75 results about "Atom model" patented technology

The invention provides a metal matrix composite microstructure strengthening simulation method and system, and relates to the technical field of composite mechanical property simulation, and the method comprises the following steps: establishing a polycrystalline aluminum matrix atomic model and a spherical silicon nitride particle strengthening phase atomic model unit; embedding the spherical silicon nitride particles into the polycrystalline aluminum matrix according to the target embedding position coordinates, and integrating to generate an atomic scale structure model; according to the method, an embedded atom potential function is adopted to describe interaction among atoms in a polycrystalline aluminum matrix, a Tersoft potential function is adopted to describe covalent bond interaction among atoms in spherical silicon nitride particles, and a Lennard-Jones potential function is adopted to describe interaction among heteroatoms at a Si3N4 / Al interface; based on the interaction potential between atoms, molecular dynamics simulation is adopted for conducting uniaxial stretching simulation on the atomic scale structure model, mechanical property parameters of the particle reinforced metal matrix composite are obtained through calculation, and a visualization method is combined for analyzing the microcosmic strengthening mechanism of the particle reinforced metal matrix composite.

The invention belongs to the technical field of high-performance cutter coatings, and relates to a cross-scale bionic gradient coating design method based on a multi-principal-element high-entropy system, which comprises the following steps: sequentially forming a high-entropy alloy plastic layer, a high-entropy alloy / high-entropy ceramic tough layer and a nanocrystalline high-entropy ceramic superhard layer on the surface of a cutter matrix, and constructing a gradient transition structure; the method comprises the following steps: matching a high-entropy alloy plastic layer with a tool matrix binding phase, optimizing a high-entropy alloy / high-entropy ceramic tough layer material, improving interface binding force, optimizing gradient transition design by adopting thermal-mechanical coupling calculation, constructing an atomic model, simulating and optimizing a microstructure based on molecular dynamics, and establishing a finite element model to simulate thermal cycle and mechanical load. The interface performance is optimized, a mathematical model is constructed through a BP neural network and a particle swarm optimization algorithm, and gradual transition design of the tool base body and the coating is achieved. The problems that the tool coating interface is high in brittleness, insufficient in adhesiveness, limited in thermal stability and the like are solved, and the bonding performance of the coating interface and the stability and durability of the coated tool are improved.

The invention provides a glass elasticity modulus prediction method and system based on molecular dynamics simulation, and belongs to the technical field of glass performance prediction.The glass elasticity modulus prediction method comprises the steps that glass materials of different systems are obtained and tested, and an elasticity modulus test database is constructed; constructing an atomic model containing different system glass material component atoms, and optimizing the model; performing molecular dynamics simulation calculation on the optimized atomic model to obtain structure information of glass materials of different systems; enabling the elasticity modulus test databases of the glass materials of different systems to correspond to the structural information, and constructing a component-structure-performance data set; the elastic modulus is used as a dependent variable, the structural information is used as an independent variable, a multiple regression model is constructed, a quantitative structure-activity relationship for predicting the modulus of the glass elastic model is established, and the elastic modulus of a glass material in actual experimental production is predicted through simulation of molecular dynamics on the structural information. According to the invention, accurate simulation of the glass system structure and accurate prediction of the elastic modulus are realized.

The invention discloses a 3C-SiC crack propagation and mechanical property prediction method, and belongs to the technical field of material science and computer simulation, and the method comprises the following steps: S1, constructing a polycrystalline 3C-SiC atomic model, S2, simulating the crack propagation behavior of the polycrystalline 3C-SiC atomic model, S3, analyzing the microstructure evolution of the polycrystalline 3C-SiC by using OVITO software, S4, constructing a fracture characteristic evaluation model, and S5, evaluating the fracture characteristics of the polycrystalline 3C-SiC. S5, a mechanical property prediction database based on molecular dynamics is constructed, and visual analysis and quantitative prediction of the crack propagation behavior of the 3C-SiC are achieved. The method is used for researching the crack propagation behavior of the polycrystalline 3C-SiC under different working conditions, and prediction of the fracture toughness and the failure mode of a material is achieved.

