A magnetic shielding dynamic degaussing simulation analysis method, optimization method and medium

Abstract

The application relates to a magnetic shielding dynamic degaussing simulation analysis method, an optimization method and a medium, wherein the simulation analysis method comprises the following steps: constructing a three-dimensional finite element model of a magnetic shielding structure, an internal air domain and an external infinite air domain; applying a magnetic insulation boundary condition to the outer surface of the external infinite air domain, and applying a constant geomagnetic bias field as a global static background field; applying a periodic alternating and exponentially decaying degaussing excitation to the magnetic shielding structure; under the degaussing excitation, based on a dynamic magnetization model, a multi-cycle step iteration and transient separation solving strategy is adopted to solve the dynamic evolution process of the magnetization intensity of the magnetic shielding material; after the degaussing excitation ends, the residual magnetization intensity distribution of the magnetic shielding material is determined, and the residual magnetic field distribution of the internal air domain is obtained based on the residual magnetization intensity distribution, so that the prediction accuracy and efficiency of the residual magnetic field are improved.

Description

Technical Field

[0001] This application relates to the field of magnetic shielding technology, and in particular to a simulation analysis method, optimization method and medium for dynamic demagnetization of magnetic shielding. Background Technology

[0002] Magnetic shielding devices are core components for achieving ultra-low magnetic field environments, and the level of their internal residual magnetic field directly determines the sensitivity and stability of quantum devices and weak magnetic detection equipment. The residual magnetic field mainly consists of two parts: the penetration of the external geomagnetic field and the remanent magnetization effect of the shielding material itself. In engineering applications, magnetic shielding devices reduce remanence through a demagnetization process of "periodic alternation and amplitude decay" under a geomagnetic background field (approximately 50,000 nT). Therefore, accurately reproducing this dynamic process and predicting the residual magnetic field is a core technological bottleneck in the development of high-performance magnetic shielding devices.

[0003] The Jiles-Atherton (JA) hysteresis model, as a classic physical model describing the magnetization properties of ferromagnetic materials, can accurately characterize the hysteresis loop and remanence effect of materials, and has important theoretical value. However, the engineering modeling of the full JA model requires solving multiple nonlinear differential equations simultaneously, resulting in high computational complexity, difficulty in convergence, and large memory consumption, making it difficult to directly apply to transient simulations of long-term, multi-cycle demagnetization processes.

[0004] Current magnetic shielding demagnetization modeling and simulation analysis techniques have the following main shortcomings:

[0005] (1) Distorted physical model, neglecting geomagnetic bias and dynamic magnetization: Most simulation methods simplify the environmental magnetic field to a zero field or a constant field, without considering the continuous modulation effect of geomagnetic bias on magnetic domain reversal and magnetization trajectory. At the same time, they usually use static nonlinear permeability curves, which cannot characterize the key characteristics of materials under alternating excitation, such as dynamic magnetization, hysteresis loss and frequency response, resulting in significant deviations between the modeling analysis results and actual working conditions.

[0006] (2) The analysis strategy is inefficient and cannot reproduce the multi-cycle relaxation process: Engineering demagnetization depends on the successive relaxation of magnetic domains under multi-cycle excitation. Traditional methods mostly use steady-state approximations or simplified time-varying field models, which are difficult to stably and efficiently complete long-term, multi-cycle transient modeling and analysis.

[0007] (3) The evaluation system is too simple and lacks comprehensive quantitative indicators: Most existing technologies only output the residual magnetic field value at a single point in the center of the cabin, and cannot provide key evaluation indicators such as the spatial distribution of residual magnetism, the uniformity of residual magnetic field, and the decay rate of each cycle, making it difficult to systematically and comprehensively evaluate the demagnetization effect.

[0008] In summary, there is an urgent need in this field for a simulation analysis method that can accurately reflect the effects of geomagnetic bias, reproduce the periodic decay demagnetization mechanism, be based on dynamic magnetization characteristics, and have full-domain quantitative evaluation capabilities. Summary of the Invention

[0009] Based on this, this application provides a magnetic shielding dynamic demagnetization simulation analysis method, optimization method, and medium to solve the problem that traditional methods are difficult to stably and efficiently complete long-term, multi-cycle transient modeling and simulation analysis.

[0010] In a first aspect, embodiments of this application provide a simulation analysis method for dynamic demagnetization of magnetic shielding, the method comprising:

[0011] Construct a three-dimensional finite element model of the magnetic shielding structure, the internal air domain, and the external infinite air domain;

[0012] A magnetically insulating boundary condition is applied to the outer surface of the outer infinite air domain, and a constant geomagnetic bias field is applied to the three-dimensional finite element model as a global static background field.

[0013] A demagnetizing excitation with an amplitude decreasing over time is applied to the magnetic shielding structure;

[0014] Under the demagnetization excitation, based on the dynamic magnetization model, a multi-period step iteration and transient separation solution strategy is adopted to solve the dynamic evolution process of the total magnetization and the applied magnetic field strength inside the magnetic shielding material.

[0015] After the demagnetization excitation is completed, the residual magnetization intensity distribution inside the magnetic shielding material is determined, and the residual magnetic field distribution in the internal air domain is calculated based on the residual magnetization intensity distribution to obtain simulation analysis results.

