Dam dynamic growth visual modeling method, device and electronic equipment

Abstract

The present disclosure provides a dam dynamic growth visualization modeling method, device and electronic equipment, and relates to the technical field of engineering modeling. The method comprises the following steps: dividing a structure unit and a process unit, determining a basic unit based on the combination of the two; dividing the basic unit into a key node and a non-key node based on the logical relationship between different processes, process parameters and total duration information, and determining the time window of the basic unit; determining the space constraint satisfaction degree according to the geometric parameters of the basic unit, determining the physical influence coefficient according to the physical parameters of the basic unit, and generating a segmented growth plan matrix; binding the segmented growth plan matrix with a three-dimensional model of the dam to form a dynamic growth visualization model; processing a plurality of first-time dam feature data by using a sequence model, and outputting an optimal basic unit combination at a second time based on a preset optimization target, and displaying by the dynamic growth visualization model. The present disclosure realizes the modeling and display of the dam dynamic growth process.

Description

Technical Field

[0001] The present disclosure relates to the technical field of engineering modeling, and in particular to a method, device and electronic equipment for visualizing modeling of dynamic growth of a dam. Background Art

[0002] Dam construction is a dynamic process. Modeling technologies like BIM (Building Information Modeling) focus on statically displaying the dam structure, failing to dynamically reflect the actual conditions and changes during dam construction in real time. This hinders comprehensive and accurate decision-making by construction and management personnel. Summary of the Invention

[0003] The present disclosure provides a method, apparatus, computer program product, and electronic device for visualizing the dynamic growth of a dam, so as to realize the modeling and display of the dynamic growth process of the dam, at least to a certain extent.

[0004] According to a first aspect of the present disclosure, a method for visual modeling of dynamic growth of a dam is provided. The method includes: dividing a dam into a plurality of structural units according to a three-dimensional structure, dividing a construction process of the dam into a plurality of process units according to a process step, and determining basic units of the dam dynamic process based on a combination of the structural units and the process units; dividing the basic units into key nodes and non-key nodes based on logical relationships between different processes, process parameters, and total construction period information of the construction process, and determining time windows of the basic units; the time windows of key nodes have no floating space, while the time windows of non-key nodes have floating space; determining the degree of satisfaction of spatial constraints according to geometric parameters of the basic units, determining physical influence coefficients according to physical parameters of the basic units, and generating a segmented growth plan matrix according to the time windows, the degree of satisfaction of spatial constraints, and the physical influence coefficients of the basic units; binding the segmented growth plan matrix to the three-dimensional model of the dam to form a dynamic growth visualization model; obtaining multiple dam characteristic data at a first time, processing the dam characteristic data using a sequence model, and outputting an optimal basic unit combination at a second time based on a preset optimization target, and displaying the optimal basic unit combination through the dynamic growth visualization model.

[0005] According to a second aspect of the present disclosure, a device for visualizing the dynamic growth of a dam is provided, the device comprising: a basic unit construction module, configured to divide the dam into a plurality of structural units according to the three-dimensional structure, and to divide the construction process of the dam into a plurality of process units according to the process, and to determine the basic unit of the dam dynamic process based on the combination of the structural unit and the process unit; a time window determination module, configured to divide the basic unit into key nodes and non-key nodes based on the logical relationship between different processes, process parameters and the total construction period information of the construction process, and to determine the time window of the basic unit; the time window of the key node has no floating space, and the time window of the non-key node has floating space; a segmented growth plan matrix generation module, configured to The degree of satisfaction of the spatial constraints is determined according to the geometric parameters of the basic unit, the physical influence coefficient is determined according to the physical parameters of the basic unit, and a segmented growth plan matrix is ​​generated according to the time window, the degree of satisfaction of the spatial constraints, and the physical influence coefficient of the basic unit; a dynamic growth visualization model construction module is configured to bind the segmented growth plan matrix with the three-dimensional model of the dam to form a dynamic growth visualization model; an optimal basic unit combination processing module is configured to obtain multiple dam characteristic data at the first time, process the dam characteristic data using a sequence model, and output the optimal basic unit combination at the second time based on a preset optimization target, and display the optimal basic unit combination through the dynamic growth visualization model.

[0006] According to a third aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein when the computer program is executed by a processor, the method of the first aspect and possible implementations thereof are implemented.

[0007] According to a fourth aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the method of the above-mentioned first aspect and its possible implementation methods by executing the executable instructions.

[0008] The technical solution disclosed in this disclosure has the following beneficial effects:

[0009] The dam and its construction process are divided into basic units based on structure and process steps, forming a basic digital carrier unit that represents the dam's dynamic growth process. By calculating and quantifying the time window, spatial constraint satisfaction, and physical influence coefficients, a spatiotemporal integrated segmented growth plan matrix is ​​constructed and bound to the three-dimensional model to generate a dynamic growth visualization model. This enables the modeling and visualization of the dam's dynamic growth process. By combining digital twin technology to establish a bidirectional mapping between physical construction and virtual model growth, the optimal basic unit combination simulated based on the virtual model can be used to reverse-engineer construction scheduling, improve the scientific nature of construction scheduling and decision-making, and enhance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Figure 1 A flowchart showing a method for visualizing dynamic growth of a dam in an embodiment of the present disclosure is shown.

[0011] Figure 2 A flow chart for determining a time window in an embodiment of the present disclosure is shown.

[0012] Figure 3 A schematic diagram showing a basic unit formed by dividing a three-dimensional model in an embodiment of the present disclosure.

[0013] Figure 4 A schematic diagram showing the import of a three-dimensional model into a WebGIS platform in an embodiment of the present disclosure is shown.

[0014] Figure 5 Schematic diagram showing the model states at different time points in an embodiment of the present disclosure.

