CN115496013A - Method for predicting flow parameters of copper nanoparticle fluid and motion state of nanoparticles - Google Patents
Method for predicting flow parameters of copper nanoparticle fluid and motion state of nanoparticles Download PDFInfo
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- CN115496013A CN115496013A CN202211286763.8A CN202211286763A CN115496013A CN 115496013 A CN115496013 A CN 115496013A CN 202211286763 A CN202211286763 A CN 202211286763A CN 115496013 A CN115496013 A CN 115496013A
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- 239000002105 nanoparticle Substances 0.000 title claims abstract description 48
- 239000012530 fluid Substances 0.000 title claims abstract description 36
- 229910052802 copper Inorganic materials 0.000 title claims abstract description 19
- 239000010949 copper Substances 0.000 title claims abstract description 19
- 238000000034 method Methods 0.000 title claims abstract description 15
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 title claims description 15
- 230000002776 aggregation Effects 0.000 claims abstract description 9
- 238000004088 simulation Methods 0.000 claims abstract description 6
- 238000012805 post-processing Methods 0.000 claims abstract description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 11
- 230000002209 hydrophobic effect Effects 0.000 claims description 6
- 238000002360 preparation method Methods 0.000 claims description 6
- 238000012545 processing Methods 0.000 claims description 4
- 238000012800 visualization Methods 0.000 claims description 4
- 238000005054 agglomeration Methods 0.000 claims description 3
- 230000000903 blocking effect Effects 0.000 claims 1
- 238000004220 aggregation Methods 0.000 abstract description 6
- 238000009826 distribution Methods 0.000 abstract description 5
- 238000002474 experimental method Methods 0.000 abstract description 2
- 238000012900 molecular simulation Methods 0.000 abstract description 2
- 230000002040 relaxant effect Effects 0.000 abstract 1
- 238000010586 diagram Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003631 expected effect Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000000329 molecular dynamics simulation Methods 0.000 description 1
- 239000002086 nanomaterial Substances 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
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Abstract
The invention relates to a method for predicting a flow parameter of a water-copper nanoparticle fluid and a motion state of nanoparticles, belonging to the technical field of molecular simulation. The method comprises the steps of establishing a model, defining atoms, balancing a force field, minimizing energy, relaxing temperature, achieving thermodynamic equilibrium, simulating and post-processing data. The invention provides a nano fluid simulation process, a flow channel model and nano particle establishment, which are mainly used for researching a micro fluid different from macroscopic motion, analyzing the speed, the temperature and the distribution of density in a channel, and analyzing the slippage and the aggregation time of nano particles in motion states of the nano particles at different times, thereby providing reference for experiments.
Description
Technical Field
The invention relates to a method for predicting a flow parameter of a water-copper nanoparticle fluid and a motion state of nanoparticles, belonging to the technical field of molecular simulation.
Background
The nanofluid is prepared by mixing a base liquid and nanoparticles, and has to be deeply researched as a new nano material with excellent heat transfer and transport capacity. The traditional macroscopic motion model can not accurately predict the motion model of the microfluidic. In the preparation of nanofluids, reagents are often added to prevent agglomeration of nanoparticles, however, it is difficult to predict the expected effect of preparation to use and the various effects of various external complications on nanofluids after the nanofluids are put into use before preparation and application.
Disclosure of Invention
The invention aims to provide a method for predicting flow parameters of a water-copper nanoparticle fluid and a motion state of nanoparticles, which simulates the flow of the nanoparticle fluid to achieve stable testing speed, density, temperature and slippage length by utilizing non-equilibrium molecular dynamics, and the motion state of the nanoparticles at different times and the particle aggregation time, is used for researching the motion rule of the water and the copper nanoparticles in a copper wall flow channel, and provides motion reference for an environment which cannot be realized by a macroscopic experiment.