[0016] In one embodiment, the dynamic magnetization model satisfies the following characteristics:

[0017] The total magnetization inside the magnetic shielding material is decomposed into reversible magnetization and irreversible magnetization; wherein, the reversible magnetization corresponds to the reversible displacement of the domain walls; and the irreversible magnetization corresponds to the irreversible displacement of the domain walls and the irreversible flipping of the domains.

[0018] The evolution of the irreversible magnetization follows the magnetic domain relaxation dynamics equation, and approaches the hysteresis-free magnetization exponential with a preset relaxation time constant.

[0019] The hysteresis-free magnetization is represented by a modified Langevin function and is determined by the saturation magnetization, shape parameters, and effective magnetic field strength.

[0020] The effective magnetic field strength is a vector superposition of the geomagnetic bias field, the periodic excitation field generated by the demagnetization excitation, and the interdomain coupling term; wherein, the interdomain coupling term is equal to the interdomain coupling coefficient multiplied by the total magnetization at the current moment;

[0021] The reversible magnetization intensity is proportional to the difference between the hysteresis-free magnetization intensity and the irreversible magnetization intensity.

[0022] In one embodiment, the process of solving the dynamic evolution of the total magnetization and applied magnetic field strength inside the magnetic shielding material based on a dynamic magnetization model and employing a multi-period step iteration and transient separation solution strategy includes:

[0023] The total demagnetization time is decomposed into multiple iteration cycles;

[0024] Within each iteration cycle, based on the dynamic magnetization model and the current initial magnetization state, the total magnetic field strength and the applied magnetization strength under the demagnetization excitation within that iteration cycle are solved separately; wherein, the current initial magnetization state is the magnetization state at the end of the previous iteration cycle; the applied magnetic field strength is the vector superposition of the geomagnetic bias field and the periodic excitation field;

[0025] The iteration terminates when the rate of change of remanence at the end of an adjacent iteration cycle is less than a preset threshold.

[0026] In one embodiment, the step of separately solving for the total magnetic field strength and the applied magnetization intensity under the demagnetization excitation within each iteration cycle, based on the dynamic magnetization model and the current initial magnetization state, specifically includes:

[0027] Each iteration cycle is decomposed into multiple time steps;

[0028] Within each time step, the current total magnetization is first fixed, and the current applied magnetic field strength is obtained by solving the magnetic field control equation; then, the current total magnetization is updated by solving the dynamic magnetization model based on the current applied magnetic field strength.

[0029] Determine whether the relative change in total magnetization within the current time step is less than the preset convergence tolerance;

[0030] If not, repeat the above update process. When the relative change in total magnetization within the time step is less than the preset convergence tolerance, proceed to the next time step.

[0031] In one embodiment, calculating the residual magnetic field distribution of the internal air domain based on the residual magnetization distribution includes:

[0032] Based on the remanent magnetization distribution, the residual magnetic field distribution of the internal air domain is obtained by solving the Poisson equation for the vector magnetic potential; wherein, the Poisson equation for the vector magnetic potential is determined by the curl of the remanent magnetization distribution and the free permeability, and the residual magnetic field is the curl of the vector magnetic potential.

[0033] In one embodiment, the demagnetizing excitation is a periodically alternating sinusoidal alternating field with an exponentially decaying amplitude, and the excitation direction is consistent with the direction of the geomagnetic bias field.

[0034] Secondly, embodiments of this application also provide a magnetic shielding dynamic demagnetization simulation optimization method, the method comprising:

[0035] Based on the magnetic shielding dynamic demagnetization simulation analysis method described in the first aspect above, the distribution of residual magnetization intensity and residual magnetic field is obtained.

[0036] Evaluation indices are obtained based on the remanent magnetization distribution and the residual magnetic field distribution;

[0037] Using the evaluation index as the objective function, the demagnetization process parameters are iteratively optimized to obtain the optimal demagnetization scheme; wherein, the demagnetization process parameters include the design parameters of the magnetic shielding structure and the waveform parameters of the demagnetization excitation.

[0038] In one embodiment, the evaluation metrics include: maximum remanence, remanence suppression rate, maximum residual magnetic field, residual magnetic field uniformity, and cycle-by-cycle decay coefficient.

[0039] Wherein, the maximum remanence is the maximum value of the remanent magnetization intensity distribution; the remanence suppression rate characterizes the percentage of initial remanence suppressed by the demagnetization process; the maximum residual magnetic field is the maximum value of the residual magnetic field distribution; the residual magnetic field uniformity is the ratio of the standard deviation to the mean of the residual magnetic field distribution; and the cycle-by-cycle decay coefficient characterizes the percentage of remanence decay per cycle.

[0040] Thirdly, embodiments of this application also provide a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to perform the method as described in the first or second aspect above.

[0041] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method described in the first or second aspect above.

