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

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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Prominences: The Key to Understanding Solar Activity

Prominences are spectacular manifestations of both quiescent and eruptive solar activity. The largest examples can be seen with the naked eye during eclipses, making prominences among the first solar features to be described and catalogued. Steady improvements in temporal and spatial resolution from both ground- and space-based instruments have led us to recognize how complex and dynamic these majestic structures really are. Their distinguishing characteristics - cool knots and threads suspended in the hot corona, alignment along inversion lines in the photospheric magnetic field within highly sheared filament channels, and a tendency to disappear through eruption - offer vital clues as to their origin and dynamic evolution. Interpreting these clues has proven to be contentious, however, leading to fundamentally different models that address the basic questions: What is the magnetic structure supporting prominences, and how does so much cool, dense plasma appear in the corona? Despite centuries of increasingly detailed observations, the magnetic and plasma structures in prominences are poorly known. Routine measurements of the vector magnetic field in and around prominences have become possible only recently, while long-term monitoring of the underlying filament-channel formation process also remains scarce. The process responsible for prominence mass is equally difficult to establish, although we have long known that the chromosphere is the only plausible source. As I will discuss, however, the motions and locations of prominence material can be used to trace the coronal field, thus defining the magnetic origins of solar eruptions. A combination of observations, theory, and numerical modeling must be used to determine whether any of the competing theories accurately represents the physics of prominences. I will discuss the criteria for a successful prominence model, compare the leading models, and present in detail one promising, comprehensive scenario for prominence formation and evolution that could answer the two questions posed above.

Karpen, Judy T.↗
DOE OSTI2023

Assessing parallel path cooling tower performance via artificial neural networks

Real-time monitoring of a research nuclear reactor, a system in which all generated power is dissipated to the environment, can be performed via analysis of the heat rejection from the cooling system. Given an inlet water temperature and flow rate, the reactor power can be well-approximated from the outlet water temperature; however, the instrumentation to measure outlet conditions may not be robust or accurate. If we know how a cooling tower performs from historical data, but cannot measure the outlet temperature, a mathematical representation of the system can be inverted to obtain the outlet water temperature that describes the cooling capacity. Unfortunately, model inversion processes are computationally expensive. To address this, an artificial neural network (ANN) is implemented to assess the performance of a multi-cell cooling tower for a nuclear reactor. This approach leverages the Merkel model to obtain an extensive data set describing performance of the cooling tower cells throughout a wide array of potential operating conditions. The Merkel model is expressed as a function of four parameters: the inlet and outlet water temperatures, inlet air wet bulb temperature, and ratio of liquid-to-gas mass flow rates (L/G), which together provide a non-dimensional number indicative of cooling tower performance, called the Merkel integral. Computing a 4-dimensional data structure that describes finite combinations of the Merkel integral, an inverse model is then generated using an ANN to determine the cell outlet water temperature from the other three model parameters along with the computed Merkel integral. Compared to traditional model inversion methods, the ANN reduces the computational time by approximately 4 orders of magnitude, with effectively no sacrifice to solution accuracy, and could be applied for different cooling towers in the event the performance curve is known. Finally, three use cases of the ANN are then reviewed: (1) determining the cell outlet water temperatures when gas flow at rated conditions (GFRC) is known, (2) performing the prior case without knowledge of the GRFC, and (3) assessing performance differences between the individual tower cells.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

Relationships between evaprorative fraction and remotely sensed vegetation index and microwave brightness temperature for semiarid rangelands