[0015] Figure 6 A schematic diagram illustrating the association of security monitoring information and drawings with a dynamically growing visualization model in an embodiment of the present disclosure.

[0016] Figure 7 A structural schematic diagram of a dam dynamic growth visualization modeling device in an embodiment of the present disclosure is shown.

[0017] Figure 8 A schematic structural diagram of an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0018] Exemplary embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings.

[0019] The accompanying drawings are schematic illustrations of the present disclosure and are not necessarily drawn to scale. Some of the block diagrams shown in the accompanying drawings may be functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, or in hardware modules or integrated circuits, or in networks, processors or microcontrollers. The embodiments can be implemented in various forms and should not be construed as being limited to the examples set forth herein. The features, structures or characteristics described in the present disclosure may be combined in one or more embodiments in any suitable manner. In the description below, many specific details are provided to provide a full description of the embodiments of the present disclosure. However, those skilled in the art will appreciate that one or more specific details may be omitted when implementing the technical solution of the present disclosure, or that other methods, components, devices, steps, etc. may be used to replace one or more specific details.

[0020] Dam construction faces multiple constraints, including time, space, and physical constraints. Existing technologies often treat these constraints in isolation, lacking a unified collaborative optimization framework. This makes it difficult to comprehensively consider the interplay between these constraints, resulting in construction plans with limited adaptability to complex real-world conditions. Furthermore, most approaches rely on post-construction analysis and are unable to promptly respond to changes that arise during construction, such as sudden geological changes, design changes, and weather events. When these situations occur, it's difficult to quickly adjust construction plans and resource allocation, potentially leading to construction delays, increased costs, and quality risks. While technologies like BIM can provide some level of dam modeling and visualization capabilities, they primarily focus on static presentation and fail to dynamically reflect the actual conditions and changes occurring during dam construction. For example, current 3D dam models make it difficult to intuitively visualize the relationships between time schedules, space occupancy, and changes in physical parameters across different construction phases. Consequently, this hinders comprehensive and accurate decision-making by construction personnel and management.

[0021] In view of the above problems, an embodiment of the present disclosure provides a method for visual modeling of dynamic growth of a dam, aiming to achieve dynamic modeling and display of the dam.

[0022] Figure 1 An exemplary process of the method is shown, including the following steps S110 to S150:

[0023] Step S110: Divide the dam into a plurality of structural units according to the three-dimensional structure, divide the dam construction process into a plurality of process units according to the process, and determine the basic unit of the dam dynamic process based on the combination of the structural units and the process units;

[0024] Step S120: Based on the logical relationships between different processes, process parameters, and the total construction period information, the basic units are divided into key nodes and non-key nodes, and the time windows of the basic units are determined; the time windows of key nodes have no floating space, while the time windows of non-key nodes have floating space;

[0025] Step S130, determining the degree of satisfaction of the spatial constraint according to the geometric parameters of the basic unit, determining the physical influence coefficient according to the physical parameters of the basic unit, and generating a segmented growth plan matrix according to the time window, the degree of satisfaction of the spatial constraint, and the physical influence coefficient of the basic unit;

[0026] Step S140 , binding the segmented growth plan matrix to the three-dimensional model of the dam to form a dynamic growth visualization model;

[0027] Step S150, obtaining multiple dam characteristic data at the first time, processing the dam characteristic data using a sequence model, and outputting the optimal basic unit combination at the second time based on a preset optimization target, and displaying the optimal basic unit combination through a dynamic growth visualization model.

[0028] based on Figure 1 Using a method, the dam and its construction process are divided into basic units based on structure and process steps, forming basic digital carrier units that represent the dam's dynamic growth process. By calculating and quantifying the integration of time windows, spatial constraint satisfaction, and physical influence coefficients, a time-space integrated segmented growth plan matrix is ​​constructed and bound to the three-dimensional model to generate a dynamic growth visualization model. This enables the modeling and display of the dam's dynamic growth process. By combining digital twin technology to establish a bidirectional mapping between physical construction and virtual model growth, the optimal basic unit combination simulated based on the virtual model can be used to reversely guide construction scheduling, improve the scientific nature of construction scheduling and decision-making, and enhance efficiency.

[0029] Below Figure 1 Provide detailed instructions for each step.

[0030] refer to Figure 1 In step S110, the dam is divided into multiple structural units according to the three-dimensional structure, and the construction process of the dam is divided into multiple process units according to the process. The basic unit of the dam dynamic process is determined based on the combination of the structural unit and the process unit.

[0031] Among them, the structural unit is a unit divided from the spatial dimension, and the process unit is a unit divided from the time dimension. The two are combined to form the basic unit under the joint dimension of time and space.

[0032] In one embodiment, dividing the dam into a plurality of structural units according to the three-dimensional structure includes the following steps:

[0033] The dam is divided into multiple sections, each section is divided into multiple sub-sections according to the correspondence with the left bank and the right bank, each sub-section is layered, each layer is divided into one or more casting blocks, and each casting block is regarded as a structural unit.

[0034] For example, a three-dimensional model of the dam is established in a three-dimensional modeling software, and the dam is divided into three core sections according to the structural characteristics of the dam body: the dam foundation section, the dam body section, and the dam top section. Each section is further subdivided into left bank / right bank sub-sections, and each sub-section is further divided into multiple layers. Finally, each layer is divided into blocks according to casting blocks to form a four-level hierarchical structure of section-sub-section-layer-casting block, and multiple structural units are obtained.

[0035] In one embodiment, each structural unit has a first segment identifier, which is a combination of a segment number, a sub-segment number, a layer number, and a block number; each process unit has a second segment identifier, which is a process number; and determining a basic unit of a dam dynamic process based on the combination of the structural unit and the process unit includes the following steps:

[0036] The structure unit and the process unit are combined to form a basic unit, and a third segment identifier of the basic unit is determined according to the combination of the first segment identifier and the second segment identifier.

