WO2019010859A1 - 一种高致密度离散颗粒多相体系的建模方法 - Google Patents
一种高致密度离散颗粒多相体系的建模方法 Download PDFInfo
- Publication number
- WO2019010859A1 WO2019010859A1 PCT/CN2017/106883 CN2017106883W WO2019010859A1 WO 2019010859 A1 WO2019010859 A1 WO 2019010859A1 CN 2017106883 W CN2017106883 W CN 2017106883W WO 2019010859 A1 WO2019010859 A1 WO 2019010859A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- particle
- model
- particles
- modeling
- volume
- Prior art date
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
Definitions
- the invention belongs to the field of computational materials science, and particularly relates to a mesoscale modeling method for a mesostructure of a high-density discrete particle multi-phase system, in particular to a mesoscale structure of a particle reinforced composite material, a soft material granular material, a particle accumulation material, and the like.
- the modeling method can also be extended to short fiber reinforced composites.
- granular materials can be regarded as random stacked structures composed of particles of different scales.
- the interstices between the particles are typically filled with a medium such as a matrix material, interface, pores, or fluid.
- a medium such as a matrix material, interface, pores, or fluid.
- the random placement method also known as the Monte Carlo method, assigns the position of the particles one by one in a given time and space in a certain order. Once the allocation is successful, the placement is successful and the particles are fixed at the assigned position.
- the Monte Carlo method is highly efficient, but the bulk density of the particles is very low. The later the release, the smaller the selection space of random points, the more difficult it is to put, so it is difficult to put all the particles into the limited model space, and there are often some materials in the engineering practice. However, it is not possible to generate a mesoscale structural model of the material.
- Voronoi method can easily generate densely distributed random particles, it cannot control the gradation of the particles, that is, it is impossible to control the volume ratio or weight ratio of particles of different particle sizes.
- the Voronoi method is mainly suitable for convex particles, and is not suitable for the case where the concave shape, or the convex shape and the concave shape are simultaneously distributed.
- Chinese patent document 201510345395.3 discloses a modeling method for the mesostructure of discrete phase reinforced composite materials, which firstly generates randomly distributed particles in a large space, then divides the surface of the particles into shell elements and simulates the particles. Free fall motion, allowing it to fall into a smaller space, resulting in a highly dense particle packing structure. Finally, based on the shell element of the particle surface, the solid element of the particle is generated, and finally the finite element model of the particle is obtained.
- the method can solve the problem that the bulk density of the particle phase is insufficient in the random injection method, and the Voronoi method cannot be used for the concave particle and the particle gradation cannot be controlled, but the upper surface of the deposit body may not be flat after the drop, and the calculation of the falling process is also It is time consuming and requires two meshing of shell and solid elements, which is costly to calculate. In addition, this method works very well when all particles are inside a particular space, but special handling is required when the particles cross the model boundary.
- the object of the present invention is to provide a modeling method for a high-density discrete particle multiphase system.
- the method can model the high-density microstructure of the particle-reinforced composite material, the soft material-based granular material, the particulate-deposited material, the short-fiber reinforced composite material, etc. by the principle of shrinkage, which is described in Chinese Patent Document 201510345395.3
- the advantages of the invention are characterized by simple method, wide adaptability and high calculation efficiency.
- a modeling method for a high-density discrete particle multiphase system comprising the following steps:
- the volume of the particles in each size range is prepared, that is, the volume of the particle phase in the range of i to j is set to be V (ij) ;
- step (3) repeating step (3) to generate a compact model of the particles in all size ranges;
- the compact model of each particle in the step (4) is volume-expanded, that is, the size of the compact model of each particle is enlarged by 1/ ⁇ times, and the volume is also followed. Amplification 1/ ⁇ times, thereby expanding the compact model of each particle to a normal size model conforming to the predetermined gradation in step (2), and the obtained particle distribution model is the desired high-density particle structure model.
- the amount of expansion of the compact model can obtain the particle bulk density consistent with the real material, and solve the problem that the high-density model cannot be obtained by random placement and the like.
- FIG. 1 is a schematic diagram of a compact model for randomly generating particles in a modeling space
- FIG. 2 is a finite element mesh diagram of a high density model obtained by expanding and redistributing each particle in a compact model
- Figure 3 is a schematic diagram comparing the compact model with the expanded model.
