Crushed stone hardcore dynamic loading deformation analysis system based on computer simulation

Abstract

The invention relates to the technical field of simulation analysis, in particular to a broken stone hardcore dynamic loading deformation analysis system based on computer simulation. A broken stone hardcore dynamic loading deformation analysis system based on computer simulation comprises a graded broken stone physical model setting module used for setting a graded broken stone physical model, a graded broken stone physical model mechanical parameter set simulation setting module and a broken stone hardcore dynamic loading deformation analysis module. On the basis of comparison between an actual dynamic triaxial experiment and a simulated dynamic triaxial experiment, a graded broken stone physical model mechanical parameter set corresponding to a graded broken stone physical model is simulated and generated through an improved genetic algorithm, and the corresponding graded broken stone physical model is combined; setting of a loading numerical model for dynamic loading deformation analysis of the broken stone hardcore is completed, numerical simulation of the dynamic loading deformation analysis of the broken stone hardcore is executed on the basis of the loading numerical model, and an indoor dynamic triaxial test does not need to be adopted.

Description

Technical Field

[0001] The invention relates to the technical field of simulation analysis, and in particular to a computer-simulated crushed stone cushion layer dynamic loading deformation analysis system. Background Art

[0002] The gravel cushion layer under the road is a loose material with a certain degree of compaction. Under vibration conditions, the gravel particles will displace and shift against each other, eventually reaching a vibration-compacted state.

[0003] The vibration sources that cause rock and soil vibration can be divided into two types: natural vibration sources and artificial vibration sources. Earthquakes, wave forces, and wind forces are all natural vibration sources, while traffic loads, explosions, piling, and machine foundations are all artificial vibration sources. The vibration frequencies, vibration times, and vibration waveforms of these vibration sources are different. Natural vibration sources are exciting forces that cause random vibrations, while artificial vibration sources have both random vibrations and periodic vibrations. For example, the vibration caused by instantaneous loads such as explosions is random, while the vibration caused by continuously running machines is periodic. For the gravel cushion layer under the highway, the vibration source that causes its vibration is mainly the traffic load among the artificial vibration sources. The traffic load has a certain regularity, so it can be simulated by applying a regular periodic load. Moreover, the strength and deformation of the soil under different dynamic loads are different, and their common characteristics are that they are all affected by the loading rate and the number of loading times.

[0004] The deformation analysis of the gravel cushion layer is generally carried out by dynamic triaxial test. However, since the dynamic triaxial test is a relatively complex indoor test of rock and soil dynamic properties, the soil sample is prepared in a certain sample container according to the required humidity, density, structure and stress state, and then vibration loads of different forms and intensities are applied. The stress and strain of the sample under the vibration are measured, so as to make qualitative and quantitative judgments on the changing laws of soil properties and related indicators. The dynamic triaxial test has the disadvantages of complex test conditions, large equipment and high cost, and is not convenient to use. Summary of the invention

[0005] The present invention compares actual dynamic triaxial experiments with simulated dynamic triaxial experiments, generates a set of mechanical parameters of a graded crushed stone physical model corresponding to the graded crushed stone physical model through an improved genetic algorithm, and completes the setting of a loading numerical model for dynamic loading deformation analysis of a crushed stone cushion layer in combination with the corresponding graded crushed stone physical model, and performs numerical simulation of the dynamic loading deformation analysis of a crushed stone cushion layer on the basis of the loading numerical model, without the need for indoor dynamic triaxial tests, thereby providing convenience for the dynamic loading deformation analysis of a crushed stone cushion layer.

[0006] A computer-simulated crushed stone cushion dynamic loading deformation analysis system, comprising: The graded crushed stone physical model setting module is used to set the graded crushed stone physical model; The mechanical parameter set simulation setting module of the graded crushed stone physical model is used to simulate and generate the mechanical parameter set of the graded crushed stone physical model corresponding to the graded crushed stone physical model through the improved genetic algorithm on the basis of comparing the actual dynamic triaxial test with the simulated dynamic triaxial test, so as to complete the simulation setting of the mechanical parameter set simulation setting of the graded crushed stone physical model; The dynamic loading deformation analysis module of the crushed stone cushion is used to perform simulated dynamic triaxial experiments based on the graded crushed stone physical model and the corresponding graded crushed stone physical model mechanical parameter set to realize the dynamic loading deformation analysis of the crushed stone cushion.

