Fatigue life prediction method, device and equipment of sintered nano-silver and medium

Abstract

The invention relates to a fatigue life prediction method, device, equipment and medium for sintered nano-silver, and the fatigue life prediction method comprises the steps: constructing a sintered nano-silver RVE structure based on a microstructure image of the sintered nano-silver; based on the sintered nano-silver RVE structure, material performance parameters of the sintered nano-silver are obtained; calculating key parameters of a cyclic cohesion model based on the material performance parameters; based on the key parameters of the cyclic cohesion model, constructing an envelope curve 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; and the cyclic cohesion model is put into finite element software, boundary conditions and cyclic loads are applied on the basis of the envelope curve, the fatigue damage function, the monotonic damage function and the damage slip function, the fatigue life prediction result of the sintered nano-silver is obtained through simulation, and the prediction precision is improved.

Description

Technical Field

[0001] This application relates to the field of electronic packaging technology, and particularly to a method, device, equipment and medium for predicting the fatigue life of sintered nano-silver. Background Art

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

[0003] When stress is applied, micro-cracks will initiate and propagate inside the sintered nano-silver, including the fracture of microscopic metal bonds and the dislocation slip movement inside. Usually, this kind of minor damage to the internal structure is not easily detectable and is also irreversible. Some researchers have elaborated in detail on the irreversibility of dislocation slip in the microscopic structure. Although micro-damage has occurred, the material will still approximately return to its original position when the stress is unloaded, which is called the virtual connection phenomenon. When the stress is re-applied, the virtual connection part will immediately come apart, providing a potential propagation path for cracks. In addition, when pores appear in front of the damaged area, a larger range of sliding will occur. Based on the behavior characteristics of the above porous structure under cyclic stress, it is called the damage slip phenomenon of sintered nano-silver.

[0004] The traditional cyclic cohesive force model was initially developed for composite material delamination and colloid degradation, and is not fully applicable to the life prediction of the fatigue degradation of porous structures. When sintered nano-silver is under cyclic loading conditions, the damaged area reduces the hindrance to crack propagation, and the traditional cyclic cohesive force model that unloads along the origin and starts from the origin can no longer effectively describe the cumulative damage slip phenomenon inside the sintered body. In addition, the damage initiation condition of the traditional cyclic cohesive force model is that damage begins to be calculated when the external load reaches the maximum traction force or the opening displacement exceeds the damage initiation displacement, which undoubtedly ignores the minor damage under low stress and violates the irreversibility of cyclic damage. Therefore, it is necessary to provide a new fatigue life prediction model for this typical random porous structure of sintered nano-silver to improve the prediction accuracy. Summary of the Invention

[0005] Based on this, in view of the above technical problems, it is necessary to provide a method, device, equipment and medium for predicting the fatigue life of sintered nano-silver.

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

[0007] Based on the microscopic morphology image of sintered silver nanoparticles, construct the representative volume element (RVE) structure of sintered silver nanoparticles; based on the RVE structure of sintered silver nanoparticles, obtain the material property parameters of the sintered silver nanoparticles;

[0008] Based on the material property parameters, calculate the key parameters of the cyclic cohesive force model;

[0009] Based on the key parameters of the cyclic cohesive force model, construct the envelope curve of the cyclic cohesive force model, and define the fatigue damage function, monotonic damage function, and damage slip function of the cyclic cohesive force model;

[0010] Put the cyclic cohesive force model into the finite element software, and 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 result of sintered silver nanoparticles.

[0011] In one embodiment, the constructing the RVE structure of sintered silver nanoparticles based on the microscopic morphology image of sintered silver nanoparticles; and obtaining the material property parameters of the sintered silver nanoparticles based on the RVE structure of sintered silver nanoparticles includes:

[0012] Perform noise reduction and binarization processing on the microscopic morphology image of the sintered silver nanoparticles, and extract the porosity and pore characteristics;

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

[0014] Perform dimensionality reduction processing on the 3D Gaussian field random pore structure, and cut it according to a specified volume fraction, and reconstruct the cut two-dimensional image into a 3D binary structure to obtain the RVE structure of sintered silver nanoparticles;

[0015] Apply periodic boundary conditions to the RVE structure of the sintered silver nanoparticles, simulate the deformation and fracture of the sintered silver nanoparticles, and obtain the material property parameters of the sintered silver nanoparticles.

