Discrete-element-based three-dimensional microscopic simulation method for compressive property of steel fiber reinforced concrete

Abstract

The invention discloses a discrete element-based three-dimensional mesoscopic simulation method for the compressive property of steel fiber reinforced concrete. The method comprises the following steps of: establishing an actual three-dimensional model of each graded coarse aggregate and fiber adopted by target fiber reinforced concrete; establishing a target space of the target fiber concrete model, and randomly generating fiber particles at different angles in the target space based on the actual three-dimensional model of the fibers; putting aggregate in a target space based on the actual three-dimensional model of the coarse aggregate, and establishing a target fiber concrete model; establishing contact among particles of the target fiber concrete model and setting a boundary contact relation to generate a fiber concrete test piece; carrying out initial equilibrium state analysis; the compressive mechanical property of the fiber concrete is measured by loading an external load through a uniaxial compression test. The method has the remarkable effects that the model is finer, the axial deformation behavior of the fiber concrete can be more accurately simulated, and the simulation result is more accurate.

Description

Technical Field

[0001] The invention relates to the technical field of simulation of concrete anti-cracking performance, and in particular to a three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete elements. Background Art

[0002] Steel fiber reinforced concrete (SFRC) is a cement-based composite material widely used in civil engineering. Compared with ordinary concrete, SFRC has excellent strength, toughness and impact resistance. Steel fibers (SF) are dispersed in the concrete matrix. The geometric characteristics (length, diameter, shape) and volume fraction of steel fibers have a significant effect on the macroscopic mechanical properties of SFRC. At the same time, the presence of coarse aggregate in concrete plays a vital role. Coarse aggregate forms a skeleton inside SFRC, which is more conducive to the transfer of external loads.

[0003] At present, the research on SFRC still focuses on the use of experimental techniques to study the macroscopic mechanical properties of steel fiber reinforced concrete. However, it is difficult and inefficient to experimentally study the influence of the microscopic parameters of fiber and concrete on its mechanical properties. Therefore, a multi-scale research method is needed to fully understand the mechanism of action of the mesoscopic components of steel fiber reinforced concrete and their influence on the macroscopic mechanical properties.

[0004] Among the current multi-scale research methods, numerical methods can effectively solve the limitations of traditional experimental technology and cost on the mechanical properties of SFRC. Finite element method, boundary element method and discrete element method are often used to study the mechanical behavior and failure mechanism of SFRC under different loading conditions. Among them, the finite element method is considered to be an extremely effective research method in the microscopic modeling of SFRC. Some researchers proposed a two-dimensional three-phase model consisting of aggregate, fiber and mortar to simulate the mechanical properties of SFRC, established hook-end steel fiber and spiral steel fiber FRC models, and the size and position of coarse aggregate were defined as randomly distributed and circular, and the accuracy of the numerical model was verified by experimental results. The improvement of computing power provides a basis for the high-precision modeling of concrete models. A three-dimensional four-phase mesoscale model consisting of aggregate, fiber, mortar and interface transition zone (ITZ) was developed because it can effectively reflect the positional relationship of fibers in concrete and the geometric shape of aggregates. Other developed methods can generate realistic aggregate models between fibers with adjustable size and shape in random domains based on the relationship between Voronoi and Delaunay structures. The simulation results show that when the ITZ strength exceeds the critical value of 0.8 times the mortar, the tensile strength is almost unaffected by the ITZ strength, and the aggregate surface texture and volume ratio are exponentially related to the compressive strength. The physical properties of the ITZ region greatly affect the accuracy of the numerical calculation method, although the trial-and-error method can be used to adjust the parameters to obtain results that are consistent with the experiment. However, due to the complexity of SFRC materials with a large number of fibers and irregularly shaped coarse aggregates, a more effective mesoscale simulation method is needed. Summary of the invention

[0005] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a three-dimensional mesoscopic simulation method for the compressive performance of steel fiber reinforced concrete based on discrete elements. Through a three-dimensional four-phase mesoscopic model based on the discrete element method (DEM), the influence of steel fiber content and physical properties of coarse aggregate on the mechanical properties and failure mechanism of steel fiber reinforced concrete (SFRC) is studied to evaluate the accuracy and effectiveness of the developed model under uniaxial static compression loading conditions, which can effectively solve the technical problems described in the background technology.

