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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Experimental and Theoretical Studies of Volatile Metal Hydroxides

Modern superalloys used in the construction of turbomachinery contain a wide range of metals in trace quantities. In addition, metal oxides and silicon dioxide are used to form Thermal Barrier Coatings (TBC) to protect the underlying metal in turbine blades. Formation of volatile hydroxides at elevated temperatures is an important mechanism for corrosion of metal alloys or oxides in combustion environments (N. Jacobson, D. Myers, E. Opila, and E. Copland, J. Phys. Chem. Solids 66, 471-478, 2005). Thermodynamic data is essential to proper design of components of modern gas turbines. It is necessary to first establish the identity of volatile hydroxides formed from the reaction of a given system with high temperature water vapor, and then to determine the equilibrium pressures of the species under operating conditions. Theoretical calculations of reaction energies are an important check of experimental results. This presentation reports results for several important systems: Si-O-H, Cr-O-H, Al-O-H, Ti-O-H, and ongoing studies of Ta-O-H.

Thermal Barrier Coatings↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

COMPASS-FME Synoptic Site Tree Greenhouse Gas Concentrations

These data are tree stem greenhouse gas concentrations collected from tree gas wells at some of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales; see https://compass.pnnl.gov/) 'synoptic' sites in the Chesapeake Bay region: Moneystump (MSM), Goodwin Islands (GWI), and GCReW (GCW). The sap flow monitoring trees at these sites in the Upland (UP) and Transition (TR) zones were cored and had gas wells installed at breast height. There were also some dead standing trees cored, gas well installed, and sampled at MSM and GWI. The GCW UP samples overlap with the TEMPEST experiment control plot, so the GCW UP data was pulled from the TEMPEST page and included here. These data provide crucial information about possible pathways for the greenhouse gas (carbon dioxide and methane, CO2 and CH4 respectively) production and emission (or in the case of CH4, perhaps taken up from) the atmosphere.All data are plain text CSV (comma separated value) files and require no special software to read.Updated 2025-10-09 to fix two missing dates (lines 77 and 78 in the data file).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Installation Assignment Durations and Patterns of Army Personnel

The purpose of this document is to report on the development of personnel assignment duration statistical metrics and statistical descriptions for groups of Army personnel aggregated by rank, career management field, and other descriptors for 32 Continental United States (CONUS) Army installations. This information can be used for generating evidence-based measures of personnel exposure times associated with environmental health considerations at the installation and career management field levels. Assignment duration statistical descriptions were developed to provide temporal metrics for groups of personnel at Army installations as foundational data to support a variety of assessments. Statistical results of personnel assignment durations at the installation level are provided in several formats. The 50th percentile assignment duration represents the median number of days personnel in groups aggregated by rank and career management field spend at the 32 CONUS Army installations in this study. Likewise, other duration percentiles (90th) and quartiles of assignment durations for groups aggregated by rank and career management field spend at each installation were developed. Assignment path analysis provide statistical descriptions of assignment durations at Army installations throughout increments of time (e.g., 5 years, 10 years). Key groupings of assignment paths were achieved by analyzing the duration of assignments at installations in chronological order from entry throughout specified increments of military service to generate the most common assignment paths across the 32 CONUS Army installations in this study. The developed assignment duration analytics and duration statistical descriptions provide foundational temporal metrics for groups of personnel at 32 CONUS Army installations to support a variety of assessments including those by human resource planners and environmental health specialists.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Exploration of Options for Ultra-Fast Mass Spectroscopy for Pulsed Power Applications

Mega-ampere class pulsed power machines drive intense currents into small volumes to study high energy and density environments. Power lost during these events is a difficult and paramount problem to solve. For example, facilities such as Sandia National Laboratories’ Z machine experience meaningful power loss, which can be linked to non-linear ohmic heating at high currents (i.e., 26 MA on Z) leading to thermal desorption of contaminants and subsequent shunt plasma formation. Characterizing and understanding this type of thermal desorption is key to design optimizations necessary to minimize current loss, which will be even more important for next generation pulsed power. This type of characterization requires the ability to identify and determine concentration of analytes with nanosecond resolution given the pulse width of Z is on the order of 100 ns. This report summarizes progress on a small exploratory project focused on investigating options to meet this challenge using mass spectrometry. The main focus of these efforts utilized an Energy and Velocity Analyzer for Distributions of Electric Rockets intending to determine how quickly transient data could be resolved. This probe combines an electrostatic analyzer with a Wien velocity filter (ExB) to obtain ion energy and velocity distributions. Primary results from this exploratory project indicate significant additional work is needed to demonstrate a nanosecond time scale mass spectrometer for this application and also highlight that alternative detection methods such as laser-based diagnostics should be considered to meet the need for ultra-fast detection.

