Method, device and medium for establishing a metaverse for deep rock engineering

Abstract

The present invention discloses a method for establishing a metaverse for deep rock mass engineering. The method comprises establishing a 3D geological model, a 3D geometric model of an underground cavern, a support structure model, and an auxiliary monitoring facility model based on the geological data and measurement data of the target deep rock mass engineering; establishing a digital model of the rock mass engineering and a target numerical simulation model based on the above four models; establishing a risk assessment model for the target deep rock mass engineering based on the risk assessment data of the target deep rock mass engineering and the target numerical simulation model; and mapping and reconstructing the scene of the target deep rock mass engineering using the digital model of the rock mass engineering, the target numerical simulation model, and the risk assessment model to obtain a rock mass engineering metaverse for the target deep rock mass engineering. The present invention discloses a method, device, and medium for establishing a metaverse for deep rock mass engineering. The method can more accurately predict safety risks through the rock mass engineering metaverse, thereby reducing the probability of safety accidents in deep rock mass engineering.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a method, device and medium for establishing a metaverse for deep rock engineering. Background Art

[0002] In existing technologies, deep rock mass engineering projects are characterized by large-scale, complex structural forms and intensified geological tectonic movements, which makes the stability control of surrounding rock increasingly difficult and the unknown safety risks more numerous. Therefore, a method that can predict safety risks is urgently needed. Summary of the Invention

[0003] The embodiments of the present invention provide a method, device, and medium for establishing a metaverse for deep rock engineering, which can more accurately predict safety risks through the rock engineering metaverse and reduce the probability of safety accidents in deep rock engineering.

[0004] A first aspect of an embodiment of the present invention provides a method for establishing a metaverse for deep rock engineering, the method comprising:

[0005] Based on the geological data and measurement data of the target deep rock mass project, a 3D geological model, a 3D geometric model of the underground cavern, a support structure model, and ancillary monitoring facility models corresponding to the target deep rock mass project are established;

[0006] Establishing a rock mass engineering digital model of the target deep rock mass engineering based on the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, and the auxiliary monitoring facility model;

[0007] Establishing a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering;

[0008] Establishing a risk assessment model for the target deep rock mass engineering project based on the risk assessment data of the target deep rock mass engineering project and the target numerical simulation model, wherein the risk assessment data includes numerical assessment data, monitoring and early warning data, and surrounding rock failure data of the target deep rock mass engineering project;

[0009] The rock mass engineering digital model, the target numerical simulation model and the risk assessment model are used to map and reconstruct the scene where the target deep rock mass engineering is located, so as to obtain the rock mass engineering metaverse of the target deep rock mass engineering.

[0010] Optionally, establishing a 3D geometric model of an underground cavern corresponding to the target deep rock mass engineering according to geological data and measurement data of the target deep rock mass engineering includes:

[0011] Acquire excavation layer data and axial segmentation data of the underground cavern in the target deep rock mass engineering from the measurement data;

[0012] A 3D geometric model of the underground cavern is established based on the excavation layer data and the segmentation data.

[0013] Optionally, establishing a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering includes:

[0014] Establishing a numerical grid model of the target deep rock mass engineering project based on the 3D geological model, the 3D geometric model of the underground cavern and the support structure model;

[0015] The target numerical simulation model is established according to the numerical grid model, the initial stress field and the boundary conditions.

[0016] Optionally, establishing the target numerical simulation model according to the numerical grid model, the initial stress field and the boundary conditions includes:

[0017] superimposing the initial stress field and the boundary conditions in the numerical grid model to obtain an initial numerical simulation model;

[0018] The initial target numerical simulation model is trained using a multi-objective optimization algorithm to obtain a trained numerical simulation model as the target numerical simulation model.

[0019] Optionally, after establishing the target numerical simulation model, the method further includes:

[0020] The 3D geological model is optimized using the numerical simulation results obtained from the target numerical simulation model to obtain an optimized 3D geological model.

[0021] Optionally, after obtaining the optimized 3D geological model, the method further includes:

[0022] The optimized 3D geological model is used to optimize the rock mass engineering digital model to obtain an optimized rock mass engineering digital model.

[0023] Optionally, mapping and reconstructing the scene of the target deep rock engineering project using the rock engineering digital model, the target numerical simulation model, and the risk assessment model to obtain a rock engineering metaverse of the target deep rock engineering project includes:

[0024] Establishing a virtual twin corresponding to the target deep rock mass engineering;

[0025] The optimized rock mass engineering digital model, the target numerical simulation model and the risk assessment model are used to map and reconstruct the virtual scene corresponding to the virtual twin to obtain the rock mass engineering metaverse.

