Detector high repetition frequency laser irradiation effect evaluation method and system

Abstract

The invention belongs to the technical field of photoelectricity, and relates to a detector high repetition frequency laser irradiation effect evaluation method and system. The evaluation method comprises the following steps: determining a high repetition frequency laser parameter and a detector structure material attribute parameter; constructing a thermal coupling transient model of the detector, and setting boundary conditions of a heat transfer physical field and a solid mechanics physical field of the thermal coupling transient model; grid division is carried out on the thermal coupling transient model, and solver parameters are set; solver parameters are determined by applying a pre-trained linear neural network model, specifically, the laser pulse width and the laser frequency are input into the pre-trained linear neural network model, and calculation is performed by applying a pre-trained linear neural network model expression to obtain the solver parameters; and based on the parameters of the solver, solving the thermal coupling transient model by using the solver to obtain the temperature field and stress field distribution conditions of the detector at different irradiation moments under high repetition frequency laser irradiation. The evaluation method is high in accuracy and calculation efficiency.

Description

Technical Field

[0001] The present invention relates to the field of optoelectronic technology, and in particular to a method and system for evaluating the high-repetition-rate laser irradiation effect of a detector. Background Art

[0002] Laser interference damage to detectors is a hot topic in the field of optoelectronic technology. The interference damage to the detector when irradiated by laser is mainly caused by the combined effects of melting damage and thermal stress. Therefore, obtaining the irradiation effect of the detector under the action of laser, specifically involving the time evolution characteristics of the temperature field inside the detector and the thermal stress generated by the temperature rise, has a significant supporting role in the study of the interference damage law of the laser on the detector.

[0003] The traditional experimental method of obtaining the irradiation effect of laser irradiation detectors is relatively complicated and costly, and there are few studies on the irradiation effect of high-repetition-rate lasers (i.e., laser sequences consisting of laser pulse widths of the order of ns and laser pulse periods of the order of ms) with repetition frequencies exceeding KHz. This is mainly due to the technical limitations of existing measurement methods at extreme time scales. Specifically, the transient energy deposition process of the order of ns far exceeds the response speed of conventional temperature and stress sensors. Limited by thermal inertia effects and stress relaxation time, traditional thermocouples, thermal imagers, strain gauges and other equipment are difficult to achieve in-situ measurements with sub-microsecond time resolution; and the pulse period of the order of ms requires the measurement system to have high-frequency cyclic anti-interference capabilities, which further increases the difficulty of experimental observation. This dual constraint of time span leads to a lack of effective characterization methods for the thermal-mechanical coupling process of the interaction between high-repetition-rate lasers and detectors, which restricts in-depth research on the mechanism and laws of high-repetition-rate laser irradiation damage. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for evaluating the high repetition rate laser irradiation effect of a detector. The detector is irradiated by a high repetition rate laser to produce an irradiation effect, and the temperature field and stress field distribution of the detector under the high repetition rate laser are obtained by constructing a model and solving it. The evaluation method effectively solves the time scale contradiction between the ns-level pulse width and the ms-level pulse period under the action of the high repetition rate laser, improves the accuracy and calculation efficiency in the evaluation research, and thus can solve the problem of evaluating the irradiation effect of the high repetition rate laser irradiated detector.

[0005] In order to achieve the above object, the present invention adopts the following technical scheme: In a first aspect, the present invention provides a method for evaluating the high repetition rate laser irradiation effect of a detector, the evaluation method comprising the following steps: Determine high repetition rate laser parameters and detector structure material property parameters; Construct a thermal-mechanical coupling transient model of the detector, and set the heat transfer physical field and solid mechanics physical field boundary conditions of the thermal-mechanical coupling transient model; The thermomechanical coupling transient model is meshed and the solver parameters are set; the solver parameters include the initial step size of the solver, the storage time step of the laser irradiation time period, the storage time step of the laser non-irradiation time period, the maximum step size constraint of the laser irradiation time period and the maximum step size constraint of the laser non-irradiation time period; the solver parameters are determined by using a pre-trained linear neural network model, specifically: the high repetition rate laser pulse width and high repetition rate laser frequency are input into the pre-trained linear neural network model, and the solver parameters are obtained by calculating using the pre-trained linear neural network model expression; The solver is used to solve the thermal-mechanical coupling transient model to obtain the temperature field and stress field distribution of the detector at different irradiation times under high repetition rate laser irradiation.

