Bridge cable corrosion simulation method based on cellular automaton

Abstract

The embodiment of the invention discloses a bridge inhaul cable corrosion simulation method based on a cellular automaton, comprising: acquiring an inhaul cable cellular model of a to-be-simulated bridge inhaul cable, the inhaul cable cellular model comprising a plurality of tightly arranged steel wire cellular models, gaps between the steel wire cellular models being called steel wire gaps; a steel wire gap where the actual damage position of the bridge inhaul cable is located is filled with electrolyte liquid film cells; the permeation rule of the electrolyte liquid membrane is set as follows: S1, when one steel wire gap is filled with an electrolyte solution, the adjacent steel wire gap below the steel wire gap is filled with the electrolyte solution at a certain probability in each simulation iteration of the cellular automaton; s2, after each simulation iteration is carried out for a set number of times, passive film cells at contact points of a set number of steel wire cell models disappear; and operating the inhaul cable cellular model according to the permeation rule so as to simulate the corrosion condition of the inhaul cable. According to the embodiment, the accuracy of inhaul cable corrosion simulation is improved.

Description

Technical Field

[0001] This invention relates to the field of bridge cable corrosion simulation technology, and in particular to a bridge cable corrosion simulation method based on cellular automata. Background Technology

[0002] The study on corrosion simulation of bridge cable wires aims to simulate the corrosion process of cable wires under different environmental conditions using computer models and algorithms. Corrosion is a significant factor affecting bridge safety, especially in atmospheric and marine environments. Simulation can help predict corrosion processes, analyze the effects of factors such as humidity, temperature, and salt spray on corrosion, and study the impact of corrosion on the performance of the steel wires, providing a scientific basis for engineering design and maintenance.

[0003] Existing technologies for simulating the corrosion of cable wires mainly focus on cellular automata, neural networks, and COMSOL software methods. Because cellular automata and neural networks can represent the randomness of corrosion and generate uneven corrosion pits compared to COMSOL, cellular automata methods are more suitable for localized corrosion of cable wires. For example, Guo Zengwei et al. proposed a cellular automata-based simulation method to study the electrochemical corrosion process of cable wires in real-world environments, particularly the catalytic effect of chloride ions. By appropriately selecting the characteristic parameters of the cellular automata and adjusting the contact probability of neighboring cells, the morphology of the corrosion pits can be made more closely resemble reality. Wang Xiaoming et al. proposed a method based on a two-dimensional corrosion cellular automata model to simulate the corrosion evolution process of zinc-aluminum alloy coatings. This model combines microstructure, uniformity test data, and corrosion test data of the zinc-aluminum alloy coating, focusing on analyzing the influence of metal oxidation, hydration, dissolution reactions, and coating inhomogeneity on the corrosion process.

[0004] However, the limitations of corrosion simulation of cable wires based on cellular automata mainly lie in the fact that the corrosion of the wires does not fully consider the influence of the coating and the actual environment, resulting in an imperfect cable simulation. First, there is a lack of a wire corrosion model applicable to various coating types; second, corrosion models need to consider numerous environmental factors, and existing models can only consider as many environmental factors as possible; finally, there is no comprehensive cable corrosion model yet, and the simulation accuracy is not ideal. Summary of the Invention

[0005] This invention provides a bridge cable corrosion simulation method based on cellular automata to solve at least one of the above problems.

[0006] In a first aspect, embodiments of the present invention provide a method for simulating bridge cable corrosion based on cellular automata, comprising:

[0007] Obtain the cable cell model of the bridge cable to be simulated. The cable cell model includes multiple closely arranged wire cell models. The gap between the wire cell models is called the wire gap.

[0008] Electrolyte film cells were filled into the gaps between the steel wires where the actual damage location of the bridge cable was located.

[0009] The permeation rules for the electrolyte membrane are set as follows:

[0010] S1. When a wire gap is filled with electrolyte solution, the adjacent wire gap below the wire gap is filled with electrolyte solution with a certain probability in each simulation iteration of the cellular automaton.

[0011] S2. After each set number of simulation iterations, a set number of passivation membrane cells at the contact points of the wire cell model disappear.

[0012] The cable cell model is run according to the permeation rules to simulate the corrosion of the cable.

