Railway bridge time-varying simulation model modeling, simulation and digital platform and modeling system
By establishing a digital twin simulation calculation model of railway bridges and combining it with shrinkage strain aging curves and creep coefficient tables, the problem of insufficient simulation accuracy in bridge design and construction was solved, and accurate deformation prediction and safety improvement were achieved throughout the entire life cycle.
Patent Information
- Application Number
- CN202511093886.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-06
- Publication Date
- 2025-09-05
- Estimated Expiration
- 2045-08-06
AI Technical Summary
In existing technologies, the lack of coupling between the time-varying material parameters during the bridge design and construction stages results in poor simulation accuracy and makes it difficult to accurately predict the deformation of railway bridges throughout their life cycle, especially the impact of shrinkage and creep effects.
A digital twin simulation calculation model of the railway bridge structure and construction stage is established. Through the shrinkage strain time-dependent curve and creep coefficient table, a coupled simulation calculation model of the railway bridge shrinkage and creep is constructed to achieve comprehensive environmental factors and shrinkage-creep coupling effects in each construction stage, and realize accurate prediction of the entire life cycle.
It improves the accuracy of bridge deformation simulation, ensures structural safety and operational durability throughout the entire life cycle, reduces the cost of beam and cable adjustment during the construction phase, and improves the reusability and collaborative efficiency of the model.
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Figure CN120597567A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of bridge design and evaluation, and in particular to a time-varying simulation model of a railway bridge, a simulation, a digital platform and a modeling system. Background Art
[0002] Design optimization and meticulous construction of railway bridges are key to ensuring structural safety, smooth alignment, and operational durability. High-speed railways place extremely high demands on track smoothness. Failure to fully consider the coupled effects of shrinkage and creep during the design phase, or improper control during construction, can lead to unstable train operation and even the risk of derailment. The internal stress state of a bridge directly determines its 100-year service life. Simulation design theory that considers time-varying effects must be employed during design to optimize prestressing tie arrangements. During construction, real-time monitoring and dynamic adjustments must be implemented to eliminate accumulated errors and avoid exceeding alignment standards.
[0003] The shrinkage and creep effects of concrete persist throughout the entire lifecycle of a bridge. For example, if sufficient creep compensation is not reserved during the design phase for a 32m standard railway box girder, the deflection after 10 years of operation will reach 1 / 1500 of the span, significantly impacting the smoothness of the ballastless track. In prestressed system design, stress losses caused by shrinkage and creep must be incorporated into ultimate limit state calculations. Field tests have shown that ignoring shrinkage and creep effects during the design phase can result in deviations exceeding 30mm in the main girder joint elevation. Furthermore, a lack of monitoring during construction can significantly increase cable and beam adjustment costs. Currently, traditional simulation models typically utilize 3D model design, such as those using Building Information Modeling (BIM). However, due to the relative independence of parameters within BIM models and the lack of coupling with time-varying material parameters, the coupled effects of environmental factors and shrinkage and creep during lifecycle predictions are difficult to accurately simulate within BIM models. Furthermore, BIM models lack standardized parameter definitions for different bridge construction phases, leading to confusion and poor model reusability and efficiency. Therefore, developing a modeling method for a time-varying simulation model of railway bridges is of great significance for improving the simulation accuracy of shrinkage and creep of railway bridges and improving the reliability of bridge deformation assessment throughout their life cycle. Summary of the Invention
[0004] In view of the problem that the existing technology of using three-dimensional models to evaluate bridge deformation lacks the coupling of material time-varying parameters, resulting in poor simulation accuracy, the present invention proposes a bridge deformation simulation model modeling method, which specifically includes the following steps: S1. Establish a first digital twin simulation model of the railway bridge structure based on the design parameters of the railway bridge, and establish a second digital twin simulation model of the railway bridge during the construction phase based on the construction parameters of the railway bridge; S2. Determine a third digital twin simulation model for the railway bridge shrinkage coefficient based on the first digital twin simulation model, the second digital twin simulation model, and the shrinkage strain aging curve, wherein the shrinkage strain aging curve is a curve showing the ratio of the shrinkage strain increment to the final shrinkage value over time; S3. Determine a fourth digital twin simulation calculation model for the creep coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model, and the creep coefficient table; S4. Determine a fifth digital twin simulation calculation model of an equivalent load of a railway bridge shrinkage effect based on the second digital twin simulation calculation model and the third digital twin simulation calculation model; S5. Determine a sixth digital twin simulation calculation model of the equivalent load of the creep effect of the railway bridge based on the second digital twin simulation calculation model and the fourth digital twin simulation calculation model; S6. Establishing a seventh digital twin simulation calculation model for calculating the secondary force of the railway bridge shrinkage effect based on the fifth digital twin simulation calculation model; S7. Establishing an eighth digital twin simulation calculation model for calculating the secondary force of creep effect of railway bridges based on the sixth digital twin simulation calculation model; S8. Establish a ninth digital twin simulation model for coupling shrinkage and creep of railway bridges based on the fifth digital twin simulation model, the sixth digital twin simulation model, the seventh digital twin simulation model and the eighth digital twin simulation model.