[0007] Preferably, in the mechanical parameter set simulation setting module of the graded crushed stone physical model, based on the comparison between the actual dynamic triaxial test and the simulated dynamic triaxial test, the mechanical parameter set of the graded crushed stone physical model corresponding to the graded crushed stone physical model is simulated and generated by the improved genetic algorithm, which specifically includes the following steps: Step S1: construct M mechanical parameter simulation sets of graded crushed stone physical model, and form a population set of all mechanical parameter simulation sets of graded crushed stone physical model, and set the maximum number of iterations; Step S2: Calculate the fitness corresponding to the mechanical parameter simulation set of the graded crushed stone physical model, record the mechanical parameter simulation set of the graded crushed stone physical model with the largest fitness as the optimal mechanical parameter simulation set of the graded crushed stone physical model, and store the optimal mechanical parameter simulation set of the graded crushed stone physical model in the optimal database; Step S3: based on the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model, the population set is iteratively updated by a genetic algorithm, and the iterative update specifically includes selection, recombination and mutation operations; Step S4: Repeat steps S2-S3 until the number of iterations reaches the maximum number of iterations, and output the graded gravel physical model mechanical parameter simulation set with the largest fitness in the optimal library as the graded gravel physical model mechanical parameter set corresponding to the graded gravel physical model.

[0008] Preferably, in the simulation setting module of the mechanical parameter set of the graded gravel physical model, a simulation set of the mechanical parameters of the graded gravel physical model is constructed, which specifically includes the following steps: constructing an initial set, the initial set includes N elements, N is the total number of the mechanical parameters of the graded gravel physical model in the mechanical parameter set of the graded gravel physical model, for the nth element in the initial set, n=1, 2, 3, ..., N, selecting a random value within the parameter range corresponding to the mechanical parameter of the nth graded gravel physical model to assign a value to the nth element in the initial set; until all elements in the initial set are assigned values, the initial set is recorded as the simulation set of the mechanical parameters of the graded gravel physical model, and the setting of the simulation set of the mechanical parameters of the graded gravel physical model is completed.

[0009] Preferably, in the simulation setting module of the mechanical parameter set of the graded gravel physical model, the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model is calculated as follows: the dynamic rebound modulus corresponding to the graded gravel physical model is obtained through actual dynamic triaxial experiments, and recorded as the actual dynamic rebound modulus; the graded gravel physical model and the corresponding mechanical parameter simulation set of the graded gravel physical model are loaded, and the dynamic rebound modulus corresponding to the graded gravel physical model is calculated by numerical simulation, and recorded as the simulated dynamic rebound modulus; the mean square error between the actual dynamic rebound modulus and the simulated dynamic rebound modulus under different test conditions is calculated as the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model.

[0010] Preferably, in the simulation setting module of the mechanical parameter set of the graded gravel physical model, the selection operation includes the following contents: based on the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model, 0.5M mechanical parameter simulation sets of the graded gravel physical model are selected through a roulette selection algorithm to form a parent set, and the mechanical parameter simulation sets of the graded gravel physical model remaining in the population set except the parent set are formed into a parent set.

[0011] Preferably, in the simulation setting module of the mechanical parameter set of the graded gravel physical model, the reorganization operation includes the following contents: updating the reorganization probability corresponding to each mechanical parameter of the graded gravel physical model based on the graded gravel physical model, randomly selecting a graded gravel physical model mechanical parameter simulation set from the parent set and the parent set respectively, and selecting a graded gravel physical model mechanical parameter through a roulette wheel selection algorithm on the basis of the reorganization probabilities corresponding to all the mechanical parameters of the graded gravel physical model, and replacing the corresponding values ​​of the two selected graded gravel physical model mechanical parameter simulation sets on the selected graded gravel physical model mechanical parameter, and the selected graded gravel physical model mechanical parameter simulation set will no longer be selected subsequently.

