29th International Symposium on Rarefied Gas Dynamics
July 13 - 18, 2014, Xi'an, China

Program

Plenary lectures

  • 13th Harold Grad lecture by Mario Pulvirenti
  • Mario PulvirentiMario Pulvirenti was born in Roma on March 30, 1946. He got a Degree in Physics on December 19, 1970. He then became a professore incaricato from 1974 to 1983, an associated professor of fluid mechanics from 1983 at University of Roma, a professor of mechanics at University of L’Aquila from 1986 to 1990, a professor of mechanics at University of Roma from 1990 up to now. His research interests include: statistical mechanics, kinetic theories, fluid dynamics. He is an author of more than 100 publications and 2 monographies and a member of the National Accademia dei Lincei. Below is a short list of the last publications:

    • Boblylev, A. V.; Pulvirenti, M.; Saffirio, C. From particle systems to the Landau equation: a consistency result. Comm. Math. Phys. 319 (2013), no. 3, 683–702.
    • Caprino, S.; Marchioro, C.; Miot, E.; Pulvirenti, M. On the attractive plasma-charge system in 2-d. Comm. Partial Differential Equations 37 (2012), no. 7, 1237–1272.
    • Pulvirenti, M.; Rossi, E. The 2-D constrained NS equation and stochastic vortex theory. Atti Accad. Naz. Lincei Cl. Sci. Fis. Mat. Natur. Rend. Lincei (9) Mat. Appl. 23 (2012), no. 1, 1–27.
    • Athanassoulis, Agissilaos; Paul, Thierry; Pezzotti, Federica; Pulvirenti, Mario Strong semiclassical approximation of Wigner functions for the Hartree dynamics. Atti Accad. Naz. Lincei Cl. Sci. Fis. Mat. Natur. Rend. Lincei (9) Mat. Appl. 22 (2011), no. 4, 525–552.
    • Athanassoulis, Agissilaos; Paul, Thierry; Pezzotti, Federica; Pulvirenti, Mario Semiclassical propagation of coherent states for the Hartree equation. Ann. Henri Poincaré 12 (2011), no. 8, 1613–1634.
    • Marchioro, Carlo; Miot, Evelyne; Pulvirenti, Mario The Cauchy problem for the 3-D Vlasov-Poisson system with point charges. Arch. Ration. Mech. Anal. 201 (2011), no. 1, 1–26.
    • Miot, Evelyne; Pulvirenti, Mario; Saffirio, Chiara On the Kac model for the Landau equation. Kinet. Relat. Models 4 (2011), no. 1, 333–344.

    Quantitative analysis of the correlations in the Boltzmann-Grad limit for hard spheres

    We analyze the j-particle marginals (or rescaled correlation functions) in the Boltzmann-Grad limit for a hard-sphere system. Following the well known Lanford’s analysis on the validity of the Boltzmann equation for a short time, we improve previous results by giving explicit estimates on the error arising from the correlation effects, giving a quantitative description of the property of propagation of chaos.
  • 11th Lloyd Thomas lecture by Alexey Rebrov
  • Alexey RebrovAlexey Rebrov was born in Ukraine on July 30, 1933. He was the Candidate of Technical Sciences (PhD in Engineering) in 1962 and got a Doctor of Technical Sciences degree in 1972. He became the Head of Laboratory of Rarefied Gases in Institute of Thermophysics, Siberian Branch of Russian Academy of Sciences (RAS) in 1966 and has been an adviser of RAS since 2004. Prof. Rebrov is also a full member of RAS, and is a member of the International Advisory Committee of Symposiums on Rarified Gas Dynamics since 1974. His research interests are in the field of physical gas dynamics, the dynamics of dilute gases, in thermophysics, and vacuum engineering.

