Large light source engineering site selection technology based on constructing multi-physical coupling influence beam center offset estimation model

Abstract

Disclosed is a large light source type engineering site selection technology based on constructing a multi-physical coupling influence beam center offset estimation model, comprising: 1) using a portable device to perform rough measurement on the site; 2) determining a multi-physical field coupling influence matrix and performing threshold P i th (ω) screening; 3) performing hierarchical pre-judgment on the site; 4) performing secondary fine measurement on the Class A / Class B site; 5) based on step 4), constructing a five-dimensional coupling transfer function, calculating the predicted beam offset ΔX beam (ω); 6) generating a continuous offset distribution of the entire site by Kriging spatial interpolation method, then comparing the beam offset ΔX(ω) of each interpolation point with the threshold value; 7) performing targeted interpolation optimization design; 8) performing multi-physical coupling simulation; 9) based on the coupling simulation verification result and the measured data, using a dynamic weighting method to calculate, calculating the comprehensive score S of the site and determining the site grade according to the score.

Description

Technical Field

[0001] This invention relates to the field of large-scale precision equipment technology, and more specifically to a site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model. Background Technology

[0002] Large-scale precision instruments and equipment, such as large-scale light source projects, may face the influence of multiple physical fields, including geological vibrations, temperature fields, magnetic fields, vacuum fields, and hydrogeological fields, during system construction and operation. Furthermore, these large-scale precision instruments and equipment have high environmental requirements, making site selection crucial and potentially affecting the normal operation of the equipment. However, current methods for site selection of projects like large-scale light source projects are limited, and traditional site selection methods have some shortcomings, such as:

[0003] Isolated assessments of single physical fields can lead to distortions: Existing empirical site selection techniques only assess single physical fields such as ground vibration or foundation settlement, neglecting the vibration-thermal-magnetic coupling effect. For example, the synergistic effect of subway vibration and temperature changes was not considered in the early stages of the construction of a certain light source, resulting in a local track deviation of more than 50 nm in the storage ring, exceeding the design threshold by 45%.

[0004] Experience-driven threshold setting lacks feedback: Traditional methods rely on engineering experience to set allowable thresholds (e.g., vacuum degree ≤ 10). -9 The system lacks a particle beam stability feedback mechanism (mbar). The European XFEL previously had to invest an additional €12 million to upgrade its vacuum system after site selection because it failed to establish a quantitative model for vacuum level-beam lifetime.

[0005] Dynamic multi-field coupling weight allocation was not considered: Similar technologies use fixed weights to evaluate the site, without considering the dynamic coupling strength of the physical fields. Due to insufficient weight allocation for magnetic field interference, a certain experimental light source base encountered harmonic interference from the surrounding power grid during actual operation, resulting in a beam stability decrease of over 10%.

[0006] Therefore, new technologies are needed to at least partially overcome the shortcomings of existing technologies. Summary of the Invention

[0007] This invention aims to address the site selection challenges faced in the construction of large-scale advanced light source-type major scientific infrastructures or advanced industrial laboratories under the coupling effects of multiple physical fields, including geological vibration, temperature field, magnetic field, vacuum field, and hydrogeological field. It proposes a quantitative site selection process system. This system establishes a multi-physics field coupling influence matrix, defines particle beam stability tolerance thresholds (beam trajectory deviation ≤ 50 nm, magnet thermal deformation ΔT ≤ ±0.1℃ / 24h), constructs a collaborative constraint logic model to reveal the transmission path between physical fields and beam accuracy, and finally forms a quantitative grading evaluation model to achieve intelligent grading of site suitability.

[0008] More specifically, this invention provides a site selection technique for large-scale light source engineering projects based on constructing a multi-physics coupling influence beam center offset estimation model, including:

[0009] 1) Use portable equipment to conduct rough measurements of the site's geological vibration, temperature, magnetic field, vacuum, and settlement;

[0010] 2) Determine the multiphysics coupling influence matrix, whereby the multiphysics fields include vibration field, temperature field, magnetic field, vacuum field, and sedimentation field. Input the coarse measurement data from step 1) into the multiphysics coupling influence matrix and apply a threshold P. i th (ω) Screening;

[0011] 3) Based on the screening in step 2), the site area is classified and pre-judged according to the following criteria: if all physical field parameters are less than 50% of the threshold, it is classified as Class A; if any physical field parameter is greater than or equal to 80% of the threshold, it is classified as Class C; otherwise, it is classified as Class B. Among them, Class C is directly eliminated; Class A / Class B proceed to the next step.