- the 1-compact particle model, the 2-model boundary, the finite element mesh of the normal-sized particles obtained after 3-expansion, and the 4-expansion normal-size particle model are included in the 1-compact particle model, the 2-model boundary, the finite element mesh of the normal-sized particles obtained after 3-expansion, and the 4-expansion normal-size particle model.
- the present invention proposes a modeling method for a high-density discrete particle multi-phase system. , including the following steps:
- the volume of the particles in each size range is prepared, that is, the volume of the particle phase in the range of i to j is set to be V (ij) ;
- step (3) repeating step (3) to generate a compact model of the particles in all size ranges;
- the compact model of each particle in the step (4) is volume-expanded, that is, the size of the compact model of each particle is enlarged by 1/ ⁇ times, and the volume is also followed. Amplification 1/ ⁇ times, thereby expanding the compact model of each particle to a normal size model conforming to the predetermined gradation in step (2), and the obtained particle distribution model is the desired high-density particle structure model.
- a void between the particles serves as a second phase, and thereby a multiphase model is produced.
- step (5) the expansion method of each particle compaction model comprises the following steps:
- step (1) dividing the boundary of the modeling space in step (1) (referred to as the model boundary) into a finite element mesh, and assigning material properties;
- step (4) dividing the particles described in step (4) into a finite element mesh and assigning material properties
- the model boundary is a temperature independent rigid material.
- the particles are thermoelastic materials or thermoelastic materials, and further preferably, the particles are thermoelastic materials.
- each particle model is divided into physical units, and the model boundary is an entity element or a shell unit.
- the contact mode is a face-to-face contact, or a point-to-face contact, or a point-to-point contact.
- the high-density discrete particle multi-phase system is a particle-reinforced composite material, a soft material-based particulate material (such as a soft material-based particulate material composed of concrete or a debris flow), a particulate-deposited material, or a short-fiber reinforced composite material.
- the method for obtaining a plurality of particle models in the range of i ⁇ j ⁇ includes the following steps:
- step b judging whether the ball generated in step a interferes with the particles that have been generated around, if interference occurs, delete the generated ball, and repeat step a;
- the shape of the generated model is a spherical or ellipsoidal shape or other spherical shape.
- the particle model is directly generated by the mathematical equation, and the step c is omitted.
- the expansion method of each particle compaction model can also be solved by a numerical method such as discrete element.
- the application of the above modeling method in the modeling of fiber reinforced composite materials is characterized in that the ball generated by random points in the above modeling method is replaced by a column, and a fiber model is generated from the column.
- a modeling method for a high-density two-dimensional discrete particle multiphase system comprising the following steps:
- the finite element method is used to apply a temperature or a heat flow load to the compact model of each particle in the step (4) to cause an area expansion, that is, a compact model of each particle.
- the size of the particles i ⁇ ⁇ ⁇ j ⁇ ⁇ is a comparison of the model of the compaction model and the model after expansion, 1 is the particle compaction model, 4 It is a normal size particle model after expansion.
- the area sum of each particle also expands by 1 ⁇ ⁇ times, from S (ij) ⁇ ⁇ to S (ij) , thereby expanding the contraction model of each particle to the normal size model conforming to the predetermined gradation in step (2). .
- the particle distribution model obtained at this time is the high density particle structure model obtained.
- a void between the particles serves as a second phase, and thereby a multiphase model is produced.
- the method for obtaining a plurality of particle models in the range of i ⁇ j ⁇ includes the following steps:
- step b judging whether the circle generated in step a interferes with the particles that have been generated around, if interference occurs, delete the generated circle, and repeat step a;
- a modeling method for a three-dimensional mesostructure of a high-density particle-reinforced composite material comprising the following steps:
- the volume of the particles in each size range is prepared, that is, the volume of the particle phase in the range of i to j is set to be V (ij) ;
- a method for obtaining a plurality of particle models in the range of i ⁇ j ⁇ includes the following steps:
- step b judging whether the ball generated in step a interferes with the particles that have been generated around, if interference occurs, delete the generated ball, and repeat step a;
- step (3) repeating step (3) to generate a compact model of the particles in all size ranges;
- the compact model of each particle in the step (4) is volume-expanded, that is, the size of the compact model of each particle is enlarged by 1/ ⁇ times, and the volume is also followed. Amplification 1/ ⁇ times, thereby expanding the compact model of each particle to a normal size model conforming to the predetermined gradation in step (2), and the obtained particle distribution model is the desired high-density particle structure model.
