Multi-physics coupling modeling method based on nanosecond laser etching microgroove resistance reduction simulation

Abstract

The invention discloses a multi-physics coupling modeling method based on nanosecond laser etching microgroove resistance reduction simulation, relates to the technical field of laser processing, and is used for solving the problem of optimization of a microgroove resistance reduction effect in a laser etching process. According to the method, the drag reduction effect of the microgroove in the laser etching process is simulated by establishing a coupling model of a plurality of physical fields such as heat transfer, fluid dynamics and material removal. Specifically, an adaptive grid technology is adopted to accurately calculate a temperature field and a flow field in an etching process, and meanwhile, a pulse laser equivalent processing method is introduced to model influences of different scanning times and laser power, so that etching process parameters are optimized. According to the method, the drag reduction effect under different parameters can be efficiently predicted, a theoretical basis is provided for microgroove design and laser etching process optimization, and the method has a wide application prospect.

Description

Technical Field

[0001] The present invention relates to the field of laser processing technology, and more specifically, to a multi-physical field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation. Background Art

[0002] Nanosecond pulsed lasers are widely used in material microstructure processing and surface modification of processed materials. Due to its instantaneous high peak energy characteristics, it can effectively remove the surface of the material being processed. However, in finite element modeling and simulation, the intermittent heating characteristics of pulsed lasers increase the computational complexity. In order to simplify the calculation, it is usually used to simulate its heating behavior by equivalent pulsed lasers to continuous laser sources. Although this method effectively improves the computational efficiency, it will introduce new errors in the equivalent process, affecting the subsequent processing accuracy.

[0003] Therefore, how to optimize the scanning process and prevent overheating damage caused by heat accumulation without sacrificing processing accuracy and efficiency has become a technical problem that needs to be solved in efficient and stable laser processing.

[0004] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention are based on a multi-physics field coupling modeling method for nanosecond laser etching microgroove drag reduction simulation to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] In a preferred embodiment, it comprises:

[0008] Step 1: Establish a multi-physics finite element model;

[0009] Step 2: By treating the pulsed laser as a continuous laser source, the prediction model is corrected in combination with the scanning data;

[0010] Step 3: Construct a computational domain model and perform fluid simulation to analyze the drag reduction effect of microgrooves;

[0011] Step 4: Conduct laser etching and wind tunnel tests to verify and calibrate the model.

[0012] In a preferred embodiment, in step 1, the control equation is established, the geometric model is created, and the control equation is applied to COMSOL, the physical field is set, and the numerical calculation model is constructed; finally, the interaction between the laser and the material and the microgroove formation process are simulated.

[0013] In a preferred embodiment, in step 2, the pulse laser is equivalent to a continuous laser source, and instant response data is collected during the first scan to quantify and remove the depth error, heat-affected zone size error and surface roughness error of the processed material generated after the pulse laser is equivalent to a continuous laser; based on the feedback of the material removal efficiency and heat accumulation after the error is removed, the final number of scans is corrected and determined.

[0014] In a preferred embodiment, a numerical simulation method for microgroove drag reduction is determined, and the control equation to be solved is determined through the physical phenomena occurring at the cruising speed of a small aircraft, and a turbulence model is introduced to close the control equation.

[0015] In a preferred embodiment, the simulated microgroove structure is imported into COMSOL, and the calculation domain boundary is defined, the height of the first layer of the boundary layer grid is adjusted, and a reliable microgroove drag reduction model is established; the interaction between the fluid and the microgroove is considered, the flow field characteristics are simulated, and the pressure and velocity distribution on the microgroove surface are obtained.

[0016] In a preferred embodiment, the width, depth, and surface smoothness parameters of the microgroove are obtained by laser etching; the pressure and velocity data at different positions of the microgroove are obtained by wind tunnel testing, and the friction coefficient and drag reduction rate are calculated based on the pressure and velocity data at different positions of the microgroove.