    Nanostructure synthesis from high velocity gas mixture flows

    Civilization trends are essentially determined by creation of new materials and surface modification approaches. Modern nanotechnologies take in this the prominent place, in particular based on gas dynamic methods. The development of the very well known molecular epitaxy has become the history property. By now the methods of gas dynamic ”dusting”, when accelerated in dusty supersonic flow particles interact with a surface and splice with it, have found practical applications. In the case of a gas jet deposition or deposition from high velocity gas mixture flows the surface coating performs on molecular scale, usually more sophisticated as by molecular epitaxy. The interaction of depositing molecules with a surface can be determined by the concentration diffusion transportation only in quiescent gas. In gas flows the determining role belongs to baro- and thermo-diffusion, initiated by gradients in the flow.

    The gas jet deposition (GJD) is the typical molecular gas dynamic process. One of the first informative presentation of GJD was given in [1]. The essentials of GJD are discussed in the review [2]. Most of studies to that time were devoted to deposition nano-sized films of metals and semi-conductivity materials. Later the usual scheme of GJD was used for synthesis of polymer films of Teflon nature [3]. Polymer films change the surface properties: electric and heat conductivity, friction, hydrophobicity, biocompatibility and so on. And these properties essentially depend on parameters in reactor, where Teflon (polytetrafluorethylene) decomposes and transforms in tetrafluorethylene, depend also  on processes of expansion into vacuum and interaction with a substrate surface. Properties of films can be controlled by geometry and temperature of the permeable obstacle between reactor and substrate. The developed method of production of polymer antibacterial films is based on simultaneous deposition of Teflon and silver particles (nano-clusters) from two different sources.

    Different methods of diamond deposition from gas phase are elaborated beginning from works of Deryagin [4] and Angus [5]. The term “CVD” (Chemical Vapor Deposition) is deeply embedded in the literature. It relates different method of gas mixture activation before deposition: in jets of plasma torch, laser evaporation, in radio frequency plasma cloud and on hot wire surfaces close substrate (HWCVD). We develop the new method, which is based on synthesis from the neutral high velocity gas mixture flows activated on hot surfaces. As distinct from methods mentioned above it permits realize the diamond synthesis in a wide range of pressure from free molecular to continuum regime with a very high specific flow rate. The essential difficulties were surmounted by elaboration of this method. The principal was creation of high temperature reactor providing the stable transportation of activated gases from mixture H2+CH4 to the substrate. Some results of diamond synthesis are published in [6]. The valuable aid for experiments was obtained from the computational modeling of flows by Monte Carlo method. But modeling is confronted by the lack of data on accomodation coefficients and adsorption probability of excited molecules and fragments sticking with diamond or diamond–like surfaces: H2, CH4, C2H2, C2H, CH3, CH2, CH, H. This problem deserving attention of intellects of Lloyd Brewster Thomas or Irving Langmuir level in this particular case is not solved and looks like the challenge for future generations.

    References:

    1.  B.B. Halpern, J.J. Schmitt. Gas jet deposition of multicomponent ultrafine microstructures. Report 03/ONR-F1, June 28,1988.
    2. A. K. Rebrov. Review on gas jet deposition. Proc. of the 4th Int. Conf. on Coating on Glass, Braunschweig, Germany. 2002. p.131.
    3. A.K.  Rebrov at all. Plasma Process. Polym. 2005. v.2. № 6. p.464.
    4. B.V. Deryagin at all. (1969). Symp. Process for Nucleation Growth…, Novosibirsk, USSR.
    5. J.C. Angus, H.A.Will, W.S. Stanko.1968. J. Appl. Phys. 39; 2915-22.
    6. A.K. Rebrov, A.A. Emelyanov, I.B.Yudin. Doklady Akademii Nauk. 2013, v.450, No.1, pp.36-38
  • 2nd Graeme Bird lecture by Michael Gallis
  • Michael GallisMichael Gallis is a member of technical staff in the engineering sciences center of Sandia National Laboratories (SNL), in Albuquerque NM. He received his diploma in mechanical engineering from the National Technical University of Athens, Greece, and Ph.D. in engineering from Imperial College, London, UK. He joined SNL in 1998. His research focuses on numerical modeling of rarefied flow with DSMC.

