SEARCH · Search NASA

Results for “Data Characterization”

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.

SourceResearch connectionFrom yearThrough year

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

At least 379 records · Page 21

All sources NASA NTRS DOE OSTI

DOE OSTI2014

Geologic Modeling and Simulation Report for the Aquistore Project

The Plains CO 2 Reduction (PCOR) Partnership, through the Energy & Environmental Research Center (EERC), is collaborating with the Petroleum Technology Research Centre (PTRC) on site characterization; modeling and simulation; risk assessment; public outreach; and monitoring, verification, and accounting (MVA) activities for the Aquistore project. The Aquistore project is a carbon capture, utilization, and storage (CCUS) project situated near the town of Estevan, Saskatchewan, Canada, and the U.S.–Canada border. This project is managed by PTRC and will serve as buffer storage of carbon dioxide (CO 2 ) from the SaskPower Boundary Dam CCUS project, the world’s first commercial-scale postcombustion CCUS project from a coal-fired electric generating facility. To date, an injection well and an observation research well (~500 ft apart) have been drilled and completed at the Aquistore site, with injection anticipated to begin in 2014. Using a combination of site characterization data provided by PTRC and independently acquired information, the PCOR Partnership has constructed a static geologic model to assess the potential storage capacity of the Aquistore site and provide the foundation for dynamic simulation. The geologic model and the results of the predictive simulations will be used in the risk assessment process to help define an overall monitoring plan for the project and to assure stakeholders that the injected CO 2 will remain safely stored at the Aquistore site.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

EGS Collab SIGMA-V Project: Stimulation Investigations for Geothermal Modeling Analysis and Validation Phase 1 Report. For the period February 2017 – March 2019

The EGS Collab project was initiated in March 2017 to enable the subsurface modelling and research community to establish validations against controlled, small-scale, in-situ experiments focused on rock fracture behavior and permeability enhancement. The EGS Collab project is to provide the opportunity for reservoir model prediction and validation, in coordination with in depth analysis of geophysical and other fracture characterization data with an ultimate goal of further elucidating the basic relationship between stress, seismicity and permeability enhancement. In addition, the project is to identify and quantify other key governing parameters that impact permeability as well as understanding how these parameters change throughout the three EGS development phases (identify/characterize site, create reservoir, operate power plant). The project is to use comprehensive instrumentation and data collection effort to inform baseline, predictive, and post stimulation reservoir modeling is essential. This report describes the activities performed in Phase 1 of the project. The work done to date is extensive, and a large number of participants have contributed significant effort to enable project success. From planning to execution, we have stayed on track to address the objectives established by the Department of Energy in the paragraph above.

15 GEOTHERMAL ENERGY↗

DOE OSTI2019

EGS Collab SIGMA-V Project: Stimulation Investigations for Geothermal Modeling Analysis and Validation: For the period February 2017 – March 2019 (Phase 1 Report)

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Visualizing Uranium Crystallization from Melt: Experiment-Informed Phase Field Modeling and Machine Learning

The focus of this project was to observe and simulate the solidification of uranium metal at the crystallographic level from its molten state. Melting experiments were conducted at two different scales to observe microstructural evolution using either a laboratory-scale induction furnace (hundreds of grams of metal) or a microscope heating stage (hundreds of milligrams of metal), respectively. Experimental parameters and characterization data were then used to inform a phase field model of gamma-U crystal growth as dendrites with or without secondary phase impurities in the form of uranium carbide particles. Finally, training datasets were generated by the phase field model as inputs to a neural network, developed with the aim of providing a faster, cheaper surrogate model for microstructural simulations within a given parameter space. Progress is reported herein for each of these task areas. Ultimately, 1) an optical microscope heating stage capability has been stood-up for uranium metal solidification studies, 2) a phase field model was advanced to simulate multiple uranium grains growing in the presence of carbide impurity particles and 3) a neural network was constructed and optimized to predict the microstructure features of individually growing uranium crystals.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Stochastic Modeling Workflow to Generate Representative Geologic Variability in Training Dataset for SMART Initiative

The poster discusses the modeling workflow to generate ensemble of geologic realizations of the Illinois Basin Decatur Project (IBDP) site, based on available site characterization data and inherent uncertainty of those data, for use by project collaborators in DOE SMART Initiative (Phase 2) to build their forward modeling, history matching, and optimization workflows. This poster is summarized from the technical report for the SMART project submitted to U.S. DOE earlier this year.

