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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

High-Temperature Multi-Process Sensor Development and Demonstration at a Full-scale PC Combustion System

The main objective of this research program is to design, manufacture, and demonstrate a miniaturized, multi-process, monitoring system (mMPMS) for boiler condition management and easy system deployment to obtain a higher spatial resolution. This system will facilitate a Condition-Based Maintenance (CBM) philosophy that actively monitors the health of assets to predict and prevent failures and maximize availability and generating capacity at a reduced cost. CBM systems can provide boiler data that the advanced process control (APC) system can utilize for plant performance optimization, which is increasingly relevant as coal power plants shift from predominantly base-load operation to predominantly transient operation involving large load swings. The mMPMS is based on an electrochemical sensor that provides a real-time indication of the risk of damage to key locations in the radiant or convective section of a coal-fired boiler such as metal loss rates, heat flux, metal surface temperature, and deposit thickness. These indications can be utilized to optimize boiler performance as well as improve boiler availability in conjunction with corresponding operating conditions. This monitoring system was developed and tested in the high-temperature regions of coal-fired utility boilers in this project but can be applied to many other industries and applications as well. This project leveraged the existing electrochemical noise-based monitoring system and the new sensor design is small enough to be installed through the webbing of the waterwalls without the need for long shut-downs to bend tubes and to make it feasible to obtain high spatial resolution in the boiler. Data is transferred to the plant distributed control system (DCS) and any other control system. The sensor body that houses the sensor assembly was designed to ensure good conductive contact with boiler tubes to ensure the sensor is held at an identical temperature to the tube surface temperature. The data acquisition and signal conditioning modules were redesigned into a small footprint with optimized cooling of the module. System software was developed specifically for the new signal conditioning module and is compatible with plant PLCs. After the preliminary testing at a pilot-scale facility, the three mMPMS were installed at a full-scale pulverized coal-fired plant, PacifiCorp’s Hunter 3. The systems were demonstrated over 20,000 hours at the plant during regular operation. Also, the sensor data was fed to the plant’s advanced process control system to evaluate the corrosion control by the operation changes and utilized to understand the impacts of load cycling with different ramping up and down speeds. At the end of the project, the systems were converted to the permanent installation at the power plant to be used with the advanced process control system installed at the plant.

Advanced Sensors, Corrosion, Ash Deposition, Optim↗
NASA NTRS1994

Holographic interferometric tomography for reconstructing flow fields

Holographic interferometric tomography is a technique for instantaneously capturing and quantitatively reconstructing three-dimensional flow fields. It has a very useful application potential for high-speed aerodynamics. However, three major challenging tasks need to be accomplished before its practical applications. First, fluid flows are mostly unsteady or at least non repeatable. Consequently, a means for Instantaneously recording three-dimensional flow fields, that is, a simple holographic technique for simultaneously recording multi-directional projections, needs to be developed. Second, while holographic interferometry provides enormous data storage capabilities, expeditious data extraction from complicated interferograms is very important for timely near real-time applications. Third, unlike medical applications, flow tomography does not provide complete data sets but instead involves ill-posed reconstruction problems of incomplete projection and limited angular scanning. During this summer research period, new experimental techniques and corresponding hardware were developed and tested to address the above mentioned tasks. The first task was achieved by diffuser illumination. This concept allows instantaneous capture of many projections with a conventional setup for single-projection recording. For the second task, a phase-shifting technique was incorporated. This technique allows one to acquire multiple phase-stepped interferograms for a single projection and thus to extract phase information from intensity data almost at real-time. For the third task, the research that has been extensively conducted previously was utilized. In this research period, a complete experimental setup that provides the above three major capabilities was designed, built, and tested by integrating all the techniques. A simple laboratory experiment for simulating wind-tunnel testing was then conducted. A test flow was produced by employing a relatively simple device that generated a gravity-driven flow. The flow was then experimentally investigated to check the viability of the holographic interferometric tomographic technique before wind-tunnel application.

