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At least 1,063 records · Page 59

A51F-0123: Model Analysis of Tropospheric Aerosol Variability and Sources over the North Atlantic During NAAMES 2015-2016

The North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) is a five-year Earth-Venture Suborbital-2 Mission to characterize the plankton ecosystems and their influences on remote marine aerosols, boundary layer clouds, and their implications for climate in the North Atlantic. While marine-sourced aerosols have been shown to make important contributions to surface aerosol loading, cloud condensation nuclei and ice nuclei concentrations over remote marine and coastal regions, it is still a challenge to differentiate the marine biogenic aerosol signal from the strong influence of continental pollution outflow. We examine here the spatiotemporal variability and quantify the sources of tropospheric aerosols over the North Atlantic during the first two phases (November 2015 and May-June 2016) of NAAMES using a state-of-the-art chemical transport model (GEOS-Chem). The model is driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) from the NASA Global Modeling and Assimilation Office (GMAO). It includes sulfate-nitrate-ammonium aerosol thermodynamics coupled to ozone-NOx-hydrocarbon-aerosol chemistry, mineral dust, sea salt, elemental and organic carbon aerosols, and especially a recently implemented parameterization for the marine primary organic aerosol emission. The simulated aerosols over the North Atlantic are evaluated with available satellite (e.g., MODIS) observations of aerosol optical depths (AOD), and aircraft and ship aerosol measurements. We diagnose transport pathways for continental pollution outflow over the North Atlantic using carbon monoxide, an excellent tracer for anthropogenic pollution transport. We also conduct model perturbation experiments to quantify the relative contributions of terrestrial and oceanic sources to the aerosol loading, AOD, and their variability over the North Atlantic.

aerosols↗

Free-flight investigation of the stability and control characteristics of a STOL model with an externally blown jet flap

The stability and control characteristics of a four-engine turbofan STOL transport model having an externally blown jet flap have been investigated by means of the flying-model technique in the Langley full-scale tunnel. The flight characteristics of the model were investigated under conditions of symmetric and asymmetric (one engine inoperative) thrust at lift coefficients up to 9.5 and 5.5, respectively. Static characteristics were studied by conventional power-on force tests over the flight-test angle-of-attack range including the stall. In addition to these tests, dynamic longitudinal and lateral stability calculations were performed for comparison with the flight-test results and for use in correlating the model results with STOL handling-qualities criteria.

Parlett, L. P.↗

Mass flux and crystal composition in the Hg(0.8)Cd(0.2)Te-HgI2 vapor transport system

Chemical vapor transport (CVT) studies of the Hg(0.8)Cd(0.2)Te-HgI2 system were performed to further test and extend the transport model developed earlier in this laboratory for this system. Experimental results in terms of mass transport rates and composition of the grown crystals as a function of growth temperature and of transport agent (HgI2) pressure, for a fixed source temperature (590 C), are compared with theoretically predicted data. The good agreement between experimental and theoretical results confirms the validity of the model applied to the CVT process of this system.