42 ENGINEERING↗
DOE OSTI2020

Latest D0 results on exotic hadrons produced in $p\bar p $ collision

Prompt and nonprompt productions of exotic multiquark states are studied using the $\sim$10.4~fb$^{-1}$ data sample collected by the D0 experiment in Tevatron $p\bar{p}$ collisions at $\sqrt{s}$ = 1.96 TeV. The recent D0 results on the prompt and nonprompt production of the $X(3872)$ and $Z_c^+(3900)$ states and the $P_c$ pentaquarks at the 4450~MeV region are reported. Signals corresponding to these states are found in the nonprompt production, whereas only the $X(3872)$ state is seen in the prompt production. The ratio of prompt to nonprompt $X(3872)$ production is about three times larger in the D0 measurement than that obtained by the ATLAS experiment at 8 TeV. Theoretically, the production, formation, coalescence, and disassociation processes are expected to be quite different for conventional mesons with a spatial size of (0.4-0.8) fm, compact multiquark states such as tetraquarks with a size of a few fm, and spatially extended molecular states with a size of (4-10) fm. They can be differently affected in prompt hadron-hadron collisions where there are many additional particles emitted from the interaction point. Consequently, the prompt to nonprompt production ratio of spatially extended exotic states can be suppressed at LHC comparing with the Tevatron conditions, because of large difference in the hadron-hadron collisions particle multiplicity. The prompt production studies provide an opportunity to better understand the nature of exotic states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Search for cold gas in clusters with and without cooling flows

The dominant galaxy in each of approx. 40 clusters was studied using co-added Infrared Astronomy Satellite (IRAS) survey data, and 11 of these galaxies were observed for CO (J=1 to 0) emission with the 12 m telescope at Kitt Peak. Half of the galaxies in the sample are in clusters reported to have cooling flows while the other half are not. Six of the galaxies appear to have been detected by IRAS at fairly low flux levels, in addition to one previously known strong detection; all seven have reported cooling flows. No detectable CO emission (to 2 to 3 mK) was found in any of the 11 galaxies observed. Assuming accretion rates of approx. 100 Solar Mass yr(-1), the star formation rates and efficiencies in these galaxies must be quite high in order to render the CO undetectable. At the same time, the infrared luminosities of these galaxies is unremarkable, suggesting that the correlation between star formation efficiency and infrared luminosity found for spirals may not hold for cooling flows.

Grabelsky, D. A.↗
NASA NTRS1994

Determining structure in molecular clouds

We descibe an automatic, objective routine for analyzing the clumpy structure in a spectral line position-position-velocity data cube. The algorithm works by first contouring the data at a multiple of the rms noise of the observations, then searches for peaks of emission which locate the clumps, and then follows them down to lower intensities. No a proiri clump profile is assumed. By creating simulated data, we test the performance of the algorithm and show that a contour map most accurately depicts internal structure at a contouring interval equal to twice the rms noise of the map. Blending of clump emission leads to small errors in mass and size determinations and in severe cases can result in a number of clumps being misidentified as a single unit, flattening the measured clump mass spectrum. The algorithm is applied to two real data sets as an example of its use. The Rosette molecular cloud is a 'typical' star-forming cloud, but in the Maddalena molecular cloud high-mass star formation is completely absent. Comparison of the two clump lists generated by the algorithm show that on a one-to-one basis the clumps in the star-forming cloud have higher peak temperatures, higher average densities, and are more gravitationally bound than in the non-star-forming cloud. Collective properties of the clumps, such as temperature-size-line-width-mass relations appear very similar, however. Contrary to the initial results reported in a previous paper (Williams & Blitz 1993), we find that the current, more thoroughly tes ted analysis finds no significant difference in the clump mass spectrum of the two clouds.

