Aggregate random distribution concrete PFC (Power Factor Correction) simulation method

Abstract

The invention discloses an aggregate random distribution concrete PFC (Power Factor Correction) simulation method, which comprises the following steps: a model selection step: determining a parallel bonding model as a mechanical model for concrete material simulation; a cement mortar matrix generation step of generating a cement mortar matrix by using particles in a set size range in a set space range based on the model, and setting pore density, particle density and contact model parameters; a coarse aggregate random distribution simulation step: randomly covering and grouping original particles in the matrix in a grouping and range mode; a concrete numerical model construction step: determining particle classification so as to distinguish cement mortar and coarse aggregate; and a model reliability verification step: comparing indoor test results through a uniaxial compression test. According to the method, the simulation accuracy is improved, the randomness of aggregate is reduced, the model reliability is ensured, the matrix simulation refinement degree is improved, and a method is provided for concrete modeling and performance research.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of concrete simulation, in particular to a PFC simulation method of concrete with random distribution of aggregates. BACKGROUND

[0002] In the field of civil engineering material research, the discrete element method, especially the particle flow code simulation technology, has become an important means of analyzing the mechanical behavior of concrete materials. This technology builds a particle assembly model to simulate the movement between particles, stress transmission and energy conversion, providing an economical and effective analysis tool for the performance research of concrete materials. It plays an important role in scenarios where experiments are difficult to implement or cost is too high. Through numerical simulation, the relationship between the mesostructure and macroscopic mechanical properties of concrete can be deeply analyzed, providing theoretical support for the optimization design of concrete materials.

[0003] In existing PFC simulation methods of concrete, there are obvious deficiencies in the simulation of aggregate shape and distribution. Traditional methods mostly use simplified shapes such as spheres and ellipsoids to generate aggregates or control aggregate positions through deterministic arrangement. The former fails to truly reflect the irregular shape and random distribution characteristics of coarse aggregates in actual concrete, and the latter is too complex to build a model and has a large amount of calculation. This leads to deviations between simulation results and actual material properties. Moreover, the aggregates in existing simulation methods are mostly set as rigid bodies and do not break under the applied simulation conditions, which makes it difficult to ensure the credibility of the simulation results and affects the application value of numerical models in engineering practice. Therefore, a PFC simulation method of concrete with random distribution of aggregates is proposed. SUMMARY

[0004] To overcome the deficiencies of the prior art, the present application provides a PFC simulation method of concrete with random distribution of aggregates to solve the technical problem that the irregular shape and random distribution characteristics of coarse aggregates in actual concrete cannot be truly reflected, leading to deviations between simulation results and actual material mechanical properties.

[0005] To achieve the above purpose, the present application provides the following technical solution: a PFC simulation method of concrete with random distribution of aggregates, comprising the following steps:

[0006] S1, model selection step:

[0007] A parallel bond model is determined to be used as the mechanical model for simulating concrete materials. In this model, relative translation and rotation occur between two particles to transfer force and torque. The model includes two types of particle interaction, non-bonding and parallel bonding. The particles between the non-bonding type slide relative to each other, satisfying the Mohr-Coulomb theory. The parallel bonding type has a bonding interface that resists force and torque. When the actual force is greater than the set tensile strength and shear strength, the bond fails.

[0008] S2, cement mortar matrix generating step:

[0009] Based on the parallel bond model determined in the model selection step, particles of a set size range are generated as the cement mortar matrix within a set spatial range; after generation, the pore density, particle density, and related contact model parameters are set;

[0010] S3, coarse aggregate random distribution simulation step:

[0011] The original particles in the cement mortar matrix generated in the cement mortar matrix generating step are randomly covered and grouped in groups and ranges to simulate the random distribution of the position and shape of the coarse aggregate;

[0012] S4, concrete numerical model construction step:

[0013] According to the coarse aggregate distribution result obtained in the coarse aggregate random distribution simulation step, the classification of particles in the model is determined, the single appearing rock particles are regarded as cement mortar, and the particle groups are regarded as coarse aggregate, and a complete concrete numerical model is constructed;

[0014] S5, model reliability verification step:

[0015] The uniaxial compression test is performed on the concrete numerical model constructed in the concrete numerical model construction step, and the test results are compared with the macroscopic mechanical parameters and failure modes of the indoor test to verify the model reliability.