[0037] For example, the coding rule of the first segment identifier is: D [segment number] - S [subsegment number] - L [layer number] - B [block number], and the first segment identifier of the fifth layer of the right bank of the second segment and the third pouring block can be "D2-SR-L5-B3". According to the characteristics of the dam construction process, six types of process units are defined, which are foundation treatment unit, concrete pouring unit, grouting unit, metal structure installation unit, monitoring instrument embedding unit and maintenance unit. Gi (i = 1 ~ 6) is used as the second segment identifier of the process unit, and Table 1 shows the second segment identifier and process content of each type of process unit.

[0038] Table 1 Process unit table

[0039]

[0040] The structure unit and the process unit are combined to form a basic unit, and a third segment identifier of the basic unit is determined according to the combination of the first segment identifier and the second segment identifier. For example, the basic unit "D2-SR-L5-B3-G2" represents the concrete pouring process of the fifth layer of the right bank of the second segment and the third pouring block. The basic unit is a micro- digital carrier of the dam dynamic process, which integrates the digital twin concept. By assigning a third unit identifier to each basic unit, the design model, construction record, monitoring data and other whole life cycle information of the basic unit can be associated in the future.

[0041] With reference to Figure 1 In step S120, based on the logical relationship between different processes, process parameters and total construction period information of the construction process, the basic units are divided into key nodes and non-key nodes, and the time window of the basic unit is determined; the time window of the key node has no floating space, and the time window of the non-key node has floating space.

[0042] The logical relationship between different procedures can include a sequence relationship, such as a immediately before / after logical relationship. The procedure parameters include, but are not limited to, construction speed, construction requirements, etc. The total construction period information of the construction process can include the planned start time and the planned end time of the entire construction, and can also include important time nodes in the construction process, such as completing a specific procedure or completing 50% of the entire progress at a certain time. The time window is used to represent the expected construction time period, for example, the time window includes a lower limit and an upper limit, the time window lower limit represents the earliest start time, and the time window upper limit represents the latest end time. Based on the logical relationship between different procedures, the procedure parameters, and the total construction period information of the construction process, the time difference of each basic unit can be calculated. Generally, the basic unit with a time difference of 0 is a critical unit, and its time window has no floating space and is relatively fixed. The basic unit with a time difference not equal to 0 is a non-critical unit, and its time window has floating space, that is, it can be changed within a certain range. Further, the time window of each basic unit can be determined.

[0043] In an embodiment, referring to Figure 2 Based on the logical relationship between different procedures, the procedure parameters, and the total construction period information of the construction process, the basic unit is divided into a critical node and a non-critical node, and the time window of the basic unit is determined, including the following steps S210 to S240:

[0044] Step S210, determining the planned duration of each basic unit according to the procedure parameters;

[0045] Step S220, based on the logical relationship between different procedures, the planned duration of each basic unit, and the total construction period information, forward calculating the earliest time parameter of each basic unit and reverse calculating the latest time parameter of each basic unit;

[0046] Step S230, determining the floating space according to the earliest time parameter and the latest time parameter of each basic unit, taking the basic unit without floating space as a critical node, and taking the basic unit with floating space as a non-critical node;

[0047] Step S240, determining the time window of each basic unit by taking the earliest start time in the earliest time parameter as the lower limit of the time window and taking the latest end time in the latest time parameter as the upper limit of the time window.

[0048] For example, the procedure parameters include the construction speed, which can be obtained by historical construction data (such as the pouring speed of similar projects), combined with the engineering quantity of the basic unit, to calculate the planned duration, such as planned duration = concrete volume of basic unit ÷ pouring speed. The planned duration is denoted as PT i ( i The unit can be days, hours, etc.

[0049] The logical relationship between different processes can be established based on construction drawings and process standards, etc. For example, in the construction process of a gravity dam, "bedrock anchoring" must be performed after "overburden excavation", thereby forming a tight before / after logical relationship. In an embodiment, a directed acyclic graph can be formed according to the logical relationship between different processes. Subsequently, the construction path is determined through the directed acyclic graph, and the time window is calculated.

[0050] with basic unit i The earliest time that can be started after all the tight before processes are completed is taken as the earliest start time ES i , basic unit i The earliest time that can be completed is taken as the earliest end time EF i = ES i + PT i The earliest time parameter is calculated in a forward direction based on the planned start time of the total duration.

[0051] with basic unit i The latest time that does not affect the total duration is taken as the latest end time LF i , basic unit LF=EF , basic unit i The latest time that does not affect the total duration is taken as the latest start time LS i = LF i - PT i， The latest time parameter is calculated in a reverse direction based on the planned end time of the total duration.

[0052] The time difference of the basic unit i is calculated If the time difference is 0, it is taken as a critical node, and if the time difference is not 0, it is taken as a non-critical node. The time window of the critical node has no floating space, and the time window of the non-critical node has floating space, such as the adjustable range of the time window determined according to the time difference, which can be ±10%.

[0053] The earliest start time of the basic unit i is taken as the lower limit of the time window ES i The latest end time is taken as the upper limit of the time window LF i , forming a time window. Further, an initial segmented growth plan matrix with a temporal attribute can be formed , n is the number of basic units, 4 is the column dimension, including the following 4 dimensions: third unit identifier, planned duration, lower limit of time window, upper limit of time window.

[0054] With reference to the foregoing Figure 1 In step S130, the degree of satisfaction of the spatial constraint is determined according to the geometric parameters of the basic unit, the physical impact coefficient is determined according to the physical parameters of the basic unit, and the segmented growth plan matrix is generated according to the time window, the degree of satisfaction of the spatial constraint, and the physical impact coefficient of the basic unit.

