Pseudo-particle modeling (PPM) is a particle method (PM) proposed in 1996. Though it is effective for the simulation of microscopic particle-fluid systems, its application to practical systems is still limited by comp...Pseudo-particle modeling (PPM) is a particle method (PM) proposed in 1996. Though it is effective for the simulation of microscopic particle-fluid systems, its application to practical systems is still limited by computational cost. In this note, we speed up the computation by using a combination of weighted averaging with finite difference techniques to upgrade the particle interactions to a fluid element level, which conforms to the Navier-Stokes equation. The approach, abbreviated to MaPPM, is then applied to the problem of one-dimensional Poiseuille flow with a quantitative comparison to the results of another related PM--smoothed particle hydrodynamics (SPH), where the accuracy and efficiency of MaPPM is found to be much better than that of SPH. Flows around a cylinder and multiple freely moving particles are also simulated with the new model, resulting in reasonable flow pattern and drag coefficient. The convergence and robustness of the algorithm prove promising.展开更多
Fluidization is a process of wide application, but its dynamic behavior is not well understood because of its multi-scale heterogeneity and regime multiplicity which are difficult to simulate in traditional numerical ...Fluidization is a process of wide application, but its dynamic behavior is not well understood because of its multi-scale heterogeneity and regime multiplicity which are difficult to simulate in traditional numerical methods. By discretizing the fluid phase into a large number of interactive simple particles, which can incorporate many-body moving boundaries easily, pseudo-particle modeling (PPM) has re-produced reasonable radial and axial heterogeneity on macro-scale as well as solids clustering and fluid flows on meso- and micro-scales. The simulation suggests a consistent evolution of the complexity across different scales with itself serving as an ideal exploring tool.展开更多
By applying a general algorithm to different particle models, i.e. molecular dynamic (MD) and macro-scale pseudo-particle models (MaPPM), two physical phenomena of distinct nature and scale differences, i.e. the mutua...By applying a general algorithm to different particle models, i.e. molecular dynamic (MD) and macro-scale pseudo-particle models (MaPPM), two physical phenomena of distinct nature and scale differences, i.e. the mutual diffusion of two gases and the instability on the interface between two fluids, are simulated successfully. It demonstrates the possibility that the general algorithms of good parallelism and software of modular architecture can be established for complex physical systems based on the particle methods (PMs), which will thereby develop into a mainstream approach as finite element (FE) and finite difference (FD) approaches.展开更多
The multi-scale structures of complex flows have been great challenges to both theoretical and engineer-ing researches, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constit...The multi-scale structures of complex flows have been great challenges to both theoretical and engineer-ing researches, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constitutors and powerful probes of multi-scale models, owing to their physical insight and computational simplicity. In this paper, the role of different PMs for multi-scale modeling of complex flows is critically reviewed and possible development of PMs in this background is prospected, with the emphasis on pseudo-particle modeling (PPM). The performances of some different PMs are compared in simulations and new devel-opment in the fundamentals and applications of PPM is also reported, demonstrating PPM as a unique PM for multi-scale modeling.展开更多
The velocity profiles and temperature distributions of gas flow in microchannels, for Knudsen numbers ranging from 0.01 to 0.20, are investigated with pseudo-particle modeling (PPM). It has been found that the velocit...The velocity profiles and temperature distributions of gas flow in microchannels, for Knudsen numbers ranging from 0.01 to 0.20, are investigated with pseudo-particle modeling (PPM). It has been found that the velocity profiles are mainly affected by Knudsen number and the external force fields applied. When Knudsen number was increased, the slip velocities on the walls increased at the beginning, and then decreased. The temperature distributions were also significantly affected by the external force. The Darcy friction factor increased with increasing Knudsen number, and its variation with Mach number under increased Knudsen number was similar to the so-called premature laminar-turbulent transition observed in experiments.展开更多