Measurements of the microwave brightness temperature (TB) with the Pushbroom Microwave Radiometer (PBMR) over the Walnut Gulch Experiment Watershed were made on selected days during the MONSOON 90 field campaign. The PBMR is an L-band instrument (21-cm wavelength) that can provide estimates of near-surface soil moisture over a variety of surfaces. Aircraft observations in the visible and near-infrared wavelengths collected on selected days also were used to compute a vegetation index. Continuous micrometeorological measurements and daily soil moisture samples were obtained at eight locations during experimental period. Two sites were instrumented with time domain reflectometry probes to monitor the soil moisture profile. The fraction of available energy used for evapotranspiration was computed by taking the ratio of latent heat flux (LE) to the sum of net radiation (Rn) and soil heat flux (G). This ratio is commonly called the evaporative fraction (EF) and normally varies between 0 and 1 under daytime convective conditions with minimal advection. A wide range of environmental conditions existed during the field campaign, resulting in average EF values for the study area varying from 0.4 to 0.8 and values of TB ranging from 220 to 280 K. Comparison between measured TB and EF for the eight locations showed an inverse relationship. Other days were included in the analysis by estimating TB with the soil moisture data. Because transpiration from the vegetation is more strongly coupled to root zone soil moisture, significant scatter in this relationship existed at high values of TB or dry near-surface soil moisture conditions. The variation in EF under dry near-surface soil moisture conditions was correlated to the amount of vegetation cover estimated with a remotely sensed vegetation index. These findings indicate that information obtained from optical and microwave data can be used for quantifying the energy balance of semiarid areas. The microwave data can indicate when soil evaporation is significantly contributing to EF, while the optical data is helpful for quantifying the spatial variation in EF due to the distribution of vegetation cover.

Kustas, W. P.↗
NASA NTRS2004

Volcanic CO2 Abundance of Kilauea Plume Retrieved by Meand of AVIRIS Data

Absorbing the electromagnetic radiation in several regions of the solar spectrum, CO2 plays an important role in the Earth radiation budget since it produces the greenhouse effect. Many natural processes in the Earth s system add and remove carbon dioxide. Overall, measurements of atmospheric carbon dioxide at different sites around the world show an increased carbon dioxide concentration in the atmosphere. At Mauna Loa Observatory (Hawaii) the measured carbon dioxide increased from 315 to 365 ppm, in the period 1958 2000 [Keeling et al., 2001]. While at the large scale, the relationship between CO2 increase and global warming is established [IPCC, 1996], at the local scale, many studies are still needed to understand regional and local sources of carbon dioxide, such as volcanoes. The volcanic areas are particularly rich in carbon dioxide; this is due to magma degassing in the summit craters region of active volcanoes, and to the presence of fractures and active faults [Giammanco et al., 1998]. Several studies estimate a global flux of volcanic CO2 (34+/-24)10(exp 6) tons/day from effusive volcanic emissions, such as the tropospheric volcanic plume (Table 1) [McClelland et al., 1989]. Plumes are a turbulent mixture of gases, solid particles and liquid droplets, emitted continuously at high temperature from summit craters, fumarolic fields or during eruptive episodes. Inside the plume, water vapour represents 70 90% of the volcanic gases. The main gaseous components are CO2, SO2, HCl, H2, H2S, HF, CO, N2 and CH4. Other plume components are volcanic ash, aqueous and acid droplets and solid sulphur-derived particles [Sparks et al., 1997]. Volcanic gases and aerosols are evidences of volcanic activity [Spinetti et al., 2003] and they have important climatic and environmental effects [Fiocco et al., 1994]. For example, Etna volcano is one of the world s major volcanic gas sources [Allard et al., 1991]. New studies on volcanic gaseous emissions have pointed out that a variation of the gas ratio CO2/SO2 is related to eruptive episodes [Caltabiano et al., 1994]. However, measurements and monitoring of volcanic carbon dioxide are difficult and often hazardous, due to the high background presence of atmospheric CO2 and the inaccessibility of volcanic sites. Hyperspectral remote sensing is a suitable technique to overcome the difficulties of ground measurement. It permits a rapid, comprehensive view of volcanic plumes and their evolution over time, detection of all gases with absorption molecular lines within the sensor s multispectral range and, in general, measurement of all the volatile components evolving from craters. The molecular and particle plume components scatter and absorb incident solar radiation. The integral of the radiation difference composes the signal measured by the remote spectrometer. The inversion technique consists of retrieving the plume component concentrations, hence decomposing the signal into the different contributions. The accuracy of remote sensing techniques depends primarily on the sensor capability and sensitivity.

