Concrete Model Generation Method, Device, Equipment, Storage Medium and Product

Abstract

The present application provides a method, apparatus, device, storage medium and product for generating a concrete model. The method includes: obtaining aggregate particle size information, an initial concrete model and a preset aggregate volume ratio; generating aggregates in the initial concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a first threshold; performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a first concrete model; generating aggregates in the first concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a second threshold; performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a second concrete model; generating aggregates in the second concrete model according to the aggregate particle size information until the aggregate volume ratio reaches the preset aggregate volume ratio to obtain a final concrete model, which can improve the generation efficiency and the authenticity of the model, and at the same time realizes the efficient generation of a random aggregate model.

Description

Technical Field

[0001] The present application relates to the technical field of data processing, and in particular, to a method, device, equipment, storage medium and product for generating a concrete model. Background Art

[0002] Large-scale projects such as reservoir dams, nuclear power plants, heavy industrial infrastructures, national defense facilities, and large bridge foundations usually need to bear huge pressures and loads. The single structure volume of mass concrete is large, and the concrete volume is large and the thickness is thick, which can provide sufficient stiffness to ensure the stability and long-term bearing capacity of the structure. However, the experimental cost of measuring various properties of mass concrete is huge, and through numerical simulation technology, the test cost can be greatly reduced. Therefore, the related technologies for numerical simulation of mass concrete components are gradually developing.

[0003] In the concrete vibration compaction process, the purpose of vibration compaction is to rearrange the aggregates and mortar in the concrete through vibration, thereby improving the density of the concrete. In the prior art, a physical model can be used to simulate vibration compaction to generate a high-density concrete mesoscopic model. Compared with the physical model, the mathematical model has higher efficiency and better controllability. However, in the actual vibration compaction process, the aggregates are affected by the bonding action of the mortar, and the actual falling distance is extremely small. "Falling" refers to the position change of the aggregates due to the action of gravity during the vibration compaction process. The prior art has limitations in space, and small-sized aggregates cannot be generated in the gaps of large-sized aggregates in the lower layer during the falling process, which will cause a certain amount of volume loss and cannot efficiently generate a random aggregate model. Summary of the Invention

[0004] Embodiments of the present application provide a method, device, equipment, storage medium and product for generating a concrete model, which can efficiently generate a random aggregate model.

[0005] In a first aspect, the present application provides a method for generating a concrete model, the method comprising:

[0006] Obtaining aggregate particle size information, an initial concrete model, and a preset aggregate volume ratio, where the preset aggregate volume ratio represents the target value of the volume ratio of the aggregates in the concrete model in the concrete;

[0007] Generating aggregates in the initial concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a first threshold, where the first threshold is one-third of the preset aggregate volume ratio, and the aggregate volume ratio represents the volume ratio of the currently generated aggregates in the concrete model;

[0008] Performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete specimen to obtain a first concrete model;

[0009] Generate aggregates in the first concrete model according to the aggregate particle size information until the volume ratio of the aggregates reaches a second threshold, where the second threshold is two-thirds of the preset aggregate volume ratio;

[0010] Perform aggregate falling simulation according to the preset falling time and the bottom boundary of the concrete specimen to obtain a second concrete model;

[0011] Generate aggregates in the second concrete model according to the aggregate particle size information until the volume ratio of the aggregates reaches the preset aggregate volume ratio to obtain a final concrete model.

[0012] In some possible implementation manners, the generating aggregates in the initial concrete model according to the aggregate particle size information until the volume ratio of the aggregates reaches a first threshold includes:

[0013] Randomly select a target particle size value according to the aggregate particle size range corresponding to the aggregate particle size information;

[0014] Determine the central point coordinates of the aggregates in the initial concrete model;

[0015] Generate aggregates according to the central point coordinates and the target particle size value;

[0016] Continue to randomly select a target particle size value according to the aggregate particle size range corresponding to the aggregate particle size information and generate aggregates again until the volume ratio of the aggregates reaches the first threshold.

[0017] In some possible implementation manners, the generating aggregates according to the central point coordinates and the target particle size value includes:

[0018] Determine the position of the aggregate to be generated according to the central point coordinates and the target particle size value, and judge whether the aggregate to be generated overlaps with the existing aggregates;

[0019] In the case where the aggregate to be generated overlaps with the existing aggregates, determine the distance between the central point coordinates of the aggregate to be generated and the corresponding overlapping aggregate;

[0020] In the case where the distance meets the preset condition, update the target particle size value according to the distance so that the aggregate to be generated no longer overlaps with the overlapping aggregate;

[0021] Generate aggregates according to the central point coordinates and the updated target particle size value.

[0022] In some possible implementation manners, the aggregate is an icosahedron aggregate, and the generating aggregates according to the central point coordinates and the target particle size value includes:

[0023] Taking the coordinates of the center point as the center, generate a sphere according to the target particle size value;

[0024] Randomly generate an inscribed hexahedron of the sphere;

[0025] According to the vertex coordinates of the inscribed hexahedron, calculate the geometric center point of the hexahedron;

[0026] Based on the geometric center point, make extension lines along the normal vectors of each face to determine the extension points corresponding to the six faces respectively;

[0027] Connect each of the extension points with the vertices of the inscribed hexahedron of the corresponding face to generate a twenty-four-sided aggregate.

[0028] In some possible implementation manners, the performing aggregate falling simulation according to the preset falling time and the bottom boundary of the concrete specimen to obtain a first concrete model includes:

[0029] Mark the aggregates whose distances from the bottom boundary of the concrete specimen are less than the preset threshold;

[0030] For each unmarked aggregate, respectively perform the following steps:

[0031] Move the aggregate and let the aggregate fall a preset distance;

[0032] Determine the distances between the aggregate and other aggregates;

[0033] According to the distances between the aggregate and other aggregates, determine the final position of the aggregate;

[0034] Increase the elapsed falling time at preset time intervals;

[0035] When the elapsed falling time is less than the preset falling time, continue to execute the falling process and increase the elapsed falling time;

[0036] When the elapsed falling time is greater than or equal to the preset falling time, determine the current concrete model as the first concrete model.

[0037] In some possible implementation manners, the determining the final position of the aggregate according to the distances between the aggregate and other aggregates includes:

[0038] Detect whether the aggregate coincides with other aggregates according to whether the distances between the aggregate and other aggregates are less than the preset threshold;

[0039] When the aggregate coincides with other aggregates, calculate the direction vector of the line connecting the aggregate and the center point of the coincident aggregates;

[0040] Move the aggregate according to the direction vector so that the aggregate no longer coincides with other aggregates, and determine the final position of the aggregate.

