Academic literature on the topic 'Lagrangian Particle sub-model'
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Journal articles on the topic "Lagrangian Particle sub-model"
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GOTOH, Hitoshi, Tetsuo SAKAI, and Tomoki SHIBAHARA. "LAGRANGIAN FLOW SIMULATION WITH SUB-PARTICLE-SCALE TURBULENCE MODEL." PROCEEDINGS OF HYDRAULIC ENGINEERING 44 (2000): 575–80. http://dx.doi.org/10.2208/prohe.44.575.
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Ganshin, A., T. Oda, M. Saito, S. Maksyutov, V. Valsala, R. J. Andres, R. E. Fisher, et al. "A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations." Geoscientific Model Development 5, no. 1 (February 15, 2012): 231–43. http://dx.doi.org/10.5194/gmd-5-231-2012.
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Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using the Global Eulerian-Lagrangian Coupled Atmospheric model (GELCA), comprising a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e. a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.
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Ganshin, A., T. Oda, M. Saito, S. Maksyutov, V. Valsala, R. J. Andres, R. Fischer, et al. "A global coupled Eulerian-Lagrangian model and 1 × 1 km CO<sub>2</sub> surface flux dataset for high-resolution atmospheric CO<sub>2</sub> transport simulations." Geoscientific Model Development Discussions 4, no. 3 (August 24, 2011): 2047–80. http://dx.doi.org/10.5194/gmdd-4-2047-2011.
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Abstract. We designed a method to simulate atmospheric CO2 concentrations at several continuous observation sites around the globe using surface fluxes at a very high spatial resolution. The simulations presented in this study were performed using a Lagrangian particle dispersion model coupled to a global atmospheric tracer transport model with prescribed global surface CO2 flux maps at a 1 × 1 km resolution. The surface fluxes used in the simulations were prepared by assembling the individual components of terrestrial, oceanic and fossil fuel CO2 fluxes. This experimental setup (i.e., a transport model running at a medium resolution, coupled to a high-resolution Lagrangian particle dispersion model together with global surface fluxes at a very high resolution), which was designed to represent high-frequency variations in atmospheric CO2 concentration, has not been reported at a global scale previously. Two sensitivity experiments were performed: (a) using the global transport model without coupling to the Lagrangian dispersion model, and (b) using the coupled model with a reduced resolution of surface fluxes, in order to evaluate the performance of Eulerian-Lagrangian coupling and the role of high-resolution fluxes in simulating high-frequency variations in atmospheric CO2 concentrations. A correlation analysis between observed and simulated atmospheric CO2 concentrations at selected locations revealed that the inclusion of both Eulerian-Lagrangian coupling and high-resolution fluxes improves the high-frequency simulations of the model. The results highlight the potential of a coupled Eulerian-Lagrangian model in simulating high-frequency atmospheric CO2 concentrations at many locations worldwide. The model performs well in representing observations of atmospheric CO2 concentrations at high spatial and temporal resolutions, especially for coastal sites and sites located close to sources of large anthropogenic emissions. While this study focused on simulations of CO2 concentrations, the model could be used for other atmospheric compounds with known estimated emissions.
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Turner, Adrian K., Kara J. Peterson, and Dan Bolintineanu. "Geometric remapping of particle distributions in the Discrete Element Model for Sea Ice (DEMSI v0.0)." Geoscientific Model Development 15, no. 5 (March 9, 2022): 1953–70. http://dx.doi.org/10.5194/gmd-15-1953-2022.
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Abstract. A new sea ice dynamical core, the Discrete Element Model for Sea Ice (DEMSI), is under development for use in coupled Earth system models. DEMSI is based on the discrete element method, which models collections of ice floes as interacting Lagrangian particles. In basin-scale sea ice simulations the Lagrangian motion results in significant convergence and ridging, which requires periodic remapping of sea ice variables from a deformed particle configuration back to an undeformed initial distribution. At the resolution required for Earth system models we cannot resolve individual sea ice floes, so we adopt the sub-grid-scale thickness distribution used in continuum sea ice models. This choice leads to a series of hierarchical tracers depending on ice fractional area or concentration that must be remapped consistently. The circular discrete elements employed in DEMSI help improve the computational efficiency at the cost of increased complexity in the effective element area definitions for sea ice cover that are required for the accurate enforcement of conservation. An additional challenge is the accurate remapping of element values along the ice edge, the location of which varies due to the Lagrangian motion of the particles. In this paper we describe a particle-to-particle remapping approach based on well-established geometric remapping ideas that enforces conservation, bounds preservation, and compatibility between associated tracer quantities, while also robustly managing remapping at the ice edge. One element of the remapping algorithm is a novel optimization-based flux correction that enforces concentration bounds in the case of nonuniform motion. We demonstrate the accuracy and utility of the algorithm in a series of numerical test cases.
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Rutherford, B., and M. T. Montgomery. "A Lagrangian analysis of a developing and non-developing disturbance observed during the PREDICT experiment." Atmospheric Chemistry and Physics Discussions 11, no. 12 (December 19, 2011): 33273–323. http://dx.doi.org/10.5194/acpd-11-33273-2011.
