A multi-material on-demand site-specific design method based on heterogeneous interface action

Abstract

The present application relates to the field of composite structure design and gear structure design, and more particularly to a multi-material on-demand fixed-point design method based on heterogeneous interface action. To solve the bottleneck of multi-functional collaborative design, the method comprises the following steps: step one, according to the expected demand, using the structure and material type in the database to determine the model type, and establishing a three-dimensional model; step two, using the finite element and micro-scale experiment combination mode for the three-dimensional model, and systematically studying the influence law of heterogeneous interface stress and performance; step three, revealing the action mechanism of interface macro-configuration, microstructure and chemical bond connection, and constructing the theoretical model and design criterion of multi-material heterogeneous interface fusion process; step four, combining the solid-liquid interface fluid dynamics and chemical energy transfer law, and establishing a multi-material digital model; step five, combining the multi-material voxel modeling and three-dimensional gridding technology, and developing a distribution model of adjustable material.

Description

Technical Field

[0001] This invention relates to the fields of composite material structure design and gear structure design, and more specifically to a multi-material on-demand fixed-point design method based on heterogeneous interface effects. Background Technology

[0002] Composite material structures are characterized by lightweight, high strength, and multifunctionality, and are widely used in aerospace, microelectronics, and biomedicine. Multifunctional devices, exemplified by micro gears, integrate transmission, sensing, and direct drive functions, and are key components in novel security code detectors, micropumps, and other equipment. However, traditional design methods primarily rely on empirical formulas to optimize the performance of single materials. They lack systematic research on stress distribution and failure mechanisms at heterogeneous interfaces at the microscale, leading to insufficient performance and chemical bond strength at these interfaces, thus hindering the improvement of composite material performance.

[0003] In existing technologies, the performance regulation of heterogeneous interfaces is mainly achieved by changing the interface morphology, such as coating or surface roughening treatment. However, there is still a lack of systematic analysis on the macroscopic configuration, microstructure, material elastic modulus differences, and chemical bond connection methods of the interface. In particular, there is a lack of clear theoretical support for the correlation mechanism between interface stress concentration and long-term service stability, which makes it difficult to meet the design requirements of multifunctional structures under complex working conditions.

[0004] However, current composite material design often focuses on single functions, such as high strength or conductivity. There is a lack of research on the integrated functions of multiple physical fields, such as magnetic response, self-lubrication, and thermal conductivity. The distribution patterns of functional materials and the laws of interfacial energy transfer (such as light / chemical energy conversion and solid-liquid interface fluid behavior) lack quantitative correlation models, which leads to the realization of functions mainly relying on empirical trial and error, resulting in low design efficiency and insufficient reliability.

[0005] At the level of modeling and optimization methods, although traditional finite element analysis can simulate the stress distribution at the interface, it is difficult to be compatible with multi-scale (micro-macro) coupled design. Multi-material distribution optimization often adopts homogenization methods or topology optimization, which do not provide sufficient support for the precise positioning of voxel-level materials. Although intelligent optimization methods such as genetic algorithms have been introduced, they are slow to converge and are prone to getting trapped in local optima due to the lack of high-quality training data and cross-physics constraints.

[0006] The demand for composite micro gears in microelectromechanical systems requires a balance between high-precision transmission and multi-functional integration. However, traditional micro gears mainly focus on single gears and surface treatment technologies, which cannot achieve synergistic control of the intrinsic properties of materials and interface characteristics. Furthermore, the interfacial fluid dynamics behavior, such as the formation of lubricating films at the microscale, differs significantly from that at the macroscale, making it difficult to directly transfer and apply traditional lubrication theories. Summary of the Invention

[0007] This invention provides a multi-material on-demand fixed-point design method based on heterogeneous interface interaction, which can effectively solve the bottleneck of multi-functional collaborative design, thereby completing the multi-material on-demand fixed-point design and analyzing the heterogeneous interface interaction mechanism according to the expected structural requirements.

[0008] A multi-material on-demand fixed-point design method based on heterogeneous interface interactions includes the following steps:

[0009] S1: Based on the target functional requirements, select the initial structure (interface parameters, macroscopic configuration parameters) and material type (constitutive parameters) from the existing database to establish a parametric initial three-dimensional model;

[0010] S2: The influence of stress and performance on heterogeneous interfaces is systematically studied by combining finite element method with microscale experiments on three-dimensional models.

