Search NASA⌕ Search

SEARCH · Search NASA

Results for “Aerosol Development”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Technical Assistance for RingIR Aerosol Penetration Study with RingIR

Sandia provided technical assistance to RingIR to test and evaluate of the RingIR molecular detector. The detector can identify gas phase species using molecular fingerprinting and has potential application for SARS-CoV-2 detection in near real time. As part of the development process Sandia will utilize the biological aerosol test bed deployed at the Aerosol Complex to evaluate the penetration of MS2 bacteriophage aerosol through the RingIR system. The objective of this project is to provide experimentally derived measurements of the RingIR molecular detector penetration efficiency, including external exhaust filter for mitigation of exhaust aerosol and operation using MS2 bacteriophage as a biological surrogate to the SARS-CoV-2 virus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Developing and testing capabilities for simulating cases with heterogeneous land/water surfaces in a novel atmospheric large eddy simulation code

Large eddy simulations (LES) are the primary computational tool used to simulate high Reynolds number three-dimensional turbulent flows. In the context of earth system sciences, particularly atmospheric science, LES are uniquely able to resolve the scales of atmospheric motion that are key for building process-level understanding of boundary layer turbulence, atmosphere-surface interaction, clouds, and cloud-aerosol-chemistry interaction, and are a core limited-area modeling capability. Increasing demands are being placed on LES code bases as growing high performance computing resources allow LES to address a wider range of scientific problems. In addition, LES are emerging as a source of high-quality machine learning training data. These demands necessitate an agile and extensible code base that allows the model to quickly adapt to emergent needs. However, LES have largely relied on legacy Fortran code bases that lack flexibility. A new, Python-based LES capability called Predicting INteractions of Aerosol and Clouds in Large Eddy Simulation (PINACLES) has been developed as part of the Department of Energy’s Earth System Model Development (ESMD) program area’s Enabling Aerosol-cloud interactions at Global convection-permitting scalES (EAGLES) project. PINACLES was developed from the ground up with a philosophy of maximizing scientific throughput, by attempting to optimize for both model throughput and software extensibility. The initial development of PINACLES delivered a state-of-the-art idealized LES capability solving the non-hydrostatic anelastic equations of motion with doubly periodic boundary conditions and idealized homogenous surface boundary conditions. Here we provide a final report on the outcomes of a fiscal year 2021 Seed Laboratory Directed Research Project that extended PINACLES in two key ways. First, PINACLES was coupled to a state-of-the-art land surface model enabling it to simulate spatially inhomogeneous land-atmosphere interactions that are known to control key atmospheric processes. Second, the dynamical core of PINACLES was modified to permit non-periodic boundary conditions. This model enhancement enables simulation of realistic cases with boundary conditions prescribed from atmospheric reanalysis and enables nested simulations conducted on a hierarchy of computational domains with increasing resolution. Together, these extensions to PINACLES make it a formidable modeling capability and expand its potential application to diverse components of DOE’s atmospheric science portfolio.

42 ENGINEERING↗
DOE OSTI2022

Mitigation of Alkali Induced Aerosols

Barr, in partnership with the University of North Dakota, Microbeam Technologies Inc., Envergex LLC, and MLJ Consulting, worked to develop a transformational technology that controls the formation of alkali aerosols found in coal ash. This technology mitigates ash deposition by injecting sorbents into the boiler and capturing volatile species responsible for boiler fouling, the primary cause for boiler outages. In this session, we’ll explore the science behind this technology and see some real-world results of its implementation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

#COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol

We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus obscure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Cloud Condensation Nuclei Hygroscopicity Value-Added Product Report

