A method and system for near-field dynamic heterogeneous simulation of a concrete beam

Abstract

The application discloses a kind of concrete beam's near-field dynamics heterogeneous simulation method and system, comprising: obtaining the analysis model of concrete beam, and the analysis model is dispersed into material point in space;The material point is traversed, and the range of the analysis model is divided into aggregate particle area and non-aggregate particle area, wherein the aggregate particle area includes different sizes aggregate particles, and the non-aggregate particle area includes the gap between the aggregate particle area;According to the range of the material point on the analysis model, different material properties are configured to the material point, wherein the material point of the aggregate particle area is configured with aggregate material properties, and the material point of the non-aggregate particle area is configured with matrix material properties;According to the material properties, the near-field dynamics heterogeneous simulation of the concrete beam is carried out.Reduce the distribution of aggregate particles in real situation, improve simulation accuracy.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology for concrete materials, and in particular to a method and system for simulating the near-field dynamics of heterogeneous concrete beams. Background Technology

[0002] Concrete beams are composed of matrices and particles of varying sizes and materials, so using homogeneous modeling methods may lead to significant simulation errors. Homogeneous modeling methods assume that the materials are uniform and cannot reflect the true properties of the materials, especially when dealing with complex structures or material compositions, such as particle distribution and pore structure in concrete.

[0003] Current methods for simulating non-homogeneous aggregates do not take into account the actual distribution of aggregate particles, which leads to reduced simulation accuracy. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for simulating the near-field dynamics of concrete beams in heterogeneous environments, so as to improve the accuracy of the simulation.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for simulating near-field dynamics in heterogeneous concrete beams, the method comprising:

[0006] Obtain the analysis model of the concrete beam and discretize the analysis model into material points in space;

[0007] The material points are traversed to divide the scope of the analysis model into aggregate particle area and non-aggregate particle area, wherein the aggregate particle area includes aggregate particles of different sizes and the non-aggregate particle area includes the gaps between the aggregate particle areas.

[0008] Based on the range of the material points on the analysis model, different material properties are configured for the material points, wherein the material points in the aggregate particle area are configured with aggregate material properties, and the material points in the non-aggregate particle area are configured with matrix material properties.

[0009] Based on the material properties, a near-field dynamic heterogeneous simulation of the concrete beam was performed.

[0010] In one embodiment, the step of traversing the material points to divide the scope of the analysis model into aggregate particle region and non-aggregate particle region includes:

[0011] Based on the range of the analytical model, determine the baseline value for aggregate particle content;

[0012] For any material point, generate a random integer corresponding to that material point. If the random integer is less than or equal to the aggregate particle content benchmark value, mark the material point as the center of the aggregate particle circle, and randomly select a radius to generate the circumcircle of the aggregate particle. Each random integer is not greater than the total number of all material points.

[0013] Intersection is determined based on the distance between the centers of the newly generated circumcircle of the aggregate particle and the already generated circumcircle of the aggregate particle, and the target circumcircle of the aggregate particle is determined based on the judgment result.

[0014] Traverse each of the material points until the aggregate particle region formed by the outer circle of each of the target aggregate particles and the non-aggregate particle region formed by the gap between the outer circles of each of the target aggregate particles are obtained.

[0015] In one embodiment, the method for determining the benchmark value of aggregate particle content includes:

[0016]

[0017] Where n is the baseline value of aggregate particle content, V is the average radius of the aggregate particles, V is the total volume of the analysis model, and c is the volume content of the aggregate particles in the analysis model.

[0018] In one embodiment, the random selection of radius includes randomly selecting the smallest radius of aggregate particles in the actual aggregate particles; the step of determining the intersection of the newly generated aggregate particle circumcircle and the already generated aggregate particle circumcircle based on the center distance, and determining the target aggregate particle circumcircle based on the determination result, includes:

[0019] If the distance between the centers is greater than or equal to the sum of the radii of the newly generated circumcircle of the aggregate particle and the circumcircle of the already generated aggregate particle, then the newly generated circumcircle of the aggregate particle is determined to be the target aggregate particle circumcircle.

[0020] If the center distance is less than the sum of the radii of the newly generated aggregate particle's circumcircle and the already generated aggregate particle's circumcircle, and the center distance is greater than or equal to the sum of the minimum radius of the aggregate particle and the radius of the already generated aggregate particle's circumcircle, then the radius of the newly generated aggregate particle's circumcircle is adjusted to the minimum radius of the aggregate particle, and the adjusted aggregate particle's circumcircle is determined as the target aggregate particle's circumcircle.