[0026] A second aspect of an embodiment of the present invention further provides a device for establishing a metaverse for deep rock mass engineering, the device comprising:

[0027] A rock model building unit is used to build a 3D geological model, a 3D geometric model of the underground cavern, a support structure model, and an auxiliary monitoring facility model corresponding to the target deep rock mass project based on the geological data and measurement data of the target deep rock mass project;

[0028] a digital model building unit, configured to build a digital model of the rock mass engineering of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, and the auxiliary monitoring facility model;

[0029] a numerical model building unit, configured to build a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering;

[0030] a risk assessment model establishing unit, configured to establish a risk assessment model for the target deep rock mass engineering project based on the risk assessment data of the target deep rock mass engineering project and the target numerical simulation model, wherein the risk assessment data includes numerical assessment data, monitoring and early warning data, and surrounding rock failure data of the target deep rock mass engineering project;

[0031] The rock mass engineering metaverse acquisition unit is used to map and reconstruct the scene where the target deep rock mass engineering is located using the rock mass engineering digital model, the target numerical simulation model and the risk assessment model to obtain the rock mass engineering metaverse of the target deep rock mass engineering.

[0032] A third aspect of an embodiment of the present invention provides an electronic device comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors to execute the operating instructions corresponding to the method for establishing a metaverse for deep rock engineering as provided in the first aspect.

[0033] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps corresponding to the method for establishing a metaverse for deep rock engineering provided in the first aspect.

[0034] The above one or at least one technical solution in the embodiments of the present application has at least the following technical effects:

[0035] Based on the above technical solution, first, according to the geological data and measurement data of the target deep rock mass engineering, a 3D geological model, an underground cavern 3D geometric model, a support structure model and ancillary monitoring facility model corresponding to the target deep rock mass engineering will be established; then, the 3D geological model, the underground cavern 3D geometric model, the support structure model, the ancillary monitoring facility model and the boundary conditions corresponding to the target deep rock mass engineering will be used to establish a rock mass engineering digital model and a target numerical simulation model; then, the risk assessment data and the target numerical simulation model will be used to establish a risk assessment model; finally, the rock mass engineering digital model, the target numerical simulation model and the risk assessment model will be used to map and reconstruct the scene where the target deep rock mass engineering is located to obtain the rock mass engineering metaverse of the target deep rock mass engineering, so that the rock mass engineering metaverse has a higher degree of matching with the scene where the target deep rock mass engineering is located. In addition, the risk assessment model is used when establishing the rock mass engineering metaverse, so that the safety risks of the target deep rock mass engineering can be predicted through the rock mass engineering metaverse, and the accuracy of the predicted safety risks can be ensured, thereby reducing the probability of safety accidents in deep rock mass engineering. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic flow chart of a method for establishing a metaverse for deep rock engineering provided in an embodiment of the present application;

[0037] Figure 2 A schematic diagram showing the structure of M expansion areas provided in an embodiment of the present application displayed in a vertical row;

[0038] Figure 3 A block diagram of an apparatus for establishing a metaverse for deep rock engineering provided in an embodiment of the present application;

[0039] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The main implementation principles, specific implementation methods and corresponding beneficial effects of the technical solutions of the embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0041] Example

[0042] Please refer to Figure 1The present invention provides a method for establishing a metaverse for deep rock engineering, the method comprising:

[0043] S101. Establishing a 3D geological model, a 3D geometric model of an underground cavern, a support structure model, and an auxiliary monitoring facility model corresponding to the target deep rock mass project based on geological data and measurement data of the target deep rock mass project;

[0044] S102, establishing a rock mass engineering digital model of the target deep rock mass engineering based on the 3D geological model, the underground cavern 3D geometric model, the support structure model, and the auxiliary monitoring facility model;

[0045] S103, establishing a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering;

[0046] S104: establishing a risk assessment model for the target deep rock mass engineering project based on the risk assessment data of the target deep rock mass engineering project and the target numerical simulation model, wherein the risk assessment data includes numerical assessment data, monitoring and early warning data, and surrounding rock failure data of the target deep rock mass engineering project;

[0047] S105 , mapping and reconstructing the scene where the target deep rock mass engineering is located using the rock mass engineering digital model, the target numerical simulation model, and the risk assessment model to obtain a rock mass engineering metaverse of the target deep rock mass engineering.