[0011] S3: Reveal the mechanism of macroscopic configuration, microstructure, and chemical bond connection of the interface, and construct a theoretical model and design criteria for the fusion process of multi-material heterogeneous interfaces;

[0012] S4: Establish a multi-material digital model by combining solid-liquid interface fluid dynamics and chemical energy transfer laws;

[0013] S5: Combining multi-material voxelization modeling and 3D meshing techniques, develop adjustable material distribution models.

[0014] The location of heterogeneous interfaces, geometric parameters, material types and / or mating relationships of the structure can be obtained from the three-dimensional model.

[0015] S21. The breaking energy of chemical bonds at the heterogeneous interface is calculated by using molecular dynamics modeling, and a mapping relationship model between atomic arrangement structure and heterogeneous interface strength is established.

[0016] S22. The model is processed and subjected to cyclic stress of 0-500 MPa and temperature field of 20-800℃. The crack path is tracked in real time with sub-nanometer (~0.2 nm) resolution under in-situ transmission electron microscopy.

[0017] S23. A shear load of 0.1-5 μm / s is applied using a robotic arm, and the state change is monitored by acoustic emission signals. The crack propagation rate is measured under a laser confocal microscope.

[0018] S24. Finally, by integrating the results of molecular dynamics, in-situ transmission electron microscopy, and shearing experiments, a macro-micro cross-scale model was constructed to analyze the influence of elastic modulus on the stress concentration factor at the interface.

[0019] In S3, a cross-scale model was established, and the relationship between the tilt angle θ and the shear strength τ of the macroscopic model was established. It was verified that the tilt angle design can improve the interface strength. The evolution law of micro-defects was analyzed by combining dislocation dynamics theory. A fusion process model including the elastoplastic response of materials was constructed, and a matching criterion between the gradient transition layer thickness and the difference in elastic modulus was proposed.

[0020] S31. Based on molecular dynamics simulations of chemical bond breaking energy at the interface, combined with in-situ shear experiments, establish the relationship between macroscopic configuration tilt angle θ and interfacial shear strength. Quantitative relationship:

[0021]

[0022] In the formula, The reference shear strength is given by k, which is the configuration strengthening factor, typically taken as 0.1-0.5.

[0023] S32. Using dislocation dynamics theory, the evolution law of micro-defects under cyclic loading is analyzed, a theoretical model of heterogeneous interface fusion process incorporating nonlinear elastoplasticity of materials is constructed, and a design criterion for gradient transition layer thickness is proposed:

[0024]

[0025] In the formula, K t ρ is the stress concentration factor; α is the material constant, determined to be 1.38 through in-situ shear tests; d is the characteristic dimension of the gradient transition layer; ρ is the radius of curvature, ranging from 5 to 200 μm.

[0026] S41. Use microfluidic experiments to obtain data on the slip effect at the solid-liquid interface and establish microscale fluid dynamics control equations.

[0027] S42. Calculate the transmission loss rate of light / chemical energy at the heterogeneous interface using first-principles calculations and integrate it into the energy transfer efficiency model.

[0028] S43. Couple the fluid pressure distribution field, energy dissipation field and topological database to establish a multi-material constitutive parameter mapping relationship model.

[0029] In S5, an adaptive meshing technique is used to discretize the three-dimensional structure into voxel elements. One or more material properties are dynamically assigned to each voxel, and physical parameter gradient constraint rules are set between heterogeneous voxel elements. When the difference in elastic modulus between adjacent voxel materials exceeds the expected value, a transition layer is generated inside. The high stress risk area is visualized through a real-time feedback module to guide the adjustment of material distribution.

[0030] S6: The model is optimized using a multi-objective genetic algorithm with physical constraints, and the functionality of the on-demand fixed-point model is verified.

[0031] When executing a physical constraint genetic algorithm, prior design knowledge constraints need to be implanted during population initialization, and then the fitness function is defined as follows:

[0032]

[0033] In the formula, , , These are the weighting coefficients, and S represents interface strength, and FID represents functional integration.

[0034] Introducing simulated annealing mechanism to balance multi-objective conflicts, Accepting inferior solutions, annealing temperature according to Attenuation occurs, where the initial temperature Termination temperature t is the number of iterations.

[0035] The voxel clusters generated in the high-stress region of the tooth root should have a gradient distribution of voxel density along the principal stress direction; the tooth surface region achieves self-lubrication by controlling the lubricant retention characteristics through surface texture voxels; magnetic response material unit groups are arranged in the axial region to optimize the topological configuration of the closed magnetic circuit voxels; the nonlinear component gradient transition layer automatically generated at the heterogeneous interface has its concentration distribution function dynamically driven by the elastic modulus ratio.

