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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Controlling pollutant emissions in a high-pressure combustor with fuel-diluent blending

This paper investigates the formation of nitric oxide (NO) and carbon monoxide (CO) emissions as a function of nitrogen (N 2 ) or carbon dioxide (CO 2 ) diluent content, added to a premixed reacting jet in crossflow. Here, reaction characteristics of a rich methane-air jet injected into a lean vitiated crossflow were analyzed at an elevated pressure of 5 atm. The jet was pre-heated and enriched with 0%, 15%, 30%, and 50% mass fraction to quantify the effect on pollutant emissions. Simulated results of the full chemistry Star-CCM+CFD model were verified with data taken in the experimental high-pressure combustion facility, which provides pressure, temperature and velocity profiles, as well as line-of-sight chemiluminescence and exit emission measurements. The analysis revealed the significant influence of the diluent to delay axial combustion; this mixing delay increased the axial flame lift-off and controlled any thermal ignition limitations. Increasing the diluent content increased the timescale for the flame to stabilize, which allowed for greater entrainment of crossflow oxidizer into the axial jet stream, and led to decreased pollutant emissions. Hence, crossflow entrainment is a critical driving force at high diluent content. Local nitric oxide (NO) emission formation in the axial stage was predicted numerically, showing the correlation between diluent addition, axial heat release, and the formation of nitric oxide pollution. The high diluent levels leaned out the jet mixture and delayed axial combustion, while reducing prompt and thermal NOx by mitigating flame hotspots and minimizing the timescale that the products remain at high temperatures.

03 NATURAL GAS↗
DOE OSTI2022

Machine learning-based observation-constrained projections reveal elevated global socioeconomic risks from wildfire

Reliable projections of wildfire and associated socioeconomic risks are crucial for the development of efficient and effective adaptation and mitigation strategies. The lack of or limited observational constraints for modeling outputs impairs the credibility of wildfire projections. Here, we present a machine learning framework to constrain the future fire carbon emissions simulated by 13 Earth system models from the Coupled Model Intercomparison Project phase 6 (CMIP6), using historical, observed joint states of fire-relevant variables. During the twenty-first century, the observation-constrained ensemble indicates a weaker increase in global fire carbon emissions but higher increase in global wildfire exposure in population, gross domestic production, and agricultural area, compared with the default ensemble. Such elevated socioeconomic risks are primarily caused by the compound regional enhancement of future wildfire activity and socioeconomic development in the western and central African countries, necessitating an emergent strategic preparedness to wildfires in these countries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

NLR's FleetDNA Speed Distributions for EPA MOVES

The U.S. Environmental Protection Agency (EPA) MOtor Vehicle Emission Simulator (MOVES) models mobile sources of air toxics at small and large scales across the Unites States. Vehicle speed distributions based on the type of vehicle, type of road traveled, and hour of the day are inputs into MOVES. In conjunction with vehicle miles traveled (VMT) inputs, they are used to estimate total operation time and select the relevant driving cycles from which running operating modes and emissions are estimated. In an ongoing research effort, the National Laboratory of the Rockies (NLR) partnered with the EPA to provide default average speed data for heavy-duty vehicles based on NLR's FleetDNA database and the Bourns College of Engineering - Center for Environmental Research and Technology (CE-CERT) data set from the University of California, Riverside.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Implementation and Evaluation of Emission‐Driven Land‐Atmosphere Coupled Simulation in E3SMv2.1

Emissions-driven (prognostic CO 2 ) simulations are essential for representing two-way carbon-climate feedback in Earth System Models. We present an emissions-driven land–atmosphere coupled biogeochemistry (BGC) configuration (BGCLNDATM_progCO2) in version 2.1 of the Energy Exascale Earth System Model (E3SMv2.1). This is the first E3SM configuration that performs land-atmosphere emission-hindcasts. Here, we document its implementation, evaluate the model's performance against observations and other models, and propose a structured evaluation protocol for such emissions-driven simulations. We conducted transient historical simulations (1850–2014) with BGCLNDATM_progCO2 and compare them to reference simulations—a land-atmosphere coupled simulation without BGC and a standalone land simulation with BGC, both using prescribed CO 2 concentrations—and to observations. BGCLNDATM_progCO2 overestimates atmospheric CO 2 concentrations by 11–23 ppm yet stays within the 40-ppm spread CMIP6 emission-driven models and retains physical climate properties comparable to the reference runs. The CO 2 biases are partly attributed to underrepresented oceanic CO 2 uptake and inadequate representations of some terrestrial processes. In general, introducing prognostic CO 2 did not change physical climate metrics at the global scale but had larger regional effects, particularly over land where spatially heterogeneous CO 2 and prognostic leaf area index influenced surface energy balance. Finally, we propose a general evaluation protocol including spin-up assessment, atmospheric CO 2 benchmarking, physical climate evaluation, and land biogeochemical analysis to support scientific rigor and facilitate inter-model comparisons. The new configuration lays the groundwork for future enhancements, including improved terrestrial biogeochemical processes, integrated marine biogeochemistry, and additional human–Earth system interactions. These developments advance E3SM toward fully coupled emissions-driven simulations, enabling more accurate carbon–climate feedback projections and informing mitigation policy by providing physically consistent carbon-budget metrics for mitigation scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Developing a heavy-duty vehicle activity database to estimate start and idle emissions