The technical scheme adopted by the invention is as follows: a method for predicting the fluid flow parameters and the motion states of water copper nanoparticles comprises the following steps:
1) Establishing a model: parameters required for model establishment are set in the molecular dynamics software lammps:
establishing walls of an upper flow passage and a lower flow passage of a model;
dividing a runner area;
arranging the position of the copper nano-particles;
2) Defining atoms, namely the number of atoms corresponding to the flow channel region in the filling step 1):
filling atoms, and setting corresponding molar mass;
3) Force field balance, simulating real force in reality:
setting different force field parameters to realize hydrophilic and hydrophobic wall surfaces;
4) Performing energy minimization:
system balance is achieved, and preparation is simulated;
5) Temperature relaxation is carried out to reach thermodynamic equilibrium:
setting the temperature to 300k to reach the normal temperature;
6) Carrying out simulation:
setting the force to make the fluid flow to a stable flow rate;
setting a time step length;
layering the model, collecting data and outputting the data, wherein the collected data comprises temperature, speed, density and motion parameters of the nano particles;
7) And (3) data post-processing:
and (3) describing a data graph of speed, density, temperature and slip length of the fluid reaching the stable flow rate through origin software for the data output in the step 6), and performing molecular visualization motion processing including a motion rule and final aggregation time of nanoparticles in the nano fluid through ovito software.
Specifically, in the step 1), the wall surface for limiting the fluid flow up and down is modeled to be circular, square and triangular to realize rough wall surfaces with different shapes, the required flow channel area is divided by adopting a block command, and the position of the copper nano-particle is determined according to the circle center and the radius.
Specifically, in the step 3), the influence of different hydrophilic (showing attraction to water molecules) and hydrophobic (not attracting to water molecules) wall surfaces on the fluid is simulated by changing the potential function.
Specifically, in the step 6), the magnitude of the applied force is changed according to the magnitude of the model.
The invention has the beneficial effects that: the curve trend of the temperature velocity density slip length of the nanoparticle fluid under the flow of the microscopic Poiseuille can be accurately researched, and the motion state and the aggregation time of the nanoparticles can be accurately researched.
Drawings
FIG. 1 is a flow chart of the experimental simulation;
FIG. 2 is a diagram of a base model proposed code;
FIG. 3 is a model diagram;
FIG. 4 is a graph of differential roughness;
FIG. 5 is a velocity map;
FIG. 6 is a density map;
FIG. 7 is a temperature diagram;
FIG. 8 is a speed slip map;
fig. 9 is a graph of nanoparticle motion and nanoparticle aggregation at different times.
Detailed Description
In order to better explain the technical scheme of the invention, the following detailed description is made in conjunction with the accompanying drawings.
Example 1: a method for predicting the fluid flow parameters and the motion state of water-copper nanoparticles is characterized in that: the method comprises the following steps:
1) Establishing a model: parameters required for model building were set in lammps (molecular dynamics software) software:
establishing walls of an upper flow passage and a lower flow passage of a model;
dividing a runner area;
positioning copper nanoparticles;
2) Defining atoms, namely the number of atoms corresponding to the flow channel region in the filling step 1):
filling atoms, and setting corresponding molar mass;
3) Force field balance, simulating real force in reality:
setting different force field parameters to realize hydrophilic (showing attraction to water molecules) and hydrophobic (not attracting to water molecules) wall surfaces;
4) Carrying out energy minimization:
system balance is achieved, and preparation is simulated;
5) Temperature relaxation is carried out to reach thermodynamic equilibrium:
setting the temperature to 300k to reach normal temperature;
6) Carrying out simulation:
setting the force; make the fluid flow to a stable flow rate
Setting a time step length;
layering the model, collecting data and outputting the data, wherein the collected data comprises temperature, speed, density and motion parameters of the nano particles;
7) And (3) describing a data graph of speed, density, temperature and slip length of the fluid reaching the stable flow rate through origin software for the data output in the step 6), and performing molecular visualization motion processing including a motion rule and final aggregation time of nanoparticles in the nano fluid through ovito software.
Further, in the step 1), the wall surface for limiting the fluid flow up and down is modeled to be circular, square and triangular to realize rough wall surfaces with different shapes, the required flow channel area is divided by adopting a block command, and the position of the copper nano-particle is determined according to the circle center and the radius.
Further, in the step 3), the influence of different hydrophilic (attractive to water molecules) and hydrophobic (unattractive to water molecules) wall surfaces on the fluid is simulated by changing the potential function.
Further, in the step 6), the magnitude of the applied force is changed according to the magnitude of the model.
The present invention will be described in detail with reference to specific data.
Using lammps modeling, first establishing a model box to determine the size of the model, where the model uses periodic conditions for infinite flow in x and y, and uses fixed boundary conditions for fixed boundary in z direction, and the instruction corresponds to ppf. And (4) carrying out partition wall surface building on copper atoms, filling the copper atoms, and achieving the purpose of building the wall surface. And filling water molecules into the two wall surfaces to realize the fluid condition. And adding nanoparticles to the fluid. And establishing a model required by calculation. The code of the model is shown in fig. 2.
