Interface layer high temperature strength prediction method based on molecular dynamics and mesoscopic morphology

Abstract

The application discloses a high-temperature strength prediction method of an interface layer based on molecular dynamics and micro morphology, in which, when a geometric model of the interface layer is established, not only the morphology of the interface layer is considered, but also the oxidation behavior of the interface layer is considered, so that the real conditions of the interface layer are more fitted, and in the subsequent simulation process of the interface layer model, a stretching in a direction orthogonal to uniaxial stretching is added, the stress-strain curve of biaxial stretching is obtained through biaxial stretching simulation, so that the tensile strength of biaxial stretching is obtained, and through combined analysis of the tensile strength of uniaxial stretching and the tensile strength of biaxial stretching, the mechanical properties of the interface layer can be more truly reflected, so that more accurate material performance parameters can be provided for high-temperature service performance prediction of a thermal protection structure of a spacecraft.

Description

Technical Field

[0001] This invention relates to the field of aerospace technology, and in particular to a method for predicting the high-temperature strength of an interface layer based on molecular dynamics and microstructure. Background Technology

[0002] The pyrogenic carbon (PyC) interfacial layer is the intermediate phase between the fibers and the matrix of the composite material, such as... Figure 1 As shown, its microstructure exhibits a wavy, lamellar morphology, which can improve the fracture toughness and oxidation resistance of SiC fiber-reinforced SiC matrix composites (SiCf / SiC). Its mechanical properties have a significant impact on the overall performance of SiCf / SiC composites. Accurately and effectively predicting the mechanical properties of the PyC interface layer can provide the most fundamental material performance parameters for predicting the high-temperature service performance of aerospace vehicle thermal protection structures.

[0003] The main methods for predicting the mechanical properties of PyC interface layers are as follows: a) Methods based on microscopic mechanical models, which establish corresponding mechanical models, such as elastic models, plasticity models, and damage models, based on the microstructure and composition of the PyC interface layer. Mechanical parameters of the PyC interface layer, such as elastic modulus, yield strength, fracture strength, and fracture toughness, are calculated through numerical simulation or analytical solutions; b) Methods based on macroscopic mechanical models, which establish mechanical models, such as elastic models, plasticity models, and damage models, based on the macroscopic behavior of the PyC interface layer. Mechanical parameters of the interface layer are calculated through experimental measurement or inversion solutions; c) Methods based on molecular dynamics simulations, which establish corresponding molecular dynamics models, such as ReaxFF potential and Tersoff potential, based on the molecular structure and interactions of the PyC interface layer. Molecular dynamics simulation software is used to simulate the molecular motion and deformation of the PyC interface layer and calculate its mechanical parameters.

[0004] Methods based on microscopic mechanical models require a large amount of microscopic parameters and experimental data as input, resulting in complex calculations and often severely distorted results. Methods based on macroscopic mechanical models assume that the macroscopic behavior of the PyC interface layer conforms to an ideal model, neglecting the microscopic characteristics and nonlinear effects of the PyC interface layer. Methods based on molecular dynamics simulations can reveal the mechanical mechanisms of the PyC interface layer at the molecular level, considering effects such as chemical reactions and phase transitions. However, they require the selection of appropriate molecular dynamic potentials and simulation conditions, and their computational accuracy and efficiency are limited by the limitations of molecular dynamics simulations.

[0005] Existing molecular dynamics simulation methods do not consider the morphology and oxidation behavior of the PyC interface layer during modeling, and only perform uniaxial tensile performance calculations. These factors affect the accuracy of the predicted mechanical properties of the PyC interface layer. Therefore, how to more realistically reflect the mechanical properties of the PyC interface layer is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0006] In view of this, embodiments of the present invention provide a method for predicting the high-temperature strength of the interface layer based on molecular dynamics and microstructure, so as to more realistically reflect the mechanical properties of the PyC interface layer.

[0007] Therefore, embodiments of the present invention provide a method for predicting the high-temperature intensity of an interface layer based on molecular dynamics and microstructure, comprising the following steps:

[0008] S1: Simulate the shape of the interface layer in the modeling software, perform geometric modeling of the interface layer, and obtain the interface layer model.

[0009] S2: Create an oxygen molecule box in the modeling software, copy the oxygen molecules to the vacuum area of ​​the interface layer model, and export the interface layer model containing oxygen molecules as a data file that can be read by LAMMPS.

[0010] S3: Set general parameters in .in files based on lammps;

[0011] S4: Configure parameters for the oxidation file in the .in file based on lammps;

[0012] S5: Configure parameters for files used for uniaxial stretching in .in files based on lammps;

[0013] S6: Add a stretching direction orthogonal to the uniaxial stretching based on the uniaxial stretching, and set parameters for the file used for biaxial stretching in the .in file based on lammps;

[0014] S7: Perform oxidation simulation on the exported data file, and then perform uniaxial tensile simulation and biaxial tensile simulation based on the oxidation simulation.