[0055] The degree of satisfaction of the spatial constraint represents the degree to which the basic unit satisfies the spatial constraint rule, such as 0 when the spatial constraint rule is not satisfied at all, 1 when it is partially satisfied, and 2 when it is fully satisfied. The physical impact coefficient is used to quantify the influence of the physical state of the basic unit on the construction process. According to the characteristics of the dam project, the information of the spatial constraint and the physical impact coefficient is introduced and mapped into the dynamic space-time segmented decision of the dam to form a more accurate construction constraint system, realizing three-dimensional collaborative modeling of time, space, and physical properties in the construction process.

[0056] In one embodiment, the degree of satisfaction of the spatial constraint is determined according to the geometric parameters of the basic unit, including the following steps:

[0057] Obtaining the spatial constraint rule;

[0058] Determining the degree of satisfaction of the spatial constraint of the basic unit according to the geometric parameters of the basic unit and the spatial constraint rule;

[0059] The spatial constraint rule at least includes:

[0060] Gravity conduction constraint: the basic unit of the upper layer can be activated only when the strength of the lower layer pouring block reaches the standard (such as not less than 80% of the design strength).

[0061] Joint alignment constraint: the misalignment distance of adjacent dam segments at the same elevation pouring block is not less than a preset distance, which can be set according to experience or specific business requirements, such as 50 cm. Whether the joint alignment constraint is satisfied can be checked through the geometric parameters of the three-dimensional model of the dam.

[0062] Construction equipment constraint: the number of pouring blocks simultaneously constructed within the coverage radius of the tower crane does not exceed a preset number, which can be set according to experience or specific business requirements, such as 3. Whether the construction equipment constraint is satisfied can be analyzed in real time in combination with GIS (Geographic Information System) information.

[0063] For example, a spatial constraint knowledge base is established according to the spatial constraint rule, and the degree of satisfaction of the spatial constraint is calculated for the basic unit i The degree of satisfaction of the spatial constraint , reference is as follows:

[0064] ; (1)

[0065] In one embodiment, the basic unit is calculated by the following formula i Physical influence coefficient P i :

[0066] ; (2)

[0067] in, f j For the j physical parameters, w j For the j The weight corresponding to each physical parameter, f j,min 、 f j,max For the j The minimum and maximum values ​​in the historical data corresponding to the physical parameters, m is the number of physical parameters.

[0068] In one embodiment, the method may further include the following steps:

[0069] If the physical influence coefficient of the basic unit exceeds a preset threshold, the upper limit of the time window of the basic unit is updated according to the physical influence coefficient.

[0070] The preset threshold can be set based on experience or specific business needs, such as 0.7. When the physical impact coefficient of a basic unit exceeds the preset threshold, the upper limit of the time window of the basic unit can be extended, such as by referring to the following formula:

[0071] T u ' = T u × (1 + k × P i );(3)

[0072] in, T u 、 T u ' are the upper limits of the time window before and after the update, k The adjustment coefficient can be set according to experience or specific business needs, such as 0.3 by default. In one embodiment, the formula (3) can be P i Replace withP i -P th ( P th is the preset threshold).

[0073] In the embodiment of the present disclosure, construction-related data or monitoring data can be collected in real time through the deployed Internet of Things sensor network to obtain geometric parameters (such as position) and physical parameters (such as temperature and stress), periodically update the spatial constraint satisfaction and physical influence coefficient of the basic unit, and timely adjust the basic units with low spatial constraint satisfaction or large physical influence coefficient.

[0074] According to the time window of the basic unit, the degree of satisfaction of the spatial constraints, and the physical influence coefficient, a segmented growth plan matrix can be generated. , where n is the number of basic units, and 6 is the column dimension, including the third unit identifier, planned duration, time window lower limit, time window upper limit, spatial constraint satisfaction degree, and physical impact coefficient.

[0075] Continue to refer Figure 1 ,In step S140, the segmented growth plan matrix is ​​bound to the three-dimensional model of the dam to form a dynamic growth visualization model.

[0076] The segmented growth plan matrix can be imported into the 3D model. The segmented growth plan matrix includes information about each basic unit, which can be bound to each basic unit in the 3D model, such as by the third unit identifier of the basic unit, to form a dynamic growth visualization model. A timeline can be set in the dynamic growth visualization model, allowing users to adjust the viewing time. Based on the time window in the segmented growth plan matrix, the status of each basic unit at the viewing time can be determined, and the corresponding model status can be displayed, thus mapping the digital twin model of the dam to the actual situation. In addition, other data can be bound to the 3D model on a per-unit basis for easier viewing. This other data includes, but is not limited to, geometric parameters (such as volume, coordinates, and formwork type), material parameters (such as slump and initial setting time), and process parameters (such as vibration time and curing cycle).

[0077] In one embodiment, the three-dimensional model can be divided into basic grids (such as 1m×1m×1m cube grids) to establish a dam growth space index. The construction process is divided into time slices (such as 15 minutes as a time slice) according to the construction plan accuracy, and a timeline driven queue TQ is generated. t 0, t 1,…, t x}, t 0. t1 and so on represent each time slice, which is used to establish the time index of dam growth. Users can view it in units of basic grids and time slices. The system displays the corresponding basic units based on the relationship between basic grids, time slices and basic units.

[0078] Continue to refer Figure 1 In step S150, multiple dam characteristic data of the first time are obtained, the dam characteristic data are processed using the sequence model, and based on the preset optimization target, the optimal basic unit combination of the second time is output, and the optimal basic unit combination is displayed through the dynamic growth visualization model.