[0005] Furthermore, in S2, the shrinkage strain aging curve includes a first shrinkage strain aging curve and a second shrinkage strain aging curve, and the specific steps of determining the third digital twin simulation calculation model for the railway bridge shrinkage coefficient are: S21, determining calculation nodes in the first shrinkage strain aging curve and the second shrinkage strain aging curve; S22. Fitting a first shrinkage strain aging curve digital twin simulation calculation model based on calculation nodes in the first shrinkage strain aging curve; S23. Fitting a second shrinkage strain aging curve digital twin simulation calculation model based on the calculation nodes in the second shrinkage strain aging curve; S24. Calculating, based on the first shrinkage strain aging curve digital twin simulation calculation model and the second shrinkage strain aging curve digital twin simulation calculation model, a ratio of the shrinkage strain increment to the shrinkage final value of the railway bridge under various working conditions; S25. Based on the ratio and the final value of the contraction coefficient, calculate the contraction coefficient under various working conditions and determine the third digital twin simulation calculation model.
[0006] Furthermore, in S3, the specific steps of the fourth digital twin simulation calculation model for determining the creep coefficient of the railway bridge are: S31, fitting a creep coefficient curve according to the discrete data in the creep coefficient table; S32. Convert the creep coefficient curve into a series form to determine the fourth digital twin simulation calculation model.
[0007] Furthermore, in said S4, in said step S4, the fifth digital twin simulation calculation model for determining the equivalent load of the railway bridge shrinkage effect includes: S41. Determine the construction parameters of the railway bridge during the calculated construction phase; S42. Calculate the shrinkage strain increment corresponding to each concrete unit in the calculated construction stage based on the third digital twin simulation calculation model; S43. Determine, based on the construction parameters and the shrinkage strain increment, an equivalent load model of the shrinkage effect corresponding to the calculated construction stage of the railway bridge, and determine the fifth digital twin simulation calculation model.
[0008] Furthermore, in S5, the sixth digital twin simulation calculation model for determining the equivalent load of the creep effect of the railway bridge includes: S51. Determine the construction parameters of the railway bridge during the calculated construction phase; S52. Calculate the creep strain increment corresponding to each concrete unit in the calculated construction stage based on the fourth digital twin simulation calculation model; S53. Determine the creep effect equivalent load model corresponding to the calculated construction stage of the railway bridge according to the construction parameters and the creep strain increment, and determine the sixth digital twin simulation calculation model.
[0009] Furthermore, in S6, establishing a seventh digital twin simulation calculation model for calculating the secondary force of the railway bridge shrinkage effect includes: S61. Calculate the shrinkage effect mechanical response parameters of each concrete unit based on the fifth digital twin simulation calculation model; S62. Determine the secondary force information of the contraction effect according to the mechanical response parameters of the contraction effect, and determine the seventh digital twin simulation calculation model.
[0010] Furthermore, in S7, establishing an eighth digital twin simulation calculation model for calculating the secondary force of creep effect of railway bridges includes: S71. Calculate the creep effect mechanical response parameters of each concrete unit based on the sixth digital twin simulation calculation model; S72. Determine the secondary force information of the creep effect according to the creep effect mechanical response parameters, and determine the eighth digital twin simulation calculation model.
[0011] Furthermore, in S8, establishing a ninth digital twin simulation model for railway bridge shrinkage and creep coupling based on the fifth digital twin simulation model, the sixth digital twin simulation model, the seventh digital twin simulation model, and the eighth digital twin simulation model includes: S81. Calculate creep strain increment based on shrinkage effect mechanical response parameters and secondary force information of shrinkage effect; S82. Calculating tendon loss based on the mechanical response parameters of the shrinkage effect and the secondary force information of the shrinkage effect, as well as the mechanical response parameters of the creep effect and the secondary force information of the creep effect; S83, adjusting the creep strain increment by the steel strand loss; S84, in each construction stage, cyclically execute S81-S83 until the changes in shrinkage internal force, creep strain increment, and tendon loss are all less than the set threshold; S85. Determine the ninth digital twin simulation calculation model based on the final value of the shrinkage internal force, the creep strain increment, and the steel bundle loss.
[0012] The present invention also proposes a simulation calculation method, comprising: S10, dividing the construction process of the railway bridge into a preset number of stages; S20. In each construction stage, the shrinkage internal force and creep effect are simulated based on the ninth digital twin simulation calculation model.
[0013] Furthermore, the simulation of shrinkage force and creep effect based on the ninth digital twin simulation calculation model includes: S201, calculating the primary force information and the secondary force information of the shrinkage effect in the current construction stage; S202, taking shrinkage internal force into stress increment and calculating creep strain increment in combination with creep coefficient; S203, calculating the steel strand loss according to the shrinkage internal force and the creep strain increment; S204, adjusting the creep strain increment by the steel strand loss; S205, looping through S201-S204 until the changes in the shrinkage internal force, creep strain increment, and tendon loss are all less than a set threshold; S206 : Determine simulation results of the shrinkage internal force and the creep effect based on the shrinkage internal force, the creep strain increment, and the final value of the strand loss.
