CN115438411A - Analysis method, system, equipment and medium capable of simulating component bending shear coupling - Google Patents
Analysis method, system, equipment and medium capable of simulating component bending shear coupling Download PDFInfo
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Abstract
The invention relates to an analysis method, a system, equipment and a medium capable of simulating bending shear coupling of a component, wherein the method comprises the following steps: in the process of carrying out elastic-plastic analysis on the concrete component to be analyzed, judging whether the stress characteristic of the component to be analyzed in the analysis step i-1 meets the requirement of the updating threshold of constitutive parameters or not when the structural rigidity of the analysis step i is calculated; if the structural rigidity of the ith analysis step is satisfied, mapping a mapping framework control parameter and a mapping hysteresis loop control parameter according to the stress characteristic of the component to be analyzed through a trained neural network topological relation, updating the mapping framework and the mapping hysteresis loop, calculating the structural rigidity of the ith analysis step according to the updated mapping framework and the updated mapping hysteresis loop, completing the elastoplasticity analysis of the ith analysis step, and continuing the structural rigidity calculation of the (i + 1) th analysis step. According to the method, the constitutive parameters are updated in real time, so that the high solving cost is avoided, and meanwhile, the more real bending shear coupling effect of the concrete member is simulated.
Description
Technical Field
The invention relates to the technical field of concrete member simulation, in particular to an analysis method, system, equipment and medium capable of simulating member bending shear coupling.
Background
Multiple earthquake damages show that a large number of reinforced concrete frame structures are seriously damaged or even collapsed under the action of strong earthquake, huge casualties and economic losses are caused, and concrete members are main lateral force resisting members of the reinforced concrete frame structures and need to accurately simulate the earthquake resistance of concrete members. The failure mode and the deformation performance of the concrete member are mainly controlled by the shearing span, the bending deformation is mainly used as the large shearing span member, and the shearing deformation is mainly used as the small shearing span member. However, even in a concrete member mainly subjected to bending deformation, horizontal cracks and oblique cracks in the plastic region tend to occur together. Therefore, there is an inherent coupling effect between the non-linear bending deformation and the non-linear shear deformation of the concrete member, i.e., a bending shear coupling effect. Under the action of earthquake, because the vertical load effect and the horizontal load effect have different internal force distribution modes, the shearing span of the concrete beam is changed along with the change of earthquake excitation, so that the concrete beam presents different failure modes under different earthquake motion excitations; in addition, the concrete column bears the action of a circulating axial force, the concrete beam bears the action of the circulating axial force under the restraint of the floor slab and the vertical member, the circulating axial force aggravates the development of the plasticity of the member, the internal force is redistributed to cause the shearing-span cyclic change of the member, and further the deformation capacity and the failure mode of the member are obviously influenced. Therefore, under the action of earthquake, a remarkable coupling effect exists between the axial force and the bending deformation and the shearing deformation of the member, namely the bending and shearing coupling effect.
The bending shear coupling effect has obvious influence on the rigidity, the bearing capacity, the deformation capacity and the energy consumption capacity of the concrete member, and the neglect coupling effect can overestimate the bearing capacity of the member and underestimate the damage degree of the member. Therefore, the buckling-shear coupling effect is not negligible in numerical simulations of concrete structures.
The elastic-plastic units of the existing simulated concrete members can be divided into two categories, namely distributed plastic hinge units and concentrated plastic hinge units. The theory of the centralized plastic hinge unit is simple, the simulation precision can be obviously improved by combining with machine learning, but the deformation capability and the energy consumption capability of the unit are constant in the solving process, and the bending shear coupling effect cannot be simulated. In the existing method, plastic hinge units are combined with a dispersion crack theory, and a bending shear coupling effect is simulated through a multi-dimensional concrete constitutive model and a flat section hypothesis. However, the introduction of the dispersion crack theory and the multidimensional concrete constitutive model increases the complexity of the elastoplastic model, obviously improves the calculation cost and the convergence difficulty, and cannot be practical in engineering due to the processing speed of the existing computer. In addition, the distributed plastic hinge units and the dispersion crack theory describe the complex nonlinear behavior of the member based on the constitutive relation of the stress-strain material, so that the calibration cannot be carried out through the member test, the bending-shearing coupling effect simulation result cannot be supported by the test, the real mechanical behavior of the concrete member under the action of the earthquake cannot be effectively reflected, and the hidden danger is caused to the earthquake-resistant safety of the concrete structure.
Disclosure of Invention
The present invention is directed to overcome at least one of the above-mentioned drawbacks (disadvantages) of the prior art, and provides an analysis method, system, device and medium capable of simulating bending-shear coupling of a member, so as to solve the problem that a more realistic bending-shear coupling effect of a concrete member cannot be simulated in an elasto-plastic analysis.
The technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides an analysis method for simulating bending shear coupling of a component, including:
performing elastic-plastic analysis of the concrete members to be analyzed in analysis steps one by one;
when the structural rigidity of the ith analysis step is calculated, i is an integer more than or equal to 2, and whether the stress characteristic of the component to be analyzed meets the requirement of the update threshold of the constitutive parameter or not under the ith-1 analysis step is judged;
if the requirement of updating the threshold value is not met, not updating the mapping framework and the mapping hysteresis loop of the component to be analyzed, calculating the structural rigidity of the ith analysis step according to the mapping framework and the mapping hysteresis loop in the ith-1 analysis step, completing the elastoplasticity analysis of the ith analysis step, and continuing the structural rigidity calculation of the (i + 1) analysis step until the elastoplasticity analysis is finished;
if the requirement of updating the threshold is met, mapping the mapping framework control parameters matched with the stress characteristics and the physical characteristics according to the stress characteristics of the component to be analyzed in the i-1 th analysis step and the predefined physical characteristics of each component to be analyzed through the trained neural network topological relation
And mapping hysteresis loop control parameters
According to the mapping framework control parameters
Updating mapping skeleton, and controlling parameters according to the mapping hysteresis loop
Updating a mapping hysteresis loop, calculating the structural rigidity of the ith analysis step according to the updated mapping framework and the updated mapping hysteresis loop, completing the elastoplasticity analysis of the ith analysis step, and continuing the calculation of the structural rigidity of the (i + 1) th analysis step until the elastoplasticity analysis is finished;
the stress characteristics comprise a shear-span ratio and an axial compression coefficient, and the physical characteristics comprise a hoop characteristic value and a reinforcement characteristic value.
Optionally, the determining whether the force characteristic of the member to be analyzed in the analysis step i-1 meets the update threshold requirement of the parameter of the pointer includes:
judging whether the stress characteristic of the component to be analyzed in the analysis step (i-1) meets the following formula:
λ i 、λ i-1 The shear-span ratios, μ, of the ith analysis step and the ith-1 analysis step, respectively i 、μ i-1 The axial pressure coefficients of the ith analysis step and the i-1 analysis step are respectively,
is a pre-set cut-off threshold value,
is a preset axial pressure threshold value.
Optionally, the training of the neural network topological relation includes:
acquiring stress characteristics and physical characteristics of a plurality of different test components, and a test framework and a test hysteresis loop of a pseudo-static test;
identifying mapped skeleton control parameters from the test skeleton
Identifying a mapped hysteresis loop control parameter from the test hysteresis loop
The stress characteristics and the physical characteristics of the test component and the identified mapping framework control parameters
Mapping hysteretic loop control parameters
And training the neural network topological relation according to the sample training set as a sample data set.
Optionally, mapping skeleton control parameters are identified from the test skeleton
The method comprises the following steps:
calculating the energy surrounding error of the mapping framework and the test framework according to the following formula
f ske,ex (D) In order to test the framework of the test,
is a mapping skeleton;
to obtain the minimum energy enclosing error between the mapping skeleton and the experimental skeleton
Iteratively identifying mapping skeleton control parameters for a target
Optionally, mapping hysteresis loop control parameters are identified from the trial hysteresis loop
The method comprises the following steps:
calculating the energy surrounding error of the mapping hysteresis loop and the experimental hysteresis loop according to the formula
In the formula
f hy,ex (D) To test hysteresis loop:
to obtain the minimum energy wrapping error of mapping hysteresis loop and experimental hysteresis loop
Iteratively identifying mapped hysteresis control parameters for a target
Optionally, the mapping skeleton is described using the following formula:
x＝D/D c ，y＝M/M c ，(D c ，M c ) For mapping a framework peak point, D and M are respectively deformation and internal force of the restoring force model at the moment, and M and n are both deformation capability shape coefficients used for adjusting the mapping framework;
the mapping skeleton control parameter
Including mapping skeleton peak points D c 、M c And deformability form factors m, n.
Optionally, the mapping hysteresis loop comprises an unloading section and a reloading section, the rigidity of the unloading section is controlled by a parameter alpha, the reloading section controls the position of an inflection point by parameters beta and gamma, and the mapping hysteresis loop controls the strength degradation effect by a parameter eta;
the mapped hysteresis control parameter
Including parameters α, β, γ, η.