[0041] In a second aspect, the present application provides a concrete model generation device, the device includes:

[0042] An acquisition module, configured to acquire aggregate particle size information, an initial concrete model, and a preset aggregate volume ratio, where the preset aggregate volume ratio represents the target value of the volume ratio of the aggregate in the concrete in the concrete model;

[0043] A generation module, configured to generate aggregates in the initial concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a first threshold, where the first threshold is one-third of the preset aggregate volume ratio, and the aggregate volume ratio represents the volume ratio of the currently generated aggregates in the concrete model;

[0044] A simulation module, configured to perform aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete specimen to obtain a first concrete model;

[0045] The generation module is further configured to generate aggregates in the first concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a second threshold, where the second threshold is two-thirds of the preset aggregate volume ratio;

[0046] The simulation module is further configured to perform aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete specimen to obtain a second concrete model;

[0047] The generation module is further configured to generate aggregates in the second concrete model according to the aggregate particle size information until the aggregate volume ratio reaches the preset aggregate volume ratio to obtain a final concrete model.

[0048] In a third aspect, the present application provides a concrete model generation device, the device includes: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the concrete model generation method described above.

[0049] In a fourth aspect, the present application provides a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are executed by a processor, the concrete model generation method described above is implemented.

[0050] In a fifth aspect, the present application provides a computer program product, when the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is caused to execute the concrete model generation method described above.

[0051] The concrete model generation method, device, equipment, storage medium and product provided by the embodiments of the present application, through an optimized algorithm and a step-by-step generation method, without the assistance of a physical model, greatly reduces the complexity of the algorithm, simplifies the generation process, and uses the optimized algorithm and an aggregate model closer to the real situation, significantly improving the generation efficiency and the authenticity of the model, and at the same time realizing the efficient generation of a random aggregate model. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The present application can be better understood from the following description of the specific embodiments in conjunction with the drawings, where:

[0053] By reading the following detailed description of non-limiting embodiments with reference to the drawings, other features, objects and advantages of the present application will become more apparent, where the same or similar reference numerals represent the same or similar features.

[0054] Figure 1 is a flowchart of a concrete model generation method provided by an embodiment of the present application;

[0055] Figure 2 is a schematic diagram of the generation process of a twenty-four-sided body aggregate provided by an embodiment of the present application;

[0056] Figure 3 is a schematic diagram of a concrete model provided by another embodiment of the present application;

[0057] Figure 4 is a schematic diagram of the generation process of a concrete model provided by another embodiment of the present application;

[0058] Figure 5 is a schematic diagram of a concrete model provided by another embodiment of the present application;

[0059] Figure 6 is a schematic cross-sectional view of a concrete model provided by another embodiment of the present application;

[0060] Figure 7 is a schematic structural diagram of a concrete model generation device provided by an embodiment of the present application;

[0061] Figure 8 is a schematic hardware structure diagram of a concrete model generation device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0062] The features and exemplary embodiments of various aspects of the present application will be described in detail below. To make the objectives, technical solutions, and advantages of the present application clearer and more understandable, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application and not to limit the present application. For those skilled in the art, the present application can be implemented without some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0063] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising..." does not exclude the existence of additional identical elements in the process, method, article or device comprising the above elements.

[0064] To solve the problems of the prior art, an embodiment of the present application provides a method, device, equipment, storage medium and product for generating a concrete model. First, the method for generating a concrete model provided by the embodiment of the present application will be introduced below.

[0065] Figure 1 The flowchart of the method for generating a concrete model provided by an embodiment of the present application is shown. As Figure 1 shown, the method includes the following steps: S101 to S106.

[0066] S101: Obtain aggregate particle size information, an initial concrete model, and a preset aggregate volume ratio, where the preset aggregate volume ratio represents the target value of the volume ratio of aggregates in the concrete in the concrete model.

[0067] In a specific implementation, the aggregate particle size information is usually obtained through input parameters or a database, and these particle size data determine the size distribution of the aggregates. The initial concrete model is a concrete model that does not include aggregates, and its size is pre-determined. The preset aggregate volume ratio is the target aggregate volume ratio preset by the user and is used to determine how to introduce the aggregates into the concrete model.

[0068] S102: Generate aggregates in the above initial concrete model according to the above aggregate particle size information until the volume ratio of the aggregates reaches a first threshold, where the first threshold is one-third of the preset aggregate volume ratio, and the aggregate volume ratio represents the volume ratio of the currently generated aggregates in the concrete model.

[0069] In specific implementation, according to the particle size information obtained in step S101, insert into the initial concrete model step by step according to the characteristics of aggregates with different particle sizes. During the process of inserting aggregates into the initial concrete model, calculate the current volume ratio in real time. When the volume of aggregates filled into the model reaches the first threshold, the insertion process stops.

[0070] S103: Perform aggregate falling simulation according to the preset falling time and the bottom boundary of the concrete specimen to obtain a first concrete model.

[0071] In specific implementation, preset the falling time in advance, that is, the duration of the process of aggregates falling from above to the bottom of the concrete specimen. During the simulation process, the aggregates will finally obtain a new concrete model, namely the first concrete model, according to conditions such as time, falling speed, and the bottom boundary of the concrete specimen.

[0072] S104: Generate aggregates in the above first concrete model according to the above aggregate particle size information until the volume ratio of the aggregates reaches a second threshold, where the second threshold is two-thirds of the preset aggregate volume ratio.

[0073] In specific implementation, based on the first concrete model, add more aggregates according to the particle size information again. At this time, use a method similar to that in S102 to continue inserting more aggregates into the model until the requirements of the second threshold are met. The second threshold is two-thirds of the preset aggregate volume ratio.

[0074] S105: Perform aggregate falling simulation according to the preset falling time and the bottom boundary of the concrete specimen to obtain a second concrete model.

[0075] In specific implementation, after the second filling, continue to perform the falling simulation to simulate the settlement of aggregates in the concrete and obtain the second concrete model, which has an updated aggregate distribution and volume ratio.

[0076] S106: Generate aggregates in the above second concrete model according to the above aggregate particle size information until the volume ratio of the aggregates reaches the above preset aggregate volume ratio to obtain a final concrete model.

[0077] In specific implementation, according to the final preset aggregate volume ratio, the software continues to generate aggregates and add them to the second concrete model until the set ratio is reached to obtain a final concrete model.

[0078] The concrete model generation method provided by the embodiments of the present application, through an optimized algorithm and a step-by-step generation method, without the assistance of a physical model, greatly reduces the complexity of the algorithm, simplifies the generation process, and uses the optimized algorithm and an aggregate model closer to the actual situation, significantly improving the generation efficiency and the authenticity of the model, and at the same time realizing the efficient generation of a random aggregate model.