[0042] The aforementioned magnetic shielding dynamic demagnetization simulation analysis method, optimization method, and medium, by constructing a multi-field coupled modeling analysis model of "geomagnetic bias + periodic decay excitation + dynamic magnetization," realistically reproduces the demagnetization physical process of periodic decay excitation under geomagnetic conditions, eliminating the deviation between existing modeling analysis results and actual working conditions. Through multi-period step iteration and transient separation solution strategies, the iterative magnetic field equation and magnetization intensity update equation are decoupled, achieving stable solutions for the entire demagnetization process and overcoming the problems of easy divergence and large memory consumption in long-term periodic simulations. Through dynamic magnetization and magnetic domain relaxation mechanisms, the dynamic evolution of magnetization intensity and spatial distribution of remanent magnetization are directly solved without equivalent current conversion, while improving the prediction accuracy of residual magnetic field. Through the above technical means, the problems of physical model distortion and inefficient calculation strategies in existing technologies are solved, improving the prediction accuracy and efficiency of simulation modeling analysis.

[0043] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0044] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0045] Figure 1 This is a hardware structure block diagram of the terminal device of the magnetic shielding dynamic demagnetization simulation analysis method in one embodiment;

[0046] Figure 2 This is a flowchart illustrating the simulation analysis method for dynamic demagnetization of magnetic shielding in one embodiment;

[0047] Figure 3 This is a schematic diagram of a three-dimensional geometric model of the magnetic shielding device in one embodiment;

[0048] Figure 4 This is a schematic diagram of magnetization intensity decomposition and relaxation evolution in a dynamic magnetization model in one embodiment;

[0049] Figure 5 This is a schematic diagram of a multi-cycle step iteration and transient separation solution strategy in one embodiment;

[0050] Figure 6 This is a schematic diagram illustrating the calculation principle of remanence and residual magnetic field in one embodiment;

[0051] Figure 7 This is a flowchart illustrating the simulation optimization method for dynamic demagnetization of magnetic shielding in one embodiment. Detailed Implementation

[0052] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0053] The method embodiments provided in this example can be executed on a terminal, computer, or similar computing device. For example, it can run on a terminal. Figure 1 This is a hardware structure block diagram of the terminal for the magnetic shielding dynamic demagnetization simulation analysis method in this embodiment. (See diagram for example.) Figure 1 As shown, a terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 and a memory 104 for storing data are also included. The processor 102 may be, but is not limited to, a microprocessor (MCU) or a programmable logic device (FPGA). The terminal may also include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that… Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the terminal described above. For example, the terminal may also include components that are larger than... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown are illustrated.

[0054] The terminal supports a general-purpose finite element modeling and analysis platform, and the modeling and analysis method of this application can be implemented based on such a platform. As a specific embodiment of this application, the COMSOL Multiphysics multiphysics modeling and analysis platform is used as an example for illustration below. It should be noted that COMSOL Multiphysics is merely an exemplary implementation tool, and those skilled in the art can also implement the methods of the embodiments of this application based on other finite element software with AC / DC modules and transient solution capabilities.

[0055] This application provides a simulation analysis method for dynamic demagnetization of magnetic shielding, which can be applied to... Figure 1 Let's take the terminal in the middle as an example for explanation. Figure 2 This is a flowchart illustrating the magnetic shielding dynamic demagnetization simulation analysis method according to an embodiment of this application. The method includes the following steps:

[0056] Step S201: Construct a three-dimensional finite element model of the magnetic shielding structure, the internal air domain, and the external infinite air domain.

[0057] The magnetic shielding structure is designed according to the actual engineering dimensions, and its geometry includes, but is not limited to, a cube, cylinder, or sphere, and is composed of one or more layers of high-permeability soft magnetic material. The wall thickness, number of layers and interlayer spacing of the magnetic shielding structure, the number of coil turns in each direction, and the coil geometry are determined according to the design specifications.

[0058] The internal air domain completely covers the internal space enclosed by the magnetic shielding structure and is used for subsequent calculations of the residual magnetic field distribution inside the magnetic shielding device.

[0059] The outer infinite air domain is set as the outer space that encloses the magnetic shielding structure and the inner air domain. Its size is 5 to 8 times the characteristic size of the magnetic shielding body, so as to simulate the boundary conditions of infinite space and eliminate the influence of boundary reflection on the magnetic field calculation results.

[0060] This application utilizes a finite element modeling and analysis platform to construct three-dimensional finite element models of the magnetic shielding structure, the internal air domain, and the external infinite air domain. Figure 3 An example of one of the three-dimensional finite element models is shown.

[0061] After constructing the three-dimensional finite element model, the finite element method was used to spatially discretize the constructed three-dimensional geometric model. Tetrahedral elements were used for the mesh, with local mesh refinement along the thickness direction of the magnetic shielding layer. Two to three layers of elements were set to accurately capture the magnetic field gradient along the thickness direction. Gradient meshing was used for the internal air domain, with finer meshing near the magnetic shielding layer and relatively sparse meshing in the central region, to control the total number of elements while ensuring computational accuracy. The quality of the global mesh was controlled within acceptable limits.

[0062] Step S202: Apply magnetic insulation boundary conditions to the outer surface of the outer infinite air domain, and apply a constant geomagnetic bias field to the three-dimensional finite element model as a global static background field.

[0063] Applying a magnetically insulating boundary condition to the outer surface of an infinitely distant air region, its mathematical expression is:

[0064]

[0065] in, The unit vector normal to the boundary. This represents the applied magnetic field strength vector. This boundary condition is used to simulate the physical condition where the magnetic field decays to zero at infinity.