[0017] In a preferred embodiment, the laser etching and wind tunnel tests are repeated multiple times, the friction coefficient and drag reduction rate under different experimental conditions are recorded, the differences are found and the model parameters are adjusted.

[0018] In a preferred embodiment, the timely response data includes the following:

[0019] Initial scanning depth ΔD1: used to record the actual depth of material removal;

[0020] Heat affected zone size HAZ: measures the size of the heat affected zone of the material after the initial scan;

[0021] Processed material surface temperature feedback: record the processed material surface temperature after the initial scan;

[0022] Surface roughness and topography of processed materials: Measure the surface roughness and topography of the processed materials after the initial scan.

[0023] In a preferred embodiment, the material removal efficiency is obtained as follows:

[0024] The material removal efficiency correction formula is: N adjusted =N predicted ×(1-c·E removal )

[0025] In the formula, Eremoval is the material removal efficiency, and c is the correction factor.

[0026] In a preferred embodiment, the heat accumulation feedback is obtained as follows:

[0027] The heat accumulation feedback correction formula is:

[0028] Where, T current is the current surface temperature, T limit is the thermal damage threshold temperature.

[0029] The present invention discloses a multi-physical field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation, which relates to the field of laser processing technology and is used to solve the optimization problem of microgroove drag reduction effect during laser etching; the method simulates the drag reduction effect of microgroove during laser etching by establishing a coupling model of multiple physical fields such as heat transfer, fluid dynamics, and material removal. Specifically, adaptive grid technology is used to accurately calculate the temperature field and flow field during the etching process, and a pulsed laser equivalent processing method is introduced to model the influence of different scanning times and laser power to optimize the etching process parameters. This method can efficiently predict the drag reduction effect under different parameters, provide a theoretical basis for microgroove design and laser etching process optimization, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 This is a flow chart of the multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] Example

[0033] The present invention discloses a multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation, such as Figure 1 As shown, including:

[0034] Step 1: Establish a multi-physics finite element model;

[0035] First, starting from laser physics, thermodynamics, and fluid mechanics, the control equations are established in turn according to heat transfer, phase change, and dynamics during the processing, as follows:

[0036] The energy conservation equation describing the temperature change during laser heating is:

[0037]

[0038] Among them, ρ represents the density of molten metal, Cp represents specific heat capacity, T represents temperature, t represents time, and k represents thermal conductivity. represents the direction of heat flow, and Q represents the laser energy input;

[0039] It should be noted that Q is determined by the laser power density, and is specifically obtained according to the formula:

[0040]

[0041] Where P represents the laser power, r represents the radial distance from a point on the material surface to the center of the laser beam, and w 0 represents the spot radius, and η represents the absorption rate of the material to the laser;

[0042] The mass conservation equation that describes the rate at which material is removed during laser etching is:

[0043]

[0044] Where v represents the flow rate of molten metal, and S represents the material loss caused by laser ablation;

[0045] It should be noted that S is determined by the vaporization rate of the material, and is specifically obtained according to the formula:

[0046] S=ρv ablation

[0047] Among them, v ablation Indicates the vaporization rate of the material;

[0048] The momentum conservation equation describing the motion of molten metal in the microgroove is:

[0049]

[0050] Among them, μ represents the internal friction of the molten metal, p represents the pressure of the fluid, and F represents external forces such as steam recoil and surface tension;

[0051] It should be noted that the acquisition of factors such as density, temperature, flow rate and material loss data in the present invention is based on conventional selection in the prior art and will not be elaborated here.

