Search NASA⌕ Search

SEARCH · Search NASA

Results for “Plume monitoring”

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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Gas transport across the low-permeability containment zone of an underground nuclear explosion

Understanding the nature of gas transport from an underground nuclear explosion (UNE) is required for evaluating the ability to detect and interpret either on-site or atmospheric signatures of noble gas radionuclides resulting from the event. We performed a pressure and chemical tracer monitoring experiment at the site of an underground nuclear test that occurred in a tunnel in Nevada to evaluate the possible modes of gas transport to the surface. The site represents a very well-contained, low gaspermeability end member for past UNEs at the Nevada National Security Site. However, there is very strong evidence that gases detected at the surface during a period of low atmospheric pressure resulted from fractures of extremely small aperture that are essentially invisible. Our analyses also suggest that gases would have easily migrated to the top of the high-permeability collapse zone following the detonation minimizing the final distance required for migration along these narrow fractures to the surface. This indicates that on-site detection of gases emanating from such low-permeability sites is feasible while standoff detection of atmospheric plumes may also be possible at local distances for sufficiently high fracture densities. Finally, our results show that gas leakage into the atmosphere also occurred directly from the tunnel portal and should be monitored in future tunnel gas sampling experiments for the purpose of better understanding relative contributions to detection of radioxenon releases via both fracture network and tunnel transport.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2021

Seismic monitoring of a small CO 2 injection using a multi-well DAS array: Operations and initial results of Stage 3 of the CO 2 CRC Otway project

Active time-lapse seismic is widely employed for monitoring CO 2 geosequestration due to its ability to track the distribution of fluids in space and time. However, standard 4D seismic monitoring suffers from several challenges, including high cost, disruption to other land uses, and, consequently, relatively large intervals between monitor surveys. Some of these challenges can be mitigated using permanently installed sources and receivers. Such an approach was tested at the CO 2 CRC Otway site by continuous offset VSP monitoring of 15,000 t of supercritical CO 2 injected into an aquifer 1,500 m deep with nine permanent seismic sources (surface orbital vibrators or SOVs) and five downhole fibre-optic receivers. This continuous monitoring is complemented by multi-well 4D VSP using a mobile vibroseis source and the same DAS receivers, which included one baseline and two monitor surveys after injection of 4,000 and 12,000 t of CO 2 . The continuous DAS-SOV monitoring detected an abrupt increase of travel times below the injection interval on the second day of injection (after injection of 300 t of CO 2 ) and tracked the growth of the areal CO 2 plume by mapping changes of reflection amplitudes. The plume is also detected by time-lapse changes of reflection amplitudes in multi-well 4D VSPs. The plume images obtained from continuous offset VSP and 4D VSP are broadly consistent with each other but with some differences due to differences in illumination, lateral variations of velocities and seismic anisotropy. Furthermore, these differences also serve as a measure of uncertainty of 4D VSP images.

4D VSP↗
DOE OSTI2021

Laser-induced fluorescence of filament-produced plasmas

Self-guided ultrafast laser filaments are a promising method for laser beam delivery and plasma generation for standoff and remote detection of elements and isotopes via filament-induced breakdown spectroscopy (FIBS). Yet, there are several challenges associated with the practical application of FIBS, including delivery of sufficient laser energy at the target for generating plasma with a copious amount of emission signals for obtaining a high signal-to-noise ratio. Here, in this study, we use laser-induced fluorescence (LIF) to boost the emission signal and reduce self-reversal in the spectral profiles. Ultrafast laser filaments were used to produce plasmas from an Al 6061 alloy target at various standoff distances from 1 to 10 m. For LIF emission enhancement, a narrow linewidth continuous-wave laser was used in resonance with a 394.40 nm Al I resonant transition, and the emission signal was monitored from the directly coupled transition at 396.15 nm. Emission signal features of Al I are significantly enhanced by resonant excitation. In addition, LIF of filament ablation plumes reduces the self-reversal features seen in the thermally excited spectral profiles. Time-resolved two-dimensional fluorescence spectroscopy was performed for evaluating the optical saturation effects, which are found to be non-negligible due to high Al atomic densities in the filament-produced plasmas.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Multi-Scale Seismic Measurements for Site Characterization and CO2 Monitoring in an Enhanced Oil Recovery/Carbon Capture, Utilization, and Sequestration Project, Farnsworth Field, Texas