Ganesh, Priya Ravi↗

DOE OSTI2024

NORTH DAKOTA CARBONSAFE PHASE III: SITE CHARACTERIZATION AND PERMITTING OF GEOLOGIC STORAGE OF CARBON DIOXIDE

The Energy & Environmental Research Center (EERC), in partnership with Minnkota Power Cooperative Inc. (Minnkota), SLB, and Computer Modelling Group Ltd. (CMG), supported wide-scale deployment of carbon capture and storage (CCS) as part of the U.S. Department of Energy (DOE) National Energy Technology Laboratory Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Initiative Phase III. This phase included the acquisition, analysis, and development of information to fully characterize two storage complexes to demonstrate viable storage resources for commercial volumes of CO2 (defined by DOE as a minimum of 50 million tonnes [MMt] of CO2 within a 30-year period) (National Energy Technology Laboratory, 2024). Phase III also involved the preparation, submission, and approval of North Dakota underground injection control (UIC) Class VI storage facility permits (SFPs)—required precursors to applications for Class VI injection well permits. The presumed viability of commercial-scale CCS, situated adjacent to Minnkota’s Milton R. Young Station (MRYS), is validated by Minnkota’s continued pursuit of Project Tundra—an initiative to build the world’s largest lignite-based CCS project in central North Dakota (www.projecttundrand.com). Project Tundra comprises two scopes of work, Tundra Capture (installation of postcombustion CO2 capture at MRYS) and Tundra SGS (secure geologic storage). The efforts of North Dakota CarbonSAFE Phase III, Site Characterization and Permitting, supported Tundra SGS. Extensive site-specific characterization activities included a successful multimeasurement geophysical approach and drilling a stratigraphic test well (J-ROC 1, subsequently renamed Liberty-1) adjacent to MRYS. Core collection and analyses, downhole testing and fluid sampling, and geophysical logging were performed on J-ROC 1 and on a nearby stratigraphic test well (known as J-LOC 1), which was drilled, cored, and tested under a complementary project funded by the North Dakota Lignite Research Program. The injection tests performed on J-LOC 1 positively impacted the CarbonSAFE project, resulting in fewer proposed injection wells and significant construction, operations, and monitoring cost savings. The characterization data collected and analyses performed were integrated into geologic models, and successive numerical simulations were run to determine CO2 plume extent and subsurface pressure buildup associated with the planned CO2 injection rate of nearly 4 MMt per year. The latter doubles the CarbonSAFE Initiative goal with an estimated 100 MMt of CO2 stored in 20 years. Application of the U.S. Environmental Protection Agency’s (EPA’s) method for estimating the Class VI Rule area of review (AOR) to the overpressurized Broom Creek Formation inspired an alternative method of calculation, called risk-based AOR delineation. This peer-reviewed method was applied for the first time during the storage facility-permitting process. The two SFP applications submitted in 2021 successfully resulted in North Dakota Industrial Commission (NDIC) orders in 2022 authorizing the creation of the storage facility areas and amalgamation of pore space as well as establishing financial responsibility requirements. After approval of the SFPs, Minnkota filed in 2022 applications for permits to reenter the J-ROC 1 well and to drill two new wells—all with the intended purpose to become Class VI injection wells. To establish eligibility under the Internal Revenue Code for Section 45Q tax incentives, a monitoring, reporting, and verification (MRV) plan was prepared and submitted by Minnkota to EPA in 2022, resulting in the first such plan approved in North Dakota. Also in 2022, under the National Environmental Policy Act (NEPA), Minnkota prepared and submitted an environmental information volume (EIV) describing the proposed CCS project and associated potential environmental impacts. Based on the EIV, DOE determined that the proposed construction project required an environmental assessment, and Minnkota submitted the first draft in 2023 and a revised draft in 2024. Both submissions were followed by a public comment period. Subsequently, DOE issued a finding of no significant impact (FONSI) on September 13, 2024. A successful outreach program, strongly based in the production, presentation, and dissemination of informational material, fostered an environment to aid stakeholders in making informed decisions regarding the planned project. Opportunities for public input were provided at various steps along the way, including at county planning and zoning meetings, before and during the SFP administrative hearing, and during environmental assessment public comment periods. In addition, land/pore space owners and mineral owners had various points of contact, including granting access rights, securing pore space leasing, and mineral owner notifications. Based upon the successful storage facility permitting issued by NDIC, approval of the MRV plan by EPA, and receipt of a FONSI under the NEPA, Minnkota is continuing its pursuit of Project Tundra. In December 2023, the Office of Clean Energy Demonstrations under its Carbon Capture Demonstrations Projects Program announced funding for the capture system (Office of Clean Energy Demonstrations, 2023) and a proposal for CarbonSAFE Phase IV: Construction funding was submitted in March 2024 for the storage project. A go/no-go decision to proceed with construction and operations in the Broom Creek Formation is anticipated in 2024. References National Energy Technology Laboratory, CarbonSafe Initiative, https://netl.doe.gov/carbon-management/carbon-storage/carbonsafe (accessed August 2024). Office of Clean Energy Demonstrations, 2023, OCED selects three projects in CA, ND, and TX to reduce harmful carbon pollution, create new economic opportunities, and advance carbon reducing technologies, December, www.energy.gov/oced/articles/oced-selects-three-projects-ca-nd-and-tx-reduce-harmful-carbon-pollution-create-new (accessed August 2024).