Williams, Jonathan P.↗
NASA NTRS1995

The Atmospheric Data Acquisition And Interpolation Process For Center-TRACON Automation System

The Center-TRACON Automation System (CTAS), an advanced new air traffic automation program, requires knowledge of spatial and temporal atmospheric conditions such as the wind speed and direction, the temperature and the pressure in order to accurately predict aircraft trajectories. Real-time atmospheric data is available in a grid format so that CTAS must interpolate between the grid points to estimate the atmospheric parameter values. The atmospheric data grid is generally not in the same coordinate system as that used by CTAS so that coordinate conversions are required. Both the interpolation and coordinate conversion processes can introduce errors into the atmospheric data and reduce interpolation accuracy. More accurate algorithms may be computationally expensive or may require a prohibitively large amount of data storage capacity so that trade-offs must be made between accuracy and the available computational and data storage resources. The atmospheric data acquisition and processing employed by CTAS will be outlined in this report. The effects of atmospheric data processing on CTAS trajectory prediction will also be analyzed, and several examples of the trajectory prediction process will be given.

Jardin, M. R.↗
NASA NTRS2005

Surface and Internal Structure of Pristine Presolar Silicon Carbide

Silicon carbide is the most well-studied type of presolar grain. Isotope measurements of thousands [1,2] and structural data from over 500 individual grains have been reported [3]. The isotope data indicate that approximately 98% originated in asymptotic giant branch stars and 2% in supernovae. Although tens of different polytypes of SiC are known to form synthetically, only two polytypes have been reported for presolar grains. Daulton et al. [3] found that for SiC grains isolated from Murchison by acid treatments, 79.4% are 3C cubic beta-SiC, 2.7% are 2H hexagonal alpha-SiC, 17.1% are intergrowths of and , and 0.9% are heavily disordered. They report that the occurrence of only the and polytypes is consistent with the observed range of condensation temperatures of circumstellar dust for carbon stars. Further constraint on the formation and subsequent alteration of the grains can be obtained from studies of the surfaces and interior structure of grains in pristine form, i.e., prepared without acid treatments [4,5]. The acid treatments remove surface coatings, produce etch pits around defect sites and could remove some subgrains. Surface oxides have been predicted by theoretical modeling as a survival mechanism for SiC grains exposed to the hot oxidizing solar nebula [6]. Scanning electron microscopy studies of pristine SiC shows some evidence for the existence of oxide and organic coatings [4]. We report herein on transmission electron microscopy studies of the surface and internal structure of two pristine SiC grains, including definitive evidence of an oxide rim on one grain, and the presence of internal TiC and AlN grains.

Stroud, Rhonda, M.↗
NASA NTRS2014

Series-Bosch Technology for Oxygen Recovery During Lunar or Martian Surface Missions

Long‐duration surface missions to the Moon or Mars will require life support systems that maximize resource recovery to minimize resupply from Earth. To address this need, NASA previously proposed a Series‐Bosch (S‐Bosch) oxygen recovery system, based on the Bosch process, which can theoretically recover 100% of the oxygen from metabolic carbon dioxide. Bosch processes have the added benefits of the potential to recover oxygen from atmospheric carbon dioxide and the use of regolith materials as catalysts, thereby eliminating the need for catalyst resupply from Earth. In 2012, NASA completed an initial design for an S‐Bosch development test stand that incorporates two catalytic reactors in series including a Reverse Water‐Gas Shift (RWGS) Reactor and a Carbon Formation Reactor (CFR). In 2013, fabrication of system components, with the exception of a CFR, and assembly of the test stand was initiated. Stand‐alone testing of the RWGS reactor was completed to compare performance with design models. Continued testing of Lunar and Martian regolith simulants provided sufficient data to design a CFR intended to utilize these materials as catalysts. Finally, a study was conducted to explore the possibility of producing bricks from spend regolith catalysts. The results of initial demonstration testing of the RWGS reactor, results of continued catalyst performance testing of regolith simulants, and results of brick material properties testing are reported. Additionally, design considerations for a regolith‐based CFR are discussed.

