WO2020087826A1 - 基于组合超椭球模型的颗粒系统的仿真分析方法 - Google Patents

基于组合超椭球模型的颗粒系统的仿真分析方法 Download PDF

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WO2020087826A1
WO2020087826A1 PCT/CN2019/077255 CN2019077255W WO2020087826A1 WO 2020087826 A1 WO2020087826 A1 WO 2020087826A1 CN 2019077255 W CN2019077255 W CN 2019077255W WO 2020087826 A1 WO2020087826 A1 WO 2020087826A1
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particles
super
particle
combined
ellipsoid
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赵永志
刘子寒
尤瑛
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Zhejiang University
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    • G06F30/20—Design optimisation, verification or simulation

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  • the invention relates to the field of particle systems, and in particular to a simulation analysis method of particle systems based on a combined super-ellipsoid model.
  • Discrete element method is the main simulation method to study the particle system. Among them, the accuracy of the particle model has a great influence on the simulation results.
  • the modeling of spherical particles is relatively simple, and for some non-spherical particles, the currently used particle models mainly include super-ellipsoid model, combined spherical model, polyhedron model, etc.
  • the combined sphere model is to realize the construction of complex particles by combining spherical particles
  • the polyhedron model is to realize the construction of complex particles by splicing different surfaces.
  • the combined spherical model and polyhedral model can construct particles of any shape, but the particle accuracy of the combined spherical model and polyhedral model is not high, and there is a certain gap between the obtained particle model and the real particle, which affects the simulation results.
  • the super-ellipsoid model can accurately construct some non-spherical particles, such as columnar particles, disc-shaped particles, and ellipsoid particles. But for some non-spherical particles with more complicated shapes, it is not available through the super-ellipsoid model.
  • Industrial products and industrial processes often involve particle systems, such as powder preparation devices, bulk processing devices, earth-moving machinery, particles and fluids, particles and structures, and other products or fields.
  • particle systems such as powder preparation devices, bulk processing devices, earth-moving machinery, particles and fluids, particles and structures, and other products or fields.
  • industrial production processes such as rotating drums, drug coating and particle filling.
  • Rotating drums are widely used in many processing industries, such as food, pharmaceutical, chemical and ceramic processing industries.
  • the industrial processes involved include mixing, heating, cooling, and drying. In these industrial projects, there is movement of particle systems.
  • the selected process parameters should be monitored and controlled to obtain the desired final product quality.
  • These process parameters are generally global, and may include, for example, the pressure of the coating container, the gas supplying the coating container, and the flow rate and temperature of the coating liquid.
  • the impact of this global process parameter on the coating process, and ultimately the coating performance of the final product can only be known from experience in specific workshops. In this way, for each specific workshop, a large number of tests are required to develop a processing plan. For example, when the size or shape of the coating container changes during the scale-up process, the local environment of the particles may be changed. In order to regain the same coating performance of the final product, this requires time-consuming measurement and adjustment.
  • the purpose of the present invention is to provide a simulation analysis method of a particle system based on a combined super-ellipsoid model, which solves the problem of inaccurate simulation results caused by the construction of the particle model inconsistent with real particles; and improves the simulation of the particle system
  • the authenticity of the results meets the needs of actual simulation; applying the simulation results to actual industrial processes improves production efficiency.
  • the simulation analysis method of particle system based on combined hyperellipsoid model includes the following steps:
  • step (3) Apply the combined super-ellipsoid model obtained in step (2) to discrete unit simulation to simulate the particle system in the industrial process and obtain the simulation results.
  • the corresponding real industrial process can be controlled according to the simulation results obtained in step (3).
  • step (1) the construction of real particles.
  • the actual shape of the particles is obtained by observation or scanning.
  • the sub-particles can be filled in according to the actual shape of the particles obtained.
  • the surface of the particles should be filled according to the surface shape of the particles.
  • the super-ellipsoid particles to construct the surface shape of the particles as realistic as possible.
  • the particles are capsule particles, and the sub-super-ellipsoids constituting the particles are two spheres and a cylinder.
