- Email: [email protected]
Mesoscopic Methods in Engineering and Science
Computers and Mathematics with Applications 67 (2014) 237–238
Contents lists available at ScienceDirect
Computers and Mathematics with Applications journal homepage: www.elsevier.com/locate/camwa
Editorial
Mesoscopic Methods in Engineering and Science
Matter, conceptually classified into fluids and solids, can be completely described by the microscopic physics of its constituent atoms or molecules. However, for most engineering applications a macroscopic or continuum description has usually been sufficient, because of the large disparity between the spatial and temporal scales relevant to these applications and the scales of the underlying molecular dynamics. In this case, the microscopic physics merely determines material properties such as the viscosity of a fluid or the elastic constants of a solid. These material properties cannot be derived within the macroscopic framework, but the qualitative nature of the macroscopic dynamics is usually insensitive to the details of the underlying microscopic interactions. The traditional picture of the role of microscopic and macroscopic physics is now being challenged as new multi-scale and multi-physics problems begin to emerge. For example, in nano-scale systems, the assumption of scale separation breaks down; macroscopic theory is therefore inadequate, yet microscopic theory may be impractical because it requires computational capabilities far beyond our present reach. This new class of problems poses unprecedented challenges to mathematical modeling as well as numerical simulation and requires new and non-traditional analysis and modeling paradigms. Methods based on mesoscopic theories, which connect the microscopic and macroscopic descriptions of the dynamics, provide a promising approach. They can lead to useful models, possibly requiring empirical inputs to determine some of the model parameters, which are sub-macroscopic, yet indispensable to the relevant physical phenomena. The area of complex fluids focuses on materials such as suspensions, emulsions and gels, where the internal structure is relevant to the macroscopic dynamics. An important challenge will be to construct meaningful mesoscopic models by extracting all the macroscopically relevant information from the microscopic dynamics. There already exist a few mesoscopic methods such as the Lattice Gas Cellular Automata (LGCA), the Lattice Boltzmann Equation (LBE), Discrete Velocity Models (DVM) of the Boltzmann equation, Gas-Kinetic Schemes (GKS), Smoothed Particle Hydrodynamics (SPH) and Dissipative Particle Dynamics (DPD). Although these methods are sometimes designed for macroscopic hydrodynamics, they are not based upon the Navier–Stokes equations; instead, they are closely related to kinetic theory and the Boltzmann equation. These methods are promising candidates to effectively connect microscopic and macroscopic scales and thereby substantially extend the capabilities of numerical simulations. For this reason, they are the focus of the International Conferences on Mesoscopic Methods in Engineering and Science (ICMMES, http://www.icmmes.org). The Nineth ICMMES Conference was held in Institute of Applied Mechanics, National Taiwan University, Taipei, Taiwan, July 23–27, 2011. This special issue of the Computers and Mathematics with Applications devoted to this conference includes nineteen selected and peer-reviewed papers on a wide range of topics related to the focused areas of ICMMES covering theory and analysis [1,2], modeling [3], numerical simulations of various fluid systems [4–16], and algorithm implementations and optimizations on different hardware platforms [17–19], In particular, the papers in this proceedings covers topics of the analysis of the rotational invariance of lattice Boltzmann schemes [1], DVM models [2,18], hybrid molecular-continuum methods [3], simulations of droplet dynamics [4,5] and droplet boundary interactions [6], lattice-Boltzmann scheme for freesurface flows and its applications [7,8], lattice Boltzmann models for multi-component flows [9] and multiphase flows [10], simulations of particles [11] and sediments [12] in turbulent flows, flows through porous media [13–15], the mechanism of axis switching in jets [16], rotational turbulence [17], and implementation of algorithms on graphic