Knowledge Management System Of Institute of process engineering,CAS
|关键词||气固流态化 离散模拟 粗粒化 虚拟过程工程 并行计算|
Gas-solid fluidization is widely found in process engineering, such as in chemical, material, energy, resource, food and pharmaceutical industries. Due to the complex interactions between the fluid and particles, it is a typical non-linear and non-equilibrium system featuring multiscale spatial-temporal heterogeneity. With the increase of computation capacity and development of physical models and numerical algorithms, simulation becomes a powerful tool in the study of fluidization. In the two fluid model (TFM), the particles are treated as a continuum phase and solved on Eulerian grids. The particle-scale behaviors are therefore averaged and no reliable constitutive laws for the solid phase properties such as viscosity and pressure have been established. On the other hand, the discrete particle method (DPM) tracks particles directly while the fluid is solved on Eulerian grids. It can be used to study particles with different diameters, irregular shapes, complex forces and particle residence time distribution. In real systems, since the particle number is very large and a very small time step is needed to resolve the collision process, practical application of this method is rarely seen. Even accelerated with supercomputers, only small fluidized with large particles can be simulated so far. With the development of process engineering and the increasing demand on simulation accuracy and scales, improvement of the simulation method in both models and algorithms is highly desirable.This dissertation tried to improve discrete method from physical models to computation methods and expanded its application scope both spatially and temporally. The main innovations are as follows:Reducing the number of tracked particles and increasing time step is the fundamental approach to expanding the application of DPM. We proposed a coarse grained method, EMMS-DPM, which is based on the analysis of meso-scale structures. In EMMS-DPM, the number of tracked particles is reduced significantly and a larger time step can be used. The diameter and inner voidage of coarse grained particles are defined by the cluster properties solved from the EMMS model. The restitution coefficient of the coarse grained particles are calculated from the kinetic theory of granular flow (KTGF), ensuring a same level of energy dissipation due to collisions. This model was verified by the simulations on the pressure drop in a fixed bed and the flow fields in two different risers.Considering the multiscale structure of particle fluid systems and the short range collision forces, a multiscale parallel computation method was developed combining the use of many core processors and multi core processors (such as GPUs). The computation is overlapped with communication and the computation speed, efficiency and scalability are improved significantly. Using system shared memory, the CPU and GPU in each process can run concurrently and eliminate the IO cost of data exchange between solid phase and gas phase. This method was verified with the simulations on the pressure drop of a fixed bed and the voidage distribution in a CFB riser. The details can be found in Chapter 2.Based on these innovations, the EMMS paradigm was implemented completely for gas-solid fluidization. The initial state of the particles is generated according the voidage distribution predicted by the macro-scale EMMS model. The simulation domain is then divided non-uniformly according to this distribution, resulting in a balanced load among different processes. Finally, the dynamic behavior of this system is simulated using the coarse grained method we developed. For the simulation of the riser in a typical CFB, the computation speed is improved about 20%. By integrating these works and coupling the computational program with visualization and control programs, a demo system for virtual process engineering (VPE) of CFB was developed. A typical CFB riser was simulated with different parameters focusing on accuracy (A), capability (C) and efficiency (E), respectively. The simulations achieved comparable accuracy of traditional DPM (A), real time speed (C) and highest particle update rate (E), respectively. This indicates that VPE of gas-solid fluidization is on the horizon already. With these developments we went on to demonstrate that EMMS-DPM is capabable of practical applications already. On one hand, simulation of industrial scale fluidized beds in EMMS-DPM can afford to track the process for hours, at a speed of about 10min, providing a powerful tool for the understanding of long-term behavior of particle and reactant in the fluidization process, such as resistance time distribution. For example, our simulation on a fluidized bed in the methanol to orifin (MTO) process lasted more than 6800s, which is very helpful to the study of carbon depositon of the catalyst particles. On the other hand, 3D full loop simulation of quasi-pilot-scale CFBs becomes possible. For example, we have simulated a whole CFB with 30kg 82mm particles of the Gedart A type, with 302 million coarse-grained particles representing 4226 billion real particles running at a speed of 8s/day. The particle cycling time, particle residence time, voidage distributions compare well with experimental data and/or theoretical analysis. These applications well demonstrated the capability and potential of EMMS-DPM and the related works in this dissertation.In summary, a coarse grained discrete particle method, EMMS-DPM, was proposed in this dissertation. It is based on the analysis of the meso-scale structures in fluidization and can reduce the computation cost of DPM significantly. A new parallel algorithm for the simulation of particle fluid systems which overlaps CPU and GPU computation and communication was also proposed, and the EMM paradigm was fully implemented in the simulations with the initial conditions and load balance basis provided by the macro-scale EMMS model. The computing software is further coupled with visualization and control programs to achieve quasi-realtime interactive simulation, a prototype of VPE. These works expanded the scope of DPM simulation both spatially and temporally, setting up a computational mode for VPE of gas-solid fluidization.
|卢利强. 气固流态化的多尺度离散模拟[D]. 北京. 中国科学院研究生院,2015.|
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