Cha, Soyoung S.↗
NASA NTRS1992

Spherical harmonic analysis of steady photospheric flows. II

The use of the spherical harmonic functions to analyze the nearly steady flows in the solar photosphere is extended to situations in which B(0) the latitude at disk center, is nonzero and spurious velocities are present. The procedures for extracting the rotation profile and meridional circulation are altered to account for the seasonal tilt of the sun's rotation axis toward and away from the observer. A more robust and accurate method for separating the limb shift and meridional circulation signals is described. The analysis procedures include the ability to mask out areas containing spurious velocities (velocity-like signals that do not represent true flow velocities in the photosphere). The procedures are shown to work well in extracting the various flow components from realistic artificial data with a broad, continuous spectrum for the supergranulation. The presence of this supergranulation signal introduces errors of a few m/s in the measurements of the rotation profile, meridional circulation, and limb shift from a single Doppler image.

Hathaway, David H.↗
NASA NTRS1992

Coded 16-CPFSK for downlink applications

A bandwidth-efficient constant-envelope Proof-of-Concept (POC) modem is described. The modem was developed on an Advanced Modulation Techniques Development contract for the NASA/Lewis Research Center. The POC modem employs 16-ary Continuous Phase Frequency Shift Keying (16-CPFSK) modulation. The 16 frequencies are spaced every 1/16th baud rate which produces a compact spectrum allowing 2 bits/sec/Hz operation. The modem is designed for 200 mb/s Time Division Multiple Access (TDMA) application with 100 MHz adjacent channel spacing. Overall rate 3.4 convolutional coding is incorporated. The demodulator differs significantly from typical quadrature phase detector approaches in that phase is coherently measured by processing the baseband output of a frequency discriminator. Baud rate phase samples for the baseband processor are subsequently decoded to yield the original data stream. The method of encoding onto the 16-ary symbol-ending phase nodes, together with convolutional coding gain, results in near Quadrature Phase Shift Keying (QPSK) theoretical performance. The modulated signal is of constant envelope; thus the power amplifier can be saturated for peak performance. The spectrum is inherently bandlimited and requires no RF filter for sidelobe containment. Two novel theoretical techniques are used in this 16-CPFSK modem: (1) coherent phase measurements are obtained by processing an FM discriminator baseband output; and (2) modulation is accomplished via a closed-loop-linearized voltage controlled oscillator (VCO).

Davis, Robert↗
NASA NTRS1990

Early results from the Cosmic Background Explorer (COBE)

The Cosmic Background Explorer, launched 18 Nov. 1989, has nearly completed its first full mapping of the sky with all three of its instruments: A Far Infrared Absolute Spectrometer (FIRAS) covering 0.1 to 10 mm, a set of Differential Microwave Radiometers (DMR) operating at 3.3, 5.7, and 9.6 mm, and a diffuse Infrared Background Experiment (DIRBE) spanning 1 to 300 microns in ten bands. A preliminary map of the sky derived from DIRBE data is presented. Initial cosmological implications include: a limit on the comptonization parameter of 0.001, on the chemical potential parameter of 0.01, a strong limit on the existence of a hot smooth intergalactic medium, and a confirmation that the dipole anisotropy has the spectrum expected from a Doppler shift of a blackbody. There are no significant anisotropies in the microwave sky detected, other than from our own galaxy and a cos theta dipole anisotropy whose amplitude and direction agree with previous data. At shorter wavelengths, the sky spectrum and anisotropies are dominated by emission from local sources of emission within our Galaxy and Solar System. Preliminary comparison of IRAS (Infrared Astronomical Satellite) and DRIBE sky brightnesses toward the ecliptic poles shows the IRAS values to be significantly higher than found by DRIBE at 100 microns. The presence of gain and zero point errors in the IRAS total brightness data is suggested. The spacecraft, instrument designs, and data reduction methods are described.