[0066] This application employs a reduced field method to apply a constant geomagnetic bias field as the global background field. In the finite element model, the total magnetic vector potential is... Decomposed into background magnetic vector potential With reduced magnetic vector potential The sum: where the background magnetic vector potential is... Corresponding to the preset geomagnetic bias field, satisfying ; Reduced magnetic vector potential This represents the quantity to be solved corresponding to the magnetic field generated by demagnetization excitation and magnetizing materials. Geomagnetic bias field. For a constant uniform field, its expression is: , These are the components of the geomagnetic bias field in the three orthogonal directions.

[0067] Among them, the total magnetic vector potential , i.e., vector magnetic potential, is the vector potential function used in electromagnetism to describe a magnetic field, satisfying ,in, denoted as magnetic flux density.

[0068] Apply an external magnetic vector potential boundary condition on the outer infinite air domain boundary: This condition ensures that the reduced field is insulated at the boundary while allowing the background field to pass through the boundary without obstruction, simulating the geomagnetic environment in infinite space.

[0069] Step S203: Apply a demagnetizing excitation with an amplitude that decreases over time to the magnetic shielding structure.

[0070] Preferably, a periodically alternating demagnetizing excitation with exponentially decaying amplitude is applied. Demagnetizing coils are arranged in the three orthogonal directions (X, Y, Z), with each coil connected in series and supplied with the same demagnetizing current. The mathematical expression for the excitation current is:

[0071]

[0072] in, The initial current amplitude, The decay time constant, For alternating frequency, The current is applied to the edge current nodes in each direction of the finite element model, generating the periodic excitation magnetic field to be solved. External magnetic field strength This is the superposition of the geomagnetic bias field and the periodic excitation magnetic field. Because the reduced field method is used, the solver directly solves the problem. The corresponding reduced field components.

[0073] Step S204: Under the demagnetization excitation, based on the dynamic magnetization model, a multi-period step iteration and transient separation solution strategy is adopted to solve the dynamic evolution process of the total magnetization intensity and the applied magnetic field intensity inside the magnetic shielding material.

[0074] This application will include the total magnetization. Decomposed into irreversible components That is, irreversible magnetization and reversible components. The reversible magnetization intensity, its decomposition and evolution mechanism is as follows: Figure 4 As shown: Among them, the irreversible component The irreversible displacement of domain walls and the irreversible flipping of domains are the main sources of remanence, and their evolution follows the domain relaxation dynamics equation; reversible components This mainly corresponds to the reversible bending or vibration of the domain walls within the pinned potential well, as well as the rotation of some reversible domains. After the external excitation is removed, this component elastically returns to its original state, tending towards zero, and therefore contributes no remanence. This application, based on a dynamic magnetization model, differs from existing simplified methods such as static magnetization curve approximation and remanence equivalent current, thus improving prediction accuracy.

[0075] Step S205: After the demagnetization excitation is completed, determine the residual magnetization intensity distribution inside the magnetic shielding material, and calculate the residual magnetic field distribution in the internal air domain based on the residual magnetization intensity distribution to obtain the simulation analysis results.

[0076] This application strictly distinguishes between the two physical concepts of "remanence" and "residual magnetic field": remanence This refers to the residual magnetization within the magnetic shielding material after demagnetization excitation. It is the source of the magnetic field, located inside the magnetic shielding material, and is measured in A / m. Residual magnetic field. This refers to the magnetic field generated in the air domain inside a magnetically shielded chamber by remanent magnetization as the field source. It is a direct environmental quantity that ultimately affects precision equipment, and its unit is terabytes (T). The relationship between the two is: remanent magnetization is the cause, and the residual magnetic field is the effect. This application obtains more accurate prediction results by strictly distinguishing between the two, first calculating the distribution of remanent magnetization, and then calculating the residual magnetic field based on the remanent magnetization.

[0077] This application embodiment constructs a multi-field coupled analysis model of "geomagnetic bias + periodic decay excitation + dynamic magnetization" to realistically reproduce the demagnetization physical process of periodic decay excitation under geomagnetic conditions, eliminating the deviation between existing modeling analysis results and actual working conditions. Through a multi-period step iteration and transient separation solution strategy, the iterative magnetic field equation and magnetization intensity update equation are decoupled, achieving stable solutions for the entire demagnetization process and overcoming the problems of easy divergence and large memory consumption in long-term periodic simulations. Through dynamic magnetization and magnetic domain relaxation mechanisms, the dynamic evolution of magnetization intensity and the spatial distribution of remanent magnetization are directly solved without equivalent current conversion, while simultaneously improving the prediction accuracy of the residual magnetic field. These technical means solve the problems of physical model distortion and inefficient calculation strategies in existing technologies, improving the prediction accuracy and efficiency of simulation modeling analysis.

[0078] In one embodiment, the dynamic magnetization model satisfies the following characteristics:

[0079] This application decomposes the total magnetization inside the magnetic shielding material into reversible magnetization and irreversible magnetization; wherein, the reversible magnetization corresponds to the reversible displacement of the domain walls; and the irreversible magnetization corresponds to the irreversible displacement of the domain walls and the irreversible flipping of the domains.

