Artificial stratum freezing engineering monitoring and early warning method and system based on digital twinning

Abstract

The invention discloses an artificial stratum freezing engineering monitoring and early warning method and system based on digital twinning, and relates to the field of underground engineering. According to the method, the three-dimensional geometric structure of an artificial stratum freezing engineering site, freezing pipe arrangement, the preset temperature of freezing liquid and stratum physical and mechanical parameters are calculated according to the three-dimensional geometric structure, the freezing pipe arrangement, the preset temperature of freezing liquid and the stratum physical and mechanical parameters; the stratum thermophysical parameters serve as the actual situation of the freezing project and are input into the numerical model, and prediction data of all positions of an artificial stratum freezing project site within preset time are output; determining the numerical model as a trained numerical model based on the preset value, the prediction data and the real temperature of the rock-soil body monitored at each temperature measurement point in real time; based on the trained numerical model, determining target prediction data of each position of the artificial stratum freezing engineering site within a preset time; based on the target prediction data, determining a freezing result of the on-site artificial stratum freezing project; and according to the freezing result and a preset deformation standard, determining an abnormal freezing result and carrying out early warning. And the monitoring and early warning efficiency of the freezing effect is improved.

Description

Technical Field

[0001] The present application relates to the field of underground engineering technology, and in particular to a monitoring and early warning method and system for artificial ground freezing engineering based on digital twins. Background Art

[0002] Artificial ground freezing is a temporary reinforcement technology used in underground engineering construction. It drives freezing pipes into the ground, circulates low-temperature freezing fluid and freezes loose water-bearing rock and soil layers to form a freezing curtain, which increases the strength and stability of the ground and isolates groundwater. Under the reinforcement of the freezing curtain, underground engineering construction or emergency repair work can be carried out safely and quickly. Artificial ground freezing is highly efficient, flexible, environmentally friendly and pollution-free. It has been widely used in subway, deep foundation pit, mine construction and other projects.

[0003] However, due to the limited accuracy of engineering surveys, the properties of rock, soil and groundwater in the project site are inevitably different from the survey data, resulting in possible deviations between the actual freezing effect and the design plan. In order to meet these challenges, on the one hand, it is necessary to make real-time adjustments to the design plan based on the temperature data detected at the site of the artificial ground freezing project, but it is often difficult to deploy sensors at the site of the artificial ground freezing project, and analyzing the real-time updated temperature data also requires a lot of manpower costs, and whether temperature anomalies can be found is highly dependent on the experience of technicians; on the other hand, the freezing effect of the artificial ground cannot be fully reflected based only on the temperature data of the on-site temperature measurement points, and the prediction accuracy of the freezing effect and the monitoring and early warning efficiency are low.

[0004] In order to address the problems of limited survey accuracy and difficult on-site monitoring in artificial ground freezing projects, a monitoring and early warning method for artificial ground freezing projects based on digital twins is urgently needed to improve the prediction accuracy of freezing effects and the efficiency of monitoring and early warning, and ensure that the freezing effects meet the design requirements. Summary of the invention

[0005] The purpose of this application is to provide a monitoring and early warning method and system for artificial ground freezing projects based on digital twins, which can solve the problems of low prediction accuracy of freezing effects and low monitoring and early warning efficiency in the prior art.

[0006] To achieve the above objectives, this application provides the following solutions.

[0007] In the first aspect, the present application provides a monitoring and early warning method for artificial stratum freezing projects based on digital twins, including: constructing a three-dimensional geometric structure of the artificial stratum freezing project site; taking the three-dimensional geometric structure, freezing pipe arrangement, preset temperature of the freezing liquid, stratum physical and mechanical parameters and stratum thermal and physical parameters as the actual situation of the freezing project, inputting the numerical model, and outputting the predicted data of each location of the artificial stratum freezing project site within a preset time; the predicted data includes the predicted temperature, predicted stress and predicted deformation of the rock and soil body; the freezing pipe arrangement includes the number, position, spacing and depth of the freezing pipe arrangement; the stratum physical and mechanical parameters include the elastic modulus and Poisson's ratio of the rock and soil body ; The formation thermal physical property parameters include thermal conductivity and specific heat capacity of the rock and soil; based on the preset value, the predicted data and the actual temperature of the rock and soil monitored in real time at each temperature measuring point, determine that the numerical model is a trained numerical model; based on the trained numerical model, determine the target prediction data of each location on the site of the artificial formation freezing project within a preset time; the target prediction data include the target predicted temperature, target predicted stress and target predicted deformation of the rock and soil; based on the target prediction data, determine the freezing result of the on-site artificial formation freezing project; according to the freezing result and the preset deformation standard, determine the abnormal freezing result, and issue a danger warning based on the abnormal freezing result.