To address the challenges of climate change, significantly more geologic carbon sequestration projects are beginning. The characterization of the subsurface and the migration of the plume of supercritical carbon dioxide are two elements of carbon sequestration that can be addressed through the use of the available seismic methods in the oil and gas industry. In an enhanced oil recovery site in Farnsworth, TX, we employed three separate seismic techniques. The three-dimensional (3D) surface seismic survey required significant planning, design, and processing, but produces both a better understanding of the subsurface structure and a three-dimensional velocity model, which is essential for the second technique, a timelapse vertical seismic profile, and the third technique, cross-well seismic tomography. The timelapse 3D Vertical Seismic Profile (3D VSP) revealed both significant changes in the reservoir between the second and third surveys and geo-bodies that may represent the extent of the underground carbon dioxide. The asymmetry of the primary geo-body may indicate the preferential migration of the carbon dioxide. The third technique, cross-well seismic tomography, suggested a strong correlation between the well logs and the tomographic velocities, but did not observe changes in the injection interval.

Energy & Fuels↗
DOE OSTI2024

Time-lapse seismic inversion for CO 2 saturation with SeisCO2Net: An application to Frio-II site

Seismic monitoring of geological CO 2 storage (GCS) involves highly nonlinear seismic inversion and petrophysical inversion, making it challenging to estimate CO 2 volume efficiently and detect possible early CO 2 leakages. Deep learning (DL) using convolutional neural networks (CNNs) has shown promise in solving highly nonlinear seismic inversion problems. However, direct estimation of CO 2 plume extent/saturation from time-lapse seismic gathers using DL is still underexplored, with no reported field applications to date. The investigation of field data is primarily hindered by scarcity of field data for neural network training. Other obstacles include highly nonlinear seismic-petrophysics inverse relationship, and presence of noise in field seismic data. We introduce SeisCO2Net, a deep CNN that predicts CO 2 saturation maps directly from time-lapse full waveform shot gathers. For training, we use site-specific geological information, fluid flow physics, rock physics, and seismic modeling to generate synthetic datasets that closely resemble the CO 2 storage site. Synthetic tests show promising results, inspiring us to apply SeisCO2Net's trained weights on field data collected at Frio-II GCS site by leveraging transfer learning principles. As reference, we compare SeisCO2Net's predicted CO 2 saturation maps with results obtained from physics-based inversion. Our analyses show both methods display similar CO 2 plume shapes, reasonable CO 2 plume characteristics, and comparable saturation values. Our results suggest pre-training CNNs on physics-informed synthetic datasets and then applying the learned weights to field data is a viable approach to estimating field CO 2 saturation. This method effectively addresses the scarcity of field training data, thus encouraging the feasibility of long-term GCS monitoring.

58 GEOSCIENCES↗
DOE OSTI2021

A Statistical Evaluation of WRF-LES Trace Gas Dispersion Using Project Prairie Grass Measurements

In recent years, new measurement systems have been deployed to monitor and quantify methane emissions from the natural gas sector. Large-eddy simulation (LES) has complemented measurement campaigns by serving as a controlled environment in which to study plume dynamics and sampling strategies. However, with few comparisons with controlled-release experiments, the accuracy of LES for modeling natural gas emissions is poorly characterized. In this paper, we evaluate LES from the Weather Research and Forecasting (WRF) Model against Project Prairie Grass campaign measurements and surface layer similarity theory. Using WRF-LES, we simulate continuous emissions from 30 near-surface trace gas sources in two stability regimes: strong convection and weak convection. We examine the impact of grid resolutions ranging from 6.25 to 52 m in the horizontal dimension on model results. We evaluate performance in a statistical framework, calculating fractional bias and conducting Welch’s t tests. WRF-LES accurately simulates observed surface concentrations at 100 m and beyond under strong convection; simulated concentrations pass t tests in this region irrespective of grid resolution. However, in weakly convective conditions with strong winds, WRF-LES substantially overpredicts concentrations—the magnitude of fractional bias often exceeds 30%, and all but one t test fails. The good performance of WRF-LES under strong convection correlates with agreement with local free convection theory and a minimal amount of parameterized turbulent kinetic energy. The poor performance under weak convection corresponds to misalignment with Monin–Obukhov similarity theory and a significant amount of parameterized turbulent kinetic energy.