Abney, Morgan B.↗
DOE OSTI2026

SPRUCE Soil Volumetric Water Content in Experimental Plots, Marcell Experimental Forest, Minnesota, 2017-2025

This dataset contains soil volumetric water content (VWC) measurements from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) Experiment. Measurements were made inside SPRUCE experimental plots in the S1 Bog at the US Forest Service Marcell Experimental Forest in northern Minnesota, USA from 2018-2025 (2018-06-14 to 2025-12-31). Observations were made with METER 10HS soil moisture sensors. To reduce bulk density related variability, 10HS sensors were placed inside mesh tubes filled with peat at a standard bulk density. The observations under standard bulk density represent relative differences in water content between hummock and hollow positions, and in response to experimental treatments. Productivity of peatlands, and their keystone species sphagnum, are highly dependent on water availability, which is affected by lateral inputs, precipitation, ground water depth and evapotranspiration. Knowledge of near surface and sphagnum water content is useful to understand peatland function. This dataset contains 8 data files in comma-separate values (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma-separate values (*.csv) format and a user guide in PDF (*.pdf) format.

Warren, Jeffrey [ORNL] (ORCID:0000000206804697)↗
DOE OSTI2024

Volatile Organic Compounds and Meteorological Conditions in the Missouri Ozark AmeriFlux (MOFLUX) Site, 2023

This data set contains measurements of atmospheric components and meteorological conditions of central Missouri, United States during the summer of 2023. Data serve to examine the impact of meteorological conditions relevant to future climate on the emission and transformation of volatile organic compounds (VOCs). During the field campaign, researchers were also able to incorporate opportunistic analyses of the long-range transport of smoke plumes generated from extreme forest fire activities in Canada. VOC measurements were conducted at the Missouri Ozark AmeriFlux (MOFLUX) site (latitude 38.7441, longitude −92.2000) using a proton transfer reaction time of flight mass spectrometer (PTR-ToF-MS 6000 X2). The sampling campaign was conducted during the summer of 2023 (2023-06-25 to 2023-08-12) with measurements being taken at high temporal resolution (1 hour). Particular VOCs analyzed include: Methanol, Acetonitrile, Acetone, Isoprene, Methylvinyl ketone (MVK) and methacrolein (MACr), Benzene, Toluene, Catechol, and Monoterpene. Meteorological parameters included in this dataset were collected from a nearby Columbia Regional Airport (~10 km). Global solar radiation data were measured at a weather site in Ashland, MO, 5.22 km from the MOFLUX tower. The data were accessed using the MesoWest online website (https://mesowest.utah.edu/) provided by the Department of Atmospheric Sciences, University of Utah. Discussion of the data providers, database, and dissemination were highlighted in prior studies (Horel et al., 2002a; Horel et al., 2002b) . Smoke mixing ratios (in mg m−3) were estimated from the High-Resolution Rapid Refresh (HRRR) 3 km weather model for Missouri at 6-hour intervals (Dowell et al., 2022). This dataset contains three data files in comma separate (*.csv) format. Additional metadata are provided: three data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