  • the particles are cylindrical particles protruding from both sides, and the sub-super-ellipsoids constituting the particles are two ellipsoids and one cylinder.
  • the particles are elliptical column-like particles protruding from both sides, and the sub-super-ellipsoids constituting the particles are four spheres, two cylinders, and one ellipse-like cylinder.
  • the particles are elliptic cylindrical particles protruding from both sides, and the sub-super-ellipsoids constituting the particles are two ellipsoids and one elliptic cylinder.
  • step (2) one form of the basic equations of the super-ellipsoid model (also called hyperquadratic surface) is:
  • a, b, and c are the lengths of the three semi-major axes of the particle, and s 1 and s 2 are shape indexes, which determine the curvature of the particle edge.
  • the particles in the particle system are selected from one or a combination of at least two of capsule particles, cylindrical particles protruding on both sides, or elliptical column-like particles protruding on both sides.
  • the particles in the simulation analysis method provided by the present invention are not limited to the above shapes.
  • the simulation analysis method provided by the present invention can construct a combined super-ellipsoid model of non-spherical particles of any shape.
  • one sub super ellipsoid will not completely cover another sub super ellipsoid.
  • step (3) there will be contact between particles in the discrete unit simulation process.
  • the contact between the combined super-ellipsoid particles is determined by detecting each sub-sphere particle and other particles Whether to contact or not.
  • the discrete element method takes each particle as the calculation object, and the simulation of the particle system needs to cyclically calculate the particle displacement increment and the contact force increment.
  • Newton's second law is used to calculate the velocity and displacement of the particle, and before calculating the contact force of the particle with other particles, first determine the contact with the particle Particles or borders. This process is called contact judgment.
  • step (3) in the discrete element simulation, the interaction between the sub-super-ellipsoids in the combined super-ellipsoid particles is not considered, and the combined super-ellipsoid particles will not be deformed.
  • step (3) the industrial process is a drug coating process, and the simulation result is the number of particles with different coating qualities within a certain period of time.
  • step (3) the industrial process is particle filling, and the simulation result is the filling height of the particles in the container within a certain period of time.
  • step (3) the industrial process is a rotary drum, and the simulation result is the shape of the surface layer of particles.
  • the simulation analysis method provided by the present invention is not limited to the above industrial process.
  • the simulation analysis method provided by the present invention constructs a drug particle model by combining a super-ellipsoid model, which is closer to the real drug particles, and then applies the constructed drug particle model to the simulation in the drug coating process to obtain more accurate and true Coating effect, according to the coating effect to control the coating production process, so as to get better coating effect in the actual coating process.
  • the angle and rotation speed of the coating pan involved in the drug coating process changing the angle and rotation speed of the coating pan in the simulation can obtain the influence of the rotation speed and angle of the coating pan on the coating effect of the drug, and then the coating The rotation speed and angle of the coating pot corresponding to the best coating effect are applied to the actual drug coating process to realize the control of the drug coating process.
  • the discrete unit simulation described in the present invention is also called discrete element method.
  • the present invention can accurately reproduce the particle shape by using the combined super-ellipsoid model, and at the same time, compared with the combined spherical model, fewer sub-particles are required.
  • the present invention combines multiple sub-super-ellipsoids to form non-spherical particles with more complicated shapes and higher particle model accuracy, thereby realizing particles with more complicated shapes
  • the accurate modeling of the model solves the problem that the combined spherical model and the polyhedral model are not accurate enough when constructing some non-spherical particles; then the obtained combined super-ellipsoid model is used in discrete element simulation to improve the simulation results of the particle system.
  • the authenticity is more instructive to the actual industrial production process and helps to improve production efficiency.