[0012] 4) Deploy high-density sensor arrays in Class A / Class B areas to conduct secondary detailed measurements of vibration field, temperature field, magnetic field, vacuum field and settlement field, with continuous monitoring time ≥30 days;

[0013] 5) Based on step 4), construct a five-dimensional coupling transfer function and calculate the predicted beam offset:

[0014]

[0015] Where, ΔX beam (ω) is the frequency domain representation of the particle beam trajectory deviation; ω is the angular frequency; H i (ω) is the device transfer function for the i-th type of physical field; P i (ω) is the spectral density of the site perturbation power of the i-th type of physical field; Γ i (ω) is the beam offset coupling coefficient caused by the i-th type of physical field disturbance;

[0016] 6) Based on the discrete data of the measurement points obtained in step 4), i.e., the predicted beam offset, a continuous offset distribution for the entire Class A / Class B region is generated using the Kriging space interpolation method.

[0017] Then, the beam offset ΔX(ω) at each point is compared with the threshold 50nm. If ΔX(ω)≤50nm, proceed to step 9) to calculate the dynamic weighted score; if ΔX(ω)>50nm, proceed to step 7) for interpolation optimization design.

[0018] 7) For potential risk points or parameters exceeding thresholds exposed in the prediction, perform targeted interpolation optimization design in the Class A / Class B region, including:

[0019] Isothermal layer depth interpolation: Based on the thermal diffusion equation and spatial geological variability characteristics, the optimal isothermal layer depth is calculated by Kriging interpolation. The goal is to suppress temperature fluctuations to ≤±0.02℃ / 24h.

[0020] Vibration isolation base parameter interpolation: The base stiffness / damping parameters are inverted based on the vibration spectral density. The goal is to suppress the vibration transmissibility (TR) to ≤5%.

[0021] Magnetic shielding distance interpolation: Combining the geomagnetic gradient and frequency-varying attenuation model, radial basis function interpolation is used, with the goal of attenuating magnetic field interference to ≤0.5μT;

[0022] 8) Multiphysics Coupled Simulation: Input the measured data and interpolated optimized design parameters into high-fidelity multiphysics coupled simulation software to perform full-system, full-coupled numerical simulation and output detailed beam offset prediction results;

[0023] 9) Dynamic weighted scoring: Based on the coupled simulation verification results and measured data, the comprehensive score S of each point in the Class A / Class B region is calculated using a dynamic weighting method. The calculation formula is as follows;

[0024]

[0025] Among them, S i For the score of the i-th type of physical field, k i For each physical field coefficient, W is the threshold value of the power spectral density of the site perturbation of the i-th type of physical field. i These are the dynamic weights of each physical field, calculated as follows:

[0026]

[0027] Where, x ij This represents the measured value of the i-th physical field at the j-th measurement point; e represents the theoretical minimum value at the j-th measurement point; i Represents information entropy;

[0028] If S ≥ 85 points, it is classified as Grade A and can be constructed; if S is between 70 and 84 points, it is classified as Grade B and needs to be upgraded; if S < 70 points, it is classified as Grade C and should be eliminated.

[0029] According to the embodiments of the present invention, the site selection technology for large-scale light source projects based on the construction of a multi-physics coupling influence beam center offset estimation model also includes a customized debugging and optimization scheme for Class B generation to solve the problem of specific physical field exceeding the standard.

[0030] According to an embodiment of the present invention, the optimization judgment in the debugging and optimization scheme is based on the following three indicators:

[0031] Excessive vibration: Vibration velocity spectral density (PSD) in the 1-100Hz frequency band v >1nm2 / Hz

[0032] Temperature fluctuation: Daily temperature difference ΔT of the foundation > 0.05℃ / 24h

[0033] Magnetic disturbance: Earth's magnetic field fluctuation ΔB > 5nT.