In a second aspect, the invention provides an analysis system capable of simulating bending-shear coupling of a component, comprising an analysis module;
the analysis module is used for performing elastoplasticity analysis of the concrete members to be analyzed in one-by-one analysis step;
the analysis module is provided with a judgment updating module;
the judgment updating module is used for:
when the structural rigidity of the ith analysis step is calculated, i is an integer more than or equal to 2, and whether the stress characteristic of the component to be analyzed meets the requirement of the update threshold of the constitutive parameter or not under the ith-1 analysis step is judged;
if the requirement of updating the threshold value is not met, the mapping framework and the mapping hysteresis loop of the component to be analyzed are not updated, so that the analysis module calculates the structural rigidity of the ith analysis step according to the mapping framework and the mapping hysteresis loop in the ith-1 analysis step, and elastic-plastic analysis of the ith analysis step is completed;
if the requirement of updating the threshold is met, mapping the mapping framework control parameters matched with the stress characteristics and the physical characteristics according to the stress characteristics of the component to be analyzed in the i-1 th analysis step and the predefined physical characteristics of each component to be analyzed through the trained neural network topological relation
And mapping hysteresis loop control parameters
According to the mapping framework control parameters
Updating mapping skeleton, and controlling parameters according to the hysteresis loop
Updating a mapping hysteresis loop such that the analysis module counts from the updated mapping skeleton and the updated mapping hysteresis loopCalculating the structural rigidity of the ith analysis step to finish the elastoplasticity analysis of the ith analysis step;
the stress characteristics comprise a shear-span ratio and an axial compression coefficient, and the physical characteristics comprise a hoop characteristic value and a reinforcement characteristic value.
In a third aspect, the present invention provides a computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the method for analyzing a bending shear coupling of a simulatable member according to the first aspect when executing the computer program.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of analysing a modelable member bending shear coupling as described in the first aspect.
Compared with the prior art, the invention has the beneficial effects that: compared with the prior art that bending shear coupling is simulated through a theoretical model, the method effectively realizes real-time feedback and correction of an elastoplasticity analysis result, avoids high solving cost caused by introducing a bending shear coupling theoretical model, and simulates a more real bending shear coupling effect.
Drawings
FIG. 1 is a flow chart of an analysis method for simulating bending shear coupling of a component in embodiment 1 of the present invention.
Fig. 2 is a flowchart of training a neural network topology relationship according to embodiment 2 of the present invention.
FIG. 3 is a schematic diagram of a mapping skeleton that can characterize the softening property of strength and different ductility characteristics in example 2 of the present invention.
Fig. 4 is a schematic diagram of a mapping hysteresis loop capable of characterizing a pinch-out hysteresis characteristic in embodiment 2 of the present invention.
Fig. 5 is a schematic diagram of a network structure of a neural network topology relationship in embodiment 2 of the present invention.
FIG. 6 is a graph showing the hysteresis response simulation test of different failure type members according to the elasto-plastic analysis example of the concrete member in example 2 of the present invention.
Fig. 7 is a test chart of the number of iterations and the solution efficiency in different manners of the concrete member elastic-plastic analysis example in embodiment 2 of the present invention.
Fig. 8 is a time-course graph of the acceleration of the artificial seismic waves used in the example of elastoplasticity analysis of the concrete structure in embodiment 2 of the present invention.
Fig. 9 is a graph showing a shear-span ratio time-varying process of a concrete beam of an example of an elastoplasticity analysis calculation of a concrete structure in example 2 of the present invention.
Fig. 10 is a graph showing a test of influence of hysteresis characteristics of a concrete member according to an example of elastoplasticity analysis of a concrete structure in example 2 of the present invention.
Fig. 11 is a test chart of the influence of the response of the concrete structure according to the comparative example of the elasto-plastic analysis of the concrete structure in example 2 of the present invention.
Fig. 12 is a composition diagram of an analysis system capable of simulating bending shear coupling of a component in embodiment 3 of the present invention.
Detailed Description
The drawings are only for purposes of illustration and are not to be construed as limiting the invention. For a better understanding of the following embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
Example 1
The embodiment provides an analysis method capable of simulating bending shear coupling of a member, which can realize real-time feedback and real-time correction of an elastic-plastic analysis result when a concrete member is subjected to elastic-plastic analysis, and simulate a more real bending shear coupling effect while avoiding high solving cost caused by introducing a bending shear coupling theoretical model.
Fig. 1 is a flowchart of an analysis method for simulating bending shear coupling of a component according to this embodiment, and as shown in fig. 1, the method may include:
performing elastic-plastic analysis of the concrete members to be analyzed in analysis steps one by one;
after the beginning of the elasto-plastic analysis:
s11, when the structural rigidity of the ith analysis step is calculated, i is an integer larger than or equal to 2, whether the stress characteristic of the component to be analyzed in the ith-1 analysis step meets the requirement of the updating threshold of the constitutive parameter is judged, if not, the step S12 is executed, and if yes, the step S13 is executed.
The force characteristics may include a shear-span ratio λ and an axial compression coefficient μ, and may also include other characteristic parameters. The formula for calculating the shear-to-span ratio λ may be: λ = M/(Vh) 0 ) The formula for calculating the axial compression coefficient μmay be: μ = N/(f) ck A) M, V, N is respectively the bending moment, shearing force and axial force borne by the plastic zone of the component to be analyzed, h 0 The effective height of the section of the component to be analyzed in the stress direction is A, and the area of the whole section of the component to be analyzed is A.
