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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A new aerial approach for quantifying and attributing methane emissions: implementation and validation

Methane (CH 4 ) is a powerful greenhouse gas that is produced by a diverse set of natural and anthropogenic emission sources. Biogenic methane sources generally involve anaerobic decay processes such as those occurring in wetlands, melting permafrost, or the digestion of organic matter in the guts of ruminant animals. Thermogenic CH 4 sources originate from the breakdown of organic material at high temperatures and pressure within the Earth's crust, a process which also produces more complex trace hydrocarbons such as ethane (C 2 H 6 ). Here, we present the development and deployment of an uncrewed aerial system (UAS) that employs a fast (1 Hz) and sensitive (1–0.5 ppb s -1 ) CH 4 and C 2 H 6 sensor and ultrasonic anemometer. The UAS platform is a vertical-takeoff, hexarotor drone (DJI Matrice 600 Pro, M600P) capable of vertical profiling to 120 m altitude and plume sampling across scales up to 1 km. Simultaneous measurements of CH 4 and C 2 H 6 concentrations, vector winds, and positional data allow for source classification (biogenic versus thermogenic), differentiation, and emission rates without the need for modeling or a priori assumptions about winds, vertical mixing, or other environmental conditions. The system has been used for direct quantification of methane point sources, such as orphan wells, and distributed emitters, such as landfills and wastewater treatment facilities. With detectable source rates as low as 0.04 and up to ~1500 kg h -1 , this UAS offers a direct and repeatable method of horizontal and vertical profiling of emission plumes at scales that are complementary to regional aerial surveys and localized ground-based monitoring.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A semi–automatic analytical methodology for characterizing the energy consumption of MRI systems using load duration curves

Background and purpose: Magnetic resonance imaging (MRI) scanners are a major contributor to greenhouse gas emissions from the healthcare sector, and efforts to improve energy efficiency and reduce energy consumption rely on quantification of the characteristics of energy consumption. The purpose of this work was to develop a semi-automatic analytical methodology for the characterization of the energy consumption of MRI systems using only the load duration curve (LDC). LDCs are a fundamental tool used across various fields to analyze and understand the behavior of loads over time. Methods: An electric current transformer sensor and data logger were installed on two 3T MRI scanners from two vendors, termed M1 (outpatient scanner) and M2 (inpatient/emergency scanner). Data was collected for 1 month (7/11/2023 to 8/11/2023). Active power was calculated, assuming a balanced three-phase system, using the average current measured across all three phases, a 480 V reference voltage for both machines, and vendor-provided power factors. An LDC was constructed for each system by sorting the active power values in descending order and computing the cumulative time (in units of percentage) for each data point. The first derivative of the LDC was then computed (LDC’), smoothed by convolution with a window function (sLDC’), and used to detect transitions between different system modes including (in descending power levels): scan, prepared-to-scan, idle, low-power, and off. The final, segmented LDC was used to measure time (% total time), total energy (kWh), and mean power (kW) for each system mode on both scanners. The method was validated by comparing mean power values, computed using the segmented 1-month LDC, for each nonproductive system mode (i.e., prepared-to-scan, idle, lower-power, and off) against power levels measured after a deliberate system shutdown was performed for each scanner (1 day worth of data). Results: The validation revealed differences in mean power values <1.4% for all nonproductive modes and both scanners. In the scan system mode, the mean power values ranged from 29.8 to 37.2 kW and the total energy consumed for 1 month ranged from 11 106 to 14 466 kWh depending on the scanner. Over the course of 1 month, the portion of time the scanners were in nonproductive modes ranged from 76% to 80% across scanners and the nonproductive energy consumption ranged from 8010 to 6722 kWh depending on the scanner. The M1 (outpatient) scanner consumed 99.9 and 183.9 kWh/day in idle mode for weekdays and weekends, respectively, because the scanner spent 23% more time proportionally in idle mode on the weekends. Conclusions: A semi-automatic method for quantifying energy consumption characteristics of MRI scanners was introduced and validated. This method is relatively simple to implement as it requires only power data from the scanners and avoids the technical challenges associated with extracting and processing scanner log files. Finally, the methodology enables quantitative evaluation of the power, time, and energy characteristics of MRI scanners in scan and nonproductive system modes, providing baseline data and the capability of identifying potential opportunities for enhancing the energy efficiency of MRI scanners.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2021

