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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 19 records

The Atmospheric Effects of HSCT Emissions Simulated by a 3-Wave Interactive Model

An interactive model which couples a semi-spectral dynamical model, a radiative transfer code and a two-dimensional chemistry transport model (2-D CTM), is used to assess the atmospheric effects of the High-Speed Civil Transport (HSCT) engine emissions. The residual mean meridional circulation, the zonal-mean temperature and the eddy diffusion coefficients are calculated using zonal means and three longest zonal waves of dynamical variables integrated in the semi-spectral dynamical model. They are used in the 2-D CTM to simulate the distribution of trace gases in the atmosphere. The simulated ozone is sent to the radiative transfer code to calculate the heating rates, which drive the dynamics. This radiative coupling connects the dynamical and photochemical processes and creates feedback when the atmosphere is perturbed. It is found that in most areas the ozone depletion caused by HSCT emissions calculated using the 3-wave model has the features similar to, but with significantly larger magnitude than that calculated by the AER 2-D CTM with prescribed transport parameters and temperature. The difference is mostly due to the differences in the circulation in the two models. The radiative feedback effects are investigated by comparing the ozone depletion calculated with the baseline dynamics and with the dynamics perturbed by the HSCT emissions. The feedback through changes in the residual mean meridional circulation and the eddy diffusion coefficients has moderate effects on the simulated ozone depletion. It reduced the ozone depletion by 20-30% in northern mid and high-latitudes. However, the feedback through changes in the zonal- mean temperature is negligible.

Shia, R.-L.↗

Loop heating by D.C. electric current and electromagnetic wave emissions simulated by 3-D EM particle zone

We have shown that a current-carrying plasma loop can be heated by magnetic pinch driven by the pressure imbalance between inside and outside the loop, using a 3-dimensional electromagnetic (EM) particle code. Both electrons and ions in the loop can be heated in the direction perpendicular to the ambient magnetic field, therefore the perpendicular temperature can be increased about 10 times compared with the parallel temperature. This temperature anisotropy produced by the magnetic pinch heating can induce a plasma instability, by which high-frequency electromagnetic waves can be excited. The plasma current which is enhanced by the magnetic pinch can also excite a kinetic kink instability, which can heat ions perpendicular to the magnetic field. The heating mechanism of ions as well as the electromagnetic emission could be important for an understanding of the coronal loop heating and the electromagnetic wave emissions from active coronal regions.

Sakai, J. I.↗

ILAMBv2.7 benchmarking results comparing E3SMv2.1 land-atmosphere coupled (BGCv2LNDATM) and stand alone land (ELM) simulations with CMIP6 emission driven historical simulations

This dataset contains land model benchmarking results for the Energy Exascale Earth System Model version 2.1 (E3SMv2.1), including outputs from both coupled biogeochemistry simulations and stand-alone land model simulations. These results are compared against several emission-driven historical simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Benchmarking was conducted using the International Land Model Benchmarking (ILAMB) package, version 2.7 (ILAMBv2.7). CMIP6 model outputs were sourced from the Earth System Grid Federation (ESGF), while the E3SMv2.1 results were derived from raw model outputs. These outputs underwent processing steps such as time serialization, conservative regridding, and data standardization to ensure comparability. For spatial interpolation, the Earth System Modeling Framework (ESMF) tool, ESMF_RegridWeightGen, was employed to generate regridding weights, enabling the transformation of E3SM’s native cubed-sphere grid to a regular latitude-longitude grid.

Feng, Sha [PNNL]↗

Divine-garrett model and Jovian synchrotron emission

Simulations of synchrotron emission from relativistic electrons trapped in Jupiter's magnetic field are used to evaluate the energetic electron distribution of the Divine-Garrett Jupiter radiation belt model at radial distances less than 4 Jovian radii.

