A method for predicting damage evolution of optical components based on laser irradiation

Abstract

The present invention relates to the technical field of optical elements, and in particular to a method for predicting the damage evolution of optical elements based on laser irradiation. The method comprises the following steps: first, obtaining the physical parameters (oxygen-silicon ratio, transmittance, and absorption coefficient) of the optical element and the laser irradiation parameters (wavelength, energy density, and repetition frequency). Then, a multi-environment damage prediction model is established to map the relationship between the environmental parameters and the damage threshold. A correlation model of oxygen-silicon ratio-transmittance-damage threshold is constructed to analyze the evolution of the physical parameters with the number of laser shots. Finally, a thermal-optical-mechanical multi-physics field coupling model is established to explore the damage mechanism. Finally, these models are used to predict the evolution of the damage threshold of the optical element after different laser shots, and a damage threshold variation trend curve and critical damage point are obtained. A damage prediction model based on the physical parameters is established, which enables early prediction of the damage evolution of the optical element, reduces the experimental cycle, and improves the evaluation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of optical elements, and in particular to a method for predicting the damage evolution of optical elements based on laser irradiation, which can be applied to damage prediction and life assessment of optical elements in high-power laser systems. Background Art

[0002] The problem of laser damage to fused quartz in a vacuum environment has always been one of the key issues restricting its application performance. In a vacuum environment, the ability of fused quartz to resist laser damage decreases, and the damage threshold is lower than that in the atmospheric environment, which leads to further expansion of the damage under subsequent laser irradiation, thereby increasing the operating cost and utilization efficiency of the system.

[0003] The study found that this change is mainly attributed to the enhancement of surface and internal defects of fused quartz in a vacuum environment and the change of heat transfer mode. Microscopically, when fused quartz is placed in a vacuum environment, ultraviolet laser irradiation will cause it to have induced defects such as ODCs and NBOHCs, resulting in a substoichiometric ratio of the material (SiO x )x<2. Studies have shown that higher laser flux, more irradiation cycles, and lower oxygen-to-silicon ratios accelerate the appearance of oxygen defects. Oxygen defects strongly absorb laser light, thus reducing the laser damage threshold. Macroscopically, due to the extremely low gas content in a vacuum environment, the fused silica window cannot effectively transfer energy through air convection, leading to heat accumulation. As the number of laser pulses increases, the laser damage threshold generally decreases. These two energy accumulation processes increase the risk of damage to the fused silica and reduce its resistance to laser damage.

[0004] Optical components are crucial components of laser systems, and their quality and stability directly impact their performance and lifespan. In high-power laser systems, optical components can gradually become damaged by prolonged exposure to laser radiation. Understanding and predicting the evolution of this damage is crucial for improving system reliability and extending component lifespan.

[0005] Prior art, such as Chinese patent publication number CN115014718B, "A Method for Studying Laser-Irradiated Optical Component Damage," discloses a technical solution for experimentally studying optical component damage. This method determines the damage threshold of the optical component, using an irradiation energy density below the damage threshold to measure the optical component's lifespan under long-term laser irradiation. Fluorescence spectroscopy combined with changes in helium-neon laser light is then used to determine component damage. Changes or damage, such as deformation, stress mutations, and cracks, are then monitored in real time.

[0006] However, the above methods mainly focus on real-time monitoring and experimental testing, and have the following shortcomings: First, the predictive ability is limited, and it is impossible to predict in advance the damage trend of optical components under different laser irradiation times; second, the parameter correlation is insufficient, and a quantitative relationship model between the physical property parameters of optical components and the development of damage has not been established; third, the environmental limitations are mainly targeted at conventional environments, and the differences in damage mechanisms of optical components in vacuum environments are not considered; fourth, there is a lack of analysis of composite damage mechanisms, and the composite mechanism of photochemical and photothermal damage has not been deeply analyzed; fifth, the experimental cycle is long, and a large number of experiments are required to obtain the damage law, which is inefficient. In addition, although this method mentions the thermal accumulation effect, it lacks a detailed quantitative analysis model for thermal effects.

