A coke drum strain digital twin analysis method and device based on cold spot effect

Abstract

This application discloses a digital twin analysis method and device for coke tower strain based on the cold point effect, relating to the field of coke tower stress analysis technology. The method includes: constructing a three-dimensional solid model based on point cloud data; constructing a structural digital twin model of the target coke tower based on the three-dimensional solid model; determining the region with the largest bulging on the target coke tower shell and continuously collecting the metal wall temperature-operation time curves at each monitoring point within the current working cycle; compiling the load steps of the cold point temperature loading history based on the metal wall temperature-operation time curves of the non-cold point region and the cold point region, and determining the digital twin temperature field of the target coke tower; obtaining the digital twin stress-strain analysis results through transient stress analysis in finite element software. This application performs digital twin simulation of the strain of coke tower equipment by considering the cold point effect of in-service coke towers and combining temperature monitoring statistics with finite element numerical analysis.

Description

Technical Field

[0001] This application relates to the field of coke tower stress analysis technology, and in particular to a digital twin analysis method and equipment for coke tower strain based on the cold point effect. Background Technology

[0002] The coking tower is a key piece of equipment in oil refineries for coke production. Its production process involves delayed coking, and its function is to provide a site for the thermal decomposition and synthesis of raw materials. The coking tower operates under harsh conditions, acting as a pressure vessel subjected to cyclic thermomechanical stress. Generally, a single operating cycle of a coking tower is 24 to 48 hours, and the process flow includes four stages: steam heating, oil filling, water cooling, and decapping and coking removal. During each production cycle, the temperature inside the tower cyclically changes from room temperature to 490°C. Frequent heating and cooling generate high cyclic thermal stress in the coking tower shell and at the connection between the shell and the skirt, making the coking tower highly susceptible to low-cycle thermomechanical fatigue damage, resulting in tower deformation and weld cracking. The American Petroleum Institute (API) conducted three surveys on the operating conditions of coking towers, finding that in cases of coking tower failure, approximately 61% of the towers experienced shell bulging deformation, and approximately 97% experienced circumferential cracking.

[0003] Further research by an American company suggests that during the coking stage of a coking tower, the gas flows irregularly and forms tree-like channels that extend randomly outwards from the central trunk of a tree. During the cooling stage, cold water flows along these channels to the high-temperature tower wall, rapidly cooling a specific area while the surrounding wall is covered by hot coke. This creates a cold spot effect, which is highly detrimental to the tower. The cold spot causes uneven axial and circumferential temperature distribution, leading to more significant thermal stress, sometimes exceeding the yield strength and inducing fatigue failure in the coking tower. Currently, the cold spot effect in coking towers is not adequately studied. Some studies have used finite element numerical simulations to estimate the thermal stress caused by the cold spot and calculate the fatigue life of the coking tower. However, due to the highly random temperature field distribution during the cooling stage of the coking tower, and the variations in each cycle, traditional simulation methods generally rely on experience and assume a large temperature difference between the cold spot and the surrounding metal to calculate conservative stress analysis results, which often deviate significantly from reality. Summary of the Invention

[0004] The purpose of this application is to provide a digital twin analysis method and equipment for coke tower strain based on the cold point effect. By considering the cold point effect of the in-service coke tower and combining temperature monitoring statistics and finite element numerical analysis, the strain of the coke tower equipment is simulated digitally, thereby accurately calculating the fatigue life of the coke tower.