[0008] In the second aspect, the present application provides an artificial stratum freezing project monitoring and early warning system based on digital twins, including: a data transmission module and a digital twin computing module; the data transmission module includes a cloud server; the cloud server is connected to the artificial stratum freezing project on-site temperature measurement module and the artificial stratum freezing project on-site monitoring and early warning module; the digital twin computing module includes a digital twin parameter optimization calculation program; the digital twin computing module is used to output the target prediction data of each location of the artificial stratum freezing project site within a preset time based on the digital twin parameter optimization calculation program; the data transmission module is used to transmit data between the artificial stratum freezing project on-site temperature measurement module, the artificial stratum freezing project on-site monitoring and early warning module and the digital twin parameter optimization calculation program based on the cloud server; the artificial stratum freezing project on-site temperature measurement module is used to output the real temperature of each temperature measuring point of the artificial stratum freezing project; the artificial stratum freezing project on-site monitoring and early warning module is used to display, monitor and warn the real temperature of the rock and soil body monitored in real time at each temperature measuring point output by the artificial stratum freezing project on-site temperature measurement module and the target prediction data of each location of the artificial stratum freezing project site within a preset time output by the digital twin computing module.

[0009] According to the specific embodiments provided in this application, this application discloses the following technical effects.

[0010] The present application constructs a three-dimensional geometric structure of the site of the artificial stratum freezing project, and takes the three-dimensional geometric structure, freezing pipe arrangement, preset temperature of the freezing liquid, stratum physical and mechanical parameters and stratum thermal physical parameters as the actual situation of the freezing project and inputs the numerical model, thereby avoiding the situation in which the rock and soil and groundwater properties in the project site are different from the survey data in the prior art, resulting in inaccurate prediction data output by the numerical model. Then, the trained numerical model is obtained by predicting the predicted temperature of the rock and soil at each temperature measuring point in the prediction data, the preset value and the real temperature of the rock and soil monitored in real time at each temperature measuring point. Based on the trained numerical model, accurate target prediction data of each location of the site of the artificial stratum freezing project within the preset time is output; and the target prediction data includes the target predicted temperature, target predicted stress and target predicted deformation of the rock and soil at each temperature measuring point. Based on the predicted data, the freezing result of the on-site artificial stratum freezing project is determined, which improves the prediction accuracy of the freezing effect compared with the problem of low accuracy of predicting the freezing result based on temperature data in the prior art. At the same time, based on the trained numerical model, it can be achieved that no sensors are deployed on the site of the artificial stratum freezing project, and accurate temperature can still be predicted, reducing labor costs and technical dependence. Furthermore, according to the freezing results and the preset deformation standard, the abnormal freezing results are determined, and a danger warning is issued based on the abnormal freezing results, thereby improving the monitoring and early warning efficiency of the freezing effect and ensuring that the freezing effect meets the design requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0012] Figure 1 A flow chart of a method for monitoring and early warning of artificial ground freezing engineering based on digital twins provided in an embodiment of the present application.

[0013] Figure 2 This is a structural schematic diagram of an artificial ground freezing engineering monitoring and early warning system based on digital twins provided in an embodiment of the present application.

[0014] Figure 3 This is a plan layout diagram of freezing pipes and temperature measuring holes in an artificial ground freezing project provided in an embodiment of the present application. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0016] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0017] like Figure 1 As shown, the present application provides a monitoring and early warning method for artificial ground freezing engineering based on digital twins, including steps 101 to 106.