[0006] As a possible implementation method, the pre-trained linear neural network model includes an input layer and an output layer; wherein the parameters of the output layer include a storage time stepping node for the laser irradiation time period, a storage time stepping node for the laser non-irradiation time period, an initial step node, a maximum step constraint node for the laser irradiation time period, and a maximum step constraint for the laser non-irradiation time period.

[0007] As a possible implementation, the pre-trained linear neural network model expression is: ; in, is the weight matrix, ; is the bias vector, ; is the storage time step of the solver during the laser irradiation period; The storage time step of the solver during the laser non-irradiation period; is the initial step size of the solver; is the maximum step size constraint of the solver during the laser irradiation period; It is the maximum step size constraint of the solver during the laser non-irradiation period; is the high repetition rate laser pulse width; It is a high repetition rate laser frequency.

[0008] As a possible implementation method, the parameters of the input layer and the parameters of the output layer are normalized, and the normalization range is [0, 1]; the normalized expression is: ; in, is the result after normalization of the corresponding parameter value in the training data set; is the corresponding parameter value in the training data set; and are the minimum and maximum values ​​of the corresponding parameters in the training data set, respectively.

[0009] As a possible implementation, and The parameters must satisfy physical constraints: ; If the prediction results do not meet the above constraints, they should be corrected in the following ways: .

[0010] As a possible implementation method, the thermal-mechanical coupling transient model of the detector is meshed, wherein the upper surface of the silicon dioxide insulating layer and the lower surface of the polysilicon electrode are meshed using free triangles, and the rest of the model is meshed using swept meshes.

[0011] As a possible implementation, the laser pulse width ranges from 100ps to 500ns, and the repetition frequency ranges from 1K to 10K.

[0012] As a possible implementation method, the process of solving the thermal-mechanical coupling transient model of the detector is: setting the use of the backward difference formula in the solver to solve the time step; the initial step size of the solver, the storage time step size of the solver in the laser irradiation section, the storage time step size of the solver in the laser non-irradiation time period, the maximum step size constraint of the solver in the laser irradiation time period and the maximum step size constraint of the solver in the laser non-irradiation time period can be set according to the pre-trained linear neural network model results.

[0013] In a second aspect, the present invention provides a detector high repetition rate laser irradiation effect evaluation system, specifically comprising: An evaluation parameter configuration unit, used to configure evaluation parameters, the evaluation parameters including high repetition rate laser parameters and detector structure material property parameters; The detector thermal-mechanical coupling model building unit builds the thermal-mechanical coupling transient model of the detector and determines the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermal-mechanical coupling transient model; Meshing unit, which meshes the thermal-mechanical coupling transient model based on the heat transfer physics and solid mechanics physics; A solver parameter configuration unit is used to configure solver parameters, including the initial step size of the solver, the storage time step of the laser irradiation time period, the storage time step of the laser non-irradiation time period, the maximum step size constraint of the laser irradiation time period, and the maximum step size constraint of the laser non-irradiation time period; the solver parameters are determined by using a pre-trained linear neural network model, specifically: the high repetition rate laser pulse width and the high repetition rate laser frequency are input into the pre-trained linear neural network model, and the solver parameters are obtained by calculation using the pre-trained linear neural network model expression; The detector temperature field and stress field distribution determination unit uses a solver to solve the thermal-mechanical coupling transient model to obtain the temperature field and stress field distribution of the detector at different irradiation times under high repetition rate laser irradiation.

[0014] Compared with the prior art, the beneficial effects of the present invention are: 1. The present invention proposes a method for evaluating the high-repetition-rate laser irradiation effect of a detector. The method has high evaluation accuracy and calculation efficiency and can solve the problem of evaluating the irradiation effect of a high-repetition-rate laser irradiation detector.