[0036] The specific manifestation of realizing the on-demand fixed-point design model of multifunctional composite micro gears is as follows:

[0037] The voxel clusters generated in the high-stress region of the tooth root should have a gradient distribution of voxel density along the principal stress direction.

[0038] The tooth surface area achieves self-lubrication by controlling the lubricant retention characteristics through surface texture voxels;

[0039] Magnetic response material unit groups are arranged in the axial region to optimize the voxel topology of the closed magnetic circuit.

[0040] The nonlinear component gradient transition layer automatically generated at the heterogeneous interface has a concentration distribution function dynamically driven by the elastic modulus ratio.

[0041] The above objectives are achieved through the following technical solutions:

[0042] The beneficial effects of the multi-material on-demand fixed-point design method based on heterogeneous interface interactions in this invention are as follows:

[0043] By establishing a macro-micro interaction mechanism at heterogeneous interfaces and a collaborative design system for multi-material voxel distribution, the interface performance is significantly enhanced using tilt angle optimization and gradient layer criteria, achieving precise integration of multiple functions such as self-lubrication of micro gear tooth surfaces and magnetic response of the shaft. Based on intelligent algorithms, a transition layer is automatically generated to eliminate stress concentration, forming a closed-loop design method that combines theoretical modeling and experimental verification, addressing the industry pain points of low efficiency and difficulty in functional coordination in traditional trial-and-error design. Attached Figure Description

[0044] Figure 1 This is a diagram illustrating the process of establishing a digital model for on-demand fixed-point multi-material heterogeneous interfaces.

[0045] Figure 2 This is a diagram illustrating the process by which the performance of heterogeneous interfaces is affected.

[0046] Figure 3 This is a diagram illustrating the systematic process of establishing a multi-material digital model;

[0047] Figure 4 This is a diagram illustrating the process of voxelization modeling and transition layer generation;

[0048] Figure 5 This is a diagram illustrating the process of optimizing the model using a genetic algorithm. Detailed Implementation

[0049] A multi-material on-demand fixed-point design method based on heterogeneous interface interaction, combined with Figure 1 This includes the following steps:

[0050] Step 1: To study the interaction characteristics at heterogeneous interfaces, determine the material and structure types from the existing database of materials (interface parameters, macroscopic configuration parameters) and structure types (constitutive parameters), establish a three-dimensional model, and obtain the heterogeneous interface location, geometric parameters, material types, and mating relationships of the structure.

[0051] Step Two: Combining Figure 2 At the simulation level, for the mentioned three-dimensional model, the breaking energy of chemical bonds at the heterogeneous interface is calculated using molecular dynamics, and a mapping relationship model between atomic arrangement structure and heterogeneous interface strength is established accordingly.

[0052] In terms of experiments, samples of the mentioned three-dimensional model were prepared. The three-dimensional model was processed and subjected to cyclic stress of 0-500 MPa and temperature field of 20-800℃. The crack path was tracked at a sub-nanometer (~0.2 nm) resolution under in-situ transmission electron microscopy. Then, a shear load of 0.1-5 μm / s was applied using a robotic arm, and the state change was monitored by acoustic emission signals. The crack propagation rate was measured under a laser confocal microscope.

[0053] Finally, by combining the above data with the results of molecular dynamics, in-situ transmission electron microscopy, and interfacial shearing experiments, a macro-micro cross-scale model was constructed to quantitatively analyze the influence of differences in key parameters such as elastic modulus on the stress concentration factor.

[0054] Step 3: Combining Figure 3 Based on molecular dynamics simulations of chemical bond breaking energy at the interface, and combined with in-situ shear experiments, a relationship between the macroscopic configuration tilt angle θ and the interfacial shear strength was established. Quantitative relationship:

[0055]

[0056] In the formula, The reference shear strength is given by k, which is the configuration strengthening factor, typically taken as 0.1-0.5.

[0057] Using dislocation dynamics theory, the evolution of micro-defects under cyclic loading is analyzed, a theoretical model of heterogeneous interface fusion process incorporating nonlinear elastoplastic properties of materials is constructed, and a design criterion for gradient transition layer thickness is proposed.

[0058]

[0059] In the formula, K t ρ is the stress concentration factor; α is the material constant, determined to be 1.38 through in-situ shear tests; ρ is the radius of curvature, ranging from 5 to 200 μm.

[0060] The material concentration distribution function of the transition layer is specifically as follows:

[0061]

[0062] Where C1 and C2 are the concentrations of adjacent voxel materials, L is the length (i.e., thickness) of the transition layer, and x is the coordinate along the thickness direction of the transition layer. The attenuation coefficient λ is determined by the ratio of the elastic moduli of adjacent voxel materials. Dynamic calculation determines ( (κ is the proportionality coefficient).