[0007] Therefore, a method is needed to predict the damage evolution of optical components based on physical parameters, so as to achieve early prediction of damage, reduce experimental cycle and improve evaluation efficiency. Summary of the Invention

[0008] The purpose of the present invention is to provide a method for predicting the evolution of damage to optical components based on laser irradiation, so as to solve the technical problems in the prior art such as limited prediction ability, insufficient parameter correlation, and poor environmental adaptability, and to achieve accurate prediction of the evolution of damage to optical components.

[0009] To achieve the above-mentioned purpose, the present invention provides a technical solution: a method for predicting damage evolution of optical components based on laser irradiation, comprising:

[0010] Acquiring physical parameters and laser irradiation parameters of the optical element, wherein the physical parameters include oxygen-silicon ratio, transmittance, and absorption coefficient, and the laser irradiation parameters include wavelength, energy density, and repetition frequency;

[0011] Establish a prediction model for laser irradiation damage evolution, including:

[0012] Based on the physical parameters and laser irradiation parameters, constructing a multi-environment damage prediction model, wherein the multi-environment damage prediction model includes a mapping relationship between environmental parameters and damage thresholds;

[0013] Based on the physical parameters, an oxygen-silicon ratio-transmittance-damage threshold correlation model is constructed, wherein the correlation model characterizes the evolution relationship of the physical parameters with the number of laser shots;

[0014] Based on the laser irradiation parameters, a heat-light-force multi-physics field coupling model is constructed, wherein the coupling model characterizes the damage mechanism under the interaction of multiple physical fields;

[0015] The multi-environment damage prediction model, the correlation model and the coupling model are used to predict the evolution of the damage threshold of the optical element after different laser irradiations. The prediction results include a trend curve of the damage threshold changing with the number of irradiations and a critical damage point.

[0016] As a preselection, the construction of the multi-environment damage prediction model specifically includes:

[0017] Establish an environmental parameter mapping system to quantify the relationship between different vacuum levels, gas components and damage parameters;

[0018] Construct a three-dimensional state diagram of temperature, pressure, and radiation to predict the change trajectory of the damage threshold under different environmental parameters;

[0019] Determine critical state identification parameters to determine the combination of environmental conditions that are most likely to cause damage.

[0020] As a preselection, the construction of the oxygen-silicon ratio-transmittance-damage threshold correlation model specifically includes:

[0021] A subsurface oxygen-to-silicon ratio gradient prediction model was established to predict the distribution of oxygen-to-silicon ratio from the surface to the subsurface.

[0022] Construct a microstructure-macro performance bridge system to correlate microscopic defects with macroscopic optical properties;

[0023] An advanced damage threshold prediction model is designed, and the prediction formula is:

[0024] ,

[0025] in, is the damage threshold after N pulses, is the single pulse damage threshold, N is the number of pulses, S is the transmittance parameter, f(T,P) is the temperature and pressure correction function, g(O:Si) is the oxygen-silicon ratio influence function, is the stress influence function.

[0026] As a preselection, the temperature and pressure correction function is expressed as:

[0027] ,

[0028] Where T is the actual temperature, is the reference temperature, P is the actual pressure, is the reference pressure, α and β are material-related constants.

[0029] As a preselection, the oxygen-silicon ratio influence function is expressed as:

[0030] ,

[0031] Wherein, O:Si is the oxygen-silicon ratio of the material, and γ is a material-related constant.

[0032] As a preselection, the stress influence function is expressed as:

[0033] ,

[0034] Where σ is the stress in the optical element, is the reference stress, and δ is a material-related constant.

[0035] As a preselection, the construction of the thermal-optical-mechanical multi-physics field coupling model specifically includes:

[0036] Establish a quantitative analysis framework for thermal accumulation effects to calculate multi-pulse temperature rise and critical thermal accumulation conditions;

[0037] Build phase transition critical point prediction technology to predict the critical conditions of local melting and evaporation of materials;

[0038] Develop time-space resolved thermal accumulation effect analysis technology to simulate the inter-pulse heat diffusion process.

[0039] As a pre-selection, the thermal accumulation effect quantitative analysis framework includes:

[0040] Single pulse temperature rise calculation: ,

[0041] Multi-pulse temperature rise calculation: ,

[0042] Critical heat accumulation condition judgment:

[0043] ,

[0044] in, is the absorbed energy, ρ is the material density, c is the specific heat capacity, V is the affected volume, is the number of characteristic pulses, N is the number of pulses, is the critical temperature rise.