[0021] In one embodiment, before performing near-field dynamic heterogeneous simulation of the concrete beam, the method further includes determining the degree of local damage, wherein determining the degree of local damage includes:

[0022] Based on the material properties corresponding to the material points, determine the target bond critical elongation of adjacent material points;

[0023] The critical elongation of the target bond and the bond elongation of the corresponding material point are compared to determine the value of the bond state function corresponding to the material point.

[0024] The degree of local damage is determined by integrating the obtained value over a unit volume.

[0025] In one embodiment, determining the target bond critical elongation of adjacent material points based on the material properties corresponding to the material points includes:

[0026] Determine the bond type of adjacent material points based on the material properties corresponding to the material points;

[0027] When the bond types are of the same type, the target critical elongation rate is determined according to a preset critical elongation rate model.

[0028] When the bond type is heterogeneous, an initial critical bond elongation rate is determined according to a preset critical bond elongation rate model, and the target critical bond elongation rate is determined according to the initial critical bond elongation rate combined with a preset weakening coefficient, wherein the weakening coefficient is a parameter characterizing the point bond strength of the substance.

[0029] In one embodiment, the bond critical elongation model is:

[0030]

[0031] Among them, f t f represents the tensile strength material property corresponding to a material point. c Let ξ be the compressive strength material property corresponding to the material point, E be the elastic modulus material property corresponding to the material point, and s(ξ) be the bond elongation.

[0032] Secondly, embodiments of the present invention provide a near-field dynamic heterogeneous simulation system for concrete beams, the system comprising:

[0033] The model discretization module is used to obtain the analysis model of the concrete beam and discretize the analysis model into material points in space.

[0034] The aggregate partitioning module is used to traverse the material points and divide the scope of the analysis model into aggregate particle area and non-aggregate particle area. The aggregate particle area includes aggregate particles of different sizes, and the non-aggregate particle area includes the gaps between the aggregate particle areas.

[0035] The material configuration module is used to configure different material properties for the material points according to their range on the analysis model, wherein the material points in the aggregate particle area are configured with aggregate material properties, and the material points in the non-aggregate particle area are configured with matrix material properties.

[0036] The iterative solution module is used to perform near-field dynamic heterogeneous simulation of the concrete beam based on the material properties.

[0037] Thirdly, embodiments of the present invention provide an electronic device, including...

[0038] memory,

[0039] processor, and

[0040] A computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the near-field dynamics heterogeneous simulation method for concrete beams as described in any of the preceding claims.

[0041] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the near-field dynamics heterogeneous simulation method for concrete beams as described in any of the preceding claims.

[0042] Compared with existing technologies, the beneficial effects of the near-field dynamic heterogeneous simulation method and system for concrete beams provided by this invention are as follows:

[0043] This invention obtains an analysis model of a concrete beam and discretizes it into spatial material points. By discretizing the concrete beam into spatial material points, the distribution of aggregate particles inside the concrete beam can be simulated more realistically, which helps to simulate the damage evolution of the concrete beam material. Next, the material points are traversed, dividing the analysis model into aggregate particle regions and non-aggregate particle regions. The aggregate particle regions include aggregate particles of different sizes, and the non-aggregate particle regions include the gaps between the aggregate particle regions. Considering that the difference in particle size has a significant impact on the performance of concrete materials, this invention, by traversing the material points, can simulate aggregate particles of different sizes in the analysis model, more accurately reflecting the damage status of the simulated concrete beam structure, making the simulation results more accurate. Then, according to the range of the material points in the analysis model, different material properties are configured for the material points. Material points in the aggregate particle regions are configured with aggregate material properties, and material points in the non-aggregate particle regions are configured with matrix material properties. By configuring different material properties, the mechanical response of different areas in the concrete structure can be captured more accurately, making the simulation results more accurately reflect the actual situation of different parts of the concrete structure. Finally, based on the aforementioned material properties, a near-field dynamic heterogeneous simulation of the concrete beam is performed. Different failure conditions can be set for different material properties to promptly identify the risk of cracking and failure in the concrete beam. Attached Figure Description

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

[0045] Figure 1 A flowchart illustrating a non-homogeneous near-field dynamics simulation method for concrete beams provided in an embodiment of the present invention;

[0046] Figure 2 This is a flowchart illustrating step S102 provided in an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of the process for determining the circumcircle of a target aggregate particle according to an embodiment of the present invention;

[0048] Figure 4 A schematic diagram of the process for determining the degree of local damage provided in an embodiment of the present invention;

[0049] Figure 5 This is a flowchart illustrating step S401 provided in an embodiment of the present invention;

[0050] Figure 6 This is a real-world experimental scenario;

[0051] Figure 7 This is a diagram showing the material property distribution and cracking situation of Comparative Example 1;

[0052] Figure 8 This is a diagram showing the material property distribution and cracking situation of Comparative Example 2;

[0053] Figure 9 This is a diagram showing the material property distribution and cracking situation in an embodiment.

