A Mesoscopic Lattice Model Modeling Method for UHPC-NC Structures

Abstract

The present invention relates to a mesoscopic lattice model modeling method for a UHPC-NC structure, including: determining the distribution range of lattice nodes, the degrees of freedom of nodes, and the element size according to the size characteristic parameters of UHPC-NC components and the characteristics of the lattice mesoscopic model, and establishing the framework of the lattice model, wherein the lattice model includes lattice nodes and lattice elements connected to each other between the lattice nodes; determining the key characteristic parameters of coarse aggregates and steel fibers according to the gradation of each component material used in UHPC and NC materials; generating mesoscopic random distribution models of steel fibers and coarse aggregates respectively based on the random distribution algorithm and the key characteristic parameters, and endowing the corresponding material properties and element properties to the lattice elements to obtain the lattice model. Compared with the prior art, the present invention comprehensively considers the mesoscopic structural characteristics of the two materials of UHPC-NC, and can model its structure more conveniently and accurately.

Description

Technical Field

[0001] The present invention relates to the field of numerical analysis of material simulation, and particularly to a mesoscopic lattice model modeling method for UHPC-NC structures. Background Art

[0002] Ultra-high performance concrete (UHPC) is an ultra-high strength cement-based composite material with extremely high tensile and compressive strengths. Steel fibers are uniformly distributed in the matrix, which not only increases the tensile strength of the material but also endows the UHPC material with good ductility, fatigue resistance, and strain hardening properties. UHPC has excellent mechanical and material properties, but its price is dozens of times that of traditional concrete (NC), which greatly restricts its popularization and application. Therefore, scholars have proposed applying UHPC materials to the parts of reinforced concrete structures that are subjected to complex mechanical loads or environmental erosion, that is, forming UHPC-NC composite structures. The UHPC-NC structure can not only give full play to the respective advantages of UHPC materials and concrete materials but also greatly reduce the construction cost and subsequent maintenance cost of the structure, and its economic and mechanical properties are also fully exerted.

[0003] The UHPC-NC composite structure is a combination of two materials with significantly different mechanical properties, namely UHPC and concrete. From a mesoscopic perspective, the UHPC material is a multiphase material composed of a matrix and steel fibers. The UHPC matrix is a typical brittle matrix. When subjected to a certain external load, microcracks will form inside the matrix and continue to expand and penetrate to form macroscopic cracks. Subsequently, the steel fibers will play a "bridging" role, making the UHPC as a whole exhibit higher tensile capacity, and the mesoscopic failure process is extremely complex. Similarly, the concrete material consists of aggregates, mortar matrix, and ITZ (Interfacial Transition Zone) at the mesoscopic scale. The mortar matrix has a higher porosity and more internal defects compared with the UHPC matrix and is more likely to form internal initial cracks. Therefore, the mesoscopic modeling of the UHPC-NC structure is of great significance for the refined study of its internal action mechanism.

[0004] Through the retrieval of the prior art, it is found that the mesoscopic modeling technology of cement-based materials mainly focuses on the modeling of concrete aggregates and steel fibers, aiming to provide an effective reference model for numerical calculation. In the Chinese patent "A two-dimensional random generation method for concrete aggregate units (authorization number CN 106874623 A)", Sharp et al. invented a two-dimensional random generation method for concrete aggregate units. This method continuously generates different polygonal aggregates and calculates the key shape parameters for comparison with the actual required aggregate units, and finally obtains polygonal aggregates with specific shapes. In the Chinese patent "A mesoscopic behavior analysis method for fiber asphalt concrete based on stochastic finite element", Xu Xunqian et al. constructed a three-dimensional random distribution model of fibers based on the Latin hypercube sampling method and the random generation algorithm. This method can generate the mesoscopic geometric distribution parameters of fibers relatively quickly and establish a mesoscopic numerical analysis model. In the existing research, there is currently no direct research on the mesoscopic modeling technology of UHPC-NC composite structures, lacking a mesoscopic modeling method for UHPC-NC composite structures. Summary of the Invention

[0005] The purpose of the present invention is to provide a mesoscopic lattice model modeling method for UHPC-NC structures, comprehensively considering the respective characteristics of the two materials in the composite structure for modeling, and providing a good mesoscopic model basis for refined analysis.