- the expansion method of each particle compact model specifically includes the following steps:
- step (1) Divide the boundary of the modeling space (called the model boundary) in step (1) into a finite element mesh, and give it no temperature. Closed body material properties;
- step (4) dividing the particles described in step (4) into a finite element mesh and imparting properties to the thermoelastic material
- the particle distribution model obtained at this time is the high density particle structure model obtained.
- a void between the particles serves as a second phase, and thereby a multiphase model is produced.
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Computer Hardware Design (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
Abstract
Description
Claims (10)
- 一种高致密度离散颗粒多相体系的建模方法,其特征是,包括以下步骤:(1)拟定模型的轮廓形状和尺寸,即确定建模空间及其边界;(2)根据预定的级配,拟定各尺寸范围内的颗粒的体积和,即设定i~j尺寸范围内的颗粒相的体积和为V(i-j);(3)在所述建模空间内,随机获得在i×α~j×α尺寸范围内的若干个颗粒模型,其中,α<1,使各个颗粒模型的体积和为V(i-j)×β,各个颗粒均与周围的颗粒之间不发生干涉,由此获了i~j尺寸范围内的各颗粒的紧缩模型;(4)重复步骤(3),生成所有尺寸范围内的颗粒的紧缩模型;(5)在步骤(1)中所述的建模空间中,将步骤(4)中各颗粒的紧缩模型进行体积膨胀,即将各颗粒的紧缩模型的尺寸放大1/α倍,体积也随之放大1/β倍,从而将各颗粒的紧缩模型膨胀至符合步骤(2)中预定级配的正常尺寸模型,此时得到的颗粒分布模型即为所求的高致密度颗粒结构模型。
- 如权利要求1所述的建模方法,其特征是:所述高致密度离散颗粒多相体系为颗粒增强复合材料、软物质系颗粒材料、颗粒堆积材料或短纤维增强复合材料。
- 如权利要求1所述的建模方法,其特征是:步骤(5)中,各颗粒紧缩模型的膨胀方法,包括如下步骤:a、将步骤(1)中建模空间的边界划分有限元网格,并赋予材料属性;b、将步骤(4)中所述的颗粒划分有限元网格,并赋予材料属性;c、定义颗粒之间以及颗粒与建模空间的边界之间的接触判断方式,使之不发生相互穿透;d、用有限元方法,对颗粒施加温度或热流载荷,使之产生热膨胀;热膨胀1/α倍后,尺寸由为i×α~j×α的颗粒变为尺寸i~j,各颗粒的体积和也随之膨胀1×β倍,由V(i-j)×β变为V(i-j)。
- 如权利要求3所述的建模方法,其特征是:步骤a中,模型边界为与温度无关的刚性材料;步骤b中,颗粒为热弹性材料或热弹塑性材料,优选的,所述颗粒为热弹性材料;步骤a~b中,将各个颗粒模型划分为实体单元,模型边界为实体元或壳单元;步骤c中,所述接触方式为面-面接触,或点-面接触,或点-点接触。
- 如权利要求1所述的建模方法,其特征是:步骤(1)~(3)中,i×α~j×α尺寸范围内的若干个颗粒模型的获得方法,包括如下步骤:a、在所述建模空间内,随机产生一个点,以该点为中心,生成一个直径在i×α~j×α尺寸范围内的球;b、判断步骤a中所生成的球是否与周围已生成的颗粒发生干涉,若发生干涉,则删除已生成的球,并重复步骤a;c、在所述球内生成内接多面体,任选该多面体的几个顶点,使之沿球的半径方向内移,形成内凹和外凸的表面,以得到逼近真实颗粒形状的颗粒模型;d、判断所生成的颗粒是否与模型边界发生干涉,若发生干涉,则删除颗粒在模型边界外的部分;e、计算步骤d中得到的颗粒模型的体积;f、重复步骤a~e,将得到的各个颗粒模型的体积求和,得到ΣV;g、判断ΣV是否达到V(i-j)×β,若不是,则重复步骤a~f;优选的,步骤a中,生成的模型的形状为球形或椭球型或其他类似球形的形状;优选的,如果颗粒的形状能够直接用数学方程描述,则在上述步骤a~c中,直接通过数学方程生成颗粒模型,并省略步骤c。
- 如权利要求1所述的建模方法,其特征是:将颗粒之间的空隙作为第二相,并由此生成多相模型。
- 如权利要求1所述的建模方法,其特征是:步骤(3)中,所述α=0.5~0.9,β=α3。
- 如权利要求1所述的建模方法,其特征是:步骤(5)中,各颗粒紧缩模型的膨胀方法,能够通过离散元数值方法进行求解。
- 权利要求1~8中任一项所述的建模方法在二维细观结构建模上的应用,其特征是:将所述建模方法中的体积用面积代替,将在随机点生成的球用圆代替,将内接多面体用圆内接多边形代替,β=α2。
- 权利要求1~8中任一项所述的建模方法在纤维增强复合材料建模上的应用,其特征是:将所述建模方法中随机点生成的球用柱代替,并由柱生成纤维模型。
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US16/314,502 US11170144B2 (en) | 2017-07-13 | 2017-10-19 | Modeling method for high-density discrete particle multiphase system |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710570950.1A CN107423498B (zh) | 2017-07-13 | 2017-07-13 | 一种高致密度离散颗粒多相体系的建模方法 |
CN201710570950.1 | 2017-07-13 |
Publications (1)
Publication Number | Publication Date |
---|---|
WO2019010859A1 true WO2019010859A1 (zh) | 2019-01-17 |