[0054] Figure 10 This is a comparison chart of the simulation results;

[0055] Figure 11 A block diagram of a non-homogeneous near-field dynamics simulation system for a concrete beam provided in an embodiment of the present invention;

[0056] Figure 12 This is a schematic diagram of the internal structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0057] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0058] Obviously, the accompanying drawings described below are merely some examples or embodiments of the present invention. Those skilled in the art can apply the present invention to other similar scenarios based on these drawings without any inventive effort. Furthermore, it is understood that although the efforts made in this development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this invention, modifications to design, manufacturing, or production based on the technical content disclosed in this invention are merely conventional technical means and should not be construed as insufficient disclosure of the present invention.

[0059] In this invention, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this invention may be combined with other embodiments without conflict.

[0060] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "a," "an," "an," "the," and similar words used in this invention do not indicate quantity limitation and may indicate singular or plural. The terms "comprising," "including," "having," and any variations thereof used in this invention are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms "connected," "linked," "coupled," and similar words used in this invention are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "A plurality" in this invention refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships may exist; for example, "A and / or B" can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following objects have an "or" relationship. The terms "first," "second," and "third" used in this invention are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0061] This invention provides a method and system for simulating the near-field dynamics of a concrete beam in a heterogeneous manner.

[0062] In a first aspect, embodiments of the present invention provide a method for simulating the near-field dynamics of a concrete beam in a heterogeneous environment. Figure 1 This is a flowchart illustrating a non-homogeneous near-field dynamics simulation method for concrete beams provided in an embodiment of the present invention, as shown below. Figure 1 As shown, the method includes the following steps:

[0063] Step S101: Obtain the analysis model of the concrete beam and discretize the analysis model into material points in space.

[0064] Discretized analysis models can better capture the microscopic details inside concrete beams, including crack propagation and localized failure, thus providing more realistic and accurate simulation results. Specifically, based on the actual size and shape of the concrete beam, a corresponding region needs to be defined in three-dimensional space to obtain the analysis model of the concrete beam. Starting from the edge of the region, the models are delineated at a preset spacing d. x Material points are generated sequentially, with a total of N material points in the model, ensuring that the distribution of material points can fully reflect the heterogeneity and complex structure of the concrete beam.

[0065] Step S102: Traverse the material points and divide the scope of the analysis model into aggregate particle area and non-aggregate particle area. The aggregate particle area includes aggregate particles of different sizes, and the non-aggregate particle area includes the gaps between aggregate particle areas.

[0066] In concrete beams, aggregate particles of varying sizes exist, and these aggregate and non-aggregate regions exhibit different deformation characteristics and failure modes. To realistically represent material properties and improve simulation accuracy, specifically, by traversing the material points, aggregate particles of different sizes can be simulated in the analysis model. This allows the simulation results to more accurately reflect the particle size distribution in actual concrete beams. Generally, aggregate particles typically possess higher stiffness and strength, while non-aggregate particles have lower stiffness and strength. By distinguishing the material points into aggregate and non-aggregate regions, the mechanical behavior of concrete structures can be simulated more accurately.

[0067] Figure 2 This is a flowchart illustrating step S102 provided in an embodiment of the present invention, as shown below. Figure 2 As shown, in Figure 1 Based on the process shown, step S102 includes the following steps:

[0068] Step S201: Determine the benchmark value of aggregate particle content based on the range of the analysis model.

[0069] In concrete beams, the content of aggregate particles has a significant impact on the mechanical properties and behavior of concrete. Different types and proportions of aggregate particles will have different effects on the performance of concrete beams. Therefore, it is necessary to determine the baseline value of aggregate particle content based on the scope of the analysis model, including the volume of the analysis model and the proportion of aggregate particles in the model. This allows for comparison of analysis results under different conditions and facilitates the simulation of the deformation and failure process of concrete beams.

[0070] In one embodiment, the method for determining the benchmark value of aggregate particle content includes:

[0071]

[0072] Where n is the baseline value of aggregate particle content, V is the average radius of the aggregate particles, V is the total volume of the analysis model, and c is the volume content of the aggregate particles in the analysis model.

[0073] Specifically, by comprehensively considering the aggregate particle volume content, average aggregate particle radius, and total volume of the analysis model, a benchmark value for aggregate particle content was determined by quantifying the distribution and content of aggregate particles in the concrete beam. This benchmark value serves as an indicator to assess the distribution of aggregate particles in the concrete beam, contributing to a more accurate analysis and design of concrete structures.

[0074] Step S202: For any material point, generate a random integer corresponding to that material point. If the random integer is less than or equal to the aggregate particle content benchmark value, mark any material point as the center of the aggregate particle circle, and randomly select a radius to generate the circumcircle of the aggregate particle. Each random integer is not greater than the total number of all material points.

