A fatigue life prediction method, device, equipment and medium for sintered nanosilver

Abstract

The present application relates to a fatigue life prediction method, device, equipment and medium for sintered nanosilver. The fatigue life prediction method includes: constructing a sintered nanosilver RVE structure based on a microscopic morphology image of the sintered nanosilver; obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure; calculating key parameters of a cyclic cohesion model based on the material performance parameters; constructing an envelope curve of the cyclic cohesion model based on the key parameters of the cyclic cohesion model, and defining a fatigue damage function, a monotonic damage function and a damage-slip function of the cyclic cohesion model; placing the cyclic cohesion model into finite element software, and simulating the fatigue life prediction results of the sintered nanosilver based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, and applying boundary conditions and cyclic loads, thereby improving the prediction accuracy.

Description

Technical Field

[0001] The present application relates to the field of electronic packaging technology, and in particular to a fatigue life prediction method, device, equipment and medium for sintered nanosilver. Background Art

[0002] Nanosilver solder paste is the preferred packaging material for high-power and high-heat chips due to its outstanding performance. Due to the particularity of the low-temperature sintering process, sintered nanosilver is a typical random porous structure, and its reliability and service life have always been the focus of attention.

[0003] When stress is applied, tiny cracks will initiate and expand inside the sintered nanosilver, including the breaking of microscopic metal bonds and internal dislocation slip movement. Under normal circumstances, this tiny damage to the internal structure is not easy to detect and is also irreversible. Some researchers have made a detailed discussion on the irreversibility of dislocation slip in the microstructure. Although microdamage has occurred, the material will still return to its original position approximately when the stress is unloaded, which is called the virtual connection phenomenon. When the stress is reloaded, the virtual connection will immediately detach, providing a potential expansion path for the crack. In addition, when pores appear in front of the damaged area, a larger range of sliding will occur. Based on the behavioral characteristics of the above-mentioned porous structure under cyclic stress, it is called the damage slip phenomenon of sintered nanosilver.

[0004] The traditional cyclic cohesion model, originally developed for composite material delamination and colloid degradation, is not fully applicable to the fatigue degradation life prediction of porous structures. When sintered nanosilver is subjected to cyclic loading conditions, the damaged area reduces the resistance to crack propagation. However, the traditional cyclic cohesion model, which unloads along the origin and continues from the origin, can no longer effectively describe the damage slip accumulation phenomenon within the sintered body. In addition, the damage initiation condition of the traditional cyclic cohesion model requires that the external load reaches the maximum traction force or the opening displacement exceeds the damage initiation displacement before damage calculation begins. This undoubtedly ignores the small damage under low stress and contradicts the irreversibility of cyclic damage. Therefore, it is necessary to develop a new fatigue life prediction model for sintered nanosilver, a typical random porous structure, to improve the prediction accuracy. Summary of the Invention

[0005] Based on this, it is necessary to provide a fatigue life prediction method, device, equipment and medium for sintered nanosilver to address the above technical problems.

[0006] In a first aspect, an embodiment of the present application provides a method for predicting fatigue life of sintered nanosilver, the method comprising:

[0007] constructing a sintered nanosilver RVE structure based on a microscopic morphology image of the sintered nanosilver; and obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure;

[0008] Calculating key parameters of a cyclic cohesion model based on the material performance parameters;

[0009] Based on the key parameters of the cyclic cohesion model, an envelope curve of the cyclic cohesion model is constructed, and a fatigue damage function, a monotonic damage function, and a damage-slip function of the cyclic cohesion model are defined;

[0010] The cyclic cohesion model is placed in finite element software, and based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, boundary conditions and cyclic loads are applied to simulate and obtain fatigue life prediction results of sintered nanosilver.

[0011] In one embodiment, the method of constructing a sintered nanosilver RVE structure based on the microscopic morphology image of the sintered nanosilver; and obtaining the material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure includes:

[0012] performing noise reduction and binarization processing on the microscopic morphology image of the sintered nanosilver to extract porosity and pore characteristics;

[0013] Based on the porosity and the pore characteristics, a 3D Gaussian random field is used to model the defect characteristics of the sintered nanosilver to obtain a 3D Gaussian field random pore structure;

[0014] Performing dimensionality reduction processing on the 3D Gaussian field random pore structure, cutting it according to a specified volume fraction, and reconstructing the cut two-dimensional image into a 3D binary structure to obtain a sintered nanosilver RVE structure;

[0015] Periodic boundary conditions are applied to the sintered nanosilver RVE structure to simulate the deformation and fracture of the sintered nanosilver and obtain material performance parameters of the sintered nanosilver.

[0016] In one embodiment, the method further comprises:

[0017] The defect characteristics of sintered nanosilver are modeled using 3D Gaussian random fields with different Gaussian kernels to obtain corresponding 3D Gaussian field random pore structures, and based on each of the 3D Gaussian field random pore structures, the corresponding sintered nanosilver RVE structures are obtained;

[0018] Each of the sintered nanosilver RVE structures is matched with a real nanosilver defect structure to determine the optimal sintered nanosilver RVE structure.