Spinetti, C.↗
DOE OSTI2025

Evaluating the feasibility of using downwind methods to quantify point source oil and gas emissions using continuously monitoring fence-line sensors

The dependable reporting of methane (CH 4 ) emissions from point sources, such as fugitive leaks from oil and gas infrastructure, is important for profit maximization (retaining more hydrocarbons), evaluating climate impacts, assessing CH 4 fees for regulatory programs, and validating CH 4 intensity in differentiated gas programs. Currently, there are disagreements between emissions reported by different quantification techniques for the same sources. It has been suggested that downwind CH 4 quantification methods using CH 4 measurements on the fence line of production facilities could be used to generate emission estimates from oil and gas operations at the site level, but it is currently unclear how accurate the quantified emissions are. To investigate the accuracy of downwind methods, this study uses fence-line simulated data collected during controlled-release experiments as input for a non-standard closed-path eddy covariance (EC), the Gaussian plume inverse model (GPIM), and the backward Lagrangian stochastic (bLs) model in a range of atmospheric conditions. This study's EC attempt was unsuccessful due to data collection and instrumentation issues, resulting in invalid results characterized by underestimated emissions, large negative fluxes, and cospectra/ogives that deviated from their ideal shapes. Consequently, the EC results could not be compared with the GPIM and bLS model. The bLs model demonstrated the highest accuracy for single-release single-point emissions, though it exhibited greater uncertainty than GPIM under multi-release conditions. Across the GPIM and bLs model, the most reliable quantification was achieved with 15 min averaging and a narrow 5° wind sector range. Although EC was limited in this context, future studies should consider employing a standard EC system and further optimizing GPIM and bLs approaches – particularly for complex multi-source scenarios – to enhance quantification accuracy and reduce uncertainty.

03 NATURAL GAS↗
DOE OSTI2023

Microseismic Monitoring of Laboratory Hydraulic Fracturing Experiments in Granitic Rocks for Different Fracture Propagation Regimes

While hydraulic fracturing (HF) is a widely employed process, the underlying fracturing processes are still heavily contested. The attributes of the HF generated fracture network can exhibit substantial variation when dealing with specific HF propagation regimes encountered in the field. In this study, HF experiments were performed on true-triaxially loaded Barre granite cubes, with microseismic monitoring, to identify and characterize the fracturing mechanisms associated with different viscosity injection fluids. Utilizing fluids with high (oil/1450 cP) and low (water/1 cP) viscosity represented two key HF propagation regimes: viscosity- and toughness-dominated. The experiments conducted with oil involved higher breakdown pressures, larger fluid volumes, and slower fracture propagation speeds. Furthermore, the frequency–magnitude distribution (b value) for all experiments (1.9–2.3) was similar to those encountered for large-scale operations. Slightly larger b values were encountered during the initiation phase (2.4–2.7) relative to the fracture propagation and post-fracturing phases (1.9–2.2). Techniques such as polarity and moment-tensor inversion were utilized to characterize the source mechanisms. For the HF experiments with oil, tensile fractures were most dominant (92%) in the initiation phase compared to fracture propagation and post-fracturing phases (70–75%). Similar tensile fracturing dominancy was not observed with water, attributable to fluid permeation and leak-off. Regardless of the injection fluid or classification criteria employed, tensile fractures were the dominant type consistently, with fewer occurring in water experiments but the specific ratio of crack types varied with different source mechanism criteria employed.