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

[0017] Use 3D Gaussian random fields with different Gaussian kernels to model the defect characteristics of sintered silver nanoparticles to obtain corresponding 3D Gaussian field random pore structures, and based on each 3D Gaussian field random pore structure, obtain each corresponding RVE structure of sintered silver nanoparticles;

[0018] Match each RVE structure of the sintered silver nanoparticles with the real silver nanoparticle defect structure to determine the optimal RVE structure of the sintered silver nanoparticles.

[0019] In one embodiment, based on the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, applying boundary conditions and cyclic loads, the simulated fatigue life prediction results of sintered nano-silver include:

[0020] Determine the transfer variables in the cyclic simulation of the cyclic cohesive force model in the finite element software. 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 cohesive force model.

[0021] Calculate 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, judge the state of the current increment step and update the displacement based on the state of the current increment step.

[0023] 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.

[0024] Update the stress state of each cohesive unit in the cyclic cohesive force model, and judge whether each cohesive unit fails according to the current cumulative damage amount.

[0025] When all the cohesive units fail, obtain the fatigue life prediction results of the sintered nano-silver.

[0026] In one embodiment, 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 stage of reloading after unloading, calculate the damage slip displacement based on the damage slip function, and update the current cumulative damage slip displacement.

[0028] 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.

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

[0030] When the cyclic load reaches the end of the unloading stage, update the current cumulative damage amount based on the fatigue damage and the monotonic damage.

[0031] In one embodiment, the calculation formula of the damage slip function is as follows:

[0032]

[0033] Among them, δ s,i represents the damage slip generated in the i-th cycle period. Among them, δ s,0 represents that the initial damage slip value is 0, and u cycMax,i represents the maximum displacement value during loading in the i-th cycle period, and f cycMax,i represents the maximum traction force during loading in the i-th cycle period, and f ne represents the negative phase point pointed to during unloading, and ne represents the cyclic cohesive force 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 the key parameters of the cyclic cohesive force model. δ0 represents the damage initiation displacement. represents the displacement increment, and 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;

[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 force at the current loading moment, k represents the stiffness, D represents the monotonic damage D montic and the 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, and f max represents the maximum traction force, and C f and a represent the cyclic cohesive force model parameters.

[0040] In a second aspect, the embodiments of the present application further provide a device for predicting the fatigue life of sintered nano-silver. The device includes:

[0041] A material parameter calculation module, configured to construct an RVE structure of sintered nano-silver based on the microscopic morphology image of the sintered nano-silver; and obtain the material property parameters of the sintered nano-silver based on the RVE structure of the sintered nano-silver;

[0042] A model parameter calculation module, configured to calculate key parameters of the cyclic cohesive force model based on the material property parameters;

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

[0044] A simulation prediction module, configured to place the cyclic cohesive force model into an explicit solver of finite element software, and 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 a fatigue life prediction result of sintered nano-silver.

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

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

[0047] The above-mentioned method, device, equipment, and medium for predicting the fatigue life of sintered nano-silver construct an RVE structure of sintered nano-silver based on the microscopic morphology image of sintered nano-silver; obtain the material property parameters of the sintered nano-silver based on the RVE structure of the sintered nano-silver; calculate the key parameters of the cyclic cohesive force model based on the material property parameters; construct an envelope curve of the cyclic cohesive force model based on the key parameters of the cyclic cohesive force model, and define a fatigue damage function, a monotonic damage function, and a damage slip function of the cyclic cohesive force model; place the cyclic cohesive force model into finite element software, and 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 a fatigue life prediction result of sintered nano-silver, taking into account the cumulative effect of damage slip inside the porous structure of sintered nano-silver during the cyclic loading process, and simulating the synchronous fatigue degradation of the stiffness and strength of the sintered nano-silver material, thereby improving the accuracy of predicting the fatigue life of sintered nano-silver.

