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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Variation in surface properties as error sources in dynamic temperature measurements

Most temperature measurement methods rely upon the assumption of a single uniform source as part of the analysis in inferring an observed temperature T from the surface of a material. This is true for the radiometric and spectroscopic methods we rely upon in shock physics. However, there are obvious cases where this is a poor assumption that can cause large errors in analysis, such as the measurement of emission from a surface composed of more than one material, such as a rusted surface of Fe and Fe 2 O 3 , or a multi-material surface that could be produced through alloying methods (e.g., mokume gane) or 3D printing. Here we perform an initial examination of the effects of varied surface properties upon the analysis using idealized test data to constrain when we may have better confidence in the resulting calculations. We also examine the structures of the fits to test whether, in principle, comparing the fit with ideal gray bodies would reveal such a structure and enable the researcher to identify when a two-temperature fitting model should be used instead of a single- T model or a wavelength-dependent emissivity model.

36 MATERIALS SCIENCE↗
DOE OSTI2026

N 2 Onet: a global collaborative network facilitating advances in measurement, modeling, and mitigation of agricultural soil nitrous oxide emissions

Nitrogen (N) fertilizer supports global food production, but its use and overuse drive emissions of nitrous oxide (N 2 O), a potent and long-lived greenhouse gas. Understanding the drivers of N 2 O fluxes remains elusive, making it difficult to predict emissions in time and space and to develop and evaluate ways to lower emissions through management. Major scientific uncertainties underlying the understanding of the drivers of N 2 O fluxes identified in a workshop of N 2 O emissions experts include poor process-based understanding of controls on soil N 2 O emissions in the field; insufficient data to reduce uncertainty in N 2 O budgets from the field to regional scales, including N 2 O emission measurements and importantly, field-scale N balances; and high uncertainty in model predictions of soil N 2 O emissions across environmental and management conditions. To reduce these uncertainties, we present the concept of N 2 Onet, a global collaborative initiative to accelerate advances in N 2 O measurement, analyses, and mitigation. N 2 Onet will serve as an observational network of supersites with multi-scale measurements; a database hub for N 2 O flux and ancillary data; and a catalyst for community building, information sharing, and training. By coalescing and coordinating the global community of researchers, N 2 Onet will provide a roadmap for reducing N 2 O emissions from agriculture worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Neutron capture measurements at UMass lowell research reactor

A new facility was designed around the thermal column beam port of the 1 MW Research Reactor at the University of Massachusetts Lowell. Thermal neutrons are collimated to a 1-inch diameter beam and incident on samples to induce the radiative neutron capture. New measurements of capture gamma rays are planned for Mn, Cu, Ni, Cr, and Gd samples in the next few years. The experiments will be carried out in close collaboration with the ENSDF (Evaluated Nuclear Structure Data File) evaluation group at Brookhaven National Laboratory. The gamma rays are measured using an array of high-resolution HPGe detectors. Some of the HPGe detectors use active Compton shields that were designed from scintillation detectors and improve significantly the signal-to-background in the measured gamma-ray spectra with HPGe. The experimental spectra will be validated by the GEANT4 simulations of the array and theoretical models of the emission of gamma rays from the compound nucleus. In conclusion, the new experimental results on the capture gamma ray intensities will be incorporated in future ENSDF evaluations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Temporal Variability of Emissions Revealed by Continuous, Long-Term Monitoring of an Underground Natural Gas Storage Facility