Wiedemeier, Heribert↗

Machine learning to discover mineral trapping signatures due to CO 2 injection

Mineral trapping is pursued as a geological CO 2 sequestration (GCS) mechanism because it permanently stores CO 2 in solid phases or minerals. However, CO 2 mineral-trapping mechanisms are poorly understood due to (1) lack of sufficient field and laboratory data characterizing these complex processes, and (2) challenges to develop site-specific reactive-transport models coupling fluid flow and geochemical reactions occurring at various temporal (from milliseconds to years) and spatial (from pore (millimeters) to field (kilometers)) scales. Reactive transport with additional complexities such as heterogeneity can make the simulation outputs even more difficult to interpret because of complex nonlinearity and multi-scale interdependencies. Furthermore, the values of model outputs such as concentrations can vary by several orders of magnitude, making it harder to correlate and characterize the impact of the variables via traditional data interpretation techniques such as exploratory data analyses. Recently, machine learning (ML) has shown promise in feature discovery and in highlighting hidden mechanisms that cannot be obtained by existing data-analytics and statistical methods. In this study, we applied an unsupervised ML approach, non-negative matrix factorization with custom -means clustering (NMF) to the data generated by reactive-transport simulations of GCS. The reactive-transport data consisted of 19 attributes, including four physio-chemical variables (pH, porosity, aqueous CO 2 , and sequestered CO 2 ), six chemical species (K + , Na + , HCO, Ca 2+ , Mg 2+ , Fe 2+ ), and four carbonate minerals (calcite, dolomite, siderite, and ankerite), a feldspar mineral (albite), and four clay minerals (illite, clinochlore, kaolinite, and smectite) over a period of 200 years of simulation time. Furthermore, the simulation data used was for Morrow B sandstone at the Farnsworth hydrocarbon unit in Texas. Data are sampled at two locations within the model domain: (1) at the injection well and (2) 200 m west of the injection well. The injection was performed for a period of 10 years. Using NMF, we estimated the temporal interdependencies among the 19 attributes over a span of 200 years. We found that NMF was able to identify four reaction stages and their dominant attributes; these cannot be directly discerned through traditional visualization (e.g., line plots, Pareto analysis, Glyph-based visualization methods) or exploratory data analysis tools of the simulation data. The four stages were: reactions in the injection phase followed by short-, mid-, and long-term reactions. The NMF analysis also revealed that 10 among the 19 attributes are dominant. These dominant attributes for mineral trapping include calcite, dolomite at injection well, siderite at 200 m away from the injection well, clinochlore, kaolinite, Na + , K + , Ca 2+ , Mg 2+ , pH, and aqeuous CO 2 . Finally, at late times (65–200 years), our results showed that calcite plays a major role in mineral trapping with insignificant contribution from siderite, ankerite, and clay minerals. These findings make the proposed unsupervised ML-model attractive for reactive-transport sensing towards real-time GCS monitoring.

54 ENVIRONMENTAL SCIENCES↗

LaPlace Transform1 Adaptive Control Law in Support of Large Flight Envelope Modeling Work

This paper presents results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented are in support of nonlinear aerodynamic modeling and instrumentation calibration.

Gregory, Irene M.↗

Evaluating Summer-Time Ozone Enhancement Events in the Southeast United States

This study evaluates source attribution of ozone (O3) in the southeast US within O3 lamina observed by the University of Alabama in Huntsville (UAH) Tropospheric Ozone Lidar Network (TOLNet) system during June 2013. This research applies surface-level and airborne in situ data and chemical transport model, GEOS-Chem, simulations in order to quantify the impact of North American anthropogenic emissions, wildfires, lightning NOx, and background stratospheric transport on the observed O3 lamina. During the summer of 2013, two anomalous O3 layers were observed and evaluated: 1) a nocturnal near-surface enhancement and 2) a late evening elevated (3-6 km above ground level) O3 plume. A "brute force" zeroing method was applied in GEOS-Chem to quantify the impact of individual emission sources and transport pathways on the vertical distribution of O3 during the two observed lamina. These model simulations suggest that the nocturnal O3 enhancement on June 12, 2013 below 3 km was primarily due to wildfire emissions and the fact that daily maximum anthropogenic emission contributions occurred during these night-time hours. During the second case study it was predicted that above average contributions from background stratospheric transport was largely contributing to the O3 lamina observed on June 29, 2013 between 3-6 km. Further evaluation suggested that a stratospheric intrusion was likely the main source contributing to this O3 enhancement between 3-6 km. Supporting information from other models, remote-sensing observations, and ground-based airborne in situ data agree with the source attribution predicted by GEOS-Chem simulations for both case studies. Overall, this study demonstrates the dynamic atmospheric chemistry occurring in the southeast US and displays the various emission sources and transport processes impacting O3 enhancements at different vertical levels of the troposphere.