[0006] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0007] A three-dimensional microscopic simulation method for compressive performance of steel fiber concrete based on discrete element, the key of which is to include the following steps:

[0008] S1. Establish the actual three-dimensional model of coarse aggregate and fiber of each grade used in the target fiber concrete;

[0009] S2, establishing a target space of a target fiber concrete model, and randomly generating fiber particles at different angles in the target space based on an actual three-dimensional model of the fiber;

[0010] S3, placing aggregates in the target space based on the actual three-dimensional model of coarse aggregates, and establishing a target fiber concrete model;

[0011] S4, using the bonding strength between fiber, aggregate and mortar as input, establishing contact between particles of the target fiber concrete model and setting boundary contact relationship to generate a fiber concrete specimen;

[0012] S5, performing stress initialization to make the target fiber concrete model reach a balanced state, and performing initial balanced state analysis;

[0013] S6. Boundary conditions are applied to the fiber concrete specimens, and external loads are applied through uniaxial compression tests to measure the compressive properties of the fiber concrete.

[0014] Furthermore, the steps of establishing the actual three-dimensional model of coarse aggregate and fiber in step S1 are as follows:

[0015] Perform 3D scanning on the coarse aggregate and fiber actually used to obtain the shape of the coarse aggregate and the outer surface characteristics of the fiber;

[0016] The geometric shapes of coarse aggregate and fiber are edited by CAD software, and the actual three-dimensional models of coarse aggregate and fiber at each level are established.

[0017] Furthermore, the process of randomly generating fiber particles at different angles in the target space based on the actual three-dimensional model of the fiber in step S2 is as follows:

[0018] S21, setting the test calculation area, establishing the target space of the target fiber concrete model, and setting the relevant parameters of the target fiber concrete model;

[0019] S22, calculating the fiber content based on relevant parameters and geometric dimensions of the target fiber concrete model;

[0020] S23. Randomly generate fiber particles at different angles in the target space based on the fiber content, the actual three-dimensional model of the fiber and the particle size of the constituent fibers.

[0021] Furthermore, the relevant parameters of the target fiber concrete model include density, effective modulus, stiffness ratio, friction coefficient, and porosity.

[0022] Furthermore, the calculation formula of the fiber content is:

[0023]

[0024] Among them, ω 1is the fiber content, M = V(1-porosity)ρball+Vfiberρfiber is the total mass of the target fiber concrete in the target fiber concrete model, ρfiber is the fiber density, Vfiber is the fiber volume, porosity is the porosity, V is the total volume of the target fiber concrete model, ρ 球 The density of the generated particle unit.

[0025] Furthermore, the steps of establishing the target fiber concrete model in step S3 are as follows:

[0026] S31, generating circular particles of different sizes according to aggregate gradation and proportion information and putting them into the target space to contact with the fiber particles of different angles generated in step S2;

[0027] S32. Take aggregate samples on site, clean the aggregate surface, and then use a 3D scanner to fully scan the aggregate to obtain the geometric data of the aggregate;

[0028] S33. For fine aggregates with a particle size less than 2 mm, round particles are used for modeling; for mortar, round particles with a particle size of 2 to 4 mm are used for modeling. The particles of fine aggregate and mortar are put into the target space to obtain the target fiber concrete model.

[0029] Furthermore, the steps of generating the fiber concrete specimen in step S4 are as follows:

[0030] S41, applying bonding to the particle combination, the particle combination requiring bonding includes: mortar particle-mortar particle, aggregate-aggregate, mortar particle-aggregate, mortar particle-fiber particle, fiber particle-fiber particle;

[0031] S42. On the basis of the bonding stage, the debonding stage and the slip stage are added to describe the shear slip mechanical behavior of the fiber particles and the matrix particles, and the bonding force chain between the aggregates is obtained to generate the fiber concrete specimen.

[0032] Furthermore, the fiber particles are bonded to each other using a linear bonding model, and the input parameters include tangential stiffness, normal stiffness, bonding tensile strength and bonding shear strength;

[0033] The mortar particles-mortar particles, aggregate-aggregate, mortar particles-aggregate, and mortar particles-fiber particles are all bonded using a parallel bonding model, and the input parameters include effective modulus, bonding tensile strength, bonding cohesion, and bonding friction angle.

[0034] Furthermore, during the initial equilibrium state analysis in step S5, the stress between the wall and the edge particles is monitored in real time. The stress between the wall and the edge particles controls the speed of the wall to ensure the stability of the applied pressure. When the stress between the edge particles and the wall reaches a preset value, the calculation is stopped.

