CN108446422B - Multi-scale coupling simulation method for complex microfluidic chip - Google Patents
Multi-scale coupling simulation method for complex microfluidic chip Download PDFInfo
- Publication number
- CN108446422B CN108446422B CN201810083277.3A CN201810083277A CN108446422B CN 108446422 B CN108446422 B CN 108446422B CN 201810083277 A CN201810083277 A CN 201810083277A CN 108446422 B CN108446422 B CN 108446422B
- Authority
- CN
- China
- Prior art keywords
- microfluidic chip
- fluid
- setting
- simulation
- module
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
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
- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/36—Circuit design at the analogue level
- G06F30/367—Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Evolutionary Computation (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a multi-scale coupling simulation method for a complex microfluidic chip, which comprises the following steps: firstly, performing simulation based on a finite element method on each single physical field action of biological particles in a microfluidic chip, and then performing multiphase flow simulation of a biological particle model based on a lattice Boltzmann method on the comprehensive action of multiple physical fields of the biological particles; compared with the problem of deformation and tracking at a two-phase interface which is difficult to process by the traditional simulation method, the invention adopts the mesoscopic lattice boltzmann simulation method, and can well reflect the deformation and the tracking of the movement locus of the cell; the mesoscopic lattice Boltzmann simulation method is adopted to solve the internal flow field of the microfluidic chip, is not limited by the assumption of fluid continuity, and can reflect the essence and slight change of fluid flow.
Description
Technical Field
The invention relates to the technical field of micro total analysis systems, in particular to a multi-scale coupling simulation method for a complex microfluidic chip.
Background
With the development of Micro Electro-mechanical systems (MEMS), the Micro fluidic Chip technology has gained much attention, which is a scientific technology mainly characterized by the manipulation of fluids in the Micro-scale space, and aims to integrate the basic functions of laboratories such as biology, chemistry, medicine, etc. into a centimeter-scale Chip, so that the Micro fluidic Chip is also called a Lab-On-a-Chip. In the microfluidic chip, laminar flow therein can be precisely controlled by fluid acting force or external field force, or thousands of cells can be manipulated. Due to the miniaturization of the microfluidic chip, the microfluidic chip can realize portable, low-consumption and integrated analysis, and can greatly shorten the analysis time, so that the microfluidic chip technology becomes an important means in particle manipulation. With the development of computer science, the numerical simulation method is more and more widely applied to the simulation of complex flow, which also provides a new way for researching complex microfluidic chips. The numerical simulation of the process of manipulating particles by the complex microfluidic chip has the following characteristics: 1. the particles are usually flexible biological cells, the deformation of the biological cells needs to be researched, and the motion track of the biological cells needs to be tracked; 2. biological cells in the microfluidic chip are simultaneously subjected to the action of multiple physical fields such as a flow field, an electric field and the like; 3. the internal flow channel reaches the micro scale, but the whole size of the whole microfluidic chip is in the macro scale. However, the conventional single numerical simulation method and the fluid dynamics model have the following problems in view of the above characteristics: 1. when a multiphase module is used for cell deformation and motion simulation, the problems of deformation and tracking at the interface of two phases are difficult to process; 2. the numerical simulation method starts from a macroscopic view, and the flowing essence of fluid inside a chip is difficult to describe; 3. the simulation calculation amount of the whole chip is large, the parallel efficiency of the traditional single simulation method is low, and the calculation time is long.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a multi-scale coupling simulation method for a complex microfluidic chip, which is a finite element-lattice Boltzmann coupling simulation method based on the complex microfluidic chip and is used for solving the problems that deformation and tracking at a two-phase interface are difficult to process and fluid flow inside the chip is difficult to depict, the calculated amount is large and the parallel efficiency is low when a multi-phase module is used for cell deformation and motion simulation in the traditional single simulation method.