Acetone↗
DOE OSTI2023

Generating MCNP Input Files for Unstructured Mesh Geometries

The Los Alamos National Laboratory’s (LANL) Monte Carlo N-Particle (MCNP)1 transport code version 6.3 (also known as MCNP6.3) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into constructive solid geometry (CSG) cells. This feature has been developed for performing calculations of complex geometry models because manually creating CSG models is time-consuming and error-prone as the complexities of geometries increase. A UM geometry model is a collection of finite elements representing a solid geometry. The first step of the MCNP UM calculation is using other software packages to create a finite element mesh representation of a solid 3D geometry because the MCNP code cannot be used to generate a UM model. Computer-aided design (CAD) software is typically used to create a solid geometry model, which is later imported into mesh generation software to create a UM model. Some mesh generation software packages may also be used to create solid geometries and thus CAD files are not needed. The MCNP UM feature was originally designed for models generated by the Abaqus/CAE software suite. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. Starting with a 6.3 version, the MCNP code can process HDF5 mesh input files. We only focus on the UM models formatted as Abaqus input files in this report since currently no external software can be used to generate HDF5 mesh input files for MCNP UM calculations. The MCNP code version 6.3 can be used to convert the Abaqus mesh input files into the HDF5 mesh input files, but this option is typically used by the MCNP code development team to test the HDF5 mesh input file feature. Several software packages (such as Abaqus, Attila4MC, or Cubit) can be used to create the Abaqus input files for MCNP UM calculations. An MCNP UM calculation using an Abaqus model requires two input file types: MCNP and Abaqus input files. The Abaqus input files needed for MCNP UM calcu lations must have the correct Abaqus syntax and meet the additional requirements by the MCNP code. The MCNP code can process only Abaqus input files that make use of part and assembly definitions, where elements in each part must be grouped into one or more element sets (i.e., elset) using *Elset keyword lines with specified naming formats. The MCNP and Abaqus input files required for MCNP UM simulations must be related; pseudo-cells in an MCNP input file must be constructed from mesh model data from an Abaqus input file. For large complex UM models, it is tedious to manually create MCNP UM input files. The um pre op (unstructured mesh pre operations) program with the -m option can be used to create a skeleton MCNP input file from an Abaqus input file [6]. Since the um pre op program was written in Fortran and was not written for optimized performance, this program is a deprecated feature in the MCNP code version 6.3 and may be removed in the next release of the code. To improve calculation flow of multiphysics calculations, a Python3 code called write mcnp um input has been developed to generate an MCNP input file instead of using the um_pre_op -m option. This Python code was initially released to the public in 2020. We have updated this Python code for MCNP6.3 and it was used to generate the MCNP input files used to verify the MCNP6.3 code. The write_mcnp_um_input code is included with the MCNP6.3 code package which will be released to the public through the Radiation Safety Information Computational Center (RSICC) at Oak Ridge National Laboratory. This report is a revision of LA-UR-20-27139 report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Unveiling mesoscopic structures in distorted lamellar phases through deep learning-based small angle neutron scattering analysis

Hypothesis: The formation of distorted lamellar phases, distinguished by their arrangement of crumpled, stacked layers, is frequently accompanied by the disruption of long-range order, leading to the formation of interconnected network structures commonly observed in the sponge phase. Nevertheless, traditional scattering functions grounded in deterministic modeling fall short of fully representing these intricate structural characteristics. Our hypothesis posits that a deep learning method, in conjunction with the generalized leveled wave approach used for describing structural features of distorted lamellar phases, can quantitatively unveil the inherent spatial correlations within these phases. Experiments and Simulations: This report outlines a novel strategy that integrates convolutional neural networks and variational autoencoders, supported by stochastically generated density fluctuations, into a regression analysis framework for extracting structural features of distorted lamellar phases from small angle neutron scattering data. To evaluate the efficacy of our proposed approach, we conducted computational accuracy assessments and applied it to the analysis of experimentally measured small angle neutron scattering spectra of AOT surfactant solutions, a frequently studied lamellar system. Findings: The findings unambiguously demonstrate that deep learning provides a dependable and quantitative approach for investigating the morphology of wide variations of distorted lamellar phases. It is adaptable for deciphering structures from the lamellar to sponge phase including intermediate structures exhibiting fused topological features. In conclusion, this research highlights the effectiveness of deep learning methods in tackling complex issues in the field of soft matter structural analysis and beyond.

36 MATERIALS SCIENCE↗
DOE OSTI2022

SCALE 6.2.4 Validation: Nuclear Criticality Safety

The computational bias of criticality safety computer codes must be established through the validation of the codes to critical experiments. A large collection of suitable experiments has been vetted by the International Criticality Safety Benchmark Evaluation Project (ICSBEP) and made available in the International Handbook of Evaluated Criticality Safety Benchmark Experiments (ICSBEP Handbook). More than 600 cases from this handbook have been prepared and reviewed within the Verified, Archived Library of Inputs and Data (VALID), which is maintained by the Reactor and Nuclear Systems Division at Oak Ridge National Laboratory. The performance of the KENO V.a and KENO-VI Monte Carlo codes within the SCALE 6.2.4 code system is assessed using the VALID models of benchmark experiments. A range of nuclear cross section libraries based on Evaluated Nuclear Data File (ENDF)/B-VII.1 in both multigroup (MG) and continuous energy (CE) formats is considered. The critical experiments available to validate the KENO V.a code cover 15 broad categories of systems. These systems use a range of fissile materials, including a range of uranium enrichments, various plutonium isotopic vectors, and some mixed uranium/plutonium oxides. The physical forms of the fissile material also vary and are represented as metal, solutions, or arrays of rods or plates in a water moderator. The neutron energy spectra of the systems also vary and cover fast, intermediate, mixed, and thermal spectra. Over 550 of the total cases use the KENO V.a code for the four nuclear data libraries considered in this report.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗
DOE OSTI2026