17 WIND ENERGY↗
DOE OSTI2026

Comparative Performance of Gaussian Plume and Backward Lagrangian Stochastic Models for Near-Field Methane Emission Estimation Using a Single Controlled Release Experiment

Methane (CH 4 ) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH 4 emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH 4 emissions at the facility-level. Near-field quantification of methane (CH 4 ) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH 4 emissions to controlled single-point emissions between 0.4 and 5.2 kg CH 4 h −1 . Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain.

gaussian plume↗
DOE OSTI2022

Reconciliation of asynchronous satellite-based $\mathrm{NO_2}$ and $\mathrm{XCO_2}$ enhancements with mesoscale modeling over two urban landscapes

Fossil fuel carbon dioxide (CO 2ff ), the main driver of global warming and climate change, is often co-emitted with nitrogen oxides (NO x ) and precursors to ground-level ozone from anthropogenic sources like power plants or vehicles. In urban and suburban areas, satellite-based NO 2 can be used as a proxy to track the emissions of CO 2ff . Because of NO 2 ’s shorter lifetime, urban NO 2 plumes are more distinguishable from backgrounds and more sensitive to variations in emissions. However, the combination of these two gases is limited by the asynchrony among NO 2 and CO 2 monitoring satellites. We used CO 2ff simulated by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) model to reconcile the tropospheric NO 2 vertical column density (VCD) from the Tropospheric Monitoring Instrument (TROPOMI) and column-averaged dry-air mole fractions of carbon dioxide enhancements (ΔXCO 2 ) from Orbiting Carbon Observatory 3 (OCO-3) Snapshot Area Maps (SAMs) over a multicity area, Washington D.C.-Baltimore (DC-Balt), and a basin city, Mexico City. NO 2 /CO 2ff ratios over DC-Balt are smaller than Mexico City, indicative of stricter emission restrictions, a more combustion-efficient vehicle fleet, and higher combustion efficiency due to lower altitude in DC-Balt. For single-track cases, the spatial correlations between NO 2 and ΔXCO 2 over Mexico City are stronger than DC-Balt because the NO 2 and CO 2 are mostly trapped in the valley of Mexico City, while DC-Balt is severely affected by distant sources (i.e., US East Coast cities). Using multi-track averaging, spatial correlation coefficients increase with the number of days used for averaging. The correlations reached a maximum when averaging >12 continuous images for DC-Balt and > 10 continuous images for Mexico City. This finding indicates that multi-track averaging using modeled CO 2ff as a proxy is helpful to filter the noise in single-track images, to cancel the interference from distant sources, and to magnify correlations between NO 2 and CO 2ff . Mexico City showed stronger spatial correlations but weaker temporal correlations than DC-Balt due to biomass burning hot spots and large transport errors caused by the trapping effects of the surrounding mountains. Tracking the 20-day moving average of CO 2ff emissions using TROPOMI NO 2 seems technically feasible, considering the relationship between correlation coefficients and the number of available satellite images.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project

We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.

CO2 plume imaging↗
DOE OSTI2020

CO 2 plume evolution in a depleted natural gas reservoir: Modeling of conformance uncertainty reduction over time

Uncertainty in the long-term fate of CO 2 injected for geologic carbon sequestration (GCS) is a significant barrier to the adoption of GCS as a greenhouse-gas emission-mitigation for industry and regulatory agencies alike. Here, we present a modeling study that demonstrates that the uncertainty in forecasts of GCS site performance decreases over time as monitoring data are used to update operational models. We consider a case study of GCS in a depleted natural gas reservoir, with CO 2 injection occurring over 20 years, with a 50-year post-injection site care period. We constructed a detailed model to generate the actual model output, which is considered synthetic observation data. A series of simpler operational models based on limited data and assumptions about how an operator would model such a site are then run and compared against actual model output at specific monitoring points after one year, two years, etc. The operational model is updated and improved using the synthetic observation data from the actual model at the same time intervals. Model parameter values and model features needed to be updated over time to improve matches to the actual model. These kinds of model adjustments would be a normal part of reservoir engineering and site management at GCS sites. Uncertainty in two key measures related to site performance decreases with time: extent of the CO 2 plume up-dip migration, and radial extent of the pressure pulse. This conclusion should help allay the concerns of industry and regulators about uncertainty in long-term fate of CO 2 at GCS sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗
DOE OSTI2020

Sustaining On-going Risk Communication at the Riverton, Wyoming, Processing Site - 20310