[0079] To ensure the accuracy during the simulation process, in some embodiments, the above S102 may include the following steps: S1021 to S1024.

[0080] S1021: Randomly select a target particle size value according to the aggregate particle size range corresponding to the above aggregate particle size information.

[0081] In a specific implementation, according to the aggregate particle size range corresponding to the above aggregate particle size information, for example, assuming the aggregate particle size range is from 5 mm to 10 mm, then randomly select a particle size value between 5 mm and 10 mm. A random number generator can be used to generate a floating particle size value within this range. For example, if the randomly generated value is 7.3 mm, then this value is used as the current aggregate particle size to obtain the target particle size value.

[0082] S1022: Determine the center point coordinates of the aggregate in the above initial concrete model.

[0083] In a specific implementation, during the simulation, a three-dimensional grid is usually set up for the spatial positioning of the aggregate. Each time an aggregate is generated, a suitable coordinate point is selected within the entire grid space as the center point coordinates of the aggregate.

[0084] S1023: Generate the aggregate according to the above center point coordinates and the above target particle size value.

[0085] In a specific implementation, first, shape selection is performed. For example, the aggregate is set to be spherical. If the particle size value is 7.3 mm, then the diameter of the aggregate will be 7.3 mm. A modeling tool is used to construct the aggregate. The aggregate can be represented by a spherical three-dimensional geometric body, or a more complex geometric model can be used according to actual needs. According to the coordinates obtained in step S1022, the generated aggregate is placed at this position. At this time, the geometric center point of the aggregate is the above determined coordinates. If there are aggregates of multiple particle sizes, the shape and size of the aggregates of different particle sizes are controlled through parameter transfer to generate the aggregates.

[0086] S1024: Return to the above S1021 to generate the aggregate again until the volume ratio of the aggregate reaches the first threshold.

[0087] In a specific implementation, continuously calculate the total volume of all the aggregates that have been inserted currently, and compare it with the total volume of the current concrete model. If the volume ratio does not reach a predetermined first threshold, continue to generate new aggregates. Specifically, repeat steps S1021 to S1023, that is, randomly select a particle size value from within the aggregate particle size range again, and insert a new aggregate into the concrete model according to the generated particle size and position. After each new aggregate is generated, recalculate the current volume ratio until the aggregate volume ratio reaches the first threshold.

[0088] The above implementation manner of the embodiment of the present application selects a target particle size value from a given particle size range through a random number generation technique, randomly selects a valid position in the concrete model as the center point of the aggregate, and ensures that there is no overlap with other objects. Generate an aggregate according to the selected particle size value and position coordinates, form a complete geometric model and insert it into the concrete. Continuously generate aggregates and insert them into the concrete model until the volume ratio of the aggregates reaches the first threshold. Fine-control the generation of aggregates in an iterative manner to ensure that the final concrete model meets the design requirements and ensure the accuracy during the simulation process.

[0089] In order to ensure that the generated aggregates do not overlap with the existing aggregates, in some implementation manners, the above S1023 may include the following steps: S10231 to S10234.

[0090] S10231: According to the above center point coordinates and the above target particle size value, determine the position of the aggregate to be generated, and judge whether there is an overlap between the aggregate to be generated and the existing aggregates.

[0091] In a specific implementation, according to the above center point coordinates and the above target particle size value, calculate the boundary of the aggregate to be generated. For example, the range of the aggregate to be generated can be regarded as a spherical region with the center point as the center of the sphere and the radius determined by the target particle size value. In order to judge whether the aggregate to be generated overlaps with the existing aggregates, distance detection can be used. Calculate the distance between the center point of the aggregate to be generated and the center point of the existing aggregates. If the distance between the two is less than the sum of their radii, it means that they overlap.

[0092] S10232: In the case where there is an overlap between the aggregate to be generated and the existing aggregates, determine the distance between the center point coordinates of the aggregate to be generated and the corresponding overlapping aggregate.

[0093] In a specific implementation, if step S10231 judges that there is an overlap between the aggregate to be generated and the existing aggregates, determine specifically which existing aggregates overlap. For each overlapping existing aggregate, calculate the distance between the center point of the aggregate to be generated and the center point of this existing aggregate.

[0094] S10233: When the above distance meets the preset condition, update the above target particle size value according to the above distance, so that the to-be-generated aggregate no longer coincides with the overlapping aggregate.

[0095] In specific implementation, set a preset distance condition, that is, a maximum allowable overlapping distance. If the distance calculated in step S10232 is less than this preset condition, then proceed to the next step of adjusting the particle size. Once it is detected that the to-be-generated aggregate coincides with the existing aggregate and the overlapping distance is less than the preset condition, update the above target particle size value so that the to-be-generated aggregate no longer coincides with the overlapping aggregate.

[0096] S10234: Generate an aggregate according to the above center point coordinates and the updated above target particle size value.

[0097] In specific implementation, according to the updated particle size value in step S10233, recalculate the boundary of the generated aggregate. For the updated particle size, the spatial range of the aggregate can be redefined to ensure that it does not coincide with other aggregates, and then generate the aggregate.

[0098] The above implementation manner of the embodiment of the present application determines the position of the to-be-generated aggregate according to the above center point coordinates and the above target particle size value, judges whether the to-be-generated aggregate coincides with the existing aggregate. When the to-be-generated aggregate coincides with the existing aggregate, determine the distance between the center point coordinates of the to-be-generated aggregate and the corresponding overlapping aggregate. When the above distance meets the preset condition, update the above target particle size value according to the above distance so that the to-be-generated aggregate no longer coincides with the overlapping aggregate. Finally, generate an aggregate according to the above center point coordinates and the updated above target particle size value, dynamically judge whether the to-be-generated aggregate coincides with the existing aggregate, and adjust the particle size and position in the case of coincidence, so as to ensure that the generated aggregate does not coincide with the existing aggregate.

[0099] In order to ensure that the finally generated aggregate meets the target particle size and has the required geometric structure, in some implementation manners, the above S1023 may include the following steps: S10231A to S10235A.

[0100] S10231A: Generate a sphere with the center point coordinates as the center and according to the target particle size value.

[0101] In specific implementation, after receiving the center point coordinates of the to-be-generated aggregate and the target particle size value, calculate the boundary of the to-be-generated aggregate according to the target particle size value. The range of the to-be-generated aggregate can be regarded as a spherical area with the center point as the center and the radius determined by the target particle size.

[0102] S10232A: Generate an inscribed random hexahedron of the sphere.

[0103] An inscribed random hexahedron refers to a hexahedron that is inscribed in a sphere, but its specific shape is randomly generated.