[0048] 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 concise and understandable. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0050] Figure 1 is a hardware structure block diagram of a terminal device for a fatigue life prediction method of sintered nano-silver in an embodiment;

[0051] Figure 2 is a schematic flowchart of a fatigue life prediction method of sintered nano-silver in an embodiment;

[0052] Figure 3 is a schematic diagram of the RVE structure of sintered nano-silver defect features generated by different Gaussian kernels in an embodiment;

[0053] Figure 4 is a schematic diagram comparing the RVE structure of sintered nano-silver generated by different Gaussian kernels with the real nano-silver defect structure in an embodiment;

[0054] Figure 5 is a schematic diagram comparing the RVE structure of sintered nano-silver generated by the optimal Gaussian kernel with the real nano-silver defect structure in an embodiment;

[0055] Figure 6 is a schematic diagram of the elastoplastic response curve of sintered nano-silver in an embodiment;

[0056] Figure 7 is a schematic flowchart of the calculation process of the new cyclic cohesive force model in a finite element software solver in an embodiment;

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

[0058] Figure 9 is a schematic diagram of the fatigue life prediction result of sintered nano-silver under cyclic loading in an embodiment;

[0059] Figure 10 is a schematic diagram of the traction-displacement curve corresponding to the first cohesive unit in the sintered nano-silver model during the cyclic loading process in an 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 nano-silver model in an embodiment;

[0061] Figure 12 is a structure block diagram of a fatigue life prediction device for sintered nano-silver in an embodiment. Detailed implementation manners

[0062] In order to make the objectives, technical solutions and advantages of the present application more clear and understandable, the present application will be described and explained below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0063] The method embodiment provided in this embodiment can be executed on a terminal, a computer or a similar computing device. For example, it runs on a terminal. Figure 1 is the hardware structure block diagram of the terminal of the fatigue life prediction method of sintered nano-silver in this embodiment. As Figure 1 shown, the terminal may include one or more ( Figure 1 only one is shown in ) a processor 102 and a memory 104 for storing data. Among them, 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 further include a transmission device 106 for communication functions and an input / output device 108. Those of ordinary skill in the art can understand that Figure 1 the structure shown is only schematic and does not limit the structure of the above terminal. For example, the terminal may further include more or fewer components than Figure 1 shown in, or have a different configuration from Figure 1 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 of sintered nano-silver in this embodiment. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, implements the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely provided with respect to the processor 102, and these remote memories may be connected to the terminal through a network. Examples of the above networks include, but are not limited to, the Internet, enterprise intranets, local area networks, mobile communication networks and their combinations.

[0065] The transmission device 106 is used to receive or send data via a network. The above network includes a wireless network provided by the communication provider of the terminal. In one instance, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one instance, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0066] An embodiment of the present application provides a method for predicting the fatigue life of sintered nano - silver. Taking the application of this method to Figure 1 the terminal in Figure 2 as an example, as

[0067] shown, the method includes the following steps:

[0068] Specifically, obtain the microscopic morphology image of the sintered nano - silver, model the defect characteristics of the sintered nano - silver using a 3D Gaussian random field to obtain the 3D Gaussian field random pore structure of the sintered nano - silver, further obtain the RVE structure of the sintered nano - silver based on the 3D Gaussian field random pore structure, and the material property parameters of the sintered nano - silver can be obtained by combining the RVE homogenization technology. Among them, the material property parameters of the sintered nano - silver include the maximum stress point and stiffness, etc.

[0069] Step 202, calculate the key parameters of the cyclic cohesive force model based on the material property parameters. It can be understood that the cyclic cohesive force model in this application is different from the traditional cyclic cohesive force model and can be called a new cyclic cohesive force model.

[0070] Specifically, the key parameters of the cyclic cohesive force model include the maximum traction force, and the calculation formula is as follows:

[0071]

[0072] In the formula, represents the maximum stress point, which refers to the stress when entering the rapid damage area 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 its value range is 0.26 - 0.3. represents the critical stress of the sintered nano - silver porous material, and f max represents the maximum traction force of the cohesive unit in the cyclic cohesive force model.

[0073] The key parameters of the cyclic cohesive force model include the cohesive energy, and the calculation formula is as follows:

[0074]

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

[0076] Step 203, construct the envelope curve of the cyclic cohesive force model based on the key parameters of the cyclic cohesive force model, and define the fatigue damage function, monotonic damage function, and damage slip function of the cyclic cohesive force model.

[0077] Specifically, according to the key parameters of the cyclic cohesive force model obtained by calculation, an envelope curve of the cyclic cohesive force model is constructed, where the rising region of the curve is the linear elastic stage and the falling region is the plastic separation stage. The corresponding calculation formula is as follows:

[0078]

[0079] Among them, 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 represents the maximum traction force of the cohesive unit in the cyclic cohesive force model, and G represents the cohesive energy, also known as the energy release rate.