Temporal variability contributes to uncertainty in inventories of methane emissions from the natural gas supply chain. Extrapolation of instantaneous, “snapshot-in-time” measurements, for example, can miss temporal intermittency and confound bottom-up/top-down comparisons. Importantly, no continuous long-term datasets record emission variability from underground natural gas storage facilities despite substantial contributions to sector-wide emissions. We present 11 months of continuous observations on a section of a storage site using dual-frequency comb spectroscopy (DCS observing system) and aircraft measurements. Here, we find high emission variability and a skewed distribution in which the 10% highest 3 h emission periods observed by the continuous DCS observing system comprise 41% of the total observed 3-hourly emissions. Monthly emission rates differ by >12×, and 3-hourly rates vary by 17× in 24 h. We find links to the operating phase of the facility—emission rates, including as a percentage of the total gas flow rate, are significantly higher during periods of injection compared to those of withdrawal. We find that if a high frequency of aircraft flights can occur, then the ground- and aircraft-based approaches show excellent agreement in emission distributions. A better understanding of emission variability at underground natural gas storage sites will improve inventories and models of methane emissions and clarify pathways toward mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Shift in Peaks of PAH-Associated Health Risks From East Asia to South Asia and Africa in the Future

Lung cancer risk from exposure to ambient polycyclic aromatic hydrocarbons (PAHs) is expected to change significantly by 2050 compared to 2008 due to changes in climate and emissions. Integrating a global atmospheric chemistry model, a lung cancer risk model, and plausible future emissions trajectories of PAHs, we assess how global PAHs and their associated lung cancer risk will likely change in the future. Benzo(a)pyrene (BaP) is used as an indicator of cancer risk from PAH mixtures. From 2008 to 2050, the population-weighted global average BaP concentrations under all RCPs consistently exceeded the WHO-recommended limits, primarily attributed to residential biofuel use. Peaks in PAH-associated incremental lifetime cancer risk shift from East Asia (4 × 10 –5 ) in 2008 to South Asia (mostly India, 2–4 × 10 –5 ) and Africa (1–2 × 10 –5 ) by 2050. In the developing regions of Africa and South Asia, PAH-associated lung cancer risk increased by 30–64% from 2008 to 2050, due to increasing residential energy demand in households for cooking, heating, and lighting, the continued use of traditional biomass use, increases in agricultural waste burning, and forest fires, accompanied by rapid population growth in these regions. Due to more stringent air quality policies in developed countries, their PAH lung cancer risk substantially decreased by ~80% from 2008 to 2050. Climate change is likely to have minor effects on PAH lung cancer risk compared to the impact of emissions. Future policies, therefore, need to consider efficient combustion technologies that reduce air pollutant emissions, including incomplete combustion products such as PAH.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

An explainable variational autoencoder model for three-dimensional acoustic emission source localization in hollow cylindrical structures

We introduce an explainable variational autoencoder for three-dimensional (3D) localization of acoustic emission sources in hollow cylindrical structures, with an unsupervised approach. This research capitalizes on multi-arrival waveforms generated by helical path propagation in cylindrical geometries to enable efficient two-receiver localization. By integrating the modal characteristics of Lamb modes under multi-path conditions, we demonstrate that two sets of time-of-arrival differences and peak amplitudes extracted from one receiver can serve as effective localization features. This initial approach identifies four potential source locations, highlighting the feasibility of two-receiver source localization using traditional feature extraction methods. However, direct extraction can be challenging when mode overlaps occur, complicating the localization process. To address this, our work proposes a novel waveform-based method. This method leverages the consistent dispersion characteristics within isotropic materials, where each unique combination of mode arrival times and peak amplitudes constructs a distinct waveform. This distinctiveness overcomes the ambiguities associated with mode overlaps, significantly enhancing the method’s precision and robustness. Our approach adopts a data-driven strategy for waveform-based localization using variational autoencoder (VAE). VAE discerns waveform patterns for localization, while also addressing data uncertainties. The VAE’s encoder and decoder networks capture the localization process and the source’s influence on waveform generation, respectively, guiding latent variables to segregate waveforms by source in the latent space. The design of the learning process focuses on specific localization characteristics to enhance result explainability. Localization predictions are generated by projecting test waveforms, not included in the training set, onto a trained latent space. The prediction is determined using a nearest-neighbor approach based on the closest latent representation of a source. Validation with pencil-lead-break tests on a metallic pipe confirmed our method’s effectiveness, achieving an averaged 3D localization accuracy of 0.84.