[0080] The evolution of the magnetization component follows the magnetic domain relaxation dynamics equation, approaching the hysteresis-free magnetization exponentially with a preset relaxation time constant. The hysteresis-free magnetization is represented by a modified Langevin function and is determined by the saturation magnetization, shape parameters, and effective magnetic field strength. The effective magnetic field strength is a vector superposition of the geomagnetic bias field, the periodic excitation field generated by the demagnetization excitation, and the interdomain coupling term; wherein the interdomain coupling term is equal to the interdomain coupling coefficient multiplied by the total magnetization at the current moment; the reversible magnetization is proportional to the difference between the hysteresis-free magnetization and the irreversible magnetization; the applied magnetic field strength is a vector superposition of the geomagnetic bias field and the periodic excitation field.

[0081] This application will include the total magnetization. Decomposed into irreversible components and reversible components Its decomposition and evolution mechanisms are as follows: Figure 4 As shown: .

[0082] Among them, the irreversible component The irreversible displacement of domain walls and the irreversible flipping of domains are the main sources of remanence, and their evolution follows the domain relaxation dynamics equation; reversible components This mainly corresponds to the reversible bending or vibration of the domain walls within the pinned potential well, as well as the rotation of some reversible domains. After the external excitation is removed, this component elastically returns to its original state, tending towards zero, and therefore contributes no remanence.

[0083] The evolution of the irreversible magnetization component follows the magnetic domain relaxation dynamics equation:

[0084]

[0085] in, The hysteresis-free magnetization represents the ideal equilibrium state of magnetic domains under a given effective field. is the domain relaxation time constant, which characterizes the response speed of a magnetic domain as it evolves from its current state to its equilibrium state.

[0086] This equation describes the irreversible magnetization component at a rate of Towards hysteresis-free magnetization The physical process of exponential convergence. The value of is related to the material properties. The smaller the value, the faster the magnetic domain response and the more rapid the demagnetization process; The larger the domain size, the slower the magnetic domain response, and the longer the relaxation time required for the demagnetization process. The introduction of this relaxation mechanism enables this application to realistically characterize the dynamic magnetization behavior of soft magnetic materials under periodic decay excitation, which differs from the traditional static magnetization model.

[0087] Hysteresis-free magnetization is described using a modified Langevin function, and the model for hysteresis-free magnetization is as follows:

[0088]

[0089] in, Saturation magnetization represents the maximum magnetization that the material can achieve. The shape parameter characterizes the steepness of the hysteresis-free magnetization curve; It is the unit vector in the direction of the effective field.

[0090] Effective magnetic field strength It is a superposition of the geomagnetic bias field, the periodic excitation field, and the interdomain coupling field: .in, For the applied constant geomagnetic bias background field; This is a periodically decaying excitation field generated by the demagnetizing current; is the interdomain coupling coefficient, which characterizes the interaction strength between magnetic domains; This represents the total magnetization at the current moment. Effective field. The introduction of this allows the model to reflect the interaction between magnetic domains within the material.

[0091] The difference between reversible magnetization and irreversible magnetization is proportional to the difference between hysteresis-free magnetization and irreversible magnetization. .

[0092] Where c is the reversible magnetic susceptibility, characterizing the sensitivity of the material's reversible magnetization response; the larger the value, the higher the proportion of reversible magnetization. Reversible magnetization It is generated instantly with the establishment of an effective field and disappears instantly with the removal of the effective field, without generating residual magnetization.

[0093] External magnetic field strength This is the superposition of the geomagnetic bias field and the periodic excitation magnetic field. .

[0094] In one embodiment, the process of solving the dynamic evolution of the magnetization intensity of the magnetic shielding material based on the dynamic magnetization model and employing a multi-period step iteration and transient separation solution strategy includes the following steps:

[0095] Step S301: Decompose the total demagnetization time into multiple iteration cycles.

[0096] The total demagnetization time is decomposed into N iterations and solved sequentially. .

[0097] Step S302: In each iteration cycle, based on the dynamic magnetization model and the current initial magnetization state, the total magnetic field strength and the applied magnetization strength under the demagnetization excitation in that iteration cycle are solved separately; wherein, the current initial magnetization state is the magnetization state at the end of the previous iteration cycle.

[0098] Single-cycle transient solution: in the first period Within each cycle, based on the current initial magnetization state, the applied magnetic field strength under dynamic demagnetization excitation within that cycle is completely solved. Total magnetization inside the magnetic shielding material The evolution of.

[0099] State transfer and iteration: The magnetization state at the end of the previous iteration cycle is used as the initial condition for the next cycle, i.e. And so on, completing N cycles of step-by-step iteration.

[0100] Step S303: When the rate of change of remanence at the end of an adjacent iteration cycle is less than a preset threshold, the iteration is terminated.

[0101] This application introduces a convergence judgment mechanism; for example, the preset threshold can be set to 10. -3 When the rate of change of remanence at the end of an adjacent cycle When the iteration is considered to have reached a stable state, the iteration is terminated early, significantly reducing unnecessary computation.

[0102] The multi-cycle step-iteration strategy proposed in this application decomposes a complex continuous demagnetization process containing tens to thousands of cycles into several quasi-static, end-to-end connected cycle subproblems. Through single-cycle transient solution, state transfer and iteration, and convergence judgment mechanism, the dynamic evolution process of the total magnetization intensity inside the magnetic shielding material is solved, thereby effectively avoiding the numerical divergence and memory explosion problems commonly found in long-term transient simulations.