Specifically, how to judge whether the stress characteristics of the component to be analyzed in the i-1 th analysis step meet the requirement of the update threshold of the constitutive parameters or not can be preset, a shear span threshold related to the shear span ratio and an axle pressure threshold related to the axle pressure coefficient can be preset, the condition relationship between the shear span ratio and the shear span threshold and the condition relationship between the axle pressure coefficient and the axle pressure threshold can be set, and the condition relationship can be designed by associating the shear span ratio and the axle pressure coefficient in different analysis steps to find the optimal update time of the trigger threshold.
In a preferred embodiment, specifically, how to determine whether the stress characteristic of the component to be analyzed at the i-1 th analysis step meets the requirement of the update threshold of the constitutive parameter may include:
judging whether the stress characteristic of the component to be analyzed in the (i-1) th analysis step meets the following formula:
λ i 、λ i-1 The shear-to-span ratios, μ, of the ith and (i-1) th analysis steps, respectively i 、μ i-1 The axial pressure coefficients of the ith analysis step and the i-1 analysis step are respectively,
for a pre-set cut-across threshold,
is a preset axial pressure threshold value.
And S12, if the requirement of updating the threshold value is not met, not updating the mapping framework and the mapping hysteresis loop of the component to be analyzed, calculating the structural rigidity of the ith analysis step according to the mapping framework and the mapping hysteresis loop in the ith-1 analysis step, completing the elastoplasticity analysis of the ith analysis step, and continuing the structural rigidity calculation of the (i + 1) th analysis step until the elastoplasticity analysis is finished.
S13, if the requirement of updating the threshold is met, mapping the mapping framework control parameters matched with the stress characteristics and the physical characteristics through the trained neural network topological relation according to the stress characteristics of the component to be analyzed in the step i-1 and the predefined physical characteristics of the component to be analyzed
And mapping hysteresis loop control parameters
The physical characteristic may include a ferrule characteristic value λ v And reinforcement characteristic value lambda s Other characteristic parameters may also be included. Characteristic value lambda of coupling v The calculation formula of (c) can adopt: lambda [ alpha ] v ＝ρ v f vyk /f ck And reinforcement characteristic value lambda s The calculation formula of (c) can be: lambda [ alpha ] s ＝ρ s f yk /f ck ，ρ v For the area of the member in the direction of force application, ρ s Reinforcement ratio f for full-section longitudinal reinforcement vyk Is a standard value of tensile strength of the stirrup, f yk Is a standard value of the tensile strength of the longitudinal bar, f ck And the standard value of the concrete compressive strength is obtained.
Mapping skeleton control parameters
Is to controlThe component maps the parameters of the skeleton and maps the control parameters of the hysteresis loop
Is a parameter of the control means mapping the hysteresis loop. The mapping framework can represent the strength softening characteristic and different ductility characteristics, and the mapping hysteresis loop can represent the pinching hysteresis characteristic.
The trained neural network topological relation is the stress characteristic (the shear-span ratio lambda and the axial pressure coefficient mu) and the physical characteristic (the hoop characteristic value lambda) v Reinforcement characteristic value lambda s ) The wall parameter multidimensional space (mapping framework control parameters)
And mapping hysteresis loop control parameters
) The non-linear topological relationship of (1).
Specifically, the stress characteristic and the physical characteristic of the component to be analyzed are input into the topological relation of the neural network, and the matched mapping framework control parameter can be output
And mapping hysteresis loop control parameters
S14, controlling parameters according to the mapping framework
Updating mapping skeleton, and controlling parameters according to mapping hysteresis loop
And updating the mapping hysteresis loop, calculating the structural rigidity of the ith analysis step according to the updated mapping framework and the updated mapping hysteresis loop, completing the elastoplasticity analysis of the ith analysis step, and continuing the calculation of the structural rigidity of the (i + 1) th analysis step until the elastoplasticity analysis is finished.
Specifically, the rigidity of the component to be analyzed in the ith analysis step is calculated according to the updated mapping framework and the mapping hysteresis loop, the component to be analyzed is assembled into an integral structural rigidity matrix, and matrix solution in the ith analysis step is completed so as to complete elastoplasticity analysis in the ith analysis step.
In the structural rigidity calculation at the (i + 1) th analysis step, step S11 is repeatedly performed,
according to the time-varying stress characteristic of the component to be analyzed in the elastoplasticity analysis, the bending shear coupling effect is simulated through the constitutive parameter real-time updating mechanism, a bending shear coupling theoretical model is not required to be introduced, the solving efficiency and the convergence are greatly improved, and the method can be widely used in engineering.
Due to the existence of the real-time update mechanism of the wall-force parameter, in the elastic-plastic analysis process, the force-displacement restoring force model does not need to define the constitutive parameter, and only needs to define the section size (used for calculating the shear-span ratio in real time) of the member to be analyzed, the concrete strength grade (used for calculating the axial compression coefficient in real time) and the physical characteristics of the member to be analyzed.