[0082] By defining damage-related characteristic parameters, a fatigue damage function, a monotonic damage function, and a damage slip function of the cyclic cohesive force model are constructed. Among them, 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 the damage slip displacement. Among them, the damage of the porous structure of sintered silver nanowires is affected by the accumulation of the damage slip displacement.

[0083] Step 204: Place the cyclic cohesive force model into finite element software, and 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 result of sintered silver nanowires.

[0084] Specifically, the cyclic cohesive force model is written using a programming language and placed into the explicit solver of the finite element. Apply the corresponding boundary conditions and cyclic loads, and according to the envelope curve, the fatigue damage function, the monotonic damage function, and the damage slip function, simulate and obtain the crack propagation process and the fatigue life prediction result of sintered silver nanowires.

[0085] The above steps S201 to S204 propose a fatigue life prediction method applicable to the complex porous structure of sintered silver nanowires. This method considers the cumulative effect of internal damage slip in the porous structure of sintered silver nanowires during the cyclic loading process, and simulates the synchronous fatigue degradation of the stiffness and strength of sintered silver nanowire materials, improving the accuracy of the fatigue life prediction of sintered silver nanowires.

[0086] In one embodiment, based on the microscopic morphology image of sintered silver nanowires, a representative volume element (RVE) structure of sintered silver nanowires is constructed; based on the RVE structure of sintered silver nanowires, the material property parameters of sintered silver nanowires are obtained, including the following steps:

[0087] Step 301: Denoise and binarize the microscopic morphology image of the sintered nano - silver, and extract the porosity and pore characteristics.

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

[0089] Among them, the discrete point values in the spatial matrix will be provided by an independent Gaussian distribution N(0,1 2 ) according to the pixel coordinates (x, y, z) and perform Gaussian filtering.

[0090] Step 303: Perform dimensionality reduction on the 3D Gaussian field random pore structure, cut it according to a specified volume fraction, and reconstruct the cut 2D image into a 3D binary structure to obtain the sintered nano - silver RVE structure.

[0091] Step 304: Apply periodic boundary conditions to the sintered nano - silver RVE structure, simulate the deformation and fracture of the sintered nano - silver, and obtain the material property parameters of the sintered nano - silver.

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

[0093] Specifically, based on the real microscopic morphology image of the sintered nano - silver, use a 3D Gaussian random field to perform defect feature modeling, and generate sintered nano - silver RVE structures corresponding to different Gaussian kernels. Figure 3 are the sintered nano - silver defect feature RVE structures generated by different Gaussian kernels. Then, each of the sintered nano - silver RVE structures is matched with the real nano - silver defect structure. Figure 4 is the comparison between the sintered nano - silver RVE structures generated by different Gaussian kernels and the real nano - silver defect structure. By optimizing the width of the Gaussian kernel, the generated sintered nano - silver RVE structure is matched with the real nano - silver defect structure.

[0094] In this application, by optimizing the width of the Gaussian kernel, the generated sintered nano - silver RVE structure is matched with the real nano - silver defect structure. The optimization goal is to minimize the minimum average percentage error of the normalized autocorrelation function between the real nano - silver defect structure and the generated sintered nano - silver RVE structure. Figure 5 is the comparison between the sintered nano - silver RVE structure generated by the optimal Gaussian kernel and the real nano - silver 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 autocorrelation function IAF is as follows:

[0096]

[0097] In the formula, (x, y) are the coordinates of the pixels in the image, and (m, n) are the target pixel points. Usually, the convolution theorem of Fourier transform can be used to quickly calculate the above formula, and the simplified form is shown as follows:

[0098]

[0099] In the formula, FT represents the Fourier transform of the image, and FT -1 represents the inverse Fourier transform of the image.

[0100] Among them, the calculation formula of the minimum average percentage error is as follows:

[0101]

[0102] In the formula, R(r i ) is the normalized autocorrelation function value corresponding to the r i pixel distance in the real silver nanodefect structure, is the normalized autocorrelation function value corresponding to the r i pixel distance in the generated sintered silver nanoscale Representative Volume Element (RVE) structure.