[0019] In one embodiment, the fatigue life prediction result of sintered nanosilver is simulated based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage-slip function, and applying boundary conditions and cyclic loads, including:

[0020] Determine the transfer variables of the cyclic cohesion model in the cyclic simulation in the finite element software, wherein the transfer variables include the stiffness value, the maximum critical stress, the fracture energy, the cumulative damage amount of the previous cycle simulation, the damage slip accumulation amount and the system state variable of the cyclic cohesion model,

[0021] Calculating the trial displacement at the current moment according to the simulation increment step of the finite element software;

[0022] Based on the trial displacement at the current moment, determining the current incremental step state, and updating the displacement based on the current incremental step state;

[0023] Calculating a current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, and updating a current cumulative damage amount;

[0024] updating the stress state of each cohesive unit in the cyclic cohesive force model, and determining whether each cohesive unit has failed based on the current accumulated damage;

[0025] When all the cohesive units fail, a fatigue life prediction result of the sintered nanosilver is obtained.

[0026] In one embodiment, the calculating the current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, and updating the current cumulative damage amount includes:

[0027] In each cyclic simulation, when the cyclic load is in the unloading and reloading stage, the damage slip displacement is calculated based on the damage slip function, and the current cumulative damage slip displacement is updated;

[0028] When the cyclic load is in a continuous loading stage, if the traction force does not exceed the envelope curve, calculating fatigue damage based on the fatigue damage function;

[0029] If the traction force exceeds the envelope curve, calculating monotonic damage based on the monotonic damage function;

[0030] When the cyclic load is in the unloading stage, the current accumulated damage is updated based on the fatigue damage and the monotonic damage.

[0031] In one embodiment, the damage-slip function is calculated as follows:

[0032]

[0033] Among them, δ s,i represents the damage slip generated in the i-th cycle, where δ s,0 Indicates that the initial damage slip value is 0, u cycMax,i Indicates the maximum displacement value during the i-th cycle loading, f cycMax,i represents the maximum traction force during the i-th cycle loading, f ne represents the negative phase point pointed to during unloading, and ne represents the cyclic cohesion model parameter.

[0034] In one embodiment, the calculation formula of the monotonic damage function is as follows:

[0035]

[0036] Among them, δ f represents the separation displacement, which is obtained based on the maximum traction force and the fracture energy. The maximum traction force and the fracture energy are key parameters of the cyclic cohesion model. δ0 represents the damage initiation displacement. represents the displacement increment, δ represents the displacement at the current moment, which is composed of the damage slip accumulation and the displacement increment accumulation;

[0037] The calculation formula of the fatigue damage function is as follows:

[0038]

[0039] Among them, D cycle represents the damage result during cyclic loading, represents the displacement increment, represents the damage scaling factor, f represents the traction at the current loading moment, k represents the stiffness, and D represents the monotonic damage D montic and fatigue damage D cycle Cumulative amount, δ represents the displacement at the current moment, which is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment, f max Indicates the maximum traction force, C f and a represent the cyclic cohesion model parameters.

[0040] In a second aspect, an embodiment of the present application further provides a fatigue life prediction device for sintered nanosilver, the device comprising:

[0041] A material parameter calculation module is used to construct a sintered nanosilver RVE structure based on a microscopic morphology image of the sintered nanosilver; and obtain material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure;

[0042] A model parameter calculation module, used to calculate key parameters of the cyclic cohesion model based on the material performance parameters;

[0043] A model construction module, configured to construct an envelope curve of the cyclic cohesion model based on key parameters of the cyclic cohesion model, and define a fatigue damage function, a monotonic damage function, and a damage-slip function of the cyclic cohesion model;

[0044] A simulation prediction module is used to place the cyclic cohesion model into the explicit solver of the finite element software, based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, and apply boundary conditions and cyclic loads to simulate and obtain the fatigue life prediction results of sintered nanosilver.

[0045] In a third aspect, an embodiment of the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the method as described in the first aspect above.

[0046] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the storage medium stores a computer program, wherein when the computer program is executed by a processor, the method described in the first aspect above is implemented.

[0047] The fatigue life prediction method, device, equipment and medium of sintered nanosilver are as follows: constructing a sintered nanosilver RVE structure based on a microscopic morphology image of sintered nanosilver; obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure; calculating key parameters of a cyclic cohesion model based on the material performance parameters; constructing an envelope curve of the cyclic cohesion model based on the key parameters of the cyclic cohesion model, and defining a fatigue damage function, a monotonic damage function and a damage-slip function of the cyclic cohesion model; placing the cyclic cohesion model into finite element software, and simulating the fatigue life prediction results of the sintered nanosilver based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, and applying boundary conditions and cyclic loads, taking into account the cumulative effect of damage slip inside the porous structure of the sintered nanosilver during cyclic loading, and simulating the synchronous fatigue degradation of the stiffness and strength of the sintered nanosilver material, thereby improving the fatigue life prediction accuracy of the sintered nanosilver.