Laminates↗

Evaluation of Modeled Vertical Distribution of Atmospheric SO2 and Sulfate in UTLS

We evaluated the vertical profiles of both SO2 and sulfate in the AEROCOM (Aerosol Model Intercomparison) Phase II participating models. SO2 and sulfate show significant concentration gradient in both horizontal and vertical directions. Both online and offline aerosol transport models show large difference in the vertical distribution of sulfur species from surface all the way up to lower stratosphere. Comparison with available aircraft measurements suggests models agree with observations well when SO2 concentration is high. For the volcanic plumes, the injection height and magnitude determines initial SO2 plume distribution and following transport pattern. At high altitude, where the background concentration of SO2 is often below the detection limit of the current aircraft instruments and satellite retrievals, modeled SO2 and sulfate concentration, lifetime, and budget, as well as their uncertainties can be difficult to be accurately quantified.

volcanic plumes↗

Quantification of the Impact of Acidified Brine on Fracture-Matrix Transport in a Naturally Fractured Shale Using in Situ Imaging and Modeling

Understanding flow, transport, chemical reactions, and hydromechanical processes in fractured geologic materials is key for optimizing a range of subsurface processes including carbon dioxide and hydrogen storage, unconventional energy resource extraction, and geothermal energy recovery. Flow and transport processes in naturally fractured shale rocks have been challenging to characterize due to experimental complexity and the multiscale nature of quantifying continuum scale descriptions of mass exchange between micrometer-scale fractures and nanometer-scale pores. In this study, we use positron emission tomography (PET) to image the transport of a conservative tracer in a naturally fractured Wolfcamp shale core before and after the core was exposed to low pH brine conditions. Image-based experimental observations are interpreted by fitting an analytical transport model to fracture-containing voxels in the core. Results of this analysis indicate subtle increases in matrix diffusivity and a slightly more uniform fracture velocity distribution following exposure to low pH conditions. These observations are compared with a multicomponent one-dimensional reactive transport model that indicates the capacity for a 10% increase in porosity at the fracture-matrix interface as a result of the low pH brine exposure. This porosity change is the result of the dissolution of carbonate minerals in the shale matrix to low pH conditions. Further, this image-based workflow represents a new approach for quantifying spatially resolved fracture-matrix transport processes and provides a foundation for future work to better understand the role of coupled transport, reaction, and mechanical processes in naturally fractured rocks.

58 GEOSCIENCES↗

Radiation and heat transport in divergent shock–bubble interactions

Shock–bubble interactions (SBIs) are important across a wide range of physical systems. In inertial confinement fusion, interactions between laser-driven shocks and micro-voids in both ablators and foam targets generate instabilities that are a major obstacle in achieving ignition. Experiments imaging the collapse of such voids at high energy densities (HED) are constrained by spatial and temporal resolution, making simulations a vital tool in understanding these systems. In this study, we benchmark several radiation and thermal transport models in the xRAGE hydrodynamic code against experimental images of a collapsing mesoscale void during the passage of a 300 GPa shock. We also quantitatively examine the role of transport physics in the evolution of the SBI. This allows us to understand the dynamics of the interaction at timescales shorter than experimental imaging framerates. We find that all radiation models examined reproduce empirical shock velocities within experimental error. Radiation transport is found to reduce shock pressures by providing an additional energy pathway in the ablation region, but this effect is small (∼1% of total shock pressure). Employing a flux-limited Spitzer model for heat conduction, we find that flux limiters between 0.03 and 0.10 produce agreement with experimental velocities, suggesting that the system is well-within the Spitzer regime. Higher heat conduction is found to lower temperatures in the ablated plasma and to prevent secondary shocks at the ablation front, resulting in weaker primary shocks. Finally, we confirm that the SBI-driven instabilities observed in the HED regime are baroclinically driven, as in the low energy case.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Data and Scripts associated with “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling.”