Varying the shape of the flow channel achieves different degrees of roughness. The roughness model and the conventional fluid model are shown in fig. 3 and 4.
And carrying out velocity + nvt initial temperature setting on the model, and operating to reach normal temperature 300k to realize balance. The specific implementation code is as follows, velocitycurrent create 300.0 4922029rot yes distgaussians + fix all nve, velocitycurrent represents an initial temperature creation instruction, create represents a creation temperature, 300k represents a temperature, 4922029 represents a random number, and rotyesdistgaussians represents obedience gaussian distribution. fix represents the ensemble command, and all represents the invention model nve herein represents the ensemble command.
And applying force in the channel direction to water molecules in the flow channel to enable the fluid to reach a stable flow speed. The specific implementation code is as follows, fix addrform 0.0006.0.0, fix representing the apply force command, addrform representing the magnitude command to apply force, 0.006 representing the force in the x direction, and two 0.0 representing the force in the y and z directions as 0, respectively.
And (3) layering the fluid reaching a stable flow rate, and counting the speed, the density and the temperature distribution. And carrying out visualization processing on the nanoparticle fluid, and acquiring motion state data of the nanoparticles at different times.
And analyzing the data of speed, density, temperature distribution and speed slip by using a mapping software origin to begin to map and analyze the data. And obtaining the speed, density, temperature and speed slip distribution diagram. As shown in fig. 5, 6, 7, 8.
The kinetic pattern of the nanoparticles at different times and the final nanoparticle agglomeration was analyzed by using the molecular visualization software ovito, as shown in fig. 9.
While the present invention has been described in detail with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, and various changes can be made without departing from the spirit and scope of the present invention.
Claims (4)
1. A method for predicting the fluid flow parameters and the motion state of water-copper nanoparticles is characterized in that: the method comprises the following steps:
1) Establishing a model: parameters required for model establishment are set in the molecular dynamics software lammps:
establishing walls of an upper flow passage and a lower flow passage of a model;
dividing a runner area;
positioning copper nanoparticles;
2) Defining atoms, namely the number of atoms corresponding to the flow channel region in the filling step 1):
filling atoms, and setting corresponding molar mass;
3) Balancing a force field, and simulating real force in reality:
setting different force field parameters to realize hydrophilic and hydrophobic wall surfaces;
4) Performing energy minimization:
system balance is achieved, and simulation preparation is carried out;
5) Temperature relaxation is carried out to reach thermodynamic equilibrium:
setting the temperature to 300k to reach normal temperature;
6) Carrying out simulation:
setting the force to make the fluid flow to a stable flow rate;
setting a time step length;
layering the model, collecting data and outputting the data, wherein the collected data comprises temperature, speed, density and motion parameters of the nano particles;
7) And (3) data post-processing:
and (3) describing a data graph of speed, density, temperature and slip length of the fluid reaching the stable flow rate through origin software for the data output in the step 6), and performing molecular visualization motion processing including different time motion states and agglomeration time of the nanoparticles in the nano fluid through ovito software.
2. The method for predicting the fluid flow parameters and nanoparticle motion states of the water copper nanoparticles as claimed in claim 1, wherein: in the step 1), the wall surface for limiting the fluid flow up and down is modeled to be round, square and triangular to realize rough wall surfaces with different shapes, a required flow channel area is divided by adopting a blocking command, and the position of the copper nano-particle is determined according to the circle center and the radius.
3. The method of predicting the fluid flow parameters and nanoparticle motion states of copper nanoparticles as claimed in claim 1, wherein: in the step 3), the influence of different hydrophilic and hydrophobic wall surfaces on the fluid is simulated by changing the potential function.
4. The method of predicting the fluid flow parameters and nanoparticle motion states of copper nanoparticles as claimed in claim 1, wherein: in the step 6), the magnitude of the applied force is changed according to the magnitude of the model.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117664507A (en) * | 2023-10-20 | 2024-03-08 | 浙江大学 | Visual density driving convection supergravity test simulation device and method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117664507A (en) * | 2023-10-20 | 2024-03-08 | 浙江大学 | Visual density driving convection supergravity test simulation device and method |
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