[0005] To achieve the above objectives, this application provides the following solution: Firstly, this application provides a digital twin analysis method for strain in coke towers based on the cold point effect, including: A three-dimensional solid model is constructed based on the point cloud data of the target coke tower shell; the point cloud data of the target coke tower shell is obtained by performing an internal three-dimensional laser scan of the target coke tower during the shutdown period within the coke removal cycle; the target coke tower shell is an in-service coke tower with shell deformation. Finite element numerical analysis software was used to preprocess and mesh the three-dimensional solid model to obtain a structural digital twin model of the target coke tower. Based on the aforementioned structural digital twin model, the region with the largest bulge on the target coke tower shell is identified as the region of maximum deformation. Multiple monitoring points are evenly set up within the maximum deformation area to form a monitoring point array; Continuously collect the metal wall temperature-run time curve at each monitoring point within the current working cycle; Determine the metal wall temperature-operation time curves for the non-cold spot region and the metal wall temperature-operation time curves for the cold spot region from the multiple metal wall temperature-operation time curves described above; Based on the metal wall temperature-operation time curves of the non-cold point region and the metal wall temperature-operation time curves of the cold point region, load steps of the cold point temperature loading process are compiled for the digital twin model of the structure, and the convective heat transfer coefficients of different working stages in the non-cold point region and the cold point region of the target coke tower are determined iteratively; the working stages include preheating, coking, air blowing and water cooling. Using the convective heat transfer coefficients of the non-cold point region and cold point region of the target coke tower at different working stages after iteration as the current loading condition, the temperature field under the current loading condition is determined as the digital twin temperature field of the target coke tower in the current working cycle. The sequential thermal-structural coupling method is adopted, and the digital twin temperature field is used as the input load to apply internal pressure, gravity load and constraint conditions to the cold point model. The digital twin stress-strain analysis results of the target coke tower shell with operating time during the current working cycle are obtained by transient stress analysis in finite element software.

[0006] Optionally, the point cloud modeling software used to construct the 3D solid model is Geomagic Studio.

[0007] Optionally, the monitoring point array is a square array; The number of monitoring points in the monitoring point array is not less than 9; The spacing between monitoring points in the monitoring point array is not less than [amount missing]. ; in, The inner radius of the coke tower; The coke tower wall is thick.

[0008] Optionally, the metal wall temperature-operating time curves for non-cold point regions and cold point regions are determined from the multiple metal wall temperature-operating time curves, specifically including: Each adjacent monitoring point in the monitoring point array is considered as a monitoring point pair, and all monitoring point pairs in the monitoring point array are determined. Subtract the metal wall temperature-run time curve of the second monitoring point from the metal wall temperature-run time curve of the first monitoring point in each monitoring point pair to obtain the temperature difference-run time curve of different monitoring point pairs. Based on the temperature difference-run time curve, the maximum temperature difference for each monitoring point pair is read. The maximum value among all maximum temperature differences is determined as the maximum cold point temperature difference; The first monitoring point in the center of the monitoring point where the maximum cold point temperature difference is located is identified as the non-cold point. The second monitoring point, located at the center of the monitoring point where the maximum cold point temperature difference is determined, is the cold point. The metal wall temperature-operation time curve at the non-cold spot is determined as the metal wall temperature-operation time curve for the non-cold spot region. The metal wall temperature-running time curve at the cold spot is determined as the metal wall temperature-running time curve of the cold spot region.

[0009] Optionally, based on the metal wall temperature-operation time curves of the non-cold point region and the metal wall temperature-operation time curves of the cold point region, load steps of the cold point temperature loading process are compiled for the digital twin model of the structure, and the convective heat transfer coefficients of the non-cold point region and the cold point region of the target coke tower are iteratively determined at different operating stages, specifically including: The current work cycle is divided into multiple first time periods based on the abrupt change in the slope of the metal wall temperature-running time curve in the cold spot region; each first time period corresponds to a work stage. Initialize the convective heat transfer coefficient for each working stage in the cold spot region; The current work cycle is divided into multiple second time periods based on the abrupt change in the slope of the metal wall temperature-running time curve in the non-cold spot area; each second time period corresponds one-to-one with the work stage. Initialize the convective heat transfer coefficient for each working stage in the non-cold spot region; The temperature field was simulated using the convective heat transfer coefficients at different working stages in the non-cold point region and the cold point region as loading conditions, and the simulated curves of metal wall temperature-running time in the non-cold point region and the metal wall temperature-running time in the cold point region were obtained. Subtract the simulated curve of metal wall temperature-running time in the cold point area from the simulated curve of metal wall temperature-running time in the non-cold point area to obtain the simulated curve of temperature difference-running time. Adjust the convective heat transfer coefficients of the non-cold point region and the cold point region at different working stages, and return to the step "Simulate the temperature field with the convective heat transfer coefficients of the non-cold point region and the cold point region at different working stages as the loading condition, and obtain the simulation curves of metal wall temperature-running time in the non-cold point region and the metal wall temperature-running time in the cold point region" until the iteration end condition is met, and obtain the convective heat transfer coefficients of the non-cold point region and the cold point region at different working stages of the target coke tower. The iteration termination condition is as follows: the root mean square error between the simulated curve of metal wall temperature-running time in the non-cold point region and the simulated curve of metal wall temperature-running time in the non-cold point region is less than a preset value, and the root mean square error between the simulated curve of metal wall temperature-running time in the cold point region and the simulated curve of metal wall temperature-running time in the cold point region is less than a preset value, and the root mean square error between the simulated curve of temperature difference-running time and the simulated curve of temperature difference-running time is less than a preset value.