processing units [17–19]. The editors would like to thank the referees who helped to review the papers in this special issue. The organizers of the ICMMES-2012 and the ICMMES Scientific Committee would like to acknowledge the generous support from National Science Council, Taiwan, Center for Quantum Science and Engineering (CQSE) and Institute of Applied Mechanics, National Taiwan University, the Computational Science Research Center (CSRC), Beijing, and donations from NVIDIA. We would also like to thank Institute for Computational Modeling in Civil Engineering (iRMB) at Technische Universität Braunschweig, Germany, and Research Foundation at Old Dominion University, USA, for logistic support. 0898-1221/$ – see front matter © 2014 Published by Elsevier Ltd http://dx.doi.org/10.1016/j.camwa.2013.11.015
238
Editorial / Computers and Mathematics with Applications 67 (2014) 237–238
References [1] Adeline Augier, François Dubois, Benjamin Graille, Pierre Lallemand, On rotational invariance of lattice Boltzmann schemes, Comput. Math. Appl. 67 (2) (2014) 239–255. [2] Hans Babovsky, Discrete kinetic models in the fluid dynamic limit, Comput. Math. Appl. 67 (2) (2014) 256–271. [3] Philipp Neumann, Wolfgang Eckhardt, Hans-Joachim Bungartz, Hybrid molecular-continuum methods: From prototypes to coupling software, Comput. Math. Appl. 67 (2) (2014) 272–281. [4] Lina Baroudi, Masahiro Kawaji, Taehun Lee, Effects of initial conditions on the simulation of inertial coalescence of two drops, Comput. Math. Appl. 67 (2) (2014) 282–289. [5] Kuo-Long Pan, Zhi-Jen Chen, Simulation of bubble dynamics in a microchannel using a fronttracking method, Comput. Math. Appl. 67 (2) (2014) 290–306. [6] Ming Cheng, Jing Lou, Lattice Boltzmann simulation of a drop impact on a moving wall with a liquid film, Comput. Math. Appl. 67 (2) (2014) 307–317. [7] Regina Ammer, Matthias Markl, Ulric Ljungblad, Carolin Körner, Ulrich Rüde, Simulating fast electron beam melting with a parallel thermal free surface lattice Boltzmann method, Comput. Math. Appl. 67 (2) (2014) 318–330. [8] Daniela Anderl, Simon Bogner, Cornelia Rauh, Ulrich Rüde, Antonio Delgado, Free surface lattice Boltzmann with enhanced bubble model, Comput. Math. Appl. 67 (2) (2014) 331–339. [9] Alexander L. Kupershtokh, Three-dimensional LBE simulations of a decay of liquid dielectrics with a solute gas into the system of gas–vapor channels under the action of strong electric fields, Comput. Math. Appl. 67 (2) (2014) 340–349. [10] Daniel Lycett-Brown, Kai H. Luo, Multiphase cascaded lattice Boltzmann method, Comput. Math. Appl. 67 (2) (2014) 350–362. [11] Lian-Ping Wang, Orlando Ayala, Hui Gao, Charles Andersen, Kevin Mathews, Study of forced turbulence and its modulation by finite-size solid particles using the lattice Boltzmann approach, Comput. Math. Appl. 67 (2) (2014) 363–380. [12] Jinfeng Zhang, Qinghe Zhang, Guangquan Qiao, A lattice Boltzmann model for the non-equilibrium flocculation of cohesive sediments in turbulent flow, Comput. Math. Appl. 67 (2) (2014) 381–392. [13] Uktam R. Salomov, Eliodoro Chiavazzo, Pietro Asinari, Pore-scale modeling of fluid flow through gas diffusion and catalyst layers for high temperature proton exchange membrane (HT-PEM) fuel cells, Comput. Math. Appl. 67 (2) (2014) 393–411. [14] Yumei Yong, Sha Li, Chao Yang, Xiaolong Yin, Direct simulation of influence of pore structure on diffusion process in porous media, Comput. Math. Appl. 67 (2) (2014) 412–423. [15] Mohammad Taghilou, Mohammad H. Rahimian, Investigation of two-phase flow in porous media using lattice Boltzmann method, Comput. Math. Appl. 67 (2) (2014) 424–436. [16] Nan Chen, Huidan Yu, Mechanism of axis switching in low aspect-ratio rectangular jets, Comput. Math. Appl. 67 (2) (2014) 437–444. [17] Huidan Yu, Rou Chen, Hengjie Wang, Zhi Yuan, Ye Zhao, Yiran An, Yousheng Xu, Luoding Zhu, GPU accelerated lattice Boltzmann simulation for rotational turbulence, Comput. Math. Appl. 67 (2) (2014) 445–451. [18] Stefan Brechtken, GPU and CPU acceleration of a class of kinetic lattice group models, Comput. Math. Appl. 67 (2) (2014) 452–461. [19] Nicolas Delbosc, Jonathan L. Summers, Amirul Khan, Nik Kapur, Cath J. Noakes, Optimised implementation of the lattice Boltzmann method on a graphics processing unit towards real-time fluid simulation, Comput. Math. Appl. 67 (2) (2014) 462–475.