[0079] The first time can include historical time or the current time, while the second time can include future time, such as three future time slices. Dam characteristic data refers to one or more types of data related to the construction process or construction decision-making. Examples include time series characteristics (such as daily pouring volume and equipment utilization), environmental characteristics (how temperature and rainfall affect concrete setting rate), and quality characteristics (rebound strength test values). Dam characteristic data can also include data on basic units, such as geometric and physical parameters, construction-related data, and monitoring data.

[0080] Sequence models are machine learning models used to process serialized information, such as recurrent neural networks (RNNs), long short-term memory networks (LSTMs), and gated recurrent units (GRUs). They can learn sequence information from data and predict current or future states based on this sequence information.

[0081] In one embodiment, dam characteristic data (e.g., a sequence of dam characteristic data at a first time) is input into a sequence model, which then outputs predicted dam characteristic data at a second time. Based on the predicted dam characteristic data at the second time, one or more basic unit combinations corresponding to the second time are determined. These basic unit combinations are those that satisfy construction-related rules (e.g., spatial constraints and conflict rules) at the second time. Based on a preset optimization objective, the system then determines the optimal basic unit combination.

[0082] In one embodiment, the preset optimization objectives include: minimizing the total construction period, which can be expressed as min∑ Ti , Ti Indicates the construction time or planned duration of the basic unit on the critical path; maximizing resource balance, such as minimizing equipment utilization variance, can be expressed as min σ 2( U ), URepresents equipment utilization. For example, for each basic unit combination corresponding to the second time, the system can deduce its complete construction process and calculate the total construction period and resource balance (or equipment utilization variance). The basic unit combination with the shortest total construction period and the highest resource balance is selected as the optimal basic unit combination corresponding to the second time. For example, a comprehensive score of the total construction period and resource balance is calculated based on preset weights, and the one with the highest score is selected as the optimal basic unit combination. The optimal basic unit combination is displayed through a dynamic growth visualization model, such as displaying the dynamic growth status corresponding to the optimal basic unit combination.

[0083] In one embodiment, the sequence model can include an LSTM with an attention mechanism. An attention module can be added to the LSTM to calculate and optimize the weights between different basic units (or processes), the weights between each basic unit (or process) and the dam as a whole, and to improve the weights corresponding to key nodes (or key processes). For example, an attention module can be added to the encoding portion of the LSTM. After inputting dam feature data into the LSTM, it is encoded according to the basic unit or process dimensions. Feature mapping is then performed in the attention module based on the attention weights to enhance features related to key nodes or key processes. This can then be used to output predicted dam feature data through time-series processing, helping to improve prediction accuracy and computational efficiency.

[0084] In one embodiment, historical dam characteristic data can be serialized into sample data and label data. For example, dam characteristic data from a continuous period of y historical time can be selected, with the first portion of the data (e.g., the dam characteristic data from the first y-3 historical time periods) used as sample data, and the second portion of the data (e.g., the dam characteristic data from the last three historical time periods) used as label data. A sequence model can be trained based on this data to obtain a usable sequence model.

[0085] In one embodiment, the method further comprises the following steps:

[0086] Obtain monitoring data of the construction process;

[0087] If the monitoring data determines that there is a first basic unit that triggers the conflict rule, a second basic unit is determined at a non-critical node at the same elevation as the first basic unit;

[0088] The time window is updated according to the first basic unit and the second basic unit, and an adjustment scheme is generated based on the updated time window.

[0089] For example, in addition to the above space constraints, you can also establish process constraints as follows:

[0090] Set strong dependencies for critical path processes (such as dam foundation consolidation grouting) (if the previous process is not completed, the subsequent process is locked); non-critical nodes are allowed a time window fluctuation range of ±10% (or other values ​​determined based on experience and specific business needs); establish process conflict resolution rules, as shown in Table 2:

[0091] Table 2 Process conflict resolution rules

[0092]

[0093] When monitoring data triggers a conflict rule, such as a 15% delay in concrete supply, the system first identifies the relevant basic unit, referred to as the first basic unit. It then searches for alternative basic units, known as second basic units, such as those at non-critical nodes at the same elevation. The system then updates the time window based on the first and second basic units, reassesses the impact on the construction period, and generates an adjustment plan. The conflict area can be visualized, for example, by highlighting the affected basic unit in red. This ensures smooth construction progress.

[0094] The following uses a hydropower station gravity dam as an example to illustrate the dynamic growth visualization modeling method of the dam:

[0095] First, a 3D model of the gravity dam is created in the 3D modeling software, and then it is divided into dimensions such as structure and process. Figure 3 The basic unit formed after the division is shown. The three-dimensional model after division is exported in the form of basic units, retaining relevant information (such as time window, etc.) to provide a model basis for subsequent dynamic growth. Figure 4 As shown, a three-dimensional model is imported into the WebGIS platform (a web-based GIS platform), and the entity objects in the platform are bound to the third unit identifier of the basic unit, and a mapping relationship between the basic unit and the entity object is established to realize the real-time binding of construction-related data (such as pouring completion) and the three-dimensional model. The timeline is set in conjunction with the construction progress, and the data collected in a certain time period is converted into a standard format file with id (identifier, such as the third unit identifier), availability (time window), label (unit label), path (path) and position (position) as basic attributes. For example, a CZML (Cesium Zoomable Markup Language, Cesium Visual Markup Language) format file can be formed on the Cesium (a data visualization framework) platform. This realizes the generation of dynamic growth model data. The sliding timeline supports jumping to any construction time point and automatically loads the corresponding basic unit to display the real-time status of the model. As shown Figure 5 The state of the model at different points in time is shown.