Conjugate Photoelectron Energy Spectra Derived From Coincident FUV and Radio Measurements

We present a method for estimating incident photoelectrons' energy spectra as a function of altitude by combining global scale far-ultraviolet (FUV) and radio-occultation (RO) measurements. This characterization provides timely insights important for accurate interpretation of ionospheric parameters inferred from the recently launched Ionospheric Connection Explorer (ICON) observations. Quantification of photoelectron impact is enabled by the fact that conjugate photoelectrons (CPEs) directly affect FUV airglow emissions but not RO measurements. We demonstrate a technique for estimation of photoelectron fluxes and their spectra by combining coincident ICON and COSMIC2 measurements and show that a significant fraction of ICON-FUV measurements is affected by CPEs during the winter solstice. A comparison of estimated photoelectron fluxes with measured photoelectron spectra is used to gain further insights into the estimation method and reveals consistent values within 10–60 eV. Plain Language Summary The impact of solar radiation on the atmosphere produces highly energetic electrons, which travel freely along the magnetic Earth's field lines from one hemisphere to the other. When these electrons flow from the sunlit side into the nightside hemisphere, they interact with the neutral species and produce noticeable effects in the ionosphere such as an increase in electron temperature and enhancement of airglow emissions. This study presents a method to quantify the amount of precipitating electrons and their energy on a global scale using two recent satellite missions, ICON and COSMIC2. Our results demonstrate that coincident far-ultraviolet (ICON) and radio-occultation (COSMIC2) measurements from space are valuable resources to study precipitating electrons in the ionosphere and their impact on inferring ionospheric plasma parameters.

J M Urco↗
NASA NTRSDate not supplied

Characterization of Additively Manufacture GRCop-42 and GRCop-84

GRCop-42 (Cu-4 at.% Cr-2 at.% Nb) is a copper-based alloy optimized for high temperature, high thermal conductivity applications such as regenerative cooled rocket engine liners. For this application, it is important to minimize contamination such as trace elements and ceramic inclusions. NASA initiated a series of ten builds by eight companies to assess the repeatability of GRCop-42 between vendors and machines. Utilizing inductively coupled plasma – atomic emission spectroscopy (ICP-AES) and energy dispersive spectroscopy (EDS) techniques allowed for identification of contaminants and quantification of their chemistry. In addition, additive manufacturing (AM) creates a unique microstructure that is often highly textured in the build (Z) direction. Electron backscattered diffraction (EBSD) was used to begin quantifying the degree of crystallographic texture in the copper matrix grains. It was also used to identify the crystallographic form of Cr2Nb, the main strengthening phase, present in the samples. Results showed the presence of ceramic inclusions, highly textured grains, and both the low and high temperature phases of Cr2Nb being present.

copper↗
NASA NTRS2022

Mapping Phyllosilicates on the Asteroid Bennu Using Thermal Emission Spectra and Machine Learning Model Applications

Bennu, the target of the OSIRIS-REx mission, is an asteroid with compositions analogous to low petrologic type CI, CM, CR, and/or ungrouped carbonaceous chondrites. Asteroids like Bennu provide information about the building blocks of the early Solar System. Analysis of the mid-infrared remote sensing data informs mineral quantification. We apply a phyllosilicate specific model, developed by Breitenfeld et al. (2021) that distinguishes between Mg and Fe serpentines, to Baseball Diamond 1 (BBD1), Equatorial Station 3 (EQ3), and Touch-And-Go OSIRIS-REx Thermal Emission Spectrometer data. The average total phyllosilicate predictions are 73 (BBD1) and 72 vol% (EQ3). We observe higher Fe-cronstedtite and lower Mg-rich serpentine content in the equatorial region of Bennu than average. Mid-infrared spectral variability may be explained by sorting effects through mass movement.