[0048] The method for establishing a metaverse for deep rock engineering in the embodiments of this specification is usually applied in a server or a user terminal. The server can be, for example, a desktop computer, a laptop computer, an all-in-one computer, a tablet computer, etc., and the user terminal can be, for example, a desktop computer, a laptop computer, an all-in-one computer, a tablet computer, and a smart phone.

[0049] Among them, in step S101, the geological data and measurement data of the target deep rock engineering are first obtained. The geology near the target deep rock engineering can be scanned in advance to obtain geological data and store it in the corresponding storage database, so that the geological data can be directly read from the storage database when the geological data is obtained; of course, it is also necessary to measure the various components corresponding to the target deep rock engineering in advance, obtain the measurement data and store it in the storage database, so that the measurement data can also be directly read from the storage database when the measurement data is obtained.

[0050] In one embodiment, when measuring the various components corresponding to the target deep rock project in advance, the underground caverns in the target deep rock project will be measured to obtain the excavation layer data of the underground caverns and the axial segmentation data of the caverns; the support structures including anchor rods, anchor cables and concrete spraying layers in the target deep rock project will also be measured to obtain the support structure data; and the various monitoring equipment in the target deep rock project will also be measured to obtain the monitoring equipment data.

[0051] In one embodiment, after obtaining geological data and measurement data, 3D modeling can be performed based on the geological and measurement data to obtain a 3D geological model. Accordingly, excavation layer data and axial segmentation data of the underground cavern in the target deep rock mass project can be obtained from the measurement data. A 3D geometric model of the underground cavern can then be established based on the excavation layer data and segmentation data. Furthermore, support structure data can be obtained from the measurement data, and a support structure model can be established based on the support structure data. Furthermore, monitoring equipment data can be obtained from the measurement data, and an auxiliary monitoring facility model can be established based on the monitoring equipment.

[0052] In one embodiment, when establishing a 3D geological model, a 3D geometric model of an underground cavern, a support structure model, and an ancillary monitoring facility model, a 3D modeling method can be used to establish the 3D geological model, the 3D geometric model of an underground cavern, the support structure model, and the ancillary monitoring facility model, and the geometric properties, motion properties, and functional properties of the geological entity, as well as the functional properties of the support structure, can be obtained. The functional properties of the geological entity include geological structural properties, stratum mechanical properties, etc.

[0053] After establishing the 3D geological model, the underground cavern 3D geometric model, the support structure model and the auxiliary monitoring facility model, step S102 is executed.

[0054] In step S102, a three-dimensional modeling algorithm is used to perform fusion modeling processing on the 3D geological model, the 3D geometric model of the underground cavern, the support structure model and the auxiliary monitoring facility model to obtain a digital model of the rock mass engineering. The geometric properties, motion properties and functional properties of the geological entity, as well as the functional properties of the support structure, are annotated in the digital model of the rock mass engineering.

[0055] Next, step S103 is executed, wherein step S103 can be executed simultaneously with step S102, or step S103 can be executed first and then step S102.

[0056] In step S103, first, a numerical grid model of the target deep rock mass engineering is established based on the 3D geological model, the underground cavern 3D geometric model and the support structure model; then, a target numerical simulation model is established based on the numerical grid model, the initial stress field and the boundary conditions.

[0057] In one embodiment, after the numerical grid model is established, the initial stress field and boundary conditions are superimposed on the numerical grid model to obtain an initial numerical simulation model. At this time, the initial numerical simulation model can be directly used as the target numerical simulation model.

[0058] In another embodiment, after the initial numerical simulation model is obtained, the initial target numerical simulation model may be trained using a multi-objective optimization algorithm to obtain a trained numerical simulation model as the target numerical simulation model.

[0059] Specifically, the 3D geological model, the 3D geometric model of the underground cavern and the support structure model can be input into the 3D modeling algorithm for modeling to construct a visual numerical grid model; the initial stress field and boundary conditions are then superimposed on the visual numerical grid model to obtain an initial numerical simulation model; and based on multi-source data, the Pareto multi-objective optimization algorithm is used to train and optimize the simulation model to obtain the trained numerical simulation model as the target numerical simulation model. When the initial simulation model is trained and optimized based on multi-source data using the Pareto multi-objective optimization algorithm, the numerical simulation model that meets the constraint conditions can be used as the trained numerical simulation model.