[0052] Furthermore, taking a cuboid as the basic geometric shape, 7075 aluminum alloy was selected, and its thermal conductivity, density, specific heat capacity, melting point, vaporization temperature and other parameters were set to create a geometric model. The control equation was applied to the COMSOL module, the physical field was set, and the numerical calculation model was constructed, as follows:

[0053] Thermal field: apply laser heat source; set environmental heat exchange conditions; set phase change temperature;

[0054] Fluid fields: calculate the motion of molten metal; set surface tension and steam recoil forces;

[0055] Solid mechanics fields: calculation of thermal stresses;

[0056] Afterwards, the mesh is optimized using adaptive meshing technology to improve the simulation accuracy of the laser etching area. For example, ultra-fine meshes are used in the laser etching area, and coarser meshes are used in areas far away from the etching area. The level set method is used to accurately simulate the interaction between the laser and the material and the microgroove formation process, according to the formula:

[0057]

[0058] Among them, φ represents the interface position, γ represents the interface diffusion coefficient;

[0059] Step 2: By treating the pulsed laser as a continuous laser source, the prediction model is corrected in combination with the initial scanning data;

[0060] Since the intermittent heating characteristics of pulsed lasers will bring about complex transient heat conduction and increase the computational complexity. Therefore, the present invention equates pulsed lasers to continuous laser sources, simplifies the simulation process of pulsed lasers, reduces the computational time in finite element simulation, and performs simulation and optimization of multiple scans. Equivalent processing can maintain good simulation accuracy under most processing conditions and provide reasonable energy distribution and heat accumulation prediction.

[0061] The equivalent heat source is defined as follows:

[0062]

[0063] In the formula, t period =1 / f is the pulse period.

[0064] The present invention collects data during the initial scan, collects the material's immediate response data through a short-term laser action, and uses it as the initial scan feedback state, which is used as a reference for predicting the number of scans. The main collected data include:

[0065] Initial scanning depth ΔD1: used to record the actual depth of material removal;

[0066] Heat Affected Zone Size (HAZ): Measures the size of the heat affected zone of the material after the initial scan;

[0067] Processed material surface temperature feedback: record the processed material surface temperature after the initial scan;

[0068] Surface roughness and topography of processed materials: Measure the surface roughness and topography of the processed materials after the initial scan.

[0069] Since the laser equivalent process may bring errors in material removal depth and heat accumulation, the error introduced by the pulse laser equivalent to the continuous laser in the present invention is quantified by the following parameters to correct the predicted value of the number of scans:

[0070] Material removal depth error:

[0071] In the formula, and Represent the removal depths under pulsed laser and continuous laser conditions, respectively.

[0072] Heat affected zone size error: ΔHAZ equiv =|ΔHAZ pulse -ΔHAZ continuous |;

[0073] Where, ΔHAZ pulse and ΔHAZ continuous They represent the size of heat affected zone of pulse laser and continuous laser respectively;

[0074] Surface roughness error of processed material: ΔR equiv =|ΔR pulse -R continuous |;

[0075] In the formula, ΔR pulse and R continuous Respectively represent the surface roughness of the processed materials by pulse laser and continuous laser.

[0076] The present invention ensures the accuracy of the model by quantifying the error source after the pulse laser is converted into a continuous laser source, and effectively compensates for the influence of the equivalence error on the processing accuracy by comprehensive analysis of the removal depth error, the heat-affected zone size error and the surface roughness error of the processed material. It provides a correction factor for the subsequent prediction of the number of scans and improves the processing accuracy of the final result.

[0077] The scan number prediction model of the present invention is:

[0078]