Bennu↗
NASA NTRS2007

Method bacterial endospore quantification using lanthanide dipicolinate luminescence

A lanthanide is combined with a medium to be tested for endospores. The dipicolinic acid released from the endospores binds the lanthanides, which have distinctive emission (i.e., luminescence) spectra, and are detected using photoluminescence. The concentration of spores is determined by preparing a calibration curve generated from photoluminescence spectra of lanthanide complex mixed with spores of a known concentration. A lanthanide complex is used as the analysis reagent, and is comprised of lanthanide ions bound to multidentate ligands that increase the dipicolinic acid binding constant through a cooperative binding effect with respect to lanthanide chloride. The resulting combined effect of increasing the binding constant and eliminating coordinated water and multiple equilibria increase the sensitivity of the endospore assay by an estimated three to four orders of magnitude over prior art of endospore detection based on lanthanide luminescence.

Ponce, Adrian↗
DOE OSTI2025

Nearby Sites Show Similar Upwind Sources and Differing Semivolatile Concentrations in Coastal Aerosol Particles

The Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) characterized aerosol composition using measurements at two sites within 3 km (Scripps Pier and Mt. Soledad) from 15 February 2023 to 14 February 2024. Comparing the two sites shows the strong influence of upwind sources that results in similar monthly compositions at both sites. The seasonal changes in chemical mass concentrations were largely driven by the upwind source regions, with coastal northwesterly back-trajectories occurring 63−65% of the year and bringing submicrometer mass concentrations that were lower than the EPCAPE average for all trajectories at each site. In contrast, refractory black carbon (rBC) and nonrefractory (NR)-organics and nitrate mass concentrations exceeded EPCAPE average concentrations for back-trajectories from urban areas such as Los Angeles-Long Beach. For hourly measurements, NR-organics and non-sea-salt (NSS)-sulfate mass concentrations at Mt. Soledad were correlated strongly (r = 0.73−0.82) to those measured at Scripps Pier, but NR-nitrate was correlated only moderately (r = 0.63). The explanation for the lower correlation of NR-nitrate is both emissions between the sites and semivolatility, with semivolatility accounting for site-to-site changes in daily averages of +0.01 μg m −3 per percentage site-to-site difference in relative humidity and −0.07 μg m −3 per degree Celsius site-to-site difference in temperature. On average, comparing Scripps Pier to Mt. Soledad, NR-nitrate was higher by 29% because of relative humidity and lower by −26% because of temperature. NR-nitrate and rBC mass concentrations at Scripps Pier for nighttime were 13−15% higher than those for daytime because land breezes brought higher inland concentrations. Concentrations of rBC were 52% higher at Mt. Soledad than those measured at Scripps Pier, accompanied by increases in tracers for brake wear because of traffic on the steep roads within 10 m of that site. The implications are that these nearby sites had comparable monthly concentrations of measured components due to their similar backtrajectories, but hourly and daily concentration differences supported quantification of the meteorological effects from relative humidity and temperature on semivolatile NR-nitrate as well as minor differences from land−sea breezes and local emissions.