[0045] As a pre-selection, also included:

[0046] Based on the damage threshold evolution trend curve, a multi-level early warning mechanism is established to judge the damage risk in a graded manner;

[0047] Design intelligent laser parameter adjustment strategies based on the current damage state to maximize the service life of optical components;

[0048] Build component-individualized characterization technology to provide customized usage recommendations for different optical components.

[0049] As a pre-selection, also included:

[0050] Establish an experimental verification and model calibration system, including:

[0051] Develop a hierarchical and progressive verification scheme, performing multi-level verification from micro parameters to macro performance;

[0052] Build an error analysis and calibration mechanism to identify sources of forecast errors and dynamically adjust model parameters;

[0053] Design a real-time feedback optimization system to continuously improve the accuracy of the prediction model through new experimental data.

[0054] The method provided by the present invention has the following beneficial effects:

[0055] 1. A damage prediction model based on physical parameters was established to achieve early prediction of damage evolution of optical components, reducing experimental cycles and improving evaluation efficiency;

[0056] 2. A multi-environment damage prediction model was constructed, expanding the scope of application of the prediction method to adapt to various environmental conditions from standard atmospheric pressure to high vacuum, and from low temperature to high temperature;

[0057] 3. A correlation model between oxygen-silicon ratio, transmittance, and damage threshold was established, revealing the correlation mechanism between microscopic physical parameters and macroscopic damage characteristics, thus improving the scientificity and accuracy of the prediction.

[0058] 4. A multi-physics coupling model of heat, light, and force was constructed, which comprehensively considered the interaction of various physical fields and provided a more in-depth analysis of the composite damage mechanism;

[0059] 5. A multi-level early warning mechanism and intelligent parameter adjustment strategy were designed to extend the service life of optical components and improve the reliability of the laser system. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 A flowchart of the method for predicting damage evolution of optical components based on laser irradiation provided by the present invention;

[0061] Figure 2 Schematic diagram of the structure of the multi-environment damage prediction model of the present invention;

[0062] Figure 3 This is a relationship diagram of the oxygen-silicon ratio-transmittance-damage threshold correlation model of the present invention;

[0063] Figure 4 A schematic diagram of the physical field interaction of the heat-light-force multi-physics field coupling model of the present invention;

[0064] Figure 5 This is a prediction curve diagram of the damage threshold according to the present invention as a function of the number of laser shots;

[0065] Figure 6 is a graph showing the relationship between transmittance and oxygen-silicon ratio;

[0066] Figure 7 is the fitting curve of the damage threshold changing with the laser firing times;

[0067] Figure 8 This is the relationship between the oxygen-silicon ratio and the number of laser shots;

[0068] Figure 9 is the linear relationship between the absorption coefficient and the oxygen-silicon ratio;

[0069] Figure 10 This is the correlation curve between damage threshold and absorption coefficient. DETAILED DESCRIPTION

[0070] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0071] Example 1

[0072] like Figures 1 to 10 As shown, the present invention provides a method for predicting the evolution of damage of an optical element based on laser irradiation, comprising the following steps:

[0073] First, obtain the physical parameters of the optical component and the laser irradiation parameters. Physical parameters include the oxygen-silicon ratio, transmittance, and absorption coefficient. These parameters can be measured experimentally or obtained from a material database. Laser irradiation parameters include wavelength, energy density, and repetition rate. These parameters are typically determined based on the actual application scenario.

[0074] Next, a laser irradiation damage evolution prediction model was established. This prediction model, the core of the present invention, comprises three key components: a multi-environment damage prediction model, an oxygen-silicon ratio-transmittance-damage threshold correlation model, and a thermal-optical-mechanical multi-physics coupling model. These three models describe the damage evolution mechanism of optical components from different perspectives, and together constitute a complete prediction system.

[0075] The established prediction model is then used to predict the evolution of the damage threshold of optical components after different laser irradiation times. The prediction results include a trend curve of the damage threshold as a function of the number of laser irradiation times and the critical damage point. This information is of great significance for assessing the service life and safety margin of optical components.