[0034] According to an embodiment of the present invention, the optimization measures include a deeply buried vibration isolation base and a tuned mass damper (TMD) for excessive vibration, a constant temperature layer embedded base and a liquid nitrogen circulating temperature control system for temperature fluctuations, and an active compensation coil array and a permalloy magnetic shielding chamber for magnetic disturbances.

[0035] According to an embodiment of the present invention, in step 4), continuous monitoring is conducted for ≥30 days to capture typical interference events. Vibration data: heavy vehicle traffic, wind turbine start-up and shutdown, rainfall-induced ground pulsation; temperature data: day-night cycle, cold front passage, equipment trial operation heat dissipation; magnetic field data: power grid load switching, rail transit peak harmonics.

[0036] According to the embodiment of the present invention, step 1) further includes the exclusion of geological restricted areas, and the site is eliminated if any of the following conditions are triggered: active fault zone, less than 5km from the core area of ​​the site; underground karst cave / mining area, with a subsidence risk of >10mm / year; groundwater flow velocity >1m / day, with potential foundation erosion.

[0037] According to an embodiment of the present invention, the simulation software is COMSOL Multiphysics.

[0038] According to an embodiment of the present invention, the simulation in COMSOL Multiphysics includes constructing a field-structure-beam joint model:

[0039] Step 1: Import the optimization parameters and calculate the response of the building / foundation / vibration isolation system;

[0040] Step 2: Export the deformation field / temperature field / magnetic field distribution to the particle tracker;

[0041] Step 3: Iterate the simulation until the beam offset is less than the design value (e.g., 0.1 μm).

[0042] According to an embodiment of the present invention, in step 4), the deployed sensor array vibration monitoring network includes: a grid density of 50m×50m, a sensor type of three-component force balance accelerometer (frequency band 0.01-100Hz); a temperature monitoring chain: a drilling depth ≥30m, a vertical temperature measurement point spacing of no more than 1m, and a temperature accuracy of ±0.01℃; and a magnetic field monitoring array: a baseline length of 200m and a sampling rate of 1kHz.

[0043] According to an embodiment of the present invention, wherein each physical field threshold P i th The values ​​of (ω) are as follows: vibration field threshold 50nm (1-100Hz), temperature field threshold ±0.1℃ / 24h, magnetic field threshold 0.1μTRMS, vacuum field threshold vacuum fluctuation ≤5%, and settlement field threshold differential settlement ≤0.1mm / 10m.

[0044] The implementation scheme of this invention, based on the construction of a multi-physics coupling influence beam center offset estimation model, can achieve beneficial technical effects in the site selection technology of large-scale light source projects: by establishing a multi-physics coupling influence matrix, defining particle beam stability tolerance thresholds (including 5 physical field thresholds); constructing a collaborative constraint logic model to reveal the transmission path between physical fields and beam accuracy; and finally forming a quantitative hierarchical evaluation model, thereby realizing the prediction of multi-physics interference in the site selection stage, reducing the risk of particle beam trajectory deviation by >70%, shortening the engineering design cycle by 50% through a quantitative design standard library, reducing the risk of insufficient design functions in the later stage caused by the complexity of site selection, and improving the site selection accuracy to 95% by using the hierarchical evaluation model, which is conducive to supporting the integration of digital twin platforms to provide digital decision support for later operation and maintenance. Attached Figure Description

[0045] Figure 1 This is a flowchart illustrating the site selection technology for large-scale light source projects based on the construction of a multi-physics coupling influence beam center offset estimation model according to an embodiment of the present invention. Detailed Implementation

[0046] The present invention can be better understood from the accompanying drawings and the following embodiments. However, those skilled in the art will readily understand that the descriptions in the embodiments are for illustrative purposes only and should not, and will not, limit the scope of the invention.