The multi-scale structures of complex flows in chemical engineering have been great challenges to the design and scaling of such systems, and multi-scale modeling is the natural way in response. Particle methods (PMs)...The multi-scale structures of complex flows in chemical engineering have been great challenges to the design and scaling of such systems, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constituents and powerful tools of multi-scale models, owing to their physical fidelity and computational simplicity. Especially, pseudo-particle modeling (PPM, Ge & Li, 1996; Ge & Li, 2003) is most suitable for molecular scale flow prediction and exploration of the origin of multi-scale structures; macro-scale PPM (MaPPM, Ge & Li, 2001) and similar models are advantageous for meso-scale simulations of flows with complex and dynamic discontinuity, while the lattice Boltzmann model is more competent for homogeneous media in complex geometries; and meso-scale methods such as dissipative particle dynamics are unique tools for complex fluids of uncertain properties or flows with strong thermal fluctuations. All these methods are favorable for seamless interconnection of models for different scales. However, as PMs are not originally designed as either tools for complexity or constituents of multi-scale models, further improvements are expected. PPM is proposed for microscopic simulation of particle-fluid systems as a combination of molecular dynamics (MD) and direct simulation Monte-Carlo (DSMC). The collision dynamics in PPM is identical to that of hard-sphere MD, so that mass, momentum and energy are conserved to machine accuracy. However, the collision detection procedure, which is most time-consuming and difficult to be parallelized for hard-sphere MD, has been greatly simplified to a procedure identical to that of soft-sphere MD. Actually, the physical model behind such a treatment is essentially different from MD and is more similar to DSMC, but an intrinsic difference is that in DSMC the collisions follow designed statistical rules that are reflection of the real physical processes only in very limited cases such as dilute gas. PPM is ideal for exploring the mechanism of complex flows a展开更多
Pseudo-Particle Modeling （PPM） is a particle method proposed by Ge and Li in 1996 [Ge, W., ＆ Li, J. （1996）. Pseudo-particle approach to hydrodynamics of particle-fluid systems, in M. Kwauk ＆ J. Li （Eds.）, Proc...Pseudo-Particle Modeling （PPM） is a particle method proposed by Ge and Li in 1996 [Ge, W., ＆ Li, J. （1996）. Pseudo-particle approach to hydrodynamics of particle-fluid systems, in M. Kwauk ＆ J. Li （Eds.）, Proceedings of the 5th international conference on drculating fluidized bed （pp. 260-265）. Beijing： Science Press] and has been used to explore the microscopic mechanism in complex particle-fluid systems. But as a particle method, high computational cost remains a main obstacle for its large-scale application; therefore, parallel implementation of this method is highly desirable. Parallelization of two-dimensional PPM was carried out by spatial decomposition in this paper. The time costs of the major functions in the program were analyzed and the program was then optimized for higher efficiency by dynamic load balancing and resetting of particle arrays. Finally, simulation on a gas-solid fluidized bed with 102,400 solid particles and 1.8 × 10^7 pseudo-particles was performed successfully with this code, indicating its scalability in future applications.展开更多
A parallel algorithm suitable for simulating multi-sized particle systems and multi- phase fluid systems is proposed based on macro-scale pseudo-particle modeling (MaPPM). The algorithm employs space-decomposition of ...A parallel algorithm suitable for simulating multi-sized particle systems and multi- phase fluid systems is proposed based on macro-scale pseudo-particle modeling (MaPPM). The algorithm employs space-decomposition of the computational load among the processing ele- ments (PEs) and multi-level cell-subdivision technique for particle indexing. In this algorithm, a 2D gas-solid system is simulated with the temporal variations of drags on solids, inter-phase slip velocities and solids concentration elaborately monitored. Analysis of the results shows that the algorithm is of good parallel efficiency and scalability, demonstrating the unique advantage of MaPPM in simulating complex flows.展开更多
Pseudo-particle modeling （PPM）, a molecular modeling method which combines time-driven algorithms and hard molecule modeling, was originally developed for simulating gas in complex multiphase systems （Ge ＆ Li, 200...Pseudo-particle modeling （PPM）, a molecular modeling method which combines time-driven algorithms and hard molecule modeling, was originally developed for simulating gas in complex multiphase systems （Ge ＆ Li, 2003; Ge et al., 2005; Ge, 1998）. In this work, the properties of two- and three-dimensional pseudo-particle systems, namely, mean free path, compressibility factor, self-diffusion coefficient and shear viscosity, are systematically measured by using PPM. it is found that in terms of an effective diameter, the results well conform to the Chapman-Enskog theory, thus suggesting that PPM can be employed to simulate the micro- and meso-scale behavior of ordinary gas and fluid flows.展开更多
基金This work was supported by the National Key Program for Developing Basic Sciences (Grant No. Gl 999032801).