[0015] S8: Import the output files of the oxidation simulation, uniaxial tensile simulation and biaxial tensile simulation into the visualization software to view the simulation process of oxidation, uniaxial tensile and biaxial tensile.

[0016] S9: Based on the output file of the uniaxial tensile simulation, plot the stress-strain curve of the uniaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the uniaxial tensile test. Based on the output file of the biaxial tensile simulation, plot the stress-strain curve of the biaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the biaxial tensile test.

[0017] In one possible implementation, in the above-mentioned method for predicting the high-temperature intensity of the interface layer based on molecular dynamics and microstructure provided in the embodiments of the present invention, step S1, simulating the interface layer morphology in modeling software, performing geometric modeling of the interface layer, and obtaining the interface layer model, specifically includes the following steps:

[0018] S11: Graphite unit cells are constructed using modeling software;

[0019] S12: Expand graphite unit cells into graphite, and randomly drill nanopores on each carbon fiber layer of graphite.

[0020] S13: By relaxing the graphite with nanopores using a universal force field and a ReaxFF force field, a PyC interface layer model is obtained.

[0021] In one possible implementation, in the above-mentioned method for predicting the high-temperature strength of the interface layer based on molecular dynamics and microstructure provided in the embodiments of the present invention, step S1, simulating the interface layer morphology in modeling software, performing geometric modeling of the interface layer, and obtaining the interface layer model, further includes the following steps:

[0022] S14: Import SiC unit cells and C unit cells into the modeling software, expand the SiC unit cells into SiC, expand the C unit cells into C fibers, cut the SiC, PyC interface layer models and C fibers in the same direction, and splice them together in the direction of the cut to form the SiC@PyC@C interface layer model.

[0023] In one possible implementation, in the above-mentioned method for predicting the high-temperature intensity of the interface layer based on molecular dynamics and microstructure provided in the embodiments of the present invention, step S3, setting the general parameters in the .in file based on LAMMPS, specifically includes the following steps:

[0024] S31: Sets the units for all physical quantities in the interface layer model;

[0025] S32: Defines the type of particles in the interface layer model;

[0026] S33: Set the boundary conditions for the interface layer model;

[0027] S34: Defines the type of force field for inter-particle interactions;

[0028] S35: Set neighbor list parameters;

[0029] S36: Set the time step for the simulation;

[0030] S37: Define the ensemble;

[0031] S38: Set the temperature during the simulation process.

[0032] In one possible implementation, in the above-described method for predicting the high-temperature intensity of the interface layer based on molecular dynamics and microstructure provided in this embodiment of the invention, step S4, setting parameters for the oxidation file in the .in file based on lammps, specifically includes the following steps:

[0033] S41: Set oxidation duration;

[0034] S42: Set the output of oxidation data, including information about the atoms; where the atom information includes atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy, and the forces acting on the atom.

[0035] In one possible implementation, in the high-temperature strength prediction method for interface layers based on molecular dynamics and microstructure provided in the embodiments of the present invention, step S5, setting parameters for the file used for uniaxial stretching in the .in file based on LAMMPS, specifically includes the following steps:

[0036] S51: Set the strain rate;

[0037] S52: Set the stretching direction;

[0038] S53: Set the output of the stretching data, including the information of the output atoms and the strain and stress of the output model; where the information of the atoms includes the atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy and atom force.

[0039] In one possible implementation, in the high-temperature strength prediction method for interface layers based on molecular dynamics and microstructure provided in the embodiments of the present invention, step S6, which involves setting parameters for the file used for biaxial stretching in the .in file based on LAMMPS, specifically includes the following steps:

[0040] S61: Set the strain rate to be the same as that of uniaxial tension;

[0041] S62: Set the stretching direction, including two directions: the same as the stretching direction of uniaxial stretching and orthogonal to it;

[0042] S63: Set the output of the stretching data, including the information of the output atoms and the strain and stress of the output model; where the information of the atoms includes the atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy and atom force.

[0043] The high-temperature strength prediction method for interface layers based on molecular dynamics and microstructure provided in this invention considers not only the morphology of the interface layer but also its oxidation behavior when geometrically modeling it, thus better reflecting the actual conditions of the interface layer. Furthermore, in the subsequent simulation of the interface layer model, a stretching direction orthogonal to the uniaxial stretching is added. Through biaxial stretching simulation, the stress-strain curve of biaxial stretching is obtained, thereby obtaining the tensile strength of biaxial stretching. By combining the analysis of the tensile strength of uniaxial stretching and biaxial stretching, the mechanical properties of the interface layer can be more realistically reflected, thus providing more accurate material performance parameters for predicting the high-temperature service performance of aerospace vehicle thermal protection structures. Attached Figure Description

[0044] Figure 1 This is a detailed topographic image of the PyC interface layer.

[0045] Figure 2 A schematic flowchart of the high-temperature strength prediction method for interface layers based on molecular dynamics and microstructure provided by this invention.