[0015] 2. The present invention proposes a method for evaluating the high-repetition-rate laser irradiation effect of a detector. The process of obtaining the temperature field and stress field in the high-repetition-rate laser irradiation effect is simple and low-cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings: Figure 1 This is a flow chart of the method for evaluating the high repetition rate laser irradiation effect on detectors; Figure 2 A schematic diagram of a detector structure material according to an embodiment of the present invention; Figure 3 A schematic diagram of a laser switch function according to an embodiment of the present invention; Figure 4 A schematic diagram of grid division according to an embodiment of the present invention; Figure 5 is a graph showing the maximum temperature variation of the upper surface of the silicon substrate in an embodiment of the present invention; Figure 6 is a graph showing a change in maximum stress on the upper surface of a silicon substrate in an embodiment of the present invention; Figure 7 is a curve diagram of the maximum temperature change on the upper surface of the light-shielding aluminum film in an embodiment of the present invention; Figure 8 is a curve diagram of maximum stress variation on the upper surface of the light-shielding aluminum film in an embodiment of the present invention; Fig. 9 The temperature field distribution at t=1633.9us in the embodiment of the present invention; Fig.10 The thermal stress distribution at t=1633.9us in the embodiment of the present invention; Fig.11 This is the thermal expansion displacement distribution at t=1633.9us in the embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, words such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and effects. For example, the first threshold and the second threshold are only used to distinguish different thresholds, and their order is not limited. Those skilled in the art can understand that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit them to be different.

[0018] It should be noted that, in the present invention, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0019] In the present invention, "at least one" means one or more, and "plurality" means two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the associated objects before and after are in an "or" relationship. The following at least one item (items) or similar expressions thereof refer to any combination of these items, including any combination of single items (items) or plural items (items). For example, at least one item (items) of a, b or c can mean: a, b, c, the combination of a and b, the combination of a and c, the combination of b and c, or the combination of a, b and c, where a, b, c can be single or multiple.

[0020] The embodiment of the present invention aims to provide a method and system for evaluating the high repetition rate laser irradiation effect of a detector, which can comprehensively and accurately capture the transient and complex physical phenomena of the high repetition rate laser irradiating the detector at different times by optimizing the design of solver parameters. The specific implementation methods are as follows: In a first aspect, an embodiment of the present invention provides a method for evaluating the high repetition rate laser irradiation effect of a detector, see Figure 1 , the evaluation method includes the following steps: Determine high repetition rate laser parameters and detector structure material property parameters; As a possible implementation method, the high repetition rate laser pulse width ranges from 100ps to 500ns, and the repetition frequency is 1K to 10K.

[0021] Exemplarily, high repetition rate laser parameters are shown in Table 1 below; Table 1 High repetition rate laser parameters Exemplarily, the detector structure is a multi-layer structure, such as Figure 2 As shown, from bottom to top are a silicon substrate, a silicon dioxide insulating layer, a polysilicon electrode, a silicon dioxide thickening layer, a light-shielding metal layer, and a microlens layer.

[0022] Exemplarily, the detector light-shielding metal layer material includes: metals such as aluminum and tungsten, and semiconductor materials such as silicon and germanium.

[0023] The light shielding layer metal takes aluminum as an example, the microlens layer material takes polyimide as an example, and the detector structure material property parameters are shown in Table 2 below: Table 2 Detector structural material property parameters Construct a thermal-mechanical coupling transient model of the detector, and set the heat transfer physical field and mechanical physical field boundary conditions of the thermal-mechanical coupling transient model; Exemplarily, a thermal-mechanical coupling transient model of the detector is constructed based on COMSOL Multiphysics software.

[0024] Exemplarily, the thermal-mechanical coupling transient model of the detector is obtained by creating solid heat transfer and solid mechanics modules and performing high repetition rate laser irradiation thermal-mechanical coupling multi-physics field simulation.

[0025] For example, in the solid heat transfer module, the expression is: in, It is a laser heat source; is the instantaneous temperature at a certain location; is the material density; Hot melting of materials; is the thermal conductivity of the material.

[0026] For example, in the solid mechanics module, the expression is: ; in, is the displacement of a certain position; is the acceleration term; is the internal stress term, and the expression of internal stress S is: , is the fourth-order elastic matrix, is the thermal expansion strain, is the displacement strain.

[0027] For example, the thermal expansion strain of the irradiated detector structural material The relationship with temperature change is: ; in, is the thermal expansion strain of the material; is the thermal expansion coefficient of the material; is temperature; is the volume reference temperature.