[0012] Preferably, in the mechanical parameter set simulation setting module of the graded crushed stone physical model, the mutation operation includes the following steps: for any mechanical parameter simulation set of the graded crushed stone physical model, a random number η between 0 and 1 is generated by a random function, and η>P is judged. c Is it established? c is the mutation threshold, if η>P c If η>P, a random value μ between 0 and N is generated, and the μth value in the mechanical parameter simulation set of the graded crushed stone physical model is replaced with a random value in the parameter range corresponding to the mechanical parameter of the graded crushed stone physical model; if η>P c Not true, continue to select the next corrugated steel web composite beam bridge simulation design parameter set.

[0013] Preferably, in the mechanical parameter set simulation setting module of the graded crushed stone physical model, the reorganization probability corresponding to each mechanical parameter of the graded crushed stone physical model is updated based on the graded crushed stone physical model, specifically including the following steps: The graded gravel physical model feature set corresponding to the graded gravel physical model is matched with the graded gravel physical model mechanical parameter set standard library, the graded gravel physical model mechanical parameter set standard library includes the graded gravel physical model and the corresponding graded gravel physical model mechanical parameter set that have completed the graded gravel physical model mechanical parameter set simulation setting, the graded gravel physical model feature set corresponding to the graded gravel physical model and the graded gravel physical model feature set corresponding to the graded gravel physical model in the graded gravel physical model mechanical parameter set standard library are matched in sequence, the matching method is to calculate the graded gravel physical model feature set corresponding to the graded gravel physical model and the graded gravel physical model feature set corresponding to the graded gravel physical model in the graded gravel physical model mechanical parameter set standard library. The similarity between the graded crushed stone physical model feature sets corresponding to the physical model is determined, and whether the similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of graded crushed stone physical model mechanical parameter sets is higher than the similarity threshold. If the similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of graded crushed stone physical model mechanical parameter sets is higher than the similarity threshold, it is considered to be a successful match, and the graded crushed stone physical model mechanical parameter set corresponding to the successful match is output, and recorded as the standard graded crushed stone physical model mechanical parameter set; The reorganization probability A corresponding to the mechanical parameters of the physical model of the nth graded gravel n , the recombination probability A is calculated by the following formula n To update: A n =(F n -H n ) -2 A n , where F n is the value corresponding to the mechanical parameter of the nth graded crushed stone physical model in the mechanical parameter simulation set of the optimal graded crushed stone physical model, H n It is the value corresponding to the mechanical parameter of the nth graded gravel physical model in the mechanical parameter set of the standard graded gravel physical model.

[0014] The present invention has the following advantages: The present invention compares actual dynamic triaxial experiments with simulated dynamic triaxial experiments, generates a set of mechanical parameters of a graded crushed stone physical model corresponding to the graded crushed stone physical model through an improved genetic algorithm, and completes the setting of a loading numerical model for dynamic loading deformation analysis of a crushed stone cushion layer in combination with the corresponding graded crushed stone physical model, and performs numerical simulation of the dynamic loading deformation analysis of a crushed stone cushion layer on the basis of the loading numerical model, without the need for indoor dynamic triaxial tests, thereby providing convenience for the dynamic loading deformation analysis of a crushed stone cushion layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a structural schematic diagram of a crushed stone cushion dynamic loading deformation analysis system based on computer simulation adopted in an embodiment of the present invention.

[0016] Figure 2 A schematic diagram of a graded crushed stone physical model used in an embodiment of the present invention.