[0010] Optionally, the preset value is 5%.

[0011] Optionally, after employing a sequential thermal-structural coupling method, using the digital twin temperature field as the input load, applying internal pressure, gravity loads, and constraints to the cold point model, and obtaining the digital twin stress-strain analysis results of the target coke tower shell over the current working cycle through transient stress analysis in finite element software, the method further includes: The equivalent strain, plastic strain, and elastic strain values ​​of the cold spot region are obtained; these values ​​are used for fatigue life analysis of the target coke tower.

[0012] In a second aspect, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the coke tower strain digital twin analysis method based on the cold point effect as described above.

[0013] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method for digital twin analysis of coke tower strain based on cold point effect.

[0014] Fourthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described digital twin analysis method for coke tower strain based on cold point effect.

[0015] According to the specific embodiments provided in this application, the following technical effects are disclosed: This application provides a digital twin analysis method and device for coke tower strain based on the cold point effect. Combining three-dimensional laser scanning technology for the coke tower, the method directly converts the shell deformation point cloud data into a finite element model for stress-strain analysis considering the cold point effect. This more accurately reflects the stress-strain situation under extreme conditions combining the cold point effect and coke tower failure deformation. Furthermore, this application utilizes the obtained coke tower digital twin model, selecting the area with the largest expansion, and using a temperature sensor array deployed during shutdown for temperature monitoring. This yields the cold point temperature monitoring curve of the coke tower. Temperature simulations are performed in the cold point and non-cold point areas at the area with the largest expansion. The differences between the simulated temperature curve and the monitored temperature curve are compared and iterative calculations are performed to more accurately assess the remaining lifespan of the coke tower under extreme temperature conditions. The proposed digital twin model considering the cold point effect of the coke tower can also predict the strain distribution of the coke tower under different temperature differences between the cold point and non-cold point areas, thus better addressing cold point situations during temperature monitoring, guiding production units to adjust production cycles, and ensuring the safe operation of equipment. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of a digital twin analysis method for strain in a coke tower based on the cold point effect, as described in one embodiment of this application. Figure 2 This is a schematic diagram of the technical route in one embodiment of this application; Figure 3 In one embodiment of this application, point cloud data is converted into a three-dimensional solid model diagram; Figure 4 This is a digital twin model of the structure of a deformed coke tower with a shell, as shown in one embodiment of this application. Figure 5 This is a schematic diagram of the arrangement of temperature sensors in the severely deformed area of ​​the coke tower in one embodiment of this application; Figure 6 This diagram illustrates the iterative calculation steps of the digital twin temperature field for a cold point model in one embodiment of this application. Figure 7 This is a schematic diagram of the iterative calculation results of the monitored temperature field in one embodiment of this application; Figure 8 This is a schematic diagram of the simulated temperature field iterative calculation results in one embodiment of this application; Figure 9This is a digital twin temperature field cloud map of a cold spot model in one embodiment of this application; Figure 10 This is a schematic diagram of the equivalent elastic strain analysis results of the digital twin of the cold point model in one embodiment of this application; Figure 11 This is a schematic diagram of the equivalent stress analysis results of the digital twin of the cold spot model in one embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0020] In one exemplary embodiment, such as Figure 1 As shown, a digital twin analysis method for strain in a coke tower based on the cold point effect is provided, including: Step 101: Construct a 3D solid model based on the point cloud data of the target coke tower shell. The point cloud data of the target coke tower shell was obtained by performing an internal 3D laser scan of the target coke tower during a shutdown period within the coking cycle. The target coke tower shell is a deformed, in-service coke tower. The point cloud modeling software used to construct the 3D solid model is Geomagic Studio.