The purpose of the invention is realized by the following technical scheme:
a multi-scale coupling simulation method for a complex microfluidic chip comprises the following steps:
firstly, performing simulation based on a finite element method on each single physical field action of biological particles in a microfluidic chip, and then performing multiphase flow simulation of a biological particle model based on a lattice Boltzmann method on the comprehensive action of multiple physical fields of the biological particles; the simulation method specifically comprises the following three modules:
(1) a solid model of the microfluidic chip and a fluid domain solid model modeling module; the module is the most basic module for completing simulation, and mainly establishes a solid model and a fluid domain solid model of a microfluidic chip, and comprises the following specific steps:
s1.1, establishing a solid model of the microfluidic chip; according to the actual size of the microfluidic chip, a three-dimensional solid modeling software UG is used for establishing a solid model of the chip, and the structure of the chip needs to be properly optimized in the process: considering that a sharp corner which has great influence on the calculation precision exists in the structure, small-size fillet processing can be carried out on the sharp corner so as to reduce the calculation error brought by the sharp corner in the calculation and reduce the influence on the flow of fluid and biological cells;
s1.2, establishing a fluid domain entity model of the microfluidic chip; after S1.1 is finished, extracting a fluid domain of the microfluidic chip by using a Boolean operation command in three-dimensional entity modeling software UG, and outputting an extracted fluid domain model as an stp format file;
(2) a simulation module based on a finite element method; biological cells in the microfluidic chip are subjected to the comprehensive action of multiple physical fields, the module uses Comsol software developed based on a finite element method to simulate, and the specific steps are as follows:
s2.1, performing mesh division on fluid and setting corresponding initial conditions, importing an stp format file of the microfluidic chip fluid domain model obtained in the S1.2 into Comsol software for mesh division, and simultaneously adding a corresponding simulation module of the Comsol software, wherein the simulation module of the Comsol software comprises a fluid analysis module, an electric field analysis module and a particle flow tracking module, and setting fluid and dielectric characteristic parameters of fluid and biological particles;
s2.2, setting corresponding flow field boundary conditions at the fluid analysis module: setting the inlet conditions as a velocity inlet to define the velocity of the fluid flowing into the microfluidic chip; setting an outlet condition to a pressure outlet to define a pressure at the outlet; setting other boundaries of the microfluidic chip as rebound boundaries, and solving the velocity distribution of the flow field;
s2.3, setting corresponding electric field boundary conditions at the electric field analysis module: setting the frequency of the current to be f; defining a high potential at a positive electrode of the microfluidic chip and a low potential at a negative electrode of the microfluidic chip; setting other boundaries of the microfluidic chip as insulating boundaries, and solving the intensity distribution of the electric field;
s2.4, setting corresponding boundary conditions of a flow field and an electric field at the particle tracking module: the fluid inlet is arranged as a particle release inlet; setting the fluid outlet as a particle collecting outlet; setting flow field velocity distribution data required for solving the flow field drag force suffered by the particles, wherein the data is the flow field velocity distribution data solved in S2.2.2; setting electric field intensity distribution data required for solving the dielectrophoresis force of the electric field on the particles, wherein the electric field intensity distribution data are the electric field intensity distribution data solved in S2.3; finally solving dielectrophoresis force data of the particles in the microfluidic chip along with the time and position changes;
s2.5, processing dielectrophoresis force data on the particles; outputting the dielectrophoresis force data which is solved in the S2.4 and changes along with time and position to a data file with a format txt;
(3) a simulation module based on a lattice Boltzmann method; in order to solve the deformation and the motion trail of biological cells in the microfluidic chip, the module uses Xflow software developed based on a lattice Boltzmann method to simulate, and the specific steps are as follows:
s3.1, selecting a simulation module and setting initial conditions; selecting a fluid analysis module as a multi-phase flow module, setting one phase as a fluid with cell characteristics, and controlling the shape of the phase to be the circular shape of the cell; taking the txt data file containing the dielectrophoresis force data obtained in the S2.5 as one of initial conditions, applying the initial conditions to a circular cell area, automatically reading the dielectrophoresis force data in the txt data file along with simulation by Xflow software, and further setting the material property of the fluid;
s3.2, setting corresponding boundary conditions; setting the fluid inlet of the micro-fluidic chip as a speed inlet so as to define the speed of the fluid flowing into the micro-fluidic chip; setting a fluid outlet of the microfluidic chip as a pressure outlet to define the pressure of fluid at the outlet; and setting other wall surfaces of the microfluidic chip as rebound boundaries, and further solving the deformation and motion trail of the cells under the combined action of the flow field and the electric field in the flowing process.