[0018] Step 101: Construct a three-dimensional geometric structure of the artificial ground freezing project site.

[0019] In some embodiments, step 101 specifically includes: constructing the three-dimensional geometric structure of the artificial ground freezing project site according to the on-site topography, underground structures and stratum distribution of the artificial ground freezing project; the underground structures include the spatial position and geometric shape of buildings, tunnels or pipelines; the stratum distribution includes the thickness, depth and spatial distribution of different rock and soil bodies.

[0020] Step 102: The three-dimensional geometric structure, freezing pipe arrangement, preset temperature of the freezing liquid, formation physical and mechanical parameters and formation thermal physical parameters are used as the actual situation of the freezing project, input into the numerical model, and output the predicted data of each location of the artificial formation freezing project site within the preset time; the predicted data includes the predicted temperature, predicted stress and predicted deformation of the rock and soil body; the freezing pipe arrangement includes the number, position, spacing and depth of the freezing pipe arrangement; the formation physical and mechanical parameters include the elastic modulus of the rock and soil body; the formation thermal physical parameters include the thermal conductivity and specific heat capacity of the rock and soil body; the numerical model is constructed based on the digital twin computing module, and the digital twin computing module is installed with numerical simulation software, and the numerical simulation software is used to construct the numerical model based on the digital twin technology.

[0021] Among them, the three-dimensional geometric structure of the artificial ground freezing project site is constructed, and the three-dimensional geometric structure, freezing pipe arrangement, preset temperature of the freezing liquid, formation physical and mechanical parameters and formation thermal physical parameters are used as the actual situation of the freezing project as the input of the numerical model, avoiding the situation in the existing technology that the properties of the rock and soil and groundwater in the engineering site are different from the survey data, resulting in inaccurate prediction data output by the numerical model.

[0022] Among them, the numerical model is a three-dimensional water-heat-mechanical coupled numerical model.

[0023] Step 103: Based on the preset value, the predicted data and the actual temperature of the rock and soil body monitored in real time at each temperature measuring point, determine that the numerical model is a trained numerical model.

[0024] In some embodiments, step 103 specifically includes: extracting the predicted temperature of the rock and soil body corresponding to each temperature measuring point in the predicted data; comparing whether the difference between the predicted temperature and the actual temperature is less than the preset value, and obtaining a first result; if the first result is yes, determining that the numerical model is the trained numerical model; if the first result is no, returning to step 102 until the difference is less than the preset value.

[0025] Among them, the real temperature of the rock and soil at the engineering site is collected in real time by the temperature sensors at each temperature measuring point, and transmitted to the numerical model in real time. The numerical model can be adjusted using the real temperature updated in real time, which improves the reliability of the numerical model calculation. At the same time, the actual situation of the frozen project is input into the numerical model, and the parameters to be optimized in the numerical model are adjusted using the optimization algorithm. The parameters to be optimized are the physical and mechanical parameters of the formation and the thermal physical parameters of the formation. Finally, the training of the numerical model is realized.

[0026] Step 104: Based on the trained numerical model, target prediction data of each location on the artificial ground freezing project site within a preset time is determined; the target prediction data includes a target prediction temperature, a target prediction stress and a target prediction deformation of the rock and soil body.

[0027] Step 105: Determine the freezing result of the on-site artificial ground freezing project based on the target prediction data.

[0028] In some embodiments, step 105 specifically includes: determining the temperature field of the on-site artificial stratum freezing project based on the target predicted temperature; determining the stratum frost heave force of the on-site artificial stratum freezing project based on the target predicted stress; determining the stratum frost heave amount of the on-site artificial stratum freezing project based on the target predicted deformation; the freezing result includes the temperature field, the stratum frost heave force and the stratum frost heave amount.

[0029] Step 106: Determine an abnormal freezing result according to the freezing result and a preset deformation standard, and issue a danger warning based on the abnormal freezing result.

[0030] In some embodiments, step 106 specifically includes: comparing whether the difference between the frost heave amount of the formation and the preset deformation standard is greater than a preset threshold value, and obtaining a second result; if the second result is yes, determining that the freezing result is an abnormal freezing result, and issuing a danger warning based on the abnormal freezing result; if the second result is no, determining that the freezing result is a normal freezing result.