[0017] Figure 3 It is a schematic diagram of the test results of dynamic loading deformation analysis of a crushed stone cushion layer in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to enable persons skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0019] Example 1, a system for analyzing the dynamic loading deformation of a crushed stone cushion layer based on computer simulation, see Figure 1 ,include: The graded gravel physical model setting module is used to set the graded gravel physical model through the PFC2D software. It should be noted that the graded gravel physical model here is set according to the graded gravel cushion layer in the actual dynamic triaxial test process, which generally includes the following steps: (1) Test mold simulation: a closed rectangular test mold formed by four walls is used; (2) Generation of graded crushed stone: graded crushed stone aggregate particles are generated in a closed rectangular test mold. The graded crushed stone cushion layer during the actual dynamic triaxial test is monitored and the area of ​​graded crushed stone aggregate particles is generated. The amount of graded crushed stone aggregate of each specification is controlled to construct the target graded crushed stone model. (3) Generation of indenter: A row of spheres is generated on both sides of the top and bottom surfaces of the closed rectangular test mold to simulate the dynamic triaxial test indenter. The spheres are in direct contact with the target graded gravel model to apply deviatoric stress. At the same time, if the deformation of the target graded gravel model is large, some gravel particles will overflow from the pores on both sides of the indenter. Therefore, the original top and bottom surfaces are deleted, and a broken line wall is established along the edge of the indenter sphere to ensure the accuracy of the test. (4) The closed rectangular test mold and the target graded gravel model together constitute the graded gravel physical model; A physical model of graded crushed stone Figure 2 ; The mechanical parameter set simulation setting module of the graded crushed stone physical model is used to simulate and generate the mechanical parameter set of the graded crushed stone physical model corresponding to the graded crushed stone physical model through the improved genetic algorithm on the basis of comparing the actual dynamic triaxial test with the simulated dynamic triaxial test, so as to complete the simulation setting of the mechanical parameter set simulation setting of the graded crushed stone physical model. The mechanical parameter set of the graded crushed stone physical model here includes the normal stiffness, tangential stiffness and friction coefficient of the graded crushed stone physical model mechanical parameters between two contact entities (graded crushed stone aggregate particles-graded crushed stone aggregate particles or graded crushed stone aggregate particles-boundary wall). These mechanical parameter sets of the graded crushed stone physical model characterize the physical rules within the graded crushed stone physical model and are used for the subsequent simulated dynamic triaxial test. It should be added here that the actual dynamic triaxial test refers to the measurement experiment of the sample graded gravel cushion layer through the vibration triaxial instrument, while the simulated dynamic triaxial test is a numerical simulation performed by PFC2D software. The specific implementation methods of the simulated dynamic triaxial test include the following: (1) Loading: Loading the graded gravel physical model in the PFC2D software, and loading the graded gravel physical model mechanical parameter set corresponding to the graded gravel physical model. It should be noted here that before the simulation setting of the graded gravel physical model mechanical parameter set is completed, the graded gravel physical model mechanical parameter set is randomly initialized; the loaded graded gravel physical model and the corresponding graded gravel physical model mechanical parameter set can be collectively referred to as a loading numerical model; (2) Confining pressure: The servo mechanism is used to control the wall speed to keep the stress between the wall and the particles constant, thus achieving the control of the confining pressure; (3) Pressure stabilization: Apply confining pressure σ3 to the walls on both sides and static load σ s , to ensure that no impact stress is generated when dynamic load is applied. When the deformation of the sample is basically stable under static load, the stabilization process ends; (4) Dynamic load: The simulated excitation equipment applies cyclic load to the specimen, using the sine wave commonly used in indoor tests. The corresponding deviator stress σ d =σ1-σ3=d0(sinwt) 2 , where σ1 is the axial stress, w is the circular frequency of the simple harmonic stress, and the time t for each load application includes the dynamic load action time t z and dynamic load action interval time t j , where t z Includes loading time and unloading time; The test is divided into two cases: test confining pressure σ3 = 100kPa, dynamic load deviator stress σd =σ1-σ3=σd0(sinwt) 2 =300(sin(20πt)) 2 kPa and the dynamic load deviator stress is σ d =σ1-σ3=d0(sinwt) 2 =100(sin(20πt)) 2 kPa; For example, the dynamic traffic load in actual highways can be roughly estimated. The cumulative equivalent axle times of dynamic load on a lane of a highway with a design life of 15 years is 1.98*10^7 times, which can be converted into N times per second. After calculation, N=1.98*10^7 / 15 / 365 / 24 / 3600=0.042 times / second, which means that there is one dynamic traffic load acting on the road surface in 24 seconds. In the dynamic triaxial test, the dynamic load action time t z =0.1s, interval time t j =0.1s, where the action time is divided into loading time and unloading time. The loading and unloading time each accounts for half of the action time, both of which are 0.05s; (5) Arrangement: Arrange the axial strain of the target graded gravel model under different stress conditions by arranging the above experiments, draw stress-strain curves under different conditions and arrange the relevant data, calculate and obtain the dynamic rebound modulus of the target graded gravel model; The dynamic loading deformation analysis module of the crushed stone cushion is used to perform simulated dynamic triaxial experiments based on the graded crushed stone physical model and the corresponding mechanical parameter set of the graded crushed stone physical model to realize the dynamic loading deformation analysis of the crushed stone cushion, which facilitates the analysis of the dynamic rebound modulus and final deformation of the crushed stone cushion under the highway; In the process of performing the simulated dynamic triaxial test, nine graded gravel physical models and corresponding graded gravel physical model mechanical parameter sets were set, and the test conditions were constantly changed to perform dynamic loading deformation analysis of the gravel cushion layer. For example: graded gravel physical model 65-4 (the number corresponding to the graded gravel physical model), confining pressure σ3=100kPa, dynamic load function is a half-sine function, and the maximum deviatoric stress of dynamic load σ d =300kPa; dynamic load action time t z =0.1s, divided into loading time and unloading time, loading time and unloading time are 0.05s each; interval time t j = 0.1s; see Figure 3 The test results are as follows: with the application of dynamic load, the graded crushed stone is continuously vibrated and compacted, the volume is reduced, and axial compression occurs. The plastic deformation generated during the first loading is the largest and more obvious, with a strain of about 0.5%. With the application of cyclic load, the crushed stone is vibrated and compacted, and the plastic deformation and maximum axial deformation generated by each subsequent vibration loading and unloading gradually decrease, and finally the maximum axial deformation and plastic deformation tend to be stable.