  • 1 is a flowchart of a simulation analysis method based on a combined hyperellipsoid model
  • Figure 2 shows the sub-super-ellipsoid model with different parameters
  • Example 3 is a schematic structural view of a sub-super-ellipsoid of the combined super-ellipsoid model in Example 1;
  • Example 4 is a schematic structural view of a sub-super-ellipsoid of the combined super-ellipsoid model of Example 2;
  • FIG. 5 is a schematic structural view of a sub-super-ellipsoid of the combined super-ellipsoid model of Example 3;
  • FIG. 6 is a schematic structural view of a sub-super-ellipsoid of the combined super-ellipsoid model of Example 4;
  • Example 7 is a schematic diagram of equipment for the drug coating process in Example 2.
  • Example 8 is a schematic diagram of the simulation of the drug coating process in Example 2.
  • Example 9 is a simulation result of the drug coating process in Example 2.
  • Example 10 is a simulation result of the particle filling process in Example 5.
  • Example 11 is a schematic diagram of the simulation process in the rotating drum in Example 6;
  • FIG. 12 is a simulation result in the rotating drum in Example 6.
  • the simulation analysis method based on the combined hyperellipsoid model provided by the present invention includes the following steps:
  • hyperellipsoid model also called hyperquadratic surface
  • a, b, and c are the lengths of the three semi-major axes of the particle
  • s 1 and s 2 are shape indexes, which determine the curvature of the particle edge.
  • shape indices s 1 and s 2 increase, the sharpness of the edges of the particles also increases.
  • Figure 2 by changing the parameters, a variety of non-spherical particles with high accuracy can be obtained, such as spherical particles, columnar particles, ellipsoidal particles, etc.
  • step (3) Apply the combined super-ellipsoid model obtained in step (2) to discrete unit simulation to simulate the particle system in the industrial process and obtain the simulation results.
  • the particles in the particle system are drug particles and the shape is capsule particles.
  • the size data of the particles can be obtained by measuring the size of the real particles, the total length is 12mm, and the diameter of the spheres on both sides is 4mm; according to the measured data, all the required sub-super For the ellipsoidal particle model, the capsule particles need two spheres and a cylindrical particle.
  • the diameter of the sphere is 4mm
  • the diameter of the cylindrical particle is 4mm
  • the height is 8mm.
  • the center coordinates of the cylindrical particles are (0,0,0), and the center coordinates of the two spherical particles are (0,0,4) and (0,0, -4), respectively. Combined to form real capsule-shaped particles.
  • step (3) Apply the combined super-ellipsoid model obtained in step (2) to discrete unit simulation to simulate the particle system in the industrial process and obtain the simulation results.
  • the simulation results obtained using the combined hyperellipsoid model are closer to the actual data than the simulation results obtained using the combined spherical model.
  • the drug particles in this example are cylindrical particles with convex sides.
  • the size data of the particles can be obtained by measuring the size of the real particles.
  • the obtained combined super-ellipsoid model was applied to discrete unit simulation to simulate the particle system during the drug coating process, and the simulation results were obtained.
  • Figure 7 is the experimental equipment for the drug coating process
  • Figure 8 is the corresponding simulation process under the same circumstances, specifically the distribution of the coating quality of the drug particles at a certain point in the coating process
  • Figure 9 is different The curve of the number of particles corresponding to the coating quality. It can be seen from Figure 9 that the simulation results obtained by using the combined hyperellipsoid model are closer to the actual data than the simulation results obtained by using the combined spherical model.
  • the drug particles in this example are elliptic cylindrical particles protruding on both sides: as shown in FIG. 5, two ellipsoids plus an elliptical cylinder can be combined into an elliptic cylindrical shape with two protruding sides Particles.
  • the simulation results obtained using the combined hyperellipsoid model are closer to the actual data than the simulation results obtained using the combined spherical model.
  • the drug particles in this example are elliptical column-like particles protruding from both sides.
  • the drug particles in this example are elliptical column-like particles protruding from both sides.
  • four spheres, two cylinders, plus an ellipse-like cylinder can be combined into one A kind of elliptical columnar particles protruding on both sides.
  • the simulation results obtained using the combined hyperellipsoid model are closer to the actual data than the simulation results obtained using the combined spherical model.
  • Examples 1-4 are simulation simulations of the particle system during the drug coating process using the simulation analysis method provided by the present invention.