[0048] The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0050] Figure 1 This is a hardware structure block diagram of a terminal device of a fatigue life prediction method for sintered nanosilver in one embodiment;

[0051] Figure 2 is a schematic flow chart of a fatigue life prediction method for sintered nanosilver in one embodiment;

[0052] Figure 3 FIG. 1 is a schematic diagram of the defect characteristic RVE structure of sintered nanosilver generated by different Gaussian cores in one embodiment;

[0053] Figure 4 is a schematic diagram comparing the sintered nanosilver RVE structure generated by different Gaussian cores and the real nanosilver defect structure in one embodiment;

[0054] Figure 5 is a schematic diagram comparing the sintered silver nanoparticle RVE structure generated by the optimal Gaussian core in one embodiment with the real silver nanoparticle defect structure;

[0055] Figure 6 FIG. 1 is a schematic diagram of an elastic-plastic response curve of sintered nanosilver in one embodiment;

[0056] Figure 7 is a schematic diagram of a calculation flow of a new cyclic cohesion model in a finite element software solver in one embodiment;

[0057] Figure 8 is a schematic diagram of a crack propagation simulation process of a sintered nano-silver workpiece in an embodiment;

[0058] Figure 9 is a schematic diagram of fatigue life prediction results of sintered nanosilver under cyclic load in an embodiment;

[0059] Figure 10 FIG1 is a schematic diagram of a traction force-displacement curve corresponding to the first cohesive unit in a sintered nanosilver model during cyclic loading in one embodiment;

[0060] Figure 11 is a schematic diagram of the damage accumulation amount and damage slip amount of the first cohesive unit in the sintered nanosilver model in an embodiment;

[0061] Figure 12 The figure is a structural block diagram of a fatigue life prediction device for sintered nanosilver in one embodiment. DETAILED DESCRIPTION

[0062] In order to make the purpose, technical solutions and advantages of this application more clear, the following describes and illustrates this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0063] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. For example, running on a terminal, Figure 1 FIG. 1 is a block diagram of the hardware structure of the terminal of the fatigue life prediction method of sintered nanosilver in this embodiment. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown) a processor 102 and a memory 104 for storing data, wherein the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA. The above terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0064] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the fatigue life prediction method for sintered nanosilver in this embodiment. The processor 102 executes the computer program stored in the memory 104 to perform various functional applications and data processing, thereby implementing the above-mentioned method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0065] The transmission device 106 is used to receive or send data via a network. The network may include a wireless network provided by the terminal's communications provider. In one embodiment, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0066] The present invention provides a method for predicting fatigue life of sintered nanosilver. Figure 1 The terminal in the example is used to illustrate. Figure 2 As shown, the method includes the following steps:

[0067] Step 201 : constructing a sintered nanosilver RVE structure based on a microscopic morphology image of the sintered nanosilver; and obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure.

[0068] Specifically, a microscopic morphology image of sintered nanosilver is obtained, and the defect characteristics of the sintered nanosilver are modeled using a 3D Gaussian random field to obtain the sintered nanosilver's 3D Gaussian field random pore structure. The sintered nanosilver RVE structure is further derived based on the 3D Gaussian field random pore structure. Combined with RVE homogenization technology, the material performance parameters of the sintered nanosilver can be obtained. The material performance parameters of the sintered nanosilver include maximum stress point and stiffness.

[0069] Step 202: Calculate key parameters of the cyclic cohesion model based on the material performance parameters. It is understood that the cyclic cohesion model in this application is different from the traditional cyclic cohesion model and can be called a new cyclic cohesion model.

[0070] Specifically, the key parameters of the cyclic cohesion model include the maximum traction force, which is calculated as follows:

[0071]

[0072] Where, It represents the maximum stress point, which refers to the stress when entering the rapid damage region after exceeding the maximum stress point of the stress-strain curve. d is the damage scalar, which is related to the critical pore volume ratio and has a value range of 0.26-0.3. represents the critical stress of sintered nanosilver porous materials, f max Represents the maximum traction force of a cohesive element in a cyclic cohesion model.

[0073] The key parameters of the cyclic cohesion model include cohesive energy, which is calculated as follows:

[0074]

[0075] Where, δ f represents the separation displacement, δ0 represents the loss starting displacement, and k represents the stiffness.

[0076] Step 203 : constructing an envelope curve of the cyclic cohesion model based on key parameters of the cyclic cohesion model, and defining a fatigue damage function, a monotonic damage function, and a damage-slip function of the cyclic cohesion model.

[0077] Specifically, based on the key parameters of the cyclic cohesion model obtained by calculation, the envelope curve of the cyclic cohesion model is constructed, in which the rising area of ​​the curve is the linear elastic stage and the falling area is the plastic separation stage. The corresponding calculation formula is:

[0078]

[0079] Where f represents the traction force, k represents the stiffness, and δ represents the displacement.