Mather, J. C.↗
DOE OSTI2021

Digital Platform Informed Certification of Components Derived from Advanced Manufacturing Technologies

The Transformational Challenge Reactor is being designed at Oak Ridge National Laboratory to demonstrate the feasibility of constructing a reactor core using advanced manufacturing technology. This technology includes additive manufacturing combined with machine learning, materials science, and data science technologies in an effort to facilitate the expansion of additive manufacturing into advanced nuclear energy systems and other applications requiring a high level of quality assurance. The Transformational Challenge Reactor is employing additive manufacturing and artificial intelligence to deliver a new approach. Beginning in FY21, the focus of the program has shifted away from demonstrating a reactor, and instead, towards delivering on four key thrust areas: (1) artificial intelligence-informed design, (2) advanced materials, (3) integrated sensing and control, and (4) the digital platform. Of these four thrust areas, the most pertinent to this report is the digital platform. The digital platform has the potential to be a key enabler for a paradigm shift in how components, those derived from advanced manufacturing technologies, are certified for use in nuclear applications. This is achieved primarily using machine learning to discover correlations from the abundance of data produced through additive manufacturing and those physical properties critical to the performance of the component.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

A Community Energy Operations and Planning System: Concept, Use cases, Metrics, and Benefits

Community and city leaders are interested in achieving sustainability goals, providing resilient energy infrastructure, and improving economic competitiveness. Community-level data acquisition and analysis can provide energy and associated benefits that are not possible at the single building level. However, there is a lack of organizational structure, common semantic data models, interoperable systems, and methods to support data-driven decision-making for community-scale energy supply and demand systems. We explored the need and opportunity for a Community Energy Operations and Planning System (Community EOPS), a potential data exchange platform. We conducted “customer discovery” interviews, and reviewed literature, public tools, and technology platforms to identify key energy data “users” and use cases in communities. The key users of the Community EOPS could be developers of mixed-use districts, corporate, defense and university campus energy managers, and city managers of cities that own their energy utility. The value could be for community planning and reporting (for energy data-integrated land use planning and community infrastructure investments in microgrids, storage, district heating and cooling), energy efficiency (leveraging optimizations for community scale energy supply and demand), flexible load management (grid-edge load management to offset, shift, and flatten loads for multiple buildings and EV fleets), cost savings and revenue generation (participating in grid services), and social benefits such as energy resilience, equity, and awareness. We developed a conceptual Community EOPS architecture with recommendations for streamlined and prioritized data acquisition, sharing, and integration driven by prioritized use cases, common metrics, and actionable visualizations that can provide value to a community’s users.

Singh, Reshma↗
DOE OSTI2026

Detector alignment for X-ray crystallography using Millepede-II

I describe a method for accurately refining the geometrical parameters of segmented X-ray area detectors on the basis of serial crystallography data, using 'Millepede' – an algorithm created for a very similar problem in high-energy physics. The Millepede method for serial crystallography builds on the approach of Brewster et al. [Acta Cryst. (2018), D74, 877–894], in which the detector parameters are refined simultaneously with the parameters for each individual crystal. This accounts for the mutual dependency between the parameters and thereby avoids the bias and slow convergence problems that have afflicted older approaches in which the deviations between observed and calculated Bragg peak positions were taken directly as the updates for the detector panel positions. The Millepede method uses the special structure of the least-squares normal equations to reduce them to a much smaller form that can be solved very quickly, even compared with the sparse matrix methods used previously. This makes it practical to refine the detector geometry frequently and thereby maintain accurate calibration without specialized alignment campaigns. Tilts of detector panels out of the plane can be reliably refined, as can the overall distance of the detector in the beam direction. With a simulated test case, the new method produced panel shifts within 7% of the correct values with only one iteration, and produced almost exactly correct shifts after a second iteration. A simulated out-of-plane panel rotation was correctly determined to within 0.001°. Applied to experimental data from an X-ray free-electron laser, the method increased the indexable fraction of frames from 30% to 91% in a single iteration, and to 96% after two further iterations. Computing the geometry updates on the basis of 2060 crystals took only 0.819 s on desktop computing hardware, including the time taken to read the required data from disk. The scaling was found to be very close to linear for up to 100 980 sets of crystal parameters, which took only 78.2 s to process under the same conditions. The method has been applied as part of a real-time feedback system at a synchrotron radiation beamline, in which an out-of-plane detector tilt of 0.04° was detected and corrected. Possible further applications are also described here.