[0031] This application first optimizes the parameters to be optimized (physical and mechanical parameters of the formation and thermal and physical parameters of the formation) of the numerical model by measuring the actual temperature of the temperature measuring hole, ensuring that the predicted temperature of the numerical model at each temperature measuring point is consistent with the measured actual temperature, and then extracts the temperature of other locations at the freezing site predicted by the numerical model, so that a more accurate temperature can be obtained even when it is difficult to deploy the sensor position. And the entire process is automatically operated through computer programming, and no manual monitoring by personnel is required, which reduces labor costs and technical dependence. Furthermore, by predicting the target predicted temperature, target predicted stress, target predicted deformation and other indicators at each location and time of the engineering site within a preset time in the future through the trained numerical model, accurate predictions can be made on the development trend and distribution of the temperature field, frost heave force, and frost heave amount. This application has the following beneficial effects: (1) The numerical model is relatively simple, which greatly reduces the workload of numerical modeling.

[0032] (2) The numerical model is adjusted by using real-time measured field temperature data, and the calculation results of the numerical model are reliable.

[0033] (3) The calculation results of the reliable trained numerical model facilitate the observation of the freezing effect at the difficult-to-monitor locations on the freezing project site.

[0034] (4) The development of the on-site freezing project can be calculated in real time through numerical models, which is conducive to early warning of engineering hazards.

[0035] Reference Figure 2, a monitoring and early warning system for artificial stratum freezing projects based on digital twins. The monitoring and early warning system for artificial stratum freezing projects based on digital twins includes: a data transmission module 1 and a digital twin computing module 2; the data transmission module 1 includes a cloud server 11; the cloud server 11 is connected to an on-site temperature measurement module 3 for artificial stratum freezing projects and an on-site monitoring and early warning module 4 for artificial stratum freezing projects; the digital twin computing module 2 includes a digital twin parameter optimization computing program 21; the digital twin computing module 2 is used to output target prediction data for each location of the artificial stratum freezing project site within a preset time based on the digital twin parameter optimization computing program 21; the data transmission module 1 is used to calculate the on-site temperature measurement module 3 and the artificial stratum freezing project site monitoring and early warning module 4 based on the cloud server 11 The on-site monitoring and early warning module 4 of the stratum freezing project transmits data with the digital twin parameter optimization calculation program 21; the on-site temperature measurement module 3 of the artificial stratum freezing project is used to output the real temperature of each temperature measuring point of the artificial stratum freezing project; the on-site monitoring and early warning module 4 of the artificial stratum freezing project is used to display, monitor and warn the real temperature of the rock and soil body monitored in real time at each temperature measuring point output by the on-site temperature measurement module of the artificial stratum freezing project and the target prediction data of each location of the artificial stratum freezing project site within a preset time output by the digital twin calculation module 2; the digital twin calculation module 2 is installed with numerical simulation software 22, and the numerical simulation software 22 is used to build a numerical model based on digital twin technology.

[0036] Among them, each time the digital twin parameter optimization calculation program 21 receives the real temperature of the new on-site temperature sensor 31, it automatically starts to calculate and continuously updates the simulation model until the difference between the simulation model calculation result and the predicted temperature is less than the preset value.

[0037] In some embodiments, the artificial ground freezing engineering on-site temperature measurement module 3 includes a plurality of temperature measurement holes, each of which is provided with a plurality of temperature measurement points at different depths, and each of the temperature measurement points is installed with a temperature sensor 31 .

[0038] In some embodiments, each temperature sensor 31 is connected to an on-site temperature collection station 32 .

[0039] The on-site temperature collection station 32 is connected to the on-site monitoring and early warning module 4 for artificial ground freezing engineering; the on-site temperature collection station 32 is used to output the real temperature of the rock and soil body monitored in real time at each temperature measuring point to the on-site monitoring and early warning module 4 for artificial ground freezing engineering.