Heavy-duty vehicle start and idling activities were characterized from two datasets to improve emission estimates in the MOtor Vehicle Emission Simulator (MOVES): 1. Fleet DNA from the National Renewable Energy Laboratory (NREL) and 2. A dataset collected by the University of California, Riverside for the California Air Resources Board. Furthermore, the combined dataset includes 564 commercial vehicles, over 23,000 vehicle days of operation and covers seven of the nine heavy-duty source types defined by MOVES. The start and idle activities are characterized and illustrated across MOVES source types, vocations, fleets, days, and hours. This study provides the most comprehensive analysis yet made publicly available to characterize start and idle activity for heavy-duty vehicles within the United States. The results also show there is significant uncertainty in the average heavy-duty idle and start activity due to the large variation in activity across fleets and vocations, and sparsity of nation-wide vehicle population data by vocation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Constructing the Mechanism of Dinoflagellate Luciferin Bioluminescence Using Computation

Dinoflagellate luciferin bioluminescence is unique since it does not rely on decarboxylation but is poorly understood compared to that of firefly, bacteria, and coelenterata luciferins. Here, in this work, we computationally investigate possible protonation states, stereoisomers, a chemical mechanism, and the dynamics of the bioluminescence intermediate that is responsible for chemiexcitation. Using semiempirical dynamics, time-dependent density functional theory static calculations, and a correlation diagram, we find that the intermediate’s functional group that is likely responsible for chemiexcitation is a 4-member ring, a dioxetanol, that undergoes [2π + 2π] cycloreversion and the biolumiphore is the cleaved structure. The simulated emission spectra and luciferase-dependent absorbance spectra agree with the experimental data, giving support to our proposed mechanism and biolumiphore. We also compute circular dichroism spectra of the intermediate’s four stereoisomers to guide future experiments in differentiating them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

Noise equivalent circuit of a semiconductor laser diode

A small-signal model of a semiconductor laser is extended to include the effects of intrinsic noise by adding current and voltage noise sources. The current noise source represents the shot noise of carrier recombination, while the voltage noise source represents the random process of simulated emission. The usefulness of the noise equivalent circuit is demonstrated by calculating the modulation and noise characteristics of a current-driven diode as a function of bias current and frequency.

Harder, C.↗
NASA NTRS2005

High Power Laser Diode Array Qualification and Guidelines for Space Flight Environments

Semiconductor laser diodes emit coherent light by simulated emission generated inside the cavity formed by the cleaved end facets of a slab of semiconductor that is typically less than a millimeter in any dimension for single emitters. The diode is pumped by current injection in the p-n junction through the metallic contacts. Laser diodes emitting in the range of 0.8 micron to 1.06 micron have a wide variety of applications from pumping erbium doped fiber amplifiers, dual-clad fiber lasers, solid-state lasers used in telecom, aerospace, military, medical purposes and all the way to CD players, laser printers and other consumer and industrial products. Laser diode bars have many single emitters side by side and spaced approximately .5 mm on a single slab of semiconductor material approximately .5 mm x 10 mm. The individual emitters are connected in parallel maintaining the voltage at -2V but increasing the current to ~50-100A/bar. Stacking these laser diode bars in multiple layers, 2 to 20+ high, yields high power laser diode arrays capable of emitting several hundreds of Watts. Electrically the bars are wired in series increasing the voltage by 2V/bar but maintaining the total current at ~50-100A. These arrays are one of the enabling technologies for efficient, high power solid-state lasers. Traditionally these arrays are operated in QCW (Quasi CW) mode with pulse widths ~10-200 (mu)s and with repetition rates of ~10-200Hz. In QCW mode the wavelength and the output power of the laser reaches steady-state but the temperature does not. The advantage is a substantially higher output power than in CW mode, where the output power would be limited by the internal heating and hence the thermal and heat sinking properties of the device. The down side is a much higher thermal induced mechanical stress caused by the constant heating and cooling cycle inherent to the QCW mode.