[0006] The purpose of the present invention can be achieved through the following technical solutions:

[0007] A mesoscopic lattice model modeling method for UHPC-NC structures includes the following steps:

[0008] According to the size characteristic parameters of UHPC-NC components and the characteristics of the lattice mesoscopic model, determine the distribution range of lattice nodes, the degrees of freedom of nodes, and the unit size, and establish the framework of the lattice model. Among them, the lattice model includes lattice nodes and lattice units connected to each other between lattice nodes. The degrees of freedom of the nodes are used as an index to control the randomness of the positions of the lattice model nodes, and the overall shape of the lattice model is controlled by controlling the distribution range of the lattice nodes;

[0009] According to the grading of each component material used in UHPC and NC materials, determine the key characteristic parameters of coarse aggregates and steel fibers;

[0010] Based on the random distribution algorithm and the key characteristic parameters, generate the mesoscopic random distribution models of steel fibers and coarse aggregates respectively, and endow the corresponding material properties and unit properties to the lattice units to obtain the lattice model.

[0011] The size characteristic parameters of the UHPC-NC component include the overall size of the UHPC-NC composite structure, the sub-item sizes of the UHPC part and the NC part, and the size of the UHPC and NC junction area.

[0012] The degree of freedom of the node is the ratio of the side length of the distribution range of the lattice nodes to the side length of the structural grid:

[0013]

[0014] where n is the degree of freedom of the node, and l m is the length of the structural grid, and l n is the length of the lattice node grid.

[0015] The key characteristic parameters of the coarse aggregate include the particle size and quantity of the coarse aggregate, and the key characteristic parameters of the steel fiber include the quantity of the steel fiber.

[0016] The particle size of the coarse aggregate is determined based on the following method:

[0017] Step 2-1-1) Determine the cumulative distribution function of the coarse aggregate:

[0018]

[0019] where P 2d is the two-dimensional cumulative distribution function of the coarse aggregate, d m is the maximum particle size of the coarse aggregate, d0 is the minimum particle size of the coarse aggregate, and d is the particle size of the coarse aggregate;

[0020] Step 2-1-2) Determine the cumulative probability of the aggregate corresponding to different particle sizes according to the cumulative distribution function of the coarse aggregate, and obtain the particle size range of the coarse aggregate and the corresponding ratio.

[0021] When the area A ca occupied by the coarse aggregate in the two-dimensional cross-section of the concrete is determined, the method for determining the quantity of the coarse aggregate includes the following steps:

[0022] Step 2-2-1) Generate a random number z i , and let z i be the cumulative probability of the aggregate corresponding to the particle size of the i-th aggregate;

[0023] Step 2-2-2) Determine the aggregate particle size d i corresponding to z i ;

[0024] Step 2-2-3) Accumulate the cross-sectional areas of the coarse aggregates that have been generated;

[0025]

[0026] where A i is the cross-sectional area of the coarse aggregate obtained after accumulating the i-th coarse aggregate;

[0027] Step 2-2-4) Determine whether the cross-sectional area A of the coarse aggregate i exceeds the area A of the concrete two-dimensional section occupied by the coarse aggregate ca . If so, output the quantities corresponding to different particle sizes of the coarse aggregate; otherwise, accumulate the quantity of the coarse aggregate corresponding to the current particle size, and repeat steps 2-2-1) - 2-2-3).

[0028] The quantity of the steel fibers is calculated based on the volume of the UHPC member, the volume content of the steel fibers, and the volume of the steel fibers:

[0029] n s = V U ρ s / V s

[0030] where n s is the quantity of the steel fibers, V U is the volume of the UHPC member, ρ s is the volume content of the steel fibers, and V s is the volume of the steel fibers.