Lee, Guan-Wei↗
DOE OSTI2024

Modeling the Moisture Content and Dry Matter Loss in Dynamic Woody Biomass Storage Piles with Variable Extraction

The urgent need to mitigate climate change has spurred significant interest in renewable energy sources. This paper explores the storage and processing of woody biomass for biofuel production, considering the dynamic nature of biomass piles in real-world scenarios. A model has been developed to analyze moisture content changes and dry matter loss in woody biomass stored in piles prior to processing, taking into account varying extraction methods and environmental conditions. Case studies that examine the effects of different unpiling methods (FIFO, LIFO, and homogeneous) on moisture content and dry matter loss under various feedstock arrival rates and weather conditions are presented. Results indicate that unpiling methods significantly impact moisture content, with LIFO typically resulting in higher moisture content due to the utilization of fresher feedstock. Dry matter loss increases with pile size and time, emphasizing the importance of accurate modeling for assessing carbon emissions and feedstock quality. Furthermore, the model highlights the importance of process loading order and extraction methods in biomass storage, suggesting potential cost benefits associated with decreased moisture content. The difference between different extraction methods could vary the moisture content in the feedstock reaching the biofuel process by as much as 37.6%, however dry matter loss varies minimally for realistic pile changes. Overall, this research contributes to a better understanding of biomass storage dynamics and informs sustainable biofuel production practices.

Niska, Janel↗
DOE OSTI2022

Win-win transportation strategies for India: Linking air pollution and climate mitigation

Here, this article analyzes road transport in India to explore linkages between air pollution and climate change policies in the transportation sector. Five teams modeled five policy scenarios – fuel efficiency, electrification, alternative fuels, modal shifts, and moderation in transport demand – to explore which policy brings the largest synergetic effects in reducing carbon dioxide (CO 2 ) and particulate matter (PM 2.5 ) emissions. The teams also modeled the comprehensive scenario which included policy measures from individual scenarios. The paper concludes that all of the measures provide strong co-benefits in reducing air pollutant and CO 2 emissions. The modeling results show that increased energy efficiency of passenger and freight vehicles has the largest protentional for reducing both CO 2 and PM 2.5 emissions. It is possible to reach even a larger reduction of air pollutants and CO 2 emissions by combining several policy measures in the comprehensive scenario.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using Atmospheric Inverse Modelling of Methane Budgets with Copernicus Land Water and Wetness Data to Detect Land Use-Related Emissions

Climate change mitigation requires countries to report their annual greenhouse gas (GHG) emissions and sinks, including those from land use, land use change, and forestry (LULUCF). In Finland, the LULUCF sector plays a crucial role in achieving net-zero GHG emissions, as the sector is expected to be a net sink. However, accurate estimates of LULUCF-related GHG emissions, such as methane (CH 4 ), remain challenging. We estimated LULUCF-related CH 4 emissions in Finland in 2013–2020 by combining national land cover and remote-sensed surface wetness data with CH 4 emissions estimated by an inversion model. According to our inversion model, most of Finland’s CH 4 emissions were attributed to natural sources such as open pristine peatlands. However, our research indicated that forests with thin tree cover surrounding open peatlands may also be a significant source of CH 4 . Unlike open pristine peatlands and pristine peatlands with thin tree cover, surrounding transient forests are included in the Finnish GHG inventory if they meet the criteria used for forest land. The current Finnish national GHG inventory may therefore underestimate CH 4 emissions from forested organic soils surrounding open peatlands, although more precise methods and data are needed to verify this. Given the potential impact on net GHG emissions, CH 4 emissions from transitional forests on organic soils should be further investigated. Furthermore, the results demonstrate the potential of combining atmospheric inversion modelling of GHGs with diverse data sources and highlight the need for methods to more easily combine atmospheric inversions with national GHG inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Agricultural Impacts on Nitrogen Cycling: Climate and Air Pollution (Final Technical Report)