[0080]

[0081] Among them, δ f represents the separation displacement, f max It represents the maximum traction force of the cohesive unit in the cyclic cohesion model, and G represents the cohesive energy, also known as the energy release rate.

[0082] By defining damage-related characteristic parameters, the fatigue damage function, monotonic damage function and damage-slip function of the cyclic cohesion model are constructed, wherein the fatigue damage function is used to calculate fatigue damage, the monotonic damage function is used to calculate monotonic damage, and the damage-slip function is used to calculate damage-slip displacement, wherein the damage of the porous structure of sintered nanosilver is affected by the cumulative influence of the damage-slip displacement.

[0083] In step 204, the cyclic cohesion model is placed in finite element software, and based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage-slip function, boundary conditions and cyclic loads are applied to simulate and obtain fatigue life prediction results of sintered nanosilver.

[0084] Specifically, the cyclic cohesion model is written in a programming language and placed in the explicit solver of the finite element method. The corresponding boundary conditions and cyclic loads are applied. According to the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, the crack propagation process of sintered nanosilver and the fatigue life prediction results are simulated.

[0085] The above steps S201 to S204 propose a fatigue life prediction method suitable for sintered nanosilver complex porous structures. This method takes into account the cumulative effect of damage slip inside the sintered nanosilver porous structure during cyclic loading, and simulates the synchronous fatigue degradation of the stiffness and strength of the sintered nanosilver material, thereby improving the fatigue life prediction accuracy of the sintered nanosilver.

[0086] In one embodiment, constructing a sintered nanosilver RVE structure based on a microscopic morphology image of sintered nanosilver; and obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure include the following steps:

[0087] Step 301 : performing noise reduction and binarization processing on the microscopic morphology image of the sintered nanosilver to extract porosity and pore characteristics.

[0088] Step 302 : Based on the porosity and the pore characteristics, a 3D Gaussian random field is used to model the defect characteristics of the sintered nanosilver to obtain a 3D Gaussian field random pore structure.

[0089] Among them, the discrete point values ​​in the space matrix will be represented by independent Gaussian distribution N(0,1 2 ) is provided based on the pixel coordinates (x, y, z) and Gaussian filtering is performed.

[0090] Step 303 , performing dimensionality reduction processing on the 3D Gaussian field random pore structure, cutting it according to a specified volume fraction, and reconstructing the cut two-dimensional image into a 3D binary structure to obtain a sintered nanosilver RVE structure.

[0091] Step 304 : applying periodic boundary conditions to the sintered nanosilver RVE structure to simulate the deformation and fracture of the sintered nanosilver to obtain material performance parameters of the sintered nanosilver.

[0092] Furthermore, in step 302, different Gaussian kernels are used to model the defect characteristics of the sintered nanosilver to obtain different 3D Gaussian field random pore structures, which are further processed to obtain corresponding sintered nanosilver RVE structures. Then, each of the sintered nanosilver RVE structures is matched with the real nanosilver defect structure to determine the optimal sintered nanosilver RVE structure.

[0093] Specifically, based on the real microscopic morphology image of sintered nanosilver, the defect feature modeling was performed using 3D Gaussian random field to generate the sintered nanosilver RVE structure corresponding to different Gaussian cores. Figure 3 It is the sintered nanosilver defect characteristic RVE structure generated by different Gaussian cores, and then each of the sintered nanosilver RVE structures is matched with the real nanosilver defect structure. Figure 4 It is a comparison between the sintered nanosilver RVE structure generated by different Gaussian cores and the real nanosilver defect structure. By optimizing the width of the Gaussian core, the generated sintered nanosilver RVE structure is matched with the real nanosilver defect structure.

[0094] This application optimizes the width of the Gaussian kernel to match the generated sintered nanosilver RVE structure with the real nanosilver defect structure. The optimization goal is to minimize the minimum average percentage error of the normalized autocorrelation function between the real nanosilver defect structure and the generated sintered nanosilver RVE structure. Figure 5 It is a comparison between the sintered nanosilver RVE structure generated by optimal Gaussian nucleation and the real nanosilver defect structure.

[0095] This application uses the Image Autocorrelation Function (IAF) to evaluate the correlation between pixels at different positions in an image. Taking a two-dimensional image as an example, the expression of the IAF is:

[0096]

[0097] Where (x, y) is the coordinate of the pixel in the image, and (m, n) is the target pixel. Typically, the above formula can be quickly calculated using the convolution theorem of Fourier transform, and the simplified form is shown below:

[0098]

[0099] Where FT represents the Fourier transform of the image, FT -1 Stands for inverse Fourier transform of image.

[0100] The calculation formula for the minimum average percentage error is as follows:

[0101]

[0102] In the formula, R(r i ) is the rth defect structure in real nanosilver i Normalized autocorrelation function value corresponding to pixel distance, The rth i Normalized autocorrelation function value corresponding to pixel distance.