Compared with the prior art, the invention has the following beneficial effects:
(1) compared with the problem of deformation and tracking at a two-phase interface which is difficult to process by the traditional simulation method, the invention adopts the mesoscopic lattice boltzmann simulation method, and can well reflect the deformation and the tracking of the movement locus of the cell; the mesoscopic lattice Boltzmann simulation method is adopted to solve the internal flow field of the microfluidic chip, which is not limited by the assumption of fluid continuity and can reflect the essence and subtle changes of fluid flow;
(2) the invention adopts an indirect coupling method, solves a control equation of fluid flow by adopting a mesoscopic lattice Boltzmann simulation method, solves dielectrophoresis force borne by an electric field and cells in a microfluidic chip by adopting a macroscopic finite element simulation method, and realizes indirect coupling between the two by transmitting the dielectrophoresis force for solving the cells to the fluid flow field flow.
Drawings
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a flow chart of the present invention;
FIG. 3 is a grid division diagram of the present invention;
FIG. 4 is a diagram of the deformation and trajectory of cells according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but the present invention is not limited thereto.
As shown in fig. 1 to 4, a multi-scale coupling simulation method for a complex microfluidic chip includes the following steps:
firstly, simulating each single physical field action (such as physical field action of an electric field or a magnetic field and the like) on biological particles in a micro-fluidic chip based on a finite element method, and then carrying out multiphase flow simulation on a biological particle model based on a lattice Boltzmann method on the multi-physical field comprehensive action on the biological particles, wherein the multi-physical field comprehensive action is the comprehensive action of the physical fields such as the electric field, the magnetic field and the like;
the simulation result of the macroscopic scale finite element method as the initial condition of the mesoscopic scale lattice boltzmann method comprises the following steps: the time step length of the simulation of the finite element method under the macroscopic scale and the lattice boltzmann simulation under the mesoscopic scale need to be matched; the simulation result of the finite element method under the macro scale needs to be output to a data file with the format txt.
The simulation method specifically comprises the following three modules:
(1) a solid model of the microfluidic chip and a fluid domain solid model modeling module; the module is the most basic module for completing simulation, and mainly establishes a solid model and a fluid domain solid model of a microfluidic chip, and comprises the following specific steps:
s1.1, establishing a solid model of the microfluidic chip; according to the actual size of the microfluidic chip, a three-dimensional solid modeling software UG is used for establishing a solid model of the chip, and the structure of the chip needs to be properly optimized in the process: considering that a sharp corner which has great influence on the calculation precision exists in the structure, small-size fillet processing can be carried out on the sharp corner so as to reduce the calculation error brought by the sharp corner in the calculation and reduce the influence on the flow of fluid and biological cells;
s1.2, establishing a fluid domain entity model of the microfluidic chip; after S1.1 is finished, extracting a fluid domain (a fluid flowing area, namely an internal flow channel) of the microfluidic chip by using a Boolean operation command in three-dimensional entity modeling software UG, and outputting an extracted fluid domain model as an stp format file;
(2) a simulation module based on a finite element method; biological cells in the microfluidic chip are subjected to the comprehensive action of multiple physical fields, the module uses Comsol software developed based on a finite element method to simulate, and the specific steps are as follows:
s2.1, performing meshing on fluid and setting corresponding initial conditions, as shown in FIG. 3, importing an stp format file of a microfluidic chip fluid domain model obtained in S1.2 into Comsol software for meshing, and simultaneously adding a corresponding simulation module of the Comsol software, wherein the simulation module of the Comsol software comprises a fluid analysis module, an electric field analysis module and a particle flow tracking module, and setting fluid and dielectric characteristic parameters of fluid and biological particles;
s2.2, setting corresponding flow field boundary conditions at the fluid analysis module: setting the inlet conditions as a velocity inlet to define the velocity of the fluid flowing into the microfluidic chip; setting an outlet condition to a pressure outlet to define a pressure at the outlet; setting other boundaries of the microfluidic chip as rebound boundaries Wall, and solving the velocity distribution of the flow field;