[0075] Specifically, for each matter point p i Generate a random integer n between [0, N]. i To ensure that each material point has a chance to become a candidate for the center of an aggregate particle, the random generation method can be the rand() function, where n... i When n ≤ n, mark the material point as the center of the aggregate particle. For the material point marked as the center of the aggregate particle, randomly select a radius r. i A circumcircle of the aggregate particles is generated with this point as the center. The randomly selected radius can be based on the minimum radius r of the aggregate particles in the actual aggregate. min Average radius of aggregate particles and the maximum radius r of aggregate particles max The selection is made within the range of particles. This method can simulate the distribution of aggregate particles and randomly select the size of aggregate particles, thereby simulating the distribution of aggregates in heterogeneous materials to a certain extent, better simulating the characteristics of real aggregate particles, and making the simulation results closer to reality.

[0076] Step S203: Based on the center distance between the newly generated circumcircle of the aggregate particle and the already generated circumcircle of the aggregate particle, perform an intersection judgment and determine the target aggregate particle circumcircle based on the judgment result.

[0077] In heterogeneous materials, aggregate particles are typically adjacent or dispersed and do not overlap. To accurately simulate such heterogeneous materials, it is necessary to determine the intersection of the circumcircle of the newly generated aggregate particles with the circumcircle of the already generated aggregate particles based on the distance between their centers, and then determine the circumcircle of the target aggregate particles based on the determination result.

[0078] Figure 3 This is a schematic diagram of the process for determining the circumcircle of a target aggregate particle according to an embodiment of the present invention, as shown below. Figure 3 As shown, in Figure 2Based on the process shown, determining the circumcircle of the target aggregate particle includes the following steps:

[0079] Step S301: If the center distance is greater than or equal to the sum of the radii of the newly generated aggregate particle circumcircle and the already generated aggregate particle circumcircle, then the newly generated aggregate particle circumcircle is determined as the target aggregate particle circumcircle.

[0080] Step S302: If the center distance is less than the sum of the radii of the newly generated aggregate particle's circumcircle and the already generated aggregate particle's circumcircle, and the center distance is greater than or equal to the sum of the minimum radius of the aggregate particle and the radius of the already generated aggregate particle's circumcircle, then the radius of the newly generated aggregate particle's circumcircle is adjusted to the minimum radius of the aggregate particle, and the adjusted aggregate particle's circumcircle is determined as the target aggregate particle's circumcircle.

[0081] For example, when the (i+1)th material point p is marked i+1 Using the circle as the center and randomly selecting a radius r i+1 Next, it is necessary to determine whether the circumcircle of the newly generated aggregate particles intersects with the circumcircle of the already generated aggregate particles. This can be done by calculating whether the distance D between the centers of the two circles is greater than or equal to the sum of the radii r of the two circles. i +r i+1 To achieve this.

[0082] If D≥r i +r i+1 If the two circles do not intersect, the newly generated circumcircle of the aggregate particle is retained and determined as the circumcircle of the target aggregate particle.

[0083] If D < r i +r i+1 , indicates that two circles intersect. Next, it is necessary to determine whether D is greater than or equal to the minimum spacing r. min .

[0084] If D≥r i +r min Then the radius r of the circumcircle of the newly generated aggregate particles can be adjusted. i+1 For r min Then, retain the newly generated circumcircle of the aggregate particles and determine the adjusted circumcircle of the aggregate particles as the target circumcircle of the aggregate particles.

[0085] If D < r i +r min If the newly generated aggregate particle's circumcircle is deleted, the process continues to traverse the next material point.

[0086] It is important to note that during the traversal, for each newly generated aggregate particle's circumcircle p... iIt is necessary to perform intersection checks with the first i-1 already determined target aggregate particles' circumcircles to ensure that all generated target aggregate particles' circumcircles do not overlap or cover each other, thereby more accurately simulating the distribution of aggregate particles in heterogeneous materials.

[0087] Continue to refer to Figure 2 Step S204 is executed after step S203, as follows.

[0088] Step S204: Traverse each material point until the aggregate particle area formed by the outer circle of each target aggregate particle and the non-aggregate particle area formed by the gap between the outer circles of each target aggregate particle are obtained.

[0089] Specifically, during the process of traversing the material points, each point is evaluated to obtain the final target aggregate particles. After the traversal is complete, the aggregate particle regions formed by the circumcircle of each target aggregate particle are obtained. These aggregate particle regions are areas enclosed by the circumcircle of the target aggregate particles, simulating the actual aggregate particles present in materials such as concrete. In addition, the gaps between the target aggregate particles also need to be considered. These gaps are formed by the voids between the circumcircles of adjacent aggregate particles and belong to the non-aggregate particle region.