[0104] In a specific implementation, as a way to ensure that the hexahedron is inscribed in the sphere, the positions of the eight vertices of the hexahedron can be limited to the positions on the surface of the sphere, and then the coordinates of the eight vertices of the hexahedron can be determined in a randomly generated manner on the surface of the sphere to generate the inscribed random hexahedron of the sphere.

[0105] S10233A: Calculate the geometric center point of the hexahedron according to the vertex coordinates of the inscribed hexahedron.

[0106] In a specific implementation, a hexahedron is defined by eight vertices, each face is composed of four vertices, and each face is a quadrilateral. By traversing the eight vertex coordinates and averaging their respective coordinates, the coordinates of the geometric center point of the hexahedron can be obtained.

[0107] Furthermore, the above eight vertices are obtained by first determining a quadrilateral face and a corresponding point, and then calculating the remaining three points based on these 5 vertices.

[0108] S10234A: Based on the geometric center point, draw extension lines along the normal vectors of each face to determine the corresponding extension points of the six faces.

[0109] In a specific implementation, each face has a normal vector, which can be determined by the vertex coordinates of the hexahedron. The normal vector is a vector perpendicular to the face, and the normal vector can be obtained by the cross product of two edges on the face. The normal vector points from the geometric center point of the hexahedron to the normal of each face. Starting from the geometric center point, draw perpendicular lines along the direction of the normal vector of each face. The end points of these perpendicular lines will be the extension points inside the sphere. Measure the extension length of each perpendicular line so that the perpendicular line intersects the surface of the sphere. Specifically, the intersection point of the perpendicular line and the sphere can be solved by the sphere equation. According to the sphere equation, solve the intersection point of each perpendicular line and the sphere to determine each extension point.

[0110] S10235A: Connect each of the extension points with the vertices of the inscribed random hexahedron of the corresponding face to generate a twenty - four - faced aggregate.

[0111] In a specific implementation, for the extension point on each face, connect it with the four vertices on that face, that is, the vertices of the inscribed random hexahedron. Each face will generate four triangles (each extension point and four vertices form a triangular face). In this way, 4 new triangles can be generated for each face. A total of 24 triangular faces are generated on the six faces, and the set of these triangular faces constitutes a twenty - four - faced body, thereby generating a twenty - four - faced aggregate.

[0112] Through multiple geometric calculations in the above embodiments of the present application, an inscribed random hexahedron is generated, and then the geometric center point and the calculated extension point are deduced. Finally, by connecting the extension point and the vertex, an icosahedron is constructed, ensuring that the finally generated aggregate meets the target particle size and has the required geometric structure.

[0113] As another example, in some embodiments, the above S1023 may include the following steps:

[0114] Determine the body diagonal length of the target cube according to the above target particle size value, and generate a cube based on the above center point coordinates.

[0115] The body diagonal is a line segment connecting the vertices opposite to each other on the faces that are not in the same plane of the cube to be generated. Its length determines the size of the generated cube and is also equivalent to the aggregate particle size.

[0116] In a specific implementation, the body diagonal length of the cube is directly related to the target particle size value. Given the target particle size value, the body diagonal length of the cube can be deduced. Based on the above center point coordinates, the 8 vertices of the cube are determined according to the diagonal length, and the geometric shape of the cube is defined by these vertices to generate the cube.

[0117] Based on the above center point coordinates, perpendiculars are drawn to the six faces of the cube according to the above target particle size value to determine the extension points corresponding to the six faces respectively.

[0118] In a specific implementation, starting from the geometric center point of the cube, perpendiculars are drawn along the normal vector direction of each face until the perpendiculars intersect with the surface of the sphere. The extension points will be outside the cube and on the surface of the sphere, and the extension points corresponding to the six faces are obtained.

[0119] Connect each of the above extension points with the cube vertices of the corresponding face to generate an icosahedron aggregate.

[0120] In a specific implementation, for each face of the cube, the extension point forms connections with the four vertices on that face to generate four triangles. Four triangles are generated for each face. Therefore, a total of 24 triangular faces will be generated for the six faces. These triangular faces together form an icosahedron. Each face of the icosahedron consists of the extension point and the four vertices of the cube. By connecting these vertices and the extension point, the aggregate of the icosahedron is finally constructed.

[0121] In order to generate a reasonable concrete model, in some embodiments, the above S103 may include the following steps: S1031 to S1037.

[0122] S1031: Mark the aggregates whose distance from the bottom boundary of the concrete specimen is less than a preset threshold.

[0123] In a specific implementation, first, the coordinate position of the bottom boundary of the concrete specimen needs to be obtained. For each aggregate, calculate the distance between its current position and the bottom of the concrete specimen. Set a threshold. If the distance of the aggregate is less than this threshold, mark the aggregate as having approached the bottom or having touched the bottom. For the qualified aggregates, mark their status as "having touched the bottom".

[0124] For each unmarked aggregate, perform the following steps S1032 to S1034 respectively.

[0125] S1032: Move the aggregate and let the above-mentioned aggregate fall a preset distance.

[0126] In a specific implementation, for the unmarked aggregate, set a preset falling distance, and move the aggregate according to the preset falling distance, and update its current coordinates to the new position.

[0127] As another example, if the falling process of the aggregate is simulated by a physics engine, it may be necessary to check whether the aggregate collides with or touches other objects, and these collisions and contacts will affect the falling process.

[0128] S1033: Determine the distance between the above-mentioned aggregate and other aggregates.

[0129] In a specific implementation, for the current aggregate, traverse all other aggregates and calculate the distance between them.

[0130] S1034: Determine the final position of the above-mentioned aggregate according to the distance between the above-mentioned aggregate and other aggregates.

[0131] In a specific implementation, set a distance threshold. If the calculated distance is less than the threshold, it means that the two aggregates are in contact or may collide. According to the collision detection result, readjust the position of the aggregate to make the aggregate stop falling or shift relative to other aggregates.

[0132] S1035: Increase the falling time at a preset time interval.

[0133] In a specific implementation, initialize the falling time to zero. In each simulation loop, increase the falling time according to the time step.

[0134] S1036: When the above-mentioned falling time is less than the preset falling time, continue to perform steps S1032 to S1034 respectively.

[0135] In a specific implementation, when the above-mentioned elapsed falling time is less than the preset falling time, the falling process of the aggregate is continued, and the position of the aggregate is continuously updated.

[0136] S1037: When the above-mentioned elapsed falling time is greater than or equal to the preset falling time, the current concrete model is determined as the first concrete model.