Family
ID=60427018
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
PCT/CN2017/106883 WO2019010859A1 (zh) | 2017-07-13 | 2017-10-19 | 一种高致密度离散颗粒多相体系的建模方法 |
Country Status (3)
Country | Link |
---|---|
US (1) | US11170144B2 (zh) |
CN (1) | CN107423498B (zh) |
WO (1) | WO2019010859A1 (zh) |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110210178A (zh) * | 2019-06-26 | 2019-09-06 | 西安理工大学 | 一种基于Python再生混凝土三维随机球形骨料模型的构建方法 |
CN111027244A (zh) * | 2019-12-03 | 2020-04-17 | 天津大学 | 一种百亿级颗粒模型的构建方法 |
CN111428359A (zh) * | 2020-03-23 | 2020-07-17 | 河海大学 | 一种考虑晶粒咬合的各向异性岩石建模方法 |
CN111783269A (zh) * | 2019-03-18 | 2020-10-16 | 山东高速集团有限公司 | 一种基于离散元分析道路空隙结构由于扬尘造成阻塞的方法 |
CN112084694A (zh) * | 2020-09-15 | 2020-12-15 | 河南理工大学 | 一种考虑非理想界面的颗粒增强复合材料微观结构的几何建模方法 |
CN112461718A (zh) * | 2020-11-18 | 2021-03-09 | 中国石油大学(华东) | 孔隙度与颗粒粒径分布关系表征方法 |
CN113111560A (zh) * | 2021-04-26 | 2021-07-13 | 山东大学 | 一种非均质矿物铸件细观结构模型生成方法及系统 |
CN113962066A (zh) * | 2021-09-27 | 2022-01-21 | 太原理工大学 | 一种含六相组分的钢筋混凝土三维细观模型 |
CN115050431A (zh) * | 2022-04-27 | 2022-09-13 | 中南大学 | 一种水泥稳定再生集料的三维细观结构的建模分析方法 |
Families Citing this family (22)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109541186B (zh) * | 2018-11-29 | 2021-11-09 | 烟台大学 | 一种基于形状参数的粗骨料密实度计算方法 |
CN109829975A (zh) * | 2019-03-14 | 2019-05-31 | 河海大学 | 一种变孔隙度多孔介质构建方法 |
JP7160752B2 (ja) * | 2019-04-25 | 2022-10-25 | 株式会社日立製作所 | 粒子挙動シミュレーション方法、及び粒子挙動シミュレーションシステム |
CN110706352B (zh) * | 2019-10-10 | 2023-03-10 | 重庆交通大学 | 基于多边形随机骨料的混凝土三相细观模型构建及内氯离子侵蚀数值模拟方法 |
CN111310376B (zh) * | 2020-02-21 | 2021-12-28 | 南京航空航天大学 | 一种高效高精度的编织陶瓷基复合材料结构建模方法 |
CN111967066B (zh) * | 2020-04-20 | 2022-10-28 | 北京航空航天大学 | 一种多形态颗粒增强复合材料三维细观结构建模方法 |
WO2021246378A1 (ja) * | 2020-06-01 | 2021-12-09 | 住友金属鉱山株式会社 | シミュレーション装置、シミュレーション方法、プログラム |
CN112115608B (zh) * | 2020-09-16 | 2024-03-15 | 中国地质大学(北京) | 复合颗粒粒径计算和级配调整配置方法 |
CN112329318B (zh) * | 2020-11-27 | 2022-04-22 | 华中科技大学 | 重构多组分复合材料的离散元建模方法及应用 |
CN112818574B (zh) * | 2021-01-27 | 2022-10-14 | 江西理工大学 | 模拟泥石流起动形成、流动发展和再次淤积的数值方法 |
CN112861372B (zh) * | 2021-03-04 | 2023-03-21 | 中国地质调查局成都地质调查中心 | 一种泥石流容重计算方法 |
CN113128082B (zh) * | 2021-03-15 | 2022-06-17 | 山东大学 | 用于复合材料性能预测的细观模型的构建方法及系统 |
CN113139320B (zh) * | 2021-05-14 | 2022-06-10 | 上海交通大学 | 构建颗粒增强复合材料三维微观构型的方法 |
CN113722932B (zh) * | 2021-09-13 | 2022-07-05 | 江苏集萃先进高分子材料研究所有限公司 | 多维混合导电填料高分子发泡材料电导率预测方法 |
CN114818427B (zh) * | 2022-04-30 | 2023-09-26 | 湖南科技大学 | 一种基于真实颗粒形状的离散元可破碎颗粒模型建模方法 |
CN114925590B (zh) * | 2022-06-24 | 2023-07-21 | 中南大学 | 多用途二维不规则形状集料随机生成方法及模型生成方法 |
CN115107280A (zh) * | 2022-06-24 | 2022-09-27 | 重庆大学 | 一种Voronoi多孔结构智能生成方法 |
CN115081302B (zh) * | 2022-07-15 | 2023-07-07 | 中国矿业大学 | 支护构件与硐室围岩接触及相互作用的模拟方法和系统 |
CN115270477B (zh) * | 2022-08-01 | 2023-04-07 | 河海大学 | 一种采用离散元模拟二维混凝土中孔隙的生成方法 |
CN116486967B (zh) * | 2023-05-12 | 2023-10-03 | 哈尔滨工业大学 | 可控颗粒间距及面积占比的带壳颗粒随机分布的生成方法 |
