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Zonal-Based Emission Source Term Model for Predicting Particulate Emission Factors in Wildfire Simulations
A physics/chemistry-based numerical model for predicting the emission of fine particles from wildfires is proposed. This model implements the fundamental mechanisms of soot formation in a combustion environment: soot nucleation, surface growth, agglomeration, oxidation, and particle fragmentation. These mechanisms occur on a scale too fine for the discretization of most wildfire models, which need to simulate landscape-scale dynamics. As a result this model implements a zonal approach, where the computed soot particle distribution is partitioned into process zones within a single resolved grid cell. These process zones include: an inception zone (for nucleation), a heating zone (for coagulation, surface growth, and fragmentation), a reaction zone (for oxidation), and a quenched zone (for atmospheric processes). Governing mechanisms are applied to the appropriate zones to predict total particle growth and emission. Additionally, the proposed model is implemented into HIGRAD/FIRETEC, a physics-based wildfire simulation code which couples interactions between fire, fuels, atmosphere, and topography on a landscape scale. Fire simulations among grasslands and conifer forests are performed and compared against experimental data for emission factors.
Detailed hydrocarbon speciation and particulate matter emissions during cold-start from turbocharged and naturally aspirated trucks
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Dynamic Particulate Behavior in Turbulent Media
Presentation to be given on WebEx meeting February 16, Works in Progress seminar. There are 4 embedded videos in the presentation (slides 8, 13, and 19). After the 16th, presentation will be uploaded and available on the S&T website, https://insite.nv.doe.gov/Science%26Technology/SitePages/Work%20in%20Progress%20Seminars.aspx
Avoiding surface instability and slurry jamming in simultaneous multilayer coating of structured particulate films
Simultaneous multilayer coating techniques are widely known, but their industrial application remains limited to narrow market sectors. One barrier to adoption may be the mismatch between industries that are familiar with such processes but have no need, and industries that have need but are not familiar. Moreover, there are application-specific technical challenges to developing multilayer-coating processes. In this article, we describe our resolution of two specific issues in simultaneous multilayer coating of all aqueous highly loaded slurries for new and emerging energy applications. The first issue is particle jamming (associated with Shear-thickening) of the highly loaded slurries in the die internals, which we alleviated by adding small amounts of viscosity modifiers without reducing the solid loading. The second issue is a Marangoni-driven surface instability that resembles top layer de-wetting, which we solved by carefully selecting surfactants to tune the dynamic surface tensions of each slurry. Both issues were resolved early in a step-wise development, saving significant development cost which in our case was driven by expensive materials.
Iron speciation in particulate matter (PM2.5) from urban Los Angeles using spectro-microscopy methods
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Comparing the interactions between particulate matter and cloud properties over two populated cities in Texas using WRF-Chem fine-resolution modeling
Accurate modeling of aerosol-cloud interactions is essential for reliable weather and air quality simulations, given their significant impact on precipitation patterns, cloud dynamics, and aerosol distributions. This study employed the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to examine the impact of enhanced meteorological simulations, achieved through advanced microphysics parameterization supported by data assimilation techniques, on air quality across Texas on August 19 and 20, 2022. We tested four distinct configurations: (1) the Morrison two-moment bulk microphysics scheme, (2) Morrison's with observation nudging, (3) the Spectral Bin Microphysics (SBM), and (4) SBM with observation nudging. While the SBM scheme is known for its detailed representation of aerosol-cloud interactions, our focus was on how improvements in meteorological accuracy translate to more precise air quality simulations. Our findings demonstrated a progressive improvement in simulation accuracy, starting with the Morrison's scheme and further enhanced by adopting the SBM scheme, complemented by incorporating observation nudging. Specifically, the combination of the SBM scheme and the nudging substantially enhanced the model's ability to capture convective precipitation events, as shown by better alignment with NEXRAD radar reflectivity, with R increasing from –0.21 to 0.82, IOA from 0.10 to 0.87, and NMB decreasing from 99% to 34% in Houston. The enhanced meteorology translated into more accurate PM 2.5 concentration simulations, particularly through the more accurate representation of aerosol washout during precipitation events. In Houston, the SBM scheme with nudging improved the model's PM 2.5 simulations significantly, with NMB decreasing from –20% to 5% and IOA improving from 0.43 to 0.61. In San Antonio, improvements were also notable, with NMB improved from –27% to –22%, R increased from 0.48 to 0.82, and IOA increased from 0.66 to 0.86. Furthermore, our results underscore the crucial role of accurate meteorological simulations in refining our understanding of aerosol behaviors in relation to precipitation patterns, directly enhancing the reliability and effectiveness of air quality modeling.
Critical analysis of velocimetry methods for particulate flows from synthetic data
Particle tracking methods that extract high-fidelity particle velocity data from high speed video of particle laden flows is a common experimental technique applied to chemical processes. These measurements are used to better understand the motion of particles and fluids in complex systems and create data against which computational models are validated. However, the methods, codes, and experimental setups all have limitations. It is imperative that practitioners verify the methods and their implementation as well as understand the limitations of experimental setups. This work focuses on quantifying the visible depth of field in a high particle concentration fluidized bed. Following a precedent set by the particle imaging velocimetry community, a particle velocity field is manufactured using a computational fluid dynamics and discrete element method simulation. Photo realistic high-speed videos are rendered based on the simulated data using the three-dimensional creation software Blender. Particle velocities are extracted from the synthetic high-speed videos using three variants of Particle Tracking Velocimetry and Optical Flow Velocimetry methodologies. Here, the tracked results are then compared to the known solution, quantifying the error associated with the assumed visible depth. The results indicate that at depth of one particle diameter, all three particle tracking codes give accurate measurements, largely within 5%. However, the error increases when the full bed video measurements are compared to the known solution at one particle diameter, i.e., mimicking a validation study. Finally, for some statistics the constant depth assumption only increases the error slightly, for others significantly.
Automated correction for the movement of suspended particulate in microtomographic data
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A multi-modal approach to measuring particulate iron speciation in buoyant hydrothermal plumes
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Sectioned processing of compaction self-assembly of an ultralow-binder-content particulate composite
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Spark knock: A source for particulate matter emissions from gasoline spark ignited engines
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Review of technologies for preventing secondary transport of soluble and particulate radiological contamination from roadways, roadside vegetation, and adjacent soils
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