The invention relates to a molecular dynamics simulation method for constructing an amorphous model by precursor hydrolysis-pyrolysis, which utilizes the characteristic that main products in the precursor hydrolysis and pyrolysis process are respectively water, hydrogen and methane, selects reasonable criteria through a written Python script program, judges the bonding distance between atoms and identifies the generated products, and finally establishes a molecular dynamics model. And batch and circulating molecular dynamics simulation is realized, and the amorphous SiOC atomic model is obtained. According to the method, the combination of automation, batch and open source molecular dynamics calculation software LAMMPS is finally realized, the influence of human subjective factors is eliminated, the calculation efficiency is improved, the time cost of scientific researchers is saved, and careless mistakes caused by a large amount of operations are avoided. Besides, sol micromolecules can form a good network skeleton structure after being hydrolyzed and cured, the escape speed of gas products is slowed down, an amorphous SiOC model with higher free carbon content can be constructed, and the amorphous-nanocrystalline interface density of the material is improved.

The application belongs to the technical field of high-performance tool coating, and relates to a design method of a cross-scale biomimetic gradient coating based on a multi-principal-element high-entropy system, which sequentially forms a high-entropy alloy plastic layer, a high-entropy alloy / high-entropy ceramic strong and tough layer and a nanocrystalline high-entropy ceramic superhard layer on the surface of a tool base body, constructs a gradient transition structure, matches the high-entropy alloy plastic layer with a bonding phase of the tool base body, optimizes the high-entropy alloy / high-entropy ceramic strong and tough layer material, improves the interface bonding force, adopts thermal-mechanical coupling calculation to optimize the gradient transition design, constructs an atomic model and optimizes the microstructure based on molecular dynamics simulation, establishes a finite element model to simulate thermal cycles and mechanical loads, optimizes the interface performance, constructs a mathematical model by using a BP neural network and a particle swarm optimization algorithm, and realizes the gradual transition design of the tool base body and the coating. The application solves the problems of large brittleness, insufficient adhesion and limited thermal stability of the tool coating interface, and improves the interface bonding performance of the coating, the stability and durability of the coating tool.

A method for identifying compounds with threshold activity against a target macromolecule first generates multiple poses for each compound fragment in a plurality of compound fragments against an atomic model of the target macromolecule. This creates a collection of configurations, or a “pose set,” for the compound fragments. Each pose is associated with a subset of interaction features drawn from a broader set of such features. Each feature corresponds to a subregion of the target macromolecule's atomic model. Each pose is quantified by application to a physics model. This assigns a score to the interaction features associated with the poses. A binding hypothesis is formed for the macromolecule, using the collection of interaction features and their corresponding scores. From this hypothesis, derived compounds are identified. These derived compounds are tested for their activity against the macromolecule, leading to the identification of those that exhibit the desired threshold activity.

The invention relates to the technical field of metal powder metallurgy process simulation. The high-entropy alloy hot pressing sintering and nanoindentation coupled molecular dynamics simulation method comprises the steps that a three-dimensional multi-particle atomic model of a high-entropy alloy is built, and initial boundary conditions are set; adjusting an initial boundary condition to be a contractility boundary condition, setting process parameters of hot pressing sintering on the model, and executing molecular dynamics simulation of the hot pressing sintering process; performing molecular dynamics and Monte Carlo hybrid simulation on the sintered model; mechanical boundary conditions are set for the optimized atomic model, a virtual indenter is controlled to be pressed into the optimized atomic model, molecular dynamics simulation of a nanoindentation test is executed, and physical field response parameters are collected in the test process; and based on the physical field response parameters, macroscopic mechanical property indexes are extracted. According to the method, the mapping relation between the hot pressing sintering process parameters and the macroscopic mechanical property is established, and a basis is provided for optimization of the hot pressing sintering process of the high-entropy alloy powder.

To provide a method enabling creation of a polymer material model having a crosslinked structure close to reality.SOLUTION: A method for creating a polymer material model is provided. The creation method includes: a first step S1 of inputting, to a computer, a pre-crosslinking coarse grained molecular model in which a structural unit of a molecular chain before crosslinking is substituted with coarse grained particles; a second step S2 of analyzing the molecular chain after crosslinking; a third step S3 of inputting, to the computer, a chemical structure of the structural unit after crosslinking on the basis of a result of the analysis; a fourth step S4 of inputting, to the computer, a post-crosslinking structural unit model in which the chemical structure of the structural unit after crosslinking is modeled as an entire atomic model or a united atom model; a fifth step S5 of the computer calculating structural relaxation based on a molecular dynamics method for the pre-crosslinking coarse grained molecular model; and a sixth step S6 of the computer allocating a post-crosslinking structural unit model to the coarse grained particles of the pre-crosslinking coarse grained molecular model after the structural relaxation, to create a post-crosslinking molecular model in which the molecular chain after crosslinking is modeled as the entire atomic model or the united atom model.SELECTED DRAWING: Figure 3