[0096] The disclosed embodiment supports dynamic rendering of a large number of basic units (e.g., more than 100,000), can achieve smooth rendering on conventionally configured computer terminals, and can meet the needs of on-site mobile terminal use. Figure 6 As shown, the dynamic growth visualization model can be associated with security monitoring information in real time. For example, the user can select a point in the model and view the monitoring information. The system can trigger the display of one or more monitoring information of the point in the form of a window (such as Figure 6 The A05-TP-01 surface displacement monitoring value of the measuring point in the dam is used to realize the three-dimensional visualization of safety monitoring information, providing a full range of information support for the safety operation analysis and health diagnosis of the gravity dam. It also supports viewing drawings and other related data. For example, users can use Figure 6 The "Click to View" function on the right side of the drawing interface triggers the pop-up of related engineering drawings, thereby improving user convenience.

[0097] Through heterogeneous constraint fusion modeling, structural mechanics constraints (such as gravity conduction), construction process constraints (such as joint rules), and resource scheduling constraints (such as equipment radius) are unified into the rule engine, achieving multi-dimensional collaboration among design, construction, and resources. By constructing a spatiotemporal integrated segmented growth plan matrix, a quantitative fusion of temporal, spatial, and physical constraints is achieved, improving the adaptability of construction plans to complex working conditions. Integrating digital twins to drive dynamic growth, a bidirectional mapping between physical construction and virtual model growth is established. Construction-related data such as on-site pouring completion is synchronized to the virtual model in real time. The virtual model simulates the optimal basic unit combination (i.e., the optimal growth sequence) to reversely guide construction scheduling, enhancing the scientific nature of construction scheduling and decision-making, and improving efficiency.

[0098] The embodiment of the present disclosure also provides a dam dynamic growth visualization modeling device. Figure 7 As shown, the dam dynamic growth visualization modeling device 700 may include the following modules:

[0099] The basic unit construction module 710 is configured to divide the dam into a plurality of structural units according to the three-dimensional structure, divide the dam construction process into a plurality of process units according to the process, and determine the basic unit of the dam dynamic process based on the combination of the structural units and the process units;

[0100] The time window determination module 720 is configured to divide the basic unit into key nodes and non-key nodes based on the logical relationship between different processes, process parameters, and the total construction period information of the construction process, and determine the time window of the basic unit; the time window of the key node has no floating space, while the time window of the non-key node has floating space;

[0101] A segmented growth plan matrix generation module 730 is configured to determine the degree of spatial constraint satisfaction based on the geometric parameters of the basic unit, determine the physical influence coefficient based on the physical parameters of the basic unit, and generate a segmented growth plan matrix based on the time window, spatial constraint satisfaction, and physical influence coefficient of the basic unit;

[0102] A visualization model building module 740 is configured to bind the segmented growth plan matrix to the three-dimensional model of the dam to form a dynamic growth visualization model;

[0103] The optimal basic unit combination processing module 750 is configured to obtain multiple dam characteristic data at the first time, process the dam characteristic data using a sequence model, and output the optimal basic unit combination at the second time based on a preset optimization target, and display the optimal basic unit combination through the dynamic growth visualization model.

[0104] In one embodiment, dividing the dam into a plurality of structural units according to the three-dimensional structure includes:

[0105] The dam is divided into multiple sections, each section is divided into multiple sub-sections according to the correspondence with the left bank and the right bank, each sub-section is layered, each layer is divided into one or more casting blocks, and each casting block is regarded as a structural unit.

[0106] In one embodiment, each structural unit has a first segment identifier, which is a combination of a segment number, a sub-segment number, a layer number, and a block number; each process unit has a second segment identifier, which is a process number; and the basic unit for determining the dam dynamic process based on the combination of the structural unit and the process unit includes:

[0107] The structural unit and the process unit are combined to form the basic unit, and the third segment identifier of the basic unit is determined according to the combination of the first segment identifier and the second segment identifier.

[0108] In one embodiment, dividing the basic units into key nodes and non-key nodes based on the logical relationships between different processes, process parameters, and total construction period information of the construction process, and determining the time windows of the basic units includes:

[0109] Determine the planned duration of each basic unit based on the process parameters;

[0110] Based on the logical relationship between different processes, the planned duration of each basic unit and the total construction period information, the earliest time parameter of each basic unit is forward calculated, and the latest time parameter of each basic unit is reversely calculated;

[0111] Determine the floating space according to the earliest time parameter and the latest time parameter of each basic unit, and regard the basic unit without floating space as the key node, and regard the basic unit with floating space as the non-key node;

[0112] The earliest start time in the earliest time parameter is used as the lower limit of the time window, and the latest end time in the latest time parameter is used as the upper limit of the time window to determine the time window of each basic unit.

[0113] In one embodiment, determining the degree of satisfaction of the spatial constraint according to the geometric parameters of the basic unit includes:

[0114] Get spatial constraint rules;

[0115] Determining a degree of satisfaction of a space constraint of the basic unit according to the geometric parameters of the basic unit and the space constraint rule;

[0116] The spatial constraint rules include at least:

[0117] Gravity conduction constraint: The upper basic unit can only be started when the strength of the lower cast block meets the standard;

[0118] Joint alignment constraint: The staggered distance between cast blocks at the same elevation in adjacent dam sections must not be less than the preset distance;

[0119] Construction equipment constraint: The number of casting blocks constructed simultaneously within the coverage radius of the tower crane shall not exceed the preset number.

[0120] In one embodiment, determining the physical influence coefficient according to the physical parameters of the basic unit includes:

[0121] The physical influence coefficient of the basic unit is calculated by the following formula:

[0122]

[0123] in, f j For the j physical parameters, w j For the j The weight corresponding to each physical parameter, f j,min 、 f j,max For the j The minimum and maximum values ​​in the historical data corresponding to the physical parameters, m is the number of physical parameters.