[0013] In a second aspect, embodiments of the present invention provide an electronic device, the electronic device comprising:

[0014] One or more processors;

[0015] Memory, used to store one or more programs;

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement the bridge cable corrosion simulation method based on cellular automata as described in any embodiment.

[0017] Thirdly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the bridge cable corrosion simulation method based on cellular automata as described in any embodiment.

[0018] This invention provides a method for simulating bridge cable corrosion based on cellular automata. First, a cellular automata model of a single steel wire is established to obtain the relationship between corrosion depth and the number of iterations. Then, the simulation results are compared with theoretical corrosion kinetic curves, and corrosion control parameters are adjusted to ensure consistency between the simulation results and the theory. Finally, the corrosion control parameters are introduced into the cable model, and after determining the location of sheath damage, cable corrosion simulation is performed to obtain the degree of steel wire corrosion under different iteration numbers.

[0019] Specifically, this embodiment sets up corrosion cells T representing aluminum corrosion products and Y representing magnesium corrosion products for zinc-aluminum coated steel wire and zinc-aluminum-magnesium coated steel wire, and sets up movement rules and corrosion rules matching corrosion cells T and Y. Furthermore, the permeation rules of the electrolyte film consider the effects of gravity on corrosion probability in different directions, as well as the changes in sheath wrapping force over time, thus improving simulation accuracy. Attached Figure Description

[0020] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0021] Figure 1 This is a flowchart of a bridge cable corrosion simulation method based on cellular automata provided in an embodiment of the present invention;

[0022] Figure 2 This is a schematic diagram of a steel wire cell model provided in an embodiment of the present invention;

[0023] Figure 3 This is a schematic diagram of a cable cell model and its damaged location provided in an embodiment of the present invention;

[0024] Figure 4(a) is a schematic diagram of the results of 600 simulation iterations of a cable corrosion process provided in an embodiment of the present invention;

[0025] Figure 4(b) is a schematic diagram of the results of 1200 simulation iterations of a cable corrosion process provided in an embodiment of the present invention;

[0026] Figure 4(c) is a schematic diagram of the results of 1800 simulation iterations of a cable corrosion process provided in an embodiment of the present invention;

[0027] Figure 5 This is a flowchart of another bridge cable corrosion simulation method based on cellular automata provided in this embodiment of the invention;

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0030] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0031] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0032] In a cellular automaton system, the core elements of system operation are cell state, evolution rule, and cell neighbors, which can be represented as follows:

[0033] φ 2 =f(H,K,N) (1)

[0034] Where, φ 2 Let f(·) represent a two-dimensional cellular space, consisting of n discrete finite-state cellular lattices; H is the set of n cellular states in discrete time; K represents the set of k evolution rules; N represents the set of neighboring cellular states of the n cellular spaces; and f(·) represents the system function.

[0035] Based on the above basic theories Figure 1 This is a flowchart illustrating a bridge cable corrosion simulation method based on cellular automata, provided in an embodiment of the present invention. Figure 1 As shown, the method specifically includes:

[0036] S110. Determine the cell types in the Lasso cellular automaton model.

[0037] The cable cellular automaton model in this embodiment refers to a model that uses cellular automata to describe the corrosion of bridge cables. In this embodiment, 11 cell representations are constructed for the cellular space of this model:

[0038] 1) Corrosion cell O represents oxygen molecules in the electrolyte film.

[0039] 2) Corrosion-promoting cell C represents chloride ions in the electrolyte film.

[0040] 3) Solution cell W represents water molecules in the electrolyte membrane.

[0041] 4) Passivation cell G represents the passivation membrane.

[0042] 5) Metal cell Z represents metallic zinc within a zinc matrix.

[0043] 6) Metal cell A represents aluminum in a zinc matrix.

[0044] 7) Metal cell M represents magnesium metal within a zinc matrix.

[0045] 8) Metal cell F represents metallic iron within an iron matrix.

[0046] 9) Corrosion cell P represents the corrosion products of metallic zinc.

[0047] 10) Rust cell T represents the corrosion products of metallic aluminum.

[0048] 11) The corrosion cell Y represents the corrosion products of metallic magnesium.

[0049] 12) Rust cell K represents the corrosion products of metallic iron.

[0050] 12) Boundary cell H represents the cable sheath.

[0051] S120. Determine the basic assumptions of the Lasso cellular automata model.