Millepede-II↗
NASA NTRS1984

Role of cardiac volume receptors in the control of ADH release during acute simulated weightlessness in man

Hemodynamic responses and antidiuretic hormone (ADH) were measured during body position changes, designed to induce central blood volume shifts in ten cardiac and one heart-lung transplant recipients, to assess the contribution of cardiac volume receptors in the control of ADH release during the initial acute phase of exposure to weightlessness. Each subject underwent 15 min of a sitting-control period (C) followed by 30 min of 6 deg headdown tilt (T) and 30 min of resumed sitting (S). Venous blood samples and cardiac dimensions were taken at 0 and 15 min of C; 5, 15, and 30 min of T; and 5, 15, and 30 min of S. Blood samples were analyzed for hematocrit, plasma osmolality, plasma renin activity (PRA), and ADH. Heart rate and blood pressure were recorded every two min. Plasma osmolality was not altered by posture changes. Mean left ventricular end-diastolic volume increased (P less than 0.05) from 90 ml in C to 106 ml in T and returned to 87 ml in S. Plasma ADH was reduced by 20 percent (P less than 0.05) with T, and returned to control levels with S. These responses were similar in six normal cardiac-innervated control subjects. These data may suggest that cardiac volume receptors are not the primary mechanism for the control of ADH release during acute central volume shifts in man.

Convertino, V. A.↗
NASA NTRS2010

Relating Convective and Stratiform Rain to Latent Heating

The relationship among surface rainfall, its intensity, and its associated stratiform amount is established by examining observed precipitation data from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR). The results show that for moderate-high stratiform fractions, rain probabilities are strongly skewed toward light rain intensities. For convective-type rain, the peak probability of occurrence shifts to higher intensities but is still significantly skewed toward weaker rain rates. The main differences between the distributions for oceanic and continental rain are for heavily convective rain. The peak occurrence, as well as the tail of the distribution containing the extreme events, is shifted to higher intensities for continental rain. For rainy areas sampled at 0.58 horizontal resolution, the occurrence of conditional rain rates over 100 mm/day is significantly higher over land. Distributions of rain intensity versus stratiform fraction for simulated precipitation data obtained from cloud-resolving model (CRM) simulations are quite similar to those from the satellite, providing a basis for mapping simulated cloud quantities to the satellite observations. An improved convective-stratiform heating (CSH) algorithm is developed based on two sources of information: gridded rainfall quantities (i.e., the conditional intensity and the stratiform fraction) observed from the TRMM PR and synthetic cloud process data (i.e., latent heating, eddy heat flux convergence, and radiative heating/cooling) obtained from CRM simulations of convective cloud systems. The new CSH algorithm-derived heating has a noticeably different heating structure over both ocean and land regions compared to the previous CSH algorithm. Major differences between the new and old algorithms include a significant increase in the amount of low- and midlevel heating, a downward emphasis in the level of maximum cloud heating by about 1 km, and a larger variance between land and ocean in the new CSH algorithm.

Tao, Wei-Kuo↗
NASA NTRS2000

Trajectory Orientation: A Technology-Enabled Concept Requiring a Shift in Controller Roles and Responsibilities

The development of a decision support tool (DST) for the en-route domain with accurate conflict prediction time horizons of 20 minutes has introduced an interesting problem. A 20 minute time horizon for conflict prediction often results in the predicted conflict occurring one or more sectors downstream from the sector controller who "owns" (i-e., is responsible for the safe separation of aircraft) one or both of the aircraft in the conflict pair. Based on current roles and responsibilities of today's en route controllers, the upstream controller would not resolve this conflict. In most cases, the downstream controller would wait until the conflicting aircraft entered higher sector before resolving the conflict. This results in a delay of several minutes from the time when the conflict was initially predicted. This delay is inefficient from both a controller workload and user's cost of operations perspective. Trajectory orientation, a new concept for facilitating an efficient, conflict-free flight path across several sectors while conforming to metering or miles-in-trail spacing, is proposed as an alternative to today's sector-oriented method. This concept necessitates a fundamental shift in thinking about inter-sector coordination. Instead of operating independently, with the main focus on protecting their internal airspace, controllers would work cooperatively, depending on each other for well-planned, conflict-free flow of aircraft. To support the trajectory orientation concept, a long time horizon (15 to 20 minutes) for conflict prediction and resolution would most likely be a primary requirement. In addition, new tools, such as controller-pilot data link will be identified to determine their necessity and applicability for trajectory orientation. Finally, with significant controller participation from selected Air Route Traffic Control Centers, potential shifts in R-side/D-side roles and responsibilities as well as the creation of a new controller position for multi-sector planning will be examined to determine the most viable solutions.