  • the drug coating process, drug coating is of great significance in controlling the rate of drug release and improving the appearance of the drug.
  • the number of particles with different coating qualities can be obtained within a certain period of time, and then the coating effect can be obtained.
  • the angle and speed of the coating pot are changed, the speed and angle of the coating pot can also be obtained.
  • the influence of the coating effect is of guiding significance for improving the real drug coating process.
  • Figure 10 shows the different filling conditions, from left to right, are the experimental results, combined super-ellipsoid simulation results, and two different precision combined ball simulation results, as can be seen from the results, in the same size container Filling the same number of particles inside, the particle filling height obtained by using the combined super-ellipsoid model is closer to the real particle filling height.
  • Rotating drums are widely used in many processing industries, such as food, pharmaceutical, chemical and ceramic processing industries, etc.
  • the industrial processes involved include mixing, heating, cooling, drying, etc.
  • Fig. 11 is the shape of the bed surface of the particles in Fig. 4 in a rotating drum. It can be seen from Figure 12 that by comparing and observing the surface shape of the bed of the particles, the surface shape of the bed using the combined super-ellipsoid model is closer to the actual situation than the combined spherical model at two rotation speeds, where a The rotation speed of the graph is 15 rpm, and the rotation speed of the graph b is 60 rpm.

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Abstract