[0035] Furthermore, in step S6, the steps of applying boundary conditions to the fiber concrete specimen and loading an external load to measure the compressive properties of the fiber concrete through a uniaxial compression test are as follows:

[0036] The target loading speed of the uniaxial compression test is loaded on the fiber concrete specimen in sections, the stress-strain related data are saved, and the compressive stress-strain relationship is established as the calculation result of the fracture mechanics properties of the fiber concrete.

[0037] The remarkable effects of the present invention are:

[0038] 1) The present invention provides a method for constructing a target steel fiber concrete discrete element model, which establishes an actual three-dimensional model of coarse aggregate and fiber. Compared with the traditional three-dimensional model using round or elliptical particles to simplify the material, the actual three-dimensional model of the present invention is more refined and closer to the actual situation;

[0039] 2) When establishing the bonding contact relationship between the particles of the target fiber concrete model, the present invention fully considers the bonding conditions between the fiber, aggregate and mortar, so that the obtained concrete specimen can more accurately simulate the axial deformation behavior of the fiber concrete;

[0040] 3) The present invention comprehensively considers the contact relationship between mortar particles and mortar particles, aggregates and aggregates, mortar particles and aggregates, mortar particles and fiber particles, and fiber particles and fiber particles, and considers the effect of fiber on the strength of the interface transition zone between mortar and aggregate. Through the interaction between discrete particles, the friction and sliding of fiber materials in concrete and their crack-resistance effect on concrete are accurately simulated. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is a flow chart of the method of the present invention;

[0042] Figure 2 This is an example of an actual three-dimensional model of a coarse aggregate;

[0043] Figure 3 An example diagram of generating fiber particles in the target space;

[0044] Figure 4 This is a schematic diagram of aggregate placement results;

[0045] Figure 5 It is a schematic diagram of the bonding force chain between aggregates;

[0046] Figure 6 Schematic diagram of uniaxial compression test;

[0047] Figure 7 Schematic diagram of the uniaxial compression calculation results of fiber reinforced concrete beams. DETAILED DESCRIPTION

[0048] The specific implementation manner and working principle of the present invention are further described in detail below with reference to the accompanying drawings.

[0049] The present invention establishes an efficient three-dimensional four-phase (coarse aggregate, mortar matrix, ITZ and SFs) mesoscopic model calculation framework based on DEM. A series of verifications and applications will be carried out to evaluate the accuracy and effectiveness of the developed model under uniaxial static compression loading conditions. The main steps are:

[0050] Based on the cubic axial compression test, the stress-strain behavior and failure mode of SFRC were obtained. The experimental material properties such as aggregate shape, physical properties and fiber length, diameter, volume fraction, etc. will provide basic parameter settings for the DEM model;

[0051] A three-dimensional random aggregate filling model that conforms to the real gradation curve was established based on the actual mix ratio to simulate the skeleton structure and SFs of concrete coarse aggregate.

[0052] Based on the results of bi-material cube splitting tensile test and steel fiber pull-out test, a steel fiber-mortar contact model with dual nonlinear softening sections and a coarse aggregate-mortar contact model considering the effect of steel fiber volume fraction were developed.

[0053] In PFC3D software, the fiber concrete specimens were consolidated and loaded by assigning wall velocity, and the initial equilibrium state analysis was performed;

[0054] The compression behavior of SFRC was simulated based on the discrete element model, and the simulation results were compared with the experimental results. The stress-strain behavior, microcrack development and failure mechanism of SFRC were analyzed from a mesoscopic perspective.

[0055] Next, the specific implementation steps of the embodiment of the present invention are described in detail. Figure 1 :

[0056] S1. Establish the actual three-dimensional model of coarse aggregate and fiber of each grade used in the target fiber concrete;

[0057] Traditional concrete materials use round or elliptical particles to simplify the shape of the material. The concrete micro-simulation results are bound to be different from the actual situation. In order to more accurately realize the micro-simulation of fiber concrete, this embodiment establishes a high-precision three-dimensional model based on the coarse aggregate and fiber actually used, thereby improving the accuracy of the simulation.

[0058] Therefore, the steps to build the actual 3D model of coarse aggregate and fiber in this step are as follows:

[0059] First, the actual coarse aggregate and fiber are 3D scanned to obtain the shape of the coarse aggregate and the outer surface characteristics of the fiber;

[0060] Then, the geometric shapes of coarse aggregate and fiber are edited by CAD software, and the actual 3D model of each level of coarse aggregate and the actual 3D model of fiber are established. The actual 3D model of a coarse aggregate is established as follows: Figure 2 shown.