Eegholm, Niels↗
NASA NTRS2016

Constraining the Size of Near Earth Asteroids

Quick and accurate determination of the size of an asteroid is of great interest to the Asteroid Threat Assessment Project and is difficult to accomplish. With a combination of visible and thermal measurements we employ a method that leverages the size estimations of each model as physical constraints on the true diameter. This method breaks degeneracies present in the thermal and visible model from sparse data. In the visible bands we use both the established H-G relationship and its successor the H-G1G2 model, which has improved capabilities in the opposition effect and large phase angles. For the thermal models we use the Near Earth Asteroid Thermal Model (NEATM), the Night Emission Simulated Thermal Model (NESTM), and the Advanced Thermophysical Model (ATPM).

Nelson, Tyler↗
NASA NTRSDate not supplied

Temporal and Spatial Evolution of Nanoflare Heating in Solar AR

Nanoflares are thought to be prime candidates to heat the solar non-flaring active regions. However, their direct individual detection with current instrumentation remains challenging. Understanding the frequency and magnitude of nanoflares is crucial for understanding their role in coronal heating. In this study, we employ a field-aligned hydrodynamic model to simulate the evolution of an active region (AR) under nanoflare heating scenarios. By comparing the simulated emission with EUV and X-ray observations, we determine the frequency of heating events and investigate how it evolves with the AR evolution. Additionally, we analyze the impact of observational parameters, such as instrument spatial resolution and energy band, on estimating nanoflare properties. Our findings contribute to advancing our understanding of the role of nanoflares in coronal heating and refining observational parameters for detecting these events.

nano flare↗
NASA NTRS2000

Simulated Active Region Emission and Dynamics: A STEREO Perspective

We present detailed three-dimensional simulations of active regions resulting from numerical models of sunspots coupled to coronal excitation and emission. The models incorporate a fully three-dimensional magnetoconvection calculation, described in a poster by Hurlburt and Rucklidge, potential field extrapolations from the sunspot model boundary conditions, steady-state coronal loops powered by the convective motions at the surface, EUV and X-ray instrument response functions, and a full voxel rendering. The result is a simulated dynamical active region in three dimensions which enables us to explore coronal heating and its relationship to the dynamics of the photosphere and convection zone. The 3D rendering of the resulting EUV emission allows us to investigate the expected coronal signatures of the EUVI instruments on board the twin STEREO spacecraft to be launched in 2004. The hybrid model developed here also provides a simulation testbed for the development of future STEREO image reconstruction tools: an integral component in the access to STEREO data by the solar physics community.

Alexander, David↗
NASA NTRS2015

Differences Between the HUT Snow Emission Model and MEMLS and Their Effects on Brightness Temperature Simulation

Microwave emission models are a critical component of snow water equivalent retrieval algorithms applied to passive microwave measurements. Several such emission models exist, but their differences need to be systematically compared. This paper compares the basic theories of two models: the multiple-layer HUT (Helsinki University of Technology) model and MEMLS (Microwave Emission Model of Layered Snowpacks). By comparing the mathematical formulation side-by-side, three major differences were identified: (1) by assuming the scattered intensity is mostly (96) in the forward direction, the HUT model simplifies the radiative transfer (RT) equation into 1-flux; whereas MEMLS uses a 2-flux theory; (2) the HUT scattering coefficient is much larger than MEMLS; (3 ) MEMLS considers the trapped radiation inside snow due to internal reflection by a 6-flux model, which is not included in HUT. Simulation experiments indicate that, the large scattering coefficient of the HUT model compensates for its large forward scattering ratio to some extent, but the effects of 1-flux simplification and the trapped radiation still result in different T(sub B) simulations between the HUT model and MEMLS. The models were compared with observations of natural snow cover at Sodankyl, Finland; Churchill, Canada; and Colorado, USA. No optimization of the snow grain size was performed. It shows that HUT model tends to under estimate T(sub B) for deep snow. MEMLS with the physically-based improved Born approximation performed best among the models, with a bias of -1.4 K, and an RMSE of 11.0 K.

