Particle deposition model for a fully developed turbulent channel flow
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Deposition models were built to evaluate contaminant deposition on spent nuclear fuel (SNF) canisters. The primary contaminant of concern is chloride, which is dispersed in the atmosphere and then deposits onto the canisters. During dry storage, the primary degradation process is likely to be Chloride Induced Stress Corrosion Cracking (CISCC) at the heat-affected zones of the canister welds. It is known that stainless steel canisters are susceptible to CISCC; however, the rate of chloride deposition onto the canisters is poorly known, based on sparse field data from a small number of sites. The models presented in this study could be useful for determining the rate of deposition on the canisters and the likelihood of CISCC to help with SNF canister ageing management. The deposition models were developed with the commercial computational fluid dynamics (CFD) code STAR-CCM+. Various deposition mechanisms were considered and incorporated into the models, and a sensitivity study was conducted to determine the most important mechanisms for deposition within a SNF storage system. The models included both a vertical and horizontal configuration storage system: NAC International’s Modular, Advanced Generation, Nuclear All-purpose STORage System (MAGNASTOR®) and a NUHOMS® horizontal storage module respectively. The resulting canister deposition on the horizontal canister is visually compared with inspection data taken onsite at the Calvert Cliffs Nuclear Power Plant. These models are preliminary, and development of the models will continue. Future validation exercises are currently being planned, including the Canister Deposition Field Demonstration (CDFD) effort funded by U.S. Department of Energy office of Nuclear Energy office of Spent Fuel Waste Science and Technology. The goal of the modeling presented is to demonstrate a potential modeling technique that could be used to plan and inform SNF canister ageing management programs with predictive models for the timing and occurrence of canister CISCC.
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This 4-page summary will be submitted to the American Nuclear Society (ANS) Annual Meeting 2024. The submission deadline is Feb-2. We really hope to get the summary reviewed and approved for submission.
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The structure and resulting physical properties of aerosol deposited particulate films are governed by the size distribution and morphology of the depositing particles as well as the physics governing particle deposition. While particulate film deposition processes are qualitatively understood, the link between particle characteristics and deposition physics to film properties has not been probed systematically. Here we apply a combination of Langevin dynamics deposition simulations, Monte Carlo pore size distribution calculations, and predictions of thermal conductivities to better establish such process parameter-film property relationships. Furthermore, we account for partial coalescence, polydispersity, and aggregate deposition. We establish that the deposition of polydisperse and aggregated particles leads to broadening of the pore size distribution function and an increase in the mode pore size. Via a non-continuum gas conductivity model, we show that aerosol deposited films can achieve porosities and thermal conductivities similar to conventional aerogels.
The methodology to predict deposit evolution (deposition rate and subsequent flow of liquid deposits) as a function of fuel and air impurity content and relevant aerodynamic parameters for turbine airfoils is developed in this research. The spectrum of deposition conditions encountered in gas turbine operations includes the mechanisms of vapor deposition, small particle deposition with thermophoresis, and larger particle deposition with inertial effects. The focus is on using a simplified version of the comprehensive multicomponent vapor diffusion formalism to make deposition predictions for: (1) simple geometry collectors; and (2) gas turbine blade shapes, including both developing laminar and turbulent boundary layers. For the gas turbine blade the insights developed in previous programs are being combined with heat and mass transfer coefficient calculations using the STAN 5 boundary layer code to predict vapor deposition rates and corresponding liquid layer thicknesses on turbine blades. A computer program is being written which utilizes the local values of the calculated deposition rate and skin friction to calculate the increment in liquid condensate layer growth along a collector surface.
Dry deposition removes short-lived climate forcers and their precursors from the atmosphere. The aerosol dry deposition schemes in many global climate models have been untouched for decades. Previous work hints that aerosol dry deposition is an uncertainty with respect to aerosol impacts on climate change. Here we demonstrate the impact of a more mechanistic aerosol dry deposition parameterization on the historical aerosol direct and cloud albedo effects using the NASA GISS global chemistry-climate model. We investigate two aerosol configurations – a “bulk” mass-based scheme and a modal scheme that more explicitly represents internal mixing and microphysics – of the global model. Both configurations show ~20% larger historical increases in non-dust aerosols globally with more mechanistic dry deposition. Changes to particle dry deposition, which are strongly a function of particle diameter, have a greater influence on the cloud albedo effect (up to 0.1 W m-2) when aerosols are more explicitly resolved in the modal scheme. On the other hand, impacts on the direct aerosol effect are small for both model configurations. In both aerosol configurations, the global climate effects are relatively insensitive to uncertainty in the strength of the uptake to dry deposition as suggested by (limited) measurements. In general, the low number of aerosol flux measurements and strong variability across existing observations challenge confidence in our understanding of dry depositional processes and changes with environmental conditions. Nonetheless, our work suggests that changes in dry deposition may be important for accurately estimating increases in aerosol abundances over the historical period, which is key for correct inferences about how cooling from aerosols has offset warming from greenhouse gases.