[0052] The basic assumptions here refer to some fundamental conditions in the modeling and operation of the LAC cellular machine model, which form the basis for subsequently determining the cellular evolution rules. Optional basic assumptions include:

[0053] 1) One cell represents one type of molecule or atom. To ensure chemical equilibrium, it is assumed that the number of metal atoms in the metal cells (Z, M, F) is twice the number of molecules in the corrosion cells (O) or solution cells (W), and that the number of metal atoms in the metal cell (A) is three times the number of molecules in the corrosion cells (O) or solution cells (W).

[0054] 2) When the corrosion cell (O) comes into contact with the metal cell (Z, A, M, F) or the passivation cell (G), the two react with a certain probability.

[0055] 3) When the metal cells are dissolved, the lattice at that location is filled with electrolyte film cells according to the proportion of cell types, so that the concentration of corrosion cells (O) and corrosion promoting cells (C) in the electrolyte film remains constant throughout the corrosion process.

[0056] 4) Sulfur dioxide and carbon dioxide participate in the atmospheric corrosion of coated steel wire; however, their effects are ignored in this model. Chloride ions, acting as corrosion-promoting cells (C), only accelerate the corrosion reaction rate.

[0057] 5) The effects of different atmospheric environments on the corrosion process of galvanized steel are reflected by changing the concentrations of corrosion cells (O) and corrosion promoting cells (C) and the dissolution probability of corrosion cells (O) on metal cells.

[0058] 6) The corrosion cells (P, T, Y, K) play a protective role during the corrosion process, and the corrosion cells (P, T, Y, K) will detach and dissolve with a certain probability.

[0059] S130, Determine the cell movement rules.

[0060] Of all cell types, only corrosion cells (O) and corrosion-promoting cells (C) participate in active movement. Cells represent the diffusion of oxygen and chloride ions through active movement, and a random walk method conforming to Fick's second law is used to simulate the diffusion process. The specific movement rules for O and C cells are as follows:

[0061] 1) In each iteration, cells O and C can arbitrarily select a neighbor direction and move to it (the probability is the same for any direction).

[0062] 2) When both O and C cells move toward the same W or O or C cell, they remain in the original lattice.

[0063] 3) When only one O cell or C cell moves toward W cell, W cell swaps positions with O cell or C cell.

[0064] 4) Corrosion products of zinc, aluminum, magnesium, and iron are deposited on the metal surface due to gravity, preventing further corrosion. Considering the deposition effect of corrosion products, P, T, Y, and K cells will exchange positions with the nearest W, O, or C cell in the lattice along their center direction until there are no W, O, or C cells in the lattice below.

[0065] S140. Determine the erosion rules for the cells.

[0066] The corrosion process of the cells proceeds based on Faraday's law of electrochemical reactions, following these rules:

[0067] 1) Cell G is dissolved by cell O with a fixed probability Pgo, and when cell C is in the neighboring space of cell G, cell G is dissolved by cell O with a fixed probability Pgc. This can be used to represent the process of random dissolution of the passivation film in the early stage of corrosion, resulting in pitting.

[0068] 2) Z cells are dissolved by O cells with a fixed probability Pzo, and transformed into P cells with a probability of 1-Pzo; when there are C cells in the neighboring space of an O cell, it is dissolved by the O cell with a fixed probability Pzc, and transformed into a P cell with a probability of 1-Pzc. This can be used to represent the participation of metallic zinc in electrochemical reactions, in which metallic zinc loses electrons to become zinc ions, which are released into the electrolyte film and generate corrosion products.

[0069] 3) Cell A is dissolved by cell O with a fixed probability Pao, and is transformed into cell T with a probability of 1-Pao; when cell O has cell C in its neighboring space, it is dissolved by cell O with a fixed probability Pac, and is transformed into cell T with a probability of 1-Pac. This can be used to represent the participation of metallic aluminum in electrochemical reactions, in which metallic aluminum loses electrons to become aluminum ions, which are released into the electrolyte film and generate corrosion products.

[0070] 4) Cell M is dissolved by cell O with a fixed probability Pmo, and transforms into cell Y with a probability of 1-Pmo. When cell O is near cell C, cell M is dissolved by cell O with a fixed probability Pmc, and transforms into cell Y with a probability of 1-Pmc. This can be used to represent the participation of metallic magnesium in an electrochemical reaction, in which metallic magnesium loses electrons to become magnesium ions, which are released into the electrolyte film and generate corrosion products.