[0060] In this way, since the target numerical simulation model is based on multi-source data and the Pareto multi-objective optimization algorithm is used to train and optimize the initial simulation model, the target numerical simulation model has a higher matching degree with the target deep rock engineering, which can make the target numerical simulation model more accurate.

[0061] After obtaining the target numerical simulation model, step S104 is executed, wherein step S104 may be executed simultaneously with step S103, or step S104 may be executed first and then step S103.

[0062] In step S104, first, risk safety indicators such as point safety factor, degree of destruction and elastic modulus degradation index in deep rock engineering are obtained, and the obtained risk safety indicators are used as risk assessment data; and monitoring and early warning indicators including deformation value and deformation rate are obtained; and data such as surrounding rock failure probability and failure zone risk level are obtained based on historical engineering experience, and the obtained surrounding rock failure probability and failure zone risk level data are added to the surrounding rock failure data.

[0063] In this way, after obtaining the risk assessment data, monitoring and early warning indicators, and surrounding rock failure data, the model is trained using the surrounding rock deformation, damage zone depth, and other data in the target numerical simulation model, the risk assessment data, monitoring and early warning indicators, and surrounding rock failure data to obtain a risk assessment model.

[0064] In one embodiment, a corresponding risk assessment mechanism (risk level classification and release, emergency plan formulation and emergency rescue measures, etc.) can be established first by based on the damage warning indicators and comprehensive warning mechanism of the target deep rock engineering, thereby establishing an initial assessment model; then the initial assessment model is trained using the data in the target numerical simulation model, risk assessment data, monitoring and warning indicators and surrounding rock damage data to obtain the trained initial assessment model as a risk assessment model.

[0065] In one embodiment, when obtaining the damage zone risk level, surrounding rock damage zone data in the target deep rock mass project can be obtained based on a preset risk level, and the surrounding rock damage zone data can be matched with damage zone data corresponding to the preset risk level. The risk level corresponding to the data matching the surrounding rock damage zone data can be used as the damage zone risk level. For example, the preset risk levels include a first level, a second level, and a third level. If the surrounding rock damage zone data matches the damage zone data corresponding to the second level, the second level can be used as the damage zone risk level.

[0066] After obtaining the rock mass engineering digital model, the target numerical simulation model and the risk assessment model, step S105 is executed.

[0067] In step S105, the digital twin platform can be used to integrate the digital model of the rock engineering, the target numerical simulation model and the risk assessment model, and the mapping reconstruction, data mirroring, synchronous feedback and information interaction of the real scene where the target deep rock engineering is located to the virtual world can be carried out, thereby establishing a rock engineering metaverse corresponding to the target deep rock engineering.

[0068] In one embodiment, when establishing a rock engineering metaverse, a virtual twin corresponding to the target deep rock engineering project can be established; the virtual scene corresponding to the virtual twin is mapped and reconstructed using the rock engineering digital model, the target numerical simulation model and the risk assessment model to obtain the rock engineering metaverse.

[0069] In actual application, a computable data model can be constructed, and multi-source data fusion and deep learning algorithms, as well as iterative optimization and intelligent decision-making methods, can be used to achieve data mirroring and data interaction between the 3D geological model entity, the target numerical simulation model and the virtual twin; and the 3D geological model, risk assessment model, target numerical simulation model and the above data models can be integrated to realize the digital twin of the target deep rock engineering construction scene in the virtual space through data-driven and real-time interaction.

[0070] In another embodiment, to increase the accuracy of the acquired 3D geological model, after establishing the target numerical simulation model, the 3D geological model may be optimized using the numerical simulation results obtained from the target numerical simulation model to obtain an optimized 3D geological model. Thus, after obtaining the target numerical simulation model, the numerical simulation results calculated by the target numerical simulation model are obtained and fed back into the 3D geological model to optimize the 3D geological model and obtain an optimized 3D geological model.

[0071] Furthermore, after obtaining the optimized 3D geological model, the optimized 3D geological model can be used to optimize the rock mass engineering digital model to obtain the optimized rock mass engineering digital model.

[0072] Specifically, after obtaining the optimized 3D geological model, the optimized 3D geological model, the underground cavern 3D geometric model, the support structure model and the ancillary monitoring facility model can be used to optimize the rock engineering digital model to obtain the optimized rock engineering digital model. In this way, on the basis of the higher accuracy of the optimized 3D geological model, the accuracy of the optimized rock engineering digital model will also be improved.