[0124] In one embodiment, the apparatus is further configured to:

[0125] If the physical influence coefficient of the basic unit exceeds a preset threshold, refer to the following formula to update the time window upper limit of the basic unit according to the physical influence coefficient;

[0126] T u ' = T u ×(1+ k × P i );

[0127] in, P i For the basic unit i The physical influence coefficient, T u 、 T u ' are the upper limits of the time window before and after the update, k is the adjustment factor.

[0128] In one embodiment, the processing of the dam characteristic data using a sequence model and outputting an optimal basic unit combination at a second time based on a preset optimization target includes:

[0129] Inputting the dam characteristic data into the sequence model, and outputting the dam characteristic prediction data at the second time through the sequence model;

[0130] One or more basic unit combinations corresponding to the second time are determined according to the dam characteristic prediction data, and the basic unit combination with the shortest total construction period and the highest resource balance is selected as the optimal basic unit combination for the second time.

[0131] In one embodiment, the apparatus is further configured to:

[0132] Acquiring monitoring data of the construction process;

[0133] If a first basic unit that triggers a conflict rule is determined to exist according to the monitoring data, a second basic unit is determined among non-critical nodes at the same elevation as the first basic unit;

[0134] A time window is updated according to the first basic unit and the second basic unit, and an adjustment scheme is generated based on the updated time window.

[0135] The specific details of each part of the above-mentioned device have been described in detail in the implementation method part. The undisclosed details can be found in the implementation method part, so they will not be repeated here.

[0136] It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0137] The embodiments of the present disclosure further provide a computer program product, which includes a computer program, and implements the above method when the computer program is executed by a processor.

[0138] In one embodiment, a computer program product may be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The computer-readable storage medium may be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid state drive (SSD), and the like. Exemplarily, the computer program product may be implemented as a non-volatile storage medium storing the computer program, such as a read-only memory (ROM) or NAND flash memory.

[0139] In one embodiment, the computer program product may be an intangible product containing a computer program. For example, the computer program product may be implemented as a virtual digital product, such as an executable file or installation package storing the computer program.

[0140] The code of a computer program can be written in one or more programming languages, such as C, Java, C++, etc. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device can be connected to the user's computing device via any type of network, such as a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., via an internet connection provided by a carrier).

[0141] Computer programs can be carried or transmitted through electrical, magnetic, optical, electromagnetic, infrared and other signals. Electronic devices can convert signals carrying computer programs into digital signals, and then run the computer programs. When a computer program runs on an electronic device, its code is used to enable the electronic device to execute (more specifically, it can enable the processor of the electronic device to execute) the method steps of various exemplary embodiments of the present disclosure, for example: Step S110, divide the dam into multiple structural units according to the three-dimensional structure, divide the construction process of the dam into multiple process units according to the process, and determine the basic unit of the dam dynamic process based on the combination of the structural unit and the process unit; Step S120, divide the basic unit into key nodes and non-key nodes based on the logical relationship between different processes, process parameters and the total construction period information of the construction process, and determine the time window of the basic unit; the time window of the key node has no floating space, The time window of non-critical nodes has floating space; step S130, determine the degree of satisfaction of spatial constraints according to the geometric parameters of the basic unit, determine the physical influence coefficient according to the physical parameters of the basic unit, and generate a segmented growth plan matrix according to the time window, spatial constraint satisfaction degree and physical influence coefficient of the basic unit; step S140, bind the segmented growth plan matrix to the three-dimensional model of the dam to form a dynamic growth visualization model; step S150, obtain multiple dam characteristic data at the first time, use the sequence model to process the dam characteristic data, and output the optimal basic unit combination at the second time based on the preset optimization target, and display the optimal basic unit combination through the dynamic growth visualization model.

[0142] Implementing this method using a computer program, the dam and its construction process are divided into basic units based on structural and process dimensions, forming a digital representation of the dam's dynamic growth process. By calculating and quantifying the time window, spatial constraint satisfaction, and physical influence coefficients, a time-space integrated segmented growth plan matrix is ​​constructed. This matrix is ​​then bound to a three-dimensional model to generate a dynamic growth visualization. This enables the modeling and visualization of the dam's dynamic growth process. By integrating digital twin technology to establish a bidirectional mapping between physical construction and virtual model growth, the optimal basic unit combination simulated based on the virtual model can be used to reverse-engineer construction scheduling, enhancing the scientific nature of construction scheduling and decision-making, and improving efficiency.

[0143] Embodiments of the present disclosure also provide an electronic device. The electronic device may include a processor and a memory. The memory stores executable instructions for the processor, such as a computer program. The processor executes the executable instructions to perform the method steps of various exemplary embodiments of the present disclosure.

[0144] Reference below Figure 8 , the electronic device is exemplarily described in the form of a general-purpose computing device. It should be understood that Figure 8The electronic device 800 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0145] like Figure 8 As shown, the electronic device 800 may include a processor 810 , a memory 820 , a bus 830 , an I / O (input / output) interface 840 , and a network adapter 850 .

[0146] The memory 820 may include volatile memory, such as RAM 821 and cache unit 822, and may also include non-volatile memory, such as ROM 823. The memory 820 may also include one or more program modules 824. Such program modules 824 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. For example, the program modules 824 may include the modules in the aforementioned devices.

[0147] The processor 810 may include one or more processing units. For example, the processor 810 may include an AP (Application Processor), a modem processor, a GPU (Graphics Processing Unit), an ISP (Image Signal Processor), a controller, an encoder, a decoder, a DSP (Digital Signal Processor), a baseband processor and / or an NPU (Neural-Network Processing Unit) and other processing units.