s2.3, setting corresponding electric field boundary conditions at the electric field analysis module: setting the frequency of the current to be f; defining a high potential at a positive electrode of the microfluidic chip and a low potential at a negative electrode of the microfluidic chip; setting other boundaries of the microfluidic chip as insulating boundaries, and solving the intensity distribution of the electric field;
s2.4, setting corresponding boundary conditions of a flow field and an electric field at the particle tracking module: the fluid inlet is arranged as a particle release inlet; setting the fluid outlet as a particle collecting outlet; setting flow field velocity distribution data required for solving the flow field drag force suffered by the particles, wherein the data is the flow field velocity distribution data solved in S2.2.2; setting electric field intensity distribution data required for solving the dielectrophoresis force of the electric field on the particles, wherein the electric field intensity distribution data are the electric field intensity distribution data solved in S2.3; finally solving dielectrophoresis force data of the particles in the microfluidic chip along with the time and position changes;
s2.5, processing dielectrophoresis force data on the particles; outputting the dielectrophoresis force data which is solved in the S2.4 and changes along with time and position to a data file with a format txt;
(3) a simulation module based on a lattice Boltzmann method; in order to solve the deformation and the motion trail of biological cells in the microfluidic chip, the module uses Xflow software developed based on a lattice Boltzmann method to simulate, and the specific steps are as follows:
s3.1, selecting a simulation module and setting initial conditions; the Xflow software has a mesh-free method, so that mesh division is not needed, a fluid analysis module is selected as a multi-phase flow module, one phase is set as a fluid with cell characteristics, and the shape of the phase is controlled to be a circular shape of cells; then, the txt data file containing the dielectrophoretic force data obtained in S2.5 is converted into acceleration through a Newton second law, the acceleration is input into corresponding software (namely Xfolw software) based on a lattice Boltzmann method to serve as one of initial conditions of a mesoscopic scale simulation method, the acceleration is applied to a cell circular region, the Xflow software automatically reads the dielectrophoretic force data in the txt data file along with simulation, and then the material property of the fluid is set;
s3.2, setting corresponding boundary conditions; setting the fluid inlet of the micro-fluidic chip as a speed inlet so as to define the speed of the fluid flowing into the micro-fluidic chip; setting a fluid outlet of the microfluidic chip as a pressure outlet to define the pressure of fluid at the outlet; setting other Wall surfaces of the microfluidic chip as rebound boundaries Wall, and further solving the deformation and motion trail of the cell under the combined action of the flow field and the electric field in the flowing process, specifically, as shown in fig. 4, setting the time step and the total time which are the same as those in S2.5 to match with the simulation result output by the S2.5 according to the time and position change, and performing simulation calculation by solving a mass conservation equation, a momentum conservation equation and a particle motion equation to solve the deformation and motion trail of the cell under the combined action of the flow field and the electric field in the flowing process.
Compared with the problem of deformation and tracking at a two-phase interface which is difficult to process by the traditional simulation method, the invention adopts the mesoscopic lattice boltzmann simulation method, and can well reflect the deformation and the tracking of the movement locus of the cell; the mesoscopic lattice Boltzmann simulation method is adopted to solve the internal flow field of the microfluidic chip, which is not limited by the assumption of fluid continuity and can reflect the essence and subtle changes of fluid flow; the invention adopts an indirect coupling method, solves a control equation of fluid flow by adopting a mesoscopic lattice Boltzmann simulation method, solves dielectrophoresis force borne by an electric field and cells in a microfluidic chip by adopting a macroscopic finite element simulation method, and realizes indirect coupling between the two by transmitting the dielectrophoresis force for solving the cells to the fluid flow field flow.
The present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents and are included in the scope of the present invention.