Professor Jaw-Yen Yang 1 Institute of Applied Mechanics and Center for Quantum Science and Engineering (CQSE), National Taiwan University, Taipei 10764, Taiwan E-mail address: [email protected]. Professor Chao-An Lin 2 Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan E-mail address: [email protected]. Professor Li-Shi Luo 3 Department of Mathematics & Statistics, Old Dominion University, Norfolk, Virginia 23529, USA Computational Science Research Center, Beijing 100084, China E-mail address: [email protected]. URL: http://www.lions.odu.edu/∼lluo. Professor Manfred Krafczyk 4 Institut für rechnergestützte, Modellierung im Bauingenieurwesen (iRMB), Institute for Computational Modeling in Civil Engineering, Technische Universität Carola-Wilhelmina zu Braunschweig, Pockelsstr. 3, 38106 Braunschweig, Germany E-mail address: [email protected]. URL: http://www.irmb.tu-bs.de. 1 2 3 4
Tel.: +886 2 3366 5636; fax: +886 2 2363 9290. Tel.: +886 3 5722 840. Tel.: +1 757 683 5295; fax: +1 757 683 3885. Tel.: +49 531 391 94500; fax: +49 531 391 94511.
Contents lists available at ScienceDirect
Computers and Mathematics with Applications journal homepage: www.elsevier.com/locate/camwa
Editorial
Mesoscopic Methods in Engineering and Science
Matter, conceptually classified into fluids and solids, can be completely described by the microscopic physics of its constituent atoms or molecules. However, for most engineering applications a macroscopic or continuum description has usually been sufficient, because of the large disparity between the spatial and temporal scales relevant to these applications and the scales of the underlying molecular dynamics. In this case, the microscopic physics merely determines material properties such as the viscosity of a fluid or the elastic constants of a solid. These material properties cannot be derived within the macroscopic framework, but the qualitative nature of the macroscopic dynamics is usually insensitive to the details of the underlying microscopic interactions. The traditional picture of the role of microscopic and macroscopic physics is now being challenged as new multi-scale and multi-physics problems begin to emerge. For example, in nano-scale systems, the assumption of scale separation breaks down; macroscopic theory is therefore inadequate, yet microscopic theory may be impractical because it requires computational capabilities far beyond our present reach. This new class of problems poses unprecedented challenges to mathematical modeling as well as numerical simulation and requires new and non-traditional analysis and modeling paradigms. Methods based on mesoscopic theories, which connect the microscopic and macroscopic descriptions of the dynamics, provide a promising approach. They can lead to useful models, possibly requiring empirical inputs to determine some of the model parameters, which are sub-macroscopic, yet indispensable to the relevant physical phenomena. The area of complex fluids focuses on materials such as suspensions, emulsions and gels, where the internal structure is relevant to the macroscopic dynamics. An important challenge will be to construct meaningful mesoscopic models by extracting all the macroscopically relevant information from the microscopic dynamics. There already exist a few mesoscopic methods such as the Lattice Gas Cellular Automata (LGCA), the Lattice Boltzmann Equation (LBE), Discrete Velocity Models (DVM) of the Boltzmann equation, Gas-Kinetic Schemes (GKS), Smoothed Particle Hydrodynamics (SPH) and Dissipative Particle Dynamics (DPD). Although these