[0028] For example, when a high repetition rate laser irradiates the detector structure material, the material cannot completely conduct heat on a time scale of ns or less. A portion of the laser beam directly passes through the microlens layer and the silicon dioxide insulating layer to irradiate the photosensitive surface of the silicon substrate. The silicon substrate can absorb the laser in volume. Therefore, the heat source on the silicon substrate is set as the volume heat source, and the corresponding laser energy deposition expression is: ; in, is the spot radius; t For time; is the absorption coefficient of silicon to laser; is the reflectivity of the photosensitive area; is the position of any point on the laser energy deposition surface; is the center position of the spot on the laser energy deposition surface; For the laser beam Function of direction; is the average output power of a single pulse of the laser; is the laser pulse switching time function, and the function in the embodiment is specifically as follows Figure 3 As shown, the expression is: ; in, is the high repetition rate laser frequency; ; It is a Gaussian pulse function with a peak value of 1 and a standard deviation of the pulse width; Based on the aperture ratio of the detector, part of the laser is irradiated on the light-shielding aluminum film. The thickness of the light-shielding aluminum film in the model is much greater than its absorption depth of the laser. Therefore, the heat source on the light-shielding aluminum film is set as a surface heat source, and the corresponding laser energy deposition expression is: ; ; ; in, is the spot radius; For time; is the absorption coefficient of silicon to laser; is the reflectivity of the photosensitive area; is the position of any point on the laser energy deposition surface; is the center position of the spot on the laser energy deposition surface; is the absorption coefficient of aluminum to laser; For the laser beam Function of direction; is the average output power of a single pulse of the laser; is the laser single pulse energy; is the laser pulse width; is the laser pulse switching time function, and the function in the embodiment is specifically as follows Figure 3 As shown, the expression is: in, is the high repetition rate laser frequency; ; It is a Gaussian pulse function with a peak value of 1 and a standard deviation of the pulse width.

[0029] For example, the expression for the convective heat transfer between the surface of the detector structure material and the environment is: ; in, is the convective heat transfer coefficient; is the ambient temperature; is temperature; The thermal radiation of the detector structure material surface to the environment, the corresponding radiation heat flux expression is: ; in, is the surface emissivity, is the Stefan constant.

[0030] Meshing of thermal-mechanical coupled transient models; As a possible implementation, free triangle meshing is used for the upper surface of the silicon dioxide insulating layer and the lower surface of the polysilicon electrode, and swept meshing is used for the rest of the model.

[0031] Exemplarily, the thermal-mechanical coupling transient model of the detector is a three-dimensional model, such as Figure 4 As shown, the model is a 200um×200um×35um cuboid, wherein the silicon substrate and the silicon dioxide insulating layer are 200um×200um×30um and 200um×200um×1um respectively, the size of the polysilicon electrode, the silicon dioxide thickening layer and the light-shielding metal layer are all 20um×20um×1um and are arranged at equal intervals in a 9×9 array on the upper surface of the silicon dioxide insulating layer with a spacing of 2.5um; the thickness of the top microlens layer is 1um.

[0032] Set the solver parameters, including the initial step size of the solver, the storage time step of the laser irradiation time period, the storage time step of the laser non-irradiation time period, the maximum step size constraint of the laser irradiation time period, and the maximum step size constraint of the laser non-irradiation time period; the solver parameters are determined by using a pre-trained linear neural network model, specifically: input the high repetition rate laser pulse width and the high repetition rate laser frequency into the pre-trained linear neural network model, and use the pre-trained linear neural network model expression to calculate and obtain the solver parameters; As a possible implementation method, the pre-trained linear neural network model includes an input layer and an output layer; wherein the parameters of the input layer include a high repetition rate laser pulse width node and a high repetition rate laser frequency node; the parameters of the output layer include a storage time step node of a laser irradiation time period, a storage time step node of a laser non-irradiation time period, an initial step node, a maximum step constraint node of a laser irradiation time period, and a maximum step constraint of a laser non-irradiation time period.

[0033] As a possible implementation, the pre-trained linear neural network model expression is: ; in, is the weight matrix, ; is the bias vector, ; is the storage time step of the solver during the laser irradiation period; The storage time step of the solver during the laser non-irradiation period; is the initial step size of the solver; is the maximum step size constraint of the solver during the laser irradiation period; It is the maximum step size constraint of the solver during the laser non-irradiation period; is the high repetition rate laser pulse width; It is a high repetition rate laser frequency.