[0020] The present application, based on the comparison between the actual dynamic triaxial test and the simulated dynamic triaxial test, generates the mechanical parameter set of the graded gravel physical model corresponding to the graded gravel physical model through the improved genetic algorithm simulation, and completes the setting of the loading numerical model for the dynamic loading deformation analysis of the gravel cushion layer in combination with the corresponding graded gravel physical model, and performs the numerical simulation of the dynamic loading deformation analysis of the gravel cushion layer on the basis of the loading numerical model, without the need for indoor dynamic triaxial test, thereby providing convenience for the dynamic loading deformation analysis of the gravel cushion layer.

[0021] In the mechanical parameter set simulation setting module of the graded crushed stone physical model, based on the comparison between the actual dynamic triaxial test and the simulated dynamic triaxial test, the mechanical parameter set of the graded crushed stone physical model corresponding to the graded crushed stone physical model is simulated and generated by the improved genetic algorithm, which specifically includes the following steps: Step S1: construct M mechanical parameter simulation sets of graded crushed stone physical model, and form a population set of all mechanical parameter simulation sets of graded crushed stone physical model, and set the maximum number of iterations; Constructing a mechanical parameter simulation set of the graded crushed stone physical model includes the following steps: Construct an initial set, which includes N elements, where N is the total number of mechanical parameters of the graded gravel physical model in the mechanical parameter set of the graded gravel physical model. For the nth element in the initial set, n=1, 2, 3, ..., N, select a random value within the parameter range corresponding to the mechanical parameter of the nth graded gravel physical model to assign a value to the nth element in the initial set. The parameter range corresponding to the mechanical parameter of the graded gravel physical model is set by the developer according to the expert experience. Until all elements in the initial set are assigned values, the initial set is recorded as a mechanical parameter simulation set of the graded gravel physical model, and the setting of the mechanical parameter simulation set of the graded gravel physical model is completed. Step S2: Calculate the fitness corresponding to the mechanical parameter simulation set of the graded crushed stone physical model, record the mechanical parameter simulation set of the graded crushed stone physical model with the largest fitness as the optimal mechanical parameter simulation set of the graded crushed stone physical model, and store the optimal mechanical parameter simulation set of the graded crushed stone physical model in the optimal database; The fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model is calculated as follows: the dynamic rebound modulus corresponding to the graded gravel physical model is obtained through actual dynamic triaxial test, and recorded as the actual dynamic rebound modulus. The dynamic rebound modulus corresponding to the graded gravel physical model obtained through actual dynamic triaxial test here refers to the dynamic rebound modulus obtained by measuring the graded gravel cushion layer of the graded gravel physical model corresponding to the sample through indoor dynamic triaxial test; the graded gravel physical model and the corresponding mechanical parameter simulation set of the graded gravel physical model are loaded, and the dynamic rebound modulus corresponding to the graded gravel physical model is calculated by numerical simulation, and recorded as the simulated dynamic rebound modulus; the mean square error between the actual dynamic rebound modulus and the simulated dynamic rebound modulus under different test conditions is calculated as the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model; Step S3: based on the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model, the population set is iteratively updated by a genetic algorithm, and the iterative update specifically includes selection, recombination and mutation operations; The selection operation includes the following contents: based on the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model, 0.5M mechanical parameter simulation sets of the graded gravel physical model are selected by a roulette wheel selection algorithm to form a parent set. The roulette wheel selection algorithm here means that the fitness corresponding to all mechanical parameter simulation sets of the graded gravel physical model are formed into a disk, and the mechanical parameter simulation set of the graded gravel physical model is selected according to the point where the random value falls on the disk, and the mechanical parameter simulation sets of the graded gravel physical model remaining in the population set except the parent set are formed into a parent set; The reorganization operation includes the following contents: based on the graded gravel physical model, the reorganization probability corresponding to each graded gravel physical model mechanical parameter is updated; a graded gravel physical model mechanical parameter simulation set is randomly selected from the parent set and the parent set respectively; based on the reorganization probabilities corresponding to all graded gravel physical model mechanical parameters, a graded gravel physical model mechanical parameter is selected through a roulette wheel selection algorithm; and the corresponding values ​​of the two selected graded gravel physical model mechanical parameter simulation sets on the selected graded gravel physical model mechanical parameters are replaced; and the graded gravel physical model mechanical parameter simulation set that has been selected will no longer be selected subsequently.