[0137] In a specific implementation, when the above-mentioned elapsed falling time is greater than or equal to the preset falling time, the current concrete model (including the final positions and states of all aggregates) is determined as the first concrete model.

[0138] The above implementation manner of the embodiments of the present application simulates the falling process of the aggregate in the concrete, adjusts the position and state of the aggregate according to preset conditions, and manages the simulation progress through time control. The key steps include calculating the distance between the aggregate and the bottom, simulating the falling of the aggregate, detecting the collision between the aggregates, and controlling the falling progress according to time, and finally generating a reasonable concrete model.

[0139] In order to accurately determine the final position of the aggregate, in some embodiments, the above S1034 may include the following steps: S10341 to S10343.

[0140] S10341: Detect whether the above-mentioned aggregate coincides with other aggregates according to whether the distance between the above-mentioned aggregate and other aggregates is less than a preset threshold.

[0141] In a specific implementation, after calculating the distance, check whether it is less than the preset threshold. If it is found that the distance between the aggregates is less than the threshold, it is considered that they coincide and further processing is required. Otherwise, skip this pair of aggregates and continue to detect other pairs of aggregates.

[0142] S10342: When the above-mentioned aggregate coincides with other aggregates, calculate the direction vector of the line connecting the above-mentioned aggregate and the center point of the coincident aggregate.

[0143] In a specific implementation, when the above-mentioned aggregate coincides with other aggregates, the direction vector is obtained according to the line connecting the above-mentioned aggregate and the center point of the coincident aggregate.

[0144] S10343: Move the above-mentioned aggregate according to the above-mentioned direction vector so that the above-mentioned aggregate no longer coincides with other aggregates, and determine the final position of the above-mentioned aggregate.

[0145] In a specific implementation, the movement amount of the aggregate needs to be related to the distance and the threshold. If the aggregates overlap, the actual movement amount may need to be determined according to a preset movement step or distance. By applying the movement amount to the current position of the aggregate, the new position of the aggregate can be obtained. To avoid the aggregate being moved too far or out of the reasonable range, it can be checked whether there is still an overlap after the movement. If the aggregate still overlaps with other aggregates, it can be continuously adjusted until there is no overlap, and the final position of the above-mentioned aggregate is determined.

[0146] In the above implementation manner of the embodiment of the present application, by detecting whether the above-mentioned aggregate overlaps with other aggregates according to whether the distance between the above-mentioned aggregate and other aggregates is less than a preset threshold, and then, in the case where the above-mentioned aggregate overlaps with other aggregates, calculating the direction vector of the line connecting the above-mentioned aggregate and the center point of the overlapping aggregate, and then moving the above-mentioned aggregate according to the above-mentioned direction vector so that the above-mentioned aggregate no longer overlaps with other aggregates, and determining the final position of the above-mentioned aggregate, the three key steps of collision detection, direction calculation, and movement adjustment are used to finally ensure that the aggregates no longer overlap with each other and can accurately determine the final position.

[0147] In an embodiment of the present application, the concrete test block is a cube. The side length SL of the cube concrete test block is set to 10, the preset volume ratio YT is 50%, the initial aggregate volume T is 0, the maximum value of the generated aggregate particle size is 2.5, and the minimum value is 0.5. The volume ratio maxYT of the large particle size aggregate is set to 45%. And the particle size Dia is generated and stored in the aggregate information matrix. The specific setting process is as follows:

[0148] 。

[0149] Among them, is a function for generating random numbers, which usually generates random numbers uniformly distributed in the interval [0, 1). Then is to multiply the generated random number by 1.5 to obtain a random number in the interval [0, 1.5).

[0150] 。

[0151] Among them, represents generating a 1-row and 3-column random number matrix, and each element is a random number uniformly distributed in the interval [0, 1), respectively representing the coordinate values in the three directions of x, y, and z in the three-dimensional space. Multiply the generated random proportional factor matrix by the maximum side length to obtain a three-dimensional vector that varies in the interval, representing the relative position range of the aggregate center point inside the test block. Multiply the above-obtained three-dimensional vector by Add them together and finally get the center point of the aggregate.

[0152] Calculate the distance between the placed aggregate and the existing aggregate, and determine whether the placed aggregate overlaps with the existing aggregate by the distance between the aggregates. If they completely overlap, delete the placed aggregate information and return to the step of setting the volume of the large-diameter aggregate; if they partially overlap and the distance from the center point to the surface of the existing aggregate is greater than the minimum diameter, keep the coordinates of the center point of the new aggregate , regenerate particle size , so that the added aggregate does not overlap with the existing aggregate; if they do not overlap, all information of the new aggregate is retained.

[0153] Calculate whether the aggregate volume ratio reaches If the requirement is not met, return to the step of setting the volume of large-size aggregate, otherwise proceed to the next step. Use the random function to randomly generate the center point of the spherical aggregate inside the test block. and particle size And store it in the aggregate information matrix. The specific setting process is as follows:

[0154] ;

[0155] ;

[0156] Calculate the distance between the placed aggregate and the existing aggregate, and determine whether the placed aggregate overlaps with the existing aggregate based on the distance between the aggregates.

[0157] If they completely overlap, delete the aggregate information and return to the above step of randomly generating spherical aggregates; if they partially overlap and the distance from the center point to the surface of the existing aggregate is greater than the minimum particle size, keep the coordinates of the center point of the new aggregate , regenerate particle size , so that the added aggregate does not overlap with the existing aggregate; if they do not overlap, all information of the new aggregate is retained.

[0158] Calculate whether the aggregate volume ratio reaches the above preset volume ratio If the requirement is not met, return to the above step of randomly generating spherical aggregates, otherwise proceed to the next step.

[0159] After that, the spherical aggregate is degenerated into a polyhedral aggregate. The aggregate generation process can be referred to Figure 2 Specifically, an inscribed random hexahedron is generated inside the spherical aggregate, points are randomly selected on the six faces of the hexahedron, and extension points are obtained by extending to the sphere along the normal vector. The extension points and the vertices of the hexahedron are connected to form a 24-hedron aggregate model.

[0160] The method for selecting the inscribed random hexahedron is as follows: It is divided into five parts along the x-axis with the center as the center, and the specific intervals are as follows:

[0161] , , , , 。

[0162] Among them, Dia is the particle size of the above-mentioned spherical aggregate.

[0163] After that, in Take a larger quadrilateral randomly in the circular plane taken in the area. The larger quadrilateral needs to satisfy that the side length is not less than the radius of the taken circular plane. In Take a point randomly in the circular plane taken in the area. This point needs to satisfy , and then solve for the 6th, 7th, and 8th points in the upper circular plane of the area by three points being coplanar, so as to obtain an inscribed random hexahedron.