[0090] Continue to refer to Figure 1 Step S103 is executed after step S102, as follows.

[0091] Step S103: Based on the range of the material points on the analysis model, configure different material properties for the material points. Specifically, material points in the aggregate particle area are configured with aggregate material properties, while material points in the non-aggregate particle area are configured with matrix material properties.

[0092] In concrete beam structures, the differences in properties between aggregate particles and non-aggregate particles lead to variations in mechanical behavior across different regions. Since aggregate particles typically possess higher stiffness and strength, while non-aggregate particles have relatively lower strength, it is necessary to configure different material properties for material points, including but not limited to material density, elastic modulus, tensile strength, or compressive strength, in order to more realistically reproduce material properties in the simulation of non-homogeneous concrete beams.

[0093] Step S104: Based on the material properties, perform a near-field dynamic heterogeneous simulation of the concrete beam.

[0094] Traditional finite element methods struggle to accurately describe material heterogeneity. Therefore, peri-field dynamic equations are introduced to better simulate this heterogeneity. Specifically, different failure conditions can be set based on material properties. The displacement, velocity, and bond elongation of material points are iteratively solved using pre-defined peri-field dynamic equations. This allows for the determination of whether the bonds at the material points meet the failure conditions, identifying the degree of local damage, and promptly detecting the risk of cracking in concrete beams, thus more realistically simulating the deformation and failure process of concrete beams.

[0095] Specifically, by employing an adaptive dynamic relaxation algorithm, the computational parameters can be adaptively adjusted based on the collected dynamic behavior. This allows for real-time updates of the material's state by iteratively solving for displacement, velocity, and bond elongation, thereby better capturing the changes in the material at different time steps, including displacement, velocity, and bond deformation. Therefore, it enables more accurate near-field dynamic heterogeneous simulation of concrete beams.

[0096] An adaptive dynamic relaxation algorithm is employed to transform the near-field dynamic equations into ordinary differential equations by setting a virtual diagonal density matrix and a virtual damping coefficient.

[0097]

[0098] Where Λ is the virtual diagonal density matrix, d is the virtual damping coefficient, and X is the coordinate of the material point, denoted as X. T ={x1,x2,x3,……,x m}, Let X be the acceleration of the substance point X at time t. Let X be the velocity of the substance point X at time t, and U be the displacement of the substance point, expressed as... m is the number of all material points in the calculation area, F is the resultant force density on material point X, and t is the time step, preferably t=1.

[0099] Elements in the virtual diagonal density matrix Λ satisfy:

[0100]

[0101] Among them, K ij Let i be the stiffness matrix, and j represent the indexes of different material points.

[0102] Iterative solution refers to using central difference to solve for the velocity and displacement of a material point at each time step. If the preset number of iterations is not met, the velocity and displacement at the next time step are solved iteratively, as shown below:

[0103]

[0104]

[0105] in, For the velocity of the next time step, Let d be the displacement at the next time step, n be the nth iteration, Δt be the time step size, and d be the displacement at the next time step. n F represents the virtual damping coefficient that changes dynamically during the nth iteration calculation. n This represents the resultant force of material point X during the nth iteration calculation.

[0106]

[0107] in, This is the diagonal local stiffness matrix.

[0108]

[0109]

[0110] η represents the relative displacement between any two material points, and ξ represents the bond length between any two material points. The bond elongation can be solved iteratively based on the displacement in the next time step.

[0111] Therefore, it is possible to adaptively adjust the calculation parameters according to the dynamic behavior of material points, and to accurately perform near-field dynamic heterogeneous simulation of concrete beams.

[0112] Figure 4 This is a schematic diagram of the process for determining the degree of local damage provided in an embodiment of the present invention, as shown below. Figure 4 As shown, in Figure 1 Based on the illustrated process, before performing near-field dynamic heterogeneous simulation of the concrete beam, this method further includes determining the degree of local damage. Determining the degree of local damage includes the following steps:

[0113] Step S401: Determine the critical elongation of the target bond of adjacent material points based on the material properties corresponding to the material points.

[0114] Specifically, determining the target bond critical elongation of adjacent material points based on material properties is crucial for calculating the cumulative damage to these points using different fracture criteria in damage assessment. Different bonds have different critical elongation rates, and critical elongation is an important parameter for evaluating a material's tensile fracture resistance.

[0115] Figure 5 This is a flowchart illustrating step S401 provided in an embodiment of the present invention, as shown below. Figure 5 As shown, in Figure 4 Based on the process shown, step S401 includes the following steps:

[0116] Step S501: Determine the bond type of adjacent material points based on the material properties corresponding to the material points.