    Direct Simulation Monte Carlo: The Quest for Speed

    The limited computational power available when the Direct Simulation Monte Carlo (DSMC) method was first introduced1,2 has influenced both the development and the perception of the method ever since. In contrast with continuum alternatives, DSMC appeared to employ overly simplistic models (heuristic in nature) and to lack a solid mathematical foundation. Above all, DSMC was considered to be computationally slow compared to its continuum competitors.

    Over the course of the last fifty years, validation against experimental measurements and the introduction of improved procedures3,4 alleviated most of these concerns. DSMC was demonstrated to produce solutions in agreement with the Boltzmann equation for simple monatomic, non-reacting gas.5 Theoretical work and numerical comparisons for simple gases have demonstrated that DSMC is in fact better at describing the non-equilibrium behavior of gas than the established continuum methods.6,7 More importantly, DSMC can describe molecular processes for which the proper Boltzmann-type transport equations are not even known.

    The probabilistic nature of DSMC introduces numerical error in the form of stochastic noise, absent in traditional fluid formulations. The statistical scatter present in the results from DSMC calculations for rarefied flows has probably been the most unattractive feature of the method. The standard deviation of this scatter is of the order of the inverse square root of the sample size . Thus, any attempt to reduce it requires longer runs or a larger number of simulators. Nevertheless, statistical noise has been shown to be related to the fluctuations in a real gas, yet another indication of the method’s higher physical fidelity8.

    Thus, although DSMC is more rich in physical content and more capable of delivering higher-fidelity simulations than its continuum counterparts, its molecular nature makes DSMC computationally demanding. Even today, more than fifty years since the introduction of DSMC, the quest for speed is the main concern of DSMC researchers as speed appears to limit the range of applicability as well as the level of sophistication of molecular procedures.

    One of the most important, albeit often overlooked, features of DSMC is that DSMC is naturally parallelizable. Particle-simulation methods have been known to be favored in parallel implementations in comparison with partial-differential-equation solvers. As computer power approaches the exascale regime, this feature of DSMC may provide the necessary speedup that will lead to wider applicability, improved sophistication, and higher accuracy. Before the benefits of this new computational power could be realized, however, a drastic redesign of DSMC software is required. In this presentation, the current status and possible future developments of DSMC are reviewed and discussed in the light of the further increases in computer capacity that can be reasonably expected.

    References

    1. G. A. Bird, Phys. Fluids 6, 1518-1519 (1963).
    2. G. A. Bird, Molecular Gas Dynamics, OxfordUniversity Press, 1976.
    3. G. A. Bird, Molecular Gas Dynamics and the Direct Simulation of Gas Flows, Oxford Science Publications, Oxford, 1994.
    4. G. A. Bird, The DSMC Method, Version 1.1, 2013.
    5. W. Wagner, J. Stat. Phys. 66, 1011 (1992).
    6. V. Garzό and A. Santos, Kinetic Theory of Gases in Shear Flows, Kluwer Academic Publishers, 2003.
    7. M. A. Gallis, J. R. Torczynski, and D. J. Rader, Phys. Rev. E 69, 042201 (2004).

Topics

Papers are invited to be presented in one of the following sessions:

  • Boltzmann and Related Equations
  • Clusters and Aerosols
  • DSMC and Related Simulations
  • Experimental Procedures in RGD
  • Gas-Surface Interactions
  • Granular Fluids
  • Hybrid Methods
  • Jet and Plumes
  • Kinetic and Transport Theory
  • Micro- and Nano-scale Flows and Devices
  • Molecular Beam and Collisions
  • Molecular Dynamics Simulations
  • Numerical Solutions of Kinetic Equations
  • Particle Methods for Flow Simulations
  • Plasma Flows and Processing
  • Radiation and Plasma Flows
  • RGD in Astrophysics
  • Reaction and Relaxation Processes
  • Space Vehicles Aerodynamics
  • Turbulence
  • Vacuum Gas Dynamics