Peck, Wesley↗

DOE OSTI2024

Characterization of C-Reactor (105-C) Moderator Tanks 204 and 205

Area Completion Project (ACP)/Savannah River Nuclear Solutions (SRNS) has requested Savannah River National Laboratory (SRNL) to perform chemical and radiological analyses on moderator heavy water samples from C-Reactor (105-C) in Moderator Tanks 204 and 205. The heavy water samples have been characterized using SRNL analytical methods. Information generated from the characterization of these heavy water samples provide a basis for determining the residual contamination remaining in the tanks. These analyses are needed in order to update the C-Reactor Contaminant migration groundwater model and report, to help determine a disposition pathway for the moderator water, and to ship samples off-site to the Southwest Research Institute (SWRI). This report presents characterization results for the March 2024 C-Reactor Moderator Tank 204 and 205 heavy water samples. SRNL results are critical to allow ACP to complete this Performance Based Incentive project on time. Based on the characterization data provided in this report, results of these samples meet customer expectations and satisfy the Technical Assistance Request (TAR).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2018

The Hanford Waste End Effector Phase II Test Report

This report describes the Phase II testing program of the Hanford Waste End Effector (HWEE) at the Washington River Protection Solutions Cold Test Facility (CTF). Phase II testing builds on the completed Phase I development testing (PNNL-26856) to address some key actual waste challenges as outlined in the Phase II test plan (PNNL-27422). This testing demonstrated retrieval of a mixed layered simulant and retrieval of uneven simulant profiles like that found near tank walls. A separate demonstration using only the HWEE conveyance jet pump assessed the lifting capabilities of this device for transporting waste out of an underground tank. The Pacific Northwest National Laboratory (PNNL)-designed robotic gantry system and associated systems (e.g., tanks, high-pressure water delivery and valves, instruments, etc.) used at CTF during Phase I were modified and upgraded to implement the Phase II test program and measure various process parameters. The tests demonstrated retrieval of water and Kaolin (sludge) simulant to determine pumping rate, dilution factors, and screen fouling rate. This report will first describe the test equipment, instrumentation, simulant preparation procedures, and testing methodology. Testing results presented include HWEE water usage versus operating pressure of modified components from Phase I, simulant characterization data, dilution ratios, and retrieval rates. Reaction forces and other factors that would affect the remote operation of the HWEE will also be presented. Results of the separate jet pump vertical lift demonstration to a fixed height of at least 35 feet are also presented.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2022