[0076] In practical applications, this prediction method can help researchers and engineers understand in advance the damage risk of optical components during use, take corresponding preventive measures, extend component life, and improve system reliability.

[0077] Example 2

[0078] like Figure 2 As shown, the construction of the multi-environment damage prediction model is to solve the problem of poor environmental adaptability in the existing technology, and can adapt to various environmental conditions from standard atmospheric pressure to high vacuum, from low temperature to high temperature.

[0079] The construction of this model first requires the establishment of an environmental parameter mapping system to quantify the relationship between different vacuum degrees, gas components and damage parameters. In actual implementation, we divide the vacuum degree into 10 -3 Pa to 10 -8 The Pa level is different, and the effect of the composition of residual gases (such as O2, N2, H2O, etc.) on the surface state of optical components is considered. For example, in a high vacuum environment, the reduction of residual moisture content will lead to a decrease in moisture adsorbed on the surface of optical components, which in turn affects their damage mechanism.

[0080] Secondly, a three-dimensional temperature-pressure-irradiation state diagram is constructed to predict the trajectory of damage threshold changes under different environmental parameters. This state diagram covers the three-dimensional parameter space of temperature (4K-500K), pressure (vacuum-standard atmospheric pressure), and laser irradiation (energy density, frequency), and can intuitively demonstrate the combined impact of environmental parameters on damage threshold. By interpolating and extrapolating parameters in this state diagram, damage evolution under untested environmental conditions can be predicted.

[0081] Furthermore, criticality identification parameters must be determined to identify the environmental conditions most likely to cause damage. These parameters, typically based on extensive experimental data and theoretical analysis, include critical temperature, critical pressure, and critical irradiation energy density. In practice, the system automatically identifies whether current environmental conditions are approaching a criticality based on these parameters and provides appropriate warnings.

[0082] Experiments have shown that damage mechanisms vary significantly under different environmental conditions. For example, in a vacuum environment, due to reduced heat conduction efficiency, the heat accumulation effect is more significant, resulting in a generally lower damage threshold than in a standard atmospheric pressure environment. This model allows these differences to be accurately quantified and predicted.

[0083] Example 3

[0084] like Figure 3 As shown in the figure, the oxygen-silicon ratio-transmittance-damage threshold correlation model is constructed to reveal the correlation mechanism between microscopic physical parameters and macroscopic damage characteristics, and to improve the scientificity and accuracy of the prediction.

[0085] First, a subsurface oxygen-to-silicon ratio gradient prediction model was developed to predict the distribution of oxygen-to-silicon ratio from the surface to the subsurface. Through experiments and theoretical calculations, we found that laser irradiation causes the oxygen-to-silicon ratio on the fused quartz surface to change, forming a gradient distribution from the surface to the subsurface (depth of 0-500nm). The model can predict the evolution of this gradient distribution based on laser irradiation parameters (such as wavelength, energy density, and frequency).

[0086] Secondly, a microstructure-macro performance bridge system is constructed to link micro defects with macro optical properties. This system calculates the defect formation energy based on density functional theory, predicts the generation probability of different defect types (such as ODCs, NBOHCs, etc.), and establishes a quantitative relationship model between defect density and absorption coefficient. In this way, the evolution of micro defects can be linked to changes in macro optical properties, providing a theoretical basis for damage prediction. Multi-pulse laser damage is considered to be a heat accumulation process. In addition, an advanced damage threshold prediction model is designed to predict the damage threshold under different conditions. The model is expressed as:

[0087] ,

[0088] In the formula Is the single-pulse laser damage threshold. In a vacuum environment, the single-pulse laser damage threshold of fused quartz corresponding to a 50% damage probability is J1=22.0J / cm 2 N is the number of pulses, is the laser damage threshold after N pulses, S is the transmittance of the material, f(T,P) is the temperature and pressure correction function, g(O;Si) is the oxygen-silicon ratio influence function, is the stress influence function.

[0089] The temperature and pressure correction function is expressed as:

[0090] ,

[0091] Where T is the actual temperature, is the reference temperature,

[0092] P is the actual pressure, is the reference pressure, and is a material-related constant. For fused silica, the typical value is .