[0117] Step S502: When the bond type is the same, determine the target critical elongation rate of the bond according to the preset critical elongation rate model.

[0118] Step S503: When the bond type is heterogeneous, determine the initial critical elongation rate of the bond according to the preset critical elongation rate model, and determine the target critical elongation rate of the bond according to the initial critical elongation rate combined with the preset weakening coefficient, wherein the weakening coefficient is a parameter characterizing the point bond strength of the substance.

[0119] Specifically, first, it is determined whether the material points at both ends of the bond belong to the same material property. If the material points at both ends of the bond belong to the same aggregate material property or matrix material property, then the bond type is determined to be the same type of bond, and the critical elongation of the target bond can be directly determined using the parameters of the aggregate material property or the matrix material property. If the material points at both ends of the bond do not belong to the same material property, then the bond type is determined to be the opposite type of bond, and the critical elongation s of the first initial bond needs to be determined according to the parameters of the aggregate material property. t1 And determine the critical elongation s of the second initial bond based on the parameters of the matrix material properties. t2 Then, the critical elongation of the target bond is determined by combining the preset weakening coefficient ψ. Here, the critical elongation of the two initial bonds is added together and multiplied by the weakening coefficient ψ to obtain the critical elongation of the target bond. This method considers the material properties of the material points at both ends of the bond, thus enabling the differentiation between homogeneous and heterogeneous bonds based on actual conditions, and the use of corresponding parameters for calculation. This helps improve the accuracy of the simulation results. Furthermore, by introducing the weakening coefficient ψ, the critical elongation of the target bond can be adjusted when considering different material properties, making the simulation more flexible.

[0120] In one embodiment, the bond critical elongation model is as follows:

[0121]

[0122] Among them, f t f represents the tensile strength material property corresponding to a material point. c Let ξ be the compressive strength material property corresponding to the material point, E be the elastic modulus material property corresponding to the material point, and s(ξ) be the bond elongation.

[0123] Continue to refer to Figure 4 Step S402 is executed after step S401, as follows.

[0124] Step S402: Compare the critical elongation of the target bond with the bond elongation of the corresponding material point to determine the value of the bond state function corresponding to the material point.

[0125] Specifically, s is the bond elongation of a material point, η is the relative displacement between any two material points, and ξ is the bond length between any two material points.

[0126] If the bond elongation is less than or equal to the target bond critical elongation (s≤s) t If the bond elongation does not reach or exceed the critical value, the bond is still within an acceptable range and has not broken or failed. The bond state function takes the value of μ=1. If the bond elongation is greater than the target bond critical elongation (s>s), then the bond is considered to be in a state where μ is within the acceptable range and has not broken or failed. t When μ = 0, it means that the elongation of the bond exceeds the critical value, the bond has broken or failed, and the condition for the bond state function to take the value is μ = 0.

[0127] Step S403: Determine the degree of local damage based on the integral of the measured value within a unit volume.

[0128] Specifically, the degree of local damage is characterized by the integral of the number of broken bonds per unit volume, representing the degree of local damage to the material at the current spatial location. The degree of local damage D(x,t) at material point x at time t is:

[0129]

[0130] Among them, H x For a selected near-field region with radius δ, V x It represents the volume formed by all matter points within the near-field region.

[0131] The effects of this invention will be described below in conjunction with specific application scenarios. See also... Figure 6 , Figure 6 For a realistic test scenario, in this specific application, the concrete beam dimensions are 400mm*100mm*100mm, the overall elastic modulus of the concrete beam is E=35MPa, and the overall density is ρ=2800kg / m3; among which, the elastic modulus of the cement-fine aggregate matrix is ​​E1=29MPa, and the density is ρ1=2500kg / m3. 3 The elastic modulus of the coarse aggregate matrix is ​​E2 = 41 MPa, and its density is ρ2 = 3000 kg / m³. 3 The loading method was displacement loading, with a pressure head compression rate of 2 mm / min. Three-point bending tests were conducted on concrete beams, and different heterogeneous modeling methods were compared through multiple simulations. Detailed analysis is now provided for Example 1, Comparative Example 2, and the embodiment:

[0132] Comparative Example 1: Conventional homogeneous modeling method;

[0133] The concrete beam was simulated using the overall modulus of elasticity and overall density. (See [link]) Figure 7 The diagram shows the distribution of material properties and the cracking situation.

[0134] Comparative Example 2: Heterogeneous modeling method without considering particle size;

[0135] Simulations were performed using material information from both cement-fine aggregate matrix and coarse aggregate, as detailed in publication number CN115600385A. However, the influence of particle size was not considered. Figure 8 The diagram shows the distribution of material properties and the cracking situation.