[0021] Step 102: Use finite element numerical analysis software to preprocess and mesh the three-dimensional solid model to obtain a digital twin model of the target coke tower structure.

[0022] Step 103: Based on the structural digital twin model, determine the area with the largest bulge on the target coke tower shell as the area of ​​maximum deformation.

[0023] Step 104: Evenly distribute multiple monitoring points within the maximum deformation area to form a monitoring point array. The monitoring point array is a square array. The number of monitoring points in the monitoring point array is no less than 9. The spacing between the monitoring points in the monitoring point array is no less than... Wherein, the inner radius of the coke tower is in mm; The thickness of the coke tower wall is in mm.

[0024] Step 105: Continuously collect the metal wall temperature-run time curve at each monitoring point within the current working cycle.

[0025] Step 106: Determine the metal wall temperature-running time curves for the non-cold spot region and the metal wall temperature-running time curves for the cold spot region from multiple metal wall temperature-running time curves.

[0026] Step 106 specifically includes: Step 106: Treat adjacent monitoring points in the monitoring point array as a monitoring point pair, and determine all monitoring point pairs in the monitoring point array.

[0027] Step 106-1: Subtract the metal wall temperature-running time curve of the second monitoring point from the metal wall temperature-running time curve of the first monitoring point in each monitoring point pair to obtain the temperature difference-running time curve of different monitoring point pairs.

[0028] Step 106-2: Based on the temperature difference-run time curve, read the maximum temperature difference for each monitoring point pair.

[0029] Step 106-3: Determine the maximum value among all maximum temperature differences as the maximum cold point temperature difference.

[0030] Step 106-4: Determine the first monitoring point in the monitoring point where the maximum cold point temperature difference is located as the non-cold point.

[0031] Step 106-5: Determine the second monitoring point as the cold point, based on the monitoring point where the maximum cold point temperature difference is located. Step 106-6: Determine the metal wall temperature-running time curve at the non-cold point as the metal wall temperature-running time curve for the non-cold point region.

[0032] Step 106-7: Determine the metal wall temperature-running time curve at the cold spot as the metal wall temperature-running time curve for the cold spot region.

[0033] Step 107: Based on the metal wall temperature-operation time curves of the non-cold point region and the cold point region, compile the load steps of the cold point temperature loading process for the structural digital twin model, and iteratively determine the convective heat transfer coefficients of different operating stages in the non-cold point and cold point regions of the target coke tower. The operating stages include preheating, coking, air blowing, and water cooling.

[0034] Step 107 specifically includes: Step 107-1: Divide the current work cycle into multiple first time periods based on the abrupt change in the slope of the metal wall temperature-running time curve in the cold spot area. Each first time period corresponds to a work stage.

[0035] Step 107-2: Initialize the convective heat transfer coefficient for each working stage in the cold spot region.

[0036] Step 107-3: Divide the current work cycle into multiple second time periods based on the abrupt change in the slope of the metal wall temperature-running time curve in the non-cold spot area. Each second time period corresponds to a work stage.

[0037] Step 107-4: Initialize the convective heat transfer coefficient for each working stage in the non-cold spot region.

[0038] Step 107-5: Simulate the temperature field using the convective heat transfer coefficients at different working stages in the non-cold point region and the cold point region as loading conditions, and obtain the simulated curves of metal wall temperature-running time in the non-cold point region and the metal wall temperature-running time in the cold point region.