[0073] In one embodiment, after obtaining the optimized rock mass engineering digital model, the optimized rock mass engineering digital model, the target numerical simulation model, and the risk assessment model can be used to map and reconstruct the virtual scene corresponding to the virtual twin to obtain the rock mass engineering metaverse. In this case, based on the higher accuracy of the optimized rock mass engineering digital model, the accuracy of the rock mass engineering metaverse derived based on the accuracy of the optimized rock mass engineering digital model is also improved.

[0074] In actual application, see Figure 2 After establishing the digital model 20 of rock mass engineering, the target numerical simulation model 21 and the risk assessment model 22, the digital twin platform 23 of deep rock mass engineering will integrate the digital model 20 of rock mass engineering, the target numerical simulation model 21 and the risk assessment model 22, and integrate the digital model, numerical simulation model and risk assessment model to realize the mapping reconstruction, data mirroring, synchronous feedback and information interaction of the real scene of deep rock mass engineering construction to the virtual world.

[0075] In addition, the virtual application scenario customization platform 24 can customize the virtual application scenarios corresponding to the target deep rock engineering construction according to the actual needs of the engineering project and the construction parties, and can set up corresponding functional modules to set up the surrounding rock damage risk area highlighting and no-entry prompts during the target deep rock engineering construction process in the virtual application scenario, construction personnel role definition and positioning, construction personnel psychological assessment test, construction equipment definition and positioning, and sudden engineering disaster scenario simulation and emergency plan release, etc.

[0076] Furthermore, the Metaverse scene integration platform 25 couples the deep rock engineering digital twin platform 23 and the virtual application scene customization platform 24 through technologies such as extended reality, providing construction personnel with an immersive experience in the Metaverse for deep rock engineering construction, predicting safety risks during the construction process and making reasonable risk avoidance behaviors. The Metaverse scene integration platform 25 can also map the real-time monitoring data of the target deep rock engineering construction scene through AR technology.

[0077] In addition, the data model of the deep rock engineering digital twin platform 23 includes a perception layer, a network layer, a data layer and an application layer, wherein the perception layer is used to perceive the scene working environment, equipment operating parameters and equipment working status of the target deep rock engineering, and provide information flow for the data model; the network layer is used for unified networking, protocol conversion, edge computing and network transmission of the scene equipment of the target deep rock engineering, and provides a communication interface for the perception layer and the data layer; the data layer is used for the aggregation, fusion, iterative calculation, analysis and mining, data twin and storage management of the scene multi-source data of the target deep rock engineering, and provides data flow for the data model; the application layer provides users with target deep rock data models and information interaction services, intelligent identification of construction scene equipment of deep rock engineering, precise positioning of personnel, real-time monitoring and reliable operation and maintenance, and provides decision-making for the project.

[0078] In one embodiment, after the rock engineering metaverse obtains the real-time data of the target deep rock engineering project in real time, it uses the risk assessment model to process the risk assessment data in the real-time data to predict whether there is a safety risk. When there is a safety risk, the emergency plan corresponding to the safety risk is released, so that the current construction personnel can handle it according to the emergency plan, which can effectively reduce the probability of safety accidents in deep rock engineering.

[0079] The above one or at least one technical solution in the embodiments of the present application has at least the following technical effects:

[0080] Based on the above technical solution, first, according to the geological data and measurement data of the target deep rock mass engineering, a 3D geological model, an underground cavern 3D geometric model, a support structure model and ancillary monitoring facility model corresponding to the target deep rock mass engineering will be established; then, the 3D geological model, the underground cavern 3D geometric model, the support structure model, the ancillary monitoring facility model and the boundary conditions corresponding to the target deep rock mass engineering will be used to establish a rock mass engineering digital model and a target numerical simulation model; then, the risk assessment data and the target numerical simulation model will be used to establish a risk assessment model; finally, the rock mass engineering digital model, the target numerical simulation model and the risk assessment model will be used to map and reconstruct the scene where the target deep rock mass engineering is located to obtain the rock mass engineering metaverse of the target deep rock mass engineering, so that the rock mass engineering metaverse has a higher degree of matching with the scene where the target deep rock mass engineering is located. In addition, the risk assessment model is used when establishing the rock mass engineering metaverse, so that the safety risks of the target deep rock mass engineering can be predicted through the rock mass engineering metaverse, and the accuracy of the predicted safety risks can be ensured, thereby reducing the probability of safety accidents in deep rock mass engineering.