[0164] After that, translate the vertices of the twenty-four-sided aggregate to the origin, then generate a random rotation matrix, multiply the translated vertex coordinates by the rotation matrix to obtain the rotated vertex coordinates, and then add the center coordinates of the aggregate to obtain the final vertex coordinates. The generated model can be referred to Figure 3 。

[0165] As another example of this application, using a spherical aggregate model, this example is divided into three stages according to a preset percentage. Each stage generates an aggregate model with a volume ratio of about 1 / 3, and performs simulated vibration respectively to achieve the purpose of quickly generating an aggregate model with a high volume ratio. First, set the model geometric parameters, including the specimen size, the aggregate particle size range, and the preset percentage of 0.65. It can be referred to Figure 4 , where 301 is the state of the aggregate after the first stage of generation; 302 is the state of the aggregate after the first stage of vibration; 303 is the state of the aggregate after the second stage of continuous generation; 304 is the state of the aggregate after the second stage of vibration; 305 is the state of the aggregate after the third stage of continuous generation; 306 is the state of the aggregate after the third stage of vibration.

[0166] Specifically, the final volume ratio of the first stage is 0.22 and the volume ratio of the coarse aggregate in the first stage. Set the stage variable , where = 0, 1. If = 0, then control the aggregate particle size to generate coarse aggregate at this time. If = 1, then control the aggregate particle size to generate fine aggregate at this time, The initial setting is 0. Use the random function Generate the aggregate particle size and the center point coordinates inside the test block and store them in the first aggregate information matrix. Calculate the distance between aggregates, and judge whether the newly generated aggregate coincides with the original aggregate based on the distance between aggregates. The distance between aggregates is

[0167] ; where represents the center point coordinates of the placed aggregate, represents the center point coordinates of the existing aggregate. j = 1, 2, ……, i - 1.

[0168] If it completely coincides, delete and regenerate. The judgment basis is ; which means that the placed aggregate is completely inside the existing aggregate or the distance from the center of the placed aggregate to the surface of the existing aggregate is greater than the minimum particle size, where is the radius of the placed aggregate, is the radius of the existing aggregate, is the minimum particle size value in the aggregate particle size range. If it partially coincides and the distance from the center point to the surface of the old aggregate is greater than the minimum particle size, retain the center point coordinates of the new aggregate and regenerate the particle size so that the new aggregate does not coincide with the original aggregate. The judgment basis is ; which means that the placed aggregate partially coincides with the existing aggregate and the distance from the center of the placed aggregate to the surface of the existing aggregate is greater than the minimum particle size. If it does not coincide, retain all the information of the new aggregate. The judgment basis is ; which means that the placed aggregate does not coincide with the existing aggregate at all.

[0169] Calculate whether the volume of the coarse aggregate reaches the requirement of the proportion of the coarse aggregate volume. If not, generate the aggregate again. Otherwise, proceed to the next step. If = 1, then switch the particle sizes of the coarse and fine aggregates, calculate whether the volume of the aggregate reaches the requirement of the final volume proportion. If not, return to generate the aggregate again. Otherwise, proceed to the next step.

[0170] Input the total vibration time T and the initial time t, and then vibrate in the Y-axis direction, and mark the boundary aggregates at the bottom in the Y-axis direction and in the X and Z-axis directions of the test block.

[0171] Fix the center points of the aggregates at the bottom in the Y-axis, and the center points of the remaining aggregates (including the boundary aggregates in the X and Z axes) drop 0.1 cm in the y direction. Then, calculate the distances between all aggregates, and judge whether all aggregates coincide based on the distances. The judgment basis is the same as the above steps. If there is a coincidence, calculate the direction vector of the connection line of the aggregate center points and the adjustment distance.

[0172] ; where represents the distance of the overlapping part on the center line, represents the sum of the radii of the two aggregates, represents the actual distance between the aggregates.

[0173] ; where represents the direction vector, n = 1, 2, 3; when n = 1, the values of y and z are 0, representing the x-axis direction vector; when n = 2, the values of x and z are 0, representing the y-axis direction vector; when n = 3, the values of x and y are 0, representing the z-axis direction vector. And ; represents the negative direction of the direction vector of the i-sphere in the y-direction adjusted by half of the overlapping distance. ; represents the positive direction of the direction vector of the j-sphere in the y-direction adjusted by half of the overlapping distance.

[0174] Adjust all marked aggregates (i.e., aggregates at the bottom of the Y-axis and the boundaries of the X and Z axes). The boundary aggregates are not adjusted in the corresponding boundary directions, and the unmarked aggregates are slightly separated in the corresponding directions until they do not overlap. The boundary aggregates have adjustment priority to ensure the convergence of internal aggregates and that the aggregates do not exceed the boundaries.

[0175] Specifically, for the adjustment of xyz boundary aggregates, taking the i-sphere as an example:

[0176] If the i-sphere is at the bottom of the y-axis, then , ; that is, the j-sphere moves a complete overlapping distance in the direction vector in the y-direction.

[0177] If the i-sphere is at the x-axis boundary, then , ; that is, the j-sphere moves a complete overlapping distance in the direction vector in the x-direction.

[0178] If the i-sphere is at the z-axis boundary, then , That is, the j-sphere moves a complete overlapping distance in the direction vector in the z-direction.

[0179] After the vibration reaches the predetermined time, calculate the final volume ratio of the second stage to be 0.21 and the volume ratio of coarse aggregates in the second stage.

[0180] Similarly, set the switching conditions for the coarse and fine aggregate stages = 0, 1; if = 0, then control the aggregate particle size to generate coarse aggregates at this time. If = 1, then control the aggregate particle size to generate fine aggregates at this time, and the initial value is 0. Using the random function Generate the aggregate particle size and the center point coordinates at the upper part of the test block and store them in the second aggregate information matrix. Calculate the distance between aggregates, and determine whether the newly generated aggregate coincides with the original aggregates based on the distance between aggregates. If they completely coincide, delete the information of the new aggregate and regenerate it; if they partially coincide and the distance from the center point to the surface of the old aggregate is greater than the minimum particle size, retain the center point coordinates of the new aggregate and regenerate the particle size so that the new aggregate does not coincide with the original aggregates; if they do not coincide, retain all the information of the new aggregate. The judgment basis is the same as that in the first stage and the above steps. Calculate whether the volume of the coarse aggregates meets the requirement of the proportion of the volume of the coarse aggregates. If it meets the proportion requirement, = 1, and switch to the stage of coarse and fine aggregates. Calculate whether the volume of the aggregates meets the requirement of the final volume proportion in the second stage. If it meets the requirement, integrate the first aggregate information matrix and the second aggregate information matrix, and perform vibration simulation on all the aggregates. If there is a coincidence, calculate the direction vector of the line connecting the center points of the aggregates and the adjustment distance. Adjust all the marked aggregates (i.e., the aggregates at the bottom of the Y-axis and the boundaries of the X and Z axes). The boundary aggregates are not adjusted in the corresponding boundary directions, and the unmarked aggregates are slightly separated in the corresponding directions until they do not coincide. The boundary aggregates have adjustment priority to ensure the convergence of the internal aggregates and that the aggregates do not exceed the boundaries.