[0014] The present invention also provides a digital twin platform, which adopts the modeling method of the time-varying simulation model of the railway bridge and specifically includes the following modules: Infrastructure module: used to establish the first digital twin simulation calculation model of the railway bridge structure and the second digital twin simulation calculation model of the railway bridge construction stage; The contraction coefficient model construction module is communicatively connected to the infrastructure module: used to determine a third digital twin simulation calculation model of the contraction coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model and the contraction strain aging curve; The creep coefficient model construction module is communicatively connected to the infrastructure module: used to determine a fourth digital twin simulation calculation model of the creep coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model and the creep coefficient table; The shrinkage effect equivalent load model construction module is communicatively connected to the infrastructure module and the shrinkage coefficient model construction module: and is used to determine a fifth digital twin simulation calculation model of the shrinkage effect equivalent load of the railway bridge based on the second digital twin simulation calculation model and the third digital twin simulation calculation model; The creep effect equivalent load model construction module is communicatively connected to the infrastructure module and the creep coefficient model construction module: and is used to determine a sixth digital twin simulation calculation model of the creep effect equivalent load of the railway bridge based on the second digital twin simulation calculation model and the fourth digital twin simulation calculation model; The shrinkage effect secondary force model construction module is communicatively connected to the shrinkage effect equivalent load model construction module: used to establish a seventh digital twin simulation calculation model for calculating the shrinkage effect secondary force of the railway bridge based on the fifth digital twin simulation calculation model; The creep effect secondary force model construction module is communicatively connected to the creep effect equivalent load model construction module: used to establish an eighth digital twin simulation calculation model for calculating the creep effect secondary force of the railway bridge based on the sixth digital twin simulation calculation model; The shrinkage and creep coupling model construction module is communicatively connected to the shrinkage effect equivalent load model construction module, the creep effect equivalent load model construction module, the shrinkage effect secondary force model construction module, and the creep effect secondary force model construction module: it is used to establish a ninth digital twin simulation calculation model for shrinkage and creep coupling of railway bridges based on the fifth digital twin simulation calculation model, the sixth digital twin simulation calculation model, the seventh digital twin simulation calculation model, and the eighth digital twin simulation calculation model.
[0015] The present invention also provides a modeling system, including the digital twin platform.
[0016] Compared with the prior art, the present invention has the following beneficial effects: First, the present invention establishes a railway bridge structure model and a railway bridge construction stage model, and based on the railway bridge structure model and the railway bridge construction stage model, establishes an equivalent load model for railway bridge shrinkage effect, an equivalent load model for railway bridge creep effect, a secondary force calculation model for railway bridge shrinkage effect, and a secondary force calculation model for railway bridge creep effect. Based on the above shrinkage effect-related model and creep effect-related model, a digital twin simulation calculation model for railway bridge shrinkage and creep coupling is established. This allows for accurate prediction of the entire life cycle of the railway bridge by integrating environmental factors and shrinkage-creep coupling effects at each construction stage. Second, based on the shrinkage strain-dependence curve (i.e., β curve) specified in the concrete structure model specification, a railway bridge shrinkage coefficient model was fitted for various operating conditions. Shrinkage effects were simulated based on the fitted β value and the final shrinkage coefficient value specified in the specification. A creep coefficient curve was fitted based on the discrete data in the creep coefficient table specified in the specification. The creep coefficient was converted into a series form, taking into account the influence of time history and load conditions during the creep calculation process, to determine the railway bridge creep coefficient model. These railway bridge shrinkage coefficient and creep coefficient models were fitted based on the data specified in the specification, resulting in more standardized parameter values within the models and avoiding the issues of poor model reusability and collaborative efficiency caused by inconsistent BIM model parameter definitions. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0018] Figure 1 This is a flow chart of a modeling method for a time-varying simulation model of a railway bridge provided by an embodiment of the present invention; Figure 2 This is a flow chart of a simulation calculation method provided by an embodiment of the present invention; Figure 3 This is a structural diagram of a digital twin platform provided by an embodiment of the present invention; Figure 4 is a structural diagram of a modeling system provided by an embodiment of the present invention; Figure 5 This is a comparison chart of the shrinkage results calculated by the digital twin platform provided by an embodiment of the present invention and MIDAS; Figure 6This is a comparison chart of creep results calculated by the digital twin platform provided by an embodiment of the present invention and MIDAS. DETAILED DESCRIPTION
[0019] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.
[0020] The specific embodiments of the present invention are described below.
[0021] To address the problem of poor simulation accuracy caused by the lack of coupling of time-varying material parameters when using three-dimensional models for bridge deformation assessment in the prior art, the present invention establishes a railway bridge structural model and a railway bridge construction stage model. Based on these models, an equivalent load model for the railway bridge shrinkage effect, an equivalent load model for the railway bridge creep effect, a secondary force calculation model for the railway bridge shrinkage effect, and a secondary force calculation model for the railway bridge creep effect are established. Based on these shrinkage effect-related models and creep effect-related models, a digital twin simulation calculation model for railway bridge shrinkage and creep coupling is established. This allows for accurate prediction of the entire lifecycle of the railway bridge by integrating environmental factors and shrinkage-creep coupling effects at each construction stage.
[0022] Example 1 Figure 1 This is a flow chart of a modeling method for a time-varying simulation model of a railway bridge provided by an embodiment of the present invention. Figure 1 As shown, the modeling method specifically includes the following steps: S1. Based on the design parameters of the railway bridge, a first digital twin simulation calculation model of the railway bridge structure is established. Based on the construction parameters of the railway bridge, a second digital twin simulation calculation model of the railway bridge construction stage is established.
[0023] The design parameters of railway bridges include geometric parameters, material parameters, load parameters, and boundary conditions. The first digital twin simulation model of the railway bridge structure accurately reflects the geometric information of the railway bridge. This model parametrically associates material parameters, load combination rules, boundary conditions, and other parameters with the geometric model, forming a computable digital twin. The specific modeling process for this first digital twin simulation model of the railway bridge structure includes: First, a finite element model of the railway bridge structure is established using variable-section spatial beam elements to simulate the forces acting on the railway bridge. Then, considering the effects of steel strand alignment and prestress loss, the effective prestress is applied as an external load to the finite element model of the railway bridge structure. Pile foundation constraints utilize equivalent soil spring elements based on the m-method to simulate pile-soil interaction. Time-effect parameters of the railway bridge structure are dynamically updated during each construction phase. These parameters correspond to shrinkage and creep effects.
[0024] Railway bridge construction parameters include process parameters, process parameters, and environmental parameters. The second digital twin simulation model for the railway bridge construction phase superimposes the time dimension on the first digital twin simulation model, enabling dynamic simulation of the construction process. For example, IoT sensors can be used to collect field data and dynamically update model parameters. The specific modeling process for the second digital twin simulation model for the railway bridge construction phase includes dividing the railway bridge construction process into construction phases. Within each construction phase, the loads, units, boundary constraints, and other information involved in the calculation are determined. Furthermore, the age of each concrete unit, the temperature and humidity of the environment, and other information related to the construction parameters of each construction phase are determined.
[0025] By constructing the first digital twin simulation calculation model and the second digital twin simulation calculation model, the digital mapping of the entire process of railway bridges from design to construction can be achieved, providing a basis for the accurate evaluation of time-varying effects such as shrinkage and creep.
[0026] S2. Determine a third digital twin simulation model for the railway bridge's shrinkage coefficient based on the first digital twin simulation model, the second digital twin simulation model, and the shrinkage strain aging curve. The shrinkage strain aging curve is a β curve, representing the ratio of the shrinkage strain increment to the final shrinkage value over time. In JTJ 023-85, "Design Specification for Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts," shrinkage strain aging curves include a first shrinkage strain aging curve (first β curve) and a second shrinkage strain aging curve (second β curve). The specific steps for determining the third digital twin simulation model for the railway bridge's shrinkage coefficient are as follows: S21 . Determine calculation nodes in the first β curve and the second β curve.
[0027] S22. Based on the calculation nodes in the first β curve, fit the first β curve digital twin simulation calculation model.
[0028] S23. Based on the calculation nodes in the second β curve, fit the second β curve digital twin simulation calculation model.
[0029] The first β curve and the second β curve are shrinkage strain aging curves in JTJ 023-85, "Design Specifications for Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts." The first β curve is for a component thickness less than 20 cm, and the second β curve is for a component thickness greater than 60 cm. The two β curves cannot quickly find β values under varying parameters such as theoretical component thickness and humidity. Based on the above embodiment, this approach is designed to meet the needs of shrinkage and creep simulation calculations for the construction of a digital twin platform for the entire life cycle of railway bridges. The specific processing method is as follows: First, determine the calculation nodes in the β curve of the ratio of shrinkage strain to final shrinkage value in the shrinkage calculation of railway bridges. That is, determine the key age nodes as 4th, 7th, 14th, 28th, 56th, 90th, 180th, 360th, 720th, 1440th, and 1500th days, and calculate the corresponding β values.
[0030] Then, based on the β values at each key node, a β-curve digital twin simulation model was fitted for a theoretical component thickness less than 20 cm, and a β-curve digital twin simulation model was fitted for a theoretical component thickness greater than 60 cm. Table 1 shows the first β-curve digital twin simulation model, and Table 2 shows the second β-curve digital twin simulation model. x represents the concrete calculation time in days. The expressions in both tables are applicable to the conditions where the initial concrete age at shrinkage is 3 days, the initial concrete age is 0 during the initial stage, and the relative humidity is 60%.
[0031] Table 1 Digital twin simulation model of the first β curve
[0032] Table 2 Second β curve digital twin simulation calculation model
[0033] S24. Calculate the β values of the railway bridge under various operating conditions based on the first β curve digital twin simulation model and the second β curve digital twin simulation model. The various operating conditions include conditions with varying relative humidity and theoretical component thicknesses. For example, a two-dimensional linear interpolation algorithm may be used to first perform linear interpolation based on relative humidity and then perform linear interpolation based on theoretical component thickness. Calculate the β values of the railway bridge under various operating conditions.
[0034] S25. Based on the β value and the final value of the shrinkage coefficient, calculate the shrinkage coefficient under various working conditions.
[0035] The β curve value and the final value of the shrinkage coefficient are used to obtain the shrinkage coefficient corresponding to each stage required for calculation. The calculation formula is as follows:
[0036] Where, To calculate the shrinkage coefficient at time t, is the final value of the shrinkage coefficient.
[0037] S3. Determine the fourth digital twin simulation model for the creep coefficient of railway bridges based on the first digital twin simulation model, the second digital twin simulation model, and the creep coefficient table in JTJ 023-85, "Code for Design of Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts." The specific steps are: S31. Fit the discrete data in the creep coefficient table into a creep coefficient curve.
[0038] S32. Convert the creep coefficient curve into a series form.
[0039] Considering that the creep calculation process needs to consider the influence of time history and load state, the creep coefficient is fitted into a series form. The basic parameter values in the series form are determined, and ultimately a digital twin simulation calculation model for the creep coefficient of railway bridges is formed. Specifically, the creep coefficient is fitted into a series form expression. The specific steps and formula are as follows: Construct the model expression and select the Dirichlet series as the mathematical expression of the creep coefficient, which is in the form of:
[0040] Where, The calculation time (usually the loading and bearing time) The corresponding creep coefficient; is the unknown coefficient, and the calculation time Parameters related to the shape of the creep coefficient curve; is the unknown coefficient, which is a parameter related to the shape of the creep coefficient that changes with time; It is the parameter of the calculation time (usually also the loading and bearing time), which needs to be set in advance or determined through time scale analysis; e is the exponential operator; i is the series identifier, and n is the number of series.
[0041] Data collection at fitting points, collect concrete creep test data or corresponding data of collection points in the specification, including the measured values of creep coefficients at different time points in, No. The measured creep coefficient or code value corresponding to each point; The number of data collections.
[0042] Objective function construction, define the residual sum of squares as the objective function:
[0043] This function characterizes the overall deviation between the model predicted value and the measured value or the standard value. In the formula, S represents the objective function (residual sum of squares), and the other symbols are the same as above.
[0044] Linear equations are formed, and the objective function S is related to each coefficient Taking partial derivatives and setting them equal to zero, we get a system of linear equations:
[0045] In the formula, k is the subscript of the series operation, is the time parameter when the subscript is k, and the other parameters are the same as above.
[0046] Parameter solution and verification, using numerical methods (such as Gaussian elimination or matrix inversion) to solve the linear equations and obtain the coefficients Compare the fitting results with the test data or standard value data, calculate the relative error, and evaluate the fitting accuracy.
[0047] Parameter optimization, if the fitting accuracy is insufficient, the number of series terms can be adjusted Or reselect the time parameter (For example, logarithmic segmentation optimization For nonlinear parameter optimization problems, iterative algorithms can be used to further optimize parameter values.
[0048] S4, based on the second digital twin simulation calculation model and the third digital twin simulation calculation model, determining a fifth digital twin simulation calculation model of the equivalent load of the railway bridge shrinkage effect. Specifically comprising: S41. Determine the construction parameters of the railway bridge during the calculated construction phase, including data such as the concrete units, boundary conditions, load conditions, and material information for each concrete unit corresponding to the construction phase.
[0049] S42. Calculate the shrinkage strain increment corresponding to each concrete unit in the calculated construction stage based on the third digital twin simulation calculation model; S43. Determine the equivalent load model of shrinkage effect corresponding to the calculated construction stage of the railway bridge based on the construction parameters and shrinkage strain increment.
[0050] S5: Determine a sixth digital twin simulation model of the equivalent load of the creep effect of the railway bridge based on the second digital twin simulation model and the fourth digital twin simulation model. Specifically comprising: S51. Determine the construction parameters of the railway bridge at the calculated construction stage. This includes determining information such as the concrete units, boundary conditions, load conditions, age of each concrete unit, stage duration, and unit stress state corresponding to the calculated construction stage of the railway bridge.
[0051] S52. Calculate the creep strain increment corresponding to each concrete unit in the calculated construction stage based on the fourth digital twin simulation calculation model; S53. Determine a creep effect equivalent load model corresponding to the calculated construction stage of the railway bridge according to the construction parameters and the creep strain increment.
[0052] S6: Establishing a seventh digital twin simulation model for calculating the secondary force of the railway bridge contraction effect based on the fifth digital twin simulation model. Specifically comprising: S61. Calculate the shrinkage effect mechanical response parameters of each concrete unit based on the fifth digital twin simulation calculation model, wherein the shrinkage effect mechanical response parameters include information such as shrinkage displacement and shrinkage primary force.
[0053] S62: Determine secondary force information of the contraction effect according to the contraction effect mechanical response parameters.
[0054] S7. Establishing an eighth digital twin simulation model for calculating the secondary force of creep effect of railway bridges based on the sixth digital twin simulation model. Specifically comprising: S71. Calculate creep effect mechanical response parameters of each concrete unit based on the sixth digital twin simulation calculation model. The creep effect mechanical response parameters include creep displacement, creep primary force, and other information.
[0055] S72. Determine the secondary force information of the creep effect based on the mechanical response parameters of the creep effect.
[0056] S8. Establish a ninth digital twin simulation model for railway bridge shrinkage and creep coupling based on the fifth digital twin simulation model, the sixth digital twin simulation model, the seventh digital twin simulation model, and the eighth digital twin simulation model. Specifically, the ninth digital twin simulation model includes: S81. Calculate the creep strain increment based on the mechanical response parameters of the shrinkage effect and the secondary force information of the shrinkage effect.
[0057] S82. Calculate the strand loss based on the mechanical response parameters of the shrinkage effect and the secondary force information of the shrinkage effect, as well as the mechanical response parameters of the creep effect and the secondary force information of the creep effect.
[0058] S83. Tendon loss adjusts creep strain increment.
[0059] S84. In each construction stage, S81-S83 are executed cyclically until the changes in shrinkage internal force, creep strain increment, and tendon loss are all less than the set threshold.
[0060] S85. Determine the ninth digital twin simulation calculation model based on the final values of the shrinkage internal force, creep strain increment, and steel strand loss.
[0061] First, the calculated primary and secondary shrinkage forces are incorporated into the stress increments in the creep calculation. When calculating the creep effect, the time course of the primary and secondary shrinkage forces acting on each concrete unit must be accurately calculated. When calculating tendon loss, the effects of shrinkage and creep primary and secondary forces are considered. The tendon loss caused by these primary and secondary forces further negatively impacts the creep effect. This process is repeated for each construction stage until the changes in shrinkage internal forces, creep strain increments, and tendon loss are all less than a set threshold. At this point, shrinkage, creep, and tendon loss are balanced. This closed-loop design, which accounts for shrinkage forces, creep effects, tendon loss, and the negative impact of creep, replicates the dynamic interaction between material properties, stress states, and prestress loss in actual structures. For example, tensile stresses generated by shrinkage accelerate creep, while tendon loss caused by creep reduces stresses, thereby slowing creep. This coupled calculation is closer to measured data than traditional one-way calculations. This significantly improves the accuracy and reliability of the prediction model for the time-varying effects of railway bridges.
[0062] Example 2 Figure 2 This is a flow chart of a simulation calculation method provided by an embodiment of the present invention. Figure 2 As shown, the simulation method includes: S10. Divide the construction process of the railway bridge into a preset number of stages.
[0063] S20. At each construction stage, the shrinkage internal force and creep effect are simulated based on the ninth digital twin simulation calculation model.