Claims (1)
1. A multi-scale coupling simulation method for a complex microfluidic chip is characterized by comprising the following steps:
firstly, performing simulation based on a finite element method on each single physical field action of biological particles in a microfluidic chip, and then performing multiphase flow simulation of a biological particle model based on a lattice Boltzmann method on the comprehensive action of multiple physical fields of the biological particles; the simulation method specifically comprises the following three modules:
(1) a solid model of the microfluidic chip and a fluid domain solid model modeling module; the module is the most basic module for completing simulation, and mainly establishes a solid model and a fluid domain solid model of a microfluidic chip, and comprises the following specific steps:
s1.1, establishing a solid model of the microfluidic chip; according to the actual size of the microfluidic chip, a three-dimensional solid modeling software UG is used for establishing a solid model of the chip, and the structure of the chip needs to be properly optimized in the process: considering that a sharp corner which has great influence on the calculation precision exists in the structure, small-size fillet processing can be carried out on the sharp corner so as to reduce the calculation error brought by the sharp corner in the calculation and reduce the influence on the flow of fluid and biological cells;
s1.2, establishing a fluid domain entity model of the microfluidic chip; after S1.1 is finished, extracting a fluid domain of the microfluidic chip by using a Boolean operation command in three-dimensional entity modeling software UG, and outputting an extracted fluid domain model as an stp format file;
(2) a simulation module based on a finite element method; biological cells in the microfluidic chip are subjected to the comprehensive action of multiple physical fields, the module uses Comsol software developed based on a finite element method to simulate, and the specific steps are as follows:
s2.1, performing mesh division on fluid and setting corresponding initial conditions, importing an stp format file of the microfluidic chip fluid domain model obtained in the S1.2 into Comsol software for mesh division, and simultaneously adding a corresponding simulation module of the Comsol software, wherein the simulation module of the Comsol software comprises a fluid analysis module, an electric field analysis module and a particle flow tracking module, and setting fluid and dielectric characteristic parameters of fluid and biological particles;
s2.2, setting corresponding flow field boundary conditions at the fluid analysis module: setting the inlet conditions as a velocity inlet to define the velocity of the fluid flowing into the microfluidic chip; setting an outlet condition to a pressure outlet to define a pressure at the outlet; setting other boundaries of the microfluidic chip as rebound boundaries, and solving the velocity distribution of the flow field;
s2.3, setting corresponding electric field boundary conditions at the electric field analysis module: setting the frequency of the current to be f; defining a high potential at a positive electrode of the microfluidic chip and a low potential at a negative electrode of the microfluidic chip; setting other boundaries of the microfluidic chip as insulating boundaries, and solving the intensity distribution of the electric field;
s2.4, setting corresponding boundary conditions of a flow field and an electric field at the particle tracking module: the fluid inlet is arranged as a particle release inlet; setting the fluid outlet as a particle collecting outlet; setting flow field velocity distribution data required for solving the flow field drag force suffered by the particles, wherein the data is the flow field velocity distribution data solved in S2.2; setting electric field intensity distribution data required for solving the dielectrophoresis force of the electric field on the particles, wherein the electric field intensity distribution data are the electric field intensity distribution data solved in S2.3; finally solving dielectrophoresis force data of the particles in the microfluidic chip along with the time and position changes;
s2.5, processing dielectrophoresis force data on the particles; outputting the dielectrophoresis force data which is solved in the S2.4 and changes along with time and position to a data file with a format txt;
(3) a simulation module based on a lattice Boltzmann method; in order to solve the deformation and the motion trail of biological cells in the microfluidic chip, the module uses Xflow software developed based on a lattice Boltzmann method to simulate, and the specific steps are as follows:
s3.1, selecting a simulation module and setting initial conditions; selecting a fluid analysis module as a multi-phase flow module, setting one phase as a fluid with cell characteristics, and controlling the shape of the phase to be the circular shape of the cell; taking the txt data file containing the dielectrophoresis force data obtained in the S2.5 as one of initial conditions, applying the initial conditions to a circular cell area, automatically reading the dielectrophoresis force data in the txt data file along with simulation by Xflow software, and further setting the material property of the fluid;