CN116884540B (zh) * | 2023-06-15 | 2024-05-10 | 湖北工业大学 | 多相材料三维模型生成与连通性判断方法 |
CN117195382B (zh) * | 2023-11-08 | 2024-02-23 | 北京理工大学 | 一种混凝土细观模型的构建方法 |
Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006259910A (ja) * | 2005-03-15 | 2006-09-28 | Fuji Xerox Co Ltd | 粒子充填シミュレーション装置及び粒子充填シミュレーション方法、並びにコンピュータ・プログラム |
US20100211330A1 (en) * | 2009-01-13 | 2010-08-19 | New York University | Packing Properties of Particulate Compositions |
WO2012131372A1 (en) * | 2011-03-31 | 2012-10-04 | Dem Solutions Limited | Method and apparatus for discrete element modeling involving a bulk material |
EP2509009A1 (en) * | 2011-04-05 | 2012-10-10 | Japan Agency for Marine-Earth Science and Technology | Particle simulator and method of simulating particles |
CN104899393A (zh) * | 2015-06-19 | 2015-09-09 | 山东大学 | 一种离散相增强复合材料细观结构的建模方法 |
CN105740532A (zh) * | 2016-01-28 | 2016-07-06 | 重庆交通大学 | 母岩及其颗粒料的二维离散元模型构建方法 |
CN106777807A (zh) * | 2017-01-13 | 2017-05-31 | 北京航空航天大学 | 一种粉末冶金随机粒度分布3d有限元建模与仿真方法 |
Family Cites Families (28)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7353153B2 (en) * | 2001-10-17 | 2008-04-01 | Maria-Grazia Ascenzi | Method and system for modeling bone structure |
US7131105B2 (en) * | 2003-09-19 | 2006-10-31 | Coventor, Inc. | System and method for automatic mesh generation from a system-level MEMS design |
US7142297B2 (en) * | 2003-10-31 | 2006-11-28 | Synopsys Switzerland Llc | Method for simulating the movement of particles |
US20070165948A1 (en) * | 2004-01-13 | 2007-07-19 | Koninklijke Philips Electronic, N.V. | Mesh models with internal discrete elements |
DE602004026566D1 (de) * | 2004-07-28 | 2010-05-27 | Procter & Gamble | Indirekter Druck von AMG |
EA014375B1 (ru) * | 2006-07-12 | 2010-10-29 | Де Юниверсити Оф Квинсленд | Способ прогнозирования характеристик измельчения материала в виде частиц, подвергающегося ударному воздействию |
US20080099569A1 (en) * | 2006-10-31 | 2008-05-01 | Husky Injection Molding Systems Ltd. | Thermal Analysis of Apparatus having Multiple Thermal Control Zones |
RU2009124594A (ru) * | 2006-11-29 | 2011-01-10 | Бейкер Хьюз Инкорпорейтед (Us) | Моделирование разрушения породы в условиях высокого давления методом дискретных элементов |
EP2481550B1 (en) * | 2007-07-02 | 2014-10-08 | MAGMA Giessereitechnologie GmbH | Method for describing the statistical orientation distribution of particles in a simulation of a mould filling process and computer software product including a software code for performing said method. |
WO2009057190A1 (ja) * | 2007-10-29 | 2009-05-07 | Japan Agency For Marine-Earth Science And Technology | 気象シミュレーション装置、及び、方法 |
US8042736B2 (en) * | 2008-04-23 | 2011-10-25 | Engineering Consultants Group, Inc. | Tracking and properties control system for bulk materials |
FR2934050B1 (fr) * | 2008-07-15 | 2016-01-29 | Univ Paris Curie | Procede et dispositif de lecture d'une emulsion |