methods are sometimes designed for macroscopic hydrodynamics, they are not based upon the Navier–Stokes equations; instead, they are closely related to kinetic theory and the Boltzmann equation. These methods are promising candidates to effectively connect microscopic and macroscopic scales and thereby substantially extend the capabilities of numerical simulations. For this reason, they are the focus of the International Conferences on Mesoscopic Methods in Engineering and Science (ICMMES, http://www.icmmes.org). The Nineth ICMMES Conference was held in Institute of Applied Mechanics, National Taiwan University, Taipei, Taiwan, July 23–27, 2011. This special issue of the Computers and Mathematics with Applications devoted to this conference includes nineteen selected and peer-reviewed papers on a wide range of topics related to the focused areas of ICMMES covering theory and analysis [1,2], modeling [3], numerical simulations of various fluid systems [4–16], and algorithm implementations and optimizations on different hardware platforms [17–19], In particular, the papers in this proceedings covers topics of the analysis of the rotational invariance of lattice Boltzmann schemes [1], DVM models [2,18], hybrid molecular-continuum methods [3], simulations of droplet dynamics [4,5] and droplet boundary interactions [6], lattice-Boltzmann scheme for freesurface flows and its applications [7,8], lattice Boltzmann models for multi-component flows [9] and multiphase flows [10], simulations of particles [11] and sediments [12] in turbulent flows, flows through porous media [13–15], the mechanism of axis switching in jets [16], rotational turbulence [17], and implementation of algorithms on graphic processing units [17–19]. The editors would like to thank the referees who helped to review the papers in this special issue. The organizers of the ICMMES-2012 and the ICMMES Scientific Committee would like to acknowledge the generous support from National Science Council, Taiwan, Center for Quantum Science and Engineering (CQSE) and Institute of Applied Mechanics, National Taiwan University, the Computational Science Research Center (CSRC), Beijing, and donations from NVIDIA. We would also like to thank Institute for Computational Modeling in Civil Engineering (iRMB) at Technische Universität Braunschweig, Germany, and Research Foundation at Old Dominion University, USA, for logistic support. 0898-1221/$ – see front matter © 2014 Published by Elsevier Ltd http://dx.doi.org/10.1016/j.camwa.2013.11.015
238
Editorial / Computers and Mathematics with Applications 67 (2014) 237–238
References [1] Adeline Augier, François Dubois, Benjamin Graille, Pierre Lallemand, On rotational invariance of lattice Boltzmann schemes, Comput. Math. Appl. 67 (2) (2014) 239–255. [2] Hans Babovsky, Discrete kinetic models in the fluid dynamic limit, Comput. Math. Appl. 67 (2) (2014) 256–271. [3] Philipp Neumann, Wolfgang Eckhardt, Hans-Joachim Bungartz, Hybrid molecular-continuum methods: From prototypes to coupling software, Comput. Math. Appl. 67 (2) (2014) 272–281. [4] Lina Baroudi, Masahiro Kawaji, Taehun Lee, Effects of initial conditions on the simulation of inertial coalescence of two drops, Comput. Math. Appl. 67 (2) (2014) 282–289. [5] Kuo-Long Pan, Zhi-Jen Chen, Simulation of bubble dynamics in a microchannel using a fronttracking method, Comput. Math. Appl. 67 (2) (2014) 290–306. [6] Ming Cheng, Jing Lou, Lattice Boltzmann simulation of a drop impact on a moving wall with a liquid film, Comput. Math. Appl. 67 (2) (2014) 307–317. [7] Regina Ammer, Matthias