Leiden, Ken↗
DOE OSTI2025

Applying a Multisector Scenario Framework to Evaluate Past and Future Public Surface Water Supply Infrastructure Strategies in Texas

Datasets supporting the index model and scenario analysis used in evaluating surface water supply strategies across different water system types in Texas. These data underpin the scenario development and application of five key indicators: Water Availability Index (WAI), Water Quality Index (WQI), Energy Requirement Index (ERI), Water Treatment Cost (WTC), and Water Infrastructure Cost (WIC). The datasets are organized by system type—stream reaches (flowlines), waterbodies, and reservoirs—and include both raw and standardized index values. The integrated datasets also provide scenario classifications (original and adjusted) based on infrastructure and planning priorities, enabling comparison across Shared Socioeconomic Pathways (SSPs). Additional strategy-level data are included to support evaluation of state-level new reservoir projects in relation to cost and availability tradeoffs. Please refer to the README file provided in Files for more details. Descriptions of the datasets are provided below. Dataset(s) Descriptions Folder: Index_model_database.zip Subfolder: Stream_reach.zip Fl_wf.csv, Fl_wq.csv, Fl_er.csv, Fl_wf_wtcUV.csv, Fl_wf_wtcnoUV.csv, Fl_allfac_wic1.csv, Fl_allfac_wic2.csvDatasets for computing WAI, WQI, ERI, WTC, and WIC for surface water systems classified as stream reaches (flowlines). Subfolder: Waterbody.zip Wb_wf.csv, Wb_wq.csv, Wb_er.csv, Wb_wf_wtcUV.csv, Wb_wf_wtcnoUV.csv, Wb_allfac_wic1.csv, Wb_allfac_wic2.csvEquivalent index model datasets for waterbodies, reflecting hydrologic and infrastructure attributes specific to impounded natural systems. Subfolder: Reservoir.zip Rs_wf.csv, Rs_wq.csv, Rs_er.csv, Rs_wf_wtcUV.csv, Rs_wf_wtcnoUV.csv, Rs_allfac_wic1.csv, Rs_allfac_wic2.csvIndex model datasets specific to regulated reservoir systems, incorporating both resource indicators and cost parameters. Folder: Integrated data.zip combined_merged_data.csv, combined_merged_data_scenario.csvDatasets integrating index model indicators (both raw and scaled) with scenario classifications, including adjustments reflecting SSP-aligned transitions and planning shifts. Folder: Additional data.zip wai_supplystrat_wic_merged.csvCurated dataset capturing proposed major reservoir-based municipal water supply strategies in Texas. Integrates site-level planning data with estimated capital infrastructure costs and water availability scores for comparative assessment.

geospatial↗
DOE OSTI2025

High-count-rate effects in event processing for the XRISM/Resolve X-ray microcalorimeter. II. Energy scale and resolution in orbit