[0103] In step 304, the material parameters of the sintered silver nanoscale RVE structure in Table 1 are used, and the homogenization method is used to apply periodic boundary conditions to the sintered silver nanoscale RVE structure to simulate the surrounding material deformation and fracture, so as to obtain the elastoplastic response curve of the sintered silver nanoscale, as Figure 6 shown. Based on the elastoplastic response curve of the sintered silver nanoscale, the material property parameters of the sintered silver nanoscale are obtained. The specific implementation method is to apply periodic boundary conditions to the sintered silver nanoscale RVE structure in the finite element software to simulate the surrounding material deformation and fracture, so as to obtain the material properties of the sintered silver nanoscale. Among them, the solid silver structure in the RVE structure should adopt the complete material constitutive curve or the hardening equation containing the plastic stage.

[0104] Table 1 Material parameters of the sintered silver nanoscale RVE structure

[0105]

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

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

[0108]

[0109] In one embodiment, 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, the steps for simulating the fatigue life prediction result of sintered nano-silver include the following:

[0110] Step 401, determine the transfer variables in the cyclic simulation of the cyclic cohesive force model in the finite element software, where the transfer variables include the stiffness value of the cyclic cohesive force model, 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.

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

[0112] Step 403, based on the trial displacement at the current moment, judge the state of the current increment step, and update the displacement based on the state of the current increment step.

[0113] Judge whether the state of the current increment step is in the continuous rising or reloading stage or unloading stage, 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 cohesive force in calculating fatigue damage. Based on this, the fatigue damage calculation formula, the monotonic damage calculation formula, and the damage slip calculation formula of the new cyclic cohesive force model can be completely constructed.

[0116] Table 3 Damage-related characteristic parameters in the new cyclic cohesive force model corresponding to sintered nano-silver

[0117]

[0118] Among them, damage slip is defined as the intersection point with the horizontal axis when the maximum stress loading point points to the non-zero negative phase within a cyclic period. 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] where δ s,i represents the damage slip generated in the i-th cycle period, where δ s,0 represents that the initial damage slip value is 0, u cycMax,i represents the maximum displacement value during loading in the i-th cycle period, f cycMax,i represents the maximum traction force during loading in the i-th cycle period, 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] where 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 the key parameters of the cyclic cohesion model. δ0 represents the damage initiation displacement, represents the displacement increment, and 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;

[0125] In the process of calculating the monotonic damage in this application, the displacement at the current moment is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment, considering the cumulative effect of the internal damage slip of the sintered silver nanowire porous structure during the cyclic loading process, improving the prediction accuracy of the fatigue life of the sintered silver nanowire.

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

[0127]

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

[0129] During the process of calculating the fatigue damage in this application, since the displacement at the current moment consists of the cumulative amount of damage slip and the cumulative amount of displacement increment, the cumulative effect of internal damage slip in the sintered silver nanoporous structure during the cyclic loading process is considered, improving the accuracy of predicting the fatigue life of the sintered silver nanoparticle.

[0130] Step 405: Update the stress state of each cohesive unit in the cyclic cohesive model, and determine whether each cohesive unit fails according to the current cumulative damage amount.

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

[0132]

[0133] Where S element represents the state of the cohesive unit. If the total damage amount of the cohesive unit exceeds 1 or the displacement value uNew of the current cohesive unit exceeds the separation displacement δ f at this time, the cohesive unit will be marked as the deleted state 0.0. In other cases, it will be marked as 1.0, which is convenient for subsequent call analysis and software recognition.

[0134] Step 406: When all the cohesive units fail, obtain the prediction result of the fatigue life of the sintered silver nanoparticle.

[0135] In one of the embodiments, 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 stage of reloading after unloading, calculate the damage slip displacement based on the damage slip function, and update the current cumulative damage slip displacement;

[0137] Step 502: 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;

[0138] Step 503: If the traction force exceeds the envelope curve, calculate the monotonic damage based on the monotonic damage function;

[0139] Step 504: When the cyclic load is at the end of the unloading stage, update the current cumulative damage amount based on the fatigue damage and the monotonic damage.

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

[0141] Step 601, determine the transfer variables. Determine the transfer variables in the cyclic simulation of the cyclic cohesive model in finite element software, where 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 cohesive model, etc.

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

[0143] Step 603, judge the state of the current increment step. Based on the trial displacement at the current moment, judge whether the state of the current increment step is in the continuous rising or reloading stage or unloading stage, and update the displacement based on this.

[0144] Step 604, calculate the cumulative damage amount. When the cyclic load is in the reloading stage after unloading, 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, judge 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 load ends the unloading stage, 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 cohesive model according to the current cumulative damage amount.