[0047] Figure 1This is a flowchart illustrating the site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model according to an embodiment of the present invention. As shown in the figure, the site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model may include the following steps:

[0048] First, a preliminary site survey is conducted. Portable equipment can be used to perform preliminary measurements of the site's geological vibrations, temperature, magnetic field, vacuum, and settlement. For example, in geology: a handheld seismograph measures Vs30 (average shear wave velocity at 30m above the ground surface) to preliminarily determine soil stiffness; in vibration: a broadband seismometer records the 1-hour environmental vibration RMS value; in temperature: an infrared thermal imager scans the surface temperature distribution; in magnetic field: a triaxial magnetometer measures the background field strength (in μT). In this step, geological exclusion zones can also be identified by setting geological safety thresholds, which will eliminate the site if any condition is triggered: for example, active fault zones (<5km from the core area of ​​the site); underground karst caves / mining areas (settlement risk >10mm / year); groundwater flow velocity >1m / day (potential foundation erosion).

[0049] Then, the multiphysics coupling influence matrix is ​​determined, whereby the multiphysics fields include vibration field, temperature field, magnetic field, vacuum field, and sedimentation field. That is, a multiphysics coupling influence matrix is ​​established under the mapping relationship between physical field, equipment, and beam. The main contents include the influence of five physical fields, setting the physical field, the affected object, setting the single-field allowable threshold, and defining the interference source. For the stability of physical field indicators under typical interference sources, quantitative setting suggestions for the main control thresholds are given, as detailed in the table below.

[0050]

[0051] The coarse measurement data is input into the multiphysics coupling influence matrix to perform a threshold P. i th (ω) Screening. Based on the screening results, the site area is classified and pre-judged according to the following criteria: if all physical field parameters are less than 50% of the threshold, it is classified as Class A; if any physical field parameter is greater than or equal to 80% of the threshold, it is classified as Class C; otherwise, it is classified as Class B; among them, Class C is directly eliminated; Class A / Class B proceed to the next step.

[0052] A high-density sensor array was deployed in the Class A / Class B areas to conduct secondary detailed measurements of the vibration field, temperature field, magnetic field, vacuum field, and sedimentation field, with continuous monitoring time ≥30 days.

[0053] The sensor array may include, for example: a vibration monitoring network with a grid density of 50m × 50m, using three-component force-balanced accelerometers (frequency band 0.01-100Hz); a temperature monitoring chain with a borehole depth ≥30m (≥50m in bedrock areas), temperature measurement points spaced 1m apart vertically (0.5m near the surface), with an accuracy of ±0.01℃ (platinum resistance thermometer PT1000); and a magnetic field monitoring array with a baseline length of 200m (gradient measurement) and a sampling rate of 1kHz (capturing pulse interference). This allows for the capture of typical interference events, such as vibration data (heavy vehicle traffic, wind turbine start-up and shutdown, rainfall-induced ground pulsations), temperature data (day-night cycles, cold front passage, equipment trial operation heat dissipation), and magnetic field data (power grid load switching, rail transit peak harmonics).

[0054] Next, a five-dimensional coupling transfer function is constructed to calculate the predicted beam offset:

[0055]

[0056] Where, ΔX beam (ω) is the frequency domain representation of the particle beam trajectory deviation; ω is the angular frequency; H i (ω) is the device transfer function for the i-th type of physical field; P i (ω) is the spectral density of the site perturbation power of the i-th type of physical field; Γ i (ω) is the beam offset coupling coefficient caused by the i-th type of physical field disturbance.

[0057] Device transfer function H for various physical fields i (ω) can be calculated using known methods. For example, for a vibration field, the equipment transfer function is related to the equivalent stiffness, damping attenuation factor, equipment mass, damping coefficient, stiffness coefficient, etc., which will not be elaborated here. P i (ω) can be obtained by converting the time-domain data into a frequency-domain power spectrum, performing signal processing on the acquired raw data, and then performing a Fourier transform. Γ i (ω) can be obtained empirically, for example, by taking the average value of the key frequency band, such as for a vibration field, Γ i (ω) can take the value 1.2 x 10. -6 (i.e., a 1.2m beam shift caused by a 1mm equipment displacement), with a temperature field value of 0.8x10. -3 m / ℃ (i.e., a 1℃ temperature change causes a 0.8mm beam deflection), and the magnetic field value is 5.0x10. -3 m / uT (i.e., a 1uT change in magnetic field causes a 5mm beam shift), with a vacuum field value of 2.0x10. -2 m / Pa (i.e., a 2cm beam shift caused by a 1Pa pressure change), with the settling field value taken as 1.0x10. -3m / m (meaning 1m foundation settlement causes 1mm beam deflection; in reality, the settlement is very small, usually on the order of mm).