58 GEOSCIENCES↗
NASA NTRS2001

RXTE, VLBA, Optical, and Radio Monitoring of the Quasars 3C 279, PKS 1510--089, and 3C 273

We are continuing our combined RXTE X-ray, VLBA imaging (at 43 GHz), optical (several observatories), and radio (University of Michigan Radio Astronomy Observatory) monitoring of the quasars 3C 279 and PKS 1510-089, and have started similar monitoring of 3C 273. X-ray flares in 3C 279 and PKS 1510-089 are associated with ejections of superluminal components. In addition, there is a close connection between the optical and X-ray variability of 3C 279. There is a strong correlation between the 14.5 GHz and X-ray variability of PKS 1510-089 in 1997 and 1998 (with the radio leading the X-ray) that becomes weaker in subsequent years. X-ray fluctuations occur on a variety of timescales in 3C 273, with a major prolonged outburst in mid-2001. The lead author will discuss the correlations in terms of inverse Compton models for the X-ray emission coupled with synchrotron models for the lower-frequency radiation. Synchrotron self-Compton models can explain the "reverse" time lag in PKS 1510-089 is well as the variable correlation between the X-ray variations and those at lower frequencies in this object and in 3C 279.

Marscher, A. P.↗
DOE OSTI2020

Novel Perovskite Semiconductors for the Detection of Special Nuclear Material

Special nuclear material detection using portable, highly efficient detectors is of paramount importance to national security and environmental monitoring. Current neutron detectors, including gas proportional counters and scintillators, are not suitable for discrete or portable monitoring due to size, weight, and power limitations. For example, 3 He gas proportional detectors have significant drawbacks, including long absorption lengths, high voltage requirements, and dependence on the availability of 3 He. The goal of this project is to synthesize a novel, boron-based perovskite semiconductor crystals to create a more efficient and more portable neutron detector. This innovative material will lead to a significant decrease in power and size requirements with higher operating temperatures than other traditional solid-state detectors. Directly incorporating 10 B eliminates the need for a conversion layer and leads to high neutron absorption coefficients. In this seedling project, we used inverse temperature crystallization with boron precursors to create CH 3 NH 3 PbI 3-x (BF 4 ) x . The crystals were analyzed with X-ray diffraction, but the results were inconclusive. Future work will focus on tailoring the solution growth and selecting appropriate solvents and precursors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2013

Advanced Optical Diagnostics for Ice Crystal Cloud Measurements in the NASA Glenn Propulsion Systems Laboratory

A light extinction tomography technique has been developed to monitor ice water clouds upstream of a direct connected engine in the Propulsion Systems Laboratory (PSL) at NASA Glenn Research Center (GRC). The system consists of 60 laser diodes with sheet generating optics and 120 detectors mounted around a 36-inch diameter ring. The sources are pulsed sequentially while the detectors acquire line-of-sight extinction data for each laser pulse. Using computed tomography algorithms, the extinction data are analyzed to produce a plot of the relative water content in the measurement plane. To target the low-spatial-frequency nature of ice water clouds, unique tomography algorithms were developed using filtered back-projection methods and direct inversion methods that use Gaussian basis functions. With the availability of a priori knowledge of the mean droplet size and the total water content at some point in the measurement plane, the tomography system can provide near real-time in-situ quantitative full-field total water content data at a measurement plane approximately 5 feet upstream of the engine inlet. Results from ice crystal clouds in the PSL are presented. In addition to the optical tomography technique, laser sheet imaging has also been applied in the PSL to provide planar ice cloud uniformity and relative water content data during facility calibration before the tomography system was available and also as validation data for the tomography system. A comparison between the laser sheet system and light extinction tomography resulting data are also presented. Very good agreement of imaged intensity and water content is demonstrated for both techniques. Also, comparative studies between the two techniques show excellent agreement in calculation of bulk total water content averaged over the center of the pipe.