本发明公开了基于组合超椭球模型的颗粒系统的仿真分析方法，包括以下步骤：(1)根据真实颗粒的尺寸和形状，确定构成颗粒的子超椭球的形状、尺寸和个数；(2)通过超椭球模型构建子超椭球，再根据真实颗粒的尺寸赋予子超椭球颗粒模型不同的坐标位置，组合子超椭球，构成颗粒的组合超椭球模型；(3)将步骤(2)得到的组合超椭球模型应用于离散单元仿真，模拟工业过程中的颗粒系统，得到仿真结果。本发明提供的仿真分析方法解决了因为颗粒模型的构建与真实颗粒不符的问题，而导致的仿真结果的不准确；提升了颗粒系统的仿真结果的真实性，满足了实际仿真的需要；将仿真结果应用于实际工业过程，提高了生产效率。

Description

基于组合超椭球模型的颗粒系统的仿真分析方法 技术领域
本发明涉及颗粒系统领域，尤其涉及基于组合超椭球模型的颗粒系统的仿真分析方法。
背景技术
自然界存在着大量的颗粒材料，获取颗粒运动的规律，对于改善许多工业过程具有重要意义。离散单元法是研究颗粒系统的较为主要的仿真手段，其中，颗粒模型的精确程度对于仿真结果具有较大的影响。球形颗粒建模较为简单，而对于一些非球形颗粒，目前采用的颗粒模型主要有超椭球模型、组合球模型、多面体模型等。
而对于以上颗粒模型，均存在一定的缺点和不足：
组合球模型是通过组合球形颗粒来实现复杂颗粒的构建，多面体模型则是通过不同面的拼接来实现复杂颗粒的构建。从理论上来说，组合球模型和多面体模型可以构建出任何形状的颗粒，但组合球模型和多面体模型的颗粒精度不高，得到的颗粒模型与真实颗粒相比存在一定的差距，从而影响仿真结果的真实性。超椭球模型可以精确的构建一些非球形颗粒，例如柱状颗粒、盘状颗粒、椭球颗粒等。但对于一些形状较为复杂的非球形颗粒，通过超椭球模型是无法得到的。
工业产品和工业过程中经常涉及到颗粒系统，如粉体制备装置、散体处理装置、土方机械、颗粒与流体、颗粒与结构等产品或领域。具体地，如旋转滚筒、药物包衣和颗粒填充等工业生产过程。
旋转滚筒广泛应用于许多加工行业，例如食品，制药，化学和陶瓷加工业等，涉及到的工业过程包括混合、加热、冷却和干燥等，在这些工业工程中都存在颗粒系统的运动。
对药品进行包衣的工厂车间，要对所选择的工艺参数进行监测控制以获得所期望的最终产品的质量。这些工艺参数通常是全局性的，并且可能包括如包衣容器的压力、供应包衣容器的气体和包衣液的流速和温度等。然而，这种全局性工艺参数对包衣过程的影响，以及最终对最终产品的包衣性能的影响，只能在特定车间中从经验中知道。这样，对于每一个具体的车间要通过大量的试验来开发加工方案。例如，在扩大工艺规模过程中当包衣容器的尺寸或形状变化时，颗粒的局部环境可能被改变。为了重新得到最终产品的相同包衣性能这就要求耗时的测量和调整。
而很多药品具有不规则形状，为复杂的非球形颗粒，而现有技术构建的药物颗粒模型往往不能完全符合药物颗粒的实际形状，进而造成药物包衣过程的仿真结果与真实性相差甚远，将仿真结果应用于药物包衣生产过程控制，会出现较大的偏差，降低生产效率。
发明内容
本发明的目的在于提供基于组合超椭球模型的颗粒系统的仿真分析方法，解决了因为颗粒模型的构建与真实颗粒不符的问题，而导致的仿真结果的不准确；提升了对颗粒系统的仿真结果的真实性，满足了实际仿真的需要；将仿真结果应用于实际工业过程，提高了生产效率。
基于组合超椭球模型的颗粒系统的仿真分析方法，包括以下步骤：
(1)根据真实颗粒的尺寸和形状，确定构成颗粒的子超椭球的形状、尺寸和个数；
(2)通过超椭球模型构建子超椭球，再根据真实颗粒的尺寸赋予子超椭球颗粒模型不同的坐标位置，组合子超椭球，构成颗粒的组合超椭球模型；
(3)将步骤(2)得到的组合超椭球模型应用于离散单元仿真，模拟工业过程中的颗粒系统，得到仿真结果。
根据步骤(3)得到的仿真结果可以对对应的真实工业过程进行控制。
在步骤(1)中，真实颗粒的构建。首先通过观察或扫描等手段，得到颗粒的真实形状，对于形状不规则的颗粒，可根据得到的颗粒真实形状，在内部进行子颗粒的填充，同时需根据颗粒的表面形状，在颗粒表面填充相应的超椭球颗粒，以尽可能真实的构建出颗粒表面形状。同时，在满足一定的颗粒模型精度的条件下，需要尽可能减少子颗粒的数量。