[0034] As a possible implementation method, the parameters of the input layer and the parameters of the output layer are normalized, and the normalization range is [0, 1]; the normalized expression is: ; in, is the result after normalization of the corresponding parameter value in the training data set; is the corresponding parameter value in the training data set; and are the minimum and maximum values ​​of the corresponding parameters in the training data set, respectively.

[0035] As a possible implementation, , and The parameters must satisfy physical constraints: ; If the prediction results do not meet the above constraints, they should be corrected in the following ways: ; .

[0036] As a possible implementation method, the initial step size of the solver, the storage time step of the solver in the laser irradiation section, the storage time step of the solver in the laser non-irradiation time period, the maximum step size constraint of the solver in the laser irradiation time period and the maximum step size constraint of the solver in the laser non-irradiation time period can be set according to the results of a pre-trained linear neural network model.

[0037] The solver is used to solve the thermal-mechanical coupling transient model to obtain the temperature field and stress field distribution of the detector at different irradiation times under high repetition rate laser irradiation. After the solution is completed, the model is post-processed, the data of the required monitoring data sets such as the section line, cross section or intercept point are called, and the corresponding temperature, stress, thermal expansion displacement and other physical quantity change diagrams are drawn using the drawing group.

[0038] like Figures 5 to 8 As shown, in this embodiment, the upper surface of the silicon substrate and the light-shielding aluminum film are selected, and their maximum temperature and maximum stress change curves are plotted in the one-dimensional plot group. Fig. 9 , 10 As shown in Figure 11, a three-dimensional drawing group is added in this embodiment to draw the temperature field distribution diagram, thermal stress distribution diagram and thermal expansion displacement distribution diagram of the detector when t=1633.9us. The figure shows the changes in the physical characteristics of the detector well, and effectively solves the time scale contradiction between the ns-level pulse width and the ms-level pulse period under the action of high repetition rate laser in the simulation, improves the accuracy and calculation efficiency of the simulation evaluation, and thus can solve the problem of irradiation effect evaluation of high repetition rate laser irradiation detector.

[0039] In a second aspect, the present invention provides a detector high repetition rate laser irradiation effect evaluation system, specifically comprising: An evaluation parameter configuration unit, used to configure evaluation parameters, the evaluation parameters including high repetition rate laser parameters and detector structure material property parameters; The detector thermal-mechanical coupling model building unit builds the thermal-mechanical coupling transient model of the detector and determines the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermal-mechanical coupling transient model; Meshing unit, which meshes the thermal-mechanical coupling transient model based on the heat transfer physics and solid mechanics physics; A solver parameter configuration unit is used to configure solver parameters, including the initial step size of the solver, the storage time step of the laser irradiation time period, the storage time step of the laser non-irradiation time period, the maximum step size constraint of the laser irradiation time period, and the maximum step size constraint of the laser non-irradiation time period; the solver parameters are determined by using a pre-trained linear neural network model, specifically: the high repetition rate laser pulse width and the high repetition rate laser frequency are input into the pre-trained linear neural network model, and the solver parameters are obtained by calculation using the pre-trained linear neural network model expression; The detector temperature field and stress field distribution determination unit uses a solver to solve the thermal-mechanical coupling transient model to obtain the temperature field and stress field distribution of the detector at different irradiation times under high repetition rate laser irradiation.

[0040] Although the present invention is described herein in conjunction with various embodiments, in the process of implementing the claimed invention, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the drawings, etc. In the specification, the word "comprising" does not exclude other components or steps, and "one" or "an" does not exclude multiple situations. A single processor or other unit can implement several functions listed in the specification. Certain measures are recorded in different embodiments, but this does not mean that these measures cannot be combined to produce good results.

[0041] Although the present invention has been described in conjunction with specific features and embodiments thereof, it is apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present invention. Accordingly, this specification and the accompanying drawings are merely exemplary illustrations of the present invention and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present invention. Obviously, those skilled in the art may make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, the present invention is intended to include such modifications and variations if they fall within the scope of the present invention and its equivalents.