[0031] The mesoscopic random distribution model of the steel fibers generated based on the random distribution algorithm includes the following steps:

[0032] Step 3-1-1) Determine the distribution range of the steel fibers and the quantity of the steel fibers;

[0033] Step 3-1-2) Each steel fiber includes 2 nodes. For the i-th steel fiber, randomly generate an initial node of the steel fiber inside the distribution range of the steel fibers. The position of the initial node is determined by the random numbers x i and y i . Taking the initial node as the origin of the polar coordinates, determine the coordinates of the second node according to the actual length of the steel fiber and the random polar coordinate angle ρ;

[0034] Step 3-1-3) Determine whether the coordinates of the second node exceed the pre-configured matrix range. If so, delete the coordinates and regenerate the coordinates of the second node of the steel fiber;

[0035] Step 3-1-4) Repeat steps 3-1-2) - 3-1-3) until all the steel fiber nodes are generated.

[0036] The mesoscopic random distribution model of the coarse aggregate generated based on the random distribution algorithm includes the following steps:

[0037] Step 3-2-1) Generate the coarse aggregate based on the particle size and quantity of the coarse aggregate;

[0038] Step 3-2-2) Arrange the generated coarse aggregate in descending order according to the particle size from large to small;

[0039] Step 3-2-3) Determine the placement range of the center of each coarse aggregate size. For the i-th coarse aggregate, determine the horizontal placement range as [d i / 2, b - d i / 2], and the vertical placement range as [d i / 2, a - d i / 2], where (a, b) represents the overall dimensions of the concrete member;

[0040] Step 3-2-4) Generate two random numbers X i and Y i , representing the center coordinates of the coarse aggregate;

[0041] Step 3-2-5) Determine whether the coarse aggregate to be pre-placed at the center coordinates corresponding to X i and Y i coincides with the already placed coarse aggregates. If they coincide, delete the center coordinates of the current coarse aggregate and repeat Step 3-2-4). If they do not coincide, place the current coarse aggregate;

[0042] Step 3-2-6) Repeat Steps 3-2-3) - 3-2-5) until all the randomly placed coarse aggregates are generated, obtaining the mesoscopic random distribution model of the coarse aggregates.

[0043] The principle of endowing the corresponding material properties and element properties to the lattice units is as follows:

[0044] Endow the corresponding lattice unit NC material properties to the NC material part in the framework of the lattice model to obtain the NC part model. In the UHPC material part, directly embed the generated steel fibers into the lattice model framework, and connect the steel fiber nodes with the lattice nodes to form connection units. In the junction area part, endow the corresponding lattice units with material properties conforming to the junction area characteristics to obtain the junction area units.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention comprehensively considers the mesoscopic structural characteristics of the two materials, concrete and UHPC, in the UHPC-NC composite structure. Therefore, it can establish the mesoscopic lattice model of the UHPC-NC composite structure according to the mesoscopic aggregate characteristic parameters of concrete and the steel fiber characteristic parameters, etc. It can not only make full use of the characteristics of the lattice truss model for more convenient simulation, but also provide a good mesoscopic model basis for subsequent refined analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 is the flowchart of the method of the present invention;

[0048] Figure 2 is the schematic diagram of the basic elements of the lattice model;

[0049] Figure 3 Schematic diagram of the dimensions of the UHPC-NC structure in one embodiment;

[0050] Figure 4 Schematic diagram of the lattice model framework in one embodiment;

[0051] Figure 5 Schematic diagram of the cumulative distribution probability of coarse aggregates in one embodiment;

[0052] Figure 6 Schematic diagram of the steel fiber distribution in one embodiment;

[0053] Figure 7 Schematic diagram of the distribution of concrete coarse aggregates in one embodiment;

[0054] Figure 8 Schematic diagram of the assignment of lattice model materials and unit properties;

[0055] Figure 9 Mesoscopic lattice model of the UHPC-NC composite member in one embodiment;

[0056] Figure 10 Junction zone lattice model in one embodiment. Detailed implementation mode

[0057] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation manners and specific operation processes are given, but the protection scope of the present invention is not limited to the following embodiments.