The Resolve instrument on the X-ray Imaging and Spectroscopy Mission (XRISM) uses a 36 pixel microcalorimeter designed to deliver high-resolution, non-dispersive X-ray spectroscopy. Although it is optimized for extended sources with low count rates, Resolve observations of bright point sources are still able to provide unique insights into the physics of these objects, as long as high-count-rate effects are addressed in the analysis. These effects include the loss of exposure time for each pixel, changes in the energy scale, and changes in the energy resolution. To investigate these effects under realistic observational conditions, we observed the bright X-ray source, the Crab Nebula, with XRISM at several offset positions with respect to the Resolve field of view and with continuous illumination from 55 Fe sources on the filter wheel. For the spectral analysis, we excluded data where exposure-time loss was too significant to ensure reliable spectral statistics. The energy scale at 6 keV shows a slight negative shift in the high-count-rate regime. The energy resolution at 6 keV worsens as the count rate in electrically neighboring pixels increases, but can be restored by applying a nearest-neighbor coincidence cut (“cross-talk cut”). We examined how these effects influence the observation of bright point sources, using GX 13+1 as a test case, and identified an eV-scale energy offset at 6 keV between the inner (brighter) and outer (fainter) pixels. Users who seek to analyze velocity structures on the order of tens of km s–1 should account for such high-count-rate effects. These findings will aid in the interpretation of Resolve data from bright sources and provide valuable considerations for designing and planning for future microcalorimeter missions.

X-rays: general↗
NASA NTRS1996

Development of an automated control center for the EUVE mission

The Automated Project Operations Control Center (APOCC) was developed to enable automated data acquisition, ground system management and spacecraft health and safety monitoring. The control center will be used for the Extreme Ultraviolet Explorer (EUVE) project to reduce operations staffing from three to one shift per day, while maintaining the science return and performing routine health and safety monitoring activities. The staff reduction is expected to yield a cost reduction of 250,000 dollars per year in comparison with a fully staffed, 24 hour/day operation. The APOCC infrastructure was designed to be reusable and extensible. Configurable data items are stored in data bases and spacecraft-specific information is stored in a health and safety monitoring knowledge base.

Penafiel, Catherine↗
NASA NTRS1984

An analysis of the annual cycle in upper stratospheric ozone

The mid-latitude upper stratospheric ozone profiles obtained by the solar backscatter ultraviolet instrument on the Nimbus 7 satellite show a clear annual cycle both in the absolute ozone amounts between 0.98 and 15.6 mbar and in the magnitude of disturbances that reveal themselves as longitudinal structure. At the lowest pressure analyzed a winter maximum in ozone exists, but as one progresses downward in altitude a shift in the temporal phase of the annual cycle occurs in the vicinity of 3 to 4 mbar. Comparison of the observed behavior with the predictions of a one-dimensional photochemical model shows a systematic tendency for calculated ozone amount to be 20-27 percent below the data for pressures less than 7.8 mbar. The chemical model successfully predicts the change in phase of the annual cycle, although at a pressure greater than observed. Diagnosis of model results shows the observed shift to be closely coupled to the magnitude of the ozone column density near 3-4 mbar. The wavelength-dependent attenuation of the solar radiation field by ozone alters the relative magnitude of the molecular oxygen and ozone dissociation rates, leading to a change in the temporal phase of the annual cycle.

Frederick, J. E.↗
DOE OSTI2025

Robust Spectral Anomaly Detection in EELS Spectral Images via 3D Convolutional Variational Autoencoders

Abstract A 3D Convolutional Variational Autoencoder (3D‐CVAE) is introduced for automated anomaly detection in electron energy‐loss spectroscopy spectrum imaging (EELS‐SI) data. This approach leverages the full 3D structure of EELS‐SI data to detect subtle spectral anomalies while preserving both spatial and spectral correlations across the datacube. By employing cross‐entropy loss and training on bulk spectra, the model learns to reconstruct bulk features characteristic of the defect‐free material. In exploring methods for anomaly detection, both the 3D‐CVAE approach and principal component analysis (PCA) are evaluated, testing their performance using FeL‐edge ΔEpeak shifts designed to simulate material defects. These results show that 3D‐CVAE achieves superior anomaly detection and maintains consistent performance across various shift magnitudes. The method demonstrates clear bimodal separation between bulk and anomalous spectra, enabling reliable classification. Further analysis verifies that lower‐dimensional representations are robust to anomalies in the data. While performance advantages over PCA diminish with decreasing anomaly concentration, our method maintains high reconstruction quality even in challenging, noise‐dominated spectral regions. This approach provides a robust framework for unsupervised automated detection of spectral anomalies in EELS‐SI data, particularly valuable for analyzing complex material systems.