[0046] Figure 3 This is a schematic diagram of a graphite unit cell in Embodiment 1 of the present invention;

[0047] Figure 4 This is a schematic diagram of the modeling process of the PyC interface layer model in Embodiment 1 of the present invention;

[0048] Figure 5 This is a schematic diagram of the PyC interface layer model containing oxygen molecules in Embodiment 1 of the present invention;

[0049] Figure 6 This is a data file diagram of the PyC interface layer model in Embodiment 1 of the present invention;

[0050] Figure 7 This is a diagram of the oxidation command in the file executed in Embodiment 1 of the present invention;

[0051] Figure 8 This is a file diagram of the uniaxial stretching command executed in Embodiment 1 of the present invention;

[0052] Figure 9 This is a file diagram of the biaxial stretching command executed in Embodiment 1 of the present invention;

[0053] Figure 10 a is a schematic diagram of the PyC interface layer model after oxidation of 0fs in Embodiment 1 of the present invention;

[0054] Figure 10 b is a schematic diagram of the PyC interface layer model after oxidation for 10000 fs in Embodiment 1 of the present invention;

[0055] Figure 10 c is a schematic diagram of the PyC interface layer model after oxidation for 40000 fs in Embodiment 1 of the present invention;

[0056] Figure 10 d is a schematic diagram of the PyC interface layer model after oxidation for 50,000 fs in Embodiment 1 of the present invention;

[0057] Figure 10 e is a schematic diagram of the PyC interface layer model after oxidation for 75000 fs in Embodiment 1 of the present invention;

[0058] Figure 10 f is a schematic diagram of the PyC interface layer model after oxidation for 100,000 fs in Embodiment 1 of the present invention;

[0059] Figure 11 a is a schematic diagram of the PyC interface layer model when the uniaxial tensile strain is 0% in Embodiment 1 of the present invention;

[0060] Figure 11 b is a schematic diagram of the PyC interface layer model with a uniaxial tensile strain of 5% in Embodiment 1 of the present invention;

[0061] Figure 11 c is a schematic diagram of the PyC interface layer model with a uniaxial tensile strain of 10% in Embodiment 1 of the present invention;

[0062] Figure 11 d is a schematic diagram of the PyC interface layer model with a uniaxial tensile strain of 25% in Embodiment 1 of the present invention;

[0063] Figure 11 e is a schematic diagram of the PyC interface layer model with a uniaxial tensile strain of 50% in Embodiment 1 of the present invention;

[0064] Figure 12 a is a schematic diagram of the PyC interface layer model when the biaxial tensile strain is 0% in Embodiment 1 of the present invention;

[0065] Figure 12 b is a schematic diagram of the PyC interface layer model with a biaxial tensile strain of 5% in Embodiment 1 of the present invention;

[0066] Figure 12 c is a schematic diagram of the PyC interface layer model with a biaxial tensile strain of 10% in Embodiment 1 of the present invention;

[0067] Figure 12 d is a schematic diagram of the PyC interface layer model with a biaxial tensile strain of 25% in Embodiment 1 of the present invention;

[0068] Figure 12e is a schematic diagram of the PyC interface layer model with a biaxial tensile strain of 50% in Embodiment 1 of the present invention;

[0069] Figure 13 This is a stress-strain curve diagram of the PyC interface layer model simulating the uniaxial tensile process in Embodiment 1 of the present invention;

[0070] Figure 14 This is a stress-strain curve diagram of the PyC interface layer model simulating the biaxial tensile process in Embodiment 1 of the present invention;

[0071] Figure 15 This is a schematic diagram of the modeling process of the SiC@PyC@C interface layer model in Embodiment 2 of the present invention;

[0072] Figure 16 This is a schematic diagram of the SiC@PyC@C interface layer model containing oxygen molecules in Embodiment 2 of the present invention;

[0073] Figure 17 This is a data file diagram of the SiC@PyC@C interface layer model in Embodiment 2 of the present invention;

[0074] Figure 18 This is a diagram of the oxidation command in the file executed in Embodiment 2 of the present invention;

[0075] Figure 19 This is a file diagram of the uniaxial stretching command executed in Embodiment 2 of the present invention;

[0076] Figure 20 This is a file diagram of the biaxial stretching command executed in Embodiment 2 of the present invention;

[0077] Figure 21 a is a schematic diagram of the SiC@PyC@C interface layer model after oxidation at 0fs in Embodiment 2 of the present invention;

[0078] Figure 21 b is a schematic diagram of the SiC@PyC@C interface layer model after oxidation for 10000 fs in Embodiment 2 of the present invention;

[0079] Figure 21 c is a schematic diagram of the SiC@PyC@C interface layer model after oxidation for 40000 fs in Example 2 of the present invention;

[0080] Figure 21 d is a schematic diagram of the SiC@PyC@C interface layer model after oxidation for 50,000 fs in Example 2 of this invention;