[0064] The shrinkage and creep effects are simulated based on the ninth digital twin simulation model, including: S201. Calculate the primary force information and the secondary force information of the shrinkage effect in the current construction stage.
[0065] S202. Include shrinkage internal force in stress increment and calculate creep strain increment in combination with creep coefficient.
[0066] S203. Calculate the strand loss based on the shrinkage internal force and the creep strain increment.
[0067] S204. Adjust the creep strain increment by steel strand loss.
[0068] S205. Execute S201-S204 cyclically until the changes in shrinkage internal force, creep strain increment, and tendon loss are all less than the set threshold.
[0069] S206. Determine simulation results of shrinkage internal force and creep effect based on the final values of shrinkage internal force, creep strain increment, and tendon loss.
[0070] The simulation method of this embodiment is based on the ninth digital twin simulation calculation model in the above embodiment, which can ensure the accuracy of the simulation of the time-varying effects of railway bridges.
[0071] Example 3 Figure 3 This is a structural diagram of a digital twin platform provided by an embodiment of the present invention, such as Figure 3 As shown, the digital twin platform 100 adopts the modeling method in the above embodiment, and specifically includes the following modules: Infrastructure module 10: used to establish a first digital twin simulation calculation model of the railway bridge structure and a second digital twin simulation calculation model of the railway bridge construction stage.
[0072] The shrinkage coefficient model construction module 20 is communicated with the infrastructure module 10: it is used to determine the third digital twin simulation calculation model of the railway bridge shrinkage coefficient based on the first digital twin simulation calculation model, the second digital twin simulation calculation model and the β curve in JTJ 023-85 "Highway Reinforced Concrete and Prestressed Concrete Bridge and Culvert Design Code".
[0073] The creep coefficient model construction module 30 is communicated with the infrastructure module 10: it is used to determine the fourth digital twin simulation calculation model of the creep coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model and the creep coefficient table in JTJ 023-85 "Design Code for Highway Reinforced Concrete and Prestressed Concrete Bridges and Culverts".
[0074] The shrinkage effect equivalent load model construction module 40 is communicated with the infrastructure module 10 and the shrinkage coefficient model construction module 20: it is used to determine the fifth digital twin simulation calculation model of the shrinkage effect equivalent load of the railway bridge based on the second digital twin simulation calculation model and the third digital twin simulation calculation model.
[0075] The creep effect equivalent load model construction module 50 is communicated with the infrastructure module 10 and the creep coefficient model construction module 30: it is used to determine the sixth digital twin simulation calculation model of the creep effect equivalent load of the railway bridge based on the second digital twin simulation calculation model and the fourth digital twin simulation calculation model.
[0076] The shrinkage effect secondary force model construction module 60 is communicatively connected to the shrinkage effect equivalent load model construction module 40 : used to establish a seventh digital twin simulation calculation model for calculating the shrinkage effect secondary force of the railway bridge based on the fifth digital twin simulation calculation model.
[0077] The creep effect secondary force model construction module 70 is communicatively connected to the creep effect equivalent load model construction module 50 : it is used to establish an eighth digital twin simulation calculation model for calculating the creep effect secondary force of railway bridges based on the sixth digital twin simulation calculation model.
[0078] The shrinkage and creep coupling model construction module 80 is communicated with the shrinkage effect equivalent load model construction module 40, the creep effect equivalent load model construction module 50, the shrinkage effect secondary force model construction module 60, and the creep effect secondary force model construction module 70: used to establish a ninth digital twin simulation calculation model for shrinkage and creep coupling of railway bridges based on the fifth digital twin simulation calculation model, the sixth digital twin simulation calculation model, the seventh digital twin simulation calculation model, and the eighth digital twin simulation calculation model.
[0079] In this embodiment, the shrinkage and creep coupling model construction module 80 couples models related to shrinkage and creep effects, enabling the integration of environmental factors and shrinkage-creep coupling effects at each construction stage. By establishing a digital twin platform for the entire "design-construction-operation and maintenance" lifecycle, shrinkage and creep simulation methods are integrated. Multi-physics coupling algorithms are integrated on the design side to optimize prestressing tie-laying schemes. A virtual-real dual closed-loop system is established on the construction side, enabling creep prediction errors to be controlled within 5%. This is of great significance for optimizing structural design and construction plans.
[0080] Example 4 Figure 4 This is a structural diagram of a modeling system provided by an embodiment of the present invention, such as Figure 4 As shown, modeling system 20 includes the digital twin platform 100 of the aforementioned embodiment. Because the digital twin platform can access real-time monitoring data from physical entities, such as temperature, strain, and displacement collected by sensors, it allows the virtual model to maintain dynamic synchronization with the physical state. Applying the digital twin platform of the aforementioned embodiment to the modeling system significantly improves design reliability, construction efficiency, and operational safety in complex projects such as railway bridges, providing valuable insights for future intelligent modeling.
[0081] For example, the structural design finite element analysis software (MIDAS) and the digital twin platform in the above embodiment are used to simulate the shrinkage and creep calculation values of three continuous beams with a span of (94.5+166.4+107.9) m, and the simulation results are analyzed.
[0082] The shrinkage calculation results of the railway bridge's full life cycle calculated by MIDAS and the digital twin platform are extracted. The corresponding data of each unit of the whole bridge are shown in Table 3, and the comparison chart is as follows: Figure 5 As shown in Table 3, the calculation errors of all units fluctuate below 1%, indicating that the shrinkage results calculated by the digital twin platform are very close to those calculated by MIDAS.