[0040] Among them, the digital twin computing module 2 includes a supercomputer with high-performance computing capabilities, in which numerical simulation software 22 is installed. The numerical simulation software 22 is used to build a numerical model based on digital twin technology; the digital twin parameter optimization calculation program 21 is used to optimize the formation physical and mechanical parameters and formation thermal physical parameters of the numerical model.

[0041] Specifically, the Digital Twin Parameter Optimization Calculation Program (DTP-OC) is an intelligent system that combines numerical simulation, real-time data acquisition and optimization algorithms. It aims to adjust the key parameters of the simulation model through continuous iteration to ensure that it can accurately reflect the actual engineering situation. Among them, the key parameters include the physical and mechanical parameters of the formation and the thermal and physical parameters of the formation.

[0042] Reference Figure 3 , take an artificial ground freezing project with two layers of ground, 64 freezing pipes, and a square freezing area as an example, where A is the freezing pipe, B is the artificial ground freezing project, and C is the temperature measuring hole. The temperature measuring holes are distributed at the boundary and center of the freezing curtain, and the hole depth is greater than the depth of the freezing area. The temperature measuring points are spaced 2~5m apart within the depth range of the freezing area (i.e. the site of the artificial ground freezing project), and 3~8m apart outside the depth range of the freezing area.

[0043] The on-site temperature collection station collects the real temperature of all temperature sensors at fixed intervals, and uploads all the real temperatures and collection times to the cloud server 11 via the Internet. The real temperature is the temperature at different depths in each temperature measuring hole after freezing begins.

[0044] In some embodiments, the data transmission module 1 further includes a numerical simulation software interface 12 .

[0045] The numerical simulation software interface 12 is used for data transmission between the digital twin parameter optimization calculation program 21 and the numerical simulation software 22 .

[0046] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A monitoring and early warning method for artificial ground freezing engineering based on digital twins, characterized in that: include: Construct the three-dimensional geometric structure of the artificial ground freezing project site; The three-dimensional geometric structure, freezing pipe arrangement, preset temperature of freezing liquid, physical and mechanical parameters of formation and thermal physical parameters of formation are used as the actual situation of freezing engineering, input into the numerical model, and output the prediction data of each location of the artificial formation freezing engineering site within the preset time; the prediction data includes the predicted temperature, predicted stress and predicted deformation of the rock and soil body; the freezing pipe arrangement includes the number, position, spacing and depth of the freezing pipe arrangement; the physical and mechanical parameters of formation include the elastic modulus and Poisson's ratio of the rock and soil body; the thermal physical parameters of formation include the thermal conductivity and specific heat capacity of the rock and soil body; The numerical model is constructed based on a digital twin computing module, and the digital twin computing module is installed with numerical simulation software, and the numerical simulation software is used to construct a numerical model based on digital twin technology; Determining that the numerical model is a trained numerical model based on a preset value, the predicted data, and the actual temperature of the rock and soil body monitored in real time at each temperature measuring point; Based on the trained numerical model, target prediction data of each location on the artificial ground freezing project site within a preset time is determined; the target prediction data includes target prediction temperature, target prediction stress and target prediction deformation of the rock and soil body; Determining the freezing result of the artificial ground freezing project site based on the target prediction data; According to the freezing result and the preset deformation standard, an abnormal freezing result is determined, and a danger warning is issued based on the abnormal freezing result.

2. The method for monitoring and early warning of artificial ground freezing engineering based on digital twin according to claim 1 is characterized in that: Based on the preset value, the predicted data and the actual temperature of the rock and soil body monitored in real time at each temperature measuring point, determining that the numerical model is a trained numerical model specifically includes: Extracting the predicted temperature of the rock and soil body corresponding to each temperature measuring point in the predicted data; Comparing whether the difference between the predicted temperature and the actual temperature is less than the preset value, and obtaining a first result; If the first result is yes, determining that the numerical model is the trained numerical model; If the first result is no, return to the step of "taking the three-dimensional geometric structure, freezing pipe arrangement, preset temperature of the freezing liquid, formation physical and mechanical parameters and formation thermal physical parameters as the actual situation of the freezing project, inputting the numerical model, and outputting the predicted data of each location on the site of the artificial formation freezing project within the preset time" until the difference is less than the preset value.