[0081] Figure 21 e is a schematic diagram of the SiC@PyC@C interface layer model after oxidation for 75000 fs in Embodiment 2 of the present invention;

[0082] Figure 21 f is a schematic diagram of the SiC@PyC@C interface layer model after oxidation for 100,000 fs in Embodiment 2 of the present invention;

[0083] Figure 22 a is a schematic diagram of the SiC@PyC@C interface layer model in Embodiment 2 of the present invention when the uniaxial tensile strain is 0%;

[0084] Figure 22 b is a schematic diagram of the SiC@PyC@C interface layer model with a uniaxial tensile strain of 5% in Embodiment 2 of the present invention;

[0085] Figure 22 c is a schematic diagram of the SiC@PyC@C interface layer model with a uniaxial tensile strain of 10% in Embodiment 2 of the present invention.

[0086] Figure 22 d is a schematic diagram of the SiC@PyC@C interface layer model in Embodiment 2 of the present invention when the uniaxial tensile strain is 20%;

[0087] Figure 22 e is a schematic diagram of the SiC@PyC@C interface layer model with a uniaxial tensile strain of 25% in Embodiment 2 of the present invention;

[0088] Figure 22 f is a schematic diagram of the SiC@PyC@C interface layer model with a uniaxial tensile strain of 50% in Embodiment 2 of the present invention;

[0089] Figure 23 a is a schematic diagram of the SiC@PyC@C interface layer model with a biaxial tensile strain of 0% in Embodiment 2 of the present invention;

[0090] Figure 23 b is a schematic diagram of the SiC@PyC@C interface layer model with a biaxial tensile strain of 5% in Embodiment 2 of the present invention;

[0091] Figure 23 c is a schematic diagram of the SiC@PyC@C interface layer model with a biaxial tensile strain of 10% in Embodiment 2 of the present invention;

[0092] Figure 23 d is a schematic diagram of the SiC@PyC@C interface layer model with a biaxial tensile strain of 20% in Embodiment 2 of the present invention;

[0093] Figure 23 e is a schematic diagram of the SiC@PyC@C interface layer model with a biaxial tensile strain of 25% in Embodiment 2 of the present invention;

[0094] Figure 23 f is a schematic diagram of the SiC@PyC@C interface layer model with a biaxial tensile strain of 50% in Embodiment 2 of the present invention;

[0095] Figure 24 This is a stress-strain curve diagram of the SiC@PyC@C interface layer model simulating the uniaxial tensile process in Embodiment 2 of the present invention;

[0096] Figure 25 This is a stress-strain curve diagram of the SiC@PyC@C interface layer model simulating the biaxial tensile process in Embodiment 2 of the present invention. Detailed Implementation

[0097] The following detailed description, in conjunction with the accompanying drawings, provides a specific implementation of the high-temperature strength prediction method for interface layers based on molecular dynamics and microstructure provided by this invention.

[0098] This invention provides a method for predicting the high-temperature strength of an interface layer based on molecular dynamics and microstructure, such as... Figure 2 As shown, it may include the following steps:

[0099] S1: Simulate the shape of the interface layer in the modeling software, perform geometric modeling of the interface layer, and obtain the interface layer model.

[0100] Specifically, the modeling software can be Materials Studio, or other modeling software, which is not limited here. The micromorphology of the interface layer is wavy and layered. When performing geometric modeling of the interface layer, considering the real morphology of the interface layer can better match the real conditions of the interface layer. In this way, the predicted results of the mechanical properties of the interface layer will be more realistic.

[0101] S2: Create an oxygen molecule box in the modeling software, copy the oxygen molecules to the vacuum area of ​​the interface layer model, and export the interface layer model containing oxygen molecules as a data file that can be read by LAMMPS.

[0102] Because the oxidation behavior of the interface layer is considered when performing geometric modeling of the interface layer, it can better match the real conditions of the interface layer. As a result, the predicted results of the mechanical properties of the interface layer will be more realistic.

[0103] S3: Set general parameters in .in files based on lammps;

[0104] Specifically, the general parameters include the units of physical quantities in the interface layer model, the particle types in the interface layer model, the boundary conditions of the interface layer model, the type of force field for inter-particle interaction, the neighbor list parameters, the simulation time step, the ensemble, and the temperature during the simulation process.

[0105] S4: Configure parameters for the oxidation file in the .in file based on lammps;

[0106] Specifically, the parameters used for oxidation include oxidation time and the output of oxidation data. The output of oxidation data includes information about the atoms; among which, the information about the atoms includes atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy, and the forces acting on the atom.

[0107] S5: Configure parameters for files used for uniaxial stretching in .in files based on lammps;

[0108] Specifically, the parameters used for uniaxial tension include strain rate, tension direction, and the output of tension data. The output of tension data includes information about the atoms and the strain and stress of the output model. Among them, the information about the atoms includes atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy, and atom force.