文摘Pseudo-particle modeling (PPM) is a particle method (PM) proposed in 1996. Though it is effective for the simulation of microscopic particle-fluid systems, its application to practical systems is still limited by computational cost. In this note, we speed up the computation by using a combination of weighted averaging with finite difference techniques to upgrade the particle interactions to a fluid element level, which conforms to the Navier-Stokes equation. The approach, abbreviated to MaPPM, is then applied to the problem of one-dimensional Poiseuille flow with a quantitative comparison to the results of another related PM--smoothed particle hydrodynamics (SPH), where the accuracy and efficiency of MaPPM is found to be much better than that of SPH. Flows around a cylinder and multiple freely moving particles are also simulated with the new model, resulting in reasonable flow pattern and drag coefficient. The convergence and robustness of the algorithm prove promising.
基金supported by the National Natural Science Foundation of China(Grant No.20176059)China National Key Projects for Developing Basic Sciences(Grant Nos.G1999032801 and G1999022103).
文摘Fluidization is a process of wide application, but its dynamic behavior is not well understood because of its multi-scale heterogeneity and regime multiplicity which are difficult to simulate in traditional numerical methods. By discretizing the fluid phase into a large number of interactive simple particles, which can incorporate many-body moving boundaries easily, pseudo-particle modeling (PPM) has re-produced reasonable radial and axial heterogeneity on macro-scale as well as solids clustering and fluid flows on meso- and micro-scales. The simulation suggests a consistent evolution of the complexity across different scales with itself serving as an ideal exploring tool.
基金This work was supported by the National Key Program for Developing Basic Sciences (Grant No. G1999032801)the National Natural Science Foundation of China (Grant No. 20176059).
文摘By applying a general algorithm to different particle models, i.e. molecular dynamic (MD) and macro-scale pseudo-particle models (MaPPM), two physical phenomena of distinct nature and scale differences, i.e. the mutual diffusion of two gases and the instability on the interface between two fluids, are simulated successfully. It demonstrates the possibility that the general algorithms of good parallelism and software of modular architecture can be established for complex physical systems based on the particle methods (PMs), which will thereby develop into a mainstream approach as finite element (FE) and finite difference (FD) approaches.
基金the National Natural Science Foundation of China(Grant Nos.20336040 , 20490201)the Chinese Academy of Sciences(Grant No.INF105-SCE-2-07).
文摘The multi-scale structures of complex flows have been great challenges to both theoretical and engineer-ing researches, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constitutors and powerful probes of multi-scale models, owing to their physical insight and computational simplicity. In this paper, the role of different PMs for multi-scale modeling of complex flows is critically reviewed and possible development of PMs in this background is prospected, with the emphasis on pseudo-particle modeling (PPM). The performances of some different PMs are compared in simulations and new devel-opment in the fundamentals and applications of PPM is also reported, demonstrating PPM as a unique PM for multi-scale modeling.
基金Supported by the National Natural Science Foundation of China (Grant Nos. 20336040, 20490201 and 20221603)the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant No. KJCX-SW-L08)
文摘The velocity profiles and temperature distributions of gas flow in microchannels, for Knudsen numbers ranging from 0.01 to 0.20, are investigated with pseudo-particle modeling (PPM). It has been found that the velocity profiles are mainly affected by Knudsen number and the external force fields applied. When Knudsen number was increased, the slip velocities on the walls increased at the beginning, and then decreased. The temperature distributions were also significantly affected by the external force. The Darcy friction factor increased with increasing Knudsen number, and its variation with Mach number under increased Knudsen number was similar to the so-called premature laminar-turbulent transition observed in experiments.