GB2462261A (en) * | 2008-07-28 | 2010-02-03 | Fujitsu Ltd | Method, apparatus and computer program for simulating behaviou r of thermodynamic systems |
US9342636B2 (en) * | 2008-08-13 | 2016-05-17 | Dem Solutions Ltd | Method and apparatus for simulation by discrete element modeling and supporting customisable particle properties |
US8126684B2 (en) * | 2009-04-10 | 2012-02-28 | Livermore Software Technology Corporation | Topology optimization for designing engineering product |
US8531463B2 (en) * | 2009-08-10 | 2013-09-10 | Dem Solutions Limited | Method and apparatus for discrete element modeling with a virtual geometry object |
EP2317348B1 (en) * | 2009-10-30 | 2014-05-21 | Services Pétroliers Schlumberger | Method for building a depositional space corresponding to a geological domain |
US9122821B2 (en) * | 2010-05-25 | 2015-09-01 | Siemens Products Lifecycle Management Software Inc. | Method and system for simulation of automated processes |
US8554527B2 (en) * | 2011-04-08 | 2013-10-08 | Japan Agency For Marine-Earth Science And Technology | Particle simulator and method of simulating particles |
US9020784B2 (en) * | 2012-04-27 | 2015-04-28 | Livermore Software Technology Corp. | Methods for providing a bonded-particle model in computer aided engineering system |
US20140278292A1 (en) * | 2013-03-15 | 2014-09-18 | Airbus Operations (Sas) | Method for coupling non-destructive inspection data for a material or structure to an analysis tool |
US9861569B2 (en) * | 2013-05-01 | 2018-01-09 | New York University | Specificity, flexibility and valence of DNA bonds for guided emulsion architecture |
CN103425899B (zh) * | 2013-09-10 | 2017-03-29 | 南京大学 | 用于页岩气水力压裂的三维离散元建模和模拟方法 |
US20150112651A1 (en) * | 2013-10-18 | 2015-04-23 | Livermore Software Technology Corporation | Bond Model For Representing Heterogeneous Material In Discrete Element Method |
CN103745042A (zh) * | 2013-12-25 | 2014-04-23 | 广西科技大学 | 一种壁流式颗粒捕集器的建模方法 |
EP3097148A4 (en) * | 2014-01-23 | 2017-08-30 | Peterson Chemical Technology LLC | Cushioning foams containing reflective particulates with visually distinguishable reflective surfaces to create a unique appearance |
US9792391B2 (en) * | 2014-06-06 | 2017-10-17 | Siemens Product Lifecyle Management Software Inc. | Refining of material definitions for designed parts |
US11783100B2 (en) * | 2018-09-14 | 2023-10-10 | Northwestern University | Integrated process-structure-property modeling frameworks and methods for design optimization and/or performance prediction of material systems and applications of same |
-
2017
- 2017-07-13 CN CN201710570950.1A patent/CN107423498B/zh active Active
- 2017-10-19 WO PCT/CN2017/106883 patent/WO2019010859A1/zh active Application Filing
- 2017-10-19 US US16/314,502 patent/US11170144B2/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006259910A (ja) * | 2005-03-15 | 2006-09-28 | Fuji Xerox Co Ltd | 粒子充填シミュレーション装置及び粒子充填シミュレーション方法、並びにコンピュータ・プログラム |