Aerosols↗
DOE OSTI2024

Statistical data analysis of x-ray spectroscopy data enabled by neural network accelerated Bayesian inference

Bayesian inference applied to x-ray spectroscopy data analysis enables uncertainty quantification necessary to rigorously test theoretical models. However, when comparing to data, detailed atomic physics and radiation transfer calculations of x-ray emission from non-uniform plasma conditions are typically too slow to be performed in line with statistical sampling methods, such as Markov Chain Monte Carlo sampling. Furthermore, differences in transition energies and x-ray opacities often make direct comparisons between simulated and measured spectra unreliable. Here, we present a spectral decomposition method that allows for corrections to line positions and bound–bound opacities to best fit experimental data, with the goal of providing quantitative feedback to improve the underlying theoretical models and guide future experiments. In this work, we use a neural network (NN) surrogate model to replace spectral calculations of isobaric hot-spots created in Kr-doped implosions at the National Ignition Facility. The NN was trained on calculations of x-ray spectra using an isobaric hot-spot model post-processed with Cretin, a multi-species atomic kinetics and radiation code. The speedup provided by the NN model to generate x-ray emission spectra enables statistical analysis of parameterized models with sufficient detail to accurately represent the physical system and extract the plasma parameters of interest.

47 OTHER INSTRUMENTATION↗
NASA NTRS2015

Quantitative Measurements of CH* Concentration in Normal Gravity and Microgravity Coflow Laminar Diffusion Flames

With the conclusion of the SLICE campaign aboard the ISS in 2012, a large amount of data was made available for the analysis of the effect of microgravity on laminar coflow diffusion flames. Previous work focused on the study of sooty flames in microgravity as well as the ability of numerical models to predict its formation in a simplified buoyancy-free environment. The current work shifts the investigation to soot-free flames, putting an emphasis on the chemiluminescence emission from electronically excited CH (CH*). This radical species is of significant interest in combustion studies: it has been shown that the CH* spatial distribution is indicative of the flame front position and, given the relatively simple diagnostic involved with its measurement, several works have been done trying to understand the ability of CH* chemiluminescence to predict the total and local flame heat release rate. In this work, a subset of the SLICE nitrogen-diluted methane flames has been considered, and the effect of fuel and coflow velocity on CH* concentration is discussed and compared with both normal gravity results and numerical simulations. Experimentally, the spectral characterization of the DSLR color camera used to acquire the flame images allowed the signal collected by the blue channel to be considered representative of the CH* emission centered around 431 nm. Due to the axisymmetric flame structure, an Abel deconvolution of the line-of-sight chemiluminescence was used to obtain the radial intensity profile and, thanks to an absolute light intensity calibration, a quantification of the CH* concentration was possible. Results show that, in microgravity, the maximum flame CH* concentration increases with the coflow velocity, but it is weakly dependent on the fuel velocity; normal gravity flames, if not lifted, tend to follow the same trend, albeit with different peak concentrations. Comparisons with numerical simulations display reasonably good agreement between measured and computed flame lengths and radii, and it is shown that the integrated CH* emission scales proportionally to the computed total heat release rate; the two-dimensional CH* spatial distribution, however, does not appear to be a good marker for the local heat release rate.

microgravity↗
NASA NTRS2012

Global Burned Area and Biomass Burning Emissions from Small Fires

In several biomes, including croplands, wooded savannas, and tropical forests, many small fires occur each year that are well below the detection limit of the current generation of global burned area products derived from moderate resolution surface reflectance imagery. Although these fires often generate thermal anomalies that can be detected by satellites, their contributions to burned area and carbon fluxes have not been systematically quantified across different regions and continents. Here we developed a preliminary method for combining 1-km thermal anomalies (active fires) and 500 m burned area observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate the influence of these fires. In our approach, we calculated the number of active fires inside and outside of 500 m burn scars derived from reflectance data. We estimated small fire burned area by computing the difference normalized burn ratio (dNBR) for these two sets of active fires and then combining these observations with other information. In a final step, we used the Global Fire Emissions Database version 3 (GFED3) biogeochemical model to estimate the impact of these fires on biomass burning emissions. We found that the spatial distribution of active fires and 500 m burned areas were in close agreement in ecosystems that experience large fires, including savannas across southern Africa and Australia and boreal forests in North America and Eurasia. In other areas, however, we observed many active fires outside of burned area perimeters. Fire radiative power was lower for this class of active fires. Small fires substantially increased burned area in several continental-scale regions, including Equatorial Asia (157%), Central America (143%), and Southeast Asia (90%) during 2001-2010. Globally, accounting for small fires increased total burned area by approximately by 35%, from 345 Mha/yr to 464 Mha/yr. A formal quantification of uncertainties was not possible, but sensitivity analyses of key model parameters caused estimates of global burned area increases from small fires to vary between 24% and 54%. Biomass burning carbon emissions increased by 35% at a global scale when small fires were included in GFED3, from 1.9 Pg C/yr to 2.5 Pg C/yr. The contribution of tropical forest fires to year-to-year variability in carbon fluxes increased because small fires amplified emissions from Central America, South America and Southeast Asia-regions where drought stress and burned area varied considerably from year to year in response to El Nino-Southern Oscillation and other climate modes.