文摘The multi-scale structures of complex flows in chemical engineering have been great challenges to the design and scaling of such systems, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constituents and powerful tools of multi-scale models, owing to their physical fidelity and computational simplicity. Especially, pseudo-particle modeling (PPM, Ge & Li, 1996; Ge & Li, 2003) is most suitable for molecular scale flow prediction and exploration of the origin of multi-scale structures; macro-scale PPM (MaPPM, Ge & Li, 2001) and similar models are advantageous for meso-scale simulations of flows with complex and dynamic discontinuity, while the lattice Boltzmann model is more competent for homogeneous media in complex geometries; and meso-scale methods such as dissipative particle dynamics are unique tools for complex fluids of uncertain properties or flows with strong thermal fluctuations. All these methods are favorable for seamless interconnection of models for different scales. However, as PMs are not originally designed as either tools for complexity or constituents of multi-scale models, further improvements are expected. PPM is proposed for microscopic simulation of particle-fluid systems as a combination of molecular dynamics (MD) and direct simulation Monte-Carlo (DSMC). The collision dynamics in PPM is identical to that of hard-sphere MD, so that mass, momentum and energy are conserved to machine accuracy. However, the collision detection procedure, which is most time-consuming and difficult to be parallelized for hard-sphere MD, has been greatly simplified to a procedure identical to that of soft-sphere MD. Actually, the physical model behind such a treatment is essentially different from MD and is more similar to DSMC, but an intrinsic difference is that in DSMC the collisions follow designed statistical rules that are reflection of the real physical processes only in very limited cases such as dilute gas. PPM is ideal for exploring the mechanism of complex flows a
基金the Designated Funding for Winners of President’s Awards of Chinese Academy of Sciences(CAS,2006)financial supports from the National Natural Science Foundation of China(NSFC)under the Grant No.20221603 and 20706057
文摘Pseudo-Particle Modeling （PPM） is a particle method proposed by Ge and Li in 1996 [Ge, W., ＆ Li, J. （1996）. Pseudo-particle approach to hydrodynamics of particle-fluid systems, in M. Kwauk ＆ J. Li （Eds.）, Proceedings of the 5th international conference on drculating fluidized bed （pp. 260-265）. Beijing： Science Press] and has been used to explore the microscopic mechanism in complex particle-fluid systems. But as a particle method, high computational cost remains a main obstacle for its large-scale application; therefore, parallel implementation of this method is highly desirable. Parallelization of two-dimensional PPM was carried out by spatial decomposition in this paper. The time costs of the major functions in the program were analyzed and the program was then optimized for higher efficiency by dynamic load balancing and resetting of particle arrays. Finally, simulation on a gas-solid fluidized bed with 102,400 solid particles and 1.8 × 10^7 pseudo-particles was performed successfully with this code, indicating its scalability in future applications.
基金This work was supported by the National Key Program for Developing Basic Sciences(Grant No.G1999032801)the National Natural Science Foundation of China(Grant Nos.20336040and 20221603)the Chinese Academy of Sciences(Grant No.INF105-SCE-2-07).
文摘A parallel algorithm suitable for simulating multi-sized particle systems and multi- phase fluid systems is proposed based on macro-scale pseudo-particle modeling (MaPPM). The algorithm employs space-decomposition of the computational load among the processing ele- ments (PEs) and multi-level cell-subdivision technique for particle indexing. In this algorithm, a 2D gas-solid system is simulated with the temporal variations of drags on solids, inter-phase slip velocities and solids concentration elaborately monitored. Analysis of the results shows that the algorithm is of good parallel efficiency and scalability, demonstrating the unique advantage of MaPPM in simulating complex flows.
基金supported by the National Natural Science Foundation of China(Grant No.20821092)National Basic Research Program of China(Grant No.2009CB219906)Chinese Academy of Sciences(Grant No.KJCX2-YW-222)
文摘Pseudo-particle modeling （PPM）, a molecular modeling method which combines time-driven algorithms and hard molecule modeling, was originally developed for simulating gas in complex multiphase systems （Ge ＆ Li, 2003; Ge et al., 2005; Ge, 1998）. In this work, the properties of two- and three-dimensional pseudo-particle systems, namely, mean free path, compressibility factor, self-diffusion coefficient and shear viscosity, are systematically measured by using PPM. it is found that in terms of an effective diameter, the results well conform to the Chapman-Enskog theory, thus suggesting that PPM can be employed to simulate the micro- and meso-scale behavior of ordinary gas and fluid flows.