[0061] S2. Establish the target space of the target fiber concrete model, and randomly generate fiber particles at different angles in the target space based on the actual three-dimensional model of the fiber. The specific steps are as follows:

[0062] S21, setting the test calculation area, establishing the target space of the target fiber concrete model, and setting the relevant parameters of the target fiber concrete model;

[0063] Determine the geometric dimensions of the target fiber concrete model and set the test calculation area according to the geometric dimensions. In the PFC3D software, use the "wall generate" command to generate a wall of the required size, with the bottom length twice the diameter of the sample and the height twice the height of the sample. The indoor test block is a 100*100*100mm cube. This is to ensure that the particles will not pass through the wall from the bottom corners in the subsequent calculations after generation, and to ensure that no large strain will occur during the subsequent model loading process.

[0064] The side and upper and lower walls are used to control the overall confining pressure of the test, and the top and bottom walls are used to control the loading process of subsequent samples. The space enclosed by the walls is the target space, and then the relevant parameters of the target fiber concrete model to be established are determined, such as density, effective modulus, stiffness ratio, friction coefficient, porosity, etc. The present invention establishes a discrete element model of fiber concrete, establishes contact relationships, and analyzes the initial equilibrium state in the target space.

[0065] S22, calculating the fiber content based on relevant parameters and geometric dimensions of the target fiber concrete model;

[0066] In this example, the calculation formula for the fiber content is:

[0067]

[0068] Among them, ω 1is the fiber content, M = V(1-porosity)ρball+Vfiberρfiber is the total mass of the target fiber concrete in the target fiber concrete model, ρfiber is the fiber density, Vfiber is the fiber volume, porosity is the porosity, V is the total volume of the target fiber concrete model, ρ 球 The density of the generated particle unit.

[0069] S23, randomly generating fiber particles at different angles in a target space based on the fiber content, the actual three-dimensional model of the fiber, and the particle size of the constituent fibers;

[0070] The actual three-dimensional model of the fiber established in step S1 is imported into the PFC3D software, and the fiber shape is generated by the *clump templatecreate command, where the main input parameter is the particle size of the fiber composition, and the particle size is determined by the actual radius of the fiber. Finally, the *clump generate command is used to randomly generate fiber particles at different angles in the target space, and the number of generated fibers is determined by the fiber content calculation. The fiber particles generated in this way are the same as the actual three-dimensional model. Figure 3 Shown is an example of generating fiber particles in the target space.

[0071] S3, placing aggregates in the target space based on the actual three-dimensional model of coarse aggregates, and establishing a target fiber concrete model;

[0072] S31, according to the aggregate gradation and its proportion information, use the command "balldistribute" in the PFC3D software to generate circular particles of different sizes and put them into the target space to contact with the fiber particles of different angles generated in step S2;

[0073] S32. Take aggregate samples on site, clean the aggregate surface, and then use a 3D scanner to fully scan the aggregate to obtain the geometric data of the aggregate;

[0074] Then, use the “geometry import” command in the PFC3D software to import the actual 3D model file (.dxf) of the coarse aggregate edited in step S1;

[0075] Then, the "clump template" command is used to replace the circular particles of different sizes with the actual three-dimensional models of coarse aggregates with different gradations. This substitution method makes the target concrete model more consistent with the actual situation.

[0076] S33. For mortar, round particles with a particle size of 2 to 4 mm are used for modeling. In order to simplify the calculation, the mortar and fine aggregate with a particle size less than 2 mm can be modeled together. Using the same component representatives, the particles of fine aggregate and mortar are put into the target space to obtain the target fiber concrete model, completing the discretization process. The target fiber concrete model is the discrete element model. Figure 4 Shown is a schematic diagram of aggregate placement results.