The purpose of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Cloud Condensation Nuclei Hygroscopicity Parameter (AOSCCNSMPSKAPPA and AOSCCNUHSASKAPPA) Value-Added Product (VAP) is to calculate the hygroscopicity parameter, kappa, to quantify the ability of aerosols to activate into cloud water droplets. The hygroscopicity parameter is often used to model the cloud condensation nuclei (CCN) activity of atmospheric aerosols of different sizes and compositions, providing additional insight on the influence of aerosols on climate. The AOSCCNUHSASKAPPA VAP was recently developed to provides kappa data for ARM sites where AOSCCNSMPSKAPPA was missing. Laboratory experiments show that the kappa values for highly hygroscopic aerosols vary from 0.5 to 1.4 (Petters and Kreidenweis 2007). For organic compounds they are observed to vary between 0.01 and 0.5. For non-hygroscopic aerosols, such as soot, kappa values are very close to zero. Ambient aerosols are complex mixtures of organic and inorganic compounds and previous observations indicate that kappa values for these aerosols typically vary from 0.05 to 0.9 (Petters and Kreidenweis 2007).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

pnnl/NEURALMIE

NeuralMie was developed to improve the representation of aerosol optical properties in E3SM, the DOE's Earth system model. NeuralMie is able to closely emulate numerical solutions to the problem at a fraction of the computational cost. TAMie was written to generate training data for NeuralMie.

Geiss, Andrew↗
DOE OSTI2024

Two-Step Hyperparameter Optimization Method: Accelerating Hyperparameter Search by Using a Fraction of a Training Dataset

Abstract Hyperparameter optimization (HPO) is an important step in machine learning (ML) model development, but common practices are archaic—primarily relying on manual or grid searches. This is partly because adopting advanced HPO algorithms introduces added complexity to the workflow, leading to longer computation times. This poses a notable challenge to ML applications, as suboptimal hyperparameter selections curtail the potential of ML model performance, ultimately obstructing the full exploitation of ML techniques. In this article, we present a two-step HPO method as a strategic solution to curbing computational demands and wait times, gleaned from practical experiences in applied ML parameterization work. The initial phase involves a preliminary evaluation of hyperparameters on a small subset of the training dataset, followed by a reevaluation of the top-performing candidate models postretraining with the entire training dataset. This two-step HPO method is universally applicable across HPO search algorithms, and we argue it has attractive efficiency gains. As a case study, we present our recent application of the two-step HPO method to the development of neural network emulators for aerosol activation. Although our primary use case is a data-rich limit with many millions of samples, we also find that using up to 0.0025% of the data—a few thousand samples—in the initial step is sufficient to find optimal hyperparameter configurations from much more extensive sampling, achieving up to 135× speedup. The benefits of this method materialize through an assessment of hyperparameters and model performance, revealing the minimal model complexity required to achieve the best performance. The assortment of top-performing models harvested from the HPO process allows us to choose a high-performing model with a low inference cost for efficient use in global climate models (GCMs).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data

The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite developed by the European Space Agency (ESA) and the Japan Aerospace Exploration Agency (JAXA) launched in May 2024 carries a novel 94 GHz cloud profiling radar (CPR) with Doppler capability. This work describes the open-source instrument simulator Orbital-Radar, which transforms high-resolution radar data from field observations or forward simulations of numerical models to CPR primary measurements and uncertainties. The transformation accounts for sampling geometry and surface effects. We demonstrate Orbital-Radar's ability to provide realistic CPR views of typical cloud and precipitation scenes. The presented case studies show small-scale convection, marine stratus clouds, and Arctic mixed-phase cloud cases. These results provide valuable insights into the capabilities and challenges of the EarthCARE CPR mission and its advantages over the CloudSat CPR. Finally, Orbital-Radar allows for evaluating kilometre-scale numerical weather prediction models with EarthCARE CPR observations. So, Orbital-Radar can generate calibration and validation (Cal/Val) data sets already pre-launch. Nevertheless, an evaluation of synthetic CPR output data to accurate EarthCARE CPR data is missing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Filtration Performance Results: Sierra Peaks Material No. 4