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

Carbon capture and storage (CCS) is one approach being studied by the U.S. Department of Energy to help mitigate global warming. The process involves capturing CO 2 emissions from industrial sources and permanently storing them in deep geologic formations (storage reservoirs). However, CCS projects generally target “green field sites,” where there is often little characterization data and therefore large uncertainty about the petrophysical properties and other geologic attributes of the storage reservoir. Consequently, ensemble-based approaches are often used to forecast multiple realizations prior to CO 2 injection to visualize a range of potential outcomes. In addition, monitoring data during injection operations are used to update the pre-injection forecasts and thereby improve agreement between forecasted and observed behavior. Thus, a system for generating accurate, timely forecasts of pressure buildup and CO 2 movement and distribution within the storage reservoir and for updating those forecasts via monitoring measurements becomes crucial. This study proposes a learning-based prediction method that can accurately and rapidly forecast spatial distribution of CO 2 concentration and pressure with uncertainty quantification without relying on traditional inverse modeling. The machine learning techniques include dimension reduction, multivariate data analysis, and Bayesian learning. The outcome is expected to provide CO 2 storage site operators with an effective tool for timely and informative decision making based on limited simulation and monitoring data.

58 GEOSCIENCES↗

DOE OSTI2016

Fusion of mobile in situ and satellite remote sensing observations of chemical release emissions to improve disaster response

Chemical release disasters have serious consequences, disrupting ecosystems, society, and causing significant loss of life. Mitigating the destructive impacts relies on identification and mapping, monitoring, and trajectory forecasting. Improvements in sensor capabilities are enabling airborne and space-based remote sensing to support response activities. Key applications are improving transport models in complex terrain and improved disaster response. Understanding urban atmospheric transport in the Los Angeles Basin, where topographic influences on transport patterns are significant, was improved by leveraging the Aliso Canyon leak as an atmospheric tracer. Plume characterization data was collected by the AutoMObile trace Gas (AMOG) Surveyor, a commuter car modified for science. Mobile surface in situ CH 4 and winds were measured by AMOG Surveyor under Santa Ana conditions to estimate an emission rate of 365±30% Gg yr -1 . Vertical profiles were collected by AMOG Surveyor by leveraging local topography for vertical profiling to identify the planetary boundary layer at ~700 m. Topography significantly constrained plume dispersion by up to a factor of two. The observed plume trajectory was used to validate satellite aerosol optical depth-inferred atmospheric transport, which suggested the plume first was driven offshore, but then veered back towards land. Numerical long-range transport model predictions confirm this interpretation. Lastly, this study demonstrated a novel application of satellite aerosol remote sensing for disaster response.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The De-Icing Comparison Experiment (D-ICE): a study of broadband radiometric measurements under icing conditions in the Arctic