[0058] A mesoscopic lattice model modeling method for a UHPC-NC structure, as Figure 1 shown, includes the following steps:

[0059] 1) According to the size characteristic parameters of the UHPC-NC member and the characteristics of the lattice mesoscopic model, determine the distribution range of lattice nodes, the degrees of freedom of nodes, and the size of unit cells, and establish the framework of the lattice model;

[0060] The size characteristic parameters of the UHPC-NC member include the overall size of the UHPC-NC composite structure, the itemized sizes of the UHPC part and the NC part, and the size of the UHPC and NC junction zone.

[0061] The lattice model is a mesoscopic numerical model that discretizes a continuous structure into a finite number of units to calculate the macroscopic stress-strain relationship, including lattice nodes and lattice units that are interconnected between lattice nodes, as Figure 2As shown in the figure. First, the structure is divided into several grids, and the positions of each lattice node can be randomly distributed in the corresponding structural grids. To quantitatively control the grid shape of the entire lattice model, the present invention introduces the node degree of freedom n as an index to control the randomness degree of the lattice model node positions, and controls the overall shape of the lattice model by controlling the distribution range of the lattice nodes.

[0062] The node degree of freedom is the ratio of the side length of the lattice node distribution range to the side length of the structural grid:

[0063]

[0064] Among them, n is the node degree of freedom, l m is the length of the structural grid, and l n is the length of the lattice node grid.

[0065] In this embodiment, the mesoscopic lattice model is modeled with the UHPC-NC shear test as an example. The size of UHPC-NC is 150×150×150 mm, and the size schematic diagram is as Figure 3 shown.

[0066] The size of the shear two-dimensional model of the UHPC-NC composite specimen is 15×15 cm. To ensure that the width and position of the lattice model junction area are consistent with the test specimen, the lattice bar sizes of the bending and shear models are both taken as 1 mm. And when generating the two-dimensional image model of the concrete part and numerically dividing it into grids, the grid size is also selected as 1 mm. The framework of the finally generated UHPC-NC composite specimen lattice model is as Figure 4 shown.

[0067] 2) According to the gradations of the component materials used in UHPC and NC materials, determine the key characteristic parameters of the coarse aggregate and steel fiber. The key characteristic parameters of the coarse aggregate include the coarse aggregate particle size and quantity, and the key characteristic parameters of the steel fiber include the steel fiber quantity;

[0068] The concrete grade adopted in this embodiment is C50 concrete, and the range of its coarse aggregate particle size is 5-20 mm, and the proportion of the cross-sectional area of the coarse aggregate is 46%.

[0069] The coarse aggregate particle size is determined based on the following method:

[0070] Step 2-1-1) Determine the cumulative distribution function of the coarse aggregate:

[0071]

[0072] Among them, P 2d is the two-dimensional cumulative distribution function of the coarse aggregate, d m is the maximum coarse aggregate particle size, d0 is the minimum coarse aggregate particle size, and d is the coarse aggregate particle size;

[0073] Step 2-1-2) Determine the aggregate cumulative probability corresponding to different particle sizes according to the cumulative distribution function of coarse aggregate, and obtain the proportion corresponding to each particle size in the particle size range of 5-20 mm, as Figure 5 shown.

[0074] Under the condition that the area A ca occupied by the coarse aggregate in the two-dimensional section of the concrete is determined, the method for determining the quantity of the coarse aggregate includes the following steps:

[0075] Step 2-2-1) Generate a random number z in the interval [0, 1] i , and let z i be the aggregate cumulative probability corresponding to the particle size of the i-th aggregate;

[0076] Step 2-2-2) Determine the aggregate particle size d i corresponding to z i ;

[0077] Step 2-2-3) Accumulate the cross-sectional areas of the coarse aggregates that have been generated;

[0078]

[0079] where A i is the cross-sectional area of the coarse aggregate obtained after accumulating the i-th coarse aggregate;

[0080] Step 2-2-4) Determine whether the cross-sectional area A i of the coarse aggregate exceeds the area A ca occupied by the coarse aggregate in the two-dimensional section of the concrete. If so, output the quantities corresponding to different particle sizes of the coarse aggregate. Otherwise, accumulate the quantity of the coarse aggregate corresponding to the current particle size, and repeat steps 2-2-1)-2-2-3).