3. The method for monitoring and early warning of artificial ground freezing engineering based on digital twin according to claim 1 is characterized in that: Determining the freezing result of the on-site artificial ground freezing project based on the target prediction data specifically includes: Determining the temperature field of the on-site artificial ground freezing project according to the target predicted temperature; Determining the ground frost heave force of the on-site artificial ground freezing project according to the target predicted stress; According to the target predicted deformation, the ground frost heave amount of the on-site artificial ground freezing project is determined; the freezing result includes the temperature field, the ground frost heave force and the ground frost heave amount.

4. The method for monitoring and early warning of artificial ground freezing engineering based on digital twin according to claim 3 is characterized in that: According to the freezing result and the preset deformation standard, determining an abnormal freezing result, and performing a danger warning based on the abnormal freezing result, specifically includes: Comparing the difference between the frost heave amount of the stratum and the preset deformation standard to determine whether it is greater than a preset threshold, and obtaining a second result; If the second result is yes, determining that the freezing result is an abnormal freezing result, and issuing a danger warning based on the abnormal freezing result; If the second result is no, it is determined that the freezing result is a normal freezing result.

5. The method for monitoring and early warning of artificial ground freezing engineering based on digital twin according to claim 1 is characterized in that: Construct the three-dimensional geometric structure of the artificial ground freezing project site, including: The three-dimensional geometric structure of the artificial ground freezing project site is constructed according to the on-site topography, underground structures and stratum distribution of the artificial ground freezing project; the underground structures include the spatial position and geometric shape of buildings, tunnels or pipelines; the stratum distribution includes the thickness, depth and spatial distribution of different rock and soil bodies.

6. A monitoring and early warning system for artificial ground freezing engineering based on digital twins, characterized in that: The method for monitoring and early warning of artificial stratum freezing engineering based on digital twins as described in any one of claims 1 to 5, wherein the monitoring and early warning system for artificial stratum freezing engineering based on digital twins comprises: a data transmission module and a digital twin computing module; The data transmission module includes a cloud server; the cloud server is connected to the artificial ground freezing project site temperature measurement module and the artificial ground freezing project site monitoring and early warning module; The digital twin computing module includes a digital twin parameter optimization computing program; the digital twin computing module is used to output target prediction data of various locations of the artificial ground freezing project site within a preset time based on the digital twin parameter optimization computing program; the digital twin computing module is installed with numerical simulation software, and the numerical simulation software is used to construct a numerical model based on digital twin technology; The data transmission module is used to transmit data between the artificial stratum freezing project site temperature measurement module, the artificial stratum freezing project site monitoring and early warning module and the digital twin parameter optimization calculation program based on the cloud server; The artificial ground freezing project on-site temperature measurement module is used to output the real temperature of each temperature measurement point in the artificial ground freezing project; The artificial ground freezing project site monitoring and early warning module is used to display, monitor and warn the actual temperature of the rock and soil body monitored in real time at each temperature measuring point output by the artificial ground freezing project site temperature measurement module and the target prediction data of each location on the artificial ground freezing project site within a preset time output by the digital twin calculation module.

7. The artificial ground freezing engineering monitoring and early warning system based on digital twin according to claim 6 is characterized in that: The on-site temperature measurement module for artificial ground freezing engineering comprises a plurality of temperature measurement holes, a plurality of temperature measurement points at different depths are arranged in each of the temperature measurement holes, and a temperature sensor is installed at each of the temperature measurement points.

8. The artificial ground freezing engineering monitoring and early warning system based on digital twin according to claim 7 is characterized in that: Each temperature sensor is connected to an on-site temperature collection station; The on-site temperature collection station is connected to the on-site monitoring and early warning module of the artificial ground freezing project; the on-site temperature collection station is used to output the real temperature of the rock and soil body monitored in real time at each temperature measuring point to the on-site monitoring and early warning module of the artificial ground freezing project.

9. The artificial ground freezing engineering monitoring and early warning system based on digital twin according to claim 6 is characterized in that: The data transmission module also includes a numerical simulation software interface; The numerical simulation software interface is used for data transmission between the digital twin parameter optimization calculation program and the numerical simulation software.

Images