[0079] Where D target The target depth is pre-set by the processing requirements and is used to determine the required total removal depth. The basic number of scans is calculated based on the removal depth of the initial scan. target The target heat affected zone size is set by the process requirements and is used to evaluate the impact of heat accumulation on subsequent scans in combination with the equivalent error to ensure that the heat affected zone size is within the target range.target The target surface roughness of the processed material is pre-set according to the processing requirements and quality standards. It is used to control the final surface roughness of the processed material in combination with the surface roughness error of the processed material to reduce the unevenness of the processed material surface caused by the error. equiv In order to remove the depth error, the removal depth of pulsed laser and equivalent continuous laser is compared to quantify the equivalence error, which is used to compensate for the deviation of the removal depth in the equivalent process, ΔHAZ equiv The error in the size of the heat affected zone is calculated by comparing the size difference of the HAZ between the pulsed laser and the continuous laser through simulation or experiment, and quantifying the equivalence error. This error is used to adjust the number of scans in combination with the target range of the HAZ to control heat accumulation and prevent material damage caused by excessive temperature. equiv The surface roughness error of the processed material is quantified by comparing the surface roughness of the processed material processed by pulse laser and continuous laser, and used to correct the number of scans to ensure that the surface of the processed material reaches the required roughness standard. k1, k2, and k3 are the weight coefficients of the removal depth error, the heat-affected zone size error, and the surface roughness error of the processed material, respectively. They are set according to the actual situation, so as to adjust the influence of each equivalent error in the prediction of the number of scans by weighted adjustment to ensure that the processing effect meets the actual needs.

[0080] Therefore, the predicted number of scans can be adjusted according to the removal efficiency and heat accumulation, optimizing the thermal control during the processing and reducing the thermal damage caused by multiple scans. The dynamic adjustment ensures the consistency of the processing effect and can be fine-tuned according to the actual situation to improve the adaptability of the prediction model.

[0081] At the same time, during the scanning process, the number of scans is further corrected according to the material removal efficiency and heat accumulation feedback, and the final number of scans N is determined. final It is used for initial processing settings and dynamically adjusted during subsequent processing to ensure that the processing depth and topography meet expectations.

[0082] Among them, the material removal efficiency correction formula is: N adjusted =N predicted ×(1-c·E removal );where E removal is the material removal efficiency, which is the average material removal depth in each scan. The higher the removal efficiency, the more depth is removed in each scan, so the total number of scans required can be reduced; c is the correction factor, which indicates the degree of influence of the removal efficiency on the total number of scans, which is determined based on experiments or processing experience. It is used to quantify the influence of material removal efficiency on the final number of scans.

[0083] The heat accumulation feedback correction formula is: Where, T currentis the current surface temperature, indicating the surface temperature of the material at the current scanning stage. If the temperature is high, it means that the material has a lot of heat accumulation and the number of scans needs to be reduced; T limit The thermal damage threshold temperature refers to the maximum temperature that the material can withstand during processing. Exceeding this temperature may cause damage to the material surface or structure.

[0084] After the initial scan times are determined by the comprehensive prediction model, further dynamic adjustments can be made during the processing based on real-time feedback, making the processing process more adaptable. The dynamic adjustment mechanism reduces the trial and error process of laser processing, improves processing efficiency while ensuring quality, helps reduce processing costs and improves the industrial applicability of laser processing.

[0085] The final number of scans ensures the processing depth and topography accuracy, and is dynamically adjusted during actual processing to further optimize the processing effect. While ensuring the processing results, the efficiency of laser processing is improved, minimizing the processing time while meeting the processing quality.

[0086] The present invention can maintain the uniformity of morphology in multi-layer scanning and gradually meet the requirements of processing depth and morphology through reasonable setting of scanning times and energy control.

[0087] Specifically, the heat source distribution for each scan is as follows:

[0088] In the formula, is the basic heat source for a single scan, g i (t) controls the laser switch state of each scan, and n is the current scan number.

[0089] Step 3: Construct a computational domain model and perform fluid simulation to analyze the drag reduction effect of microgrooves.

[0090] The current numerical simulation methods for microgroove drag reduction mainly include:

[0091] Direct numerical simulation: It can analyze all scales of turbulence and has the highest accuracy, but it is extremely computationally intensive and is not suitable for engineering applications.