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Abstract. The problem of tropical cyclone formation requires among other things an improved understanding of recirculating flow regions on sub-synoptic scales in a time evolving flow with typically sparse real-time data. This recirculation problem has previously been approached assuming as a first approximation both a layer-wise two-dimensional and nearly steady flow in a co-moving frame with the parent tropical wave or disturbance. This paper provides an introduction of new Lagrangian techniques for locating flow boundaries that encompass regions of recirculation in time-dependent flows that relax the steady flow approximation. Lagrangian methods detect recirculating regions from time-dependent data and offer a more complete methodology than the approximate steady framework. The Lagrangian reference frame follows particle trajectories so that flow boundaries which constrain particle transport can be viewed objectively. Finite-time Lagrangian scalar field methods from dynamical systems theory offer a way to compute boundaries from grids of particles seeded in and near a disturbance. The methods are applied to both a developing and non-developing disturbance observed during the recent pre-depression investigation of cloud systems in the tropics (PREDICT) experiment. The data for this analysis is derived from global forecast model output that assimilated the dropsonde observations as they were being collected by research aircraft. Since Lagrangian methods require trajectory integrations, we address some practical issues of using Lagrangian methods in the tropical cyclogenesis problem. Lagrangian diagnostics developed here are used to evaluate the previously hypothesized import of dry air into ex-Gaston, which did not re-develop into a tropical cyclone, and the exclusion of dry air from pre-Karl, which did become a tropical cyclone and later a major hurricane.
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Rutherford, B., and M. T. Montgomery. "A Lagrangian analysis of a developing and non-developing disturbance observed during the PREDICT experiment." Atmospheric Chemistry and Physics 12, no. 23 (December 3, 2012): 11355–81. http://dx.doi.org/10.5194/acp-12-11355-2012.
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Abstract. The problem of tropical cyclone formation requires among other things an improved understanding of recirculating flow regions on sub-synoptic scales in a time evolving flow with typically sparse real-time data. This recirculation problem has previously been approached assuming as a first approximation both a layer-wise two-dimensional and nearly steady flow in a co-moving frame with the parent tropical wave or disturbance. This paper provides an introduction of Lagrangian techniques for locating flow boundaries that encompass regions of recirculation in time-dependent flows that relax the steady flow approximation. Lagrangian methods detect recirculating regions from time-dependent data and offer a more complete methodology than the approximate steady framework. The Lagrangian reference frame follows particle trajectories so that flow boundaries which constrain particle transport can be viewed in a frame-independent setting. Finite-time Lagrangian scalar field methods from dynamical systems theory offer a way to compute boundaries from grids of particles seeded in and near a disturbance. The methods are applied to both a developing and non-developing disturbance observed during the recent pre-depression investigation of cloud systems in the tropics (PREDICT) experiment. The data for this analysis is derived from global forecast model output that assimilated the dropsonde observations as they were being collected by research aircraft. Since Lagrangian methods require trajectory integrations, we address some practical issues of using Lagrangian methods in the tropical cyclogenesis problem. Lagrangian diagnostics are used to evaluate the previously hypothesized import of dry air into ex-Gaston, which did not re-develop into a tropical cyclone, and the exclusion of dry air from pre-Karl, which did become a tropical cyclone and later a major hurricane.
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Sanchez, Kevin J., Bo Zhang, Hongyu Liu, Matthew D. Brown, Ewan C. Crosbie, Francesca Gallo, Johnathan W. Hair, et al. "North Atlantic Ocean SST-gradient-driven variations in aerosol and cloud evolution along Lagrangian cold-air outbreak trajectories." Atmospheric Chemistry and Physics 22, no. 4 (March 2, 2022): 2795–815. http://dx.doi.org/10.5194/acp-22-2795-2022.
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Abstract. Atmospheric marine particle concentrations impact cloud properties, which strongly impact the amount of solar radiation reflected back into space or absorbed by the ocean surface. While satellites can provide a snapshot of current conditions at the overpass time, models are necessary to simulate temporal variations in both particle and cloud properties. However, poor model accuracy limits the reliability with which these tools can be used to predict future climate. Here, we leverage the comprehensive ocean ecosystem and atmospheric aerosol–cloud dataset obtained during the third deployment of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES3). Airborne and ship-based measurements were collected in and around a cold-air outbreak during a 3 d (where d stands for day) intensive operations period from 17–19 September 2017. Cold-air outbreaks are of keen interest for model validation because they are challenging to accurately simulate, which is due, in part, to the numerous feedbacks and sub-grid-scale processes that influence aerosol and cloud evolution. The NAAMES observations are particularly valuable because the flight plans were tailored to lie along Lagrangian trajectories, making it possible to spatiotemporally connect upwind and downwind measurements with the state-of-the-art FLEXible PARTicle (FLEXPART) Lagrangian particle dispersion model and then calculate a rate of change in particle properties. Initial aerosol conditions spanning an east–west, closed-cell-to-clear-air transition region of the cold-air outbreak indicate similar particle concentrations and properties. However, despite the similarities in the aerosol fields, the cloud properties downwind of each region evolved quite differently. One trajectory carried particles through a cold-air outbreak, resulting in a decrease in accumulation mode particle concentration (−42 %) and cloud droplet concentrations, while the other remained outside of the cold-air outbreak and experienced an increase in accumulation mode particle concentrations (+62 %). The variable meteorological conditions between these two adjacent trajectories result from differences in the local sea surface temperature in the Labrador Current and surrounding waters, altering the stability of the marine atmospheric boundary layer. Further comparisons of historical satellite observations indicate that the observed pattern occurs annually in the region, making it an ideal location for future airborne Lagrangian studies tracking the evolution of aerosols and clouds over time under cold-air outbreak conditions.
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Wu, Dien, John C. Lin, Benjamin Fasoli, Tomohiro Oda, Xinxin Ye, Thomas Lauvaux, Emily G. Yang, and Eric A. Kort. "A Lagrangian approach towards extracting signals of urban CO<sub>2</sub> emissions from satellite observations of atmospheric column CO<sub>2</sub> (XCO<sub>2</sub>): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)." Geoscientific Model Development 11, no. 12 (December 4, 2018): 4843–71. http://dx.doi.org/10.5194/gmd-11-4843-2018.
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Abstract. Urban regions are responsible for emitting significant amounts of fossil fuel carbon dioxide (FFCO2), and emissions at the finer, city scales are more uncertain than those aggregated at the global scale. Carbon-observing satellites may provide independent top-down emission evaluations and compensate for the sparseness of surface CO2 observing networks in urban areas. Although some previous studies have attempted to derive urban CO2 signals from satellite column-averaged CO2 data (XCO2) using simple statistical measures, less work has been carried out to link upwind emission sources to downwind atmospheric columns using atmospheric models. In addition to Eulerian atmospheric models that have been customized for emission estimates over specific cities, the Lagrangian modeling approach – in particular, the Lagrangian particle dispersion model (LPDM) approach – has the potential to efficiently determine the sensitivity of downwind concentration changes to upwind sources. However, when applying LPDMs to interpret satellite XCO2, several issues have yet to be addressed, including quantifying uncertainties in urban XCO2 signals due to receptor configurations and errors in atmospheric transport and background XCO2. In this study, we present a modified version of the Stochastic Time-Inverted Lagrangian Transport (STILT) model, “X-STILT”, for extracting urban XCO2 signals from NASA's Orbiting Carbon Observatory 2 (OCO-2) XCO2 data. X-STILT incorporates satellite profiles and provides comprehensive uncertainty estimates of urban XCO2 enhancements on a per sounding basis. Several methods to initialize receptor/particle setups and determine background XCO2 are presented and discussed via sensitivity analyses and comparisons. To illustrate X-STILT's utilities and applications, we examined five OCO-2 overpasses over Riyadh, Saudi Arabia, during a 2-year time period and performed a simple scaling factor-based inverse analysis. As a result, the model is able to reproduce most observed XCO2 enhancements. Error estimates show that the 68 % confidence limit of XCO2 uncertainties due to transport (horizontal wind plus vertical mixing) and emission uncertainties contribute to ∼33 % and ∼20 % of the mean latitudinally integrated urban signals, respectively, over the five overpasses, using meteorological fields from the Global Data Assimilation System (GDAS). In addition, a sizeable mean difference of −0.55 ppm in background derived from a previous study employing simple statistics (regional daily median) leads to a ∼39 % higher mean observed urban signal and a larger posterior scaling factor. Based on our signal estimates and associated error impacts, we foresee X-STILT serving as a tool for interpreting column measurements, estimating urban enhancement signals, and carrying out inverse modeling to improve quantification of urban emissions.
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Olin, M., T. Rönkkö, and M. Dal Maso. "CFD modeling of a vehicle exhaust laboratory sampling system: sulfur driven nucleation and growth in diluting diesel exhaust." Atmospheric Chemistry and Physics Discussions 15, no. 2 (January 29, 2015): 2905–56. http://dx.doi.org/10.5194/acpd-15-2905-2015.
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Abstract. A new exhaust aerosol model CFD-TUTEAM (Tampere University of Technology Exhaust Aerosol Model for Computational Fluid Dynamics) was developed. The model can be used to simulate particle formation and evolution in diesel exhaust. The model has an Eulerian sub-model that provides spatial information within the computational domain, and a computationally less expensive Lagrangian sub-model that can be used to examine particle formation in a high temporal resolution. Particle formation in a laboratory sampling system that includes a porous tube type diluter and an aging chamber was modeled with CFD-TUTEAM. The simulation results imply that over 99% of new particles are formed in the aging chamber region, because nucleation rate remains at high level in the aging chamber due to low dilution ratio and low nucleation exponents. The nucleation exponents for sulfuric acid in sulfuric acid-water nucleation ranging from 0.25 to 1 appeared to fit best with measurement data, which are the same values as the slopes of volatile nucleation mode number concentration vs. raw exhaust sulfuric acid concentration obtained from the measurement data. These nucleation exponents are very low compared to the nucleation exponents obtained from the classical nucleation theory of binary sulfuric acid-water nucleation. The values of nucleation exponent lower than unity suggest that other compounds, such as hydrocarbons, might have a significant role in the nucleation process.
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Emmerson, K. M., A. R. MacKenzie, S. M. Owen, M. J. Evans, and D. E. Shallcross. "A Lagrangian model with simple primary and secondary aerosol scheme 1: comparison with UK PM<sub>10</sub> data." Atmospheric Chemistry and Physics Discussions 4, no. 3 (June 15, 2004): 3127–57. http://dx.doi.org/10.5194/acpd-4-3127-2004.
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Abstract. A Lagrangian trajectory model used to simulate photochemistry has been extended to include a simple parameterisation of primary and secondary aerosol particles. The model uses emission inventories of primary particles for the UK from the NAEI (National Atmospheric Emissions Inventory for the UK), and for Europe from the TNO (Institute of Environmental Sciences, Energy Research and Process Innovation, the Netherlands) respectively, to transport tracers representing PM10. One biogenic and two anthropogenic organic compounds were chosen as surrogates to model the formation of condensable material suitable for the production of secondary organic aerosol (SOA). The SOA is added to the primary PM10 and compared to measured PM10 at one urban and two rural UK receptor sites. The results show an average under-prediction by factors of 4.5 and 8.9 in the urban and rural cases respectively. The model is also used to simulate production of two secondary inorganic species, H2SO4 and HNO3, which are assumed, as a limiting case, to be present in the particle phase. The relationships between modelled and measured total PM10 improved with the addition of secondary inorganic compounds, and the overall model under-prediction factors are reduced to 3.5 and 3.9 in the urban and rural cases respectively. Nevertheless, our conclusion is that current emissions and chemistry do not appear to provide sufficient information to model PM10 well (i.e. to within a factor of two). There is a need for further process studies to inform global climate modelling that includes climate forcing by aerosol.
Dissertations / Theses on the topic "Lagrangian Particle sub-model"
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Wadhwani, Rahul. "Physics-based simulation of short-range spotting in wildfires." Thesis, 2019. https://vuir.vu.edu.au/40025/.
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Firebrands play a vital role in the propagation of fire fronts and starting new fires called spotfires ahead of fire fronts during wildfire progression. Firebrands are a harbinger of damage to infrastructure; their effects cause a particularly important threat to people living within the wildland-urban-interface, hampers the suppression of the wildfire or even blocking the evacuation routes for communities and emergency services. Short-range firebrands (<750m) which travel along with the wind with little or no lofting are particularly crucial in increasing the fire front propagation and damaging structures situated closed to wildland-urban interface. In the Daylesford fire of 1962, massive short-range spotting (the process of spot fire ignition and merging of spots caused by firebrands) occurred in eucalyptus forest and increased the rate of fire spread by roughly three times more than the computed using empiricial correlation used by operational fire model. Despite the massive importance of short-range firebrands, little research has been conducted because of the safety risks and challenges of fire to emergency service personnel and to the remote equipment like collection boxes, IR cameras, UAVs, which could be used by researchers to quantify and measure fire properties.
An operational model to represent the transport of short-range firebrand and their likelihood to ignite the surface fuel like forest litter could be developed from a numerical model. This study first attempts to validate a numerical model of firebrand transport with a set of benchmark experiments. The validation of numerical model is carried out using idealised regular shaped firebrand. Fire Dynamic Simulator (FDS) is an open-source Computational Fluid Dynamics (CFD) based fire model which is used in this study. The validation of the numerical model is split into two parts focusing on validation of (1) transport, and (2) ignition potential of firebrands.
Transport of short range firebrands are modelled in FDS using a lagrangian particle sub-model. The model was validated using two firebrand generators (a plastic pipe-based prototype and stainless steel based main firebrand generator) constructed at our facility as a part of this study. The firebrand generator is equipment which generates a repeatable firebrand shower in a confined space. There are few firebrand dragons built around the world. However, our firebrand generators produce a uniform flow field which simplifies the transport of short-range firebrand to be validated. The set of experiments conducted is used to validate the Lagrangian particle model available in FDS used in the transport of short-range firebrands. The validation is carried out on cubiform, cylindrical, and square disc-shaped firebrands. As the default drag model in FDS was not suitable for shapes of firebrands, the drag model is improved to account for a generic shape of firebrand particle. The results show a reasonable agreement with the experiments for all three shapes over a range of particle Reynolds number.
A set of laboratory scale equipment is used to study the ignition likelihood from a short-range firebrand in the numerical model. The boundary fuel vegetation model of FDS is validated. The pyrolysis of vegetation is first tested using thermogravimetric analyser and then with cone calorimeter to estimate mass loss rate, heat-release rate, and time to sustained flaming ignition of three forest litter (pine, eucalyptus, and hay) fuels. Further, a set of thermo-physical properties (thermal conductivity, heat capacity, the heat of pyrolysis, the heat of combustion) of the material tested are also measured using in-house equipment required in the above numerical model. The result showed that the simple linear pyrolysis model is good enough for different forest litter tested with thermogravimetric analyser and cone calorimeter.
Finally, a parametric study of short-range firebrand transport inside an open woodland forest canopy is carried out using the validated Lagrangian particle sub-model. The work focuses on understanding how firebrand distribution varies with a set of variable firebrand characteristics in a wildfire and set a stepping stone for the future study. The results are found to be qualitatively similar to the literature.
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Akinlabi, Emmanuel Olutayo. "Analysis and Modelling of Small-Scale Turbulence." Doctoral thesis, 2020. https://depotuw.ceon.pl/handle/item/3669.
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The analysis and modelling of small-scale turbulence in the atmosphere
play a significant role in improving our understanding of cloud processes,
thereby contributing to the development of better parameterization of
climate models. Advancement in our understanding of turbulence can be
fueled from a more in-depth study of small-scale turbulence, which is the
subject of this thesis. Within this thesis, small scales are understood as
turbulent structures affected by viscosity as well as scales from the highwavenumber part of the inertial range which are of O(0.1m−1m) typically
neglected in numerical simulations of atmospheric turbulence.
This work is divided into two parts. In the first part, various approaches
to estimate the turbulence kinetic energy (TKE) dissipation rate , from
one-dimensional (1D) intersections that resemble experimental series, are
tested using direct numerical simulation (DNS) of the stratocumulus cloudtop mixing layer and free convective boundary layer. Results of these
estimates are compared with “true” DNS values of in buoyant and inhomogeneous atmospheric flows. This research focuses on recently proposed
methods of the TKE dissipation-rate retrievals based on signal’s zero
crossings and on recovering the missing part of the spectrum. The methods are tested on fully resolved turbulence fields and compared to standard retrievals from power spectra and structure functions. Anisotropy
of turbulence due to buoyancy is shown to influence retrievals based on
the vertical velocity component. TKE dissipation-rate estimates from the
number of crossings correspond well to spectral estimates. As far as the
recovery of the missing part of the spectrum is concerned, different models
for the dissipation spectra was investigated, and the best one is chosen for
further study. Results were improved when the Taylors’ microscale was
used in the iterative method, instead of the Liepmann scale based on the
number of signal’s zero crossings. This also allowed for the characterization of external intermittency by the Taylor-to-Liepmann scale ratio. It
was shown that the new methods of TKE dissipation-rate retrieval from
1D series provide a valuable complement to standard approaches.
The second part of this study addresses the reconstruction of sub-grid
scales in large eddy simulation (LES) of turbulent flows in stratocumulus cloud-top. The approach is based on the fractality assumption of the
turbulent velocity field. The fractal model reconstructs sub-grid velocity
fields from known filtered values on LES grid, using fractal interpolation,
proposed by Scotti and Meneveau [Physica D 127, 198–232 1999]. The
characteristics of the reconstructed signal depend on the stretching parameter d, which is related to the fractal dimension of the signal. In many
previous studies, the stretching parameter values were assumed to be constant in space and time. To improve the fractal interpolation approach,
the stretching parameter variability is accounted for. The local stretching
parameter is calculated from DNS data with an algorithm proposed by
Mazel and Hayes [IEEE Trans. Signal Process 40(7), 1724–1734, 1992],
and its probability density function (PDF) is determined. It is found that
the PDFs of d have a universal form when the velocity field is filtered
to wave-numbers within the inertial range. The inertial-range PDFs of d
in DNS and LES of stratocumulus cloud-top and experimental airborne
data from physics of stratocumulus top (POST) research campaign were
compared in order to investigate its Reynolds number (Re) dependence.
Next, fractal reconstruction of the subgrid velocity is performed and energy spectra and statistics of velocity increments are compared with DNS
data. It is assumed that the stretching parameter d is a random variable with the prescribed PDF. Moreover, the autocorrelation of d in time
is examined. It was discovered that d decorrelates with the characteristic timescale of the order of the Kolmogorov’s time scale and hence can
be chosen randomly after each time step in LES. This follows from the
fact that the time steps used in LES are typically considerably larger than
Kolmogorov’s timescale. The implemented fractal model gives good agreement with the DNS and physics of stratocumulus cloud (POST) airborne
data in terms of their spectra and PDFs of velocity increments. The error
in mass conservation is smaller compared to the use of constant values of d.
In conclusion, possible applications of the fractal model were addressed. A
priori LES test shows that the fractal model can reconstruct the resolved
stresses and residual kinetic energy. Also, based on the preliminary test,
the fractal model can improve LES velocity fields used in the Lagrangian
tracking of droplets for the simulation of cloud microphysics.
Both parts of the thesis are based on the assumptions of scale self-similarity
of Kolmogorov and local isotropy, which may not be satisfied in real atmospheric conditions. Since the standard methods for TKE dissipation rate
retrieval are derived from these assumptions, the level of discrepancy is
investigated by comparing the actual value of from DNS with estimates
from these methods. Also, in the case of the modelling of small (subgrid) scales, the improved fractal model relies on scale-similarity. Range
of scales, in which this assumption is sufficiently satisfied (i.e. inertial
range scales) is reconstructed. Statistical tools from the Kolmogorov’s
similarity hypotheses are used to assess the performance of the improved
fractal model.
Conference papers on the topic "Lagrangian Particle sub-model"
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GOTOH, Hitoshi, Minoru HAYASHI, Tetsuo SAKAI, and Koji ODA. "Numerical Model of Wave Breaking by Lagrangian Particle Method with Sub-Particle-Scale Turbulence Model." In Proceedings of the 2nd International Conference. WORLD SCIENTIFIC, 2004. http://dx.doi.org/10.1142/9789812703040_0026.
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Rybalko, Michael, Eric Loth, and Dennis Lankford. "LES Sub-Grid Diffusion for Lagrangian Particles." In ASME 2008 Fluids Engineering Division Summer Meeting collocated with the Heat Transfer, Energy Sustainability, and 3rd Energy Nanotechnology Conferences. ASMEDC, 2008. http://dx.doi.org/10.1115/fedsm2008-55207.
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A continuous random walk (CRW) turbulent diffusion model was developed for Lagrangian particles within flow fields simulated by hybrid RANS/LES methodologies. For RANS flow-fields, the conventional time-scale and length-scale constants were determined by the turbulence intensity and dissipation values computed by the single-phase solver with a k-ω (Menter SST) model and subsequent comparison with turbulent particle diffusion experimental results of Snyder & Lumley (1971). This allowed validation against data for four particle types ranging from hollow glass to copper shot in grid-generated turbulence. The stochastic diffusion model was then extended to utilize the Nichols-Nelson k-ω hybrid RANS-LES turbulence model in a more complex turbulent flow resulting from the unsteady, three dimensional wake of a cylinder at Mach number of 0.1 and Reynolds number (ReD) of 800. The gas flow was computed with a 5th-order upwind-biased scheme. Throughout the wake, the sub-grid random walk model yielded good predictions of particle diffusion as compared with DNS. Also, these results indicate that crossing trajectory effects and inertia-based drift corrections are critical to handling a variety of particle Stokes numbers as well as regions of non-homogeneous turbulence, even when most of the kinetic energy is captured with the resolved-scales of an LES approach.
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Lei, Kangbin, Kiwamu Kase, Nobuyuki Oshima, and Toshio Kobayashi. "A Disperse-Phase Dynamic SGS Coupling Model for Particle-Laden Turbulent Flows." In ASME/JSME 2007 5th Joint Fluids Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/fedsm2007-37059.
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In order to study the effects of turbulence sub-grid-scale (SGS) fluctuation on particle Lagrangian motion in turbulent flows, a dynamic random walk (DRW) SGS coupling model based on an Eulerian-Lagrangian approach was developed. The advantage of the new model is that the Gaussian statistical distribution and local isotropic properties of turbulence SGS fluctuation can be parameterized by Germano’s (1991) Eulerian dynamic procedure. Using the present model, large eddy simulation (LES) was performed for downward channel flow at a Reynolds number of 180, as in the direct numerical simulation (DNS) done by Rouson & Eaton in 1997. Through a comparing of the statistical properties of particle diffusion with DNS, the capabilities and limitations of the present DRW SGS model were verified. Moreover, it was found that turbulence SGS fluctuation was strongly associated with particle motion, because preferred particles were affected by the preferred length scale of the eddy structure around. It was also found that turbulence SGS fluctuations are indispensable in calculating particles’ Lagrangian trajectories in LES even when the particle Stokes number is high.
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Rousta, Farid, Bamdad Lessani, and Goodarz Ahmadi. "A Numerical Study on the Effect of Carrier Fluid Subgrid Scales Fluctuations on Deposition and Dispersion of Lagrangian Particles." In ASME 2022 Fluids Engineering Division Summer Meeting. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/fedsm2022-87651.
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Abstract Large-eddy simulation (LES) coupled with a Lagrangian particle tracking was performed, and the particle deposition and dispersion in turbulent channel flows were investigated. Different test cases with particle Stokes numbers varying from St = 2 to St = 100 were considered in a fully developed turbulent channel flow at a friction Reynolds number of Reτ = 180. The Dynamic Smagorinsky model was used to model the sub-grid scale fluctuations of carrier flow. In the first set of simulations, the effects of sub-grid scale fluctuations in LES were not considered on the Lagrangian particles. Instead, the velocity of carrier flow seen by particles was simply taken as the fluid filtered velocity. Next, direct numerical simulations (DNS) for the same test cases were performed to clarify the importance of sub-grid scale fluctuations seen by the Lagrangian particles. To clarify the differences, the predicted deposition velocities predicted by both LES and DNS methods were compared with the available data in the literature. Deposition velocities predicted by LES were significantly less than those predicted by DNS, especially for the cases with lower particle Stokes numbers. In addition to the deposition velocity, the particle dispersion was also significantly affected by the sub-grid scale fluctuations in the channel. To shed light on differences between particle dispersion for different cases, time and space averaged particle concentrations were evaluated and compared. Finally, the particle mean and fluctuating velocity profiles for different cases were reported.