Wet and dry deposition remove aerosols from the atmosphere, and these processes control aerosol lifetime and thus impact climate and air quality. Dry deposition is a significant source of aerosol uncertainty in global chemical transport and climate models. Dry deposition parameterizations in most global models were developed when few particle deposition measurements were available. However, new measurement techniques have enabled more size-resolved particle flux observations. We combined literature measurements with data that we collected over a grassland in Oklahoma and a pine forest in Colorado to develop a dry deposition parameterization. We find that relative to observations, previous parameterizations overestimated deposition of the accumulation and Aitken mode particles, and underestimated in the coarse mode. These systematic differences in observed and modeled accumulation mode particle deposition velocities are as large as an order of magnitude over terrestrial ecosystems. As accumulation mode particles form most of the cloud condensation nuclei (CCN) that influence the indirect radiative effect, this model-measurement discrepancy in dry deposition alters modeled CCN and radiative forcing. We present a revised observationally driven parameterization for regional and global aerosol models. Using this revised dry deposition scheme in the Goddard Earth Observing System (GEOS)-Chem chemical transport model, we find that global surface accumulation-mode number concentrations increase by 62% and enhance the global combined anthropogenic and natural aerosol indirect effect by −0.63 W m −2 . Our observationally constrained approach should reduce the uncertainty of particle dry deposition in global chemical transport models.
Dry deposition (DD) is a primary removal pathway of particulate matter (PM). The aerosol DD schemes in most global models do not reflect current mechanistic understanding gleaned from observations. The NASA GISS global chemistry-climate model has a new and more dynamic DD scheme that largely captures observed changes in deposition velocities with particle size. We quantify the response of simulated PM to changes in the DD scheme for the Northeast US, Central Europe, North China Plain, and Punjab. Relative to the widely used old scheme, the new scheme shows higher annual PM2.5 for all regions (up to +14%) except C. Europe where there are very small decreases. For PM1, annual increases occur over all regions (up to +20%). For PM10, there are decreases in C. Europe (-8%) and very small decreases in the NE US yet increases (up to +12%) in Punjab and N. China Plain. While there are always increases across seasons for Punjab and N. China Plain, there are both seasonal increases and decreases for the NE US and C. Europe. Given incomplete understanding of observed variations in deposition velocities for a given particle size, we perform sensitivity simulations that perturb the magnitude of the deposition velocities simulated by the new scheme. The annual PM response to increasing DD is similar in magnitude to decreasing DD, implying linearity in the PM sensitivity to DD. The relative annual response to perturbing the DD magnitude is weaker over Punjab and sometimes N. China Plain than the NE US and C. Europe. Higher PM over Punjab and N. China Plain implies a stronger sensitivity to DD when aerosol abundances are low. More mechanistic representation of aerosol DD can sometimes improve or worsen existing model PM biases, which suggests that PM biases due to other processes can be confounded or compounded by biases in DD. Further improvements to DD parameterizations require not only more observational constraints on aerosol deposition velocities but also an advanced understanding of the processes controlling observed variability.
Dry deposition of atmospheric aerosols in large-scale models is a critical, but highly uncertain, sink process with a strong dependence on particle size, meteorological conditions, and land surface properties. This study investigates the particle dry deposition scheme implemented in the standard Community Multiscale Air Quality (CMAQ) model v5.2.1, characterizes its underlying parameterized components with comparison to a similar scheme in a contemporary regional-scale model, and proposes two updated schemes that are then evaluated with available ambient particle deposition velocity (V d ) measurements. Both updated schemes reduce the surprisingly strong dependence of deposition velocity on the aerosol mode width, with one scheme further introducing a dependence on vegetation coverage that is broadly consistent with variability in observations between vegetated and non-vegetated surfaces. Compared to the base scheme, the updated scheme with vegetation dependence increases V d for submicron particles and decreases it for larger particles by an average of 37% and –66%, respectively. This scheme performs statistically better than the base scheme, reducing fractional biases by 56%–97% for vegetated land-use types and has roughly equivalent performance over water. The base and updated schemes are tested with three annual CMAQ (v5.2.1) simulations for the year 2011; predicted ambient aerosol concentrations are evaluated with routine monitoring network observations and predicted dry deposition fluxes are evaluated with data from the Clean Air Status and Trends Network (CASTNET). The updated scheme with vegetation dependence reduces negative fractional biases for PM 10 by 41% and positive fractional biases for PM 2.5 organic carbon by 15%. This scheme has been incorporated into the most recent publicly accessible versions of CMAQ (v5.3 and beyond) to replace the scheme used in previous versions of CMAQ (v4.5 through v5.2.1).