[0103] In step 304, the material parameters of the sintered nanosilver RVE structure in Table 1 are used, and a homogenization method is used to apply periodic boundary conditions to the sintered nanosilver RVE structure to simulate the deformation and fracture of the surrounding material, thereby obtaining the elastic-plastic response curve of the sintered nanosilver, as shown in FIG. Figure 6 As shown in Figure 2 . The material properties of sintered nanosilver are obtained based on the elastic-plastic response curve of sintered nanosilver. The specific implementation method is to apply periodic boundary conditions to the sintered nanosilver RVE structure in finite element software to simulate the deformation and fracture of the surrounding material, thereby obtaining the material properties of the sintered nanosilver. The solid silver structure within the RVE structure should adopt the complete material constitutive curve or a hardening equation containing a plastic stage.

[0104] Table 1 Material parameters of sintered nanosilver RVE structure

[0105]

[0106] like Figure 6As shown in Table 2, after obtaining the elastic-plastic constitutive curves of the sintered nanosilver in the normal and tangential directions, the calculation formula in step 202 can be used to obtain the cohesive unit parameters and key parameters of the cohesive force model in the new cyclic cohesive force model corresponding to the sintered nanosilver, as shown in Table 2.

[0107] Table 2 Parameters of the new cyclic cohesive force model corresponding to sintered nanosilver

[0108]

[0109] In one embodiment, the simulation to obtain the fatigue life prediction result of sintered nanosilver based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage-slip function, and applying boundary conditions and cyclic loads, includes the following steps:

[0110] Step 401: determining the transfer variables of the cyclic cohesion model in the cyclic simulation in the finite element software, wherein the transfer variables include the stiffness value, the maximum critical stress, the fracture energy, the cumulative damage amount of the previous cyclic simulation, the cumulative damage slip amount, and the system state variables of the cyclic cohesion model.

[0111] Step 402, calculating the trial displacement at the current moment according to the simulation increment step of the finite element software;

[0112] Step 403: determining the current incremental step state based on the trial displacement at the current moment, and updating the displacement based on the current incremental step state;

[0113] Determine whether the current incremental step state is in the continuous rise or reloading phase or unloading phase, and update the displacement based on this.

[0114] Step 404: Calculate the current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, and update the current cumulative damage amount;

[0115] Table 3 gives the characteristic parameters of the new cyclic cohesion when calculating fatigue damage. Based on this, the fatigue damage calculation formula, monotonic damage calculation formula, and damage slip calculation formula of the new cyclic cohesion model can be fully constructed.

[0116] Table 3 Damage-related characteristic parameters in the new cyclic cohesion model corresponding to sintered nanosilver

[0117]

[0118] Among them, the damage slip is defined as the intersection of the maximum stress loading point and the horizontal axis when it points to a non-zero negative phase within a cycle. The damage slip obtained using this method is a non-fixed value, and as the damage increases, the increment of the damage slip displacement also increases.

[0119] The calculation formula of the damage slip function is as follows:

[0120]

[0121] Among them, δ s,i represents the damage slip generated in the i-th cycle, where δ s,0 Indicates that the initial damage slip value is 0, u cycMax,i Indicates the maximum displacement value during the i-th cycle loading, f cycMax,i represents the maximum traction force during the i-th cycle loading, f ne represents the negative phase point pointed to during unloading, and ne represents the cyclic cohesion model parameter.

[0122] The calculation formula of the monotonic damage function is as follows:

[0123]

[0124] Among them, δ f represents the separation displacement, which is obtained based on the maximum traction force and the fracture energy. The maximum traction force and the fracture energy are key parameters of the cyclic cohesion model. δ0 represents the damage initiation displacement. represents the displacement increment, δ represents the displacement at the current moment, which is composed of the damage slip accumulation and the displacement increment accumulation;

[0125] In the process of calculating monotonic damage, the displacement at the current moment is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment. The cumulative effect of damage slip inside the porous structure of sintered nanosilver during cyclic loading is taken into account, thereby improving the accuracy of fatigue life prediction of sintered nanosilver.

[0126] The calculation formula of the fatigue damage function is as follows:

[0127]

[0128] Among them, D cycle represents the damage result during cyclic loading, represents the displacement increment, represents the damage scaling factor, f represents the traction at the current loading moment, k represents the stiffness, and D represents the monotonic damage D montic and fatigue damage D cycle Cumulative amount, δ represents the displacement at the current moment, which is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment, f max Indicates the maximum traction force, C f and a represent the cyclic cohesion model parameters.

[0129] In the process of calculating fatigue damage, the present application takes into account the cumulative effect of damage slip inside the porous structure of sintered nanosilver during cyclic loading, since the displacement at the current moment is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment, thereby improving the accuracy of fatigue life prediction of sintered nanosilver.