Pan, Jinmei↗
DOE OSTI2026

Mechanistic Modeling of TEG Dehydrator Emissions in Oil and Gas Industry

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviors were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades.

MAES↗
NASA NTRS1991

Procedures for Including Secondary Electron Emission in Numerical Simulations of Plasma-Insulator Interactions

Previous Monte Carlo simulations provide a data base for properties of secondary electron emission (SEE) from insulators and metals. Incident primary electrons are considered at energies up to 1200 eV. The behavior of secondary electrons is characterized by (1) yield vs. primary energy E(sub p), (2) distribution vs. secondary energy E(sub s), and (3) distribution vs. angle of emission theta. Special attention is paid to the low energy range E(sub p) up to 50 eV, where the number and energy of secondary electrons is limited by the finite band gap of the insulator. For primary energies above 50 eV the SEE yield curve can be conveniently parameterized by a Haffner formula. The energy distribution of secondary electrons is described by an empirical formula with average energy about 8.0 eV. The angular distribution of secondaries is slightly more peaked in the forward direction than the customary cos theta distribution. Empirical formulas and parameters are given for all yield and distribution curves. Procedures and algorithms are described for using these results to find the SEE yield, and then to choose the energy and angle of emergence of each secondary electron. These procedures can readily be incorporated into numerical simulations of plasma-solid surface interactions in low earth orbit.

Beyst, Brian↗
NASA NTRS2016

Disk Emission from Magnetohydrodynamic Simulations of Spinning Black Holes

We present the results of a new series of global, three-dimensional, relativistic magnetohydrodynamic (MHD) simulations of thin accretion disks around spinning black holes. The disks have aspect ratios of H/R approx. 0.05 and spin parameters of a/M = 0, 0.5, 0.9, and 0.99. Using the ray-tracing code Pandurata, we generate broadband thermal spectra and polarization signatures from the MHD simulations. We find that the simulated spectra can be well fit with a simple, universal emissivity profile that better reproduces the behavior of the emission from the inner disk, compared to traditional analyses carried out using a Novikov-Thorne thin disk model. Finally, we show how spectropolarization observations can be used to convincingly break the spin-inclination degeneracy well known to the continuum-fitting method of measuring black hole spin.

accretion↗
NASA NTRS1978

VEEP: A Vehicle Economy, Emissions, and Performance simulation program

The purpose of the VEEP simulation program was to: (1) predict vehicle fuel economy and relative emissions over any specified driving cycle; (2) calculate various measures of vehicle performance (acceleration, passing manuevers, gradeability, top speed), and (3) give information on the various categories of energy dissipation (rolling friction, aerodynamics, accessories, inertial effects, component inefficiences, etc.). The vehicle is described based on detailed subsystem information and numerical parameters characterizing the components of a wide variety of self-propelled vehicles. Conventionally arranged heat engine powered automobiles were emphasized, but with consideration in the design toward the requirement of other types of vehicles.

Klose, G. J.↗
NASA NTRS2019

Cluster Analysis of Spectroscopic Line Profiles and EUV Emission in RMHD Simulations and Observations of the Solar Atmosphere

Spatially-resolved observations from the IRIS, SDO/AIA, and other space mission and ground-based telescopes, coupled with realistic 3D RMHD simulations, are a powerful tool for analysis of processes in the solar atmosphere. To better understand the dynamical and thermodynamic properties in the simulation data and their connection to observations, it is essential to determine similarities in the behaviors of the synthesized and observed emission. However, the complexity of observational data and physical processes makes comparison of observations and modeling results difficult. In this work, we show the initial results of application of K-Means clustering (unsupervised machine learning) algorithm to two different problems: 1) recognition of the typical spectroscopic line profiles observed by IRIS during solar flares and their typical dynamic behavior; 2) recognition of shocks and heating events in synthetic AIA emission data obtained from StellarBox quiet-Sun simulations. The average silhouette width technique for the KMeans algorithm is utilized in different ways to obtain optimal numbers of clusters. We discuss application of the emission clustering to visualizations of the computational volume, understanding its evolutionary trends and behavior patterns, and inversion (reconstruction) of physical properties of the solar atmosphere from synthesizes emission data.

Sadykov, Viacheslav↗