Our interdisciplinary background and fundamentally-oriented studies of the laws governing multi-component chemical vapor deposition (VD), particle deposition (PD), and their interactions, put the Yale University HTCRE Laboratory in a unique position to significantly advance the 'state-of-the-art' of chemical vapor deposition (CVD) R&D. With NASA-Lewis RC financial support, we initiated a program in March of 1988 that has led to the advances described in this report (Section 2) in predicting chemical vapor transport in high temperature systems relevant to the fabrication of refractory ceramic coatings for turbine engine components. This Final Report covers our principal results and activities for the total NASA grant of $190,000. over the 4.67 year period: 1 March 1988-1 November 1992. Since our methods and the technical details are contained in the publications listed (9 Abstracts are given as Appendices) our emphasis here is on broad conclusions/implications and administrative data, including personnel, talks, interactions with industry, and some known applications of our work.
A parameterization scheme for the dry deposition of aerosol particles for use in tracer transport models is presented. Expressions of the particle deposition velocities relative to the bottom transport model level are derived for smooth surfaces, surfaces with bluff roughness elements, ocean surfaces, and vegetative canopies. The scheme is applied to a general circulation model to calculate the deposition velocities of ambient tropospheric aerosols. The calculated deposition velocities show a strong dependence upon the wind field in the bottom model level, the particle size distribution, and the surface type.
The charged particle observations proposed for the new low altitude weather satellites, TIROS-N, are described that will provide the capability of routine monitoring of the instantaneous total energy deposition into the upper atmosphere by the precipitation of charged particles from higher altitudes. Estimates are given to assess the potential importance of this type of energy deposition. Discussion and examples are presented illustrating the importance in distinguishing between solar and geomagnetic activity as possible causative sources.
Microbiological sampling methods presently used for enumeration of microorganisms on spacecraft surfaces require contact with easily damaged components. Estimation of viable particles on surfaces using air sampling methods in conjunction with a mathematical model would be desirable. Parameters necessary for the mathematical model are the effect of angled surfaces on viable particle collection and the number of viable cells per viable particle. Deposition of viable particles on angled surfaces closely followed a cosine function, and the number of viable cells per viable particle was consistent with a Poisson distribution. Other parameters considered by the mathematical model included deposition rate and fractional removal per unit time. A close nonlinear correlation between volumetric air sampling and airborne fallout on surfaces was established with all fallout data points falling within the 95% confidence limits as determined by the mathematical model.
The evaluation of aerosol exposure relies on generic mathematical models that assume uniform particle deposition profiles over the human respiratory tract and do not account for subject-specific characteristics. Here we introduce a hybrid-automated computational workflow that generates personalized particle deposition profiles in 3D reconstructed human airways from computed tomography scans using Computational Fluid and Particle Dynamics simulations. This is the first large-scale study to consider realistic airways variability, where 380 lower and 40 upper human respiratory tract 3D geometries are reconstructed and parameterized. The data is clustered into nine groups using random forest regression. Computational fluid and particle dynamics simulations are conducted on these representative geometries using a realistic heavy-breathing respiratory cycle and radioactive iodine-131 as a source term. Monte Carlo radiation transport simulations are performed to obtain detailed energy deposition maps. Our findings emphasize the importance of personalized studies, as minor respiratory tract variations notably influence deposition patterns rather than global parameters of the lower airways, observing more than 30% variance in the mass deposition fraction.
The Surface Eroding Thermocouple (SETC) is a robust diagnostic utilized in DIII-D to provide fast, edge-localized modes (ELMs) resolved heat flux measurements, in particular in geometric regions that are too shadowed for traditional infrared thermography. In order to further investigate the power dissipation in the divertor region, a combination of flush-mounted and recessed SETCs was developed to assess the effect on surface heating from non-charged particles at the divertor target. Utilizing the Divertor Materials Evaluation System sample exposure platform, the first demonstration of the feasibility of using this new method to distinguish between the heat flux from charged particles and that from neutrals and radiative heating was achieved. This paper details the process of using the combination of flush SETCs and recessed SETCs to measure the multiple heat flux components at the divertor target and further discusses how to determine two important ratios, α (ratio of heat flux from charged particles deposit on recessed SETC to that deposit on flush SETC) and β (ratio of heat flux from non-charged particles deposit on recessed SETC to that deposit on flush SETC), in the estimation of the heat flux from non-charged particle sources. Using a time dependent ratio α, it was found that ~50% of the total incident heat flux is attributable to the non-charged particles in the fully detached open divertor in DIII-D. Finally, the new application of similar SETC diagnostics in the Small Angle Slot divertor with a V-like configuration and partial tungsten coated surface (SAS-VW) is also introduced.