[0130] Step 405: update the stress state of each cohesive unit in the cyclic cohesive force model, and determine whether each cohesive unit has failed based on the current accumulated damage.

[0131] If invalid, the cohesive unit is deleted. Specifically, the following formula is used to determine whether the cohesive unit should be deleted.

[0132]

[0133] Among them, S element Represents the state of the cohesive unit. If the total damage of the cohesive unit exceeds 1 or the displacement value uNew of the current cohesive unit exceeds the separation displacement δ f When the cohesive unit is deleted, it will be marked as deleted state 0.0. In other cases, it will be marked as 1.0 to facilitate subsequent call analysis and software identification.

[0134] Step 406: When all the cohesive units fail, a fatigue life prediction result of the sintered nanosilver is obtained.

[0135] In one embodiment, the calculating the current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, and updating the current cumulative damage amount includes:

[0136] Step 501: in each cyclic simulation, when the cyclic load is in the unloading and reloading stage, the damage slip displacement is calculated based on the damage slip function, and the current cumulative damage slip displacement is updated;

[0137] Step 502 , when the cyclic load is in a continuous loading stage, if the traction force does not exceed the envelope curve, calculating fatigue damage based on the fatigue damage function;

[0138] Step 503 , if the traction force exceeds the envelope curve, calculating the monotonic damage based on the monotonic damage function;

[0139] Step 504: When the cyclic load is in the unloading stage, the current accumulated damage amount is updated based on the fatigue damage and the monotonic damage.

[0140] In this embodiment, Figure 7 The calculation process of the cyclic cohesion model of this application in the finite element explicit solver is given, which specifically includes the following steps:

[0141] Step 601: Determine transfer variables. Determine transfer variables in the cyclic simulation of the cyclic cohesion model in the finite element software. The transfer variables include the stiffness value, maximum critical stress, fracture energy, cumulative damage amount of the previous cyclic simulation, cumulative damage slip amount, and system state variables of the cyclic cohesion model.

[0142] Step 602: Calculate the trial displacement at the current moment. Calculate the trial displacement at the current moment according to the simulation increment of the finite element software.

[0143] Step 603: Determine the current incremental step state. Based on the current trial displacement, determine whether the current incremental step state is in the continuous rise, reload phase, or unload phase, and update the displacement accordingly.

[0144] Step 604: Calculate the cumulative damage amount. When the cyclic loading is in the unloading and reloading phase, the damage slip displacement is calculated based on the damage slip function, and the current cumulative damage slip displacement is updated. When the cyclic loading is in the continuous loading phase, determine whether the traction force exceeds the envelope curve. If the traction force does not exceed the envelope curve, calculate the fatigue damage based on the fatigue damage function. If the traction force exceeds the envelope curve, calculate the monotonic damage based on the monotonic damage function. When the cyclic loading ends in the unloading phase, sum the fatigue damage and the monotonic damage to obtain the current damage amount, and update the current cumulative damage amount.

[0145] Step 605: Update the state of each cohesive unit in the cyclic cohesion model according to the current accumulated damage amount.

[0146] This application takes a sintered nanosilver profile specimen as an example, and applies periodic horizontal loading conditions at both ends, with a maximum tensile displacement of 0.2 mm and a loading and unloading rate of 1.2 mm / min. The crack propagation simulation process of the sintered nanosilver profile specimen is as follows: Figure 8 The prediction results of fatigue life of sintered nanosilver are shown in Figure 9 shown. Figure 10 This is the traction-displacement curve corresponding to the first cohesive unit during cyclic loading. Figure 11 is the damage accumulation and damage slip of the first cohesive unit in the sintered nanosilver specimen model.

[0147] It should be noted that the steps shown in the above process or the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0148] In one embodiment, Figure 12As shown, a fatigue life prediction device for sintered nanosilver, the device comprising:

[0149] The material parameter calculation module 10 is used to construct a sintered nanosilver RVE structure based on the microscopic morphology image of the sintered nanosilver; and obtain the material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure;

[0150] A model parameter calculation module 20 is used to calculate key parameters of the cyclic cohesion model based on the material performance parameters;

[0151] A model construction module 30 is used to construct an envelope curve of the cyclic cohesion model based on key parameters of the cyclic cohesion model, and define a fatigue damage function, a monotonic damage function, and a damage-slip function of the cyclic cohesion model;

[0152] The simulation prediction module 40 is used to place the cyclic cohesion model into the explicit solver of the finite element software, based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, and apply boundary conditions and cyclic loads to simulate and obtain the fatigue life prediction results of sintered nanosilver.

[0153] In one embodiment, the material parameter calculation module 10 is further used to: perform denoising and binarization on the microscopic morphology image of the sintered nanosilver to extract porosity and pore characteristics; based on the porosity and the pore characteristics, use a 3D Gaussian random field to model the defect characteristics of the sintered nanosilver to obtain a 3D Gaussian field random pore structure; perform dimensionality reduction on the 3D Gaussian field random pore structure, and cut it according to a specified volume fraction, reconstruct the cut two-dimensional image into a 3D binary structure to obtain a sintered nanosilver RVE structure; apply periodic boundary conditions to the sintered nanosilver RVE structure to simulate the deformation and fracture of the sintered nanosilver to obtain the material performance parameters of the sintered nanosilver.