[0093] The oxygen-silicon ratio influence function is expressed as:

[0094] ,

[0095] Where O:Si is the oxygen-silicon ratio of the material, and γ is a material-related constant. For fused silica, a typical value is Y=0.3.

[0096] The stress influence function is expressed as:

[0097] ,

[0098] in, is the stress in the optical element, is the reference stress, is a material-dependent constant. For fused silica, a typical value is .

[0099] After N laser irradiations, the heat accumulation process of fused quartz is reflected in the factor Ignoring the reflection process temporarily, the laser passing through fused silica will not cause heat accumulation in the material. The changes in the material structure and properties at the damage point are caused by the energy absorbed by the material. Therefore, the factor The S in has the physical meaning of material transmittance.

[0100] The absorption coefficient changes with the number of times it is emitted. The relationship between the transmittance and absorption coefficient of the material after different times of emission can be derived through the Beer-Lambert law.

[0101] ,

[0102] in is the incident laser intensity, is the laser intensity transmitted through the medium, is the absorption coefficient, is the distance the laser travels in the medium. Defined as transmittance, the expression can be obtained:

[0103] ,

[0104] The formula can finally be expressed as:

[0105] ,

[0106] The obtained results were processed and fitted data graphs were drawn. The relationship between several parameters was obtained. The data processing procedure is as follows: According to the existing experimental results, at a wavelength of 355nm and an energy density of 4J / cm 2 After 30 laser irradiations, the damage threshold of fused silica was determined to be 17.82 J / cm 2 Calculated using the formula, the parameter S is 0.938. The transmittance of fused quartz under a single pulse of 355nm laser light is 0.975, indicating that after 30 irradiations, the transmittance of fused quartz decreases to 0.938, a reasonable result. Furthermore, the above formula can be used to determine the transmittance and damage threshold at different irradiation times, providing a reasonable assessment of damage growth in fused quartz.

[0107] Through the above model, the damage threshold evolution of optical components under different conditions can be accurately predicted, providing a scientific basis for component service life assessment.

[0108] like Figure 6As shown, there is a clear linear relationship between transmittance (S) and the oxygen-silicon ratio (O:Si). When the O:Si ratio is 2.0, the transmittance reaches a maximum of 0.975; as the O:Si ratio decreases, the transmittance decreases accordingly. Experimental data shows that when the O:Si ratio decreases from 2.0 to 1.4, the transmittance decreases from 0.975 to approximately 0.933, a change that corresponds to a change in the material's microstructure.

[0109] like Figure 7 As shown, the damage threshold decreases with increasing laser bursts, exhibiting a nonlinear attenuation trend. The single-pulse damage threshold is 22.0 J / cm², decreasing to 16.3 J / cm² after 100 bursts, further decreasing to 13.9 J / cm² after 1000 bursts, and stabilizing at approximately 12.9 J / cm² after 3000 bursts. Curve fitting using the prediction formula proposed in this paper shows a high degree of agreement with experimental data, demonstrating the effectiveness of the model.

[0110] like Figure 8 As shown in the figure, the oxygen-to-silicon ratio decreases with increasing laser irradiation. The change is rapid within the first 100 irradiations, dropping rapidly from an initial value of 2.0 to approximately 1.435. The rate of change then slows, stabilizing at approximately 1.409 around 3000 irradiations. This change reflects the structural changes in the material caused by laser irradiation.

[0111] like Figure 9 As shown, the absorption coefficient and the oxygen-to-silicon ratio exhibit a good linear relationship. The fitting equation for the two is y = -2893.48x + 6524.10, with a correlation coefficient R² = 0.9724, indicating that the absorption coefficient increases with decreasing oxygen-to-silicon ratio. This relationship provides an important basis for predicting damage threshold.

[0112] like Figure 10 As shown, there is a clear negative correlation between the damage threshold and the absorption coefficient. As the absorption coefficient increases, the damage threshold decreases, and the relationship between the two can be fitted with a power function. This relationship reveals the mechanism by which material absorption properties influence the damage threshold.

[0113] Example 4

[0114] like Figure 4 As shown in the figure, the construction of the thermal-optical-mechanical multi-physics field coupling model is to comprehensively consider the interaction of various physical fields and to analyze the composite damage mechanism more deeply.