Sandia National Laboratories (SNL) assessed the filtration performance of materials from Sierra Peaks to identify alternatives which may perform similarly to materials used in FDA-approved N95 respirators. This work is meant to characterize the aerosol performance of materials to give Sierra Peaks information for them to determine if they elect to submit masks made using these materials for follow-on N95 certification testing at an accredited facility. The R&D testbed used is a large-scale filtration system designed to test commercial filter boxes. System modifications were performed to simulate, where possible, parameters defined by the National Institute for Occupational Safety and Health (NIOSH) for certification of filter materials for N95 respirators (NIOSH 2019). The system is a pull-through design. Air enters through a Laminar Flow Element (LFE) and the volumetric flow is measured based on the pressure drop across the LFE. Pressure is measured via a Pressure Transducer (PT). The air then passes through a High Efficiency Particulate Air (HEPA) filter to purge the air of ambient airborne particulates. Test aerosol is injected into the flow shortly after and mixing is induced via a coarse mesh. The airflow is allowed to fully develop prior to arriving at the test section. The aerosol then passes through the test material mounted in a box in the test section. Pressure drop across the test article is measured and aerosol sampling probes measure the aerosol concentrations upstream and downstream of the sample. The air passes through a second HEPA filter prior to being exhausted to ambient by a blower. A Topas aerosol generator is used to produce the test aerosol from Sodium Chloride (NaC1) dissolved in deionized (DI) water. Generated aerosol passes through a heated mixing chamber and a desiccant dryer to produce nanosized solid-state particulates. A dilution loop allows for the aerosol concentration to be regulated. The aerosol sampling probes upstream and downstream of the test section are aligned with the flow path. These are ducted directly to the aerosol sizing and counting instruments. A Laser Aerosol Spectrometer (LAS) was used for data collection in the original configuration of the system and was also used for initial testing in this project. Because the lower measurement range for the LAS is 90 nanometers (nm), the LAS was switched out for a more complicated Scanning Mobility Particle Sizer (SMPS) spectrometer system. The SMPS is comprised of an Electrostatic Classifier (EC), Differential Mobility Analyzer (DMA), and a Condensation Particle Counter (CPC). This enabled data collection at 75 nm, the particle size called out in the NIOSH guidelines.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Industrial emission inventories of iron and phosphorus for past, present and future

Global emission inventories of aerosol iron by species, and of phosphorus, were developed for inclusion in Earth system modeling that includes atmospheric transport. The time period covered was 1850-2010 to evaluate human influence. A variety of approaches to compare measured and modeled values of aerosol iron was synthesized to estimate how well anthropogenic emissions are known. Anthropogenic emissions are constrained within a factor of two and if there is a bias, it is an overestimation. The exception is shipping emissions, which may be underestimated. Direct radiative forcing by iron aerosol is small in the global average (0.02 W m -2 ) but reaches 0.25 W m -2 around source regions. Regions of high direct radiative forcing are poorly constrained by observations. The central value of change in oceanic net primary productivity due to iron deposition is about 0.26 PgC yr -1 , also highly localized. This leads to a decrease in atmospheric CO2 accumulation that corresponds to a forcing of 0.008 W m -2 since 1850 (0.003-0.18 W m -2 ). Emissions of particulate matter to 2050 were estimated in response to different policy scenarios, including the need for renewable energy installations under decarbonization scenarios. Under the business-as-usual scenario, the total metal demand is 195 Mt/yr in 2020, peaking at 270 Mt/yr in years 2040-2045; under the Rapid Decarbonization scenario, total metal demand is nearly doubled at its peak: 480 Mt/yr in year 2040. Primary particulate matter emissions attributable to processing metals for renewable energy are also amplified under rapid decarbonization, but total atmospheric emissions are much lower because of the shift away from combustion.