Randerson, J. T.↗
DOE OSTI2026

Fracture Analysis of Cohesive Zone Models for Modeling Residual Stress Induced Delamination in Composite Structures

A fracture study of coupon-scale composite cylinders with embedded defects was conducted with an objective to assess and validate a modeling approach using two available cohesive material models. The study included experimental and simulation evaluations of initiation of crack growth and progression. Interrupted thermal experiments used acoustic emissions monitoring to identify the onset of crack progression during each cooling interval and ultrasonic scanning provided images of defect growth. Verification, validation, and uncertainty quantification (VVUQ) processes were performed in the assessment of the simulation predicted temperature at which crack propagation begins (quantity of interest). The Sobol sensitivity analysis identified the hoop direction elastic modulus in the carbon fiber reinforced polymer (CFRP) plies as the most influential parameter for simulations using both cohesive models, accounting for at least 70% of the variation in the temperature at crack propagation. The UQ temperature range for the Tvergaard-Hutchinson model was higher (more conservative) than the experimental acoustic measurement indicators of crack progression, while the temperature range for the Thouless-Parmigiani model enveloped the experimental data points for the primary defect size of 0.75 x 1 in. The simulations could not capture the stable crack growth indicated in the experiments. This is likely due to the models’ inability to represent anisotropic fracture toughness attributed to the structure of the orthotropic fiber weave in a woven composite laminate.

42 ENGINEERING↗
NASA NTRS2015

Quantitative Measurements of Electronically Excited CH Concentration in Normal Gravity and Microgravity Coflow Laminar Diffusion Flames

With the conclusion of the SLICE campaign aboard the ISS in 2012, a large amount of data was made available for the analysis of the effect of microgravity on laminar coflow diffusion flames. Previous work focused on the study of sooty flames in microgravity as well as the ability of numerical models to predict its formation in a simplified buoyancy-free environment. The current work shifts the investigation to soot-free flames, putting an emphasis on the chemiluminescence emission from electronically excited CH (CH*). This radical species is of significant interest in combustion studies: it has been shown that the electronically excited CH spatial distribution is indicative of the flame front position and, given the relatively simple diagnostic involved with its measurement, several works have been done trying to understand the ability of electronically excited CH chemiluminescence to predict the total and local flame heat release rate. In this work, a subset of the SLICE nitrogen-diluted methane flames has been considered, and the effect of fuel and coflow velocity on electronically excited CH concentration is discussed and compared with both normal gravity results and numerical simulations. Experimentally, the spectral characterization of the DSLR color camera used to acquire the flame images allowed the signal collected by the blue channel to be considered representative of the electronically excited CH emission centered around 431 nm. Due to the axisymmetric flame structure, an Abel deconvolution of the line-of-sight chemiluminescence was used to obtain the radial intensity profile and, thanks to an absolute light intensity calibration, a quantification of the electronically excited CH concentration was possible. Results show that, in microgravity, the maximum flame electronically excited CH concentration increases with the coflow velocity, but it is weakly dependent on the fuel velocity; normal gravity flames, if not lifted, tend to follow the same trend, albeit with different peak concentrations. Comparisons with numerical simulations display reasonably good agreement between measured and computed flame lengths and radii, and it is shown that the integrated electronically excited CH emission scales proportionally to the computed total heat release rate; the two-dimensional electronically excited CH spatial distribution, however, does not appear to be a good marker for the local heat release rate.

