• Title/Summary/Keyword: Brownian dynamics

Search Result 40, Processing Time 0.031 seconds

Simulation of particle filtration by Brownian dynamics (Brownian dynamics 를 이용한 입자 포집 모사)

  • Bang, Jong-Geun;Yoon, Yoong-Sup
    • Proceedings of the KSME Conference
    • /
    • 2008.11a
    • /
    • pp.1922-1927
    • /
    • 2008
  • In the present study, deposition of discrete and small particles, which diameter is less than $1{\mu}m$, on a filter element was simulated by stochastic method. Trajectory of each particle was numerically solved by Langevin equation and Brownian random motion was treated by Brownian dynamics. Lattice Boltzmann method (LBM) was used to solve flow field around the filter collector and deposit layer. Interaction between flow field and deposit layer was obtained from a converged solution from an inner-loop calculation. Simulation method is properly validated and collection efficiency due to different filtration parameters are examined and discussed. Morphology of deposit layer and its evolution was visualized in terms of the particle size. The particle loaded effect on collection efficiency was also discussed.

  • PDF

First Passage Time between Ends of a Polymer Chain

  • Sung, Jae-Young
    • Journal of the Korean Chemical Society
    • /
    • v.51 no.3
    • /
    • pp.227-231
    • /
    • 2007
  • We improve Wilehemski-Fixmann theory for intrachain reaction dynamics of a polymer chain by taking into account excluded volume effects between reactive groups in the polymerchain. An approximate analytic expression for the intra-chain reaction dynamics is obtained for Gaussian chain model and compared to Brownian dynamics simulation results. The results of the present theory are in a better agreement to Brownian dynamics simulation results than those calculated by previously reported theories.

Phase Separation of Lennard-Jones Particles Using Molecular Dynamics and Brownian Dynamics Simulations

  • Jeong, Ji-Yun;Lee, Ju-Min;Kim, Jun-Su
    • Proceeding of EDISON Challenge
    • /
    • 2014.03a
    • /
    • pp.169-182
    • /
    • 2014
  • 이 연구에서는 Lennard-Jones (LJ) particle을 이용하여 상분리 현상을 이해하기 위한 컴퓨터 시뮬레이션 연구를 수행하였다. 초기에 균일하게 분포되어 있는 LJ 입자들을 시뮬레이션 하면 상대적으로 dense phase와 dilute phase로 상분리 현상이 일어나게 된다. 상분리 현상의 첫 번째 단계를 핵 생성 (nucleation) 이라고 한다. 본 연구에서는 Brownian Dynamics (BD) Simulation과 Molecular Dynamics (MD) Simulation을 이용하여 상평형 그림을 구하고 초기에 일어나는 LJ 입자들의 nucleation rates를 구하였다.

  • PDF

WHITE NOISE APPROACH TO FEYNMAN INTEGRALS

  • Hida, Takeyuki
    • Journal of the Korean Mathematical Society
    • /
    • v.38 no.2
    • /
    • pp.275-281
    • /
    • 2001
  • The trajectory of a classical dynamics is determined by the least action principle. As soon as we come to quantum dynamics, we have to consider all possible trajectories which are proposed to be a sum of the classical trajectory and Brownian fluctuation. Thus, the action involves the square of the derivative B(t) (white noise) of a Brownian motion B(t). The square is a typical example of a generalized white noise functional. The Feynman propagator should therefore be an average of a certain generalized white noise functional. This idea can be applied to a large class of dynamics with various kinds of Lagrangians.

  • PDF

Computation of dilute polymer solution flows using BCF-RBFN based method and domain decomposition technique

  • Tran, Canh-Dung;Phillips, David G.;Tran-Cong, Thanh
    • Korea-Australia Rheology Journal
    • /
    • v.21 no.1
    • /
    • pp.1-12
    • /
    • 2009
  • This paper reports the suitability of a domain decomposition technique for the hybrid simulation of dilute polymer solution flows using Eulerian Brownian dynamics and Radial Basis Function Networks (RBFN) based methods. The Brownian Configuration Fields (BCF) and RBFN method incorporates the features of the BCF scheme (which render both closed form constitutive equations and a particle tracking process unnecessary) and a mesh-less method (which eliminates element-based discretisation of domains). However, when dealing with large scale problems, there appear several difficulties: the high computational time associated with the Stochastic Simulation Technique (SST), and the ill-condition of the system matrix associated with the RBFN. One way to overcome these disadvantages is to use parallel domain decomposition (DD) techniques. This approach makes the BCF-RBFN method more suitable for large scale problems.

Analysis of Filtration Performance by Brownian Dynamics (Brownian Dynamics 를 이용한 입자 포집 과정 및 여과 성능 해석)

  • Bang, Jong-Geun;Yoon, Yoong-Sup
    • Transactions of the Korean Society of Mechanical Engineers B
    • /
    • v.33 no.10
    • /
    • pp.811-819
    • /
    • 2009
  • In the present study, deposition of discrete and small particles on a filter fiber was simulated by stochastic method. Trajectory of each particle was numerically solved by Langevin equation. And Lattice Boltzmann method (LBM) was used to solve flow field around the filter collector for considering complex shape of deposit layer. Interaction between the flow field and the deposit layer was obtained from a converged solution from an inner-loop calculation. Simulation method is properly validated with filtration theory and collection efficiency due to different filtration parameters are examined and discussed. Morphology of deposit layer and its evolution was visualized in terms of the particle size. The particle loaded effect on collection efficiency was also discussed.

Computation of viscoelastic flow using neural networks and stochastic simulation

  • Tran-Canh, D.;Tran-Cong, T.
    • Korea-Australia Rheology Journal
    • /
    • v.14 no.4
    • /
    • pp.161-174
    • /
    • 2002
  • A new technique for numerical calculation of viscoelastic flow based on the combination of Neural Net-works (NN) and Brownian Dynamics simulation or Stochastic Simulation Technique (SST) is presented in this paper. This method uses a "universal approximator" based on neural network methodology in combination with the kinetic theory of polymeric liquid in which the stress is computed from the molecular configuration rather than from closed form constitutive equations. Thus the new method obviates not only the need for a rheological constitutive equation to describe the fluid (as in the original Calculation Of Non-Newtonian Flows: Finite Elements St Stochastic Simulation Techniques (CONNFFESSIT) idea) but also any kind of finite element-type discretisation of the domain and its boundary for numerical solution of the governing PDE's. As an illustration of the method, the time development of the planar Couette flow is studied for two molecular kinetic models with finite extensibility, namely the Finitely Extensible Nonlinear Elastic (FENE) and FENE-Peterlin (FENE-P) models.P) models.