在步骤(1)中，所述的颗粒为胶囊颗粒，构成颗粒的子超椭球为两个球体和一个圆柱。
在步骤(1)中，所述的颗粒为两面凸出的圆柱状颗粒，构成颗粒的子超椭球为两个椭球和一个圆柱。
在步骤(1)中，所述的颗粒为两面凸出的类椭圆柱状颗粒，构成颗粒的子超椭球为四个球体、两个圆柱体以及一个类椭圆柱体。
在步骤(1)中，所述的颗粒为两面凸出的椭圆柱状颗粒，构成颗粒的子超椭球为两个椭球体和一个椭圆柱体。
在步骤(2)中，所述的超椭球模型(又称超二次曲面)基本方程的一种形式为：
Figure PCTCN2019077255-appb-000001
其中a、b、c分别为颗粒的三个半长轴的长度，s 1、s 2为形状指数，决定颗粒边缘的曲率。
在步骤(4)中，颗粒系统中的颗粒选自胶囊颗粒、两面凸出的圆柱状颗粒或两面凸出的类椭圆柱状颗粒中的一种或至少两种的组合。
本发明提供的仿真分析方法中的颗粒不仅仅局限于上述形状，通过本发明提供的仿真分析方法可以构建任何形状的非球形颗粒的组合超椭球模型。
本发明提供的组合超椭球模型中，某一子超椭球不会完全包覆另一个子超椭球。
在步骤(3)中，所述的离散单元仿真过程中会出现颗粒之间相互接 触的情况，离散单元法中判断组合超椭球颗粒之间的接触是通过检测每一个子球颗粒与其他颗粒是否接触来判断的。
离散单元法以每一个颗粒为计算对象，颗粒系统的模拟需要对颗粒位移增量与接触力增量进行循环计算。通过求解某一颗粒与其他颗粒或边界的接触力，利用牛顿第二定律来计算该颗粒的运动速度和位移，而在计算该颗粒与其他颗粒的接触作用力前，首先应确定与该颗粒接触的颗粒或边界。这个过程称为接触判断。
在步骤(3)中，所述的离散单元仿真中，不考虑组合超椭球颗粒中的子超椭球间的相互作用，组合超椭球颗粒不会产生变形。
在步骤(3)中，所述的工业过程为药物包衣过程，仿真结果为一定时间内不同包衣质量的颗粒个数。
在步骤(3)中，所述的工业过程为颗粒填充，仿真结果为一定时间内颗粒在容器内的填充高度。
在步骤(3)中，所述的工业过程为旋转滚筒，仿真结果为颗粒的表面床层形状。
本发明提供的仿真分析方法不局限于上述工业过程。
本发明提供的仿真分析方法通过组合超椭球模型构建了药物颗粒模型，更接近真实的药物颗粒，再将构建的药物颗粒模型应用于药物包衣过程中的仿真，可以得到更加准确和真实的包衣效果，根据包衣效果对包衣生产过程进行控制，从而在实际包衣过程中得到更佳的包衣效果。如，药 物包衣过程中涉及的包衣锅的角度和转速：在仿真中改变包衣锅的角度和转速，可以获得包衣锅转速及角度对药物的包衣效果的影响，进而可以将包衣效果最好所对应的包衣锅转速及角度应用于实际药物包衣过程中，实现对药物包衣过程的控制。
本发明所述的离散单元仿真又称为离散元素法。
与现有技术相比，本发明的有益效果体现在：
本发明通过观察或扫描得到真实的颗粒形状后，使用组合超椭球模型，可以精准的复现颗粒形状，同时相对组合球模型而言，需要的子颗粒个数更少。
本发明通过给予不同的子超椭球不同的坐标位置和大小，将多个子超椭球进行组合，构成形状较为复杂，颗粒模型精度较高的非球形颗粒，从而实现了对形状较为复杂的颗粒的精确建模，解决了组合球模型、多面体模型在构建一些非球形颗粒时精度不够的问题；再将得到的组合超椭球模型用于离散单元仿真中，提高了对颗粒系统的仿真结果的真实性，对实际的工业生产过程更具有指导意义，有利于提高生产效率。
附图说明
图1为基于组合超椭球模型的仿真分析方法的流程图；
图2为不同参数下的子超椭球模型；
图3为实施例1中组合超椭球模型的子超椭球的结构示意图；
图4为实施例2组合超椭球模型的子超椭球的结构示意图；
图5为实施例3组合超椭球模型的子超椭球的结构示意图；
图6为实施例4组合超椭球模型的子超椭球的结构示意图；
图7为实施例2中药物包衣过程的设备示意图；
图8为实施例2中药物包衣过程的仿真示意图；
图9为实施例2中药物包衣过程的仿真结果；
图10为实施例5中颗粒填充过程中的仿真结果；
图11为实施例6中旋转滚筒中的仿真过程示意图；
图12为实施例6中旋转滚筒中的仿真结果。