[0109] S6: Add a stretching direction orthogonal to the uniaxial stretching based on the uniaxial stretching, and set parameters for the file used for biaxial stretching in the .in file based on lammps;

[0110] Specifically, the parameters used for biaxial tension are the same as those used for uniaxial tension;

[0111] S7: Perform oxidation simulation on the exported data file, and then perform uniaxial tensile simulation and biaxial tensile simulation based on the oxidation simulation.

[0112] S8: Import the output files of the oxidation simulation, uniaxial tensile simulation and biaxial tensile simulation into the visualization software to view the simulation process of oxidation, uniaxial tensile and biaxial tensile.

[0113] S9: Based on the output file of the uniaxial tensile simulation, plot the stress-strain curve of the uniaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the uniaxial tensile test. Based on the output file of the biaxial tensile simulation, plot the stress-strain curve of the biaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the biaxial tensile test.

[0114] The high-temperature strength prediction method for interface layers based on molecular dynamics and microstructure provided by this invention considers not only the morphology of the interface layer but also its oxidation behavior when geometrically modeling it, thus better reflecting the actual conditions of the interface layer. Furthermore, in the subsequent simulation of the interface layer model, a stretching direction orthogonal to the uniaxial stretching is added. Through biaxial stretching simulation, the stress-strain curve of biaxial stretching is obtained, thereby obtaining the tensile strength of biaxial stretching. By combining the analysis of the tensile strength of uniaxial stretching and biaxial stretching, the mechanical properties of the interface layer can be more realistically reflected, thus providing more accurate material performance parameters for predicting the high-temperature service performance of aerospace vehicle thermal protection structures.

[0115] It should be noted that the high-temperature intensity prediction method for interface layers based on molecular dynamics and microstructure provided by this invention is applicable to both PyC interface layers and SiC@PyC@C interface layers. The following two specific embodiments illustrate in detail the application of the high-temperature intensity prediction method for interface layers based on molecular dynamics and microstructure to PyC and SiC@PyC@C interface layers, respectively.

[0116] Example 1: The high-temperature strength prediction method of the interface layer based on molecular dynamics and micromorphology provided by the present invention is applied to the PyC interface layer.

[0117] The first step is to simulate the shape of the PyC interface layer in the modeling software Materials Studio, and to perform geometric modeling of the PyC interface layer to obtain the PyC interface layer model. This can specifically include the following steps:

[0118] (1) Graphite unit cells were created using the modeling software Materials Studio, such as... Figure 3 As shown;

[0119] (2) Expand the graphite unit cell into graphite and randomly drill nanopores on each carbon fiber layer of graphite.

[0120] (3) The graphite with nanopores was relaxed using a universal force field and a ReaxFF force field to obtain a PyC interface layer model. The modeling process is as follows: Figure 4 As shown.

[0121] The second step is to create a model in the Material Studio software with an average oxygen molecule density of 8 / The oxygen molecule box copies oxygen molecules to the vacuum area of ​​the PyC interface layer model, such as... Figure 5 As shown; export the PyC interface layer model containing oxygen molecules into a data file that can be read by LAMMPS, such as... Figure 6 As shown.

[0122] The third step is to set the general parameters in the .in file based on LAMMPS as follows:

[0123] (1) Set the unit of all physical quantities in the PyC interface layer model to real;

[0124] (2) Define the particle type as charge in the PyC interface layer model;

[0125] (3) Set the boundary conditions of the PyC interface layer model to periodic boundary conditions;

[0126] (4) Define the type of the force field of inter-particle interaction as the ReaxFF potential;

[0127] (5) Set the neighbor list parameter to 2.0;

[0128] (6) Set the simulation time step to 1fs;

[0129] (7) Define the ensemble as NVT;

[0130] (8) Set the temperature during the simulation process to 800K.

[0131] Step four, as Figure 7 As shown, the following parameter settings are applied to the file used for oxidation in the .in file based on LAMMPS:

[0132] (1) Set the oxidation time to 100 ps, ​​which means simulating 100,000 time steps;

[0133] (2) Set the output of oxidation data: Define an output command named 4 to output information about atoms, such as atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy and atom force. The output file name is dump.ss.*, and the output frequency is every 200 time steps.

[0134] Fifth step, as Figure 8 As shown, the following parameter settings are applied to the file used for uniaxial stretching in the .in file based on LAMMPS:

[0135] (1) Set the strain rate, stretching at each time step. Length;

[0136] (2) Set the stretching direction to be along the x-axis;

[0137] (3) Set the output of the stretching data: Define an output command named 4 to output atomic information, such as atomic number, atomic type, atomic coordinates, atomic charge, atomic potential energy, atomic kinetic energy and atomic force. The output file name is dump.ss.*, and the output frequency is every 200 time steps. Define a modifier named def1 to be applied to the PyC interface layer model to output the strain and stress of the PyC interface layer model. The output content is the values ​​of variables p1, p2, p3 and p4, namely strain, stress in the x direction, stress in the y direction and stress in the z direction. The output file name is SC_0001_ss.def1.txt, and the output frequency is 1 time / fs. Perform molecular dynamics simulation on the PyC interface layer model for 1000 time steps, i.e. 1 ps.

