• Title/Summary/Keyword: Lagrangian Stochastic Model (LSM)

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Numerical Simulation of Buoyant flume Dispersion in a Stratified Atmosphere Using a Lagrangian Stochastic Model

  • Kim, Hyun-Goo;Noh, Yoo-Jeong;Lee, Choung-Mook;Park, Don-Bum
    • Journal of Mechanical Science and Technology
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    • v.17 no.3
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    • pp.440-448
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    • 2003
  • In the present paper, numerical simulations of buoyant plume dispersion in a neutral and stable atmospheric boundary layer have been carride out. A Lagrangian Stochastic Model (LSM) with a Non-Linear Eddy Viscosity Model (NLEVM) for turbulence is used to generate a Reynolds stress field as an input condition of dispersion simulation. A modified plume-rise equation is included in dispersion simulation in order to consider momentum effect in an initial stage of plume rise resulting in an improved prediction by comparing with the experimental data. The LSM is validated by comparing with the prediction of an Eulerian Dispersion Model (EDM) and by the measured results of vertical profiles of mean concentration in the downstream of an elevated source in an atmospheric boundary layer. The LSM predicts accurate results especially in the vicinity of the source where the EDM underestimates the peak concentration by 40% due to inherent limitations of gradient diffusion theory. As a verification study, the LSM simulation of buoyant plume dispersions under a neutral and stable atmospheric condition is compared with a wind-tunnel experiment, which shows good qualitative agreements.

The Third National Congress on Fluids Engineering: (제 4 회 한국 유체공학 학술대회)

  • Kim, Kyung-Rock;Jung, Jae-Dal;Lee, Chang-Hoon
    • 유체기계공업학회:학술대회논문집
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    • 2006.08a
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    • pp.433-436
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    • 2006
  • In this study we perform Lagrangian stochastic model simulation for heavy particle. Reynolds(2002) construct simple LSM for heavy particle, which lack in detailed parameter study and statistics of turbulent flow within his paper. we investigate more simple but important turbulent statistics such as autocorrelation for velocity and acceleration, Lagrangian structure function and dispersion statistics parameterized by using DNS.

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