具体实施方式
下面结合附图及实施例对本发明的发明内容进一步的阐述。
如图1所示，本发明提供的基于组合超椭球模型的仿真分析方法，包括以下步骤：
(1)根据真实颗粒的尺寸和形状，确定构成颗粒的子超椭球的形状、尺寸和个数。
(2)通过超椭球模型构建子超椭球，再根据真实颗粒的尺寸赋予子超椭球颗粒模型不同的坐标位置，组合子超椭球，构成颗粒的组合超椭球模型。
超椭球模型(又称超二次曲面)基本方程的一种形式为：
Figure PCTCN2019077255-appb-000002
其中a、b、c分别为颗粒的三个半长轴的长度，s 1、s 2为形状指数，决定颗粒边缘的曲率。随着形状指数s 1、s 2的增大，颗粒边缘的锐利程度也不断增大。如图2所示，通过改变参数，可以得到多种精度较高的非球形颗粒，例如球形颗粒、柱状颗粒、椭球颗粒等。
(3)将步骤(2)得到的组合超椭球模型应用于离散单元仿真，模拟工业过程中的颗粒系统，得到仿真结果。
实施例1
颗粒系统中的颗粒为药物颗粒，形状为胶囊颗粒。
(1)根据真实颗粒的尺寸和形状，确定构成颗粒的子超椭球的形状、尺寸和个数。
对于真实的胶囊状颗粒，如图3所示，通过测量真实颗粒的大小，可以得到颗粒的尺寸数据，总长12mm，两侧球体直径为4mm；根据测得的数据，构建所需的所有子超椭球颗粒模型，胶囊颗粒所需的是两个球体以及一个圆柱颗粒，球体直径为4mm，圆柱颗粒直径为4mm，高度为8mm。
(2)通过超椭球模型构建子超椭球，再根据真实颗粒的尺寸赋予子超椭球颗粒模型不同的坐标位置，组合子超椭球，构成颗粒的组合超椭球模型。
构建过程如图3所示，根据超椭球模型颗粒公式，对于球形颗粒，a＝b＝c＝2，s 1＝s 2＝2，对于圆柱颗粒，a＝b＝2，c＝4，s 1＝20，s 2＝2，构建得到子超椭球颗粒模型。
圆柱颗粒的中心坐标为(0,0,0)，两个球体颗粒的球心坐标分别为(0,0,4)和(0,0,-4)，经过三个子超椭球颗粒模型的组合，构成真实的胶囊状颗粒。
(3)将步骤(2)得到的组合超椭球模型应用于离散单元仿真，模拟工业过程中的颗粒系统，得到仿真结果。
利用组合超椭球模型得到的仿真结果，比利用组合球模型得到的仿真结果，与实际数据更为接近。
实施例2
如实施例1提供的药物颗粒，本实施例中的药物颗粒为两面凸出的圆柱状颗粒。
如图4所示，通过测量真实颗粒的大小，可以得到颗粒的尺寸数据，直径为8mm，高为4mm，其中圆柱段高度为2mm；根据测得的数据，构建所需的所有子超椭球颗粒模型，该颗粒所需的是两个椭球颗粒和一个圆柱颗粒，根据超椭球模型颗粒公式，对于椭球颗粒，a＝b＝4，c＝1，s 1＝s 2＝2，对于圆柱颗粒，a＝b＝4，c＝1，s 1＝20，s 2＝2；将得到的所有子超椭球颗粒进行组合，圆柱颗粒的中心坐标为(0,0,0)，两个椭球体颗粒的球心坐标分 别为(0,0,1)和(0,0,-1)，经过三个子超椭球颗粒模型的组合，可以得到真实的两面凸出的圆柱状颗粒。
将得到的组合超椭球模型应用于离散单元仿真，模拟药物包衣过程中的颗粒系统，得到仿真结果。
具体地，基于组合超椭球模型，对图4所示的药片颗粒的包衣过程的仿真。图7为药物包衣过程的实验设备；图8为相同情况下进行的相应的仿真过程，具体为在包衣过程中，某一时刻下药物颗粒的包衣质量的分布情况；图9为不同包衣质量所对应的颗粒数量的曲线。从图9可以看出，利用组合超椭球模型得到的仿真结果，比利用组合球模型得到的仿真结果，与实际数据更为接近。
实施例3
如实施例2所示，本实施例中的药物颗粒为两面凸出的椭圆柱状颗粒：如图5所示，利用两个椭球体加上一个椭圆柱体可以组合成一种两面凸出的椭圆柱状颗粒。利用组合超椭球模型得到的仿真结果，比利用组合球模型得到的仿真结果，与实际数据更为接近。
实施例4
如实施例2所示，本实施例中的药物颗粒为两面凸出的类椭圆柱状颗粒，如图6所示，利用四个球体，两个圆柱体，加上一个类椭圆柱体可以 组合成一种两面凸出的类椭圆柱状颗粒。利用组合超椭球模型得到的仿真结果，比利用组合球模型得到的仿真结果，与实际数据更为接近。