This data package is associated with the publication “Lambda-PFLOTRAN: Workflow for Incorporating Organic Matter Chemistry Informed by Ultra High Resolution Mass Spectrometry into Biogeochemical Modeling” submitted to Geoscientific Model Development (Muller et al., 2024). In this manuscript, organic matter chemistry and thermodynamics are directly connected to reactive transport simulators through the newly developed Lambda-PFLOTRAN (Parallel Reactive Flow and Transport model) workflow tool that succinctly incorporates organic matter chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate aerobic respiration of the organic matter and the resulting biogeochemistry. Lambda-PFLOTRAN is a python-based workflow, executed through a Jupyter Notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow, and transport code PFLOTRAN. This data package contains Jupyter Notebook based workflows for two test cases for running biogeochemical simulations of organic matter oxidation identified by FTICR-MS. It contains four primary folders (workflow, data, src, and analysis), a file-level metadata file (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_flmd.csv) that lists all the files contained in this data package with a short description of each, and a data dictionary (Muller_2024_Lambda_PFLOTRAN_Manuscript_Data_Package_dd.csv) file that describes the tabular column headers. The ‘workflow’ folder contains the Jupyter Notebook based workflows for running the lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘data’ folder contains the FTICR-MS data, initial conditions, and incubation data for test cases 1 and 2 in folders titled ‘WHONDRS’ and ‘Colloids’, respectively. The data folder also has a ‘Database’ folder containing a reaction network for bulk organic matter (assumed to be CH2O) and a general database for PFLOTRAN (hanford_rxn_network). The CH2O reaction network defines bulk organic matter oxidation. Biogeochemical simulations are completed for both the lambda binned organic matter and bulk organic matter reaction networks. The ‘hanford_rxn_network’ database includes information required for PFLTORAN simulations including ion size, molar mass, and charge of the aqueous species, gases, and minerals phases. The ‘src’ folder contains python source codes for performing lambda analysis, PFLOTRAN simulation, sensitivity analysis and parameter estimation. The ‘analysis’ folder contains outputs from the test cases 1 and 2 including lambda analysis, PFLOTRAN runs and the calibration results.

54 ENVIRONMENTAL SCIENCES↗

New Insights into Physical Aging-Induced Structure Evolution in Carbon Molecular Sieve Membranes

Carbon molecular sieve (CMS) membranes offer the best available combination of scalable economical processability with excellent separation performance. Physical aging of CMS membranes causes pore structure changes over time that affect CMS membrane performance. To provide fundamental insights into the structure evolution in CMS membranes during physical aging, a combined dual-mode sorption and transport model is used in this study to characterize the diffusion coefficients of gas molecules in fresh and 7-day vacuum aged CMS membranes. Further, the results show physical aging of CMS membrane is primarily “diffusion related” and such aging behavior simultaneously causes ultramicropore changes in the continuous phase and Langmuir phase of CMS membrane. The new insights offered in this study suggest strategies to control the physical aging of CMS membranes and even use it as a valuable tool to tune the separation performance of CMS membranes for demanding gas separations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Characterization factors and other air quality impact metrics: Case study for PM 2.5 -emitting area sources from biofuel feedstock supply

In this paper, we develop a framework and metrics for estimating the impact of emission sources on regulatory compliance and human health for applications in air quality planning and life cycle impact assessment (LCIA). Our framework is based on a pollutant's characterization factor (CF) and three new metrics: Available Regulatory Capacity for Incremental Emissions (ARCIE), Source CF Ratio, and Activity Health Impact (AHI) Ratio. ARCIE can be used to assess whether a receptor location has capacity to accommodate additional source emissions while complying with regulatory limits. We present CF as a midpoint indicator of health impacts per unit mass of emitted pollutant. Source CF Ratio enables comparison of potential new-source locations based on human health impacts. The AHI Ratio estimates the health impacts of a pollutant in relation to the utilization of the source for each unit of product or service. These metrics can be applied to any pollutant, energy source sector (e.g., agriculture, electricity), source type (point, line, area), and spatial modeling domain (nation, state, city, region). We demonstrate these metrics through a case study of fine particulate (PM 2.5 ) emissions from U.S. corn stover harvesting and local processing at various scales, representing steps in the biofuel production process. We model PM 2.5 formation in the atmosphere using a novel reduced-complexity chemical transport model called the Intervention Model for Air Pollution (InMAP). Through this case study, we present the first area-source PM 2.5 CFs that address the recommendations of several LCIA studies to establish spatially explicit CFs specific to an energy source sector or type. Overall, the framework developed in this work provides multiple new ways to consider the potential impacts of air emissions through spatially differentiated metrics.