[0154] In one embodiment, the material parameter calculation module 10 is further used to: use 3D Gaussian random fields with different Gaussian kernels to model the defect characteristics of sintered nanosilver to obtain corresponding 3D Gaussian field random pore structures, and based on each of the 3D Gaussian field random pore structures, obtain each corresponding sintered nanosilver RVE structure; match each of the sintered nanosilver RVE structures with the real nanosilver defect structure to determine the optimal sintered nanosilver RVE structure.

[0155] In one embodiment, the model building module 30 is also used to determine the transfer variables of the cyclic cohesion model in the cyclic simulation in the finite element software, and the transfer variables include the stiffness value, maximum critical stress, fracture energy, cumulative damage of the previous cycle simulation, cumulative damage slip and system state variables of the cyclic cohesion model, and calculate the trial displacement at the current moment according to the simulation increment of the finite element software; judge the current incremental step state based on the trial displacement at the current moment, and update the displacement based on the current incremental step state; calculate the current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage slip function, and update the current cumulative damage amount; update the stress state of each cohesive unit in the cyclic cohesion model, and judge whether each cohesive unit fails according to the current cumulative damage amount; when all the cohesive units fail, obtain the fatigue life prediction result of the sintered nanosilver.

[0156] In one embodiment, the model building module 30 is further used to: in each cyclic simulation, when the cyclic load is in the unloading and reloading stage, calculate the damage slip displacement based on the damage slip function, and update the current cumulative damage slip displacement; when the cyclic load is in the continuous loading stage, if the traction force does not exceed the envelope curve, calculate the fatigue damage based on the fatigue damage function; if the traction force exceeds the envelope curve, calculate the monotonic damage based on the monotonic damage function; when the cyclic load ends in the unloading stage, update the current cumulative damage based on the fatigue damage and the monotonic damage.

[0157] In one embodiment, the damage-slip function is calculated as follows:

[0158]

[0159] Among them, δ s,i represents the damage slip generated in the i-th cycle, where δ s,0 Indicates that the initial damage slip value is 0, u cycMax,i Indicates the maximum displacement value during the i-th cycle loading, f cycMax,i represents the maximum traction force during the i-th cycle loading, f ne represents the negative phase point pointed to during unloading, and ne represents the cyclic cohesion model parameter.

[0160] In one embodiment, the calculation formula of the monotonic damage function is as follows:

[0161]

[0162] Among them, δ frepresents the separation displacement, which is obtained based on the maximum traction force and the fracture energy. The maximum traction force and the fracture energy are key parameters of the cyclic cohesion model. δ0 represents the damage initiation displacement. represents the displacement increment, δ represents the displacement at the current moment, which is composed of the damage slip accumulation and the displacement increment accumulation;

[0163] The calculation formula of the fatigue damage function is as follows:

[0164]

[0165] Among them, D cycle represents the damage result during cyclic loading, represents the displacement increment, represents the damage scaling factor, f represents the traction at the current loading moment, k represents the stiffness, and D represents the monotonic damage D montic and fatigue damage D cycle Cumulative amount, δ represents the displacement at the current moment, which is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment, f max Indicates the maximum traction force, C f and a represent the cyclic cohesion model parameters.

[0166] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0167] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal via wired or wireless communication, where the wireless communication can be achieved via Wi-Fi, a mobile cellular network, NFC (near field communication), or other technologies. When executed by the processor, the computer program implements a fatigue life prediction method for sintered nanosilver.

[0168] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any of the above-mentioned fatigue life prediction methods for sintered nanosilver are implemented.

[0169] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0170] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0171] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A fatigue life prediction method for sintered nanosilver, characterized in that: The method comprises: constructing a sintered nanosilver RVE structure based on a microscopic morphology image of the sintered nanosilver; and obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure; Calculating key parameters of a cyclic cohesion model based on the material performance parameters; Based on the key parameters of the cyclic cohesion model, an envelope curve of the cyclic cohesion model is constructed, and a fatigue damage function, a monotonic damage function, and a damage-slip function of the cyclic cohesion model are defined; The cyclic cohesion model is placed in finite element software, and based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, boundary conditions and cyclic loads are applied to simulate and obtain fatigue life prediction results of sintered nanosilver.

