relevant to remote sensing and meteorological applications (5km), along with observations of the nested subscale processes with Distributed Temperature Sensors (DTS). This proposal aims to fill the gaps in modeling and observing land-atmosphere interactions across scales via a novel Cross-Scale Land-Atmosphere Experiment (CSLAEX) to be implemented as part of the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site near Lamont, Oklahoma. The proposed research effort aims at exploring land-atmosphere processes across multiple spatial scales and to investigate the effect of landscape heterogeneity using Distributed Temperature Sensor measurements. The novel instrumentation of the Surface Energy Balance and simultaneous observations of the atmospheric state (boundary layer, cloud, convection) available at the DOE ARM SGP site will be used to create CSLAEX. This dataset will be used to frame and evaluate new transport laws and parameterizations for the boundary layer and the land surface, which can be implemented into the Weather and Research Forecasting (WRF) model and Community Atmospheric Model (CAM). The result of this study should impact multiple fields: meteorology, climate, and hydrology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment (BIRDIE) (Final Report)

The Beryllium Isotopes in Rainfall for Stratospheric-Tropospheric Exchange Dynamics Experiment or BIRDIE was a precipitation collection campaign designed to measure cosmogenic isotopes of beryllium in rainfall and other forms of precipitation across the DOE Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) site. Precipitation samples were collected over three weeks (May 21-June 10, 2022) at 11 SGP sites across a 120 km 2 domain in northern and central Oklahoma. The field campaign targeted summer-time convection rain events. We aimed to capture any spatial and/or temporal variability in the concentrations of beryllium-10 (10Be) and beryllium-7 (7Be) across the SGP ARM site during these rainfall events. The ratio of 10Be to 7Be (10/7Be) has been shown to be a powerful tracer for transport processes in the stratosphere-troposphere exchange (STE) system (e.g., Koch and Rind 1998). Any observed variability is analyzed to see if it could be linked to STE processes, including overshooting of deep convection clouds which penetrate the lower stratosphere. Six wet weather system events were collected within our three-week span. Five out of six of these rainfall events are classified as moderately to strongly convective. Those events are studied in more detail. The five systems also follow each other over a short time period of eleven days. In our rainfall samples we observed spatial and event variability in the concentrations of beryllium-10 and -7 which resulted in variability of 10/7 Be ratios. Each weather event appeared to exhibit a unique 10/7Be pattern across the domain that was not directly linked to storm total precipitation amount. To better understand the causes for this spatial variability, cloud characteristics in the domain were looked at to assess cloud type, cloud height and depth information. We also ran Hysplit back trajectories to identify possible air mass and moisture origins across our events. Detailed analysis is still on-going. The purpose of this technical report is to provide background on using cosmogenic isotopes as atmospheric tracers, describe the experimental design, and present the beryllium concentration and ratio data.

58 GEOSCIENCES↗