[0181] Subsequently, calculate the final volume proportion in the third stage to be 0.21 and the proportion of the volume of the coarse aggregates in the third stage. Set the switching conditions for the stage of coarse and fine aggregates, = 0, 1; if = 0, then control the aggregate particle size to generate coarse aggregates at this time. If = 1, then control the aggregate particle size to generate fine aggregates at this time, and the initial value is 0. Use the random function Generate the aggregate particle size and the center point coordinates above the test block and store them in the second aggregate information matrix. Calculate the distance between aggregates, and determine whether the newly generated aggregate coincides with the original aggregates based on the distance between aggregates. If they completely coincide, delete the information of the new aggregate and regenerate it; if they partially coincide and the distance from the center point to the surface of the old aggregate is greater than the minimum particle size, retain the center point coordinates of the new aggregate and regenerate the particle size so that the new aggregate does not coincide with the original aggregates; if they do not coincide, retain all the information of the new aggregate. The judgment basis is the same as the corresponding steps in the first stage.

[0182] Calculate whether the volume of the coarse aggregates meets the requirement of the proportion of the volume of the coarse aggregates. If it meets the requirement, = 1, and switch to the stage of coarse and fine aggregates. Calculate whether the volume of the aggregates meets the requirement of the final volume proportion in the second stage. If it meets the requirement, then integrate the current information matrix and the third aggregate information matrix, and perform vibration simulation on all the aggregates. The vibration process is the same as above and will not be elaborated here. Count all the aggregates and calculate whether there is a coincidence. If there is a coincidence, adjust the particle size of the small particle size aggregates until they do not coincide. Finally, obtain a suitable concrete model. Refer to Figure 5 andFigure 6 , Figure 5 is a schematic diagram of a concrete model; Figure 6 is a schematic cross-sectional view of the concrete model.

[0183] Based on the concrete model generation method provided in the above embodiments, correspondingly, the present application also provides a specific implementation manner of the concrete model generation device. Please refer to the following embodiments.

[0184] First, refer to Figure 7 , the concrete model generation device 400 provided in the embodiments of the present application includes the following modules:

[0185] An acquisition module 401, configured to acquire aggregate particle size information, an initial concrete model, and a preset aggregate volume ratio, where the preset aggregate volume ratio represents a target value of the volume ratio of the aggregate in the concrete in the concrete model.

[0186] A generation module 402, configured to generate aggregates in the initial concrete model according to the above aggregate particle size information until the aggregate volume ratio reaches a first threshold, where the first threshold is one-third of the preset aggregate volume ratio, and the aggregate volume ratio represents the volume ratio of the currently generated aggregates in the concrete model.

[0187] A simulation module 403, configured to perform aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a first concrete model.

[0188] The generation module 402 is further configured to generate aggregates in the first concrete model according to the above aggregate particle size information until the aggregate volume ratio reaches a second threshold, where the second threshold is two-thirds of the preset aggregate volume ratio.

[0189] The simulation module 403 is further configured to perform aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a second concrete model.

[0190] The generation module 402 is further configured to generate aggregates in the second concrete model according to the above aggregate particle size information until the aggregate volume ratio reaches the above preset aggregate volume ratio to obtain a final concrete model.

[0191] The concrete model generation device provided in the embodiments of the present application, through an optimized algorithm and a step-by-step generation method, without the assistance of a physical model, greatly reduces the complexity of the algorithm, simplifies the generation process, and uses the optimized algorithm and an aggregate model closer to the real situation to significantly improve the generation efficiency and the authenticity of the model, and at the same time realizes the efficient generation of a random aggregate model.

[0192] Each module in the concrete model generation device provided by the embodiments of the present application can implement each step in the above-mentioned concrete model generation method and achieve the corresponding effects. For the sake of brief description, it will not be elaborated herein.

[0193] Figure 8 The structural schematic diagram of the concrete model generation hardware provided by the embodiments of the present application is shown.

[0194] In the concrete model generation device, it may include a processor 501 and a memory 502 storing computer program instructions.

[0195] Specifically, the above-mentioned processor 501 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0196] The memory 502 may include a mass storage for data or instructions. By way of example and not limitation, the memory 502 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disc, a magneto-optical disc, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. In a suitable case, the memory 502 may include a removable or non-removable (or fixed) medium. In a suitable case, the memory 502 may be inside or outside the integrated gateway disaster recovery device. In a specific embodiment, the memory 502 is a non-volatile solid-state memory.

[0197] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical, or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the concrete model generation method according to any one of the embodiments of the present disclosure.

[0198] The processor 501 reads and executes the computer program instructions stored in the memory 502 to implement any one of the concrete model generation methods in the above embodiments.

[0199] In one example, the concrete model generation device may further include a communication interface 503 and a bus 510. Among them, as Figure 8As shown, a processor 501, a memory 502, and a communication interface 503 are connected via a bus 510 and complete communication with each other.

[0200] The communication interface 503 is mainly used to implement communication between various modules, devices, units, and / or equipment in the embodiments of the present application.

[0201] The bus 510 includes hardware, software, or both, and couples the components of the online data flow meter charging device to each other. By way of example and not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses or a combination of two or more of these. In a suitable case, the bus 510 may include one or more buses. Although the embodiments of the present application describe and illustrate specific buses, the present application contemplates any suitable bus or interconnect.

[0202] In addition, in combination with the method for generating a concrete model in the above embodiments, the embodiments of the present application can be implemented by providing a computer storage medium. Computer program instructions are stored on the computer storage medium; when the computer program instructions are executed by a processor, any one of the methods for generating a concrete model in the above embodiments is implemented.

[0203] The embodiments of the present application also provide a computer program product, including a computer program, which when executed by a processor implements any one of the methods for generating a concrete model in the above embodiments.

[0204] It should be clear that the present application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present application is not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications, and additions, or change the order between steps after understanding the spirit of the present application.

[0205] The functional blocks shown in the above-described structural block diagrams can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, and so on. When implemented in software, the elements of the present application are programs or code segments for performing the required tasks. The program or code segment can be stored in a machine-readable medium or transmitted via a data signal carried in a carrier wave over a transmission medium or a communication link. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical discs, hard disks, fiber optic media, radio frequency (RF) links, and so on. The code segment can be downloaded via a computer network such as the Internet, an intranet, and so on.