2. The method according to claim 1, characterized in that The method comprises constructing a sintered nanosilver RVE structure based on the microscopic morphology image of the sintered nanosilver; and obtaining material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure, including: performing noise reduction and binarization processing on the microscopic morphology image of the sintered nanosilver to extract porosity and pore characteristics; Based on the porosity and the pore characteristics, a 3D Gaussian random field is used to model the defect characteristics of the sintered nanosilver to obtain a 3D Gaussian field random pore structure; Performing dimensionality reduction processing on the 3D Gaussian field random pore structure, cutting it according to a specified volume fraction, and reconstructing the cut two-dimensional image into a 3D binary structure to obtain a sintered nanosilver RVE structure; Periodic boundary conditions are applied to the sintered nanosilver RVE structure to simulate the deformation and fracture of the sintered nanosilver and obtain material performance parameters of the sintered nanosilver.

3. The method according to claim 2, characterized in that The method further comprises: The defect characteristics of sintered nanosilver are modeled using 3D Gaussian random fields with different Gaussian kernels to obtain corresponding 3D Gaussian field random pore structures, and based on each of the 3D Gaussian field random pore structures, the corresponding sintered nanosilver RVE structures are obtained; Each of the sintered nanosilver RVE structures is matched with the actual sintered nanosilver defect structure to determine the optimal sintered nanosilver RVE structure.

4. The method according to claim 1, wherein The fatigue life prediction result of sintered nanosilver is simulated based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage-slip function, and boundary conditions and cyclic loads are applied, including: Determine the transfer variables of the cyclic cohesion model in the cyclic simulation in the finite element software, wherein the transfer variables include the stiffness value, the maximum critical stress, the fracture energy, the cumulative damage amount of the previous cycle simulation, the damage slip accumulation amount and the system state variable of the cyclic cohesion model, Calculating the trial displacement at the current moment according to the simulation increment step of the finite element software; Based on the trial displacement at the current moment, determining the current incremental step state, and updating the displacement based on the current incremental step state; Calculating a current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, and updating a current cumulative damage amount; updating the stress state of each cohesive unit in the cyclic cohesive force model, and determining whether each cohesive unit has failed based on the current accumulated damage; When all the cohesive units fail, a fatigue life prediction result of the sintered nanosilver is obtained.

5. The method according to claim 4, characterized in that The calculating the current damage amount based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, and updating the current cumulative damage amount includes: In each cyclic simulation, when the cyclic load is in the unloading and reloading stage, the damage slip displacement is calculated based on the damage slip function, and the current cumulative damage slip displacement is updated; When the cyclic load is in a continuous loading stage, if the traction force does not exceed the envelope curve, calculating fatigue damage based on the fatigue damage function; If the traction force exceeds the envelope curve, calculating monotonic damage based on the monotonic damage function; When the cyclic load is in the unloading stage, the current accumulated damage is updated based on the fatigue damage and the monotonic damage.

6. The method according to claim 5, characterized in that: The calculation formula of the damage slip function is as follows: ； Among them, δ s,i represents the damage slip generated in the i-th cycle, where δ s,0 Indicates that the initial damage slip value is 0, δ s,i-1 represents the damage slip generated in the i-1th cycle, u cycMax,i Indicates the maximum displacement value during the i-th cycle loading, f cycMax,i represents the maximum traction force during the i-th cycle loading, f ne represents the negative phase point pointed to during unloading, ne represents the cyclic cohesion model parameter, and f max Indicates maximum traction.

7. The method according to claim 6, characterized in that: The calculation formula of the monotonic damage function is as follows: ； Among them, δ f represents the separation displacement, which is obtained based on the maximum traction force and the fracture energy. The maximum traction force and the fracture energy are key parameters of the cyclic cohesion model. δ0 represents the damage initiation displacement. represents the displacement increment, δ s,i represents the damage slip generated in the i-th cycle, δ represents the displacement at the current moment, which is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment; The calculation formula of the fatigue damage function is as follows: ； Among them, D cycle represents the damage result during cyclic loading, represents the displacement increment, represents the damage scaling factor, f represents the traction at the current loading moment, k represents the stiffness, and D represents the monotonic damage D montic and fatigue damage D cycle Cumulative amount, δ represents the displacement at the current moment, which is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment, f max Indicates the maximum traction force, C f and a represent the cyclic cohesion model parameters.

8. A fatigue life prediction device for sintered nanosilver, characterized in that: The device comprises: A material parameter calculation module is used to construct a sintered nanosilver RVE structure based on a microscopic morphology image of the sintered nanosilver; and obtain material performance parameters of the sintered nanosilver based on the sintered nanosilver RVE structure; A model parameter calculation module, used to calculate key parameters of the cyclic cohesion model based on the material performance parameters; A model construction module, configured to construct an envelope curve of the cyclic cohesion model based on key parameters of the cyclic cohesion model, and define a fatigue damage function, a monotonic damage function, and a damage-slip function of the cyclic cohesion model; A simulation prediction module is used to place the cyclic cohesion model into the explicit solver of the finite element software, based on the envelope curve, the fatigue damage function, the monotonic damage function and the damage-slip function, and apply boundary conditions and cyclic loads to simulate and obtain the fatigue life prediction results of sintered nanosilver.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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