[0146] This application takes a sintered nano - silver type I specimen as an example, applies periodic transverse loading conditions at both ends, the maximum tensile displacement is 0.2 mm, and the loading and unloading rates are both 1.2 mm / min. The crack propagation simulation process of the sintered nano - silver type I specimen is as Figure 8 shown. The prediction results of the fatigue life of the sintered nano - silver are as Figure 9 shown. Figure 10 It is the traction - displacement curve corresponding to the first cohesive unit during the cyclic loading process. Figure 11 It is the cumulative damage amount and damage slip amount of the first cohesive unit in the sintered nano - silver specimen model.

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

[0148] In one embodiment, as Figure 12As shown, a device for predicting the fatigue life of sintered nano - silver, the device comprising:

[0149] A material parameter calculation module 10, configured to construct a representative volume element (RVE) structure of the sintered nano - silver based on the microscopic morphology image of the sintered nano - silver; and obtain the material property parameters of the sintered nano - silver based on the sintered nano - silver RVE structure;

[0150] A model parameter calculation module 20, configured to calculate the key parameters of the cyclic cohesive force model based on the material property parameters;

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

[0152] A simulation prediction module 40, configured to place the cyclic cohesive force model into an explicit solver of finite element software, and 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 result of the sintered nano - silver.

[0153] In one embodiment, the material parameter calculation module 10 is further configured to: perform noise reduction and binarization processing on the microscopic morphology image of the sintered nano - silver, extract the 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 nano - silver to obtain a 3D Gaussian field random pore structure; perform dimensionality reduction processing on the 3D Gaussian field random pore structure, and cut it according to a specified volume fraction, and reconstruct the cut two - dimensional image into a 3D binary structure to obtain a sintered nano - silver RVE structure; apply periodic boundary conditions to the sintered nano - silver RVE structure, simulate the deformation and fracture of the sintered nano - silver, and obtain the material property parameters of the sintered nano - silver.

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

[0155] In one embodiment, the model construction module 30 is further configured to determine the transfer variables in the cyclic simulation of the cyclic cohesive force model in the finite element software, where 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 cohesive force model, calculate 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, judge the state of the current increment step, and update the displacement based on the state of the current increment step; 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 cohesive force 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 nano silver.

[0156] In one embodiment, the model construction module 30 is further configured to: in each cyclic simulation, when the cyclic load is in the stage of reloading after unloading, 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 is at the end of the unloading stage, update the current cumulative damage amount based on the fatigue damage and the monotonic damage.

[0157] In one embodiment, the calculation formula of the damage slip function is as follows:

[0158]

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

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

[0161]

[0162] where δ fDenotes 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 cohesive force model. δ0 denotes the damage initiation displacement. Denotes the displacement increment. δ denotes the displacement at the current moment, which is composed of the cumulative amount of damage slip and the cumulative amount of displacement increment.

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

[0164]

[0165] Where D cycle Denotes the damage result during cyclic loading. Denotes the displacement increment. Denotes the damage scaling factor. f denotes the traction force at the current loading moment. k denotes the stiffness. D denotes the monotonic damage D montic And the fatigue damage D cycle Cumulative amount. δ denotes 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 Denotes the maximum traction force. C f And a denote the cyclic cohesive force model parameters.

[0166] It should be noted that the above-mentioned each module can be a functional module or a program module, and can be implemented either by software or by hardware. For the modules implemented by hardware, the above-mentioned each module can be located in the same processor; or the above-mentioned each module can also be located in different processors in any combined form.

[0167] In one embodiment, a computer device is provided. The computer device can be a terminal. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Among them, 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 the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner. The wireless manner can be implemented through WIFI, a mobile cellular network, NFC (Near Field Communication), or other technologies. The computer program, when executed by the processor, implements a fatigue life prediction method for sintered nano-silver.

[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 in any of the above-mentioned embodiments of the fatigue life prediction method for sintered nano-silver are implemented.