Markl, Ulric Ljungblad, Carolin Körner, Ulrich Rüde, Simulating fast electron beam melting with a parallel thermal free surface lattice Boltzmann method, Comput. Math. Appl. 67 (2) (2014) 318–330. [8] Daniela Anderl, Simon Bogner, Cornelia Rauh, Ulrich Rüde, Antonio Delgado, Free surface lattice Boltzmann with enhanced bubble model, Comput. Math. Appl. 67 (2) (2014) 331–339. [9] Alexander L. Kupershtokh, Three-dimensional LBE simulations of a decay of liquid dielectrics with a solute gas into the system of gas–vapor channels under the action of strong electric fields, Comput. Math. Appl. 67 (2) (2014) 340–349. [10] Daniel Lycett-Brown, Kai H. Luo, Multiphase cascaded lattice Boltzmann method, Comput. Math. Appl. 67 (2) (2014) 350–362. [11] Lian-Ping Wang, Orlando Ayala, Hui Gao, Charles Andersen, Kevin Mathews, Study of forced turbulence and its modulation by finite-size solid particles using the lattice Boltzmann approach, Comput. Math. Appl. 67 (2) (2014) 363–380. [12] Jinfeng Zhang, Qinghe Zhang, Guangquan Qiao, A lattice Boltzmann model for the non-equilibrium flocculation of cohesive sediments in turbulent flow, Comput. Math. Appl. 67 (2) (2014) 381–392. [13] Uktam R. Salomov, Eliodoro Chiavazzo, Pietro Asinari, Pore-scale modeling of fluid flow through gas diffusion and catalyst layers for high temperature proton exchange membrane (HT-PEM) fuel cells, Comput. Math. Appl. 67 (2) (2014) 393–411. [14] Yumei Yong, Sha Li, Chao Yang, Xiaolong Yin, Direct simulation of influence of pore structure on diffusion process in porous media, Comput. Math. Appl. 67 (2) (2014) 412–423. [15] Mohammad Taghilou, Mohammad H. Rahimian, Investigation of two-phase flow in porous media using lattice Boltzmann method, Comput. Math. Appl. 67 (2) (2014) 424–436. [16] Nan Chen, Huidan Yu, Mechanism of axis switching in low aspect-ratio rectangular jets, Comput. Math. Appl. 67 (2) (2014) 437–444. [17] Huidan Yu, Rou Chen, Hengjie Wang, Zhi Yuan, Ye Zhao, Yiran An, Yousheng Xu, Luoding Zhu, GPU accelerated lattice Boltzmann simulation for rotational turbulence, Comput. Math. Appl. 67 (2) (2014) 445–451. [18] Stefan Brechtken, GPU and CPU acceleration of a class of kinetic lattice group models, Comput. Math. Appl. 67 (2) (2014) 452–461. [19] Nicolas Delbosc, Jonathan L. Summers, Amirul Khan, Nik Kapur, Cath J. Noakes, Optimised implementation of the lattice Boltzmann method on a graphics processing unit towards real-time fluid simulation, Comput. Math. Appl. 67 (2) (2014) 462–475.
Professor Jaw-Yen Yang 1 Institute of Applied Mechanics and Center for Quantum Science and Engineering (CQSE), National Taiwan University, Taipei 10764, Taiwan E-mail address: [email protected]. Professor Chao-An Lin 2 Department of Power Mechanical Engineering, National Tsing Hua University, Hsinchu 30013, Taiwan E-mail address: [email protected]. Professor Li-Shi Luo 3 Department of Mathematics & Statistics, Old Dominion University, Norfolk, Virginia 23529, USA Computational Science Research Center, Beijing 100084, China E-mail address: [email protected]. URL: http://www.lions.odu.edu/∼lluo. Professor Manfred Krafczyk 4 Institut für rechnergestützte, Modellierung im Bauingenieurwesen (iRMB), Institute for Computational Modeling in Civil Engineering, Technische Universität Carola-Wilhelmina zu Braunschweig, Pockelsstr. 3, 38106 Braunschweig, Germany E-mail address: [email protected]. URL: http://www.irmb.tu-bs.de. 1 2 3 4
Tel.: +886 2 3366 5636; fax: +886 2 2363 9290. Tel.: +886 3 5722 840. Tel.: +1 757 683 5295; fax: +1 757 683 3885. Tel.: +49 531 391 94500; fax: +49 531 391 94511.