[0138] Step 6, as follows Figure 9 As shown, the following parameter settings are applied to the file used for biaxial stretching in the .in file based on LAMMPS:

[0139] (1) Set the strain rate to be the same as that of uniaxial tension, that is, tension per time step. Length;

[0140] (2) Set the stretching direction, including two directions: the same as the stretching direction of uniaxial stretching and orthogonal to it, that is, along the x-axis and z-axis;

[0141] (3) Set the output of the stretching data: Define an output command named 4 to output atomic information, such as atomic number, atomic type, atomic coordinates, atomic charge, atomic potential energy, atomic kinetic energy and atomic force. The output file name is dump.ss.*, and the output frequency is every 200 time steps. Define a modifier named def1 to be applied to the PyC interface layer model to output the strain and stress of the PyC interface layer model. The output content is the values ​​of variables p1, p2, p3 and p4, namely strain, stress in the x direction, stress in the y direction and stress in the z direction. The output file name is SC_0001_ss.def1.txt, and the output frequency is 1 time / fs. Perform molecular dynamics simulation on the PyC interface layer model for 1000 time steps, i.e. 1 ps.

[0142] Step 7: Simulation.

[0143] (1) Perform oxidation simulation on the exported data file;

[0144] (2) Based on the oxidation simulation, perform uniaxial tensile simulation;

[0145] (3) Based on the oxidation simulation, biaxial tensile simulation is performed.

[0146] Step 8: Post-processing and analysis of results.

[0147] (1) Import the output files from the oxidation simulation, uniaxial tensile simulation, and biaxial tensile simulation into OVITO software to view the oxidation simulation process (e.g., Figure 10 As shown), the simulation process of uniaxial tension (e.g.) Figure 11 (as shown) and the simulation process of biaxial stretching (as shown) Figure 12 (as shown); where, Figure 10 a~ Figure 10 f represents the PyC interface layer model after oxidation of 0fs, 10000fs, 40000fs, 50000fs, 75000fs, and 100000fs, respectively. Figure 11 a~ Figure 11 e represents the PyC interface layer model when the uniaxial tensile strain is 0%, 5%, 10%, 25%, and 50%, respectively; Figure 12 a~ Figure 12 e represents the PyC interface layer model when the biaxial tensile strain is 0%, 5%, 10%, 25%, and 50%, respectively;

[0148] (2) Based on the output file of the uniaxial tensile simulation, plot the stress-strain curve of the uniaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the uniaxial tensile test. Figure 13 As shown, the highest point of the curve is (17.5, 0.12165), corresponding to a strain of 17.5%, a stress of 121.65 kPa, and a tensile strength of 121.65 kPa. Based on the output file of the biaxial tensile simulation, the stress-strain curve for biaxial tension is plotted. The stress value corresponding to the highest point of the curve is the tensile strength of the biaxial tension. Figure 14 As shown, the highest point of the curve is (18.3, 0.10349), corresponding to a strain of 18.3%, a stress of 103.49 kPa, and a tensile strength of 103.49 kPa.

[0149] Example 2: The high-temperature strength prediction method of the interface layer based on molecular dynamics and micromorphology provided by the present invention is applied to the SiC@PyC@C interface layer.

[0150] The first step is to establish the SiC@PyC@C interface layer model:

[0151] (1) Graphite unit cells were constructed using the modeling software Materials Studio;

[0152] (2) Expand the graphite unit cell into graphite and randomly drill nanopores on each carbon fiber layer of graphite.

[0153] (3) The graphite with nanopores was relaxed by using a general force field and a ReaxFF force field to obtain a PyC interface layer model.

[0154] (4) Import SiC unit cells and C unit cells into the modeling software Materials Studio. Expand the SiC unit cells to SiC with a size of 5*10*3 and expand the C unit cells to C fibers with a size of 10*10*2. Cut the SiC, PyC interface layer model and C fibers in the 001 direction and splice them in the 001 direction to form the SiC@PyC@C interface layer model.

[0155] The second step is to create a model in the Material Studio software with an average oxygen molecule density of 8 / The oxygen molecule box copies oxygen molecules to the vacuum area of ​​the PyC interface layer model, such as... Figure 15 and Figure 16 As shown; the SiC@PyC@C interface layer model containing oxygen molecules is exported as a data file that can be read by LAMMPS, such as... Figure 17 As shown.