Wind and Temperature Consensus at Horn Point, HU-Beltsville, Piney Run (Maryland) in support of CoURAGE

The Maryland Department of the Environment (MDE) operates a ground-based atmospheric profiling network consisting of collocated radar wind profilers (RWP) and radio acoustic sounding systems (RASS) as part of its Ambient Air Monitoring Program. This network provides continuous observations of wind and temperature structure in the lower troposphere to support air quality forecasting, regulatory analysis, and atmospheric research. The network currently includes three fixed sites across Maryland: Horn Point (HP, lower eastern shore) [38.587525°,-76.141006°], Howard University-Beltsville (HUB, central Maryland) [39.055277°, -76.878632°], and Piney Run (PR, western Maryland) [39.705950°, -79.012000°] The network is designed to capture regional variability in atmospheric transport and boundary-layer processes. These systems measure vertical profiles of horizontal wind speed and direction using Doppler radar techniques, with observations typically spanning from ~100 m above ground level up to approximately 2.5–4 km. Measurements are derived from the Doppler shift of backscattered electromagnetic signals, enabling retrieval of wind vectors at multiple altitudes with high temporal resolution (e.g., 30-minute averages reported every 6 minutes). Each radar wind profiler is paired with a Radio Acoustic Sounding System (RASS) to provide profiles of virtual temperature in the lower atmosphere (~100–200 m AGL) by measuring the propagation speed of acoustic waves. Together, the RWP/RASS system yields a coupled data set of thermodynamic and kinematic atmospheric structure, including additional parameters such as vertical velocity, radial velocity, signal-to-noise ratio, and spectral width for advanced analysis. There are two types of files for each station: wind data (files with a "w" prefix) and virtual temperature RASS data (files with a "t" prefix). The wind data files are in the format wYYDDD.cns, where YY is the 2-digit year and DDD is the day of the year. The RASS virtual temperature data files are in the format tYYDDD.cns. Each record has the following header structure: Line 1 : Station Name RASS files Line 2 : RASS rev DeTect_2.0, WINDS files Line 2 : WINDS rev ATI 5.1 Line 3 : N latitude, W longitude, and site elevation (m) Line 4 : Date and begin time of consensus: yy mm dd hh mn ss plus # minutes to add to get UTC Line 5 : Consensus averaging time (minutes); number of beams; number of range gates Line 6 : Number of records required to make consensus (num) total number of records (tot) and the consensus window size (m/s) in the format: num:tot (window) RASS files Line 7 : no. of coded cells, no. of spec, pulse width (ns), and inter-pulse period (µs), WINDS files Line 7 : No. of coded cells, no. of spectra, pulse width (ns), and inter-pulse period (µs), each with a pair of values: first value is for oblique beams, second for vertical RASS files Line 8 : Full scale Doppler value (m/s) Delay to first gate (ns) Number of gates Spacing of gates (ns), WINDS files Line 8 : Full scale Doppler velocity (m/s), oblique and vertical Vertical correction applied to oblique beams? (0 = no, 1 = yes) Delay to first gate (ns), oblique and vertical Number of gates, oblique and vertical Spacing of gates (ns), oblique and vertical Line 9 : Azimuth and elevation (9s indicate vertical beam not used) RASS files Line 10, values : HT = Height above ground (km), T = Uncorrected virtual temperature consensus (deg C), Tc = Corrected virtual temperature consensus (deg C), W = Vertical wind consensus (9s indicate vertical beam not used, w-component, positive upward, m/s), CNT = Number of records that made consensus (for the 3 values in same order), SNR = Average signal to noise ratio (dB) of records in consensus (same order) WINDS files Line 10, values : HT = Height above ground (km), SPD = Wind speed (m/s), DIR = Wind direction (deg E of N from N), RAD = Radial velocities for each beam (m/s) in order given in azimuth and elevation line (positive toward radar; 9s indicate vertical beam not used, CNT = Number of records that made consensus, SNR = Average signal to noise ratio (dB) of records in consensus

{"wind speed and direction",temperature}↗