[0103] In one embodiment, the step of separately solving for the total magnetic field strength and the applied magnetization intensity under the demagnetization excitation within each iteration cycle, based on the dynamic magnetization model and the current initial magnetization state, specifically includes the following steps:

[0104] Step S401: Decompose each iteration cycle into multiple time steps.

[0105] To ensure accurate capture of the excitation waveform To capture the dynamic details and satisfy numerical stability requirements, this application decomposes each iteration cycle into multiple time steps. Time step satisfy:

[0106]

[0107] in: The iteration period, or excitation period, is defined as the period between iterations. This condition ensures that each excitation period contains at least 50 computation time points, which is sufficient to fully resolve the dynamic response of the magnetization.

[0108] In step S402, within each time step, the current total magnetization intensity is first fixed, and the current applied magnetic field intensity is obtained by solving the magnetic field control equation; then, the current total magnetization intensity is updated by solving the dynamic magnetization model based on the current applied magnetic field intensity.

[0109] This application adopts a quasi-static magnetic field control equation, neglecting the influence of displacement current, and its differential form is:

[0110]

[0111]

[0112]

[0113] in, The vector of the applied magnetic field strength. It is the magnetic flux density vector. The magnetization vector. Current density vector Permeability of free space. Current density. Including the excitation current density loaded by the demagnetizing coil and the equivalent magnetizing current density generated by the change in magnetization intensity. In the demagnetization simulation process involved in this application, there are no other external current sources besides the excitation current applied to the demagnetization coil.

[0114] Step S403: Determine whether the relative change in total magnetization intensity within the current time step is less than the preset convergence tolerance; if not, repeat the above update process. When the relative change in total magnetization intensity within the time step is less than the preset convergence tolerance, proceed to the next time step.

[0115] Within each time step, this application employs a "transient separation" strategy to decouple the strongly coupled magnetic field-magnetization problem into two sub-problems that are solved alternately, thereby avoiding matrix ill-conditioning, convergence difficulties, and excessive memory consumption caused by direct coupling solutions. Figure 5 As shown, the specific solution process includes the following steps:

[0116] Step 1: Solve for the applied magnetic field strength. Calculate the total magnetization at the current moment. Treating these as known quantities, we substitute them into the quasi-static magnetic field control equations and combine them with the magnetic insulation boundary conditions described in step S202. The applied magnetic field strength of the entire field can be obtained by solving. With magnetic flux density .in, Demagnetizing current in step S203 The current density generated on the demagnetizing coil.

[0117] Among them: Quasi-static magnetic field control equations:

[0118]

[0119]

[0120] Step 2: Update the total magnetization. Apply the external magnetic field strength obtained in Step 1. Substituting into the dynamic magnetization model, the effective field is first calculated. :

[0121]

[0122] Then update the hysteresis-free magnetization intensity sequentially. Irreversible magnetization and reversible magnetization The updated formula is as follows:

[0123]

[0124]

[0125]

[0126] Finally, the updated total magnetization was obtained. .

[0127] Step 3: Convergence Judgment. Calculate the relative change in magnetization within the current time step:

[0128]

[0129] If the relative change Less than the preset convergence tolerance (e.g.) If the iteration converges, proceed to the next time step; otherwise, As a new known quantity, return to step 1 and continue iterating.

[0130] In one embodiment, calculating the residual magnetic field distribution of the internal air domain based on the residual magnetization distribution includes: obtaining the residual magnetic field distribution of the internal air domain by solving the Poisson equation for the vector magnetic potential based on the residual magnetization distribution; wherein the Poisson equation for the vector magnetic potential is determined by the curl of the residual magnetization distribution and the free permeability, and the residual magnetic field is the curl of the vector magnetic potential.

[0131] Figure 6 A schematic diagram illustrating the calculation principle of remanence and residual magnetic field:

[0132] After the demagnetization excitation is completed, the total magnetization inside the magnetic shielding material reaches a stable state, which is the spatial distribution of the residual magnetization:

[0133]

[0134] Based on remanent magnetization By solving the vector magnetic potential The Poisson equation is used to calculate the residual magnetic field:

[0135]

[0136]

[0137] in, Vector magnetic potential (unit: Wb / m). Residual magnetic flux density (unit: T). The Poisson equation for the vector magnetic potential is determined by the curl of the remanent magnetization and the free permeability, where the residual magnetic field is the curl of the vector magnetic potential.

[0138] In one embodiment, the demagnetizing excitation is a periodically alternating sinusoidal alternating field with an exponentially decaying amplitude, and the excitation direction is consistent with the direction of the geomagnetic bias field.

[0139] This application also provides a method for optimizing dynamic demagnetization simulation of magnetic shielding, such as... Figure 7 As shown, the method includes the following steps:

[0140] Step S501: Based on the magnetic shielding dynamic demagnetization simulation analysis method, the residual magnetization intensity distribution and residual magnetic field distribution are obtained.

[0141] Step S502: Based on the residual magnetization distribution and the residual magnetic field distribution, an evaluation index is obtained.