Example 2
The embodiment provides an analysis method for simulating bending shear coupling of a component, which mainly performs detailed description on training of neural network topology relation in embodiment 1 to obtain more optimally matched mapping framework control parameters
And mapping hysteresis loop control parameters
The bending shear coupling effect of the member is simulated more truly in the elastoplasticity analysis of the concrete structure.
Fig. 2 is a flowchart of training a neural network topological relation according to this embodiment, and as shown in fig. 2, the training of the neural network topological relation may include:
s21, acquiring stress characteristics and physical characteristics of a plurality of different test components, and a test framework and a test hysteresis loop of a pseudo-static test.
Specifically, canCollecting pseudo-static test data of a plurality of different test members in advance, wherein the test data comprises stress characteristics (a shear-span ratio lambda and an axial pressure coefficient mu) and physical characteristics (a coupling characteristic value lambda) of the test members v And reinforcement characteristic value lambda s ) The test framework and the test hysteresis loop are used for establishing a component pseudo-static test database.
The test framework can represent the strength softening characteristic and different ductility characteristics of the test member, and the test hysteresis loop can represent the pinching and gathering hysteresis characteristic of the test member.
S22, identifying mapping framework control parameters according to the test framework
Fitting the test skeleton with the mapping skeleton to identify mapping skeleton control parameters for controlling the mapping skeleton
In a preferred embodiment, step S22 may be performed based on an energy equivalence principle, which may specifically include:
calculating the energy surrounding error of the mapping framework and the test framework according to the following formula
f ske,ex (D) In order to test the framework,
is a mapping skeleton;
to obtain the minimum energy enclosing error between the mapping skeleton and the experimental skeleton
Iteratively identifying mapped skeleton control parameters for a target
Specifically, when iteration starts, a mapping framework is initialized, then iterative calculation is started, and the minimum energy surrounding error meeting the requirements is obtained
Stopping iteration, and finally outputting the minimum surrounding error
Corresponding optimal mapping skeleton control parameter
The mapping framework may control the parameters by mapping the framework
And constructing a mathematical function for description. In a preferred embodiment, the following formula can be used to describe:
x＝D/D c ，y＝M/M c ，(D c ，M c ) For mapping the peak point of the skeleton, D and M are respectively the deformation and the internal force of the restoring force model at the moment, M and n are both deformation capability shape coefficients for adjusting the mapped skeleton, the shape of the deformation capability shape coefficients is shown in fig. 3 along with the change of M and n, and D and M are specifically a corner and a bending moment in fig. 3. At this point, the skeleton control parameters are mapped
Including mapping skeleton peak points D c 、M c And deformability form factors m, n.
S23, identifying mapping hysteresis loop control parameters according to the test hysteresis loop
Fitting the test hysteresis loop with the mapped hysteresis loop to identify the control parameters of the mapped hysteresis loop for controlling the mapped hysteresis loop
In a preferred embodiment, step S23 may be performed based on an energy equivalent principle, which may specifically include:
calculating the energy surrounding error of the mapping hysteresis loop and the test hysteresis loop according to the following formula
In the formula f hy,ex (D) To test hysteresis loop:
to obtain the minimum mapping hysteresis loop and the experimental hysteresis loop energy enveloping error
Iteratively identifying mapped hysteresis control parameters for a target
Specifically, when iteration starts, a mapping hysteresis loop is initialized, then iterative calculation is started, and the minimum energy surrounding error meeting requirements is obtained
Stopping iteration, and finally outputting the minimum surrounding error
Corresponding optimal mapping hysteresis control parameter
The mapped hysteresis loop can be shown in fig. 4, and comprises an unloading section and a reloading section, wherein the rigidity of the unloading section is controlled by a parameter alpha, the position of an inflection point is controlled by parameters beta and gamma, and the intensity degradation effect is controlled by a parameter eta. At this time, hysteresis control parameters are mapped
Including parameters α, β, γ, η.
S24, stress characteristics and physical characteristics of the test component and identified mapping framework control parameters
Mapping hysteretic loop control parameters
And as a sample data set, training the neural network topological relation according to the sample training set.
Specifically, the stress characteristics and the physical characteristics of the test component are taken as input, and the parameters respectively identified in the step S22 and the step S23 are mapping framework control parameters
And mapping hysteresis loop control parameters
For output, the sample data set is randomly divided into a training set, a verification set and a test set (the division ratio can be set as required, for example, can be set to 60%, 20% and 20%), and the cross-verification method is adopted to confirm through grid searchAnd (5) determining the optimal hyper-parameter combination of the topological relation of the neural network to obtain the trained neural network topological relation of the physical characteristic, the stress characteristic and the multi-dimensional space of the physical parameter.
The network structure of the trained neural network topology can be as shown in fig. 5.