[0081] The quantity of the steel fiber is calculated according to the volume of the UHPC member, the volume content of the steel fiber, and the volume of the steel fiber:

[0082] n s = V U ρ s / V s

[0083] where n s is the quantity of the steel fiber, V U is the volume of the UHPC member, ρ s is the volume content of the steel fiber, and V s is the volume of the steel fiber.

[0084] 3) Generate the mesoscopic random distribution models of steel fibers and coarse aggregates respectively based on the random distribution algorithm and key characteristic parameters, and endow the corresponding material properties and element properties to the lattice units to obtain the lattice model.

[0085] The steps for generating the mesoscopic random distribution model of steel fibers based on the random distribution algorithm are as follows:

[0086] Step 3-1-1): Determine the distribution range of steel fibers and the number of steel fibers.

[0087] Each steel fiber includes 2 nodes. For the i-th steel fiber, randomly generate an initial node of the steel fiber inside the steel fiber distribution range, and the position of the initial node is determined by random numbers x i and y i . Taking the initial node as the origin of polar coordinates, determine the coordinates of the second node according to the actual length of the steel fiber and the random polar coordinate angle ρ.

[0088] Step 3-1-3): Determine whether the coordinates of the second node exceed the pre-configured matrix range. If so, delete the coordinates and regenerate the coordinates of the second node of the steel fiber.

[0089] Step 3-1-4): Repeat steps 3-1-2) - 3-1-3) until all steel fiber nodes are generated.

[0090] The steel fiber distribution diagram obtained in this embodiment is as Figure 6 shown.

[0091] The steps for generating the mesoscopic random distribution model of coarse aggregates based on the random distribution algorithm are as follows:

[0092] Step 3-2-1): Generate coarse aggregates based on the particle size and quantity of coarse aggregates.

[0093] Step 3-2-2): Arrange the generated coarse aggregates in descending order according to the particle size from large to small.

[0094] Step 3-2-3): Determine the placement range of the center of each coarse aggregate particle size. Among them, for the i-th coarse aggregate, determine the horizontal placement range as [d i / 2, b - d i / 2], and the vertical placement range as [d i / 2, a - d i / 2], where (a, b) represents the overall size of the concrete member.

[0095] Step 3-2-4): Generate two random numbers X i and Y i respectively according to the placement range, representing the coordinates of the center point of the coarse aggregate.

[0096] Step 3-2-5) Determine X i and Y i Whether the coarse aggregate pre-placed at the corresponding central coordinates coincides with the already placed coarse aggregate. If it coincides, delete the central coordinates of the current coarse aggregate and repeat Step 3-2-4). If it does not coincide, place the current coarse aggregate;

[0097] Step 3-2-6) Repeat Step 3-2-3) - Step 3-2-5) until all the randomly placed coarse aggregates generated are completed, and a mesoscopic random distribution model of the coarse aggregates is obtained.

[0098] The schematic diagram of the concrete coarse aggregate distribution obtained in this embodiment is as shown in Figure 7 shown.

[0099] The principle of endowing the corresponding material properties and element properties to the lattice units is as follows:

[0100] Endow the corresponding lattice unit NC material properties to the NC material part in the framework of the lattice model to obtain the NC part model. In the UHPC material part, directly embed the generated steel fibers into the lattice model framework, and connect the steel fiber nodes with the lattice nodes to form connection units. In the junction area part, endow the corresponding lattice units with material properties that conform to the characteristics of the junction area to obtain the junction area units, as shown in Figure 8 shown.