[0142] This application constructs the following global quantitative evaluation index system, including maximum remanence, remanence suppression rate, maximum residual magnetic field, residual magnetic field uniformity, and cycle-by-cycle decay coefficient, wherein:

[0143] The maximum remanence is the maximum value of the remanent magnetization distribution, and the maximum residual magnetic field is the maximum value of the residual magnetic field distribution.

[0144] The remanence suppression rate characterizes the percentage of initial remanence suppressed by the demagnetization process, and is calculated using the following formula:

[0145]

[0146] in, This represents the initial maximum remanence before demagnetization. This represents the maximum residual magnetism after demagnetization.

[0147] The uniformity of the residual magnetic field is the ratio of the standard deviation to the mean of the residual magnetic field distribution, and the calculation formula is as follows:

[0148]

[0149] in, The standard deviation of the residual magnetic field in the internal air domain. This represents the average value of the residual magnetic field in the internal air domain. The smaller the value, the more uniform the spatial distribution of the residual magnetic field.

[0150] The cycle-by-cycle attenuation coefficient characterizes the percentage decrease in remanence per cycle, and is calculated using the following formula:

[0151]

[0152] in, For the first The maximum remanence at the end of the cycle. This coefficient reflects the cycle-by-cycle decay trend of remanence during demagnetization. When the value tends to stabilize and approaches zero, it indicates that the demagnetization process has reached an equilibrium state.

[0153] Step S503: Using the evaluation index as the objective function, iteratively optimize the demagnetization process parameters to obtain the optimal demagnetization scheme; wherein, the demagnetization process parameters include the design parameters of the magnetic shielding structure and the waveform parameters of the demagnetization excitation.

[0154] Specifically, this application takes "minimum residual magnetic field peak value, optimal uniformity, and highest residual magnetism suppression rate" as the optimization objectives, and uses a combination of single-factor analysis and multi-objective optimization algorithms (such as NSGA-II) to iteratively optimize the following demagnetization process parameters:

[0155] The waveform parameters of the demagnetizing excitation include: initial amplitude H0, decay time constant. Alternating frequency The total number of cycles, N; the design parameters of the magnetic shielding structure include magnetic shielding structure parameters and coil layout parameters. Magnetic shielding structure parameters include: shielding layer wall thickness, number of layers, and interlayer spacing. Coil layout parameters include: number of coil turns in each direction and coil geometry.

[0156] After optimization, the Pareto optimal solution set is output, and the optimal demagnetization process scheme is selected by combining the actual engineering constraints.

[0157] The following provides a specific implementation method. This embodiment takes the COMSOL Multiphysics platform as an example to illustrate the specific implementation of the simulation analysis method of this application.

[0158] Construct a three-dimensional geometric model of the magnetically shielded cabin shell, the internal air domain, and the external air domain, such as... Figure 3 As shown. The shielding layer material is described using the dynamic magnetization model described in this application. The key parameter of the dynamic magnetization model is the saturation magnetization. Shape parameters Interdomain coupling coefficient Magnetic domain relaxation time constant The reversible magnetic susceptibility c can be obtained by experimentally measuring the saturation hysteresis loop of the soft magnetic material and fitting it using a nonlinear optimization algorithm. Tetrahedral elements are used for mesh generation, with finer meshing along the thickness direction of the shielding layer.

[0159] Applying a geomagnetic bias background field and demagnetizing excitation with alternating loading period and exponentially decaying amplitude. .

[0160] The proposed "multi-cycle step iteration" and "transient separate solution" strategies are employed: a separate solver is configured, with each cycle using... The time step is incremented by a fixed time step; within each time step, the total magnetization is first fixed. Solve for the applied magnetic field strength Then update the total magnetization. The process iterates alternately until the relative change in magnetization is less than a preset inner layer tolerance. The magnetization state is transferred during each cycle, and the process terminates when the relative change in remanence at the end of an adjacent cycle is less than a preset outer layer threshold. Figure 5 As shown.

[0161] The remanent magnetization is obtained after solving. ,pass and Calculate the residual magnetic field distribution, such as Figure 6 As shown.

[0162] Then calculate the evaluation index: maximum remanence. Maximum residual magnetic field Residual magnetic field uniformity Remanence suppression rate and the periodic decay coefficient .

[0163] Beneficial effects: The modeling and analysis method described in this application can accurately predict the distribution of residual magnetic fields under different demagnetization process parameters. Based on this, process parameters can be optimized, and a global quantitative evaluation system including maximum remanence, remanence suppression rate, residual magnetic field uniformity, and cycle-by-cycle attenuation coefficient can be constructed. This system supports multi-objective iterative optimization and can obtain the optimal demagnetization scheme that significantly reduces the residual magnetic field, thus providing theoretical guidance and data support for the demagnetization process of magnetic shielding devices.

[0164] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a communication interface, a display screen, and an input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for wired or wireless communication with external terminals. Wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements the steps in an embodiment of a magnetic shielding dynamic demagnetization simulation analysis method or simulation optimization method.

[0165] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps in any of the above embodiments of the magnetic shielding dynamic demagnetization simulation analysis method or simulation optimization method.