An environmental risk assessment report has been completed to provide an updated assessment regarding current site conditions for the Riverton, Wyoming, Processing site. Argonne National Laboratory conducted the assessment in collaboration with the U.S Department of Energy (DOE) Office of Legacy Management (LM) and the Northern Arapaho Natural Resources Office (NANRO). The data quality objectives process conducted confirmed that data from plants growing on the Riverton site would be useful and would address an outstanding concern. Data available from site soil, groundwater, and surface water were also used in the assessment in conjunction with the new plant data. A plant survey was then conducted in 2018 to identify the plants at the Riverton site with known traditional Native American cultural uses for sampling and analysis. Laboratory analysis was conducted on the plant samples for the contaminants of concern. Samples were collected from plants growing on the groundwater plume area of the site, and the same was done for eight other areas not affected by the groundwater plume but still within the institutional control boundary. These eight areas served as reference areas for this study. This human health and ecological assessment update provide the quantitative risk information that was qualitatively addressed in a 1995 Risk Assessment Report on plants, livestock, and surface water exposures at the Riverton site [1]. The conditions at the Riverton site are protective of human health and the environment given the results of the update, in combination with past completed remedial action and ongoing monitoring activities and IC implementation. (authors)

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

Oxidation in laser-generated metal plumes

The temporal evolution of atoms and molecules in a laser-produced plasma was investigated using optical emission spectroscopy for several metal targets (i.e., Al, Ti, Fe, Zr, Nb, and Ta). Plasmas from metal targets were generated by focusing 1064 nm, 6 ns pulses from an Nd:YAG laser. Gas-phase oxidation/plasma chemistry was initiated by adding O2 (partial pressures up to ≈20%) to an N2 environment where the total background pressure was kept at a constant 1 atmosphere. Temporally resolved emission spectral features were used to track the gas-phase oxidation. The dynamics of atomic and molecular species were monitored using space-resolved time-of-flight emission spectroscopy. Our results highlight that the partial pressure of O2 strongly influences spectral features and molecular formation in laser-produced plasmas. Atoms and molecules co-exist in plasmas, although with different temporal histories depending on the target material due to differences in thermo- and plasma chemical reactions occurring in the plume.

Kautz, Elizabeth J. (ORCID:0000000263389223)↗
DOE OSTI2025

Building 100 Groundwater Bioremediation at the Former DOE Pinellas Plant, Florida: Review of Progress and Opportunities

Weapons research, development, and production operations at the former Pinellas Plant, which includes the Building 100 area, released chlorinated organic solvents into the subsurface, contaminating the underlying soil and groundwater. The site was sold to Pinellas County and is now home to a thriving industrial park known as the Young - Rainey Science, Technology, and Research (STAR) Center. The US Department of Energy (DOE) has applied bioremediation at the Building 100 Area as a key technology to clean up the chlorinated volatile organic compound (cVOC) contamination in soil and groundwater. The monitoring data indicate significant progress toward remedial objectives over the past two decades. Starting conditions in the 1980s-1990s included areas containing residual undissolved dense nonaqueous phase liquids (DNAPLs) and the associated presence of an extensive high concentration plume in the groundwater. The original parent cVOCs were primarily tetrachloroethene (PCE) and trichloroethene (TCE). After several informative pilot studies, bioremediation was implemented at the Building 100 Area of the site and relies on reductive biological pathways and the sequential removal of chlorine from the parent cVOCs forming dichloroethane (DCE) and chloroethene (vinyl chloride, VC). As bioremediation sites evolve toward cleanup, the trends in VC concentrations often serve as a critical indicator for progress and remediation timeframe because VC typically has a lower concentration target remedial objective (nominally 1 to 2 μg/L) compared to PCE and TCE (nominally 3 to 5 μg/L).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Time-Lapse Gravity Monitoring of CO2 Migration Based on Numerical Modeling of a Faulted Storage Complex

In this study, the performance of both surface and borehole time-lapse gravity monitoring to detect CO2 leakage from a carbon storage site is evaluated. Several hypothetical scenarios of CO2 migration in a leaky fault, and thief zones at different depths at the Kimberlina site (California, USA) constitute the basis of the approach. The CO2 displacement is simulated using the TOUGH2 simulator applied to a detailed geological model of the site. The gravity responses to these CO2 plumes are simulated using forward modeling with sensors at ground surface and in vertical boreholes. Results of inversion on one scenario are also presented. The surface-based gravity responses obtained for the different leakage scenarios demonstrate that leakage can be detected at the surface in all the scenarios but the time to detection is highly variable (10 to 40 years) and dependent on the detection threshold considered. Borehole measurements of the vertical component of gravity provide excellent constrains in depth when they are located in proximity of the density anomaly associated with the presence of CO2, thus discriminating multiple leaks in different thief zones. Joint inversion of surface and borehole data can bring valuable information of the occurrence of leakages and their importance by providing a reasonable estimate of mass of displaced fluids. This study demonstrates the importance of combining multiphase flow simulations with gravity modeling in order to define if and when gravity monitoring would be applicable at a given storage site.