[0136] Example: Heterogeneous Modeling Method Considering Particle Size

[0137] Information on both cement-fine aggregate matrix and coarse aggregate was used, and the effect of particle size was considered. See [link / reference]. Figure 9 The diagram shows the distribution of material properties and the cracking situation.

[0138] See simulation results Figure 10 Therefore, it is evident that Comparative Example 1, due to its homogeneous modeling method, may not accurately reflect the influence of different components within the concrete, leading to significant differences between the crack propagation mode and load-displacement curve characteristics and experimental data. While Comparative Example 2 considers the heterogeneity of the material, neglecting the influence of particle size may result in some deviation between the simulation results and experimental data, particularly regarding crack propagation mode and load-displacement curves. The example, considering the influence of particle size on the mechanical properties of concrete, can more accurately simulate the behavior of concrete beams. Therefore, the simulation results more accurately reproduce the cracking situation of the concrete beams obtained from experiments, and the extracted load-displacement curve data is closer to the experimentally measured data, demonstrating superior performance.

[0139] The above comparative analysis clearly shows that the heterogeneous simulation method used in the embodiments of the present invention exhibits higher accuracy and reliability in simulating the three-point bending test of concrete beams, and its simulation results are closer to the experimental data, thus proving the superiority of the method.

[0140] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0141] Secondly, embodiments of the present invention provide a near-field dynamics heterogeneous simulation system for concrete beams. This system is used to implement the above embodiments and preferred embodiments, and details already described will not be repeated. As used below, terms such as "module," "unit," and "subunit" can refer to combinations of software and / or hardware that perform predetermined functions. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0142] Figure 11 A block diagram of a near-field dynamic heterogeneous simulation system for concrete beams provided in an embodiment of the present invention is shown below. Figure 11 As shown, the system includes:

[0143] The model discretization module 601 is used to obtain the analysis model of the concrete beam and discretize the analysis model into material points in space.

[0144] The aggregate partitioning module 602 is used to traverse the material points and divide the scope of the analysis model into aggregate particle area and non-aggregate particle area, wherein the aggregate particle area includes aggregate particles of different sizes and the non-aggregate particle area includes the gaps between the aggregate particle areas.

[0145] The material configuration module 603 is used to configure different material properties for the material points according to their range on the analysis model, wherein the material points in the aggregate particle area are configured with aggregate material properties, and the material points in the non-aggregate particle area are configured with matrix material properties.

[0146] The iterative solution module 604 is used to perform near-field dynamic heterogeneous simulation of the concrete beam based on the material properties.

[0147] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination.

[0148] Thirdly, embodiments of the present invention provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the near-field dynamic heterogeneous simulation method for concrete beams as described in any of the preceding claims.

[0149] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0150] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0151] Fourthly, in conjunction with the near-field dynamics heterogeneous simulation method for concrete beams in the above embodiments, this invention can provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements the near-field dynamics heterogeneous simulation method for any concrete beam in the above embodiments.

[0152] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, a network interface, a display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory 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 network interface is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, it implements a method for simulating the near-field dynamics of a concrete beam in a heterogeneous manner. The display screen may be a liquid crystal display (LCD) or an e-ink display. The input devices may be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0153] In one embodiment, Figure 12 This is a schematic diagram of the internal structure of an electronic device provided in an embodiment of the present invention, such as... Figure 12 As shown, an electronic device is provided, which can be a server, and its internal structure diagram can be as follows. Figure 12 As shown, the electronic device includes a processor, a network interface, internal memory, and non-volatile memory connected via an internal bus. The non-volatile memory stores the operating system, computer programs, and a database. The processor provides computing and control capabilities, the network interface communicates with external terminals via a network, the internal memory provides an environment for the operating system and computer programs to run, the computer programs are executed by the processor to implement a near-field dynamics heterogeneous simulation method for concrete beams, and the database stores data.

[0154] Those skilled in the art will understand that Figure 12 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the electronic device to which the present invention is applied. A specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0155] 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. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0156] Those skilled in the art should understand that 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 have been 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.