Based on the pseudo-static test data of the test component, the neural network topological relation is trained, the real-time feedback and the real-time correction of the elastoplasticity analysis result by the pseudo-static test database of the component can be realized, and the more real bending and shearing coupling effect of the component can be simulated.
Taking the elastoplasticity analysis of the concrete member as an example, by using the method provided by the embodiment and three modes of the bending shear coupling multi-drop-bar unit (SFI-MVELM) and the layered shell unit capable of simulating the bending shear coupling effect, the elastoplasticity analysis is respectively performed on the rectangular reinforced concrete column with bending damage as a main component and shearing damage as a main component to realize low-cycle reciprocating simulation, which shows that the method provided by the embodiment contributes to the simulation precision and solving efficiency of the bending shear coupling effect of the concrete member.
For a bending-damaged rectangular reinforced concrete column, the section dimension is 300mm multiplied by 800mm, the member length is 3390mm, the shear span ratio lambda =4.2, the axial pressure coefficient is mu =0.1, and the full-section longitudinal bar reinforcement ratio rho s =2.14%, area hoop ratio ρ in force-receiving direction v =0.315%, concrete compression strength standard value f ck =20.1MPa, standard value f of tensile strength of longitudinal bar yk =384MPa, standard value of tensile strength of stirrup is f vyk ＝300MPa。
For a shear-failure rectangular reinforced concrete column, the section dimension is 200mm multiplied by 400mm, the member length is 600mm, the shear span ratio lambda =1.5, the axial pressure coefficient is mu =0.6, and the full-section longitudinal bar reinforcement ratio rho s =2.3%, area hoop ratio ρ in the direction of force application v =0.714%, concrete compression strength standard value f ck =49.9MPa, standard value f of tensile strength of longitudinal rib yk =510MPa, standard value of tensile strength of stirrup is f vyk ＝469MPa。
By using the method of the embodiment and the existing SFI capable of simulating the bending-shearing coupling effectLow cycle reciprocating simulations were performed separately for MVELM and the layered shell units. In the stage of model definition, the method provided by the embodiment only needs to define the section size, the concrete strength grade and the hoop characteristic value lambda of the component v And reinforcement characteristic value lambda s In the process of elastoplasticity analysis, the shear-span ratio lambda and the axial pressure coefficient mu of the automatic calculation component can be set, and the trained neural network topological relation is utilized to update the constitutive parameter values of the mapping framework and the mapping hysteresis loop.
The simulation result is shown in fig. 6, and the solution time and the iteration number of the elasto-plastic analysis are shown in fig. 7. The method of the embodiment is adopted to complete the loading of the whole displacement sequence, and due to the convergence problem of the SFI-MVELM and the layered shell, the loading of only partial displacement sequence is completed for the shear control component.
According to the graph 6, the simulation results are better for all modes of the bending control component, but for the shearing control component, the SFI-MVELM and the laminated shell unit overestimate the bearing capacity and even the energy consumption capacity of the component, and the method of the embodiment has better simulation effect.
As can be seen from fig. 7, the solution time and the iteration number of the method of the present embodiment are significantly lower than those of the SFI-MVELM and the layered shell unit, and the solution efficiency of 2 orders of magnitude is improved. The method realizes the simulation of the bending shear coupling effect through the constitutive parameter real-time updating mechanism without introducing a bending shear coupling theoretical model, improves the solving efficiency and the convergence by a number level, can simulate the more real bending shear coupling effect, and can be widely used in engineering.
Taking elastic-plastic analysis of a concrete structure comprising a plurality of members as an example, dynamic elastic-plastic time-course analysis is performed on an engineering frame structure by using the method of the embodiment, and the operation mode and the application scene of real-time updating of constitutive parameters are explained.
The height of the engineering frame structure is 23 meters, and the engineering frame structure has 7 layers and is a 7-degree fortification structure for II-type soil. The dynamic elastoplasticity time course analysis under the condition of extremely rare earthquake is carried out on the frame structure by adopting artificial waves, the earthquake motion time course curve is shown in figure 8, and the peak acceleration is 0.5g.
In order to better reflect the influence of a constitutive parameter real-time updating mechanism, two analysis models, namely an analysis model A and an analysis model B, are arranged. The real-time constitutive parameter updating mechanism of the method of the embodiment is started for the analysis model A, and the real-time constitutive parameter updating mechanism is closed for the analysis model B. Fig. 9 shows a time-varying situation of the shear-span ratio of the concrete beam of the structural part in the loading process, and the analysis model a updates constitutive parameter values of the mapping framework and the mapping hysteresis loop by using a trained neural network topological relation in combination with the time-varying shear-span ratio and the axial pressure coefficient, so as to realize the bending-shearing coupling effect simulation.