Radial diffusion-models electrons jupiter↗

Instrumental and observational requirements for space-based imaging of magnetospheric emissions

Simulated images of extreme ultraviolet (EUV) emissions from energetic outflowing ions have been constructed to study techniques for remotely sensing the dynamic behavior of hot plasmas in the near-Earth environment. These calculations include realistic assumptions about the energetic ion outflow from high latitudes and take into account the effects of cold plasmaspheric and ionospheric ions. The energetic ion outflow is determined from a statistical study based on five years of measurements from the Energetic Ion Composition Spectrometer on Dynamics Explorer 1. The simulated images change significantly with viewing geometry and certain spacecraft locations are clearly favorable for observing emissions from energetic ions. For example, for a near equatorial orbit, viewing locations greater than 9 Earth radii are required to observe outflowing ions above the cold plasmaspheric background. We will discuss other important considerations for magnetospheric imaging including the sensitivity requirements of the detector. In particular, we consider the performance of multi-layer optics for EUV wavelengths.

Robinson, R. M.↗

Simulated infrared emission spectra of highly excited polyatomic molecules: a detailed model of the PAH-UIR hypothesis

A detailed description of the polycyclic aromatic hydrocarbon (PAH)/unidentified infrared band (UIR) mechanism is presented in which experimental spectral bandshape functions are used to simulate IR emission spectra for individual molecules. These spectra are additively superimposed to produce a conglomerate spectrum representative of a family of PAH molecules. Ab initio vibrational frequencies and intensities for nine PAHs (neutral and cationic) as large as ovalene are used in conjunction with measured bandshape and temperature-dependent redshift data to simulate the UIR bands. The calculated spectra of cations provide a closer match to the UIRs than do those of the neutrals. However, the PAH cations used in the simulations fail to reproduce the details of the UIR emission spectra. The discrepancies are potentially alleviated if both larger PAHs and a greater number of PAHs were included in the simulation.

Non-NASA Center↗

Sensitivity of Simulated Radiative Emission from Nitrogen Flows to Chemical Parameters

Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.

Kaelan B Hansson↗

Sensitivity of Simulated Radiative Emission from Nitrogen Flows to Chemical Parameters

Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.

Kaelan Hansson↗

Experimental Characterization of Gas Turbine Emissions at Simulated Flight Altitude Conditions

NASA's Atmospheric Effects of Aviation Project (AEAP) is developing a scientific basis for assessment of the atmospheric impact of subsonic and supersonic aviation. A primary goal is to assist assessments of United Nations scientific organizations and hence, consideration of emissions standards by the International Civil Aviation Organization (ICAO). Engine tests have been conducted at AEDC to fulfill the need of AEAP. The purpose of these tests is to obtain a comprehensive database to be used for supplying critical information to the atmospheric research community. It includes: (1) simulated sea-level-static test data as well as simulated altitude data; and (2) intrusive (extractive probe) data as well as non-intrusive (optical techniques) data. A commercial-type bypass engine with aviation fuel was used in this test series. The test matrix was set by parametrically selecting the temperature, pressure, and flow rate at sea-level-static and different altitudes to obtain a parametric set of data.

GAS TURBINES↗

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗

Regional Oil and gas Aerial Methane Synthesis model (ROAMS) v2.0

The Regional Oil and gas Aerial Methane Synthesis model is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

Regional Oil and gas Aerial Methane Synthesis model (Analytica) (ROAMS Analytica) v1.5.2

The Regional Oil and gas Aerial Methane Synthesis model (Analytica) is a tool to convert the results of wide-area, source-resolved aerial methane remote sensing surveys of oil and natural gas infrastructure in a given region into methane emissions inventories (estimates of the magnitude and breakdown of methane emissions from the surveyed infrastructure). This version is written in the Analytica programming language, and this version accompanies a correction in preparation for submission to Sherwin et al. 2024 (Nature). The tool leverages databases of source-resolved methane emissions detected in aerial surveys, aerial survey coverage information (which areas were measured and when), data summarizing surveyed oil and natural gas infrastructure and production (derived from third-party databases), as well as state-of-the-art mechanistic emissions simulation tools to characterize emissions too small for the aerial system to see. The regional methane emissions estimates produced by this tool are much more granular in both space and asset type than common satellite- or flux tower-based regional estimates. Unlike other tools for converting site-level measurements into regional emissions estimates, our unique geostatistical approach integrates aerially measured emissions with limited need for statistical extrapolation, which can be highly sensitive to modeler assumptions. As a result, ROAMS-based estimates of regional methane emissions from oil and gas activity are widely viewed as highly credible, as evidenced by the success of Dr. Sherwin's recent paper in Nature.