[0058] Based on the discrete data from the deployed measurement points, i.e., the aforementioned predicted beam offset ΔX beam (ω), the continuous offset distribution of the entire Class A / Class B region is generated by Kriging space interpolation (generating offset cloud map), and then the beam offset ΔX(ω) at each point is compared with the threshold 50nm. If ΔX(ω)≤50nm, the dynamic weighting score operation is calculated; if ΔX(ω)>50nm, the interpolation optimization design operation is performed.

[0059] For potential risks or parameters exceeding thresholds revealed in the predictions, targeted interpolation optimization designs are implemented in Class A / Class B sites. More specifically, the interpolation optimization design includes:

[0060] Isothermal layer depth interpolation: Based on the thermal diffusion equation and spatial geological variability characteristics, the optimal isothermal layer depth is calculated by Kriging interpolation. Objective: To suppress temperature fluctuations to ≤±0.02℃ / 24h; Function: To generate depth optimization solutions for different strata such as clay and sandstone (e.g., depth ≈8-10m in granite areas) and eliminate thermal deformation of concrete foundations.

[0061] Vibration isolation base parameter interpolation: The stiffness / damping parameters of the base are inverted based on the vibration spectral density. The goal is to suppress the vibration transmissibility (TR) to ≤5%. The function is to dynamically match the natural frequency of the equipment and block the resonance transmission path.

[0062] Magnetic shielding distance interpolation: Combining the geomagnetic gradient and frequency-varying attenuation model, radial basis function interpolation is used. Objective: Attenuate magnetic field interference to ≤0.5μT; Function: Generate optimized shielding distance values ​​(e.g., ≥420m for 110kV substations) to suppress the risk of superconducting magnet quenching.

[0063] Next, multiphysics coupling simulation is performed: Measured data and interpolated optimized design parameters are input into high-fidelity multiphysics coupling simulation software (such as COMSOL Multiphysics) to perform a full-system, fully coupled numerical simulation, outputting detailed beam migration prediction results. For example, constructing a field-structure-beam joint model in COMSOL Multiphysics includes the following steps:

[0064] Step 1: Import the optimization parameters and calculate the response of the building / foundation / vibration isolation system.

[0065] Step 2: Export the deformation field / temperature field / magnetic field distribution to the particle tracker (e.g., ELEGANT).

[0066] Step 3: Iterate through simulations until the beam offset is less than the design value (e.g., 0.1 μm).

[0067] Dynamic weighted scoring: Based on coupled simulation verification results and measured data, a dynamic weighted method is used to calculate the comprehensive score S of each point in the Class A / Class B region, specifically including:

[0068] The influence weights of physical fields are calculated using a dynamic weighting method, as shown in the following formula:

[0069]

[0070] Please refer to the table below for parameter descriptions:

[0071]

[0072] The weighting feature has an adaptive mechanism, that is, when the data of a certain physical field has a large dispersion (such as the vibration value fluctuating between 0.05 and 1 μm / s), its entropy value increases, which leads to an increase in weight.

[0073] Then, based on dynamic weighting, the influence of individual physical fields is comprehensively scored, and the standardized scoring function is as follows:

[0074]

[0075] Among them, S i For the score of the i-th type of physical field, k i P represents the coefficients of each physical field. i th (ω) is the threshold value of the power spectral density of the site disturbance of the i-th type of physical field, W i These are the dynamic weights of each physical field; see the table below for parameter descriptions:

[0076]

[0077] Finally, the level of each point in the Class A / Class B area is determined based on the score S: if S≥85, it is determined to be Class A and can be built; if S is between 70 and 84, it is determined to be Class B and needs to be modified; if S<70, it is determined to be Class C and is eliminated.