[0071] 5) P cells disappear with a fixed probability Pp. This can be used to represent the cracking, detachment, and dissolution process of corrosion products due to environmental factors.

[0072] 6) T cells disappear with a fixed probability of Pt. This can be used to represent the cracking, detachment, and dissolution process of corrosion products due to environmental factors.

[0073] 7) Y cells disappear with a fixed probability Py. This can be used to represent the cracking, detachment, and dissolution process of corrosion products due to environmental factors.

[0074] 8) Cell F is dissolved by cell O with a fixed probability of Pfo, and is transformed into cell K with a probability of 1-Pfo. When cell O is near cell C, cell Fc is dissolved by cell O with a fixed probability of Pfc, and is transformed into cell K with a probability of 1-Pfc. This can be used to represent the participation of metallic iron in electrochemical reactions, in which metallic iron loses electrons to become iron ions, which are released into the electrolyte film and generate corrosion products.

[0075] 9) K cells disappear with a fixed probability Pk. This can be used to represent the cracking, detachment, and dissolution process of corrosion products due to environmental factors.

[0076] 10) When G, Z, A, M, and F cells are dissolved by O cells or P and K cells disappear with a fixed probability, O cells will occupy their lattice, and the original lattice will generate W, O, and C cells with the same probability as the initial concentration.

[0077] S110 to S140 can be systematically assembled into the following functions:

[0078]

[0079] Where a is the two-dimensional position of the cell; t is the current time step; t+1 is the next time step; k1, k2, and k3 are different transformation rules (including movement rules and erosion rules); a m Let a be the four neighboring cells above, below, left, and right of cell a. n Let m = n = 4 be the four neighboring cells of cell a, located at the top right, bottom right, top left, and bottom left.

[0080] S150. Based on the above cell types and rules, construct a cellular automaton model for the steel wire.

[0081] This embodiment first constructs a cellular automata model of the steel wire used in bridge cables. In one specific implementation, a field emission scanning electron microscope and an energy dispersive spectroscopy (EDS) instrument can be used to analyze the coating of the cut steel wire to obtain the composition ratio of each metal at different depths.

[0082] A two-dimensional square blank cell space is established, and the cell lattice spacing of the steel wire cellular automaton model is set to 10 μm. A circular steel wire blank cell model is established in the blank cell space according to the diameter of the steel wire used in the cable.

[0083] In the blank cell model of the steel wire, an interval is divided every 10μm depth. According to the composition content of each metal element obtained from the coating analysis, the corresponding cell is set for each blank cell position in sequence; the outermost cell of the model is set as the passivation film cell G.

[0084] Besides the wire cells, the remaining empty cells are set as electrolyte membrane cells, including W, O, and C cells, with an initial ratio of 0.8:0.15:0.05, resulting in the wire cell model. To illustrate the wire cell model more clearly, Figure 2 A cellular model of a pure zinc-coated steel wire with a diameter of 20 cm is shown, with the wire having a diameter of 2000 cells.

[0085] The aforementioned steel wire cell model, along with the cell's basic assumptions, movement rules, corrosion rules, and penetration rules, together constitute the steel wire cell automata model.

[0086] S160. Determine the corrosion control parameters for the steel wire cellular automata model.

[0087] Based on the aforementioned fundamental assumptions, movement rules, and corrosion rules, a steel wire cell model is run for iterative simulation calculations. The average corrosion depth is calculated every 10 iterations, yielding a simulated curve showing the corrosion depth changing over time.

[0088] By comparing the simulated curves with the theoretical curves from the corrosion kinetic model of this type of steel wire, the corrosion control parameters Pgo, Pgc, Pzo, Pzc, Pao, Pac, Pmo, Pmc, Pfo, Pfc, Pp, Pt, Py, and Pk can be adjusted to ensure consistency between the simulated and theoretical curves. Simultaneously, based on the number of model iterations at the same corrosion depth and the actual time of the theoretical curve, the conversion relationship between the number of iterations and the actual corrosion time is determined.

[0089] S170. Based on the cellular automaton model of steel wire, construct the cellular automaton model of cable.

[0090] First, the wire cell model constructed using S150 is expanded according to the actual cable specifications, and arranged closely in a two-dimensional space to obtain the complete cable cross-section. The gaps between the wire cell models in the cross-section are called wire gaps. Boundary cells H are set around the wire region of the cable.

[0091] Next, the location of the sheath breakage is determined. Optionally, electrolyte film cells are filled into the gaps between the steel wires at the actual breakage location of the bridge cable. Since the actual breakage location is always on the outer ring of the cable, the actual breakage location can be found along the gaps between the steel wires on the outer ring of the cable, and electrolyte film cells are filled into these gaps to obtain the cable cell model. The ratio of W, O, and C cells remains 0.8:0.15:0.05. Taking a 1x127 hot-dip galvanized steel wire φ5 as an example, the constructed cable cell model and the angle breakage are as follows: Figure 3 As shown.

[0092] The movement and corrosion rules of the LAC cells are as described in S130 and S140. The permeation rules of the electrolyte membrane are as follows:

[0093] 1) When corrosion cell O corrodes any passivated cell at any point of contact in the wire cell model within the wire gap, the electrolyte film enters the wire gap through the contact point voids and fills the gap space in a fixed proportion. One wire gap consists of three contact points.

[0094] 2) When a wire gap is filled with electrolyte solution, the adjacent cable gap below it is directly filled with electrolyte solution in each iteration with probability Pr. This indicates that the liquid film is subject to gravity, making the probability of wire corrosion in the region below the solution greater than in the regions on the left and right.

[0095] 3) After every 50 iterations, x passivated membrane cells at contact points disappear, indicating that the sheath's enveloping force decreases over time, causing the electrolyte solution to penetrate a wider range over time.

[0096] The aforementioned Lasso cellular model and basic assumptions, along with the cell movement rules, corrosion rules, and electrolyte membrane permeation rules, together constitute the Lasso cellular automata model.

[0097] S180. Run the cable cellular automaton model to simulate the corrosion of the cable.

[0098] Based on the aforementioned basic assumptions, movement rules, corrosion rules, and penetration rules, a cable cellular model was run to simulate and iteratively calculate the cable corrosion situation. The total number of iterations was determined by converting the number of iterations to practical applications. Every 10 iterations, the number of remaining cells for each wire was calculated, converted into the wire weight loss rate and average corrosion depth. Cable corrosion results were generated for different iteration numbers as needed. As shown in Figures 4(a), 4(b), and 4(c), the percentage of remaining mass of each wire was generated after 600, 1200, and 1800 iterations, respectively.

[0099] The above process S110-S180 can be combined with Figure 5 Please refer to the flowchart shown for comprehension.

[0100] In summary, this embodiment provides a bridge cable corrosion simulation method based on cellular automata. First, a cellular automata model of a single steel wire is established to obtain the relationship between corrosion depth and the number of iterations. Then, the simulation results are compared with theoretical corrosion kinetic curves, and the corrosion control parameters are adjusted to ensure consistency between the simulation results and the theory. Finally, the corrosion control parameters are introduced into the cable model, and after determining the location of sheath damage, cable corrosion simulation is performed to obtain the degree of steel wire corrosion under different iteration numbers.

[0101] Specifically, this embodiment sets up corrosion cells T representing aluminum corrosion products and Y representing magnesium corrosion products for zinc-aluminum coated steel wire and zinc-aluminum-magnesium coated steel wire, and sets up movement rules and corrosion rules matching corrosion cells T and Y. Furthermore, the permeation rules of the electrolyte film consider the effects of gravity on corrosion probability in different directions, as well as the changes in sheath wrapping force over time, thus improving simulation accuracy.

[0102] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, such as... Figure 6 As shown, the device includes a processor 60, a memory 61, an input device 62, and an output device 63; the number of processors 60 in the device can be one or more. Figure 6Taking a processor 60 as an example; the processor 60, memory 61, input device 62, and output device 63 in the device can be connected via a bus or other means. Figure 6 Taking the example of a connection between China and Israel via a bus.

[0103] The memory 61, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the bridge cable corrosion simulation method based on cellular automata in this embodiment of the invention. The processor 60 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 61, thereby realizing the aforementioned bridge cable corrosion simulation method based on cellular automata.