This invention discloses a method for analyzing the wear of micro-milling tools, relating to the fields of wear mechanism research and molecular dynamics analysis in micro-milling. Specifically, it includes: constructing atomic models of the tool and workpiece, incorporating the geometric features of the cutting edge arc; setting up a simulation environment and dividing the workpiece atoms into boundary layers, isothermal layers, and Newtonian layers; assigning potential functions to the atoms and performing energy minimization and relaxation; constructing a dimensionless scale ratio loading condition based on the equivalent uncut thickness and the cutting edge arc radius; extracting the mechanothermal process quantities and quantitatively characterizing the wear state according to the number of detached atoms, the change in effective cutting edge radius, and interface mixing indices. The aim is to achieve atomic-level quantitative characterization of the wear process of micro-milling tools.

This invention provides an atomic-level electron tomography 3D reconstruction method. Its core is to match the simulated projection of an atomic model with experimental images through iterative optimization. The method first constructs a 3D space based on the sample contour and initializes the atomic model parameters. Then, it acquires experimental images from multiple angles and their imaging parameters. In each iteration, a simulated projection image is generated based on the current atomic model and imaging parameters, and the difference between it and the corresponding experimental image is calculated as the loss value. An optimization algorithm dynamically adjusts atomic parameters (position, size, etc.) and imaging parameters (such as focus distance and aberrations) to minimize the total loss. This process includes intelligent simplification steps, which can merge or delete atoms to optimize model complexity. Finally, using the converged high-precision atomic model, 3D reconstructed images with arbitrary viewpoints and depths can be generated. This method can achieve high-precision atomic-level 3D reconstruction without completely relying on 360-degree scan data, helping to reduce data acquisition costs.

The invention provides a material microstructure digital design method based on a non-local model. The material microstructure digital design method can be used for controlling the microstructure and performance of a material. The method comprises the following steps: establishing a fractional order Cahn-Hilliard equation model for describing diffusion and phase separation processes of components in a material; selecting non-local parameters to control the phase distribution characteristics of the material; the fractional order equation is solved through numerical values, and material component space distribution under different non-local parameter values is obtained; constructing a material atom model based on the obtained component distribution; and analyzing the performance of the constructed model in combination with molecular dynamics simulation. By regulating and controlling non-local parameters, materials with different microstructures can be obtained under the same component proportion, accurate control of the microstructures and collaborative optimization of multiple properties such as strength, toughness and conductivity are achieved, and the method is suitable for material design in the fields of electronic packaging, high-performance conductors, aerospace and the like.

The invention discloses a construction method of a gradient nanocrystalline metal atom model. The construction method comprises the following steps: S1, defining initial conditions and a function relationship; s2, discretizing a gradient function; s3, defining the space size of the model; s4, carrying out model space discretization; s5, defining the dispersion of the nodes; s6, setting node coordinates; s7, filling atoms; and S8, visualizing the gradient nanocrystalline structure and the grain boundary distribution characteristics. According to the method, the construction of two-dimensional and three-dimensional gradient nanocrystalline atomic models of any metal material is realized; particularly, the grain size follows the gradient arrangement of any function in the space direction, and technical support is provided for molecular dynamics simulation of the gradient nanocrystalline metal complex process.

The present disclosure discloses a molecular dynamics modeling method for alloy steel containing multiple alloying elements, which is not only used for modeling but also for further evaluation: first, an iron matrix model of a certain size and shape is established, and then a certain amount of iron atoms are replaced with a certain amount of atoms of a first type of alloying element by atomic replacement, and a certain amount of atoms of a second type of alloying element are added to the iron atom model by random insertion, and the atoms are evenly distributed to form an initial molecular dynamics model of the alloy steel; further, in order to avoid the randomly inserted atoms of the second type of alloying element from overlapping with other atoms or being too close to each other, resulting in excessive system stress and energy, the model is energy minimized, and then the model is simulated through melting, cooling and room temperature aging processes to fully eliminate gaps, structural cracks, etc. in the model and reduce stress within the model; finally, the model is verified and evaluated by means of nanoindentation simulation.