[0206] It should also be noted that in the exemplary embodiments mentioned in the present application, some methods or systems are described based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be executed in the order mentioned in the embodiments, or different from the order in the embodiments, or several steps can be executed simultaneously.

[0207] Aspects of the present disclosure have been described above with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and the combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device to produce a machine such that the instructions executed by the processor of the computer or other programmable data processing device enable the implementation of the functions / actions specified in one or more blocks of the flowcharts and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It should also be understood that each block in the block diagrams and / or flowcharts, and the combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware for performing the specified functions or actions, or by a combination of dedicated hardware and computer instructions.

[0208] As described above, this is only the specific implementation manner of the present application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein. It should be understood that the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present application.

Claims

1. A method for generating a concrete model, characterized in that, The method includes: Obtaining aggregate particle size information, an initial concrete model, and a preset aggregate volume ratio, where the preset aggregate volume ratio represents the target value of the volume ratio of the aggregate in the concrete in the concrete model; Generating aggregates in the initial concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a first threshold, where the first threshold is one-third of the preset aggregate volume ratio, and the aggregate volume ratio represents the volume ratio of the currently generated aggregates in the concrete model; Performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a first concrete model; Generating aggregates in the first concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a second threshold, where the second threshold is two-thirds of the preset aggregate volume ratio; Performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a second concrete model; Generating aggregates in the second concrete model according to the aggregate particle size information until the aggregate volume ratio reaches the preset aggregate volume ratio to obtain a final concrete model; Wherein, the performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete test block to obtain a first concrete model includes: Marking the aggregates whose distance from the bottom boundary of the concrete test block is less than a preset threshold; For each unmarked aggregate, the following steps are respectively executed: Moving the aggregate and dropping the aggregate by a preset distance; Determining the distance between the aggregate and other aggregates; Determining the final position of the aggregate according to the distance between the aggregate and other aggregates; Increasing the elapsed falling time at preset time intervals; In the case where the elapsed falling time is less than the preset falling time, continuing to execute the falling process and increasing the elapsed falling time; In the case where the elapsed falling time is greater than or equal to the preset falling time, determining the current concrete model as the first concrete model.

2. The concrete model generation method according to claim 1, wherein, The generating aggregates in the initial concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a first threshold includes: Randomly selecting a target particle size value according to the aggregate particle size range corresponding to the aggregate particle size information; Determining the center point coordinates of the aggregate in the initial concrete model; Generating an aggregate according to the center point coordinates and the target particle size value; Continuing to randomly select a target particle size value according to the aggregate particle size range corresponding to the aggregate particle size information and generating an aggregate again until the aggregate volume ratio reaches a first threshold.

3. The concrete model generation method according to claim 2, characterized in that The generating an aggregate according to the center point coordinates and the target particle size value includes: Determining the position of the aggregate to be generated according to the center point coordinates and the target particle size value, and judging whether the aggregate to be generated overlaps with the existing aggregates; In the case where the aggregate to be generated overlaps with the existing aggregates, determining the distance between the center point coordinates of the aggregate to be generated and the corresponding overlapping aggregate; In the case where the distance meets a preset condition, updating the target particle size value according to the distance so that the aggregate to be generated no longer overlaps with the overlapping aggregate; Generating an aggregate according to the center point coordinates and the updated target particle size value.

4. The concrete model generation method according to claim 2, characterized in that, The aggregate is an icosahedron aggregate. Generating the aggregate according to the center point coordinates and the target particle size value includes: Taking the center point coordinates as the center of a circle, generating a sphere according to the target particle size value; Randomly generating an inscribed hexahedron of the sphere; Calculating the geometric center point of the hexahedron according to the vertex coordinates of the inscribed hexahedron; Based on the geometric center point, making extension lines along the normal vectors of each face to determine the extension points corresponding to the six faces respectively; Connecting each of the extension points to the vertices of the inscribed hexahedron of the corresponding face respectively to generate an icosahedron aggregate.

5. The concrete model generation method according to claim 1, characterized in that Determining the final position of the aggregate according to the distance between the aggregate and other aggregates includes: Detecting whether the aggregate coincides with other aggregates according to whether the distance between the aggregate and other aggregates is less than a preset threshold; When the aggregate coincides with other aggregates, calculating the direction vector of the line connecting the center points of the aggregate and the coincident aggregates; Moving the aggregate according to the direction vector so that the aggregate no longer coincides with other aggregates, and determining the final position of the aggregate.

6. A concrete model generation device, characterized in that, The device includes: an acquisition module for acquiring aggregate particle size information, an initial concrete model, and a preset aggregate volume ratio, where the preset aggregate volume ratio represents the target value of the volume ratio of the aggregate in the concrete in the concrete model; A generation module for generating aggregates in the initial concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a first threshold, where the first threshold is one-third of the preset aggregate volume ratio, and the aggregate volume ratio represents the volume ratio of the currently generated aggregates in the concrete model; A simulation module for performing aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete specimen to obtain a first concrete model; The generation module is further configured to generate aggregates in the first concrete model according to the aggregate particle size information until the aggregate volume ratio reaches a second threshold, where the second threshold is two-thirds of the preset aggregate volume ratio; The simulation module is further configured to perform aggregate falling simulation according to a preset falling time and the bottom boundary of the concrete specimen to obtain a second concrete model; The generation module is further configured to generate aggregates in the second concrete model according to the aggregate particle size information until the aggregate volume ratio reaches the preset aggregate volume ratio to obtain a final concrete model; Wherein, the simulation module is further configured to: mark the aggregates whose distance from the bottom boundary of the concrete specimen is less than a preset threshold; for each unmarked aggregate, respectively perform the following steps: Move the aggregate, drop the aggregate a preset distance; determine the distance between the aggregate and other aggregates; determine the final position of the aggregate according to the distance between the aggregate and other aggregates; increase the fallen time at a preset time interval; when the fallen time is less than the preset falling time, continue to execute the falling process and increase the fallen time; when the fallen time is greater than or equal to the preset falling time, determine the current concrete model as the first concrete model.

7. A concrete model generating device, characterized in that, The device includes: a processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the concrete model generation method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, Computer program instructions are stored on the computer-readable storage medium, and when the computer program instructions are executed by a processor, the concrete model generation method according to any one of claims 1-5 is implemented.

9. A computer program product, characterized in that, When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device is caused to execute the concrete model generation method according to any one of claims 1-5.

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