[0092] Large eddy simulation: Use sub-grid scale models to deal with small-scale turbulence, suitable for detailed analysis of turbulent flow fields;

[0093] Reynolds-averaged Navier-Stokes method: It uses closed control equations of turbulence model, is suitable for microscale simulation, has high computational efficiency, and is suitable for engineering optimization design;

[0094] The present invention adopts the Reynolds average Navier-Stokes method suitable for micro-scale simulation, high computational efficiency, and suitable for engineering optimization design for simulation analysis. At the same time, considering that when the cruising speed of a small aircraft is Ma=0.2-0.3, the fluid is in a low-speed incompressible flow state, dominated by turbulence, so the incompressible Reynolds average Navier-Stokes equation is used. The standard k-ωSST turbulence model suitable for accurate prediction of wall turbulence characteristics is used for closure;

[0095] Specifically, the incompressible Reynolds-averaged Navier-Stokes equations are as follows:

[0096] Continuity equation:

[0097] Momentum equation:

[0098] Where u represents the average velocity component of the fluid, represents the Reynolds stress term and needs to be closed using the turbulence model.

[0099] Then, the microgroove structure obtained by the above simulation is imported into COMSOL without extracting cross-sectional features. In order to save computing resources, the computational domain boundary is defined:

[0100] Inlet boundary: Set uniform inflow velocity U ∞ , ensuring that there is no interference when the fluid enters the computational domain;

[0101] Outlet boundary: Use zero gradient boundary conditions to ensure the fluid flows out naturally;

[0102] Wall boundary: The micro-groove surface is set to have no slip conditions to ensure accurate calculation of wall shear stress;

[0103] Symmetrical boundary: Symmetrical boundary conditions are set on both sides of the calculation domain to avoid unnecessary calculation errors.

[0104] Furthermore, in order to adapt to complex geometries and enhance turbulence resolution capabilities, unstructured tetrahedral meshes are used for the microgroove region and layered hexahedral meshes are used for the wall boundary layer;

[0105] At the same time, in order to ensure that the micro-groove area is in a completely turbulent state, the target y is first set + , and calculate the wall shear stress T w :

[0106]

[0107] Calculate the turbulent friction velocity u T :

[0108]

[0109] Calculate the first layer grid height Δy:

[0110]

[0111] Use y + =0.5-1.0 as the target, adjust the height of the first layer of grid in the boundary layer, ensure that the microgroove area is in a fully turbulent state, and establish a reliable microgroove drag reduction model.

[0112] Afterwards, enable the following physics modules in COMSOL:

[0113] Fluid flow module: calculates the velocity and pressure distribution of the fluid;

[0114] Solid Mechanics Module: Analyze the stress and deformation of the micro-groove wall;

[0115] Fluid-Structure Interaction Module: allows fluid and solid to interact;

[0116] Moving Mesh ALE Module: allows the mesh to be dynamically adjusted as the wall deforms;

[0117] Furthermore, the pressure and shear force of the fluid on the microgroove are calculated, and the solid mechanics equations are solved to calculate the deformation of the microgroove under the action of the fluid. After that, the flow field characteristics are simulated by the moving grid ALE module and fluid-solid coupling technology, and the incompressible Reynolds-averaged Navier-Stokes equations are used to solve the wall pressure P and the velocity component of the fluid-solid interface.

[0118] Step 4: Conduct laser etching and wind tunnel tests to verify and calibrate the model.

[0119] First, use metal or semiconductor materials as the etching substrate and a high-precision laser etcher, input parameters such as laser wavelength, power, scanning speed, etc., place the sample in the laser etcher, and perform the etching process.

[0120] Mount the laser-etched sample on the sample stage of the SEM or AFM, set the acceleration voltage of the scanning electron microscope, select the appropriate scanning mode, and use the secondary electron mode (SE) to obtain the morphological image of the microgroove; measure the width, depth, surface smoothness and other parameters of the microgroove, and record the deviation from the designed morphology;

[0121] Furthermore, the etched microgroove sample was installed on the wind tunnel test platform to ensure that its position was fixed and aligned with the fluid flow direction. Pressure sensors were installed at the inlet and outlet, groove wall and other positions of the microgroove to record the pressure data at different positions. A laser Doppler velocimeter was used to measure the velocity of the fluid in the microgroove, and the flow velocity at different positions in the microgroove was recorded.