[0083] Table 3 Comparison of the ten-year shrinkage results of completed bridges calculated by the digital twin platform and MIDAS
[0084]
[0085]
[0086] The creep calculation results of the railway bridge’s full life cycle calculated by MIDAS and the digital twin platform after ten years of completion are extracted. The corresponding data of each unit of the whole bridge are shown in Table 4, and the comparison chart is as follows: Figure 6 As shown in Table 4, the calculation error of creep values at the centimeter level fluctuates around 3%, indicating that the shrinkage results calculated by the digital twin platform are very close to those calculated by MIDAS.
[0087] Table 4 Comparison of 10-year creep results of completed bridges calculated by the digital twin platform and MIDAS
[0088]
[0089]
[0090]
[0091] In this embodiment, the calculation results from the digital twin computing platform show a small error compared to those from MIDAS, validating the accuracy of the shrinkage and creep simulation method for the digital twin platform used in this embodiment for the full lifecycle construction of railway bridges. Furthermore, the digital twin platform provided by this embodiment can rapidly create a large number of digital twin models of the same or similar physical entities through standardization and parameterization, enabling batch modeling. This results in faster modeling and higher computational efficiency compared to the traditional MIDAS approach of manual, individual modeling.
[0092] Example 5 An electronic device, comprising: processor and memory; The processor is used to execute the steps of the modeling method of the time-varying simulation model of the railway bridge as described in any one of Example 1 by calling the program or instructions stored in the memory.
[0093] Example 6 A computer-readable storage medium comprising computer program instructions, wherein the computer program instructions enable a computer to execute the steps of the method for modeling a time-varying simulation model of a railway bridge as described in any one of Example 1.
[0094] The computer-readable storage medium may be any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.
[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.
Claims
1. A modeling method for a time-varying simulation model of a railway bridge, characterized in that: include: S1. Establish a first digital twin simulation model of the railway bridge structure based on the design parameters of the railway bridge, and establish a second digital twin simulation model of the railway bridge during the construction phase based on the construction parameters of the railway bridge; S2. Determine a third digital twin simulation model for the railway bridge shrinkage coefficient based on the first digital twin simulation model, the second digital twin simulation model, and the shrinkage strain aging curve, wherein the shrinkage strain aging curve is a curve showing the ratio of the shrinkage strain increment to the final shrinkage value over time; S3. Determine a fourth digital twin simulation calculation model for the creep coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model, and the creep coefficient table; S4. Determine a fifth digital twin simulation calculation model of an equivalent load of a railway bridge shrinkage effect based on the second digital twin simulation calculation model and the third digital twin simulation calculation model; S5. Determine a sixth digital twin simulation calculation model of the equivalent load of the creep effect of the railway bridge based on the second digital twin simulation calculation model and the fourth digital twin simulation calculation model; S6. Establishing a seventh digital twin simulation calculation model for calculating the secondary force of the railway bridge shrinkage effect based on the fifth digital twin simulation calculation model; S7. Establishing an eighth digital twin simulation calculation model for calculating the secondary force of creep effect of railway bridges based on the sixth digital twin simulation calculation model; S8. Establish a ninth digital twin simulation model for coupling shrinkage and creep of railway bridges based on the fifth digital twin simulation model, the sixth digital twin simulation model, the seventh digital twin simulation model and the eighth digital twin simulation model.
2. The modeling method of the time-varying simulation model of a railway bridge according to claim 1 is characterized in that: In S2, the shrinkage strain aging curve includes a first shrinkage strain aging curve and a second shrinkage strain aging curve. The specific steps of determining the third digital twin simulation calculation model for the railway bridge shrinkage coefficient are: S21, determining calculation nodes in the first shrinkage strain aging curve and the second shrinkage strain aging curve; S22. Fitting a first shrinkage strain aging curve digital twin simulation calculation model based on calculation nodes in the first shrinkage strain aging curve; S23. Fitting a second shrinkage strain aging curve digital twin simulation calculation model based on the calculation nodes in the second shrinkage strain aging curve; S24. Calculate, based on the first shrinkage strain aging curve digital twin simulation calculation model and the second shrinkage strain aging curve digital twin simulation calculation model, a ratio of the shrinkage strain increment to the shrinkage final value of the railway bridge under various working conditions; S25. Based on the ratio and the final value of the contraction coefficient, calculate the contraction coefficient under various working conditions and determine the third digital twin simulation calculation model.
3. The modeling method of the time-varying simulation model of a railway bridge according to claim 1 is characterized in that: In S3, the specific steps of the fourth digital twin simulation calculation model for determining the creep coefficient of the railway bridge are: S31, fitting a creep coefficient curve according to the discrete data in the creep coefficient table; S32. Convert the creep coefficient curve into a series form to determine the fourth digital twin simulation calculation model.
4. The modeling method of the time-varying simulation model of a railway bridge according to claim 2, characterized in that: In said S4, the fifth digital twin simulation calculation model for determining the equivalent load of the railway bridge shrinkage effect includes: S41. Determine the construction parameters of the railway bridge during the calculated construction phase; S42. Calculate the shrinkage strain increment corresponding to each concrete unit in the calculated construction stage based on the third digital twin simulation calculation model; S43. Determine the shrinkage effect equivalent load model corresponding to the railway bridge in the calculated construction stage according to the construction parameters and the shrinkage strain increment, and obtain the fifth digital twin simulation calculation model.
5. The modeling method of the time-varying simulation model of a railway bridge according to claim 3 is characterized in that: In S5, the sixth digital twin simulation calculation model for determining the equivalent load of the creep effect of the railway bridge includes: S51. Determine the construction parameters of the railway bridge during the calculated construction phase; S52. Calculate the creep strain increment corresponding to each concrete unit in the calculated construction stage based on the fourth digital twin simulation calculation model; S53. Determine the creep effect equivalent load model corresponding to the calculated construction stage of the railway bridge according to the construction parameters and the creep strain increment, and obtain the sixth digital twin simulation calculation model.
6. The modeling method of the time-varying simulation model of a railway bridge according to claim 4, characterized in that: In S6, establishing a seventh digital twin simulation calculation model for calculating the secondary force of the railway bridge shrinkage effect includes: S61. Calculate the shrinkage effect mechanical response parameters of each concrete unit based on the fifth digital twin simulation calculation model; S62. Determine the secondary force information of the contraction effect according to the mechanical response parameters of the contraction effect, and determine the seventh digital twin simulation calculation model.
7. The modeling method of the time-varying simulation model of a railway bridge according to claim 5, characterized in that: In S7, establishing an eighth digital twin simulation calculation model for calculating the secondary force of creep effect of railway bridges includes: S71. Calculate the creep effect mechanical response parameters of each concrete unit based on the sixth digital twin simulation calculation model; S72. Determine the secondary force information of the creep effect according to the creep effect mechanical response parameters, and determine the eighth digital twin simulation calculation model.
8. The modeling method of the time-varying simulation model of a railway bridge according to claim 1, characterized in that: In S8, establishing a ninth digital twin simulation model for railway bridge shrinkage and creep coupling based on the fifth digital twin simulation model, the sixth digital twin simulation model, the seventh digital twin simulation model, and the eighth digital twin simulation model includes: S81. Calculate creep strain increment based on shrinkage effect mechanical response parameters and secondary force information of shrinkage effect; S82. Calculate the tendon loss based on the mechanical response parameters of the shrinkage effect and the secondary force information of the shrinkage effect, as well as the mechanical response parameters of the creep effect and the secondary force information of the creep effect; S83, adjusting the creep strain increment by the steel strand loss; S84, in each construction stage, cyclically execute S81-S83 until the changes in shrinkage internal force, creep strain increment, and tendon loss are all less than the set threshold; S85. Determine the ninth digital twin simulation calculation model based on the final value of the shrinkage internal force, the creep strain increment, and the steel bundle loss.
9. A simulation calculation method, characterized in that: include: S10, dividing the construction process of the railway bridge into a preset number of stages; S20. At each construction stage, the shrinkage internal force and creep effect are simulated based on the ninth digital twin simulation calculation model in claim 1.
10. The simulation calculation method according to claim 9, characterized in that: The simulation of shrinkage internal force and creep effect based on the ninth digital twin simulation calculation model includes: S201, calculating the primary force information and the secondary force information of the shrinkage effect in the current construction stage; S202, taking shrinkage internal force into stress increment and calculating creep strain increment in combination with creep coefficient; S203, calculating the steel strand loss according to the shrinkage internal force and the creep strain increment; S204, adjusting the creep strain increment by the steel strand loss; S205, looping through S201-S204 until the changes in the shrinkage internal force, creep strain increment, and tendon loss are all less than a set threshold; S206 : Determine simulation results of the shrinkage internal force and the creep effect based on the shrinkage internal force, the creep strain increment, and the final value of the strand loss.
11. A digital twin platform, characterized in that: The digital twin platform adopts the modeling method of the time-varying simulation model of the railway bridge according to any one of claims 1 to 8, and specifically includes the following modules: Infrastructure module: used to establish the first digital twin simulation calculation model of the railway bridge structure and the second digital twin simulation calculation model of the railway bridge construction stage; The contraction coefficient model construction module is communicatively connected to the infrastructure module: used to determine a third digital twin simulation calculation model of the contraction coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model and the contraction strain aging curve; The creep coefficient model construction module is communicatively connected to the infrastructure module: used to determine a fourth digital twin simulation calculation model of the creep coefficient of the railway bridge based on the first digital twin simulation calculation model, the second digital twin simulation calculation model and the creep coefficient table; The shrinkage effect equivalent load model construction module is communicatively connected to the infrastructure module and the shrinkage coefficient model construction module: and is used to determine a fifth digital twin simulation calculation model of the shrinkage effect equivalent load of the railway bridge based on the second digital twin simulation calculation model and the third digital twin simulation calculation model; The creep effect equivalent load model construction module is communicatively connected to the infrastructure module and the creep coefficient model construction module: and is used to determine a sixth digital twin simulation calculation model of the creep effect equivalent load of the railway bridge based on the second digital twin simulation calculation model and the fourth digital twin simulation calculation model; The shrinkage effect secondary force model construction module is communicatively connected to the shrinkage effect equivalent load model construction module: used to establish a seventh digital twin simulation calculation model for calculating the shrinkage effect secondary force of the railway bridge based on the fifth digital twin simulation calculation model; The creep effect secondary force model construction module is communicatively connected to the creep effect equivalent load model construction module: used to establish an eighth digital twin simulation calculation model for calculating the creep effect secondary force of the railway bridge based on the sixth digital twin simulation calculation model; The shrinkage and creep coupling model construction module is communicatively connected to the shrinkage effect equivalent load model construction module, the creep effect equivalent load model construction module, the shrinkage effect secondary force model construction module, and the creep effect secondary force model construction module: it is used to establish a ninth digital twin simulation calculation model for shrinkage and creep coupling of railway bridges based on the fifth digital twin simulation calculation model, the sixth digital twin simulation calculation model, the seventh digital twin simulation calculation model, and the eighth digital twin simulation calculation model.
12. A modeling system, characterized in that: Including the digital twin platform described in claim 11.
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