FIG. 10 is a hysteresis curve of the same concrete beam in two analysis models, and it can be seen that the real-time update mechanism of constitutive parameters is closed, the bending shear coupling effect is neglected, so that the hysteresis curve of the component is fuller, the energy consumption capability of the component is overestimated, and the deformation of the component is underestimated by 50%; fig. 11 is a time-course analysis result of structural vertex displacement of two analysis models, and it can be seen that neglecting the bending-shearing coupling effect underestimates 50% of structural response and 90% of residual deformation, which adversely affects structural earthquake-resistant safety evaluation.
According to statistics, in the whole time-course sequence, the analysis model A calls 18 ten thousand times of neural networks to update constitutive parameters of the component, the total time consumption of the 18 ten thousand times of neural networks is 1.08 seconds, the total time consumption of elastoplasticity analysis is 144 seconds, and the real-time updating time consumption of the constitutive parameters only accounts for 0.7% of the total time consumption. Therefore, repeated calling of the topological relation of the neural network can continuously and actively update the mapping framework and the mapping hysteresis loop, and the solution efficiency cannot be negatively influenced.
Example 3
The present embodiments provide an analysis system that can simulate component bending shear coupling. FIG. 12 is a block diagram of an analysis system for simulating component bending shear coupling according to the present embodiment, and as shown in FIG. 12, the system may include an analysis module 31;
the analysis module 31 is used for performing elastic-plastic analysis of the concrete structures to be analyzed one by one;
the analysis module 31 is provided with a judgment module 32 and an update module 33;
a determining module 32, configured to:
when the structural rigidity of the ith analysis step is calculated, i is an integer more than or equal to 2, and whether the stress characteristics of each component to be analyzed of the concrete structure under the ith-1 analysis step meet the requirement of the update threshold of the constitutive parameters is judged;
an update module 33 configured to:
if the judgment module 32 judges that the requirement of the updating threshold is not met, the mapping framework and the mapping hysteresis loop of each component to be analyzed are not updated, so that the analysis module 31 calculates the structural rigidity of the ith analysis step according to the mapping framework and the mapping hysteresis loop in the ith-1 analysis step, and completes the elastoplasticity analysis of the ith analysis step;
if the judgment module 32 judges that the requirement of the updating threshold is met, mapping out mapping framework control parameters matched with the stress characteristics and the physical characteristics through a trained neural network topological relation according to the stress characteristics of each component to be analyzed in the step i-1 and the predefined physical characteristics of each component to be analyzed
And mapping hysteresis loop control parameters
Controlling parameters according to a mapping skeleton
Updating mapping skeleton, and controlling parameters according to mapping hysteresis loop
Updating the mapping hysteresis loop so that the analysis module 31 calculates the structural rigidity of the ith analysis step according to the updated mapping skeleton and the updated mapping hysteresis loop to complete the elastoplasticity analysis of the ith analysis step;
the stress characteristics comprise a shear-span ratio and an axial pressure coefficient, and the physical characteristics comprise a hoop characteristic value and a reinforcement characteristic value.
Based on the same inventive concept, the same or similar parts as those in embodiments 1 and 2 are not repeated herein.
It should be understood that the above-mentioned embodiments of the present invention are only examples for clearly illustrating the technical solutions of the present invention, and are not intended to limit the specific embodiments of the present invention. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention claims should be included in the protection scope of the present invention claims.
Claims (10)
1. An analysis method capable of simulating bending shear coupling of a component is characterized by comprising the following steps:
performing elastic-plastic analysis of the concrete members to be analyzed in analysis steps one by one;
when the structural rigidity of the ith analysis step is calculated, i is an integer more than or equal to 2, and whether the stress characteristic of the component to be analyzed meets the requirement of the update threshold of the constitutive parameter or not under the ith-1 analysis step is judged;
if the requirement of updating the threshold value is not met, not updating the mapping framework and the mapping hysteresis loop of the component to be analyzed, calculating the structural rigidity of the ith analysis step according to the mapping framework and the mapping hysteresis loop in the ith-1 analysis step, completing the elastoplasticity analysis of the ith analysis step, and continuing the structural rigidity calculation of the (i + 1) analysis step until the elastoplasticity analysis is finished;
if the requirement of updating the threshold value is met, mapping out mapping framework control parameters matched with the stress characteristics and the physical characteristics through a trained neural network topological relation according to the stress characteristics of the component to be analyzed in the analysis step of the (i-1) th and the predefined physical characteristics of each component to be analyzed
And mapping hysteresis loop control parameters
According to the mapping framework control parameters
Updating mapping skeleton, and controlling parameters according to the mapping hysteresis loop
Updating a mapping hysteresis loop, calculating the structural rigidity of the ith analysis step according to the updated mapping framework and the updated mapping hysteresis loop, completing the elastoplasticity analysis of the ith analysis step, and continuing the calculation of the structural rigidity of the (i + 1) th analysis step until the elastoplasticity analysis is finished;
the stress characteristics comprise a shear-span ratio and an axial compression coefficient, and the physical characteristics comprise a hoop characteristic value and a reinforcement characteristic value.