s3.2, setting corresponding boundary conditions; setting the fluid inlet of the micro-fluidic chip as a speed inlet so as to define the speed of the fluid flowing into the micro-fluidic chip; setting a fluid outlet of the microfluidic chip as a pressure outlet to define the pressure of fluid at the outlet; and setting other wall surfaces of the microfluidic chip as rebound boundaries, and further solving the deformation and motion trail of the cells under the combined action of the flow field and the electric field in the flowing process.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810083277.3A CN108446422B (en) | 2018-01-29 | 2018-01-29 | Multi-scale coupling simulation method for complex microfluidic chip |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810083277.3A CN108446422B (en) | 2018-01-29 | 2018-01-29 | Multi-scale coupling simulation method for complex microfluidic chip |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108446422A CN108446422A (en) | 2018-08-24 |
| CN108446422B true CN108446422B (en) | 2021-09-07 |
Family
ID=63191118
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810083277.3A Active CN108446422B (en) | 2018-01-29 | 2018-01-29 | Multi-scale coupling simulation method for complex microfluidic chip |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108446422B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109682745B (en) * | 2019-01-07 | 2020-07-07 | 清华大学 | Single cell parameter measuring method and device |
| CN111475983B (en) * | 2020-05-13 | 2024-01-19 | 广东工业大学 | Indirect coupling simulation method of microfluidic dielectrophoresis sorting chip |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6868347B2 (en) * | 2002-03-19 | 2005-03-15 | The Regents Of The University Of California | System for real time, non-invasive metrology of microfluidic chips |
| CN104866695A (en) * | 2015-06-24 | 2015-08-26 | 武汉大学 | GPU-accelerated fluid-structure coupling simulation method through immersion boundary and lattice Boltzmann methods |
| CN105842324A (en) * | 2016-04-27 | 2016-08-10 | 河海大学常州校区 | Integrated micro-fluidic chip and working method thereof |
-
2018
- 2018-01-29 CN CN201810083277.3A patent/CN108446422B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6868347B2 (en) * | 2002-03-19 | 2005-03-15 | The Regents Of The University Of California | System for real time, non-invasive metrology of microfluidic chips |
| CN104866695A (en) * | 2015-06-24 | 2015-08-26 | 武汉大学 | GPU-accelerated fluid-structure coupling simulation method through immersion boundary and lattice Boltzmann methods |
| CN105842324A (en) * | 2016-04-27 | 2016-08-10 | 河海大学常州校区 | Integrated micro-fluidic chip and working method thereof |
Non-Patent Citations (3)
| Title |
|---|
| Numerical simulation about trapping two particles in microfluidic dielectrophoretic chip;Liguo Chen等;《 2012 International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)》;20130307;第288-291页 * |
| 基于介电电泳的粒子分离微流控芯片的研究;曾一笑等;《仪表技术与传感器》;20170526(第2期);第5-8、14页 * |
| 格子玻尔兹曼方法模拟弯流道中粒子的惯性迁移行为;孙东科等;《物理学报》;20130131;第62卷(第2期);第399-407页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108446422A (en) | 2018-08-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Zawawi et al. | A review: Fundamentals of computational fluid dynamics (CFD) | |
| Pingen et al. | Topology optimization of flow domains using the lattice Boltzmann method | |
| Chen et al. | 3D numerical simulation of droplet passive breakup in a micro-channel T-junction using the Volume-Of-Fluid method | |
| CN108446422B (en) | Multi-scale coupling simulation method for complex microfluidic chip | |
| Chakrabarty et al. | Design automation for microfluidics-based biochips | |
| CN113569450B (en) | Method for estimating and controlling suspension and residence of liquid drops | |
| Gad-el-Hak | Flow physics | |
| Thompson et al. | Transitional and turbulent flow modeling in a tesla valve | |
| Waheed et al. | Dissipative particle dynamics for modeling micro-objects in microfluidics: application to dielectrophoresis | |
| Liu et al. | Effects of two surface acoustic wave sorting chips on particles multi-level sorting | |
| Hashem et al. | Compound droplet modeling for circulating tumor cell microfiltration with adaptive meshing refinement | |
| Padhy et al. | FluTO: Graded multi-scale topology optimization of large contact area fluid-flow devices using neural networks | |
| Li et al. | A sheathless high precise particle separation chip integrated contraction–expansion channel and deterministic lateral displacement | |
| CN102567580A (en) | Wet-type friction plate characteristic analysis method based on computational fluid dynamics | |
| Hoang et al. | Modeling of low-capillary number segmented flows in microchannels using OpenFOAM | |
| Mehner et al. | Dynamic Finite Element Modelling of a Hydrogel-Based Micro-Valve With 2-Way Fluid Structure Interactions | |
| KR20100055556A (en) | Computer simulation method by thermal lattice boltzmann method | |
| Shahraki et al. | Coupling contraction-expansion arrays with spiral microchannels to enhance microfluidic-based particle/cell separation | |
| Matviykiv | Mesoscale Modeling of Complex Microfluidic Flows | |
| Sarstedt et al. | Topology Optimization for fluid flow employing local optimality criteria | |
| Tanjung | Computational Fluid Dynamics Notes: Fluid Flow Equations | |
| Waheed et al. | Microparticle motion under dielectrophoresis: immersed boundary—Lattice Boltzmann-based multiphase model and experiments | |
| Tryggvason | Direct numerical simulations of multiphase flow | |
| Islam et al. | Simulation of Micro-Powder Injection Molding Using a Dynamic Mesh Approach | |
| Athavale et al. | Coupled electrostatics-structures-fluidic simulations of a bead mesopump |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |