Dispersion of Particles Released into a Neutral Planetary Boundary Layer Using a Markov Chain–Monte Carlo Model

Ávila, Raúl; Raza, Syed Shoaib

doi:10.1175/jam2249.1

Cited by 7 publications

(11 citation statements)

References 38 publications

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“…In order to calculate the instantaneous velocity of the solid particles within the ash column, the model proposed by Crowe et al . (), Avila and Cervantes (, ) and Avila and Raza () was used. In the LSD model, the instantaneous velocity of the solid particles along the three directions u i p (where index notation is used) is calculated using the following equation:

ρ_{p} \frac{normald u_{i normalp}}{normald t} = \frac{3 μ {Re}_{p} C_{D}}{4 d_{p}^{2}} ((), u_{i} - u_{i normalp}) + ((), ρ_{p} - ρ) g

…”

Section: The Lsd Particle Turbulent Dispersion Modelmentioning

confidence: 99%

“…The atmospheric parameters calculated by the RAMS, which are used by the Lagrangian turbulent dispersion model, are the mean wind velocity, the correlation of velocity fluctuations (Reynolds turbulent stress) and the surface layer fluxes of momentum and heat. Such a Eulerian−LSD approach has been proposed in the literature by several authors (Legg and Raupach, ; Avila and Raza, ; Raza and Avila, ; Espinosa et al ., ).…”

Section: The Eulerian−lagrangian Approach and Domain Discretizationmentioning

confidence: 99%

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A new method of simulating volcanic eruption column formation and dispersion of ejected ash clouds

Arenal

Ávila

Raza

2017

Meteorological Applications

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ABSTRACT:A new Eulerian−Lagrangian model is developed to predict the formation of eruption columns, and the long range transport and dispersion of volcanic ash clouds in the atmosphere. The model capability is tested by presenting the atmospheric dispersion of ash clouds released during two eruptions of the Popocatepetl volcano in Mexico. The atmospheric wind predictions were made by using the Eulerian regional atmospheric modelling system (RAMS), which is well tested over the Mexico region. Two Lagrangian models were also employed: (1) an eruption column formation model and (2) a Lagrangian stochastic deterministic (LSD) particle dispersion model. In a LSD model, the continuous plume is simulated by several puffs (clouds) successively released in the atmosphere. (1) The influence of the wind on the eruption column, (2) the transport and dispersion of the ash cloud and (3) the concentration of volcanic ash using a smoothed particle hydrodynamics technique are reported. This is thought to be a unique combination of mathematical prediction models and would be of interest to the broader scientific community. The formation of the eruption column is compared with ground observations, while the long range trajectory of the ash clouds is compared with images based on satellite data, qualitatively. In both cases the agreement within the observed and simulated plume shape was found to be satisfactory which indicated the suitability of the Eulerian wind prediction model (RAMS) in the region as well as that of Lagrangian models employed in the study.

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ρ_{p} \frac{normald u_{i normalp}}{normald t} = \frac{3 μ {Re}_{p} C_{D}}{4 d_{p}^{2}} ((), u_{i} - u_{i normalp}) + ((), ρ_{p} - ρ) g

…”

Section: The Lsd Particle Turbulent Dispersion Modelmentioning

confidence: 99%

Section: The Eulerian−lagrangian Approach and Domain Discretizationmentioning

confidence: 99%

A new method of simulating volcanic eruption column formation and dispersion of ejected ash clouds

Arenal

Ávila

Raza

2017

Meteorological Applications

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“…Atmospheric parameters such as mean wind velocity, potential temperature, pressure and the surface layer fluxes of momentum and heat for the nocturnal flow for use in the Lagrangian dispersion model were calculated by the RAMS code. Such an Eulerian–Lagrangian stochastic approach has been proposed by several authors (Legg and Raupach, ; Avila and Raza, ; Raza and Avila, ). In this work, the local ground mean concentration has been calculated by using a Moving Least Squares approximation (MLS) technique described by Lancaster and Salkauskas () and Fries and Matthies ().…”

Section: Introductionmentioning

confidence: 99%

Turbulent dispersion of a gas tracer in a nocturnal atmospheric flow

Espinosa¹,

Ávila²,

Raza³

et al. 2012

Met. Apps

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ABSTRACT:A Lagrangian turbulent dispersion model has been coupled with the Regional Atmospheric Modelling System (RAMS) to predict the transport, dispersion and concentration of a gas tracer released into a stable atmosphere (nocturnal drainage flow) of the Anderson Springs Valley near San Francisco, California. The mean wind velocities governed by the topography of the region and the surface layer fluxes of momentum and heat into the stable atmosphere, were calculated by the RAMS code. The atmospheric transport and dispersion of a gas tracer was simulated in non-homogeneous turbulence conditions by using a Lagrangian Stochastic Particle Model. A Moving Least Squares technique was used to calculate the tracer gas concentration. The vertical profiles of the mean wind speed and the wind direction, as well as the tracer gas concentration, were compared with the field measurements for the fourth night of the ASCOT experiment (the night between 19 and 20 September 1980) carried out in the Anderson Springs Valley, California, USAThe computed profiles for wind direction and wind speed agreed well with the field data. Although at some locations the model predicted strong winds which transported the particle to larger distances downwind, the overall pattern of concentration distribution generated by the model compared quite well with the observations. It was concluded that the concentration patterns tend to follow the topography when the synoptic winds are weak.

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“…In this work, a long-range particle transport and dispersion model (LPDM) which was developed by Avila (1997) and used in a neutral atmosphere (Avila and Raza, 2005) is further developed and coupled with the meteorological model RAMS. The coupling is provided in such a way that the meteorological fields predicted by RAMS (with a time frequency of a few seconds) are communicated directly to the LPDM without storage.…”

Section: Introductionmentioning

confidence: 99%

“…In the next section, a brief description of the mathematical models RAMS and LPDM is presented. Further details on the models can be seen elsewhere (Pielke et al, 1992;Avila, 1997;Avila and Raza, 2005).…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of particle trajectory and atmospheric dispersion of airborne releases

Raza

Ávila

2009

Meteorological Applications

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Numerical simulation of particle trajectory and atmospheric dispersion has been performed for an airborne accidental release from a nuclear power plant site. A Long-range Particle transport and Dispersion Model (LPDM) based on a Lagrangian approach is developed and tested in this work. The Lagrangian transport/dispersion model is directly coupled with an atmospheric prediction model, RAMS (Regional Atmospheric Modeling System), to provide necessary meteorological fields in a three-dimensional domain. An advantage of this direct coupling is that the meteorological data generated by RAMS can be used directly for trajectory calculations without storage, thus reducing the CPU time consumed in the data storage and retrieval. This effort was done to be able to use this directly coupled modelling system for real-time predictions in case of an accidental release from a potential site.The simulated Lagrangian trajectories were compared with those obtained using observed hourly weather data obtained from an on-site meteorological tower. The results indicated that this one-way coupling between LPDM-RAMS provided almost identical trajectories when compared with those obtained using LPDM alone driven by hourly observed wind data. The comparison demonstrated the reliability of the RAMS meteorological predictions for the site under consideration. The comparison also indicated that LPDM (run in a stand alone mode), with hourly-observed wind data, could also be used for trajectory calculations over flat terrain.The model was developed on a parallel processing computer (SGI workstation, ORIGIN 2000 computer with eight processors) for use in real-time forecast mode. The computational time was about one-third of the simulation time, while using four processors. The model options need to be explored to reduce the computational time further and test its performance for real-time atmospheric dispersion applications.

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Dispersion of Particles Released into a Neutral Planetary Boundary Layer Using a Markov Chain–Monte Carlo Model

Cited by 7 publications

References 38 publications

A new method of simulating volcanic eruption column formation and dispersion of ejected ash clouds

A new method of simulating volcanic eruption column formation and dispersion of ejected ash clouds

Turbulent dispersion of a gas tracer in a nocturnal atmospheric flow

Numerical simulation of particle trajectory and atmospheric dispersion of airborne releases

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