2. The analysis method for simulating bending shear coupling of a component according to claim 1, wherein the step of determining whether the force characteristic of the component to be analyzed at the analysis step i-1 meets the requirement of the update threshold of the parameter of the pointer includes:
judging whether the stress characteristic of the component to be analyzed in the analysis step (i-1) meets the following formula:
λ i 、λ i-1 The shear-span ratios, μ, of the ith analysis step and the ith-1 analysis step, respectively i 、μ i-1 The axial pressure coefficients of the ith analysis step and the i-1 analysis step are respectively,
for a pre-set cut-across threshold,
is a preset axial pressure threshold value.
3. The method for analyzing the bending shear coupling of the simulatable component as claimed in claim 1, wherein the training of the neural network topological relation comprises:
acquiring stress characteristics and physical characteristics of a plurality of different test components, and a test framework and a test hysteresis loop of a pseudo-static test;
identifying mapped skeleton control parameters from the test skeleton
Identifying mapped hysteresis loop control parameters according to the test hysteresis loop
The stress characteristics and the physical characteristics of the test component and the identified mapping framework control parameters
Mapping hysteresis loop control parameters
And training the neural network topological relation according to the sample training set as a sample data set.
4. A method as claimed in claim 3, wherein mapping skeleton control parameters are identified from the test skeleton
The method comprises the following steps:
calculating the energy surrounding error of the mapping framework and the test framework according to the following formula
f ske,ex (D) In order to test the framework,
is a mapping skeleton;
to obtain the minimum energy enclosing error between the mapping skeleton and the experimental skeleton
Iteratively identifying mapped skeleton control parameters for a target
5. A method according to claim 3, wherein mapped hysteresis control parameters are identified from the test hysteresis loop
The method comprises the following steps:
calculating the energy surrounding error of the mapping hysteresis loop and the test hysteresis loop according to the following formula
In the formula f hy,ex (D) To test hysteresis loop:
to obtain the minimum mapping hysteresis loop and the experimental hysteresis loop energy enveloping error
Iteratively identifying mapped hysteresis control parameters as targets
6. The method of claim 4, wherein the mapping framework is described by the following formula:
x＝D/D c ，y＝M/M c ，(D c ，M c ) D and M are respectively the deformation and the internal force of the restoring force model at the moment for mapping the skeleton peak point, and M and n are both deformation capacity shape coefficients for adjusting the mapping skeleton;
the mapping skeleton control parameter
Including mapping skeleton peak points D c 、M c And deformability form factors m, n.
7. The method of claim 5, wherein the mapped hysteresis loop comprises an unloading section and a reloading section, the stiffness of the unloading section is controlled by a parameter α, the reloading section controls the position of an inflection point by parameters β and γ, and the mapped hysteresis loop controls the strength degradation effect by a parameter η;
the mapped hysteresis control parameter
Including parameters α, β, γ, η.
8. An analysis system capable of simulating component bending shear coupling is characterized by comprising an analysis module;
the analysis module is used for performing elastic-plastic analysis of the concrete members to be analyzed one by one in an analysis step;
the analysis module is provided with a judgment module and an updating module;
the judging module is used for:
when the structural rigidity of the ith analysis step is calculated, i is an integer more than or equal to 2, and whether the stress characteristic of the component to be analyzed meets the requirement of the update threshold of the constitutive parameter or not under the ith-1 analysis step is judged;
the update module is configured to:
if the judging module judges that the requirement of updating the threshold value is not met, the mapping framework and the mapping hysteresis loop of the component to be analyzed are not updated, so that the analysis module calculates the structural rigidity of the ith analysis step according to the mapping framework and the mapping hysteresis loop in the ith-1 analysis step, and elastic-plastic analysis of the ith analysis step is completed;
if the judgment module judges that the requirement of updating the threshold value is met, mapping out mapping framework control parameters matched with the stress characteristics and the physical characteristics through a trained neural network topological relation according to the stress characteristics of the members to be analyzed in the analysis step of the (i-1) th and the predefined physical characteristics of the members to be analyzed
And mapping hysteresis loop control parameters
According to the mapping framework control parameter
Updating mapping skeleton, and controlling parameters according to the mapping hysteresis loop
Updating a mapping hysteresis loop so that the analysis module calculates the structural rigidity of the ith analysis step according to the updated mapping framework and the updated mapping hysteresis loop to complete the elastoplasticity analysis of the ith analysis step;
the stress characteristics comprise a shear-span ratio and an axial compression coefficient, and the physical characteristics comprise a hoop characteristic value and a reinforcement characteristic value.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor, when executing the computer program, implements a method of analyzing a flexural shear coupling of a simulatable member as set forth in any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of analyzing a modelable member press bending shear coupling according to any one of claims 1 to 7.
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