[0122] Finally, by measuring the wall shear stress and combining it with the velocity distribution of the fluid, the friction coefficient is calculated, and the calculated friction coefficient is compared with the theoretical value or simulation results to analyze the error; the total resistance of the fluid in the microgroove is calculated and compared with the resistance when the microgroove is not used, the drag reduction effect of the microgroove design is verified, and the results are calibrated with the simulation predictions. At the same time, the laser etching and wind tunnel tests are repeated many times to record the data under different experimental conditions, compare the experimental data with the simulation results, find the differences and adjust the model parameters;

[0123] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0124] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0125] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0126] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0127] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0128] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation, characterized in that: include: Step 1: Establish a multi-physics finite element model; Step 2: By treating the pulsed laser as a continuous laser source, the prediction model is corrected in combination with the scanning data; Step 3: Construct a computational domain model and perform fluid simulation to analyze the drag reduction effect of microgrooves; Step 4: Conduct laser etching and wind tunnel tests to verify and calibrate the model.

2. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 1 is characterized in that: In step 1, the control equations are established, the geometric model is created, and the control equations are applied to COMSOL, the physical field is set, and the numerical calculation model is constructed; finally, the interaction between the laser and the material and the microgroove formation process are simulated.

3. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 2 is characterized in that: In step 2, the pulse laser is equivalent to a continuous laser source, and instant response data is collected during the first scan to quantify and remove the depth error, heat-affected zone size error, and surface roughness error of the processed material caused by the pulse laser being equivalent to a continuous laser. The final number of scans is corrected and determined based on the feedback of material removal efficiency and heat accumulation after the error is removed.

4. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 3, characterized in that; The numerical simulation method that can be used for micro-groove drag reduction is determined, and the control equations to be solved are determined through the physical phenomena occurring at the cruising speed of a small aircraft, and a turbulence model is introduced to make the control equations closed.

5. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 4 is characterized in that: The simulated microgroove structure is imported into COMSOL, and the calculation domain boundary is defined, the height of the first layer of grid in the boundary layer is adjusted, and a reliable microgroove drag reduction model is established; the interaction between the fluid and the microgroove is considered, the flow field characteristics are simulated, and the pressure and velocity distribution on the microgroove surface are obtained.

6. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 5 is characterized in that: The width, depth and surface smoothness parameters of the microgroove are obtained through laser etching. The pressure and velocity data at different positions of the microgroove are obtained through wind tunnel tests, and the friction coefficient and drag reduction rate are calculated based on the pressure and velocity data at different positions of the microgroove.

7. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 6 is characterized in that: Repeat the laser etching and wind tunnel tests many times, record the friction coefficient and drag reduction rate under different experimental conditions, find the differences and adjust the model parameters.

8. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 3 is characterized in that: Timely response data includes the following: Initial scanning depth ΔD1: used to record the actual depth of material removal; Heat affected zone size HAZ: measures the size of the heat affected zone of the material after the initial scan; Processed material surface temperature feedback: record the processed material surface temperature after the initial scan; Surface roughness and topography of processed materials: Measure the surface roughness and topography of the processed materials after the initial scan.

9. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 3, characterized in that: The material removal efficiency is obtained as follows: The material removal efficiency correction formula is: N adjusted =N predicted ×(1-c·E removal ) In the formula, E removal is the material removal efficiency, and c is the correction coefficient.

10. The multi-physics field coupling modeling method based on nanosecond laser etching microgroove drag reduction simulation according to claim 3, characterized in that: The thermal accumulation feedback is obtained as follows: The heat accumulation feedback correction formula is: Where, T current is the current surface temperature, T limit is the thermal damage threshold temperature.

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