[0078] According to an embodiment of the present invention, the method may further include generating a customized debugging and optimization scheme for Class B to solve specific physical field exceedance problems. The debugging and optimization are based on the following three indicators:

[0079] Excessive vibration: When the vibration velocity spectral density PSDv in the 1-100Hz frequency band > 1nm² / Hz

[0080] Temperature fluctuation: Daily temperature difference ΔT of the foundation > 0.05℃ / 24h

[0081] Magnetic disturbance: Geomagnetic field fluctuation ΔB > 5nT

[0082] The optimization measures library is matched as shown in the table below:

[0083]

[0084] The embodiments of the present invention have been described above by way of example, but the present invention is not limited to the embodiments described above. The basic idea of ​​the present invention lies in the above basic scheme. For those skilled in the art, designing various modified models, formulas, and parameters based on the teachings of the present invention does not require creative effort. Changes, modifications, substitutions, and variations made to the embodiments without departing from the principles and spirit of the present invention still fall within the protection scope of the present invention.

Claims

1. A site selection technology for large-scale light source projects based on constructing a beam center offset estimation model for the effects of multi-physics coupling, characterized in that, include: 1) Use portable equipment to conduct rough measurements of the site's geological vibration, temperature, magnetic field, vacuum, and settlement; 2) Determine the multiphysics coupling influence matrix, whereby the multiphysics fields include vibration field, temperature field, magnetic field, vacuum field, and sedimentation field. Input the coarse measurement data from step 1) into the multiphysics coupling influence matrix and apply a threshold P. i th (ω) Screening; 3) Based on the screening in step 2), the site area is classified and pre-judged according to the following criteria: if all physical field parameters are less than 50% of the threshold, it is classified as Class A; if any physical field parameter is greater than or equal to 80% of the threshold, it is classified as Class C; otherwise, it is classified as Class B. Among them, Class C is directly eliminated; Class A / Class B proceed to the next step. 4) Deploy high-density sensor arrays in Class A / Class B areas to conduct secondary detailed measurements of vibration field, temperature field, magnetic field, vacuum field and settlement field, with continuous monitoring time ≥30 days; 5) Based on step 4), construct a five-dimensional coupling transfer function and calculate the predicted beam offset: Where, ΔX beam (ω) is the frequency domain representation of the particle beam trajectory deviation; ω is the angular frequency; H i (ω) is the device transfer function for the i-th type of physical field; P i (ω) is the spectral density of the site perturbation power of the i-th type of physical field; Γ i (ω) is the beam offset coupling coefficient caused by the i-th type of physical field disturbance; 6) Based on the discrete data of the measurement points obtained in step 5), i.e., the predicted beam offset, a continuous offset distribution for the entire Class A / Class B region is generated using Kriging space interpolation. Then the beam offset ΔX at each point beam (ω) is compared with the threshold of 50nm, if ΔX beam If (ω)≤50nm, proceed to step 9) to calculate the dynamic weighted score; if ΔX beam If (ω) > 50nm, then proceed to step 7) for interpolation optimization design; 7) For potential risk points or parameters exceeding thresholds exposed in the prediction, perform targeted interpolation optimization design in the Class A / Class B region, including: Isothermal layer depth interpolation: Based on the thermal diffusion equation and spatial geological variability characteristics, the optimal isothermal layer depth is calculated by Kriging interpolation. The goal is to suppress temperature fluctuations to ≤±0.02℃ / 24h. Vibration isolation base parameter interpolation: The base stiffness / damping parameters are inverted based on the vibration spectral density. The goal is to suppress the vibration transmissibility (TR) to ≤5%. Magnetic shielding distance interpolation: Combining the geomagnetic gradient and frequency-varying attenuation model, radial basis function interpolation is used, with the goal of attenuating magnetic field interference to ≤0.5μT; 8) Multiphysics Coupled Simulation: Input the measured data and interpolated optimized design parameters into high-fidelity multiphysics coupled simulation software to perform full-system, full-coupled numerical simulation and output detailed beam offset prediction results; 9) Dynamic weighted scoring: Based on the coupled simulation verification results and measured data, the dynamic weighted method is used to calculate the comprehensive score S of each point in the Class A / Class B region. The calculation formula is as follows; Among them, S i For the score of the i-th type of physical field, k i P represents the coefficients of each physical field. i th (ω) is the threshold value of the power spectral density of the site disturbance of the i-th type of physical field, W i These are the dynamic weights of each physical field, calculated as follows: Where, x ij This represents the measured value of the i-th physical field at the j-th measurement point; e represents the theoretical minimum value at the j-th measurement point; i Represents information entropy; If S ≥ 85 points, it is classified as Grade A and can be constructed; if S is between 70 and 84 points, it is classified as Grade B and needs to be upgraded; if S < 70 points, it is classified as Grade C and should be eliminated.

2. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 1, characterized in that, It also includes customized debugging and optimization solutions for Class B generation to solve specific physical field exceedance issues.

3. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 2, characterized in that, In the debugging and optimization plan, the optimization judgment is based on the following three indicators: Excessive vibration: Vibration velocity spectral density (PSD) in the 1-100Hz frequency band v >1nm2 / Hz Temperature fluctuation: Daily temperature difference ΔT of the foundation > 0.05℃ / 24h Magnetic disturbance: Earth's magnetic field fluctuation ΔB > 5nT.

4. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 3, characterized in that, The optimization measures include deep-buried vibration isolation bases and tuned mass dampers (TMDs) for excessive vibration, thermostatic layer embedded bases and liquid nitrogen circulating temperature control systems for temperature fluctuations, and active compensation coil arrays and permalloy magnetic shielding chambers for magnetic disturbances.

5. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 1, characterized in that, In step 4), continuous monitoring is conducted for ≥30 days to capture typical interference events; vibration data: heavy vehicle traffic, wind turbine start-up and shutdown, and rainfall-induced ground pulsation; temperature data: day-night cycle, cold front passage, and equipment trial operation heat dissipation; magnetic field data: power grid load switching and rail transit peak harmonics.

6. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 1, characterized in that, Step 1) also includes the exclusion of geological restricted areas. If any of the following conditions are triggered, the site will be eliminated: active fault zone, less than 5km from the core area of ​​the site; underground karst caves / mining voids, with a subsidence risk of >10mm / year; groundwater flow velocity >1m / day, with potential foundation erosion.

7. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 1, characterized in that, The simulation software is COMSOL Multiphysics.

8. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 7, characterized in that, Simulations were performed in COMSOL Multiphysics, including building a joint field-structure-beam model: Step 1: Import the optimization parameters and calculate the response of the building / foundation / vibration isolation system; Step 2: Export the deformation field / temperature field / magnetic field distribution to the particle tracker; Step 3: Iterate through simulations until the beam offset is less than the design value.

9. The site selection technology for large-scale light source projects based on constructing a multi-physics coupling influence beam center offset estimation model as described in claim 1, characterized in that, In step 4), the deployed sensor array vibration monitoring network includes: a grid density of 50m×50m, a sensor type of three-component force balance accelerometer (frequency band 0.01-100Hz); a temperature monitoring chain: a drilling depth ≥30m, a vertical temperature measurement point spacing of no more than 1m, and a temperature accuracy of ±0.01℃; and a magnetic field monitoring array: a baseline length of 200m and a sampling rate of 1kHz.

10. The site selection technology for large-scale light source projects based on the construction of a multi-physics coupling influence beam center offset estimation model as described in claim 1, characterized in that, Threshold P of each physical field i th The values ​​of (ω) are as follows: vibration field threshold 50nm (1-100Hz), temperature field threshold ±0.1℃ / 24h, magnetic field threshold 0.1μT RMS, vacuum field threshold vacuum fluctuation ≤5%, and settlement field threshold differential settlement ≤0.1mm / 10m.

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