58 GEOSCIENCES↗
DOE OSTI2024

Using MARCUS, MICRE, and COMBLE data to improve understanding and modeling of cloud, aerosol, and boundary layer processes at high-latitudes

Because it is believed general circulation (GCM) and numerical weather prediction (NWP) models underestimate shortwave radiation over the Southern Ocean (SO) due to inadequate representations of boundary layer (BL) and cloud processes, it is critical to improve our understanding of key aerosol, cloud, precipitation, and BL processes. Over the north Atlantic Ocean (NA), cold-air outbreaks are common, yet few studies of the aerosol and environmental controls of the associated convective BL clouds exist as needed to develop and evaluate GCM representations. Although processes cannot be observed, cloud and aerosol properties can be measured in-situ or remotely retrieved, which when combined with numerical simulations enable process level understanding required to improve model representations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Invisible ship tracks show large cloud sensitivity to aerosol

Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses. Increased aerosol concentrations due to human activity affect droplet number concentration, liquid water and cloud fraction, but these changes are subject to large uncertainties. Ship tracks, long lines of polluted clouds that are visible in satellite images, are one of the main tools for quantifying aerosol–cloud interactions. However, only a small fraction of the clouds polluted by shipping show ship tracks. Here we show that even when no ship tracks are visible in satellite images, aerosol emissions change cloud properties substantially. We develop a new method to quantify the effect of shipping on all clouds, showing a cloud droplet number increase and a more positive liquid water response when there are no visible tracks. We directly detect shipping-induced cloud property changes in the trade cumulus regions of the Atlantic, which are known to display almost no visible tracks. Our results indicate that previous studies of ship tracks were suffering from selection biases by focusing only on visible tracks from satellite imagery. The strong liquid water path response we find translates to a larger aerosol cooling effect on the climate, potentially masking a higher climate sensitivity than observed temperature trends would otherwise suggest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Implementing a Stochastic Soot Model in a 3D Domain

In this document a highly detailed stochastic soot model limited to 0D simulations is coupled to 3D domains through the use of a Lagrangian parcel-Eulerian fluid method. Although both the stochastic soot model used and the Lagrangian parcel-Eulerian fluid method have long histories of development, their use, as described in this document, is novel and useful. Previous works significant to the model's development include documents from both the stochastic and simpler soot model genre and the fuel, aerosol, and other particle tracking and Lagrangian parcel-Eulerian fluid genres. Developing the theory behind the model is crucial to its implementation because of the unconventional Lagrangian parcel-Eulerian fluid representation. In fact, the Lagrangian parcel-Eulerian fluid coupling is only a means of simplifying the much more difficult theoretical model. Despite the accompanying assumptions, the complete model is validated from the bottom up and then again in a holistic fashion with promising results. Then the model is used in multiple case studies, showcasing capabilities not had by other models. The optical properties of soot generated in a Spray A simulation are calculated to find measured results are likely overpredicting the mass of soot along the central axis via KL extinction measurements. A thermophoresis submodel that calculates force based on the soot particles' shape is installed to find it has a high influence on the path of the heaviest soot particles. Investigations into the HACA mechanism for soot growth and the effect of syngas on soot in 3D domains are performed with much more detail than has been available before.

Strickland, Tyler↗
DOE OSTI2022

Update on Mitigation of Aerosol Impacts on Ash Deposition and Emission from Coal Combustion

Barr, in partnership with the University of North Dakota, Microbeam Technologies Inc., Envergex LLC, and MLJ Consulting, worked to develop a transformational technology that controls the formation of alkali aerosols found in coal ash. This technology mitigates ash deposition by injecting sorbents into the boiler and capturing volatile species responsible for boiler fouling, the primary cause for boiler outages. In this session, we’ll explore the science behind this technology and see some real-world results of its implementation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2022