[0156] The third step is to set the general parameters in the .in file based on LAMMPS as follows:

[0157] (1) Set the unit of all physical quantities in the SiC@PyC@C interface layer model to real;

[0158] (2) Define the particle type as charge in the SiC@PyC@C interface layer model;

[0159] (3) Set the boundary conditions of the SiC@PyC@C interface layer model to periodic boundary conditions;

[0160] (4) Define the type of the force field of inter-particle interaction as the ReaxFF potential;

[0161] (5) Set the neighbor list parameter to 2.0;

[0162] (6) Set the simulation time step to 1fs;

[0163] (7) Define the ensemble as NVT;

[0164] (8) Set the temperature during the simulation process to 2000k.

[0165] Step four, as Figure 18 As shown, the following parameter settings are applied to the file used for oxidation in the .in file based on LAMMPS:

[0166] (1) Set the oxidation time to 100 ps, ​​which means simulating 100,000 time steps;

[0167] (2) Set the output of oxidation data: Define an output command named 4 to output information about atoms, such as atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy and atom force. The output file name is dump.ss.*, and the output frequency is every 200 time steps.

[0168] Fifth step, as Figure 19 As shown, the following parameter settings are applied to the file used for uniaxial stretching in the .in file based on LAMMPS:

[0169] (1) Set the strain rate, stretching at each time step. Length;

[0170] (2) Set the stretching direction to be along the x-axis;

[0171] (3) Set the output of the stretching data: Define an output command named 4 to output atomic information, such as atomic number, atomic type, atomic coordinates, atomic charge, atomic potential energy, atomic kinetic energy and atomic force. The output file name is dump.ss.*, and the output frequency is every 200 time steps. Define a modifier named def1 to be applied to the PyC interface layer model to output the strain and stress of the PyC interface layer model. The output content is the values ​​of variables p1, p2, p3 and p4, namely strain, stress in the x direction, stress in the y direction and stress in the z direction. The output file name is SC_0001_ss.def1.txt, and the output frequency is 1 time / fs. Perform molecular dynamics simulation on the PyC interface layer model for 1000 time steps, i.e. 1 ps.

[0172] Step 6, as follows Figure 20 As shown, the following parameter settings are applied to the file used for biaxial stretching in the .in file based on LAMMPS:

[0173] (1) Set the strain rate to be the same as that of uniaxial tension, that is, tension per time step. Length;

[0174] (2) Set the stretching direction, including two directions: the same as the stretching direction of uniaxial stretching and orthogonal to it, that is, along the x-axis and z-axis;

[0175] (3) Set the output of the stretching data: Define an output command named 4 to output atomic information, such as atomic number, atomic type, atomic coordinates, atomic charge, atomic potential energy, atomic kinetic energy and atomic force. The output file name is dump.ss.*, and the output frequency is every 200 time steps. Define a modifier named def1 to be applied to the PyC interface layer model to output the strain and stress of the PyC interface layer model. The output content is the values ​​of variables p1, p2, p3 and p4, namely strain, stress in the x direction, stress in the y direction and stress in the z direction. The output file name is SC_0001_ss.def1.txt, and the output frequency is 1 time / fs. Perform molecular dynamics simulation on the PyC interface layer model for 1000 time steps, i.e. 1 ps.

[0176] Step 7: Simulation.

[0177] (1) Perform oxidation simulation on the exported data file;

[0178] (2) Based on the oxidation simulation, perform uniaxial tensile simulation;

[0179] (3) Based on the oxidation simulation, biaxial tensile simulation is performed.

[0180] Step 8: Post-processing and analysis of results.

[0181] (1) Import the output files from the oxidation simulation, uniaxial tensile simulation, and biaxial tensile simulation into OVITO software to view the oxidation simulation process (e.g., Figure 21 As shown), the simulation process of uniaxial tension (e.g.) Figure 22 (as shown) and the simulation process of biaxial stretching (as shown) Figure 23 (as shown);

[0182] (2) Based on the output file of the uniaxial tensile simulation, plot the stress-strain curve of the uniaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the uniaxial tensile test. Figure 24 As shown, the highest point of the curve is (23, 0.1472), corresponding to a strain of 23%, a stress of 147.2 kPa, and a tensile strength of 147.2 kPa. Based on the output file of the biaxial tensile simulation, the stress-strain curve for biaxial tension is plotted. The stress value corresponding to the highest point of the curve is the tensile strength of the biaxial tension. Figure 25 As shown, the highest point of the curve is (24.2, 0.13554), corresponding to a strain of 24.2%, a stress of 135.54 kPa, and a tensile strength of 135.54 kPa.

[0183] In summary, as can be seen from Examples 1 and 2, the tensile strength obtained by biaxial stretching is lower than that obtained by uniaxial stretching in both the PyC interface layer model and the SiC@PyC@C interface layer model. This is because biaxial stretching takes into account stress and strain in other directions, and can more realistically reflect the mechanical properties of the interface layer.