We have successfully added a parameterization of ammonia emissions from synthetic fertilizer and manure from agriculture to Earth System Models. We have evaluated how emissions change in the future and the processes driving these changes. We have examined the impact of agricultural ammonia emissions on present-day air quality and have evaluated the impact of resolving the emissions with high temporal resolution. We have also examined the impact of how Earth System Models treat the cycling of emissions in soils. Our code, the Flows of Agricultural Nitrogen – version 2 – model (FANv2) has been run in both the CLM framework and the ELM framework. To my knowledge the code has not yet been fully implemented into ELM. Volatilization of ammonia (NH3) from fertilizers and livestock wastes forms a significant pathway of nitrogen losses in agricultural ecosystems and constitutes the largest source of atmospheric emissions of NH3. We have provided a major update to the process model FAN (Flow of Agricultural Nitrogen), which evaluates NH3 emissions interactively within an Earth system model; in this work, the Community Earth System Model (CESM) is used. The updated version (FANv2) includes a more detailed treatment of both physical and agricultural processes, which allows the model to differentiate between the volatilization losses from animal housings, manure storage, grazed pastures, and the application of manure and different types of mineral fertilizers. The modeled ammonia emissions are first evaluated at a local scale against experimental data for various types of fertilizers and manure, and they are subsequently run globally to evaluate NH3 emissions for 2010–2015 based on gridded datasets of fertilizer use and livestock populations. Comparison of regional emissions shows that FANv2 agrees with previous inventories for North America and Europe and is within the range of previous inventories for China. However, due to higher NH3 emissions in Africa, India, and Latin America, the global emissions simulated by FANv2(48 Tg N) are 30 %–40 % higher than in the existing inventories.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Methane Exhaust Measurements at Gathering Compressor Stations in the United States

Unburned methane entrained in exhaust from natural gas-fired compressor engines (“combustion slip”) can account for a substantial portion of station-level methane emissions. A novel in-stack, tracer gas method was coupled with Fourier transform infrared (FTIR) species measurements to quantify combustion slip from natural gas compressor engines at 67 gathering and boosting stations owned or managed by nine “study partner” operators in 11 U.S. states. The mean methane emission rate from 63 four-stroke, lean-burn (4SLB) compressor engines was 5.62 kg/h (95% CI = 5.15–6.17 kg/h) and ranged from 0.3 to 12.6 kg/h. The mean methane emission rate from 39 fourstroke, rich-burn (4SRB) compressor engines was 0.40 kg/h (95% CI = 0.37– 0.42 kg/h) and ranged from 0.01 to 4.5 kg/h. Study results for 4SLB engines were lower than both the U.S. EPA compilation of air pollutant emission factors (AP-42) and Inventory of U.S. Greenhouse Gas Emissions and Sinks (GHGI) by 8 and 9%, respectively. Study results for 4SRB engines were 43% of the AP-42 emission factor and 8% of the GHGI emission factor, the latter of which does not distinguish between engine types. Total annual combustion slip from the U.S. natural gas gathering and boosting sector was modeled using measured emission rates and compressor unit counts from the U.S. EPA Greenhouse Gas Reporting Program. Modeled results [328 Gg/y (95% CI = 235–436 Gg/y) of unburned methane] would account for 24% (95% CI = 17–31%) of the 1391 Gg of methane emissions for “Gathering and Boosting Stations”, or 6% of the net emissions for “Natural Gas Systems” (5598 Gg) as reported in the 2020 U.S. EPA GHGI. In conclusion, gathering and boosting combustion slip emissions reported in the 2020 GHGI (374 Gg) fall within the uncertainty of this model.