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Xu, Yiban, Michael A. Krammen, Guoqiang Wang, Jesse S. Fisher, and Zeses Karoutas. "Analysis of Particle Transfer Behavior in Fuel Rod Bundles Using CFD Lagrangian Particle Tracking Method." In 2021 28th International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/icone28-66793.
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Abstract Crud has been observed on the fuel rod surfaces in a variety of fuel designs around the world, and in some limited situations fuel performance was compromised due to crud-induced power shift (CIPS) and/or crud-induced localized corrosion (CILC). It is generally believed that crud deposition depends on fuel rod surface sub-cooled nucleate boiling, coolant chemistry and the availability of particles from component corrosion or from reinserted fuel. The formation, release, and accumulation of crud on the fuel and its influence on CIPS and/or CILC is a complicated process involving multi-physics phenomena. This study uses Computational Fluid Dynamics (CFD) Lagrangian Particle Tracking (LPT) techniques in analysis of particle transfer behavior in fuel rod bundles focusing on flow swirl and turbulence impacts. It is hoped that high fidelity CFD results can provide insights into particle transfer behaviors in the bulk coolant as well as near the fuel rods, which may provide guidance for model development of lumped or integrated analysis methods. The CFD model was built based on the best practices learned from previous single-phase analyses. The LPT options, including particle injectors, forces on particles, and solver settings, were verified by comparing the simulated results to the test data from simple geometry with various particle sizes, covering deposition mechanisms in diffusion-, turbulent- and inertial-dominated regimes. The tested model then was applied to Westinghouse fuel designs with and without Intermediate Flow Mixing (IFM) grids. Particle concentration and size distributions in the coolant around fuel rods were obtained and the effects of grid induced swirl flow on particle transfer were identified. The analysis results may be included in lumped or integrated crud formation/release analysis methods. Limitations and potential improvements of this analysis method are also discussed.
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Roy, Arnab, Srinath V. Ekkad, and Uri Vandsburger. "Prediction and Validation of Performance of an Entrained Flow Gasifier Model." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-63770.
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Computational fluid dynamics (CFD) simulation of a single stage, dry-feed entrained flow gasifier is carried out to predict several physical and chemical processes within the gasifier. The model is developed using a commercial software package FLUENT. The CFD model is based on an Eulerian-Lagrangian framework, where the continuous fluid phase is modeled in Eulerian approach and the particle flow trajectory is simulated in Lagrangian frame. The two phases are coupled by appropriate source terms in the conservation equations. The gasification process can be divided into the following sub-processes, which are inert heating, moisture release, coal devolatilization, char gasification and gas phase reactions. Discrete Phase Model (DPM) is used to model the coal particles and coupled with heterogeneous particle surface reactions in Species Transport module. The interaction between reaction chemistry and turbulence is described by Finite-rate/Eddy dissipation model. The simulation provides detailed information of temperature field and species concentration profile inside the gasifier. The temperature distribution clearly indicates the three different reaction zones for devolatilization, gasification and reduction. Steady state model predictions are compared with benchmark experimental data from literature. The trend of the predicted species mole fraction distribution is in good agreement within error bound of the experiment. The model thus provides a validated set of model parameters along with an insight to the underlying flow physics and chemical reactions of gasification process that can be employed to improve design of experiments. This study also develops the basis to achieve further accuracy incorporating complex effects such as detailed reaction kinetic mechanisms, proper devolatilization models, effect of ash-slag transition and particle deposition.
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Pourang, K., C. Moreau, and A. Dolatabadi. "A Three-Dimensional Analysis of the Suspension Plasma Spray Impinging on a Curved Substrate." In ITSC2015, edited by A. Agarwal, G. Bolelli, A. Concustell, Y. C. Lau, A. McDonald, F. L. Toma, E. Turunen, and C. A. Widener. ASM International, 2015. http://dx.doi.org/10.31399/asm.cp.itsc2015p0223.
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Abstract Obtaining a uniform coating on curved mechanical parts such as gas turbine blades is one of the industrial challenges in suspension plasma spraying. Through a three dimensional numerical analysis, this study is aimed at providing a better understanding of the effect of substrate curvature on in-flight particle temperature, velocity and trajectory. The high temperature and high velocity plasma flow is simulated inside the plasma torch using a uniform volumetric heat source in the energy equation. In addition, yttria stabilized zirconia (YSZ) suspension is molded as a multicomponent droplet while catastrophic breakup regime is considered for simulating the secondary break-up when the suspension interacts with the plasma flow. A two-way coupled Eulerian-Lagrangian approach along with a stochastic discrete model was used to track the particle trajectory. Particle size distribution in the vicinity of the substrate at different stand-off distances has been investigated. The results show that sub-micron particles may obtain higher velocity and temperature compared to the larger particles. However, due to the small Stokes number associated with sub-micron particles, they are more sensitive to the change of the gas flow streamlines in the vicinity of a curved substrate
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Zaman, M. S., S. Hossein Mousavizadegan, M. G. Satish, and M. Rafiqul Islam. "Towards the Comprehensive Modeling of Multiphase Fluid Flow Pumping Systems Using Smoothed Particle Hydrodynamics (SPH)." In ASME 2007 26th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2007. http://dx.doi.org/10.1115/omae2007-29592.