[0101] Among them, endowing the material properties to the NC material part includes the following steps:

[0102] According to the central point coordinates of the coarse aggregate (X i , Y i ) and the particle size d i , generate the particle size distribution image of the concrete component coarse aggregate;

[0103] Perform grayscale processing on the particle size distribution image of the coarse aggregate, use the size of the lattice unit as the smallest pixel point, and segment the particle size distribution image of the coarse aggregate;

[0104] Perform digital processing on the segmented grayscale image to digitalize the concrete mesoscopic structure, and use different numbers to represent the coarse aggregate, matrix, and aggregate-matrix junction area respectively;

[0105] According to the digital processing results, endow the corresponding material properties and element properties to the lattice units to obtain the NC part lattice model.

[0106] According to the above method, the mesoscopic lattice model of the UHPC-NC component is as shown in Figure 9 shown, and the lattice model of the junction area is as shown in Figure 10 shown.

[0107] The preferred specific embodiments of the present invention have been described in detail above. It should be understood that those of ordinary skill in the art can make many modifications and variations based on the concept of the present invention without creative efforts. Therefore, all technical solutions that can be obtained by those skilled in the art in the technical field based on the concept of the present invention through logical analysis, reasoning, or limited experiments on the basis of the prior art shall fall within the protection scope determined by the claims.

Claims

1. A mesoscopic lattice model modeling method for UHPC-NC structures, characterized in that, It includes the following steps: According to the size characteristic parameters of the UHPC-NC component and the characteristics of the lattice mesoscopic model, determine the distribution range of lattice nodes, the degrees of freedom of nodes, and the element size, and establish the framework of the lattice model. Among them, the lattice model includes lattice nodes and lattice elements connected to each other between the lattice nodes. The degrees of freedom of the nodes are used as indicators to control the randomness of the positions of the lattice model nodes. The overall shape of the lattice model is controlled by controlling the distribution range of the lattice nodes. According to the gradation of each component material used in UHPC and NC materials, determine the key characteristic parameters of coarse aggregate and steel fiber. Based on the random distribution algorithm and the key characteristic parameters, generate the mesoscopic random distribution models of steel fiber and coarse aggregate respectively, and endow the corresponding lattice elements with material properties and element properties to obtain the lattice model.

2. The mesoscopic lattice model modeling method of a UHPC-NC structure according to claim 1, characterized in that, The size characteristic parameters of the UHPC-NC component include the overall size of the UHPC-NC composite structure, the itemized sizes of the UHPC part and the NC part, and the size of the UHPC and NC junction area.

3. The meso-lattice model modeling method of a UHPC-NC structure according to claim 1, characterized in that The degrees of freedom of the nodes are the ratio of the side length of the lattice node distribution range to the side length of the structural grid: where n is the degree of freedom of the node, and l m is the length of the structural grid, and l n is the length of the grid of lattice nodes.

4. The meso-lattice model modeling method of a UHPC-NC structure according to claim 1, characterized in that, The key characteristic parameters of the coarse aggregate include the particle size and quantity of the coarse aggregate, and the key characteristic parameters of the steel fiber include the quantity of the steel fiber.

5. The meso-lattice model modeling method of a UHPC-NC structure according to claim 4, characterized in that, The particle size of the coarse aggregate is determined based on the following method: Step 2-1-1) Determine the cumulative distribution function of the coarse aggregate: where P 2d is the two-dimensional cumulative distribution function of coarse aggregates, d m is the maximum coarse aggregate size, d0 is the minimum coarse aggregate size, and d is the coarse aggregate size; Step 2-1-2) According to the cumulative distribution function of the coarse aggregate, determine the aggregate cumulative probability corresponding to different particle sizes to obtain the particle size range of the coarse aggregate and the corresponding ratio.