[0022] Based on the graded gravel physical model, the reorganization probability corresponding to the mechanical parameters of each graded gravel physical model is updated, specifically including the following steps: The graded gravel physical model feature set corresponding to the graded gravel physical model is matched with the graded gravel physical model mechanical parameter set standard library. The graded gravel physical model feature set here includes various statistical characteristics of the graded gravel physical model, such as graded gravel aggregate particle size, graded gravel aggregate particle number, graded gravel aggregate particle shape, graded gravel aggregate particle material properties and graded gravel aggregate particle grading type (continuous grading and discontinuous grading), etc. The graded gravel physical model mechanical parameter set standard library includes the graded gravel physical model and the corresponding graded gravel physical model mechanical parameter set that have completed the graded gravel physical model mechanical parameter set simulation setting. The graded gravel physical model feature set corresponding to the graded gravel physical model and the graded gravel physical model feature set corresponding to the graded gravel physical model in the graded gravel physical model mechanical parameter set standard library are matched in sequence. The matching method is to calculate the graded gravel material The similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of mechanical parameter sets of graded crushed stone physical model is calculated by using the cosine similarity algorithm, and it is judged whether the similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of mechanical parameter sets of graded crushed stone physical model is higher than the similarity threshold, and the similarity threshold is set artificially. If the similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of mechanical parameter sets of graded crushed stone physical model is higher than the similarity threshold, it is regarded as a successful match, and the mechanical parameter set of the graded crushed stone physical model corresponding to the successful match is output, and recorded as the standard mechanical parameter set of the graded crushed stone physical model; The reorganization probability A corresponding to the mechanical parameters of the physical model of the nth graded gravel n , the recombination probability A is calculated by the following formula n To update: A n =(F n -H n ) -2 A n , where F n is the value corresponding to the mechanical parameter of the nth graded crushed stone physical model in the mechanical parameter simulation set of the optimal graded crushed stone physical model, H n is the value corresponding to the mechanical parameter of the nth graded crushed stone physical model in the mechanical parameter set of the standard graded crushed stone physical model; it should be noted that the update operation here is an assignment operation. A on the right side of the equation n is the reorganization probability corresponding to the mechanical parameters of the nth graded gravel physical model before updating. A on the left side of Eq. nis the recombination probability corresponding to the updated mechanical parameters of the nth graded gravel physical model. The closer the mechanical parameter set of the standard graded gravel physical model is to the mechanical parameter simulation set of the optimal graded gravel physical model, the higher the corresponding recombination probability is, and there is a higher probability of inheriting excellent genes, which improves the convergence speed of the simulation process. The mutation operation includes the following steps: for any mechanical parameter simulation set of the graded crushed stone physical model, a random number η between 0 and 1 is generated through a random function, and η>P is judged. c Is it established? c is the mutation threshold, usually 0.7, determined by the developer. If η>P c If η>P, a random value μ between 0 and N is generated, and the μth value in the mechanical parameter simulation set of the graded crushed stone physical model is replaced with a random value in the parameter range corresponding to the mechanical parameter of the graded crushed stone physical model; if η>P c If it is not true, continue to select the next simulation design parameter set of the composite beam bridge with corrugated steel web; Step S4: Repeat steps S2-S3 until the number of iterations reaches the maximum number of iterations, and output the graded gravel physical model mechanical parameter simulation set with the largest fitness in the optimal library as the graded gravel physical model mechanical parameter set corresponding to the graded gravel physical model.