[0063] Step 4: Combining solid-liquid interface fluid dynamics and chemical energy transfer principles, establish a multi-material digital model, which includes:

[0064] Microfluidic experiments were used to obtain data on the slip effect at the solid-liquid interface, and microscale fluid dynamics control equations were established.

[0065] The transmission loss rate of light / chemical energy at the heterogeneous interface is calculated using first-principles calculations and integrated into the energy transfer efficiency model.

[0066] By coupling the fluid pressure distribution field, energy dissipation field, and topological database, a multi-material constitutive parameter mapping model is established.

[0067] Step 5: Combining Figure 4 The three-dimensional structure is discretized into voxel units using adaptive mesh generation technology. One or more material properties (including elastic modulus, interfacial energy, and thermal conductivity) are dynamically assigned to each voxel. Gradual constraint rules for physical parameters between heterogeneous voxel units are set. When the difference in elastic modulus between adjacent voxel materials exceeds the expected value, such as when the parameter difference between different regions is ≥20%, a transition layer will be generated internally to complete the voxel modeling.

[0068] Step Six: Combining Figure 5 A genetic algorithm was used to optimize the model, and the functionality of the on-demand fixed-point model was verified. When executing the physical constraint genetic algorithm, the prior model during planting was initialized, a multi-objective fitness function was constructed, a simulated annealing mechanism was introduced to balance optimization conflicts, a temperature decay function was set, and the three-dimensional reconstruction of the model was achieved through optimization. The performance of the reconstructed model was then verified.

[0069] When initializing the algorithm population, a rule-based sampling method is used, directly embedding prior design knowledge as hard constraints to ensure that all initial solutions are valid. Specifically, the prior design knowledge constraints are:

[0070] For gear structures, the yield strength of the material or its composite used in the tooth root region shall be ≥800 MPa;

[0071] For tooth surface areas with frictional contact, the selected material or its composite should have a friction coefficient ≤0.15 under specified working conditions;

[0072] For the axial region requiring magnetic function, the saturation magnetization of the selected material or its composite should be ≥1.2 T.

[0073] Calculate the fitness of each individual (i.e., each material distribution scheme). Define the fitness function F as:

[0074]

[0075] In the formula, , , These are the weighting coefficients, and S represents interface strength, and FID represents functional integration.

[0076] To balance multiple conflicting objectives and enhance the algorithm's ability to escape local optima, a simulated annealing mechanism is introduced to balance multi-objective conflicts. Accepting inferior solutions, annealing temperature according to Attenuation occurs, where the initial temperature Termination temperature t is the number of iterations.

[0077] After the optimization iteration is completed, the optimal solution in the Pareto solution set is post-processed:

[0078] The opening and closing operations in image morphology are used to filter out isolated, manufacturing-infeasible single material voxel points, ensuring the continuity of the material region;

[0079] Based on the aforementioned design criteria, all automatically generated gradient transition layers were verified to ensure that their thickness and concentration distribution functions conformed to physical laws.

[0080] The cleaned and validated material distribution model is imported into additive manufacturing slicing software for virtual manufacturing. Check for unprintable overhangs, unsupported critical overhang angles, or areas requiring additional support to ensure the design is compatible with the selected manufacturing process and is manufacturable.

[0081] The post-processed model is re-imported into finite element analysis software (ANSYS, ABAQUS, etc.), real working condition loads are applied for verification calculations, and the performance is compared with the initial design to verify the optimization effect.

Claims

1. A multi-material on-demand fixed-point design method based on heterogeneous interface interactions, characterized in that, Includes the following steps: S1: Based on the target functional requirements, select the initial structure and material type from the existing database to establish a parametric initial three-dimensional model; S2: The influence of stress and performance on heterogeneous interfaces is systematically studied by combining finite element method with microscale experiments on three-dimensional models. S3: Reveal the mechanism of macroscopic configuration, microstructure, and chemical bond connection of the interface, and construct a theoretical model and design criteria for the fusion process of multi-material heterogeneous interfaces; S4: To meet the specific requirements of self-lubrication and optical / chemical energy transfer, a multi-material digital model is established by combining solid-liquid interface fluid dynamics and chemical energy transfer laws. S5: Combining multi-material voxel modeling and 3D meshing techniques to develop adjustable material distribution models; In S3, based on the cross-scale model established in S2, the relationship between the macroscopic model tilt angle θ and the shear strength τ is established to verify that the tilt angle design can improve the interface strength. The evolution law of microscopic defects is analyzed by combining dislocation dynamics theory, a fusion process model including the material's elastoplastic response is constructed, and a matching criterion between the gradient transition layer thickness and the difference in elastic modulus is proposed. S31. Based on molecular dynamics simulations of chemical bond breaking energy at the interface, combined with in-situ shear experiments, establish the relationship between macroscopic configuration tilt angle θ and interfacial shear strength. Quantitative relationship: In the formula, The reference shear strength is given by k, which is the configuration strengthening factor, typically taken as 0.1-0.