实施例1-4为用本发明提供的仿真分析方法对药物包衣过程中的颗粒系统进行模拟仿真。药物包衣过程，药物包衣在控制药物的释放速率，改善药物的外观等方面具有重要意义。通过仿真，可以得到在一定时间内，不同包衣质量的颗粒个数，进而得到包衣效果的好坏，同时若改变包衣锅的角度和转速，也可以获得包衣锅转速及角度对包衣效果的影响，对于改善真实的药物包衣过程具有指导意义。
实施例5
将仿真结果应用于颗粒填充过程。
在绝大多数的颗粒系统中，在进行具体的操作前，都需要将颗粒进行填充。分别利用组合超椭球模型和组合球模型，对图4所示颗粒的填充过程进行研究，并与实际数据进行对比。图10所示为不同的填充情况，从左到右，分别是实验结果，组合超椭球仿真结果，以及两种不同精度的组合球仿真结果，从结果中可以看出，在相同大小的容器内填充相同数量的颗粒，利用组合超椭球模型得到的颗粒填充高度更接近于真实的颗粒填充高度。
实施例6
旋转滚筒广泛应用于许多加工行业，例如食品，制药，化学和陶瓷加工业等，涉及到的工业过程包括混合，加热，冷却，干燥等。
图11为关于图4颗粒在旋转滚筒中的床层表面形状。从图12可以看出，通过对比观察颗粒的床层表面形状，在两种转速下，利用组合超椭球模型的床层表面形状，要比组合球模型的，更接近实际情况，其中，a图的转速为15rpm，图b的转速为60rpm。

Claims (9)

  1. 基于组合超椭球模型的颗粒系统的仿真分析方法，包括以下步骤：
    (1)根据真实颗粒的尺寸和形状，确定构成颗粒的子超椭球的形状、尺寸和个数；
    (2)通过超椭球模型构建子超椭球，再根据真实颗粒的尺寸赋予子超椭球颗粒模型不同的坐标位置，组合子超椭球，构成颗粒的组合超椭球模型；
    (3)将步骤(2)得到的组合超椭球模型应用于离散单元仿真，模拟工业过程中的颗粒系统，得到仿真结果。
  2. 根据权利要求1所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，在步骤(1)中，所述的颗粒为胶囊颗粒，构成颗粒的子超椭球为两个球体和一个圆柱。
  3. 根据权利要求1所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，在步骤(1)中，所述的颗粒为两面凸出的圆柱状颗粒，构成颗粒的子超椭球为两个椭球和一个圆柱。
  4. 根据权利要求1所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，在步骤(1)中，所述的颗粒为两面凸出的类椭圆柱状颗粒，构成颗粒的子超椭球为四个球体、两个圆柱体以及一个类椭圆柱体。
  5. 根据权利要求1所述的基于组合超椭球模型的颗粒系统的仿真分 析方法，其特征在于，在步骤(2)中，所述的超椭球模型的基本方程为：
    Figure PCTCN2019077255-appb-100001
    其中a、b、c分别为颗粒的三个半长轴的长度，s 1、s 2为形状指数，决定颗粒边缘的曲率。
  6. 根据权利要求1所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，在步骤(3)中，所述的离散单元仿真中判断组合超椭球颗粒之间的接触是通过检测每一个子超椭球与另一个颗粒是否接触来判断。
  7. 根据权利要求1-6任一权利要求所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，所述的工业过程为药物包衣过程，仿真结果为一定时间内不同包衣质量的颗粒个数。
  8. 根据权利要求1-6任一权利要求所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，所述的工业过程为颗粒填充，仿真结果为一定时间内颗粒在容器内的填充高度。
  9. 根据权利要求1-6任一权利要求所述的基于组合超椭球模型的颗粒系统的仿真分析方法，其特征在于，所述的工业过程为旋转滚筒，仿真结果为颗粒的表面床层形状。
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