The present invention discloses a method for predicting the optimal dosage of additives in polyurethane materials, comprising the following steps: S1: construction of a multi-component all-atom model; S2: construction of a plasticizer / polymer chain mixing model; S3: construction of a polyurethane network and additive mixing system; S4: calculation of the intermolecular interactions between the components of the plasticizer system; S5: calculation of the mechanical properties of crosslinked systems with different curing parameters, calculating the effects of the amount of plasticizer on the system performance and the effects of curing parameters on the mechanical properties of the material respectively, and clarifying the action mechanisms of plasticizer and curing agent on the material properties respectively. By constructing models with different plasticization ratios, the present invention predicts the changes in intermolecular interactions and the diffusion ability of small molecules, and discovers the crowding effect therein. At the same time, with the increase of curing parameters, there is a maximum value in the material performance. The invention can be used to predict the optimal addition dosage of polyurethane to guide experiments.

The invention discloses a network battle-oriented model construction and assembly method, and belongs to the technical field of network battles, and the method comprises the steps: collecting network battle elements of the network battle; corresponding atomic models are established for battlefields, weapons, techniques and other components; classifying the atomic model according to a physical domain, an information domain, a weakness domain and a social domain, and determining a domain class corresponding to the atomic model; defining a corresponding model base class according to the atomic model; performing modeling simulation according to the atomic model and the model base class to form corresponding model generation requirement data; establishing a resource end according to the model generation requirement data, the model base class and the atomic model; establishing a user side for the user according to the potential demand of the network battle and the resource side; a user sets a basic model of a corresponding network battle service according to the user side; the normalization of model construction is ensured, the assembly and construction process of the composite model is greatly facilitated, and a reliable and efficient basic model is provided for the construction of a network battle basic environment.

The present application relates to a simulation method, apparatus and computer equipment based on atomic simulation use cases, wherein the simulation method based on atomic simulation use cases includes: determining multiple execution units corresponding to the simulation task to be executed, and the atomic model corresponding to each execution unit, the simulation task includes simulation requirements of different types and different scenarios; determining the undirected matrix information corresponding to each atomic model; based on the undirected matrix information, searching and processing each execution unit through a graph search algorithm to obtain the simulation use case corresponding to the simulation task; based on the simulation use case, calling the corresponding execution unit to execute the simulation task. Through the present application, the problem of low configurability of simulation use cases is solved, and the configurability of simulation use cases is improved, so that simulation use cases can be quickly configured and optimized under multiple simulation types and multiple scenarios.

The application provides a coarse-grained molecular dynamics simulation and analysis method for researching microstructure properties of electroplating liquid, the coarse-grained model is used instead of the full atomic model, the molecular details which have less influence on system properties are ignored, a few atomic groups are used as basic units of simulation for modeling and simulation, so that the time required for the evolution of the whole system is reduced, and the time scale of the system simulation is prolonged. The interaction between components is described by a classical physical potential. By fitting and adjusting the interaction force parameters between different components, the method of the application can well approximate and model different component electroplating liquid systems, and reproduce experimental phenomena on the microscale.

A method for identifying compounds with threshold activity against a target macromolecule first generates multiple poses for each compound fragment in a plurality of compound fragments against an atomic model of the target macromolecule. This creates a collection of configurations, or a "pose set," for the compound fragments. Each pose is associated with a subset of interaction features drawn from a broader set of such features. Each feature corresponds to a subregion of the target macromolecule's atomic model. Each pose is quantified by application to a physics model. This assigns a score to the interaction features associated with the poses. A binding hypothesis is formed for the macromolecule, using the collection of interaction features and their corresponding scores. From this hypothesis, derived compounds are identified. These derived compounds are tested for their activity against the macromolecule, leading to the identification of those that exhibit the desired threshold activity.

This invention discloses a method for generating typical underwater acoustic functional components based on an open architecture, belonging to the field of underwater acoustic system technology. The core of this method lies in pre-establishing an underwater acoustic functional model library containing standardized interface underwater acoustic functional atomic models, and a component configuration rule library containing configuration templates and constraints. When a component generation request is received, the system automatically selects, instantiates, and logically links multiple atomic models from the model library according to the rule library to form an initial functional component. Then, the component undergoes rigorous static verification and high-fidelity dynamic simulation verification combined with a physical model. After successful verification, the component is compiled and packaged into an executable functional component conforming to the open architecture standard. This invention solves the technical problems existing in traditional underwater acoustic system development, such as tight hardware-software coupling, poor reusability of functional components, long development and verification cycles, and insufficient deployment flexibility, through a standardized, modular, automated, and verification-driven integrated process.