Abstract. Surface-based measurements of broadband shortwave (solar) and longwave (infrared) radiative fluxes using thermopile radiometers are made regularly around the globe for scientific and operational environmental monitoring. The occurrence of ice on sensor windows in cold environments – whether snow, rime, or frost – is a common problem that is difficult to prevent as well as difficult to correct in post-processing. The Baseline Surface Radiation Network (BSRN) community recognizes radiometer icing as a major outstanding measurement uncertainty. Towards constraining this uncertainty, the De-Icing Comparison Experiment (D-ICE) was carried out at the NOAA Atmospheric Baseline Observatory in Utqiaġvik (formerly Barrow), Alaska, from August 2017 to July 2018. The purpose of D-ICE was to evaluate existing ventilation and heating technologies developed to mitigate radiometer icing. D-ICE consisted of 20 pyranometers and 5 pyrgeometers operating in various ventilator housings alongside operational systems that are part of NOAA's Barrow BSRN station and the US Department of Energy Atmospheric Radiation Measurement (ARM) program North Slope of Alaska and Oliktok Point observatories. To detect icing, radiometers were monitored continuously using cameras, with a total of more than 1 million images of radiometer domes archived. Ventilator and ventilator–heater performance overall was skillful with the average of the systems mitigating ice formation 77 % (many >90 %) of the time during which icing conditions were present. Ventilators without heating elements were also effective and capable of providing heat through roughly equal contributions of waste energy from the ventilator fan and adiabatic heating downstream of the fan. This provided ∼0.6 ∘C of warming, enough to subsaturate the air up to a relative humidity (with respect to ice) of ∼105 %. Because the mitigation technologies performed well, a near complete record of verified ice-free radiometric fluxes was assembled for the duration of the campaign. This well-characterized data set is suitable for model evaluation, in particular for the Year of Polar Prediction (YOPP) first Special Observing Period (SOP1). We used the data set to calculate short- and long-term biases in iced sensors, finding that biases can be up to +60 W m−2 (longwave) and −211 to +188 W m−2 (shortwave). However, because of the frequency of icing, mitigation of ice by ventilators, cloud conditions, and the timing of icing relative to available sunlight, the biases in the monthly means were generally less than the aggregate uncertainty attributed to other conventional sources in both the shortwave and longwave.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2013

A novel Whole Air Sample Profiler (WASP) for the quantification of volatile organic compounds in the boundary layer

The emission and fate of reactive VOCs is of inherent interest to those studying chemical biosphere-atmosphere interactions. In-canopy VOC observations are obtainable using tower-based samplers, but the lack of suitable sampling systems for the full boundary 5 layer has limited the data characterizing the vertical structure of such gases above the canopy height and still in the boundary layer. This is the important region where many reactive VOCs are oxidized or otherwise removed. Here we describe an airborne sampling system designed to collect a vertical profile of air into a 3/800 OD tube 150m in length. The inlet ram air pressure is used to flow sampled air through the 10 tube, which results in a varying flow rate based on aircraft speed and altitude. Since aircraft velocity decreases during ascent, it is necessary to account for the variable flow rate into the tube. This is accomplished using a reference gas that is pulsed into the air stream so that the precise altitude of the collected air can be reconstructed post-collection. The pulsed injections are also used to determine any significant effect 15 from diffusion/mixing within the sampling tube, either during collection or subsequent extraction for gas analysis. This system has been successfully deployed, and we show some measured vertical profiles of isoprene and its oxidation products methacrolein and methyl vinyl ketone from a mixed canopy near Columbia, Missouri.

Mak, J. E.↗

DOE OSTI2025

Raptor

Raptor is an efficient Python-based tool for predicting the formation and morphology of stochastic lack of fusion defects in metal AM processes. A major obstacle for the qualification and certification of additively manufactured parts in critical applications continues to be performance variability caused in part by porosity-related defects. High-fidelity process models that could predict these defect features are currently too computationally expensive for component-level analysis. To address this, Raptor employs a high-performance geometric method to model the dynamic melt pool rather than relying on computationally intensive thermal fluid dynamics. This allows Raptor to rapidly identify regions of unmelted material that correspond to lack of fusion pores. The efficiency of this approach significantly reduces the time and resources needed for generating 3D defect predictions, which enables users to conduct large-scale parameter studies and evaluate how process variations affect part quality. The framework offers operational flexibility; users can execute simulations through a simple command line interface or integrate core functions as a library within larger computational workflows. Simulation outputs include 3D porosity maps for visualization and tools for quantitative morphological analysis. These results are suitable for direct comparison with experimental characterization data from methods such as X-ray computed tomography and can be used for statistical process optimization.

Subraveti, Vamsi [Vanderbilt Univ., Nashville, TN ↗

DOE OSTI2019

Soil Organic Horizon Exometabolomics Extracts and Soil Characteristics with Depth, Utqiagvik (Barrow), Alaska, 2014

This dataset includes chemical characterization data for four soil cores (organic horizon) collected in August 2014 from beneath two vegetation types (Eriophorum angustifolium and Carex aquatilis) from the centers of a low-centered and high-centered polygon at NGEE Areas A and B, respectively, on the Barrow Environmental Observatory near Barrow, Alaska. Measurements include gravimetric soil water content, total carbon and nitrogen, total organic carbon, and metabolomics data (low molecular weight organics). Data from the file Processed_LMW_DOM_Results_20190422.xlsx was separated out into csv files for interoperability. This dataset contains one xlsx file, twelve csv files, two pdf files, one txt file, and four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

EGS Stimulation Design with Uncertainty Quantification at the EGS Collab Site

Engineering a robust hydraulic connection between wells is one of the most difficult aspects of enhanced geothermal systems (EGS). Designing and constructing such hydraulic connections requires and understanding of the in situ state of stress and the heterogeneities and discontinuities that naturally exist and may control the stimulation. Even with comprehensive stress and formation characterization programs substantial uncertainty remains in these key parameters. This is especially the case in high-temperature EGS environments where drilling conditions are often difficult and a far fewer logging and testing options are available. This paper presents a new approach for explicitly quantifying the uncertainties in the state of stress using a Bayesian Markov Chain Monte Carlo method. This approach produces a probability distribution for the stress tensor, including a general 3D orientation, that reflects the uncertainties in all the observations or indicators used to constrain the stress state. This method is demonstrated on the characterization data for the EGS Collab Experiment 2 site. The output of the analysis is used to guide the design of the planned stimulations. In the case of research projects like EGS Collab, explicitly quantifying the uncertainties in the stress state allow for more rigorous hypothesis testing by allowing conclusions drawn from the experiments to be interpreted in the context of the uncertain knowledge about conditions in the test bed.

Burghardt, Jeffrey A.↗

NASA NTRS1977

Electrode surface studies by LEED-Auger

The role the electronic and geometric structures of the metal surface play in electrochemical surface reactions remains as yet an unknown factor. In order to investigate these surface contributions to electrochemical reactions, a low-energy-electron diffraction (LEED) and an Auger electron spectrometer (AES) have been combined with an electrochemical thin-layer cell. The surface to be studied electrochemically is first characterized by LEED-AES and then transferred into a second chamber where it becomes part of the electrochemical thin-layer cell. Electrochemical reactions are then run on this surface. The sample may then be transferred back to the LEED-AES chamber for further characterization. Data on Pt (111) will be presented.

Ogrady, W. E.↗

NASA NTRS1977

Charge coupled devices

The results are presented of a program to design, fabricate, and test CCD arrays suitable for operation in an electron-bombarded mode. These intensified charge coupled devices have potential application to astronomy as photon-counting arrays. The objectives of this program were to deliver arrays of 250 lines of 400 pixels each and some associated electronics. Some arrays were delivered on tube-compatible headers and some were delivered after incorporation in vacuum tubes. Delivery of these devices required considerable improvements to be made in the processing associated with intensified operation. These improvements resulted in a high yield in the thinning process, reproducible results in the accumulation process, elimination of a dark current source in the accumulation process, solution of a number of header related problems, and the identification of a remaining major source of dark current. Two systematic failure modes were identified and protective measures established. The effects of tube processing on the arrays in the delivered ICCDs were determined and are reported along with the characterization data on the arrays.

Walker, J. W.↗

NASA NTRS1979

Dual-fuel, dual-throat engine preliminary analysis

A propulsion system analysis of the dual fuel, dual throat engine for launch vehicle applications was conducted. Basic dual throat engine characterization data were obtained to allow vehicle optimization studies to be conducted. A preliminary baseline engine system was defined.

Obrien, C. J.↗