[0023] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the appended claims of the present invention. Parts not described in detail in this specification belong to the prior art known to those skilled in the art.

Claims

1. A computer-simulated crushed stone cushion dynamic loading deformation analysis system, characterized in that: include: The graded crushed stone physical model setting module is used to set the graded crushed stone physical model; The mechanical parameter set simulation setting module of the graded crushed stone physical model is used to simulate and generate the mechanical parameter set of the graded crushed stone physical model corresponding to the graded crushed stone physical model through the improved genetic algorithm on the basis of comparing the actual dynamic triaxial test with the simulated dynamic triaxial test, so as to complete the simulation setting of the mechanical parameter set simulation setting of the graded crushed stone physical model; The dynamic loading deformation analysis module of the crushed stone cushion is used to perform simulated dynamic triaxial experiments based on the graded crushed stone physical model and the corresponding graded crushed stone physical model mechanical parameter set to realize the dynamic loading deformation analysis of the crushed stone cushion.

2. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 1 is characterized in that: In the mechanical parameter set simulation setting module of the graded crushed stone physical model, based on the comparison between the actual dynamic triaxial test and the simulated dynamic triaxial test, the mechanical parameter set of the graded crushed stone physical model corresponding to the graded crushed stone physical model is simulated and generated by the improved genetic algorithm, which specifically includes the following steps: Step S1: construct M mechanical parameter simulation sets of graded crushed stone physical model, and form a population set of all mechanical parameter simulation sets of graded crushed stone physical model, and set the maximum number of iterations; Step S2: Calculate the fitness corresponding to the mechanical parameter simulation set of the graded crushed stone physical model, record the mechanical parameter simulation set of the graded crushed stone physical model with the largest fitness as the optimal mechanical parameter simulation set of the graded crushed stone physical model, and store the optimal mechanical parameter simulation set of the graded crushed stone physical model in the optimal database; Step S3: based on the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model, the population set is iteratively updated by a genetic algorithm, and the iterative update specifically includes selection, recombination and mutation operations; Step S4: Repeat steps S2-S3 until the number of iterations reaches the maximum number of iterations, and output the graded gravel physical model mechanical parameter simulation set with the largest fitness in the optimal library as the graded gravel physical model mechanical parameter set corresponding to the graded gravel physical model.

3. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 2 is characterized in that: In the simulation setting module of the mechanical parameter set of the graded gravel physical model, a simulation set of the mechanical parameters of the graded gravel physical model is constructed, which specifically includes the following steps: constructing an initial set, the initial set includes N elements, N is the total number of the mechanical parameters of the graded gravel physical model in the mechanical parameter set of the graded gravel physical model, for the nth element in the initial set, n=1, 2, 3, ..., N, selecting a random value within the parameter range corresponding to the mechanical parameter of the nth graded gravel physical model to assign a value to the nth element in the initial set; until all elements in the initial set are assigned values, the initial set is recorded as the simulation set of the mechanical parameters of the graded gravel physical model, and the setting of the simulation set of the mechanical parameters of the graded gravel physical model is completed.

4. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 3 is characterized in that: In the simulation setting module of the mechanical parameter set of the graded gravel physical model, the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model is calculated as follows: the dynamic rebound modulus corresponding to the graded gravel physical model is obtained through actual dynamic triaxial experiments, and recorded as the actual dynamic rebound modulus; the graded gravel physical model and the corresponding mechanical parameter simulation set of the graded gravel physical model are loaded, and the dynamic rebound modulus corresponding to the graded gravel physical model is calculated by numerical simulation, and recorded as the simulated dynamic rebound modulus; the mean square error between the actual dynamic rebound modulus and the simulated dynamic rebound modulus under different test conditions is calculated as the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model.

5. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 4 is characterized in that: In the simulation setting module of the mechanical parameter set of the graded gravel physical model, the selection operation includes the following contents: based on the fitness corresponding to the mechanical parameter simulation set of the graded gravel physical model, 0.5M mechanical parameter simulation sets of the graded gravel physical model are selected through the roulette selection algorithm to form a parent set, and the mechanical parameter simulation sets of the graded gravel physical model remaining in the population set except the parent set are formed into a parent set.

6. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 5 is characterized in that: In the simulation setting module of the mechanical parameter set of the graded gravel physical model, the reorganization operation includes the following contents: based on the graded gravel physical model, the reorganization probability corresponding to each mechanical parameter of the graded gravel physical model is updated, and a graded gravel physical model mechanical parameter simulation set is randomly selected from the parent set and the parent set respectively, and on the basis of the reorganization probabilities corresponding to all the mechanical parameters of the graded gravel physical model, a graded gravel physical model mechanical parameter is selected by a roulette selection algorithm, and the corresponding values ​​of the two selected graded gravel physical model mechanical parameter simulation sets on the selected graded gravel physical model mechanical parameter are replaced, and the selected graded gravel physical model mechanical parameter simulation set will no longer be selected subsequently.

7. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 6 is characterized in that: In the simulation setting module of the mechanical parameter set of the graded crushed stone physical model, the mutation operation includes the following steps: for any mechanical parameter simulation set of the graded crushed stone physical model, a random number η between 0 and 1 is generated by a random function, and η>P is judged. c Is it established? c is the mutation threshold, if η>P c If η>P, a random value μ between 0 and N is generated, and the μth value in the mechanical parameter simulation set of the graded crushed stone physical model is replaced with a random value in the parameter range corresponding to the mechanical parameter of the graded crushed stone physical model; if η>P c Not true, continue to select the next corrugated steel web composite beam bridge simulation design parameter set.

8. The computer-simulated crushed stone cushion dynamic loading deformation analysis system according to claim 7, characterized in that: In the mechanical parameter set simulation setting module of the graded crushed stone physical model, the reorganization probability corresponding to each mechanical parameter of the graded crushed stone physical model is updated based on the graded crushed stone physical model, specifically including the following steps: The graded gravel physical model feature set corresponding to the graded gravel physical model is matched with the graded gravel physical model mechanical parameter set standard library, the graded gravel physical model mechanical parameter set standard library includes the graded gravel physical model and the corresponding graded gravel physical model mechanical parameter set that have completed the graded gravel physical model mechanical parameter set simulation setting, the graded gravel physical model feature set corresponding to the graded gravel physical model and the graded gravel physical model feature set corresponding to the graded gravel physical model in the graded gravel physical model mechanical parameter set standard library are matched in sequence, the matching method is to calculate the graded gravel physical model feature set corresponding to the graded gravel physical model and the graded gravel physical model feature set corresponding to the graded gravel physical model in the graded gravel physical model mechanical parameter set standard library. The similarity between the graded crushed stone physical model feature sets corresponding to the physical model is determined, and whether the similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of graded crushed stone physical model mechanical parameter sets is higher than the similarity threshold. If the similarity between the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model and the graded crushed stone physical model feature set corresponding to the graded crushed stone physical model in the standard library of graded crushed stone physical model mechanical parameter sets is higher than the similarity threshold, it is considered to be a successful match, and the graded crushed stone physical model mechanical parameter set corresponding to the successful match is output, and recorded as the standard graded crushed stone physical model mechanical parameter set; The reorganization probability A corresponding to the mechanical parameters of the physical model of the nth graded gravel n , the recombination probability A is calculated by the following formula n To update: A n =(F n -H n ) -2 A n , where F n is the value corresponding to the mechanical parameter of the nth graded crushed stone physical model in the mechanical parameter simulation set of the optimal graded crushed stone physical model, H n It is the value corresponding to the mechanical parameter of the nth graded gravel physical model in the mechanical parameter set of the standard graded gravel physical model.

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