[0104] The memory 61 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data created based on terminal usage. Furthermore, the memory 61 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory, or other non-volatile solid-state storage device. In some instances, the memory 61 may further include memory remotely located relative to the processor 60, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0105] Input device 62 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 63 may include display devices such as a display screen.

[0106] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the bridge cable corrosion simulation method based on cellular automata of any embodiment.

[0107] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0108] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0109] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0110] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages—such as Java, Smalltalk, and C++—as well as conventional procedural programming languages—such as C or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention.

Claims

1. A method for simulating bridge cable corrosion based on cellular automata, characterized in that, include: Obtain the cable cell model of the bridge cable to be simulated. The cable cell model includes multiple closely arranged wire cell models. The gap between the wire cell models is called the wire gap. Electrolyte film cells were filled into the gaps between the steel wires where the actual damage location of the bridge cable was located. The permeation rules for the electrolyte membrane are set as follows: S1. When a wire gap is filled with electrolyte solution, the adjacent wire gap below the wire gap is filled with electrolyte solution with a certain probability in each simulation iteration of the cellular automaton. S2. After each set number of simulation iterations, a set number of passivation membrane cells at the contact points of the wire cell model disappear. The cable cell model is run according to the permeation rules to simulate the corrosion of the cable.

2. The method according to claim 1, characterized in that, The process of obtaining the cable cell model of the bridge cable to be simulated includes: Determine the cell type, movement rules, and erosion rules; Based on the proportion of each metal at different depths of the steel wire, various types of steel wire cells are added in the cellular space of the steel wire, and passivation film cells are added to the outermost layer of the steel wire, with each cell arranged closely together. The moving rules, corrosion rules, and all cells together constitute the wire cell model; Based on the type of bridge cable to be simulated, multiple wire cell models are arranged closely to obtain the cable cell model of the bridge cable.

3. The method according to claim 2, characterized in that, Determining the type of cell includes: For zinc-aluminum-magnesium coated steel wire, corrosion cells T representing aluminum corrosion products and corrosion cells Y representing magnesium corrosion products are set.

4. The method according to claim 2, characterized in that, The settings determine the cell type, movement rules, and erosion rules, including: For corrosion cell T, representing corrosion products of aluminum, and corrosion cell Y, representing corrosion products of magnesium, the following movement rules are set: Corrosion cells T and Y exchange positions with solution cells W, corrosion cells O, or corrosion promoting cells C in the lattice closest to their center direction, until there are no solution cells W, corrosion cells O, or corrosion promoting cells C in the lattice below corrosion cells T and Y.

5. The method according to claim 2, characterized in that, The settings determine the cell type, movement rules, and erosion rules, including: For corrosion cell T, representing corrosion products of aluminum, and corrosion cell Y, representing corrosion products of magnesium, the following corrosion rules are set: Cell A, representing metallic aluminum within a zinc matrix, is transformed into corrosion cell T with a fixed probability, and corrosion cell T disappears with a fixed probability Pt. Cell M, representing metallic magnesium within a zinc matrix, is transformed into corrosion cell Y with a fixed probability. Corrosion cell Y then disappears with a fixed probability Py.

6. The method according to claim 5, characterized in that, After the steel wire cell model is formed by the moving corrosion rule and all cells, the following is also included: Running the steel wire cell model yields a simulated curve of corrosion depth changing over time. The simulated curve is compared with the theoretical curve of the corrosion kinetic model of the steel wire to determine the one fixed probability, the other fixed probability, and the fixed probabilities Pt and Py.

7. The method according to claim 1, characterized in that, The process of filling the gaps in the steel wires at the actual location of the bridge cable breakage with electrolyte film cells includes: Locate the actual location of the bridge cable breakage by tracing the gaps between the steel wires on the outer ring of the cable. The gap in the steel wire at the location is filled with solution cells W, corrosion-promoting cells C, and corrosion cells O in a certain proportion.

8. The method according to claim 1, characterized in that, The step of running the cable cell model according to the permeation rule to simulate the corrosion of the cable includes: Run the Lasso cell model according to the penetration rules; After running for a period of time, the number of remaining cells in each steel wire is calculated and converted into the steel wire weight loss rate and average corrosion depth.

9. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the bridge cable corrosion simulation method based on cellular automata as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, It stores a computer program that, when executed by a processor, implements the bridge cable corrosion simulation method based on cellular automata as described in any one of claims 1-8.

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