[0077] After completing the above discretization process, each particle in the DEM model needs to be assigned specific contacts. The discretized concrete square is projected onto the established mesostructure, and contacts need to be established between particles. Therefore, enter step S4:

[0078] S4, using the bonding strength between fiber, aggregate and mortar as input, establishing contact between particles of the target fiber concrete model and setting boundary contact relationship to generate a fiber concrete specimen;

[0079] S41. Use the "CMAT" command in the PFC3D software to apply bonding to the particle combination. The particle combinations that need to be bonded include: mortar particles-mortar particles, aggregate-aggregate, mortar particles-aggregate, mortar particles-fiber particles, and fiber particles-fiber particles;

[0080] The fiber particles are bonded to each other using a linear bonding model (linearcbond), and the input parameters include tangential stiffness (kn), normal stiffness (ks), bonding tensile strength (cb_tens), and bonding shear strength (cb_shears);

[0081] The mortar particles-mortar particles, aggregate-aggregate, mortar particles-aggregate, and mortar particles-fiber particles are bonded using a parallel bond model (linearpbond, PBM), and the input parameters include effective modulus (emod), bond tensile strength (pb_ten), bond cohesion (pb_coh), and bond friction angle (pb_fa);

[0082] The specific values ​​of the contact parameters input in this embodiment are obtained according to the test. Table 1 shows the material calculation parameters obtained according to the splitting tensile test of the mixed specimen.

[0083] Table 1 Material calculation parameters

[0084]

[0085] In this case, the reasonable range of the internal friction angle is 0.35-0.5, which is used as the preset value. Then, in the splitting tensile test of the mixed specimen, the bond cohesion (c) and the effective modulus (E *) to match the splitting test results.

[0086] The following equation shows the nonlinear relationship between fiber and splitting tensile strength, and predicts the cohesion of ITZ by steel fiber content:

[0087] c=(1-α)c 0

[0088] α Limestone =0.175V SF -0.083(V SF ) 2 -0.006

[0089] α Granite =0.296V SF -0.015(V SF ) 2 -0.033

[0090] Where c represents bond cohesion, c 0 It represents the cohesion between mortar and aggregate when there is no fiber. The strength is related to the type of aggregate and the mix ratio of mortar. * ) is calculated based on the conclusions of previous studies.

[0091] S42. Table 2 shows the parameters of the built-in flat joint contact model. The built-in flat joint contact model (FJM) is rewritten using the built-in FISH language in the PFC3D software. Debonding segments and slip segments are added to the built-in FJM to describe the shear slip mechanical behavior of fiber particles and matrix particles. The mechanical behaviors at different stages are shown below:

[0092] Bonding stage: τ(s) = k s w s (t)

[0093] Debonding stage:

[0094] Slip phase: τ = τ 0 +(τ max -τ 0 )exp[(w s (t)-w s (t 1 )) / w s (t ref )]

[0095] Among them, τ max is the interface bonding strength; τ break is the interface debonding strength; τ 0 is the asymptotic value of friction stress; w s (t 0) is the displacement corresponding to the maximum value of the interface bonding strength; w s (t 1 ) is the displacement corresponding to the moment of interface debonding; w s (t ref ) is the parameter that controls the descending branch of the curve.

[0096] By break , τ 0 and the branching coefficient of the curve (w s (t ref )) Repeated calibration until it matches the pull-out test result. The bond force chain between aggregates is obtained to generate the fiber concrete specimen.

[0097] Table 2 Calculation parameters of bond slip between steel fiber particles and mortar matrix particles

[0098]

[0099] The bond force chain between aggregates obtained by the contact calculation method of the present invention is as follows: Figure 5 shown.

[0100] When establishing the bonding contact relationship between the particles of the target fiber concrete model, the present invention comprehensively considers the contact relationships between mortar particles-mortar particles, aggregate-aggregate, mortar particles-aggregate, mortar particles-fiber particles, and fiber particles-fiber particles, and considers the influence of fibers on the strength of the interface transition zone between mortar and aggregate. The friction and sliding of fiber materials in concrete and the anti-cracking effect of fibers on concrete are accurately simulated through the interaction between discrete particles. The obtained concrete specimens can more accurately simulate the fracture behavior of fiber concrete.

[0101] S5. Perform stress initialization to make the target fiber concrete model reach equilibrium state, and perform initial equilibrium state analysis, as follows:

[0102] Through step S4, bonding contact has been established between the particles of the fiber concrete specimen, but some particles still have initial velocity. The coarse aggregate and mortar velocities are reset through the commands "clump attribute" and "ball attribute". At this time, stress bonding exists between the particles and stress exists between the particles and the wall.

[0103] Before applying external loads, the test materials need to be consolidated. In order to make the PFC3D simulation test more reasonable and appropriate, the servo control of the wall is used in PFC3D to control the confining pressure of the specimen. The top and bottom walls are used as loading plates, and the side walls are used to control the confining pressure of the model specimen. PFC3D cannot control the load size of the specimen by applying force to the wall, so the consolidation and loading of the specimen are achieved by giving the wall velocity.