[0039] Step 107-6: Subtract the simulated curve of metal wall temperature-running time in the cold point area from the simulated curve of metal wall temperature-running time in the non-cold point area to obtain the simulated curve of temperature difference-running time.

[0040] Step 107-7: Adjust the convective heat transfer coefficients of different working stages in the non-cold point region and the cold point region, and return to step 107-5 until the iteration termination condition is met, to obtain the convective heat transfer coefficients of different working stages in the non-cold point region and the cold point region of the target coke tower.

[0041] The iteration termination condition is as follows: the root mean square error (RMSE) between the simulated metal wall temperature-runtime curve and the simulated metal wall temperature-runtime curve in the non-cold point region is less than a preset value; the RMSE between the simulated metal wall temperature-runtime curve and the simulated metal wall temperature-runtime curve in the cold point region is less than a preset value; and the RMSE between the simulated temperature difference-runtime curve and the simulated temperature difference-runtime curve is less than a preset value. The preset value is 5%.

[0042] Step 108: Using the convective heat transfer coefficients of the non-cold point region and the cold point region of the target coke tower at different working stages after the iteration as the current loading condition, determine the temperature field under the current loading condition as the digital twin temperature field of the target coke tower in the current working cycle.

[0043] Step 109: Using the sequential thermal-structural coupling method, the digital twin temperature field is used as the input load to apply internal pressure, gravity load and constraint conditions to the cold point model. The digital twin stress-strain analysis results of the target coke tower shell with operating time are obtained through transient stress analysis in the finite element software.

[0044] Step 1010: Obtain the equivalent strain, plastic strain, and elastic strain values ​​of the cold spot region. The equivalent strain, plastic strain, and elastic strain values ​​of the cold spot region are used for fatigue life analysis of the target coke tower.

[0045] Below, we take a coking tower that has been in service for more than 20 years as the target coking tower and perform strain analysis calculations considering the cold point effect. Figure 2 The specific implementation method is as follows: Step S1: During the coking tower shutdown period, a 3D laser scan is performed on the interior of the coking tower. The 3D laser scan results are processed to obtain point cloud data of the inner surface of the coking tower shell. The areas with the most severe bulging and deformation of the coking tower are analyzed. Then, using professional modeling software, such as Geomagic Studio, the point cloud data is converted into a 3D solid model, including steps such as constructing contour lines, surfaces, and grids. Finally, a 3D solid model that can be directly read by finite element software is formed, such as... Figure 3 As shown.

[0046] Step S2: Import the 3D solid model into professional finite element numerical analysis software, and preprocess and mesh the solid model to obtain a structural digital twin model of the deformable coke tower, such as... Figure 4 .

[0047] Step S3: Based on the digital twin model, select the area with the largest bulge, and use a temperature sensor array deployed during downtime for temperature monitoring. The temperature sensors should be arranged in a square array, with no fewer than 9 sensors and a spacing of no less than [missing information]. For the layout method, see Figure 5 .

[0048] Step S4: Continuously collect monitoring data from the coke tower temperature sensor array for multiple working cycles (generally 36h-48h) to obtain the curve showing the change in metal wall temperature at sensor i as a function of operating time within that working cycle. T i (t) .

[0049] Step S5: Based on the metal wall temperature monitoring data and curves of each temperature sensor, calculate the relationship curve Δ between the monitored temperature difference and the running time for each pair of adjacent sensors. T i,j (t)、 Δ T i,m (t)… Δ T p,q (t) The maximum temperature difference appearing in the temperature difference curve of each pair of sensors is recorded as Δ. T i,j 、 Δ T i,m … Δ T p,q .

[0050] Step S6: Select Δ T i,j 、 Δ Ti,m … Δ T p,q The largest of the three is the maximum cold point temperature difference, i.e., Δ. T cold = max{Δ T i,j 、 Δ T i,m … Δ T p,q}, press to display Δ T cold The adjacent sensor metal wall temperature monitoring curves were used to simulate cold spots.