[0115] First, a quantitative analysis framework for thermal accumulation effects is established to calculate the temperature rise and critical heat accumulation conditions in multiple pulses. This framework includes the following key calculations:

[0116] Single pulse temperature rise calculation: ,

[0117] Multi-pulse temperature rise calculation: ,

[0118] Critical heat accumulation condition judgment:

[0119] ,

[0120] in, is the absorbed energy, ρ is the material density, c is the specific heat capacity, V is the affected volume, is the number of characteristic pulses, N is the number of pulses, is the critical temperature rise.

[0121] Characteristic pulse number Expressed as the ratio of the cooling time constant to the pulse interval:

[0122] ,

[0123] in, is the cooling time constant, is the pulse interval.

[0124] Secondly, a phase transition critical point prediction technology was developed to predict the critical conditions for local melting and evaporation of materials. This technology, based on thermodynamic principles, takes into account the phase transition characteristics of materials under different environmental conditions. For example, in a vacuum environment, the evaporation temperature of a material decreases, and the corresponding critical conditions also change. By establishing a mapping relationship between environmental conditions and phase transition critical points, the critical damage state under different environments can be accurately predicted.

[0125] Furthermore, a time- and space-resolved heat accumulation analysis technique has been developed to simulate the inter-pulse heat diffusion process. This technique, using finite element analysis, takes into account the thermal conductivity characteristics of the material, the geometric structure, and boundary conditions. It accurately simulates the spatial and temporal distribution and evolution of heat after each pulse. This analysis is crucial for understanding the formation and evolution of local hotspots during heat accumulation.

[0126] In practical applications, these three components work together to form a complete thermal-optical-mechanical multi-physics field coupling analysis system, which can comprehensively describe the complex physical processes inside optical components under laser irradiation and provide a solid theoretical basis for damage prediction.

[0127] Example 5

[0128] like Figure 6 As shown, based on the damage threshold evolution trend curve, a multi-level early warning mechanism can be established to assess damage risk in a graded manner. This invention designs a four-level early warning mechanism based on risk level: attention, warning, danger, and emergency replacement. Each level has clear judgment criteria and treatment recommendations.

[0129] Caution level: Triggered when the damage threshold drops to 90% of the initial value. It is recommended to pay close attention to the component status.

[0130] Warning level: triggered when the damage threshold drops to 80% of the initial value. It is recommended to reduce the frequency of use or lower the laser energy.

[0131] Danger level: Triggered when the damage threshold drops to 70% of the initial value, it is recommended to prepare to replace the component;

[0132] Emergency Replacement Level: Triggered when the damage threshold drops to 60% of its initial value, the component must be replaced immediately to avoid system failure.

[0133] In conjunction with damage risk assessment, this invention also designs an intelligent laser parameter adjustment strategy based on the current damage state to maximize the service life of optical components. This strategy automatically adjusts laser operating parameters (such as energy density and repetition rate) based on predicted damage evolution trends, mitigating damage progression while maintaining system performance. For example, when an increased damage risk is detected, the system can appropriately reduce the laser repetition rate and increase the inter-pulse cooling time to mitigate the effects of heat buildup.

[0134] Furthermore, this invention incorporates individualized component characterization technology to provide customized usage recommendations for different optical components. This technology, based on hyperspectral imaging, maps component surface defects and creates a personalized digital profile of the component, documenting data from manufacturing, testing, and usage. This allows the system to provide personalized usage recommendations based on the characteristics of each component, further extending its lifespan.

[0135] Experiments have shown that this multi-level warning and intelligent adjustment significantly extends the lifespan of optical components. In typical applications, compared to traditional methods, this method can extend component lifespan by over 30%, significantly reducing system operating costs.

[0136] Example 6

[0137] To ensure the accuracy and reliability of the prediction model, the present invention establishes a complete experimental verification and model calibration system, including a hierarchical progressive verification scheme, an error analysis and calibration mechanism, and a real-time feedback optimization system.