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

Integrated modeling of RF-induced tungsten erosion at ICRH antenna structures in the WEST tokamak *

This paper introduces STRIPE (Simulated Transport of RF Impurity Production and Emission), an advanced modeling framework developed to analyze material erosion and the global transport of eroded impurities originating from radio-frequency (RF) antenna structures in magnetic confinement fusion devices. STRIPE integrates multiple physics modules: SolEdge3x for scrape-off-layer plasma profiles, COMSOL for 3D RF rectified sheath potentials, RustBCA for erosion yields and surface interactions, and global impurity transport for 3D ion energy-angle distributions and impurity transport. The framework is applied to an ion cyclotron RF-heated L-mode discharge (#57877) in the WEST tokamak, where it predicts a thirty-fold increase in gross tungsten erosion at antenna limiters during the transition from ohmic to ICRH operation. Additionally, under ICRH conditions, a tenfold enhancement in erosion is observed when comparing RF sheath effects to purely thermal sheath conditions. High-charge-state oxygen ions ($\mathrm{O}$ 6+ and above) are identified as the dominant contributors to tungsten sputtering. To validate the model, a synthetic diagnostic tool based on inverse photon efficiency (S/XB coefficients) from the ColRadPy collisional-radiative model enables direct comparison with spectroscopic measurements. Model predictions using a plasma composition of 1% oxygen and 99% deuterium show good agreement with observed W − I (400.9 nm) emission for discharge #57877, supporting the accuracy of the STRIPE framework. This study focuses specifically on gross erosion calculations to demonstrate STRIPE’s capabilities. Future extensions of this work will incorporate net erosion, re-deposition, self-sputtering effects, and whole-device modeling of sputtered tungsten impurity transport. STRIPE is also being applied to other RF-heated linear and toroidal devices, offering valuable insights for antenna design, impurity control, and performance optimization in next-generation fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A Significant Increase in Detection of High-resolution Emission Spectra Using a Three-dimensional Atmospheric Model of a Hot Jupiter

High-resolution spectroscopy has opened the way for new, detailed study of exoplanet atmospheres. There is evidence that this technique can be sensitive to the complex, three-dimensional (3D) atmospheric structure of these planets. In this work, we perform cross-correlation analysis of high-resolution (R ∼ 100,000) CRIRES/VLT emission spectra of the hot Jupiter HD 209458b. We generate template emission spectra from a 3D atmospheric circulation model of the planet, accounting for temperature structure and atmospheric motions—winds and planetary rotation—missed by spectra calculated from one-dimensional models. In this first-of-its-kind analysis, we find that using template spectra generated from a 3D model produces a more significant detection (6.9σ) of the planet’s signal than any of the hundreds of one-dimensional models we tested (maximum of 5.1σ). We recover the planet’s thermal emission, its orbital motion, and the presence of CO in its atmosphere at high significance. Additionally, we analyzed the relative influences of 3D temperature and chemical structures in this improved detection, including the contributions from CO and H{sub 2}O, as well as the role of atmospheric Doppler signatures from winds and rotation. This work shows that the hot Jupiter’s 3D atmospheric structure has a first-order influence on its emission spectra at high resolution and motivates the use of multidimensional atmospheric models in high-resolution spectral analysis.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Potential impacts of mercury released from thawing permafrost

Abstract Mercury (Hg) is a naturally occurring element that bonds with organic matter and, when converted to methylmercury, is a potent neurotoxicant. Here we estimate potential future releases of Hg from thawing permafrost for low and high greenhouse gas emissions scenarios using a mechanistic model. By 2200, the high emissions scenario shows annual permafrost Hg emissions to the atmosphere comparable to current global anthropogenic emissions. By 2100, simulated Hg concentrations in the Yukon River increase by 14% for the low emissions scenario, but double for the high emissions scenario. Fish Hg concentrations do not exceed United States Environmental Protection Agency guidelines for the low emissions scenario by 2300, but for the high emissions scenario, fish in the Yukon River exceed EPA guidelines by 2050. Our results indicate minimal impacts to Hg concentrations in water and fish for the low emissions scenario and high impacts for the high emissions scenario.

54 ENVIRONMENTAL SCIENCES↗