US20100211330A1 (en) * | 2009-01-13 | 2010-08-19 | New York University | Packing Properties of Particulate Compositions |
WO2012131372A1 (en) * | 2011-03-31 | 2012-10-04 | Dem Solutions Limited | Method and apparatus for discrete element modeling involving a bulk material |
EP2509009A1 (en) * | 2011-04-05 | 2012-10-10 | Japan Agency for Marine-Earth Science and Technology | Particle simulator and method of simulating particles |
CN104899393A (zh) * | 2015-06-19 | 2015-09-09 | 山东大学 | 一种离散相增强复合材料细观结构的建模方法 |
CN105740532A (zh) * | 2016-01-28 | 2016-07-06 | 重庆交通大学 | 母岩及其颗粒料的二维离散元模型构建方法 |
CN106777807A (zh) * | 2017-01-13 | 2017-05-31 | 北京航空航天大学 | 一种粉末冶金随机粒度分布3d有限元建模与仿真方法 |
Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111783269A (zh) * | 2019-03-18 | 2020-10-16 | 山东高速集团有限公司 | 一种基于离散元分析道路空隙结构由于扬尘造成阻塞的方法 |
CN111783269B (zh) * | 2019-03-18 | 2024-01-12 | 山东高速集团有限公司 | 一种基于离散元分析道路空隙结构由于扬尘造成阻塞的方法 |
CN110210178A (zh) * | 2019-06-26 | 2019-09-06 | 西安理工大学 | 一种基于Python再生混凝土三维随机球形骨料模型的构建方法 |
CN111027244A (zh) * | 2019-12-03 | 2020-04-17 | 天津大学 | 一种百亿级颗粒模型的构建方法 |
CN111027244B (zh) * | 2019-12-03 | 2024-03-12 | 天津大学 | 一种百亿级颗粒模型的构建方法 |
CN111428359A (zh) * | 2020-03-23 | 2020-07-17 | 河海大学 | 一种考虑晶粒咬合的各向异性岩石建模方法 |
CN111428359B (zh) * | 2020-03-23 | 2022-03-08 | 河海大学 | 一种考虑晶粒咬合的各向异性岩石建模方法 |
CN112084694B (zh) * | 2020-09-15 | 2023-08-25 | 河南理工大学 | 一种考虑非理想界面的颗粒增强复合材料微观结构的几何建模方法 |
CN112084694A (zh) * | 2020-09-15 | 2020-12-15 | 河南理工大学 | 一种考虑非理想界面的颗粒增强复合材料微观结构的几何建模方法 |
CN112461718A (zh) * | 2020-11-18 | 2021-03-09 | 中国石油大学(华东) | 孔隙度与颗粒粒径分布关系表征方法 |
CN113111560A (zh) * | 2021-04-26 | 2021-07-13 | 山东大学 | 一种非均质矿物铸件细观结构模型生成方法及系统 |
CN113962066A (zh) * | 2021-09-27 | 2022-01-21 | 太原理工大学 | 一种含六相组分的钢筋混凝土三维细观模型 |
CN113962066B (zh) * | 2021-09-27 | 2024-03-19 | 太原理工大学 | 一种含六相组分的钢筋混凝土三维细观模型 |
CN115050431A (zh) * | 2022-04-27 | 2022-09-13 | 中南大学 | 一种水泥稳定再生集料的三维细观结构的建模分析方法 |
CN115050431B (zh) * | 2022-04-27 | 2024-05-03 | 中南大学 | 一种水泥稳定再生集料的三维细观结构的建模分析方法 |
Also Published As
Publication number | Publication date |
---|---|
US20190332733A1 (en) | 2019-10-31 |
CN107423498B (zh) | 2020-03-10 |
CN107423498A (zh) | 2017-12-01 |
US11170144B2 (en) | 2021-11-09 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
WO2019010859A1 (zh) | 一种高致密度离散颗粒多相体系的建模方法 | |
Gao et al. | Two methods for pore network of porous media | |
De Jaeger et al. | An experimentally validated and parameterized periodic unit-cell reconstruction of open-cell foams | |
Jerier et al. | Packing spherical discrete elements for large scale simulations | |
Du Plessis et al. | Pore-scale derivation of the Ergun equation to enhance its adaptability and generalization | |
Liu et al. | Simulation and analytical validation of forced convection inside open-cell metal foams | |
Sattari et al. | Meso-scale modeling of heat transport in a heterogeneous cemented geomaterial by lattice element method | |