Time-lapse gravity monitoring, leak detection, CCS↗
DOE OSTI2021

Hydrogen Wide Area Monitoring of LH2 Releases at HSE for the PRESHLY Project

The characterization of liquid hydrogen (LH2) releases has been identified as an international research priority to expand the safe use of hydrogen as an energy carrier. Empirical field measurements such as those afforded by Hydrogen Wide Area Monitoring (HyWAM) can elucidate the behavior of LH2 releases, which can then be used to support and validate dispersion models. HyWAM can be defined as the quantitative three-dimensional spatial and temporal profiling of planned or unintentional hydrogen releases. The NREL Sensor Laboratory developed a HyWAM based upon a distributed array of hydrogen Sensors. The NREL Sensor Laboratory and Health and Safety Executive (HSE) formally committed to collaborate on profiling GH2 and LH2 releases, which allowed for the integration of the NREL HyWAM into the HSE LH2 release behavior investigation supported by the FCH JU Prenormative Research for the Safe Use of Liquid Hydrogen (PRESLHY) program. A HyWAM system consisting of 32 hydrogen measurement points and co-located temperature sensors were distributed downstream of the LH2 release apparatus developed by HSE. In addition, there were proximal wind and weather monitors. In a separate presentation at this conference "HSE SD Experimental Summary for the Characterisation, Dispersion and Electrostatic Hazards of LH2 for the PRESLHY Project" HSE researchers summarize the experimental apparatus and experimental protocols utilized in the HSE LH2 releases that were performed under the auspices of PRESLHY. To supplement the HSE presentation, this presentation will focus on the spatial and temporal behavior LH2 releases as measured by the NREL HyWAM. Correlations to ambient conditions, such as wind speed and direction, plume temperature and hydrogen concentrations will be discussed in addition to the design and performance of the NREL HyWAM, and its potential for improving hydrogen facility safety.

HYDROGEN↗
DOE OSTI2022

Potential Seismicity Along Basement Faults Induced by Geological Carbon Sequestration

Large-scale CO 2 sequestration into geological formations has been suggested to reduce CO 2 emissions from industrial activities. However, much like enhanced geothermal stimulation and wastewater injection, CO 2 sequestration has a potential to induce earthquake along weak faults, which can be considered a negative impact on safety and public opinion. This research shows the physical mechanisms of potential seismic hazards along basement faults driven by CO 2 sequestration under variation in geological and operational constraints. Specifically we compare the poroelastic behaviors between multiphase flow and single-phase flow cases, highlighting specific needs of evaluating induced seismicity associated with CO 2 sequestration. In contrast to single-phase injection scenario, slower migration of the CO 2 plume than pressure pulse may delay accumulation of pressure and stress along basement faults that may not be mitigated immediately by shut-in of injection. The impact of multiphase flow system, therefore, needs to be considered for proper monitoring and mitigation strategies.

58 GEOSCIENCES↗
DOE OSTI2023

Impact of environmental oxygen on nanoparticle formation and agglomeration in aluminum laser ablation plumes

Here, the role of ambient oxygen gas (O 2 ) on molecular and nanoparticle formation and agglomeration was studied in laser ablation plumes. As a lab-scale surrogate to a high explosion detonation event, nanosecond laser ablation of an aluminum alloy (AA6061) target was performed in atmospheric pressure conditions. Optical emission spectroscopy and two mass spectrometry techniques were used to monitor the early to late stages of plasma generation to track the evolution of atoms, molecules, clusters, nanoparticles, and agglomerates. The experiments were performed under atmospheric pressure air, atmospheric pressure nitrogen, and 20% and 5% O 2 (balance N 2 ), the latter specifically with in situ mass spectrometry. Electron microscopy was performed ex situ to identify crystal structure and elemental distributions in individual nanoparticles. We find that the presence of ≈20% O 2 leads to strong AlO emission, whereas in a flowing N 2 environment (with trace O 2 ), AlN and strong, unreacted Al emissions are present. In situ mass spectrometry reveals that as O 2 availability increases, Al oxide cluster size increases. Nanoparticle agglomerates formed in air are found to be larger than those formed under N 2 gas. High-resolution transmission electron microscopy demonstrates that Al 2 O 3 and AlN nanoparticle agglomerates are formed in both environments; indicating that the presence of trace O 2 can lead to Al 2 O 3 nanoparticle formation. The present results highlight that the availability of O 2 in the ambient gas significantly impacts spectral signatures, cluster size, and nanoparticle agglomeration behavior. These results are relevant to understanding debris formation in an explosion event, and interpreting data from forensic investigations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