09 BIOMASS FUELS↗

Oligoether-Functionalized PEDOT: Combining an EDOT Backbone with Polar Side Chains for Solution Processability and High Electrical Conductivity

Conjugated polymers functionalized with oligoether (OE)-based side chains are a key class of materials for various organic electronic applications, including transparent electrodes, thermoelectrics, electrochromic displays, and electrochemical transistors. Herein, we report a highly soluble OE-functionalized poly(3,4-ethylenedioxythiophene) (PEDOT) homopolymer, prepared by direct (hetero)arylation polymerization, which allows solution processing to yield films with comparable redox properties to oxidatively polymerized PEDOT. This polymer, PEDOT(OE3), when optimally oxidatively doped, reaches among the highest electrical conductivities of any OE-functionalized polymer and is comparable to more synthetically complex OE-functionalized polymers. X-ray scattering and spectroscopy were utilized to rationalize the transport properties resulting from varying the doping level. Comparison of PEDOT(OE3) to a series of OE-functionalized dioxythiophenes with varying amounts of 3,4-ethylenedioxythiophene units allows for a deeper understanding of structure–property relationships through charge-transport models. Ultimately, PEDOT(OE3) is shown to be a material with exceptional charge-transport properties and is promising for various applications.

36 MATERIALS SCIENCE↗

ExaCA grain structure predictions for laser powder bed fusion processing

This dataset contains simulated cross-sections of laser powder bed fusion grain structures produced using the microstructure model ExaCA, in turn using time-temperature history data produced using the heat transport model AdditiveFOAM. These predictions show the grain structure using various permutations of hatch spacing and nucleation density. Also contained in the dataset are the input files necessary to reproduce the results. AdditiveFOAM (https://github.com/ORNL/AdditiveFOAM) and ExaCA (https://github.com/LLNL/ExaCA), both open source software, are required to reproduce the results in this dataset using the given input files. This DOI was updated 12/09/2025.

36 MATERIALS SCIENCE↗

2004 Kansas City Regional Household Travel Survey

The 2004 Regional Household Travel Survey documented the travel behavior characteristics of Kansas City residents to update the area's transportation model. The Mid-America Regional Council and the Kansas and Missouri Departments of Transportation sponsored the survey, which was administered by NuStats. Activity and travel information was collected for all household members, regardless of age, during a specific 24-hour period. It relied on the willingness of households to provide demographic information about its members and vehicles and to have all household members record all travel and activity for a specific 24-hour period. The study also included a subsample of household vehicles with global positioning system (GPS) devices. The objectives of the GPS component were twofold: (1) to provide an independent data stream of vehicular travel in order to measure the accuracy of the travel data reported over the telephone, and (2) to obtain details about those trips that were captured by GPS but not reported over the telephone, in order to derive a trip-correction factor.

1Hz data↗

A Three-Dimensional CFD Investigation of Secondary Flow in an Accelerating, 90 deg Elbow

NASA Glenn Research Center has recently applied the WIND National Code flow solver to an accelerating elbow with a 90 deg. bend to reveal aspects of secondary flow. This elbow was designed by NACA in the early 1950's such that flow separation would be avoided. Experimental testing was also done at that time. The current three dimensional CFD investigation shows that separation has indeed been avoided. Using its three-dimensional capability, this investigation provides various viewpoints in several planes that display the inception, development, and final location of a passage vortex. Its shape first becomes discernible as a vortex near the exit of the bend. This rendition of the exit passage vortex compares well with that found in the experiments. The viewpoints show that the passage vortex settles on the suction surface at the exit about one-third of the distance between the plane wall and midspan. Furthermore, it projects into the mainstream to about one-third of the channel width. Of several turbulence models used in this investigation, the Spalart Alimaras, Baldwin Lomax, and SST (Shear Stress Transport) models were by far the most successful in matching the experiments.

Cavicchi, Richard H.↗