6. The mesoscopic lattice model modeling method of a UHPC-NC structure according to claim 5, characterized in that When the area A of the coarse aggregate occupying the two-dimensional section of the concrete is ca determined, the method for determining the quantity of the coarse aggregate includes the following steps: Step 2-2-1) Generate a random number z within the interval [0, 1] i , and let z i be the cumulative aggregate probability corresponding to the particle size of the i-th aggregate; Step 2-2-2) Determine z according to the cumulative distribution function of coarse aggregates i The corresponding aggregate particle size d i ; Step 2-2-3) Accumulate the cross-sectional areas of the generated coarse aggregates; Among them, A i is the cross-sectional area of the coarse aggregate obtained after accumulating the i-th coarse aggregate; Step 2-2-4) Determine whether the cross-sectional area A of the coarse aggregate i exceeds the area A of the concrete two-dimensional section occupied by the coarse aggregate ca . If so, output the quantities corresponding to different particle sizes of the coarse aggregate; otherwise, accumulate the quantity of the coarse aggregate corresponding to the current particle size, and repeat steps 2-2-1) - 2-2-3).

7. A mesoscopic lattice model modeling method for a UHPC-NC structure according to claim 4, characterized in that, The quantity of the steel fiber is calculated according to the volume of the UHPC component, the volume content of the steel fiber, and the volume of the steel fiber: n s = V U ρ s / V s Among them, n s is the number of steel fibers, V U is the volume of the UHPC component, ρ s is the volume content of steel fibers, V s is the volume of steel fibers.

8. A mesoscopic lattice model modeling method for a UHPC-NC structure according to claim 7, characterized in that Generating the mesoscopic random distribution model of the steel fiber based on the random distribution algorithm includes the following steps: Step 3-1-1) Determine the distribution range of the steel fiber and the quantity of the steel fiber; Step 3-1-2): Each steel fiber includes 2 nodes. For the i-th steel fiber, a starting node of the steel fiber is randomly generated within the steel fiber distribution range, and the position of the starting node is determined by random numbers x i and y i Determine. Taking the starting node as the origin of polar coordinates, determine the coordinates of the second node according to the actual length of the steel fiber and the random polar coordinate angle ρ; Step 3-1-3) Determine whether the coordinates of the second node exceed the pre-configured matrix range. If so, delete the coordinates and regenerate the coordinates of the second node of the steel fiber; Step 3-1-4) Repeat steps 3-1-2)-3-1-3) until all steel fiber nodes are generated.

9. The mesoscopic lattice model modeling method of a UHPC-NC structure according to claim 6, characterized in that Generating the mesoscopic random distribution model of the coarse aggregate based on the random distribution algorithm includes the following steps: Step 3-2-1) Generate the coarse aggregate based on the particle size and quantity of the coarse aggregate; Step 3-2-2) Arrange the generated coarse aggregates in descending order according to the particle size from large to small; Step 3-2-3) Determine the placement range of the center of each coarse aggregate particle size. For the i-th coarse aggregate, determine the horizontal placement range as [d i / 2, b - d i / 2], and the vertical placement range as [d i / 2, a - d i / 2], where (a, b) represents the overall dimensions of the concrete member; Step 3-2-4) Generate two random numbers X i and Y i respectively according to the placement range, representing the center point coordinates of the coarse aggregate; Step 3-2-5) Determine X i and Y i whether the pre-placed coarse aggregate corresponding to the center coordinates coincides with the already placed coarse aggregate. If they coincide, delete the center coordinates of the current coarse aggregate and re-perform Step 3-2-4). If they do not coincide, place the current coarse aggregate; Step 3-2-6) Repeat steps 3-2-3)-3-2-5) until all the generated coarse aggregates are randomly placed, and obtain the mesoscopic random distribution model of the coarse aggregate.

10. The mesoscopic lattice model modeling method of a UHPC-NC structure according to claim 1, characterized in that, The principle of endowing the corresponding lattice elements with material properties and element properties is as follows: Endow the corresponding lattice elements in the NC material part of the framework of the lattice model with the NC material properties to obtain the NC part model. In the UHPC material part, directly embed the generated steel fibers into the framework of the lattice model, and connect the steel fiber nodes with the lattice nodes to form connection units. In the junction area part, endow the corresponding lattice elements with material properties that conform to the characteristics of the junction area to obtain the junction area units.

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