[0051] The load steps of the cold point temperature loading process are compiled for the digital twin finite element model of the deformed coke tower considering the cold point effect. The temperature of the tower wall changes with time in different working stages such as preheating, coking, blowing, and water cooling in the non-cold point region and the cold point region, so as to simulate the actual wall temperature state of the actual coke tower.

[0052] The load step setting method is as follows: 1) Analyze long-term temperature monitoring data and compare it with the statistical data to find the temperature change curve of a random cold point. The temperature change curve of a random cold point is defined in the cold point region. Based on the occurrence of Δ... T cold Adjacent sensors (by sensor) i and sensors j (For example) Metal wall temperature monitoring curve in non-cold spot area T i (t) and the metal wall temperature monitoring curve in the cold spot area T j (t) During the preheating and blowing stages, the temperature in the cold spot area generally changes linearly with time. However, during the coking stage, the cold spot area cools rapidly due to the action of cold water. Therefore, the entire cycle is divided into sections based on the slope change. s There are several different stages, and these 's' stages correspond to different working stages such as preheating, coking, air blowing, and water cooling. Starting from the first stage, the starting time is determined by the temperature monitoring curve. t 0,j During the end of the preheating phase t 1,j， Determine the loading time range for the first stage ( t 0,j ，t 1,j The second stage is based on... t 1,jThe start time, t 2,j The end time is calculated accordingly. The time period for the entire cycle in the non-cold spot region is consistent with that in the cold spot region. The results of the cycle division for both the cold spot and non-cold spot regions are the same.

[0053] 2) The temperature changes of the non-cold point area and the cold point area are consistent during the preheating and blowing stages at the beginning of the cycle. During the coking stage, the cold point area cools rapidly due to the cold point effect, creating a temperature difference with the non-cold point area. Therefore, the convective heat transfer coefficients of the non-cold point area and the cold point area are set for different stages of their respective stages. h s,i and h s,j .

[0054] 3) Load this load step program in the finite element software to obtain the temperature field distribution on the deformed model considering the cold point effect.

[0055] Step S7: After completing the finite element calculation, compare the simulated and actual monitored values ​​of the tower wall temperature in the non-cold point region and the cold point region, as well as the simulated and actual temperature differences between the two regions. Adjust the convective heat transfer coefficients of the non-cold point region and the cold point region based on the actual monitored temperature curves. h s,i and h s,j Among them, the first i The sensor recorded the first s Simulated values ​​of temperature change rate in stages ΔT s,i-FEA (t) / Δt Compared with measured value ΔT s,i (t) / Δt If the value is low, then increase the convective heat transfer coefficient within that stage and height range. h s,i ， This makes the temperature gradient over time closer to the measured value; j The sensor recorded the first s Simulated values ​​of temperature change rate in stages ΔT s,j-FEA (t) / Δt Compared with measured value ΔT s,j (t) / Δt If the value is low, then increase the convective heat transfer coefficient within that stage and height range. h s,j ， This makes the temperature gradient over time closer to the measured value.

[0056] Finally, through iterative calculations, the simulated and measured rates of temperature change for each sensor at each stage of the simulation process, as well as the simulated final temperature at each stage, were determined. and The measured root mean square error is less than 5%, so the temperature field under this loading condition is selected as the digital twin temperature field for this working cycle. The iterative calculation steps for the digital twin temperature field of the cold point model are as follows: Figure 6 The results of the digital twin temperature field calculation for the cold point model are as follows: Figures 7 to 9 .

[0057] Step S8: The finite element analysis adopts the sequential thermal-structural coupling method, in which the thermal load is the temperature field obtained in the final iteration of step S7 as the input load. At the same time, internal pressure, gravity load and constraint conditions are applied to the cold point model. The digital twin stress-strain analysis results of the deformable shell over time during the working cycle are obtained through transient stress analysis in the finite element software.

[0058] The sequential thermal-structural coupling analysis method first performs a thermal analysis of the digital twin temperature field, then adds the obtained digital twin temperature field as a volume load to the structural analysis model, along with other constraints of the structural analysis. This method is a mature approach for solving stress and strain results in commercial simulation software.

[0059] The internal pressure is calculated as the average pressure monitored in the company's DCS system during the working cycle.

[0060] Gravity loads and constraints are applied according to the actual conditions of the coke tower, which is a mature operating method for stress analysis of pressure vessels in commercial simulation software.

[0061] Step S9: Obtain the stress-strain contour plot using finite element software, select and set the equivalent strain, plastic strain, and elastic strain values ​​for the cold point region, and use them for fatigue life analysis of the coke tower. The results of the digital twin stress-strain analysis of the cold point model are as follows: Figure 10 and Figure 11 .

[0062] Step S10: When performing three-dimensional laser scanning monitoring on another coke tower, repeat steps S1-S2 above to obtain an updated digital twin model of the deformed coke tower structure; when calculating a new working cycle, repeat steps S3-S7 above to calculate the updated digital twin temperature field of the coke tower using the temperature monitoring data of the new working cycle; for the new load life assessment of the coke tower, repeat steps S8-S9 above to finally obtain the stress-strain analysis results of the digital twin of the coke tower for the new working cycle.

[0063] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals via a network connection.

[0064] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0065] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0066] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0067] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0068] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0069] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0070] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0071] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A digital twin analysis method for strain in a coke tower based on the cold point effect, characterized in that, include: A three-dimensional solid model is constructed based on the point cloud data of the target coke tower shell; The point cloud data of the target coke tower shell was obtained by performing an internal three-dimensional laser scan of the target coke tower during the shutdown period within the coke removal cycle. The target coke tower shell is an in-service coke tower with a deformed shell; Finite element numerical analysis software was used to preprocess and mesh the three-dimensional solid model to obtain a structural digital twin model of the target coke tower. Based on the aforementioned structural digital twin model, the region with the largest bulge on the target coke tower shell is identified as the region of maximum deformation. Multiple monitoring points are evenly set up within the maximum deformation area to form a monitoring point array; Continuously collect the metal wall temperature-run time curve at each monitoring point within the current working cycle; Determine the metal wall temperature-operation time curves for the non-cold spot region and the metal wall temperature-operation time curves for the cold spot region from the multiple metal wall temperature-operation time curves described above; Based on the metal wall temperature-operation time curves of the non-cold point region and the metal wall temperature-operation time curves of the cold point region, load steps of the cold point temperature loading process are compiled for the digital twin model of the structure, and the convective heat transfer coefficients of different working stages in the non-cold point region and the cold point region of the target coke tower are determined iteratively; the working stages include preheating, coking, air blowing and water cooling. Using the convective heat transfer coefficients of the non-cold point region and cold point region of the target coke tower at different working stages after iteration as the current loading condition, the temperature field under the current loading condition is determined as the digital twin temperature field of the target coke tower in the current working cycle. The sequential thermal-structural coupling method is adopted, and the digital twin temperature field is used as the input load to apply internal pressure, gravity load and constraint conditions to the cold point model. The digital twin stress-strain analysis results of the target coke tower shell with operating time during the current working cycle are obtained by transient stress analysis in finite element software.

2. The digital twin analysis method for coke tower strain based on cold point effect according to claim 1, characterized in that, The point cloud modeling software used to construct the 3D solid model is Geomagic Studio.

3. The digital twin analysis method for coke tower strain based on cold point effect according to claim 1, characterized in that, The monitoring point array is a square array; The number of monitoring points in the monitoring point array is not less than 9; The spacing between monitoring points in the monitoring point array is not less than [amount missing]. ; in, The inner radius of the coke tower; The coke tower wall is thick.