5. S32. Using dislocation dynamics theory, the evolution law of micro-defects under cyclic loading is analyzed, a theoretical model of heterogeneous interface fusion process incorporating nonlinear elastoplasticity of materials is constructed, and a design criterion for gradient transition layer thickness is proposed: In the formula, K t ρ is the stress concentration factor; α is the material constant, determined to be 1.38 through in-situ shear tests; d is the characteristic dimension of the gradient transition layer; ρ is the radius of curvature, ranging from 5 to 200 μm. S41. Use microfluidic experiments to obtain data on the slip effect at the solid-liquid interface and establish microscale fluid dynamics control equations. S42. Calculate the transmission loss rate of light / chemical energy at the heterogeneous interface using first-principles calculations and integrate it into the energy transfer efficiency model. S43. Couple the fluid pressure distribution field, energy dissipation field and topological database to establish a multi-material constitutive parameter mapping model; In S5, an adaptive meshing technique is used to discretize the three-dimensional structure into voxel units. One or more material properties are dynamically assigned to each voxel, and physical parameter gradient constraint rules are set between heterogeneous voxel units. When the difference in elastic modulus between adjacent voxel materials exceeds the expected value, a transition layer is generated internally. The high-stress risk area is visualized through a real-time feedback module to guide the adjustment of material distribution.

2. The multi-material on-demand fixed-point design method based on heterogeneous interface interaction according to claim 1, characterized in that, The location of the heterogeneous interface, geometric parameters, material type, and mating relationships of the structure can be obtained from the three-dimensional model.

3. The multi-material on-demand fixed-point design method based on heterogeneous interface interaction according to claim 1, characterized in that, S21. The breaking energy of chemical bonds at the heterogeneous interface is calculated by using molecular dynamics modeling, and a mapping relationship model between atomic arrangement structure and heterogeneous interface strength is established. S22. The model is processed and subjected to cyclic stress of 0-500 MPa and temperature field of 20-800℃. The crack path is tracked in real time with sub-nanometer resolution under in-situ transmission electron microscopy. S23. A shear load of 0.1-5 μm / s is applied using a robotic arm, and the state change is monitored by acoustic emission signals. The crack propagation rate is measured under a laser confocal microscope. S24. Finally, by integrating the results of molecular dynamics, in-situ transmission electron microscopy, and shearing experiments, a macro-micro cross-scale model was constructed to analyze the influence of elastic modulus on the stress concentration factor at the interface.

4. The multi-material on-demand fixed-point design method based on heterogeneous interface interaction according to any one of claims 1 to 3, characterized in that, S6: A multi-objective genetic algorithm optimization model with physical constraints is adopted; prior design knowledge is implanted as a hard constraint when initializing the population, and a fitness function with interface strength, functional integration degree and stress concentration coefficient as the core objectives is constructed; a simulated annealing mechanism is introduced to balance multi-objective conflicts and avoid local optima; the optimization results are post-processed and manufacturability verified.

5. The multi-material on-demand fixed-point design method based on heterogeneous interface interaction according to claim 4, characterized in that, When executing a physical constraint genetic algorithm, prior design knowledge constraints need to be implanted during population initialization, and then the fitness function is defined as follows: In the formula, , , These are the weighting coefficients, and ; S represents interface strength, and FID represents functional integration. Introducing simulated annealing mechanism to balance multi-objective conflicts, Accepting inferior solutions, annealing temperature according to Attenuation occurs, where the initial temperature Termination temperature t is the number of iterations.

6. The multi-material on-demand fixed-point design method based on heterogeneous interface interaction according to claim 4, characterized in that, The voxel clusters generated in the high-stress region of the tooth root should have a gradient distribution of voxel density along the principal stress direction; the tooth surface region achieves self-lubrication by controlling the lubricant retention characteristics through surface texture voxels; magnetic response material unit groups are arranged in the axial region to optimize the topological configuration of the closed magnetic circuit voxels; the nonlinear component gradient transition layer automatically generated at the heterogeneous interface has its concentration distribution function dynamically driven by the elastic modulus ratio.

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