The application discloses a method for simulating crystallinity and mechanical properties of polytetrafluoroethylene based on molecular dynamics, which comprises the following steps: constructing a full-atom model of amorphous polytetrafluoroethylene; performing sintering simulation on the full-atom model of amorphous polytetrafluoroethylene, and constructing a coarse-grained model of polytetrafluoroethylene according to bond order information obtained from the sintering simulation; performing cooling crystallization simulation on the coarse-grained model of polytetrafluoroethylene, and calculating the crystallinity of polytetrafluoroethylene according to particle coordinate information obtained from the cooling crystallization simulation; and performing uniaxial tensile simulation on the coarse-grained model of polytetrafluoroethylene after the cooling crystallization simulation, and evaluating the mechanical properties of polytetrafluoroethylene according to the result of the uniaxial tensile simulation. The method can simulate the crystallinity and mechanical properties of polytetrafluoroethylene with different molecular weights, and the simulation result is consistent with the actual result, so that the test time and cost can be saved, and the method can provide certain guidance for actual production.

The application relates to a long-period stacking-ordered magnesium-rare earth alloy prediction method and application thereof, and belongs to the technical field of metal materials. The prediction method comprises the following steps: liquid structure models of pure Mg, binary Mg-RE alloy, ternary Mg-RE-X (X is other alloy elements) alloy and single atom models of each alloy element are respectively constructed; through molecular dynamics simulation and first principle calculation, the volume, cohesive energy, chemical short program parameters and proportion of each local structure symmetry of the above models are obtained; according to the evolution trend of the volume and cohesive energy of the ternary Mg-RE-X alloy relative to the binary Mg-RE alloy, the consistency of the distribution state of the chemical short program characteristics and the proportion of each local structure symmetry evolved from the binary Mg-RE alloy and pure Mg, effective prediction of whether a long-period stacking-ordered phase can be formed in the Mg-RE-X alloy is realized. Through theoretical calculation, element design basis for development of the long-period stacking-ordered magnesium-rare earth alloy is provided, and the blindness of alloy design is reduced.

The invention provides a hydropower engineering simulation model construction method and device, equipment and a storage medium, and is applied to the field of engineering simulation, and the method comprises the steps: determining a plurality of preset hydropower engineering component types, and determining a hydropower engineering object corresponding to each hydropower engineering component type; for the hydropower engineering object in each hydropower engineering component type, constructing an individual model corresponding to each hydropower engineering object to obtain an individual model set corresponding to the hydropower engineering component type; obtaining description information corresponding to each hydropower engineering component type, and generating a first input set, a first output set, a component feature set and a processing function based on the description information; and on the basis of the individual model set, the first input set, the first output set, the component feature set and the processing function, constructing and storing an atomic model to obtain an atomic model database. According to the method, the flexibility of hydropower engineering simulation modeling can be improved.

The invention discloses a design method for cooperatively screening a high-dynamic-toughness refractory high-entropy alloy based on molecular simulation. The method comprises the following steps: 1, determining candidate elements and component spaces in the refractory high-entropy alloy; 2, constructing an initial atomic model; 3, determining a generalized fault energy curve; 4, calculating heat conductivity; 5, screening components and establishing performance criteria; and 6, experimental verification. According to the method, the dynamic toughness of the refractory high-entropy alloy is predicted and screened by taking two key parameters gamma usf--a dominant deformation mechanism and k--a dominant thermal softening behavior as quantitative indexes of collaborative screening and establishing a collaborative relationship of the key parameters gamma usf--the dominant deformation mechanism and the k-the dominant thermal softening behavior; two most core physical essence influencing the dynamic toughness of the BCC structure refractory high-entropy alloy are grasped, and the spanning from'empirical design 'to'physical mechanism driven design' is realized.

The invention provides a technical support product system contribution rate prediction method based on a BP neural network, and the method comprises the steps: obtaining a support task, serializing the current support task according to the execution process of the support task, and obtaining a support task sequence, the task atomic models required by all the process steps of the task sequence are retrieved from the task atomic model set in combination with the task atomic models required by all the process steps of the task sequence; matching a technical support product with corresponding technical capability information from a technical support product capability model library according to a technical specialty required by execution of the support task; and inputting the guarantee task, the task atomic model corresponding to the guarantee task, the attribute information of the technical support product, the service life information and the environment information into the trained technical support product system contribution rate prediction model, and outputting the contribution rate of the technical support product to the guarantee system. The artificial intelligence algorithm is introduced to predict the system contribution rate of a novel technology guarantee product, meanwhile, product life data is added, and the problem that adaptability is not high in a conventional prediction method is solved.