4. The digital twin analysis method for coke tower strain based on cold point effect according to claim 1, characterized in that, Determine the metal wall temperature-operation time curves for the non-cold spot region and the metal wall temperature-operation time curves for the cold spot region from multiple metal wall temperature-operation time curves, specifically including: Each adjacent monitoring point in the monitoring point array is considered as a monitoring point pair, and all monitoring point pairs in the monitoring point array are determined. Subtract the metal wall temperature-run time curve of the second monitoring point from the metal wall temperature-run time curve of the first monitoring point in each monitoring point pair to obtain the temperature difference-run time curve of different monitoring point pairs. Based on the temperature difference-run time curve, the maximum temperature difference for each monitoring point pair is read. The maximum value among all maximum temperature differences is determined as the maximum cold point temperature difference; The first monitoring point in the center of the monitoring point where the maximum cold point temperature difference is located is identified as the non-cold point. The second monitoring point, located at the center of the monitoring point where the maximum cold point temperature difference is determined, is the cold point. The metal wall temperature-operation time curve at the non-cold spot is determined as the metal wall temperature-operation time curve for the non-cold spot region. The metal wall temperature-running time curve at the cold spot is determined as the metal wall temperature-running time curve of the cold spot region.

5. The digital twin analysis method for coke tower strain based on cold point effect according to claim 4, characterized in that, Based on the metal wall temperature-operation time curves of the non-cold point region and the cold point region, the load steps of the cold point temperature loading process are compiled for the digital twin model of the structure. The convective heat transfer coefficients of the non-cold point region and the cold point region of the target coke tower at different operating stages are iteratively determined, specifically including: The current work cycle is divided into multiple first time periods based on the abrupt change in the slope of the metal wall temperature-running time curve in the cold spot region; each first time period corresponds to a work stage. Initialize the convective heat transfer coefficient for each working stage in the cold spot region; The current work cycle is divided into multiple second time periods based on the abrupt change in the slope of the metal wall temperature-running time curve in the non-cold spot area; each second time period corresponds one-to-one with the work stage. Initialize the convective heat transfer coefficient for each working stage in the non-cold spot region; The temperature field was simulated using the convective heat transfer coefficients at different working stages in the non-cold point region and the cold point region as loading conditions, and the simulated curves of metal wall temperature-running time in the non-cold point region and the metal wall temperature-running time in the cold point region were obtained. Subtract the simulated curve of metal wall temperature-running time in the cold point area from the simulated curve of metal wall temperature-running time in the non-cold point area to obtain the simulated curve of temperature difference-running time. Adjust the convective heat transfer coefficients of the non-cold point region and the cold point region at different working stages, and return to the step "Simulate the temperature field with the convective heat transfer coefficients of the non-cold point region and the cold point region at different working stages as the loading condition, and obtain the simulation curves of metal wall temperature-running time in the non-cold point region and the metal wall temperature-running time in the cold point region" until the iteration end condition is met, and obtain the convective heat transfer coefficients of the non-cold point region and the cold point region at different working stages of the target coke tower. The iteration termination condition is as follows: the root mean square error between the simulated curve of metal wall temperature-running time in the non-cold point region and the simulated curve of metal wall temperature-running time in the non-cold point region is less than a preset value, and the root mean square error between the simulated curve of metal wall temperature-running time in the cold point region and the simulated curve of metal wall temperature-running time in the cold point region is less than a preset value, and the root mean square error between the simulated curve of temperature difference-running time and the simulated curve of temperature difference-running time is less than a preset value.

6. The digital twin analysis method for coke tower strain based on cold point effect according to claim 5, characterized in that, The preset value is 5%.

7. The digital twin analysis method for strain of coke tower based on cold point effect according to claim 1, characterized in that, After employing a sequential thermal-structural coupling method, using the digital twin temperature field as the input load, applying internal pressure, gravity loads, and constraints to the cold point model, and obtaining the digital twin stress-strain analysis results of the target coke tower shell over the current working cycle through transient stress analysis in finite element software, the process also includes: The equivalent strain, plastic strain, and elastic strain values ​​of the cold spot region are obtained; these values ​​are used for fatigue life analysis of the target coke tower.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the digital twin analysis method for coke tower strain based on the cold point effect as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the digital twin analysis method for coke tower strain based on the cold point effect as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the digital twin analysis method for coke tower strain based on the cold point effect as described in any one of claims 1-7.

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