[0169] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. 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 various methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0170] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0171] The above embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A method for predicting the fatigue life of sintered nano - silver, characterized in that, The method includes: Constructing a representative volume element (RVE) structure of sintered nano - silver based on the microscopic morphology image of sintered nano - silver; obtaining the material property parameters of the sintered nano - silver based on the RVE structure of the sintered nano - silver; Calculating the key parameters of the cyclic cohesive force model based on the material property parameters; Constructing the envelope curve of the cyclic cohesive force model based on the key parameters of the cyclic cohesive force model, and defining the fatigue damage function, monotonic damage function, and damage slip function of the cyclic cohesive force model; Putting the cyclic cohesive force model into finite element software, and 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, simulating to obtain the fatigue life prediction result of sintered nano - silver.

2. The method according to claim 1, wherein The constructing a representative volume element (RVE) structure of sintered nano - silver based on the microscopic morphology image of sintered nano - silver; obtaining the material property parameters of the sintered nano - silver based on the RVE structure of the sintered nano - silver includes: Performing noise reduction and binarization processing on the microscopic morphology image of the sintered nano - silver, and extracting the porosity and pore characteristics; Based on the porosity and the pore characteristics, using a 3D Gaussian random field to model the defect characteristics of sintered nano - silver, and obtaining a 3D Gaussian field random pore structure; Performing dimensionality reduction processing on the 3D Gaussian field random pore structure, and cutting it according to a specified volume fraction, and reconstructing the cut - after two - dimensional image into a 3D binary structure to obtain the RVE structure of sintered nano - silver; Applying periodic boundary conditions to the RVE structure of the sintered nano - silver, simulating the deformation and fracture of the sintered nano - silver, and obtaining the material property parameters of the sintered nano - silver.

3. The method according to claim 2, wherein The method further includes: Using 3D Gaussian random fields with different Gaussian kernels to model the defect characteristics of sintered nano - silver, obtaining corresponding 3D Gaussian field random pore structures, and based on each 3D Gaussian field random pore structure, obtaining each corresponding RVE structure of sintered nano - silver; Matching each RVE structure of the sintered nano - silver with the real sintered nano - silver defect structure to determine the optimal RVE structure of sintered nano - silver.

4. The method according to claim 1, wherein The simulating to obtain the fatigue life prediction result of sintered nano - silver 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: Determining the transfer variables in the cyclic simulation of the cyclic cohesive force model in the finite element software, where the transfer variables include the stiffness value, maximum critical stress, fracture energy, cumulative damage amount of the previous cycle simulation, cumulative damage slip amount, and system state variables of the cyclic cohesive force 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, judging the state of the current increment step, and updating the displacement based on the state of the current increment step; 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; Update the stress state of each cohesive unit in the cyclic cohesive force model, and determine whether each of the cohesive units fails according to the current cumulative damage amount; When all the cohesive units fail, obtain the fatigue life prediction result of the sintered nano-silver.

5. The method according to claim 4, wherein 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 reloading stage after unloading, 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 is at the end of the unloading stage, update the current cumulative damage amount based on the fatigue damage and the monotonic damage.

6. The method according to claim 5, wherein: 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 period, where δ s,0 indicates that the initial damage slip value is 0, u cycMax,i represents the maximum displacement value during loading in the i-th cycle period, f cycMax,i represents the maximum traction force during loading in the i-th cycle period, f ne represents the negative phase point pointed to during unloading, and ne represents the cyclic cohesion model parameter.

7. The method according to claim 5, wherein: The calculation formula of the monotonic damage function is as follows: ； where 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 cohesive force model. δ0 represents the damage initiation displacement. represents the displacement increment, and 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 force at the current loading moment, k represents the stiffness, and D represents the monotonic damage D montic and the 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 represents the maximum traction force, C f and a represent the cyclic cohesion model parameters.

8. A fatigue life prediction device for sintered nano - silver, characterized in that, The device includes: A material parameter calculation module, configured to construct a sintered nano-silver RVE structure based on a microscopic morphology image of the sintered nano-silver; and obtain the material property parameters of the sintered nano-silver based on the sintered nano-silver RVE structure; A model parameter calculation module, configured to calculate the key parameters of the cyclic cohesive force model based on the material property parameters; A model construction module, configured to construct an envelope curve of the cyclic cohesive force model based on the key parameters of the cyclic cohesive force model, and define a fatigue damage function, a monotonic damage function, and a damage slip function of the cyclic cohesive force model; A simulation prediction module, configured to place the cyclic cohesive force model into an explicit solver of finite element software, and 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 result of the sintered nano-silver.

9. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, 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 the processor, the method according to any one of claims 1 to 7 is implemented.

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