Chen et al. | Global concurrent cross-scale nonlinear analysis approach of complex CFRD systems considering dynamic impervious panel-rockfill material-foundation interactions | |
Shi et al. | Discrete element cluster modeling of complex mesoscopic particles for use with the particle flow code method | |
Benabbou et al. | Geometrical modeling of granular structures in two and three dimensions. application to nanostructures | |
Lin et al. | Lattice Boltzmann simulation of fluid flow through random packing beds of Platonic particles: Effect of particle characteristics | |
Kozicki et al. | Relationship between vortex structures and shear localization in 3D granular specimens based on combined DEM and Helmholtz–Hodge decomposition | |
Burtseva et al. | Packing of monosized spheres in a cylindrical container: models and approaches | |
Grose et al. | Simulation and characterization of nanoparticle thermal conductivity for a microscale selective laser sintering system | |
Kilingar et al. | Computational generation of open-foam representative volume elements with morphological control using distance fields | |
CN113128082B (zh) | 用于复合材料性能预测的细观模型的构建方法及系统 | |
Festuccia et al. | Open-cell metal foam mesh generation for lattice Boltzmann simulations | |
Matyka et al. | Anisotropy of flow in stochastically generated porous media | |
Kadushnikov et al. | Computer simulation of spherical particle sintering | |
Varnavides et al. | Simulating infiltration as a sequence of pinning and de-pinning processes | |
Remond et al. | Simulation of the packing of granular mixtures of non-convex particles and voids characterization | |
Romanus et al. | An immersed boundary-lattice Boltzmann framework for fully resolved simulations of non-spherical particle settling in unbounded domain | |
Urbanic et al. | Development of adaptable light weighting methods for material extrusion processes | |
Burtseva et al. | Monosized sphere packing approach in the nanoporous structure modeling | |
Li et al. | Computational study on cell structure evolution of random liquid and metal-melt foams |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
121 | Ep: the epo has been informed by wipo that ep was designated in this application |
Ref document number: 17917508 Country of ref document: EP Kind code of ref document: A1 |
|
NENP | Non-entry into the national phase |
Ref country code: DE |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 17917508 Country of ref document: EP Kind code of ref document: A1 |
|
32PN | Ep: public notification in the ep bulletin as address of the adressee cannot be established |
Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 20.10.2020) |
|
122 | Ep: pct application non-entry in european phase |
Ref document number: 17917508 Country of ref document: EP Kind code of ref document: A1 |