[0081] The above embodiment provides a method for establishing a metaverse for deep rock mass engineering. The present embodiment also provides a device for establishing a metaverse for deep rock mass engineering. Figure 3 , the device comprises:

[0082] The rock model building unit 301 is used to build a 3D geological model, a 3D geometric model of the underground cavern, a support structure model, and an auxiliary monitoring facility model corresponding to the target deep rock mass project based on the geological data and measurement data of the target deep rock mass project;

[0083] A digital model building unit 302 is configured to build a digital rock mass engineering model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, and the auxiliary monitoring facility model;

[0084] A numerical model building unit 303 is configured to build a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering;

[0085] a risk assessment model establishing unit 304, configured to establish a risk assessment model for the target deep rock mass project based on the risk assessment data of the target deep rock mass project and the target numerical simulation model, wherein the risk assessment data includes numerical assessment data, monitoring and early warning data, and surrounding rock failure data of the target deep rock mass project;

[0086] The rock engineering metaverse acquisition unit 305 is used to map and reconstruct the scene of the target deep rock engineering using the rock engineering digital model, the target numerical simulation model and the risk assessment model to obtain the rock engineering metaverse of the target deep rock engineering.

[0087] In an optional embodiment, the rock model establishment unit 301 is used to obtain the excavation layer data and the axial segmentation data of the underground cavern in the target deep rock engineering from the measurement data; and establish the 3D geometric model of the underground cavern based on the excavation layer data and the segmentation data.

[0088] In an optional embodiment, the numerical model establishment unit 303 is used to establish a numerical grid model of the target deep rock engineering based on the 3D geological model, the underground cavern 3D geometric model and the support structure model; and to establish the target numerical simulation model based on the numerical grid model, the initial stress field and the boundary conditions.

[0089] In an optional embodiment, the numerical model establishment unit 303 is used to superimpose the initial stress field and the boundary conditions in the numerical grid model to obtain an initial numerical simulation model; and use a multi-objective optimization algorithm to train the initial target numerical simulation model to obtain a trained numerical simulation model as the target numerical simulation model.

[0090] In an optional embodiment, the rock model establishing unit 301 is used to optimize the 3D geological model using the numerical simulation results obtained from the target numerical simulation model after establishing the target numerical simulation model to obtain an optimized 3D geological model.

[0091] In an optional embodiment, the rock mass model establishing unit 301 is configured to optimize the rock mass engineering digital model using the optimized 3D geological model after obtaining the optimized 3D geological model to obtain the optimized rock mass engineering digital model.

[0092] In an optional embodiment, the rock engineering metaverse acquisition unit 305 is used to establish a virtual twin corresponding to the target deep rock engineering; and use the optimized rock engineering digital model, the target numerical simulation model and the risk assessment model to map and reconstruct the virtual scene corresponding to the virtual twin to obtain the rock engineering metaverse.

[0093] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0094] Figure 4The block diagram of an electronic device 800 is shown, according to an exemplary embodiment, for establishing a metaverse for deep rock engineering. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, or the like.

[0095] Reference Figure 4 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / display (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0096] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operation, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to perform all or part of the steps of the above-described method. In addition, the processing component 802 may include one or more modules to facilitate interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate interaction between the multimedia component 808 and the processing component 802.

[0097] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, pictures, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0098] The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 800.

[0099] The multimedia component 808 includes a screen that provides a presentation interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor can not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each front camera and rear camera can be a fixed optical lens system or have a focal length and optical zoom capability.

[0100] The audio component 810 is configured to present and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), which is configured to receive external audio signals when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 804 or transmitted via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for presenting audio signals.

[0101] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as a keyboard, click wheel, buttons, etc. These buttons may include but are not limited to: a home button, volume buttons, a start button, and a lock button.

[0102] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the electronic device 800. The sensor assembly 814 can also detect changes in the position of the electronic device 800 or a component of the electronic device 800, the presence or absence of user contact with the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and temperature changes of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0103] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as Wi-Fi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0104] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0105] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by the processor 820 of the electronic device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0106] Other embodiments of the present invention will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the invention being indicated by the following claims.

[0107] It should be understood that the present invention is not limited to the exact construction described above and shown in the accompanying drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

[0108] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for establishing a metaverse for deep rock engineering, characterized in that: The method comprises: Based on the geological data and measurement data of the target deep rock mass project, a 3D geological model, a 3D geometric model of the underground cavern, a support structure model, and ancillary monitoring facility models corresponding to the target deep rock mass project are established; Establishing a rock mass engineering digital model of the target deep rock mass engineering based on the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, and the auxiliary monitoring facility model; Establishing a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering; Establishing a risk assessment model for the target deep rock mass engineering project based on the risk assessment data of the target deep rock mass engineering project and the target numerical simulation model, wherein the risk assessment data includes numerical assessment data, monitoring and early warning data, and surrounding rock failure data of the target deep rock mass engineering project; The rock mass engineering digital model, the target numerical simulation model and the risk assessment model are used to map and reconstruct the scene where the target deep rock mass engineering is located, so as to obtain the rock mass engineering metaverse of the target deep rock mass engineering.

2. The method according to claim 1, wherein The step of establishing a 3D geometric model of an underground cavern corresponding to the target deep rock mass engineering project based on the geological data and measurement data of the target deep rock mass engineering project comprises: Acquire excavation layer data and axial segmentation data of the underground cavern in the target deep rock mass engineering from the measurement data; A 3D geometric model of the underground cavern is established based on the excavation layer data and the segmentation data.

3. The method according to claim 2, wherein The method of establishing a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering comprises: Establishing a numerical grid model of the target deep rock mass engineering project based on the 3D geological model, the 3D geometric model of the underground cavern and the support structure model; The target numerical simulation model is established according to the numerical grid model, the initial stress field and the boundary conditions.

4. The method according to claim 3, wherein The step of establishing the target numerical simulation model according to the numerical grid model, the initial stress field and the boundary conditions includes: superimposing the initial stress field and the boundary conditions in the numerical grid model to obtain an initial numerical simulation model; The initial numerical simulation model is trained using a multi-objective optimization algorithm to obtain a trained numerical simulation model as the target numerical simulation model.

5. The method according to claim 4, wherein After establishing the target numerical simulation model, the method further includes: The 3D geological model is optimized using the numerical simulation results obtained from the target numerical simulation model to obtain an optimized 3D geological model.

6. The method according to claim 5, wherein After obtaining the optimized 3D geological model, the method further includes: The optimized 3D geological model is used to optimize the rock mass engineering digital model to obtain an optimized rock mass engineering digital model.

7. The method according to any one of claims 1 to 5, wherein: The step of mapping and reconstructing the scene of the target deep rock mass engineering using the rock mass engineering digital model, the target numerical simulation model, and the risk assessment model to obtain the rock mass engineering metaverse of the target deep rock mass engineering comprises: Establishing a virtual twin corresponding to the target deep rock mass engineering; The optimized rock mass engineering digital model, the target numerical simulation model and the risk assessment model are used to map and reconstruct the virtual scene corresponding to the virtual twin to obtain the rock mass engineering metaverse.

8. A device for establishing a metaverse for deep rock engineering, characterized in that: The device comprises: A rock model building unit is used to build a 3D geological model, a 3D geometric model of the underground cavern, a support structure model, and an auxiliary monitoring facility model corresponding to the target deep rock mass project based on the geological data and measurement data of the target deep rock mass project; a digital model building unit, configured to build a digital model of the rock mass engineering of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, and the auxiliary monitoring facility model; a numerical model building unit, configured to build a target numerical simulation model of the target deep rock mass engineering according to the 3D geological model, the 3D geometric model of the underground cavern, the support structure model, the initial stress field of the target deep rock mass engineering, and the boundary conditions corresponding to the target deep rock mass engineering; a risk assessment model establishing unit, configured to establish a risk assessment model for the target deep rock mass engineering project based on the risk assessment data of the target deep rock mass engineering project and the target numerical simulation model, wherein the risk assessment data includes numerical assessment data, monitoring and early warning data, and surrounding rock failure data of the target deep rock mass engineering project; The rock mass engineering metaverse acquisition unit is used to map and reconstruct the scene where the target deep rock mass engineering is located using the rock mass engineering digital model, the target numerical simulation model and the risk assessment model to obtain the rock mass engineering metaverse of the target deep rock mass engineering.

9. An electronic device, characterized in that: The invention comprises a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors to execute the operation instructions corresponding to the method according to any one of claims 1 to 7 contained in the one or more programs.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps corresponding to the method according to any one of claims 1 to 7 are implemented.

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