[0138] The hierarchical progressive verification scheme conducts multi-level verification from micro parameters to macro performance, including four levels:

[0139] The first layer is micro-parameter verification, which verifies the prediction accuracy of micro-parameters such as oxygen-silicon ratio and defect density;

[0140] The second layer is mesoscopic parameter verification, which verifies the prediction accuracy of optical parameters such as absorption coefficient and transmittance;

[0141] The third layer is macro-performance verification, which verifies the prediction accuracy of macro-performance indicators such as damage threshold and life prediction;

[0142] The fourth layer is the full system prediction verification, which verifies the overall prediction effect of damage evolution under different environments and different laser parameters.

[0143] The error analysis and calibration mechanism is used to identify the source of prediction errors and dynamically adjust model parameters. This mechanism uses Bayesian methods to automatically optimize key parameters in the model based on the differences between experimental data and prediction results, such as the temperature and pressure correction function. and , Y in the oxygen-silicon ratio influence function, and Etc. In this way, the model can continuously improve itself and increase prediction accuracy.

[0144] The real-time feedback optimization system continuously improves the accuracy of the prediction model by adding new experimental data. The system utilizes an incremental learning algorithm, enabling the model to learn and improve from new data while retaining past knowledge. Furthermore, the system incorporates model evolution history analysis technology to evaluate the effectiveness of model improvements and ensure the correct direction of the model optimization process.

[0145] The experimental results show that through the above experimental verification and model calibration system, after multiple iterative optimizations of the prediction model of the present invention, the damage threshold prediction error is controlled within 5%, and the damage time prediction error is controlled within 10%, which meets the actual application requirements.

[0146] Example 7

[0147] To verify the effectiveness of our method, we predicted and validated damage evolution on fused silica window components using a high-power laser system. This system employed a 355nm UV laser with a 10ns pulse width, a 100Hz repetition rate, and a single-pulse energy density of 5J / cm².

[0148] First, the initial physical parameters of the fused silica window were obtained: an oxygen-silicon ratio of 2.0, a transmittance of 0.975, and an absorption coefficient of 740.4 cm⁻¹. Furthermore, a single-pulse damage threshold of 22.0 J / cm² was measured.

[0149] The prediction model developed by the present invention was then used to predict the evolution of the damage threshold in this window after different laser irradiation times. The prediction results showed that the damage threshold gradually decreased with increasing laser irradiation times: it dropped to 19.4 J / cm² after 10 shots, 16.3 J / cm² after 100 shots, 13.9 J / cm² after 1000 shots, and 12.9 J / cm² after 3000 shots.

[0150] The predicted trend in the oxygen-silicon ratio was also observed: it dropped to 1.579 after 10 rounds, 1.435 after 100 rounds, 1.411 after 1,000 rounds, and 1.409 after 3,000 rounds. This change reflects the structural changes in the material caused by laser irradiation.

[0151] To verify the accuracy of the predictions, we conducted actual laser irradiation experiments. The maximum error between the experimentally measured damage threshold and the predicted value was 4.3%, validating the high accuracy of the proposed method.

[0152] In addition, based on the prediction results, the system automatically generates usage recommendations for the window components: at around 2,000 rounds (approximately 5.5 hours of continuous operation), the system enters the warning level and recommends reducing the laser energy density to 4J / cm²; at around 4,500 rounds (approximately 12.5 hours of continuous operation), the system enters the danger level and recommends preparing to replace the window components.

[0153] In actual application, by following this suggestion, the average service life of the window components of the laser system was extended from the original 15 hours to 20 hours, an increase of 33.3%, which greatly reduced the system operating costs and verified the practical value of the method of the present invention.

[0154] Table 1 Physical parameters and damage threshold prediction results of fused silica window under different laser irradiation times

[0155]

[0156] Table 1 clearly shows that as the number of laser shots increases, the oxygen-to-silicon ratio gradually decreases, the transmittance decreases accordingly, the absorption coefficient increases, and the damage threshold decreases. These data strongly verify the accuracy of the prediction model presented in this paper. The maximum error between the predicted results and the experimental measurements is 4.3%, demonstrating the good applicability and reliability of this method.

[0157] These tabular data are also Figure 6-10 The data source is used to comprehensively demonstrate the relationship between the evolution of physical parameters of optical components and the damage threshold through a combination of tables and graphs.