[0016] Determine to use the parallel bond model as the basic mechanical model for simulating concrete materials, which transmits mechanical information through the relative movement and interaction between particles; define two types of particle interaction in the model, namely non-bonding and parallel bonding; among them, the mutual sliding of non-bonding particles follows the Mohr-Coulomb theory, the bonding interface of parallel bonding particles can withstand and transmit force and torque, and a bonding failure criterion is set, when the actual stress exceeds the preset tensile strength and shear strength, the bonding interface fails;

[0017] Based on the parallel bond model determined in the model selection step, particles of a set size range are generated as the cement mortar matrix within a set two-dimensional spatial range, and the pore density, particle density, and contact model parameters are assigned to ensure that the matrix structure meets the mesoscopic characteristics of the cement mortar in concrete;

[0018] Using a control method combining grouping and range, the original particles in the cement mortar matrix are randomly covered in a region; the covered particles are grouped according to a preset rule, and the random distribution of the new particle position is assigned to simulate the irregular shape and random spatial position distribution characteristics of the coarse aggregate in actual concrete;

[0019] According to the coarse aggregate distribution results obtained by the coarse aggregate random distribution simulation step, the binary classification rule of the particles in the model is determined, the single independent rock particles are defined as the cement mortar component, and the continuously distributed particle groups are defined as the coarse aggregate component; based on the classification results, the cement mortar matrix, the coarse aggregate particle groups and the interfacial structure between the particles are integrated to construct a complete concrete numerical model containing multiple components;

[0020] The uniaxial compression test simulation is performed on the concrete numerical model constructed by the concrete numerical model construction step, the axial compression is applied through the loading system, and the mechanical response data and the failure evolution process of the model are recorded; the macroscopic mechanical parameters obtained by the simulation test, such as the compressive strength and the elastic modulus, are compared quantitatively with the results of the indoor physical test, and the failure mode of the model, such as the crack propagation path and the crushing form, is compared qualitatively with the failure characteristics of the indoor test, and the reliability of the model is comprehensively judged;

[0021] The grouping coverage type coarse aggregate random distribution simulation method avoids the problem of single aggregate shape caused by traditional regular placement or simple random placement, and can accurately reproduce the random position and irregular shape characteristics of coarse aggregate in actual concrete, so that the mesoscopic structure of the numerical model is closer to the real concrete;

[0022] The binary classification rule of single particle and particle group is adopted to clearly define the particle boundary between cement mortar and coarse aggregate, solve the problem of distorted mechanical behavior caused by fuzzy component classification in existing simulation, and make the model accurately transfer the mesoscopic mechanical response of different components, thereby improving the prediction accuracy of macroscopic mechanical parameters;

[0023] A multi-dimensional verification system is constructed to ensure the reliability of the model. Through the double comparison and verification of macroscopic mechanical parameters and failure mode, the limitation of traditional single parameter verification is broken through, the reliability of the model is ensured from two dimensions of numerical consistency and physical process consistency, and a reliable numerical tool is provided for subsequent concrete performance analysis and engineering application.

[0024] Preferably, in the S2, cement mortar matrix generation step, the space range is set as a rectangular range with fixed width and height, and the particle size range is set as an interval range consisting of the minimum particle size and the maximum particle size.

[0025] In the S2, cement mortar matrix generation step, first, the space range is set as a rectangular range with fixed width and height; second, the particle size range is set as an interval range consisting of the minimum particle size and the maximum particle size, and the generation of the cement mortar matrix is completed based on the above settings;

[0026] By fixing the rectangular space range and the particle size interval, the standardization control of the geometric boundary of the cement mortar matrix and the particle grading is realized, the problem of poor consistency of the matrix simulation caused by ambiguous space range and disordered particle size is avoided, and the repeatability of the model is improved.

[0027] Preferably, in the S3, coarse aggregate random distribution simulation step, the grouping and range mode is specifically to screen and cover the original particles through grouping instructions and range instructions, to ensure that the position and shape distribution of the coarse aggregate meet the distribution characteristics of the coarse aggregate in the actual concrete.

[0028] In the S3, coarse aggregate random distribution simulation step, the grouping and range mode is used to realize the distribution of the coarse aggregate; specifically, the original particles are screened and covered through grouping instructions and range instructions, the position and shape of the coarse aggregate are controlled based on the instruction logic, and the position and shape distribution of the coarse aggregate is ensured to meet the distribution characteristics of the coarse aggregate in the actual concrete.

[0029] Through the screening and covering mechanism of instructions, the limitation of excessive randomness of the coarse aggregate distribution in the existing model and the deviation from the actual situation is broken, the controllability and reality of the aggregate distribution are balanced, and key support is provided for simulating the heterogeneous characteristics of concrete.

[0030] Preferably, in the S4, coarse aggregate random distribution simulation step, the classification of particles in the model is distinguished by color, the gray particles and independent black particles are cement mortar, and the black particle groups are coarse aggregate.

[0031] In the S4, coarse aggregate random distribution simulation step, all particles in the model are classified and identified, and the classification is realized by color; wherein, the gray particles and independent black particles are cement mortar, and the black particle groups are coarse aggregate, and the component visualization is completed by color difference.