Claims

1. A method for evaluating the high repetition rate laser irradiation effect of a detector, characterized in that: The evaluation method comprises the following steps: Determine high repetition rate laser parameters and detector structure material property parameters; Construct a thermal-mechanical coupling transient model of the detector, and set the heat transfer physical field and solid mechanics physical field boundary conditions of the thermal-mechanical coupling transient model; The thermomechanical coupling transient model is meshed and solver parameters are set; the solver parameters include the initial step size of the solver, the storage time step of the laser irradiation time period, the storage time step of the laser non-irradiation time period, the maximum step size constraint of the laser irradiation time period and the maximum step size constraint of the laser non-irradiation time period; the solver parameters are determined by using a pre-trained linear neural network model, specifically: the high repetition rate laser pulse width and the high repetition rate laser frequency are input into the pre-trained linear neural network model, and the solver parameters are obtained by calculating using the pre-trained linear neural network model expression; The solver is used to solve the thermal-mechanical coupling transient model to obtain the temperature field and stress field distribution of the detector at different irradiation times under high repetition rate laser irradiation.

2. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 1, characterized in that: The pre-trained linear neural network model includes an input layer and an output layer; wherein the parameters of the input layer include a high repetition rate laser pulse width node and a high repetition rate laser frequency node; the parameters of the output layer include a storage time stepping node for a laser irradiation time period, a storage time stepping node for a laser non-irradiation time period, an initial step length node, a maximum step length constraint node for a laser irradiation time period, and a maximum step length constraint for a laser non-irradiation time period.

3. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 2, characterized in that: The pre-trained linear neural network model expression is: ； in, is the weight matrix, ; is the bias vector, ; is the storage time step of the solver during the laser irradiation period; The storage time step of the solver during the laser non-irradiation period; is the initial step size of the solver; is the maximum step size constraint of the solver during the laser irradiation period; It is the maximum step size constraint of the solver during the laser non-irradiation period; is the high repetition rate laser pulse width; It is a high repetition rate laser frequency.

4. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 2, characterized in that: The parameters of the input layer and the output layer are normalized, and the normalization range is [0, 1]. The normalized expression is: ； in, is the result after normalization of the corresponding parameter value in the training data set; is the corresponding parameter value in the training data set; and are the minimum and maximum values ​​of the corresponding parameters in the training data set, respectively.

5. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 3, characterized in that: , and The parameters must satisfy physical constraints: ； If the prediction results do not meet the above constraints, they should be corrected in the following ways: ； 。 6. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 1, characterized in that: The mesh division adopts free triangle mesh division for the upper surface of the silicon dioxide insulating layer and the lower surface of the polysilicon electrode, and adopts swept mesh division for the remaining part of the model.

7. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 1, characterized in that: The high repetition rate laser pulse width ranges from 100ps to 500ns, and the repetition frequency ranges from 1K to 10K.

8. The method for evaluating the high repetition rate laser irradiation effect of a detector according to claim 1, characterized in that: The solver is set to use the backward difference formula to solve the time step; the initial step size of the solver, the storage time step size of the solver in the laser irradiation section, the storage time step size of the solver in the laser non-irradiation time period, the maximum step size constraint of the solver in the laser irradiation time period, and the maximum step size constraint of the solver in the laser non-irradiation time period are all set according to the pre-trained linear neural network model results.

9. A detector high repetition rate laser irradiation effect evaluation system, characterized in that: include: An evaluation parameter configuration unit, used to configure evaluation parameters, wherein the evaluation parameters include high repetition rate laser parameters and detector structure material property parameters; The detector thermal-mechanical coupling model building unit builds the thermal-mechanical coupling transient model of the detector and determines the boundary conditions of the heat transfer physical field and the solid mechanics physical field of the thermal-mechanical coupling transient model; Meshing unit, which meshes the thermal-mechanical coupling transient model based on the heat transfer physics and solid mechanics physics; A solver parameter configuration unit, used to configure solver parameters, the solver parameters include an initial step size of the solver, a storage time step of a laser irradiation time period, a storage time step of a laser non-irradiation time period, a maximum step size constraint of a laser irradiation time period, and a maximum step size constraint of a laser non-irradiation time period; the solver parameters are determined by applying a pre-trained linear neural network model, specifically: a high repetition rate laser pulse width and a high repetition rate laser frequency are input into a pre-trained linear neural network model, and the solver parameters are obtained by calculation using a pre-trained linear neural network model expression; The detector temperature field and stress field distribution determination unit uses a solver to solve the thermal-mechanical coupling transient model to obtain the temperature field and stress field distribution of the detector at different irradiation times under high repetition rate laser irradiation.

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