[0158] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for predicting damage evolution of optical components based on laser irradiation, characterized in that: include: Acquiring physical parameters and laser irradiation parameters of the optical element, wherein the physical parameters include oxygen-silicon ratio, transmittance, and absorption coefficient, and the laser irradiation parameters include wavelength, energy density, and repetition frequency; Establish a prediction model for laser irradiation damage evolution, including: Based on the physical parameters and laser irradiation parameters, constructing a multi-environment damage prediction model, wherein the multi-environment damage prediction model includes a mapping relationship between environmental parameters and damage thresholds; Based on the physical parameters, an oxygen-silicon ratio-transmittance-damage threshold correlation model is constructed, wherein the correlation model characterizes the evolution relationship of the physical parameters with the number of laser shots; Based on the laser irradiation parameters, a heat-light-force multi-physics field coupling model is constructed, wherein the coupling model characterizes the damage mechanism under the interaction of multiple physical fields; Using the multi-environment damage prediction model, the correlation model, and the coupling model, the damage threshold evolution of the optical element after different laser irradiation times is predicted, and the prediction results include a trend curve of the damage threshold changing with the number of laser irradiations and a critical damage point; The construction of the oxygen-silicon ratio-transmittance-damage threshold correlation model specifically includes: A subsurface oxygen-to-silicon ratio gradient prediction model was established to predict the distribution of oxygen-to-silicon ratio from the surface to the subsurface. Construct a microstructure-macro performance bridge system to correlate microscopic defects with macroscopic optical properties; An advanced damage threshold prediction model is designed, and the prediction formula is: ， in, is the damage threshold after N pulses, is the single pulse damage threshold, N is the number of pulses, S is the transmittance parameter, f(T,P) is the temperature and pressure correction function, g(O:Si) is the oxygen-silicon ratio influence function, and h(σ) is the stress influence function; The temperature and pressure correction function is expressed as: ， Where T is the actual temperature, is the reference temperature, P is the actual pressure, is the reference pressure, α and β are material-related constants; The oxygen-silicon ratio influence function is expressed as: ， Wherein, O:Si is the oxygen-silicon ratio of the material, and γ is a material-related constant; The stress influence function is expressed as: ， Where σ is the stress in the optical element, is the reference stress, and δ is a material-related constant.

2. The method according to claim 1, characterized in that The construction of the multi-environment damage prediction model specifically includes: Establish an environmental parameter mapping system to quantify the relationship between different vacuum levels, gas components and damage parameters; Construct a three-dimensional state diagram of temperature, pressure, and radiation to predict the change trajectory of the damage threshold under different environmental parameters; Determine critical state identification parameters to determine the combination of environmental conditions that are most likely to cause damage.

3. The method according to claim 1, characterized in that The construction of the heat-light-force multi-physics field coupling model specifically includes: Establish a quantitative analysis framework for thermal accumulation effects to calculate multi-pulse temperature rise and critical thermal accumulation conditions; Construct a phase transition critical point prediction model to predict the critical conditions of local melting and evaporation of materials; A time-space resolved thermal accumulation effect analysis model was developed to simulate the inter-pulse heat diffusion process.

4. The method according to claim 3, characterized in that The quantitative analysis framework of thermal accumulation effect includes: Single pulse temperature rise calculation: , Calculation of temperature rise in multiple pulses: , Critical heat accumulation condition judgment: ， in, is the absorbed energy, ρ is the material density, c is the specific heat capacity, V is the affected volume, is the number of characteristic pulses, N is the number of pulses, is the critical temperature rise.

5. The method according to claim 1, wherein Also includes: Based on the damage threshold evolution trend curve, a multi-level early warning mechanism is established to judge the damage risk in a graded manner; Design an intelligent adjustment strategy for laser parameters based on the current damage status to maximize the service life of optical components.

6. The method according to claim 1, characterized in that Also includes: Establish an experimental verification and model calibration system, including: Develop a hierarchical and progressive verification scheme, performing multi-level verification from micro parameters to macro performance; Build an error analysis and calibration mechanism to identify sources of forecast errors and dynamically adjust model parameters; Design a real-time feedback optimization system to continuously improve the accuracy of the prediction model through new experimental data.

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