[0104] In the process of initial equilibrium state analysis, this embodiment monitors the stress between the wall and the edge particles in real time, controls the speed of the wall according to the stress between the wall and the edge particles, ensures the stability of the applied pressure, stops the calculation when the stress between the edge particles and the wall reaches a preset value, and adjusts the calculation speed according to the input servo coefficient. The specific principle is:

[0105] The upper wall is controlled to move downward at a certain rate to compress the specimen and increase the stress between particles. When the stress is too large, the wall is controlled to move upward to reduce the stress between particles.

[0106] During the consolidation process, firstly define the axial stress, axial strain, servo coefficient and servo preloading method through the command "def"; record the data through the command "history" in combination with the id number of each parameter, and set a certain data recording time step (his_tep) to monitor the stress between the wall and the edge particles. The wall number can be obtained by using the "wall.find" in the FISH function, and the force of the contact point of the side top wall can be obtained through "wall.force.contact", and then the contact stress of the wall can be calculated. The wall position can be analyzed in real time through "wall.pos", and then the strain of the model material can be calculated. The servo system continuously obtains the wall stress and other sizes to control the speed of the wall, thereby ensuring the stability of the pressure applied in the sample calculation;

[0107] After the specimen is formed, the command "wall delete" needs to be used to delete the modeled wall; after running this step, the initial equilibrium state of the specimen meets the loading conditions.

[0108] S6. Apply boundary conditions to the fiber concrete specimens and measure the compressive properties of the fiber concrete by applying external loads through uniaxial compression tests, as follows:

[0109] First, use the command "wall generate" to generate the loading wall. The wall geometry data is obtained from the uniaxial compression test loading tool, such as Figure 6 Shown is a schematic diagram of a uniaxial compression test;

[0110] Then, use the command "wall attribute vel" to load the target loading speed on the specimen in sections. In this process, in order to prevent the sudden change of loading speed, which will cause the model specimen to be damaged due to uneven force, the loading strain rate is set to a small value at the beginning of loading, and then gradually increased to reach the loading rate consistent with the target loading speed of the test;

[0111] After the sample calculation is completed, use "history write" to record the stress, strain, and specimen fracture energy related data into the saved folder, and then use the origin software to process the data and display it in graphics.

[0112] In this example, the uniaxial compression calculation results of the fiber reinforced concrete beam are as follows: Figure 7 As shown, the result is represented by the compressive stress-strain relationship of the fiber concrete beam, and the numerical simulation results of the present invention are compared with the actual test results. The experiment shows that the numerical simulation results of the present invention can be well close to the actual situation and have high accuracy.

[0113] In summary, the embodiment of the present invention establishes a three-dimensional four-phase mesoscopic model based on discrete element method (DEM) to study the influence of steel fiber content and physical properties of coarse aggregate on the mechanical properties and failure mechanism of steel fiber reinforced concrete (SFRC). The model consists of mortar, coarse aggregate, steel fiber and interface transition zone (ITZ). In order to calibrate and verify the accuracy of the model, axial compression tests of 15 groups of SFRC cube specimens were carried out to study the influence of fiber content and aggregate volume ratio on the mechanical properties and cracking characteristics of SFRC. In the model, based on the test mix ratio, agglomerated particle modules and steel fibers with real aggregate geometry are randomly distributed in concrete. Using the Flat-Joint contact model in the DEM software (PFC3D), a steel fiber-mortar contact model with dual nonlinear softening segments and a coarse aggregate-mortar contact model considering the influence of steel fiber volume fraction are developed to describe the mechanical behavior of the steel fiber-mortar interface ITZ and the coarse aggregate-mortar interface ITZ, respectively. And based on previous experimental studies, the accuracy of these two contact models has been verified.

[0114] The technical solution provided by the present invention is described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, the present invention can also be improved and modified in a number of ways, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. A three-dimensional microscopic simulation method for compressive properties of steel fiber concrete based on discrete elements, characterized in that: The steps include: S1. Establish the actual three-dimensional model of coarse aggregate and fiber of each grade used in the target fiber concrete; S2, establishing a target space of a target fiber concrete model, and randomly generating fiber particles at different angles in the target space based on an actual three-dimensional model of the fiber; S3, placing aggregates in the target space based on the actual three-dimensional model of coarse aggregates, and establishing a target fiber concrete model; S4, using the bonding strength between fiber, aggregate and mortar as input, establishing contact between particles of the target fiber concrete model and setting boundary contact relationship to generate a fiber concrete specimen; S5, performing stress initialization to make the target fiber concrete model reach a balanced state, and performing initial balanced state analysis; S6. Boundary conditions are applied to the fiber concrete specimens, and external loads are applied through uniaxial compression tests to measure the compressive properties of the fiber concrete.

2. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 1 is characterized by: The steps for establishing the actual three-dimensional model of coarse aggregate and fiber in step S1 are as follows: Perform 3D scanning on the coarse aggregate and fiber actually used to obtain the shape of the coarse aggregate and the outer surface characteristics of the fiber; The geometric shapes of coarse aggregate and fiber are edited by CAD software, and the actual three-dimensional models of coarse aggregate and fiber at each level are established.

3. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 1 is characterized by: The process of randomly generating fiber particles at different angles in the target space based on the actual three-dimensional model of the fiber in step S2 is as follows: S21, setting the test calculation area, establishing the target space of the target fiber concrete model, and setting the relevant parameters of the target fiber concrete model; S22, calculating the fiber content based on relevant parameters and geometric dimensions of the target fiber concrete model; S23. Randomly generate fiber particles at different angles in the target space based on the fiber content, the actual three-dimensional model of the fiber and the particle size of the constituent fibers.

4. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 3 is characterized by: The relevant parameters of the target fiber concrete model include density, effective modulus, stiffness ratio, friction coefficient, and porosity.

5. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 3 is characterized by: The calculation formula of the fiber content is: Among them, ω1 is the fiber content, M=V(1-porosity)ρball+Vfiberρfiber is the total mass of the target fiber concrete in the target fiber concrete model, ρfiber is the fiber density, Vfiber is the fiber volume, porosity is the porosity, V is the total volume of the target fiber concrete model, and ρball is the density of the generated particle unit.

6. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 1 is characterized by: The steps of establishing the target fiber concrete model in step S3 are as follows: S31, generating circular particles of different sizes according to aggregate gradation and proportion information and putting them into the target space to contact with the fiber particles of different angles generated in step S2; S32. Take aggregate samples on site, clean the aggregate surface, and then use a 3D scanner to fully scan the aggregate to obtain the geometric data of the aggregate; S33. For fine aggregates with a particle size less than 2 mm, round particles are used for modeling; for mortar, round particles with a particle size of 2 to 4 mm are used for modeling. The particles of fine aggregate and mortar are put into the target space to obtain the target fiber concrete model.

7. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 1 is characterized by: The steps of generating the fiber concrete specimen in step S4 are as follows: S41, applying bonding to the particle combination, the particle combination requiring bonding includes: mortar particle-mortar particle, aggregate-aggregate, mortar particle-aggregate, mortar particle-fiber particle, fiber particle-fiber particle; S42. On the basis of the bonding stage, the debonding stage and the slip stage are added to describe the shear slip mechanical behavior of the fiber particles and the matrix particles, and the bonding force chain between the aggregates is obtained to generate the fiber concrete specimen.

8. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 7 is characterized by: The fiber particles are bonded to each other using a linear bonding model, and the input parameters include tangential stiffness, normal stiffness, bonding tensile strength and bonding shear strength; The mortar particles-mortar particles, aggregate-aggregate, mortar particles-aggregate, and mortar particles-fiber particles are all bonded using a parallel bonding model, and the input parameters include effective modulus, bonding tensile strength, bonding cohesion, and bonding friction angle.

9. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 1, characterized in that: During the initial equilibrium state analysis in step S5, the stress between the wall and the edge particles is monitored in real time. The stress between the wall and the edge particles controls the speed of the wall to ensure the stability of the applied pressure. When the stress between the edge particles and the wall reaches a preset value, the calculation is stopped.

10. The three-dimensional microscopic simulation method of steel fiber concrete compressive performance based on discrete element according to claim 1, characterized in that: In step S6, the steps of applying boundary conditions to the fiber concrete specimen and loading an external load to measure the compressive properties of the fiber concrete through a uniaxial compression test are as follows: The target loading speed of the uniaxial compression test is loaded on the fiber concrete specimen in sections, the stress-strain related data are saved, and the compressive stress-strain relationship is established as the calculation result of the fracture mechanics properties of the fiber concrete.

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