[0184] This invention provides a method for predicting the high-temperature strength of an interface layer based on molecular dynamics and microstructure. When geometrically modeling the interface layer, it considers not only the morphology but also the oxidation behavior, thus better reflecting the actual conditions of the interface layer. Furthermore, during the subsequent simulation of the interface layer model, a biaxial tensile stress orthogonal to the uniaxial tensile stress is added. Through biaxial tensile simulation, the stress-strain curve of the biaxial tensile stress is obtained, thereby yielding the biaxial tensile strength. By combining the analysis of the uniaxial and biaxial tensile strengths, the mechanical properties of the interface layer can be more realistically reflected, thus providing more accurate material performance parameters for predicting the high-temperature service performance of aerospace vehicle thermal protection structures.

[0185] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for predicting the high-temperature strength of an interface layer based on molecular dynamics and microstructure, characterized in that, Includes the following steps: S1: Simulate the shape of the interface layer in the modeling software, perform geometric modeling of the interface layer, and obtain the interface layer model. S2: Create an oxygen molecule box in the modeling software, copy the oxygen molecules to the vacuum area of ​​the interface layer model, and export the interface layer model containing oxygen molecules as a data file that can be read by LAMMPS. S3: Set general parameters in .in files based on lammps; S4: Configure parameters for the oxidation file in the .in file based on lammps; S5: Configure parameters for files used for uniaxial stretching in .in files based on lammps; S6: Add a stretching direction orthogonal to the uniaxial stretching based on the uniaxial stretching, and set parameters for the file used for biaxial stretching in the .in file based on lammps; S7: Perform oxidation simulation on the exported data file, and then perform uniaxial tensile simulation and biaxial tensile simulation based on the oxidation simulation. S8: Import the output files of the oxidation simulation, uniaxial tensile simulation and biaxial tensile simulation into the visualization software to view the simulation process of oxidation, uniaxial tensile and biaxial tensile. S9: Based on the output file of the uniaxial tensile simulation, plot the stress-strain curve of the uniaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the uniaxial tensile test. Based on the output file of the biaxial tensile simulation, plot the stress-strain curve of the biaxial tensile test. The stress value corresponding to the highest point of the curve is the tensile strength of the biaxial tensile test. Step S1: Simulate the morphology of the interface layer in the modeling software, perform geometric modeling of the interface layer, and obtain the interface layer model. This specifically includes the following steps: S11: Graphite unit cells are constructed using modeling software; S12: Expand graphite unit cells into graphite, and randomly drill nanopores on each carbon fiber layer of graphite. S13: By relaxing the graphite with nanopores using a universal force field and a ReaxFF force field, a PyC interface layer model is obtained. In step S6, the parameters for the biaxial stretching file in the .in file based on LAMMPS are set, specifically including the following steps: S61: Set the strain rate to be the same as that of uniaxial tension; S62: Set the stretching direction, including two directions: the same as the stretching direction of uniaxial stretching and orthogonal to it; S63: Set the output of the stretching data, including the information of the output atoms and the strain and stress of the output model; where the information of the atoms includes the atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy and atom force.

2. The method for predicting the high-temperature intensity of the interface layer based on molecular dynamics and microstructure as described in claim 1, characterized in that, Step S1, simulating the morphology of the interface layer in the modeling software, performing geometric modeling of the interface layer to obtain the interface layer model, also includes the following steps: S14: Import SiC unit cells and C unit cells into the modeling software, expand the SiC unit cells into SiC, expand the C unit cells into C fibers, cut the SiC, PyC interface layer models and C fibers in the same direction, and splice them together in the direction of the cut to form the SiC@PyC@C interface layer model.

3. The method for predicting the high-temperature intensity of the interface layer based on molecular dynamics and microstructure as described in any one of claims 1 to 2, characterized in that, Step S3 involves setting the general parameters in the .in file based on LAMMPS, specifically including the following steps: S31: Sets the units for all physical quantities in the interface layer model; S32: Defines the type of particles in the interface layer model; S33: Set the boundary conditions for the interface layer model; S34: Defines the type of force field for inter-particle interactions; S35: Set neighbor list parameters; S36: Set the time step for the simulation; S37: Define the ensemble; S38: Set the temperature during the simulation process.

4. The method for predicting the high-temperature strength of the interface layer based on molecular dynamics and microstructure as described in any one of claims 1 to 2, characterized in that, Step S4 involves setting parameters for the oxidation file in the .in file based on lammps, specifically including the following steps: S41: Set oxidation duration; S42: Set the output of oxidation data, including information about the atoms; where the atom information includes atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy, and the forces acting on the atom.

5. The method for predicting the high-temperature strength of the interface layer based on molecular dynamics and microstructure as described in any one of claims 1 to 2, characterized in that, Step S5 involves setting parameters for the uniaxial stretching file within the .in file based on LAMMPS, specifically including the following steps: S51: Set the strain rate; S52: Set the stretching direction; S53: Set the output of the stretching data, including the information of the output atoms and the strain and stress of the output model; where the information of the atoms includes the atom number, atom type, atom coordinates, atom charge, atom potential energy, atom kinetic energy and atom force.

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