Chemistry↗
DOE OSTI2022

An experimental and modeling study of the application of membrane contactor reactors to methanol synthesis using pure CO 2 feeds

We describe here a post-combustion CO 2 capture and utilization (CCU) technology that converts the CO 2 into methanol (MeOH), a valuable chemical, thus providing a way to monetize the carbon captured to offset process costs. Methanol synthesis (MeS) has been discussed recently for application to CCU, but thermodynamic limitations make it difficult to convert in a single pass a large CO 2 fraction. Conventional catalysts show slow kinetics in converting CO 2 -rich syngas (or pure CO 2 ) into MeOH. Our Group developed a novel MeS process, employing a membrane contactor reactor (MCR) system that attains carbon conversions significantly higher than equilibrium. Our focus here is to process pure CO 2 streams by combining the MCR with a separate reactor, which converts the CO 2 into a syngas via the reverse water gas shift (RWGS) reaction. In this preliminary effort, the RWGS reactor (RWGSR) is assumed to reach equilibrium. Additional MeS kinetic rate data are generated validating experimentally the ability of the MeS-MCR to process as a feed the RWGSR exit stream. The performance of the combined (RWGSR/MeS-MCR) system is then simulated using a recently developed MeS-MCR model. In conclusion, the findings are encouraging, and research is currently ongoing to experimentally validate the RWGSR/MeS-MCR system performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

DeFault: DEep‐Learning‐Based FAULT Delineation Using the IBDP Passive Seismic Data at the Decatur CO2 Storage Site

Abstract The carbon capture, utilization, and storage (CCUS) framework is an essential component in reducing greenhouse gas emissions, with its success hinging on the comprehensive knowledge of subsurface geology and geomechanics. Passive seismic event relocation and fault detection offer vital insights into subsurface structures and the ability to monitor fluid migration pathways. Accurate identification and localization of seismic events, however, face significant challenges, including the necessity for high‐quality seismic data and advanced computational methods. To address these challenges, we introduce a novel deep learning method, , specifically designed for passive seismic source relocation and fault delineating for passive seismic monitoring projects. By leveraging data domain‐adaptation, allows us to train a neural network with labeled synthetic data and apply it directly to field data. Using , the passive seismic sources are automatically clustered based on their recording time and spatial locations, and subsequently, faults and fractures are delineated accordingly. We demonstrate the efficacy of on a field case study involving injection related microseismic data from Decatur, Illinois area. Our approach accurately and efficiently relocated passive seismic events, identified faults and could aid in potential damage induced by seismicity. Our results highlight the potential of as a valuable tool for passive seismic monitoring, emphasizing its role in ensuring CCUS project safety. This research bolsters the understanding of subsurface characterization in CCUS, illustrating machine learning’s capacity to refine these methods. Ultimately, our work has significant implications for CCUS technology deployment, an essential strategy in combating climate change. Plain Language Summary In our quest to tackle climate change, we use a strategy known as carbon capture, utilization, and storage (CCUS) to keep greenhouse gases out of the atmosphere. This strategy relies heavily on our ability to understand what's happening deep under the earth's surface. To make sure we store super critical safely, we need to accurately map out the geological structure, especially faults, but this is tough without high‐quality data and complex computer programs. We've developed a new tool called “DeFault,” which uses advanced machine learning to improve how we find and map these underground features. “DeFault” is smart enough to learn from numerically simulated data and then apply what it’s learned to real‐world situations. It groups together seismic activity—tiny tremors and shifts in the earth—based on when and where they happen, which helps us spot where there might be cracks or faults. We tested “DeFault” in Illinois, where CO 2 is injected underground, and it successfully pinpointed where these tremors occurred and mapped out the faults, helping to prevent accidents accurately in the future. Our study shows that “DeFault” will be a powerful ally in making CCUS safer and more effective, especially for the Illinois Basin Decatur Project. Key Points Faults and fractures introduced by carbon storage can be monitored by passive seismicity DeFault algorithm enables an automatic process for accurate and efficient passive seismic event locating and clustering

58 GEOSCIENCES↗