The invention discloses a molecular dynamics simulation method and system for a bearing steel material microscopic crack initiation in-situ tensile test, and belongs to the field of alloy multi-scale modeling. Comprising the following steps: acquiring qualitative and quantitative analysis results of elements in a test area; carrying out EBSD data post-processing on the basis of a crystal structure loaded with an area needing to be subjected to in-situ tensile testing, matrix crystallography information and crystal information containing a second phase to obtain a matrix crystal boundary diagram, a matrix single crystal grain diagram and a second phase diagram of the testing area, and converting the matrix crystal boundary diagram, the matrix single crystal grain diagram and the second phase diagram into a mask file; constructing a crystal boundary model, a single crystal grain model and a second phase model based on the mask file in combination with the mask, and combining; obtaining a matrix full-atom model doped with a second phase; removing atoms contained in the second phase according to the element atomic percentage obtained by EPMA, and calculating the number of solid solution doping atoms of each element lacked in the current model; carrying out solid solution doping on each element atom by using Lammpps software to finish in-situ stretching molecular dynamics modeling; and stretching molecular dynamics simulation is completed.

The present application relates to a method for RNA structure prediction based on multi-scale molecular dynamics simulation, and a model for representing one nucleotide by three particles is constructed, which includes the linkage relationship mode of each particle in the coarse-grained model, the fitting method of the parameters of each particle in the coarse-grained model, and the fitting method of the mapping relationship between the coarse-grained model and the all-atom model. The present application provides a method for RNA structure prediction based on all-atom and coarse-grained iterative simulation. The simulation efficiency of the model is higher than that of the all-atom model, and the simulation accuracy of the all-atom model is ensured to a certain extent.

The invention discloses a wettability-adjustable porous quartz atomic-scale model generation method based on CT scanning data, and relates to the technical field of petroleum engineering and molecular simulation, and the method comprises the following steps: obtaining template coordinates; generating a quartz substrate; carrying out atom screening and hollowing; performing surface atom cleaning and surface hydroxylation treatment on the initial atomic model; on the basis of a wettability field obtained through CT scanning, the functional group type of a hydroxylation area on the pore surface is automatically adjusted, and a target atom model is obtained; and exporting the atomic coordinates of the target atomic model as a standard atomic structure file. According to the method, an atomic-scale model with geometric fidelity, chemical stability and adjustable wettability can be automatically constructed from CT scanning data, so that the physical consistency and prediction precision of molecular simulation on real rock core wetting behaviors are improved, and a high-quality initial structure is provided for molecular dynamics simulation and oil and gas flow research.

The invention discloses a data processing method and device for behavior modeling. The method comprises the following steps: acquiring behavior modeling task information; the behavior modeling task information comprises a plurality of pieces of to-be-modeled behavior information; processing the behavior modeling task information and the basic atomic model information to obtain structured atomic model information; the structured atomic model information comprises atomic condition model information and / or atomic state model information; the atomic condition model information comprises a plurality of pieces of basic atomic condition model information; the atomic state model information comprises a plurality of pieces of basic atomic state model information; the basic atomic model information comprises a plurality of pieces of entity action behavior information; and performing model construction processing on the structured atomic model information and the behavior node task information to obtain target behavior model information.

The invention provides a method for calculating the influence of rubber compatibility on mechanical properties by using dissipative particle dynamics. The method comprises the following steps: constructing a full-atom model of a to-be-calculated rubber molecular structure unit and performing energy minimization calculation; calculating solubility parameters of each unit structure by using a molecular dynamics method; carrying out coarse graining on the unit structures and calculating conservative repulsive force parameters among different particles; constructing a dissipative particle model of a to-be-calculated rubber system, wherein particles are connected through spring keys; constructing an input file to execute dissipative particle dynamics calculation, and calculating the compatibility among different rubber components; and introducing an entanglement point structure into the dissipative particle model to calculate the mechanical property in the uniaxial tensile mode. The method provides an efficient and reliable molecular simulation method for researching the influence of the rubber compatibility on the mechanical property of a composite system, effectively saves the test cost, and is suitable for solving the technical problem that the mechanical property of a rubber material is poor due to uneven dispersion of rubber.