Bencic, Timothy J.↗
DOE OSTI2024

Dynamic changes in evapotranspiration, canopy photosynthesis and expansive growth in open field under rapid fluctuating radiation

Abstract In open fields, plants experience dynamic changes in environment, particularly radiation, temperature, wind, and humidity but their short-term responses have not been adequately characterized under natural conditions. In this study, we assessed causal effects of rapid radiation fluctuation on seven plant parameters in open fields of cotton and sweet corn canopies. The parameters are evapotranspiration ( ET ), canopy photosynthesis indicated by CO2 flux from air to canopy ( FCO2 ), sensible heat energy flux ( H ), canopy conductance for water vapor ( gcw ), canopy surface temperature ( Ts ), shoot and leaf elongation rate, and stem diameter change. The energy and CO2 fluxes were measured with Bowen ratio/energy balance/CO2 gradient (BREB+) technique, using averaging time of 5 min. Shoot + leaf elongation and stem diameter change were monitored with position transducers using averaging time of 1 min. All parameters were all found to respond to change in radiation and transpiration within minutes or sooner. While radiation effects on canopy gas exchanges are expected, illuminating are the indirect but immediate effects on shoot + leaf growth and stem diameter change through radiation effects on transpiration and plant water status. A novel finding is that gcw also responded within minutes or sooner to radiation fluctuations and that FCO2 was related almost linearly to gcw . Results are discussed in terms of soil-plant-atmosphere continuum, and interpreted in terms of dynamic interactions between transpiration and plant water status. The clear inverse relationship between ET and elongation rate or stem diameter changes provides additional evidence supporting the validity of 5-min averaging for the BREB + technique.

Hsiao, Theodore C.↗
DOE OSTI2021

A deep learning-accelerated data assimilation and forecasting workflow for commercial-scale geologic carbon storage

Fast assimilation of monitoring data to update forecasts of pressure buildup and carbon dioxide (CO 2 ) plume migration under geologic uncertainties is a challenging problem in geologic carbon storage. The high computational cost of data assimilation with a high-dimensional parameter space impedes fast decision-making for commercial-scale reservoir management. We propose to leverage physical understandings of porous medium flow behavior with deep learning techniques to develop a fast data assimilation-reservoir response forecasting workflow. Applying an Ensemble Smoother Multiple Data Assimilation (ES-MDA) framework, the workflow updates geologic properties and predicts reservoir performance with quantified uncertainty from pressure history and CO 2 plumes interpreted through seismic inversion. As the most computationally expensive component in such a workflow is reservoir simulation, we developed surrogate models to predict dynamic pressure and CO 2 plume extents under multi-well injection. The surrogate models employ deep convolutional neural networks, specifically, a wide residual network and a residual U-Net. The workflow is validated against a flat threedimensional reservoir model representative of a clastic shelf depositional environment. Intelligent treatments are applied to bridge between quantities in a true-3D reservoir model and those in a single-layer reservoir model. The workflow can complete history matching and reservoir forecasting with uncertainty quantification in less than one hour on a mainstream personal workstation.

25 ENERGY STORAGE↗
NASA NTRSDate not supplied

2020 Wildfire Plumes Observed by Satellite and Ground Sensors in the San Francesco Bay Area

The main purpose of this research is to study the spreading of the 2020 wildfire plumes in the San Francisco Bay Area. Last year’s fire plumes have caused severe impact on regional air quality and public health over large part of the west coast. We studied fire plumes with two datasets: aerosol optical depth (AOD) retrieved from MODIS sensor onboard two NASA satellites (Terra and Aqua), and surface PM2.5 measurements from US EPA. Satellite can monitor fire plumes from a top-down view, including active fire location, emission amount, spreading of the fire plume in both horizontal and vertical directions. EPA records air quality using the ground network of in-situ sensors. In general the two points of view are consistent with each other. But in the peak of the 2020 fire season, we found an episode where the AOD and PM2.5 are out-of-phase for two days. We explored the possible mechanism for this shift with available meteorological measurements, including both ground measurements and sounding data. By tracking the evolution of the sounding data, we concluded a heated near surface inversion layer might shield the region from aloft fire plumes for two days before they touch down and severely downgraded the air quality over the whole Bay area.