chemiluminescence↗
DOE OSTI2025

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing↗
DOE OSTI2026

Quantification of trace iodine using laser-induced breakdown spectroscopy for real-time monitoring of nuclear off-gas streams

This study evaluated the potential of laser-induced breakdown spectroscopy (LIBS) for real-time monitoring of trace gas-phase iodine, which is an element of high significance in nuclear applications due to its long radioactive half-life (as iodine-129), volatility, and biological impact. In anticipation of iodine evolving into off-gas systems in molten salt reactor and nuclear fuel recycling applications, this research aimed to assess LIBS performance in flowing argon and helium matrices; optimize measurement parameters using a multichannel spectrometer; and perform calibrations to assess predictive capabilities and limits of detection (LODs). Experimental results successfully measured gas-phase iodine in flowing argon and helium; however, trace iodine was not detected in air. Optimal delay times were determined to be 10 µs for argon and 1 µs for helium, which are consistent with the expected shorter plasma lifetime in helium relative to argon. An emission line survey was provided with the 206.16, 804.37, 902.24, and 905.83 nm peaks, which were identified as the strongest emission peaks. Calibration models were successfully built in both helium and argon, achieving LODs down to 3 ppm in helium and 5 ppm in argon. The iodine emission at 905.83 nm emerged as the most robust for calibration and was subsequently applied to a time series dataset in argon. The predictive trace confirmed the feasibility of employing LIBS for continuous, online quantification of trace iodine in flowing gas systems.

Andrews, Hunter B. [Oak Ridge National Laboratory ↗
NASA NTRS2007

Determination of Combustion Product Radicals in a Hydrocarbon Fueled Rocket Exhaust Plume

The identification of metallic effluent materials in a rocket engine exhaust plume indicates the health of the engine. Since 1989, emission spectroscopy of the plume of the Space Shuttle Main Engine (SSME) has been used for ground testing at NASA's Stennis Space Center (SSC). This technique allows the identification and quantification of alloys from the metallic elements observed in the plume. With the prospect of hydrocarbon-fueled rocket engines, such as Rocket Propellant 1 (RP-1) or methane (CH4) fueled engines being considered for use in future space flight systems, the contributions of intermediate or final combustion products resulting from the hydrocarbon fuels are of great interest. The effect of several diatomic molecular radicals, such as Carbon Dioxide , Carbon Monoxide, Molecular Carbon, Methylene Radical, Cyanide or Cyano Radical, and Nitric Oxide, needs to be identified and the effects of their band systems on the spectral region from 300 nm to 850 nm determined. Hydrocarbon-fueled rocket engines will play a prominent role in future space exploration programs. Although hydrogen fuel provides for higher engine performance, hydrocarbon fuels are denser, safer to handle, and less costly. For hydrocarbon-fueled engines using RP-1 or CH4 , the plume is different from a hydrogen fueled engine due to the presence of several other species, such as CO2, C2, CO, CH, CN, and NO, in the exhaust plume, in addition to the standard H2O and OH. These species occur as intermediate or final combustion products or as a result of mixing of the hot plume with the atmosphere. Exhaust plume emission spectroscopy has emerged as a comprehensive non-intrusive sensing technology which can be applied to a wide variety of engine performance conditions with a high degree of sensitivity and specificity. Stennis Space Center researchers have been in the forefront of advancing experimental techniques and developing theoretical approaches in order to bring this technology to a more mature stage.