[0032] The color is used to intuitively distinguish the particle components, the problem of ambiguous boundary between aggregate and mortar in the existing model and difficult to trace is solved, the visualization degree of the model and the subsequent parameter debugging efficiency are improved, and the mechanical response characteristics of different components are accurately positioned.

[0033] Preferably, in the S4, coarse aggregate random distribution simulation step, the contact between the single appearing rock particle and the cement mortar uses the mesoscopic parameters of the cement mortar.

[0034] In the S4, coarse aggregate random distribution simulation step, the parameters of the contact interface in the model are set; for the contact between the single appearing rock particle and the cement mortar, the mesoscopic parameters of the cement mortar are used to define the mechanical properties of this kind of contact.

[0035] By setting the contact parameters of single rock particles and mortar, the model is consistent with the characteristics of the coarse aggregate and the large size of the fine aggregate in the actual concrete material, and the detail restoration degree of the model is improved.

[0036] Preferably, in the S5, model reliability verification step, the macroscopic mechanical parameters include uniaxial compressive strength, elastic modulus and failure mode, and the model accuracy is judged by comparing the numerical model test results with the indoor test results.

[0037] In the S5, model reliability verification step, macroscopic mechanical parameters are selected as core verification indexes, the macroscopic mechanical parameters include uniaxial compressive strength and elastic modulus; the model accuracy is judged according to the difference value by comparing the difference value of the two types of parameters of the numerical model test and the indoor test;

[0038] Taking uniaxial compressive strength, elastic modulus and failure mode as verification indexes, the industry standard of concrete mechanical property evaluation is met, the problem of single verification index and insufficient persuasiveness of the existing model is solved, and quantitative basis is provided for the reliability of macroscopic mechanical response of the model.

[0039] Preferably, in the S3, coarse aggregate random distribution simulation step, the coarse aggregate adopts the mesoscopic parameters of granite, and the coverage ratio of the coarse aggregate in the concrete numerical model is a fixed proportion.

[0040] In the S3, coarse aggregate random distribution simulation step, the material parameters and distribution proportion of the coarse aggregate are set; wherein the coarse aggregate adopts the mesoscopic parameters of granite, and the coverage ratio of the coarse aggregate in the concrete numerical model is a fixed proportion, and the attribute definition and throwing control of the coarse aggregate are completed based on the above setting;

[0041] By defining the mesoscopic parameters of granite and the fixed coverage ratio, the problems of ambiguous material properties of aggregate and out-of-control distribution proportion in the existing model are solved, the adaptability of the model to the specific aggregate type concrete is ensured, and the reference value of the simulation result in the actual engineering is improved.

[0042] In summary, compared with the prior art, the present application provides a concrete PFC simulation method with the following beneficial effects:

[0043] The present application constructs the concrete material by adopting the parallel bonding model, randomly simulates the coarse aggregate by grouping and range coverage, and clearly distinguishes the cement mortar and the coarse aggregate by combining the particle classification rules, effectively restores the randomness and morphological diversity of the internal aggregate distribution of the concrete, and makes the numerical model closer to the actual material structure.

[0044] The reliability of the model is ensured through the comparison and verification of the macro-mechanical parameters and the failure mode of the uniaxial compression test and the indoor test, and a precise and reliable numerical simulation tool is provided for the performance research of the concrete material. BRIEF DESCRIPTION OF DRAWINGS

[0045] Figure 1 It is a schematic diagram of the method of the present application.

[0046] Figure 2 It is a schematic diagram of the mechanical model used in the present application.

[0047] Figure 3 It is a schematic diagram of the numerical model of the concrete of the present application.

[0048] Figure 4 It is a schematic diagram of the numerical simulation of the failure mode of the concrete of the present application. DETAILED DESCRIPTION

[0049] The present application provides a technical solution, which is further described in detail in combination with the drawings and implementation examples. It should be understood that the specific examples described herein are only used to explain the present application and do not limit the present application.

[0050] S1, model selection step:

[0051] Determine to construct the concrete sample by the parallel bonding model;

[0052] S2, cement mortar matrix generation step:

[0053] The cement mortar matrix material is generated in the range of width 75mm and height 150mm with 1mm-2mm particles, and the pore density is 0.1, the particle density is 2321.83kg / m3, and the gravity acceleration is 9.8m / m2 during the generation process. The contact model mesoscopic parameters of the cement mortar are shown in Table 1;

[0054] Table 1 Mesoscopic parameters of concrete mortar matrix

[0055]

[0056] S3, coarse aggregate random distribution simulation step:

[0057] The original particles in the cement mortar matrix generated in the cement mortar matrix generation step are randomly covered and grouped in a grouping and range manner to simulate the random distribution of the position and shape of the coarse aggregate. The coarse aggregate adopts the granite mesoscopic parameters, and the coarse aggregate coverage ratio is 0.2. The mesoscopic parameters of the coarse aggregate are shown in Table 2;

[0058] Table 2 Mesoscopic parameters of concrete coarse aggregate

[0059]

[0060] S4. Steps for constructing a numerical model of concrete:

[0061] To reflect the characteristic that aggregate size is larger than cement mortar, after random covering of particle groups, the contact between individual rock particles appearing in the cement mortar and the cement mortar is still treated using the micro-parameters of the cement mortar, i.e., they are treated as cement mortar, while particle clusters are treated as coarse aggregate. A complete numerical model of concrete is constructed as follows: Figure 3 As shown, the coarse aggregate of the concrete has an irregular shape and varies in size, which is consistent with the actual model.