Sherwin, Evan [Lawrence Berkeley National Laborato↗

A Probabilistic Model for Simulating Magnetoacoustic Emission Responses in Ferromagnets

Magnetoacoustic emission (MAE) is a phenomenon where acoustic noise is generated due to the motion of non-180 magnetic domain walls in a ferromagnet with non-zero magnetostrictive constants. MAE has been studied extensively for many years and has even been applied as an NDE tool for characterizing the heat treatment of high-yield low carbon steels. A complete theory which fully accounts for the magnetoacoustic response, however, has not yet emerged. The motion of the domain walls appears to be a totally random process, however, it does exhibit features of regularity which have been identified by studying phenomena such as 1/f flicker noise and self-organized criticality (SOC). In this paper, a probabilistic model incorporating the effects of SOC has been developed to help explain the MAE response. The model uses many simplifying assumptions yet yields good qualitative agreement with observed experimental results and also provides some insight into the possible underlying mechanisms responsible for MAE. We begin by providing a brief overview of magnetoacoustic emission and the experimental set-up used to obtain the MAE signal. We then describe a pseudo-probabilistic model used to predict the MAE response and give an example of the predicted result. Finally, the model is modified to account for SOC and the new predictions are shown and compared with experiment.

Namkung, M.↗

The Effect of Transport and Circulation Differences on Stratospheric Ozone Recovery in Two 35-year Three-dimensional Simulations

The NASA Global Modeling Initiative (GMI) has completed two 35-year simulations with WMO future baseline boundary conditions that simulate increasing N2O and CH4 emissions and decreasing organic chlorine and bromine emissions. Simulations were done with the GMI offline chemistry and transport model using 1) 1 year of winds from the Finite-Volume General Circulation Model (FV-GCM), repeated for the 35 years, and 2) 1 year of winds from the Finite-Volume Data Assimilation System (FV-DAS), repeated for 35-years. The simulations have full stratospheric chemistry. To understand differences in simulated ozone recoveries, basic transport and circulation differences between these models are evaluated. The distribution of mean age of stratospheric air in the FV-GCM run agrees well with observations in the lower stratosphere but the FV-DAS ages are generally too low. This implies circulation and mixing differences that will affect the distributions of other trace species such as CH4, NO, and the organic halogens, all of which are responding to changing boundary conditions and are involved in ozone loss. Realism of model transport is evaluated, with particular attention given to regions and seasons where ozone recovery is expected. Preliminary results indicate increasing ozone trends in the lowermost stratosphere in summer and in the Antarctic and Arctic lower stratosphere in winter and spring.

Bhartia, P. K.↗

Calculating Methane Emissions from Offshore Facilities Using Bottom-Up Methods

With changing demands in regulation, understanding methane emissions from offshore oil and gas production infrastructure has become increasingly important. Reported emissions from facilities in the Gulf of Mexico range from zero to thousands of tons of methane per hour, but these is currently no clear understanding of how this range compares to expected emissions from normally operating facilities. To generate realistic emission estimates, we create two bottom-up models that simulate emissions from facilities operating in the Gulf of Mexico. We estimate type 1 prototypical facilities (typically unmanned, older, lower-producing platforms in shallow water with little processing equipment, compressors, or storage tanks) to emit an average of 13 kg CH 4 h −1 , which corresponds to a loss of 2.7% of the average facility production. Type 2 prototypical facilities (continuously manned, higher production and operate in deeper water with processing equipment, oil storage tanks, compressors and power generation) emit an average of 88 kg CH 4 h −1 , which corresponds to a loss of 2.5% of production. The average measured emission from type 1 facilities was 18 kg CH 4 h −1 with a median production loss estimated at 8%. The average measured emission from type 2 facilities was 36 kg CH 4 h −1 with a median production loss estimated at 2.4%. Using emission factors that consider the long-tail emission distribution partly reconciles the difference between modelled and measured emission estimates, but we suggest the current the fugitive emission estimate may be an underestimate and more data on the number and size of fugitive emissions could explain differences between the modelled and measured emission estimate. We suggest the bottom-up approach described here that uses production data coupled with facility equipment could be used to identify facilities that have abnormally large measured emissions, caused by methodological failure or larger than expected fugitive emissions, which should be targeted for further evaluation resulting in remeasurement or identification of source type so that a more accurate estimates can be made on the absolute emission.

bottom-up↗