[0157] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A method for simulating the near-field dynamics of a concrete beam in a heterogeneous environment, characterized in that, The method includes: Based on the actual size and shape of the concrete beam, a corresponding region is defined in three-dimensional space to obtain the analysis model of the concrete beam, and the analysis model is discretized into material points in space starting from the edge of the region at a preset interval; Based on the range of the analytical model, determine the baseline value for aggregate particle content; For any material point, generate a random integer corresponding to that material point. If the random integer is less than or equal to the aggregate particle content benchmark value, mark the material point as the center of the aggregate particle circle, and randomly select a radius to generate the circumcircle of the aggregate particle. Each random integer is not greater than the total number of all material points. Intersection is determined based on the distance between the centers of the newly generated circumcircle of the aggregate particle and the already generated circumcircle of the aggregate particle, and the target circumcircle of the aggregate particle is determined based on the judgment result. The process iterates through each of the material points until the aggregate particle region formed by the circumcircle of each target aggregate particle and the non-aggregate particle region formed by the gaps between the circumcircles of each target aggregate particle are obtained. The aggregate particle region includes aggregate particles of different sizes, and the non-aggregate particle region includes the gaps between the aggregate particle regions. The radius of the aggregate particles is selected from the minimum radius, average radius, and maximum radius of the actual aggregate particles. Based on the range of the material points on the analysis model, different material properties are configured for the material points, wherein the material points in the aggregate particle area are configured with aggregate material properties, and the material points in the non-aggregate particle area are configured with matrix material properties. By setting a virtual diagonal density matrix and a virtual damping coefficient, the near-field dynamic equations are transformed into ordinary differential equations. Based on the material properties, a near-field dynamic heterogeneous simulation of the concrete beam is performed. Prior to performing the near-field dynamic heterogeneous simulation of the concrete beam, the method further includes determining the degree of local damage, which includes: Determine the bond type of adjacent material points based on the material properties corresponding to the material points; When the bond types are of the same type, the target critical elongation rate is determined according to a preset critical elongation rate model. When the bond type is heterogeneous, an initial critical elongation rate is determined according to a preset critical elongation rate model, and the target critical elongation rate is determined based on the initial critical elongation rate combined with a preset weakening coefficient, wherein the weakening coefficient is a parameter characterizing the point bond strength of the material; the target critical elongation rate corresponding to the heterogeneous bond is determined as follows: a first initial critical elongation rate is determined based on the material property being aggregate material property; a second initial critical elongation rate is determined based on the material property being matrix material property; the first initial critical elongation rate and the second initial critical elongation rate are added together, and then multiplied by the preset weakening coefficient to determine the target critical elongation rate corresponding to the heterogeneous bond; The critical elongation of the target bond and the bond elongation of the corresponding material point are compared to determine the value of the bond state function corresponding to the material point. The degree of local damage is determined by integrating the obtained value over a unit volume.

2. The method according to claim 1, characterized in that, The method for determining the benchmark value of aggregate particle content includes: Where n is the baseline value of aggregate particle content, V is the average radius of the aggregate particles, V is the total volume of the analysis model, and c is the volume content of the aggregate particles in the analysis model.

3. The method according to claim 1, characterized in that, The random selection radius includes randomly selecting the minimum radius of aggregate particles in the actual aggregate particles; the step of determining the intersection of the newly generated aggregate particle circumcircle and the already generated aggregate particle circumcircle based on the center distance, and determining the target aggregate particle circumcircle based on the determination result, includes: If the distance between the centers is greater than or equal to the sum of the radii of the newly generated circumcircle of the aggregate particle and the circumcircle of the already generated aggregate particle, then the newly generated circumcircle of the aggregate particle is determined to be the target aggregate particle circumcircle. If the center distance is less than the sum of the radii of the newly generated aggregate particle's circumcircle and the already generated aggregate particle's circumcircle, and the center distance is greater than or equal to the sum of the minimum radius of the aggregate particle and the radius of the already generated aggregate particle's circumcircle, then the radius of the newly generated aggregate particle's circumcircle is adjusted to the minimum radius of the aggregate particle, and the adjusted aggregate particle's circumcircle is determined as the target aggregate particle's circumcircle.

4. The method according to claim 1, characterized in that, The bond critical elongation model is as follows: Among them, f t f represents the tensile strength material property corresponding to a material point. c Let ξ be the compressive strength material property corresponding to the material point, E be the elastic modulus material property corresponding to the material point, and s(ξ) be the bond elongation.

5. A system for implementing the near-field dynamics heterogeneous simulation method for concrete beams according to any one of claims 1-4, characterized in that, The system includes: The model discretization module is used to obtain the analysis model of the concrete beam and discretize the analysis model into material points in space. The aggregate partitioning module is used to traverse the material points and divide the scope of the analysis model into aggregate particle area and non-aggregate particle area. The aggregate particle area includes aggregate particles of different sizes, and the non-aggregate particle area includes the gaps between the aggregate particle areas. The material configuration module is used to configure different material properties for the material points according to their range on the analysis model, wherein the material points in the aggregate particle area are configured with aggregate material properties, and the material points in the non-aggregate particle area are configured with matrix material properties. The iterative solution module is used to perform near-field dynamic heterogeneous simulation of the concrete beam based on the material properties.

6. An electronic device, characterized in that, include memory, processor, and A computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the near-field dynamic heterogeneous simulation method for concrete beams as described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the near-field dynamics heterogeneous simulation method for concrete beams as described in any one of claims 1 to 4.

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