Hazem Mahmoud↗
NASA NTRS2004

Satellite Mapping of Rain-Induced Nitric Oxide Emissions from Soils

We use space-based observations of NO2 columns from the Global Ozone Monitoring Experiment (GOME) to map the spatial and seasonal variations of NOx emissions over Africa during 2000. The GOME observations show not only enhanced tropospheric NO2 columns from biomass burning during the dry season but also comparable enhancements from soil emissions during the rainy season over the Sahel. These soil emissions occur in strong pulses lasting 1-3 weeks following the onset of rain, and affect 3 million sq km of semiarid sub-Saharan savanna. Surface observations of NO2 from the International Global Atmospheric Chemistry (IGAC)/Deposition of Biochemically Important Trace Species (DEBITS)/Africa (IDAF) network over West Africa provide further evidence for a strong role for microbial soil sources. By combining inverse modeling of GOME NO2 columns with space-based observations of fires, we estimate that soils contribute 3.3+/-1.8 TgN/year, similar to the biomass burning source (3.8+/-2.1 TgN/year), and thus account for 40% of surface NO(x) emissions over Africa. Extrapolating to all the tropics, we estimate a 7.3 TgN/year biogenic soil source, which is a factor of 2 larger compared to model-based inventories but agrees with observation-based inventories. These large soil NO(x) emissions are likely to significantly contribute to the ozone enhancement originating from tropical Africa.

Jaegle, L.↗
NASA NTRS1992

A new technique for simultaneous monitoring of electrocardiogram and walking cadence

A new technique for simultaneously recording continuous electrocardiographic (ECG) data and walking step rate (cadence) is described. The ECG and gait signals are recorded on 2 channels of an ambulatory Holter monitor. Footfall is detected using ultrathin, force-sensitive foot switches and is frequency modulated. The footfall signal provides an indication of the subject's activity (walking or standing), as well as the instantaneous walking rate. Twenty-three young and elderly subjects were studied to demonstrate the use of this ECG and gait recorder. High-quality gait signals were obtained in all subjects, and the effects of walking on the electrocardiogram were assessed. Initial investigation revealed the following findings: (1) Although walking rates were similar in young and elderly subjects, the elderly had both decreased heart rate (HR) variability (p < 0.005) and increased cadence variability (p < 0.0001). (2) Overall, there was an inverse relation between HR and cadence variability (r = -0.73). Three elderly subjects with no known cardiac disease had HR and cadence variability similar to those of the young, whereas elderly subjects with history of congestive heart failure were among those with the lowest HR variability and the highest cadence variability. (3) Low-frequency (approximately equal to 0.1 Hz) HR oscillations (frequently observed during standing) persisted during walking in all young subjects. (4) In some subjects, both step rate and HR oscillated at the same low frequency (approximately equal to 0.1 Hz) previously identified with autonomic control of the baroreflex.(ABSTRACT TRUNCATED AT 250 WORDS).

NASA Discipline Cardiopulmonary↗
NASA NTRS2016

Extracting Ocean-Generated Tidal Magnetic Signals from Swarm Data Through Satellite Gradiometry

Ocean-generated magnetic field models of the Principal Lunar, M2, and the Larger Lunar elliptic, N2, semidiurnal tidal constituents were estimated through a "Comprehensive Inversion" of the first 20.5 months of magnetic measurements from European Space Agency's (ESA) Swarm satellite constellation mission. While the constellation provides important north-south along-track gradiometry information, it is the unique low-spacecraft pair that allows for east-west cross-track gradiometry. This latter type is crucial in delivering an M2 estimate of similar quality with that derived from over 10 years of CHAMP satellite data but over a shorter interval, at higher altitude, and during more magnetically disturbed conditions. Recovered N2 contains nonoceanic signal but is highly correlated with theoretical models in regions of maximum oceanic amplitude. Thus, satellite magnetic gradiometry may eventually enable the monitoring of ocean electrodynamic properties at temporal resolutions of 1 to 2 years, which may have important implications for the inference of ocean temperature and salinity.