[0062] S5. Model reliability verification steps:

[0063] Uniaxial compression tests were conducted on the concrete numerical model constructed using the concrete numerical model construction steps. The macroscopic mechanical parameters and failure modes of the test results were compared with those of the laboratory tests. Table 3 shows the comparison between the uniaxial compressive strength and elastic modulus obtained from the numerical simulation and the laboratory tests, with errors all within 2%.

[0064] Table 3 Comparison of macroscopic parameters between indoor test samples and numerical models

[0065]

[0066] from Figure 4 It can be seen that after the concrete specimen failed under load, significant swelling occurred in the middle of the specimen, and the crack propagation direction was mainly the same as the loading direction. The main failure mode of the concrete specimen was axial tensile splitting failure, and coarse aggregate failure was also observed. The simulation results are in good agreement with the actual failure mode, which further proves the reliability of the simulation method and results.

Claims

1. A method for simulating PFC (Polymerized Fiber Coagulation) in concrete with randomly distributed aggregates, characterized in that, Includes the following steps: S1. Model selection steps: The parallel bond model was chosen as the mechanical model for simulating concrete materials. In this model, relative translation and rotation occur between two particles to transfer forces and moments. The model includes two types of particle interactions: non-bonded and parallel bonded. In the non-bonded type, the sliding between particles satisfies the Mohr-Coulomb theory. In the parallel bonded type, the bond interface resists forces and moments. When the actual stress exceeds the set tensile and shear strengths, the bond fails. S2. Steps for generating cement mortar matrix: Based on the parallel bonding model determined in the model selection step, cement mortar matrix material is generated using particles of a set size range within a defined spatial range; during the generation process, pore density, particle density, and contact model parameters are controlled. S3. Simulation steps for random distribution of coarse aggregate: By using a grouping and range approach, the original particles in the cement mortar matrix generated in the cement mortar matrix generation step are randomly covered and grouped to simulate the random distribution of the position and shape of coarse aggregate. S4. Steps for constructing a numerical model of concrete: Based on the coarse aggregate distribution results obtained from the random distribution simulation steps, the classification of particles in the model is clarified. Individual rock particles are regarded as cement mortar, and particle clusters are regarded as coarse aggregate, thus constructing a complete concrete numerical model. S5. Model reliability verification steps: The concrete numerical model constructed in the concrete numerical model construction steps was subjected to uniaxial compression tests. The test results were compared with the macroscopic mechanical parameters and failure modes of the laboratory tests to verify the reliability of the model.

2. The method for simulating PFC in concrete with randomly distributed aggregates according to claim 1, characterized in that: In step S2, the cement mortar matrix generation step, the set spatial range is a rectangular range with fixed width and height, and the set particle size range is the interval range formed by the minimum particle size and the maximum particle size.

3. The method for simulating PFC in concrete with randomly distributed aggregates according to claim 1, characterized in that: In step S3, the random distribution simulation of coarse aggregate, the grouping and range methods specifically involve screening and covering the original particles through grouping and range commands to ensure that the position and shape distribution of coarse aggregate conforms to the distribution characteristics of coarse aggregate in actual concrete.

4. The method for simulating PFC in concrete with random aggregate distribution according to claim 1, characterized in that: In step S4, the random distribution simulation of coarse aggregate, the particles in the model are classified by color. Gray particles and independent black particles are cement mortar, while black particle clumps are coarse aggregate.

5. The method for simulating PFC in concrete with random aggregate distribution according to claim 1, characterized in that: In step S4, the random distribution simulation of coarse aggregate, the contact between a single rock particle and the cement mortar is determined using the microscopic parameters of the cement mortar.

6. The method for simulating PFC in concrete with random aggregate distribution according to claim 1, characterized in that: In step S5, the model reliability verification step, the macroscopic mechanical parameters include uniaxial compressive strength, elastic modulus, and failure mode. The accuracy of the model is judged by comparing the results of numerical model tests and indoor tests.

7. The method for simulating PFC in concrete with randomly distributed aggregates according to claim 1, characterized in that: In step S3, the random distribution simulation of coarse aggregate, the coarse aggregate adopts the microstructure parameters of granite, and the coverage ratio of coarse aggregate in the concrete numerical model is a fixed ratio.

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