EASTERN NORTH ATLANTIC (ENA) CONDENSATION PARTICLE COUNTER (CPC) with the AEROSOL MASK (ENA-AM) for the YEAR 2017

The Eastern North Atlantic (ENA) central facility is periodically affected by episodes of local aerosols. High-concentration aerosol events associated with potential local aerosol sources are sampled by the Concentration Particle Counter (CPC) and can be observed in the high-time-resolution data. In an effort to remove aerosol data that is not regionally representative from the CPC data, an aerosol mask (ENA-AM) has been previously developed and validated during the ACE-ENA campaing (Gallo et al., 2020). The ENA-AM is a standard deviation algorithm based on the statistically different behavior of adjacent data points used to determine periods when the measurements are impacted by local aerosols. This file contain one-minute time resolution submicron aerosol particle concentration datasets from the CPC for the year 2017, and the corresponding ENA-AM datasets to remove datapoints affected by local aerosol sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

EASTERN NORTH ATLANTIC (ENA) CONDENSATION PARTICLE COUNTER (CPC) with the AEROSOL MASK (ENA-AM) for the YEAR 2018

The Eastern North Atlantic (ENA) central facility is periodically affected by episodes of local aerosols. High-concentration aerosol events associated with potential local aerosol sources are sampled by the Concentration Particle Counter (CPC) and can be observed in the high-time-resolution data. In an effort to remove aerosol data that is not regionally representative from the CPC data, an aerosol mask (ENA-AM) has been previously developed and validated during the ACE-ENA campaing (Gallo et al., 2020). The ENA-AM is a standard deviation algorithm based on the statistically different behavior of adjacent data points used to determine periods when the measurements are impacted by local aerosols. This file contain one-minute time resolution submicron aerosol particle concentration datasets from the CPC for the year 2018, and the corresponding ENA-AM datasets to remove datapoints affected by local aerosol sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

EASTERN NORTH ATLANTIC (ENA) CONDENSATION PARTICLE COUNTER (CPC) with the AEROSOL MASK (ENA-AM) for the YEAR 2016

The Eastern North Atlantic (ENA) central facility is periodically affected by episodes of local aerosols. High-concentration aerosol events associated with potential local aerosol sources are sampled by the concentration particle counter (CPC) and can be observed in the high-time-resolution data. In an effort to remove aerosol data that is not regionally representative from the CPC data, an aerosol mask (ENA-AM) has been previously developed and validated during the ACE-ENA campaign (Gallo et al. 2020). The ENA-AM is a standard deviation algorithm based on the statistically different behavior of adjacent data points used to determine periods when the measurements are impacted by local aerosols. This file contains one-minute-time-resolution submicron aerosol particle concentration data sets from the CPC for the year 2016, and the corresponding ENA-AM data sets to remove data points affected by local aerosol sources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Modeling Flow and Particle Deposition in a Spent Nuclear Fuel Assembly

CFD (Computational Fluid Dynamic) simulation of aerosol-laden natural convective flow and particle deposition in a spent fuel storage canister with 37 assemblies is currently computationally prohibitive. PWR (Pressurized Water Reactor) assemblies have up to 289 pins or tubes with several spacer grids to align the pins. Spacer grids with mixing vanes induce swirling during operation to increase heat transfer. Each spacer grid contains hundreds of small structures such as retaining clips, channel walls, and openings. The largest canisters store 37 PWR assemblies thus, there are numerous pins, tubes, and spacer grids for which the flow region between and around these structures needs to be determined along with the movement and deposition of aerosol particles. Because of the complicated geometry, modeling the intricate flow even for just one assembly is currently impractical. Nonetheless, we are developing techniques for a practical model to assess the natural aerosol particle deposition process in a canister in the event that a release occurs from one or more fuel pins. In the previous work it was demonstrated that CFD can model the flow through a PWR spacer grid with mixing vanes, including particle deposition, in a reasonable amount of time on a personal computer. In this work, the analysis is extended to include the bypass region between an assembly and the canister basket walls. It is shown that the flow velocity in the bypass region is about three times that of the interstitial region between the pins. The lengths before and after the spacer grid are also extended to determine when the flow becomes fully developed. In addition, the approach of computationally “stitching together” segments of an assembly is demonstrated with the plan to ultimately model a full assembly. The fraction of particles that are deposited in a segment with a spacer grid is determined as a function of particle size and flow velocity.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