[0166] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0167] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0168] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A simulation analysis method for dynamic demagnetization of magnetic shielding, characterized in that, The method includes: Construct a three-dimensional finite element model of the magnetic shielding structure, the internal air domain, and the external infinite air domain; A magnetically insulating boundary condition is applied to the outer surface of the outer infinite air domain, and a constant geomagnetic bias field is applied to the three-dimensional finite element model as a global static background field. A demagnetizing excitation with an amplitude decreasing over time is applied to the magnetic shielding structure; Under the demagnetization excitation, based on the dynamic magnetization model, a multi-period step iteration and transient separation solution strategy is adopted to solve the dynamic evolution process of the total magnetization and the applied magnetic field strength inside the magnetic shielding material. After the demagnetization excitation is completed, the residual magnetization intensity distribution inside the magnetic shielding material is determined, and the residual magnetic field distribution in the internal air domain is calculated based on the residual magnetization intensity distribution to obtain simulation analysis results.

2. The method according to claim 1, characterized in that, The dynamic magnetization model satisfies the following characteristics: The total magnetization inside the magnetic shielding material is decomposed into reversible magnetization and irreversible magnetization; wherein, the reversible magnetization corresponds to the reversible displacement of the domain walls; and the irreversible magnetization corresponds to the irreversible displacement of the domain walls and the irreversible flipping of the domains. The evolution of the irreversible magnetization follows the magnetic domain relaxation dynamics equation, and approaches the hysteresis-free magnetization exponential with a preset relaxation time constant. The hysteresis-free magnetization is represented by a modified Langevin function and is determined by the saturation magnetization, shape parameters, and effective magnetic field strength. The effective magnetic field strength is a vector superposition of the geomagnetic bias field, the periodic excitation field generated by the demagnetization excitation, and the interdomain coupling term; wherein, the interdomain coupling term is equal to the interdomain coupling coefficient multiplied by the total magnetization at the current moment; The reversible magnetization intensity is proportional to the difference between the hysteresis-free magnetization intensity and the irreversible magnetization intensity.

3. The method according to claim 2, characterized in that, The dynamic evolution process of the total magnetization and applied magnetic field strength inside the magnetic shielding material, based on the dynamic magnetization model and employing a multi-period step iteration and transient separation solution strategy, includes: The total demagnetization time is decomposed into multiple iteration cycles; Within each iteration cycle, based on the dynamic magnetization model and the current initial magnetization state, the total magnetic field strength and the applied magnetization strength under the demagnetization excitation within that iteration cycle are solved separately; wherein, the current initial magnetization state is the magnetization state at the end of the previous iteration cycle; the applied magnetic field strength is the vector superposition of the geomagnetic bias field and the periodic excitation field; The iteration terminates when the rate of change of remanence at the end of an adjacent iteration cycle is less than a preset threshold.

4. The method according to claim 3, characterized in that, Within each iteration cycle, based on the dynamic magnetization model and the current initial magnetization state, the total magnetic field strength and the applied magnetization strength under the demagnetization excitation within that iteration cycle are solved separately, specifically including: Each iteration cycle is decomposed into multiple time steps; Within each time step, the current total magnetization is first fixed, and the current applied magnetic field strength is obtained by solving the magnetic field control equation; then, the current total magnetization is updated by solving the dynamic magnetization model based on the current applied magnetic field strength. Determine whether the relative change in total magnetization within the current time step is less than the preset convergence tolerance; If not, repeat the above update process. When the relative change in total magnetization within the time step is less than the preset convergence tolerance, proceed to the next time step.

5. The method according to claim 1, characterized in that, The calculation of the residual magnetic field distribution in the internal air domain based on the residual magnetization distribution includes: Based on the remanent magnetization distribution, the residual magnetic field distribution of the internal air domain is obtained by solving the Poisson equation for the vector magnetic potential; wherein, the Poisson equation for the vector magnetic potential is determined by the curl of the remanent magnetization distribution and the free permeability, and the residual magnetic field is the curl of the vector magnetic potential.

6. The method according to claim 1, characterized in that, The demagnetizing excitation is a periodically alternating sinusoidal alternating field with an exponentially decaying amplitude, and the excitation direction is consistent with the direction of the geomagnetic bias field.

7. A simulation optimization method for dynamic demagnetization of magnetic shielding, characterized in that, The method includes: Based on the magnetic shielding dynamic demagnetization simulation analysis method according to any one of claims 1 to 6, the residual magnetization intensity distribution and residual magnetic field distribution are obtained; Evaluation indices are obtained based on the remanent magnetization distribution and the residual magnetic field distribution; Using the evaluation index as the objective function, the demagnetization process parameters are iteratively optimized to obtain the optimal demagnetization scheme; wherein, the demagnetization process parameters include the design parameters of the magnetic shielding structure and the waveform parameters of the demagnetization excitation.

8. The method according to claim 7, characterized in that, The evaluation indicators include: maximum remanence, remanence suppression rate, maximum residual magnetic field, residual magnetic field uniformity, and cycle-by-cycle decay coefficient. Wherein, the maximum remanence is the maximum value of the remanent magnetization intensity distribution; the remanence suppression rate characterizes the percentage of initial remanence suppressed by the demagnetization process; the maximum residual magnetic field is the maximum value of the residual magnetic field distribution; the residual magnetic field uniformity is the ratio of the standard deviation to the mean of the residual magnetic field distribution; and the cycle-by-cycle decay coefficient characterizes the percentage of remanence decay per cycle.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 8.

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