Langford, Lester A.↗
NASA NTRS2018

The Impact of Prior Biosphere Models in the Inversion of Global Terrestrial CO2 Fluxes by Assimilating OCO-2 Retrievals

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emissions and biospheric fluxes. The processes controlling terrestrial biosphere-atmosphere carbon exchange are currently not fully understood, resulting in terrestrial biospheric models having significant differences in the quantification of biospheric CO2 fluxes. Atmospheric transport models assimilating measured (in situ or space-borne) CO2 concentrations to estimate "top-down" fluxes, generally use these biospheric CO2 fluxes as a priori information. Most of the flux inversion estimates result in substantially different spatio-temporal posteriori estimates of regional and global biospheric CO2 fluxes. The Orbiting Carbon Observatory 2 (OCO-2) satellite mission dedicated to accurately measure column CO2 (XCO2) allows for an improved understanding of global biospheric CO2 fluxes. OCO-2 provides much-needed CO2 observations in data-limited regions facilitating better global and regional estimates of "top-down" CO2 fluxes through inversion model simulations. The specific objectives of our research are to: 1) conduct GEOS-Chem 4D-Var assimilation of OCO-2 observations, using several state-of-the-science biospheric CO2 flux models as a priori information, to better constrain terrestrial CO2 fluxes, and 2) quantify the impact of different biospheric model prior fluxes on OCO-2-assimilated a posteriori CO2 flux estimates. Here we present our assessment of the importance of these a priori fluxes by conducting Observing System Simulation Experiments (OSSE) using simulated OCO-2 observations with known "true" fluxes.

Biosphere↗
DOE OSTI2024

Continuous integration data-driven platform of industrial-scale subsurface storage for real-time analytics

This project helped address the growing need for efficient and scalable models to support geological carbon and energy storage, which are crucial for achieving net-zero emissions. Traditionally accurate high-fidelity numerical models have been used to simulate relevant storage processes under a handful of processes, however such models are computationally demanding, making uncertainty quantification impractical. Consequently, we first developed a machine learning framework, based on Graph Neural Operators (GNOs), to improving the accuracy of model predictions for a fixed computational budget. We then developed an Ensemble of Improved Neural Operators (ENO), which uses bagging and Monte Carlo dropout techniques, to further improve prediction accuracy. Lastly, we developed the way to explain progressive transfer learning methods to reduce the amount of training data and computational cost of training (i.e., reduce trainable parameters) when using our models for multiple storage sites. Our numerical investigation, which used real-world case studies, demonstrated that our framework can significantly improve the safety and efficiency of geological storage operations, with potential applications in other domains such as geothermal reservoirs and climate modeling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

A Concept for the Inclusion of Analytical and Computational Capability in Existing Systems for Measurement of Neutron Flux

For approximately two decades, efforts have been sponsored by NASA's Marshall Space Flight Center to make possible high-speed, automated classification and quantification of constituent materials in various harsh environments. MSFC, along with the Air Force/Arnold Engineering Development Center, has led the work, developing and implementing systems that employ principles of emission and absorption spectroscopy to monitor molecular and atomic particulates in gas plasma of rocket engine flow fields. One such system identifies species and quantifies mass loss rates in H2/O2 rocket plumes. Other gases have been examined and the physics of their detection under numerous conditions were made a part of the knowledge base for the MSFC/USAF team. Additionally, efforts are being advanced to hardware encode components of the data analysis tools in order to address real-time operational requirements for health monitoring and management. NASA has a significant investment in these systems, warranting a spiral approach that meshes current tools and experience with technological advancements. This paper addresses current systems - the Optical Plume Anomaly Detector (OPAD) and the Engine Diagnostic Filtering System (EDIFIS) - and discusses what is considered a natural progression: a concept for migrating them towards detection of high energy particles, including neutrons and gamma rays. The proposal outlines system development to date, basic concepts for future advancements, and recommendations for accomplishing them.

Patrick, Clinton↗