Magnetic↗
DOE OSTI2020

Investigating effects of soil chemicals on density of small mammal bioindicators using spatial capture-recapture models

Monitoring the ecological impacts of environmental pollution and the effectiveness of remediation efforts requires identifying relationships between contaminants and the disruption of biological processes in populations, communities, or ecosystems. Wildlife are useful bioindicators, but traditional comparative experimental approaches rely on a staunch and typically unverifiable assumption that, in the absence of contaminants, reference and contaminated sites would support the same densities of bioindicators, thereby inferring direct causation from indirect data. We demonstrate the utility of spatial capture-recapture (SCR) models for overcoming these issues, testing if community density of common small mammal bioindicators was directly influenced by soil chemical concentrations. By modeling density as an inhomogeneous Poisson point process, we found evidence for an inverse spatial relationship between Peromyscus density and soil mercury concentrations, but not other chemicals, such as polychlorinated biphenyls, at a site formerly occupied by a nuclear reactor. Although the coefficient point estimate supported Peromyscus density being lower where mercury concentrations were higher (β = –0.44), the 95% confidence interval overlapped zero, suggesting no effect was also compatible with our data. Estimated density from the most parsimonious model (2.88 mice/ha; 95% CI = 1.63–5.08), which did not support a density-chemical relationship, was within the range of reported densities for Peromyscus that did not inhabit contaminated sites elsewhere. Environmental pollution remains a global threat to biodiversity and ecosystem and human health, and our study provides an illustrative example of the utility of SCR models for investigating the effects that chemicals may have on wildlife bioindicator populations and communities.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Utah FORGE: Phase 3 Magnetotelluric (MT) Data

New high-quality tensor MT data at 122 sites, including the vertical magnetic field and utilizing ultra-remote referencing, have been acquired over the Utah FORGE project area. The results will be used to delineate the densities of faults and fractures in crystalline basement rocks, to define the heat sources, and to derive baseline 3D resistivity structure for later MT monitoring of temporal changes in resistivity structure following well stimulation in the EGS reservoir. There are three files here related to Utah FORGE magnetotelluric (MT) data acquisition and processing. The FORGE MT EDIs zip file contains the observed MT responses in industry-standard EDI format. For each site, there is an EDI response file that utilized a local independent reference for noise cancellation, and a file that utilized a distant reference cancelling noise associated with the DC transmission line of the Delta IPP passing down the west side of Milford Valley. These two site files could be merged as appropriate. The FORGE Model Cell Center file contains the model volume of the 3D Forge MT inversion for characterizing the resistivity structure in the project area. It was derived using finite element inversion methodology described in Wannamaker et al, in the attached FORGE Phase3 Geophysics paper, from the MT observation EDI files. It is ASCII format (.dat) and entries are defined at top of the file in a simple x-y-z-Rho listing in UTM coordinates. The element layers drape the topography so the Rho value layers are not purely horizontal slices. This greatly simplifies the listing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Rapid Optimization of Total Variation with Applications in Imaging, Additive Manufacturing, and Qualification

Total Variation optimization penalizes the gradient of a control variable or state. While this work focuses on image processing in particular, it has also found applications in inverse problems and topology optimization. In image processing, the goal is to maintain faithfulness to the original image while denoising and/or deblurring. Additionally, bilevel optimization over the spatially varying regularization weights can illuminate interfaces such as damage regions and other anomalies. We will address two fundamental challenges with TV-optimization: (i) the typical slow convergence of existing TV-optimization methods, and (ii) the selection of spatially varying TV parameters to promote interface detection. Additionally, we will apply such techniques to image data collected in additive manufacturing. In said context, stochasticity in build events induces flaws in the manufactured piece, compromising the integrity of said part. There is a critical need for in-situ monitoring to spot anomalies once they form, and in this setting we apply our total variation and hyperparameter solvers. We will develop a customized algorithm based on for extreme-scale TV-optimization that achieves super-linear or quadratic-convergence, a critical property for real-time, image-by-image analysis. A worst-case outcome is a preprocessing step that enhances image quality in-situ, specifically for out-of-focus and noisy images.

36 MATERIALS SCIENCE↗