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Multiphase pumping is a viable option in hydrocarbon production at different conditions and especially in more challenging environments. A multiphase pump system can boost pressure without the need to separate the phases and occupies less space and weight, which is valuable for offshore applications. Sub-sea multiphase pumping in deepwater will be reliable, bringing a new economic dimension to the development of satellite oil fields. It is necessary to study the different scenarios that may happen during the transferring of a multiphase fluid through the piping systems. The flow patterns transition in horizontal pipes has been studied theoretically using the smoothed particle hydrodynamics (SPH). SPH is a Lagrangian approach, with the particles themselves being the framework on which the fluid equations are solved, and so there is no grid to constrain the dynamic range or geometry of the system being modeled. In the Lagrangian formulation, the mesh follows the fluid motion and this automatically guarantees the accurate treatment of interfaces that is really a disadvantage of the Eulerian approach. Therefore, for multi-material (oil, water, gas and also sand) problems, Lagrangian method is the most accurate tool for tracking the material interfaces. In addition, geometrically complex and/or dynamic boundaries can be handled without undue difficulty. The simultaneous flow of air and water as two representing fluids are studied through a horizontal pipe using SPH method. The mathematical model is represented and the position of the fluids particles is obtained at different time steps. The objective is to simulate the flow patterns that will help us to design multiphase fluid pumping systems and to identify the variables of interest for instrumentation.
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Wu, X. M., S. M. Ghiaasiaan, and S. I. Abdel-Khalik. "Numerical Modeling of Aerosol Transport and Removal in Channels Using the Particle Tracking Method." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/htd-24168.
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Abstract Turbulent transport and deposition of microscopic particles in commonly-used large, and micro-channels were investigated. The objective was to examine the suitability of the Reynolds-averaged Navier-Stokes (RANS)-type turbulence models, along with a Monte-Carlo Lagrangian particle tracking method that accounts for the stochastic particle-turbulent eddy interactions, for the modeling of aerosol transport when a multitude of forces act on the particles. The computer program KIVA-3 (Amsden et al., 1993) was modified and enhanced by adding several turbulence models, and including appropriate models for the effect of the following mechanisms on particle motion: drag, gravity, thermophoresis, Brownian dispersion, and shear-induced (Saffman) lift force. The effect of Brownian motion was modeled by including a random, white noise force term in the particle equation of motion. Parametric simulations were performed, leading to the following main observations. For the transport and deposition of microscopic particles, in addition to the turbulent dispersion, several other dispersion mechanisms were important. The k-ε and Reynolds-stress transport models provided similar predictions for sub-micron particles, but differed significantly for larger particles. The model provided physically consistent results with correct trends in all the simulations. The methodology, however, appears to be expensive in terms of computations, and further work is needed for streamlining the numerical solution methods and physical models.
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Suman, Alessio, Mirko Morini, Rainer Kurz, Nicola Aldi, Klaus Brun, Michele Pinelli, and Pier Ruggero Spina. "Quantitative CFD Analyses of Particle Deposition on a Transonic Axial Compressor Blade: Part II — Impact Kinematics and Particle Sticking Analysis." In ASME Turbo Expo 2014: Turbine Technical Conference and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gt2014-25473.
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In heavy-duty gas turbines, the micro-particles not captured by the air filtration system can cause fouling and, consequently, a performance drop of the compressor. This paper presents three-dimensional numerical simulations of the micro-particle ingestion (0–2 μm) on an axial compressor rotor carried out by means of a commercial computational fluid dynamic code. Particle trajectory simulations use a stochastic Lagrangian tracking method that solves the equations of motion separately from the continuous phase. The NASA Rotor 37 is considered as a case study for the numerical investigation. The compressor rotor numerical model and the discrete phase model were previously validated by the authors in the first part of this work. The kinematic characteristics (velocity and angle) of the impact of micrometric and sub-micrometric particles with the blade surface of an axial transonic compressor are shown. The blade zones affected by particle impact were extensively analyzed and reported in the first part of this work, forming the starting point for the analyses shown in this paper. The kinematic analysis showed a high tendency of particle adhesion on the suction side, especially for the particles with a diameter equal to 0.25 μm. Fluid dynamic phenomena and airfoil shape play a key role regarding particle impact velocity and angle. This work has the goal of combining, for the first time, the kinematic characteristics of particle impact on the blade with fouling phenomenon by the use of a quantity called sticking probability adopted from literature. From these analyses, some guidelines for a proper management of the power plant (in terms of filtration and washing strategies) are highlighted.