[0148] The processor 810 can be used to execute the executable instructions stored in the memory 820, which can include the method steps of various exemplary embodiments of the present disclosure, such as: step S110, dividing the dam into multiple structural units according to the three-dimensional structure, dividing the construction process of the dam into multiple process units according to the process, and determining the basic unit of the dam dynamic process based on the combination of the structural unit and the process unit; step S120, dividing the basic unit into key nodes and non-key nodes based on the logical relationship between different processes, process parameters and the total construction period information of the construction process, and determining the time window of the basic unit; the time window of the key node has no floating space, and the time window of the non-key node has no floating space. The window has floating space; step S130, determining the degree of satisfaction of the spatial constraints according to the geometric parameters of the basic unit, determining the physical influence coefficient according to the physical parameters of the basic unit, and generating a segmented growth plan matrix according to the time window, the degree of satisfaction of the spatial constraints, and the physical influence coefficient of the basic unit; step S140, binding the segmented growth plan matrix with the three-dimensional model of the dam to form a dynamic growth visualization model; step S150, obtaining multiple dam feature data at the first time, processing the dam feature data using a sequence model, and outputting the optimal basic unit combination at the second time based on the preset optimization target, and displaying the optimal basic unit combination through the dynamic growth visualization model.

[0149] Based on the execution of the above method by processor 810, the dam and its construction process are divided into basic units based on structural and process dimensions, forming basic digital carrier units that represent the dam's dynamic growth process. By calculating and quantifying the integration of time windows, spatial constraint satisfaction, and physical influence coefficients, a time-space integrated segmented growth plan matrix is ​​constructed and bound to the three-dimensional model to generate a dynamic growth visualization model. This enables the modeling and display of the dam's dynamic growth process. By combining digital twin technology to establish a bidirectional mapping between physical construction and virtual model growth, the optimal basic unit combination simulated based on the virtual model can be used to reversely guide construction scheduling, improve the scientific nature of construction scheduling and decision-making, and enhance efficiency.

[0150] The bus 830 is used to realize the connection between different components of the electronic device 800 and may include a data bus, an address bus, and a control bus.

[0151] The electronic device 800 can communicate with one or more external devices 900 (eg, a keyboard, a mouse, an external controller, etc.) through the I / O interface 840 .

[0152] The electronic device 800 can communicate with one or more networks, such as a network adapter 850, which can provide mobile communication solutions such as 3G / 4G / 5G, or wireless communication solutions such as wireless local area networks, Bluetooth, near field communication, etc. The network adapter 850 can communicate with other modules of the electronic device 800 through the bus 830.

[0153] Although Figure 8 Other hardware and / or software modules can also be provided in the electronic device 800, including but not limited to: displays, microcode, device drivers, redundant processors, external disk drive arrays, tape drives, and data backup storage systems, etc., which are not shown in the electronic device 800.

[0154] As can be seen, the technical solutions of the present disclosure can be implemented as a method, device, system, computer program product, storage medium, electronic device, etc. Those skilled in the art can understand that various aspects of the present disclosure can be implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, such as can be referred to as "circuitry", "module" or "system".

[0155] It should be understood that the present disclosure is not limited to the specific method steps or structures described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. Those skilled in the art, based on the specific embodiments provided by the present disclosure, will easily think of other embodiments. Therefore, the specific embodiments provided by the present disclosure are only exemplary, the scope and spirit of the present disclosure are indicated by the claims, and should cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure, and include common knowledge or conventional technical means in the technical field of the present disclosure that are not disclosed by the present disclosure.

Claims

1. A dam dynamic growth visualization modeling method, characterized in that: The method comprises: The dam is divided into multiple structural units according to its three-dimensional structure, and the construction process of the dam is divided into multiple process units according to the process. The basic unit of the dam dynamic process is determined based on the combination of structural units and process units; Based on the logical relationship between different processes, process parameters and the total construction period information of the construction process, the basic unit is divided into key nodes and non-key nodes, and the time window of the basic unit is determined; the time window of the key node has no floating space, and the time window of the non-key node has floating space; Determining the degree of satisfaction of spatial constraints according to the geometric parameters of the basic unit, determining the physical influence coefficient according to the physical parameters of the basic unit, and generating a segmented growth plan matrix according to the time window, the degree of satisfaction of spatial constraints, and the physical influence coefficient of the basic unit; Binding the segmented growth plan matrix to the three-dimensional model of the dam to form a dynamic growth visualization model; Acquiring multiple dam characteristic data at a first time, processing the dam characteristic data using a sequence model, and outputting an optimal basic unit combination at a second time based on a preset optimization target, and displaying the optimal basic unit combination through the dynamic growth visualization model; The process of processing the dam characteristic data using a sequence model and outputting an optimal basic unit combination at a second time based on a preset optimization target includes: Inputting the dam characteristic data into the sequence model, and outputting the dam characteristic prediction data at the second time through the sequence model; One or more basic unit combinations corresponding to the second time are determined according to the dam characteristic prediction data, and the basic unit combination with the shortest total construction period and the highest resource balance is selected as the optimal basic unit combination for the second time.

2. The method according to claim 1, characterized in that The dam is divided into multiple structural units according to the three-dimensional structure, including: The dam is divided into multiple sections, each section is divided into multiple sub-sections according to the correspondence with the left bank and the right bank, each sub-section is layered, each layer is divided into one or more casting blocks, and each casting block is regarded as a structural unit.

3. The method according to claim 2, characterized in that Each structural unit has a first segment identifier, which is a combination of a segment number, a sub-segment number, a layer number, and a block number; each process unit has a second segment identifier, which is a process number; and the basic unit for determining the dam dynamic process based on the combination of the structural unit and the process unit includes: The structural unit and the process unit are combined to form the basic unit, and a third segment identifier of the basic unit is determined according to a combination of the first segment identifier and the second segment identifier.

4. The method according to claim 1, wherein The step of dividing the basic unit into key nodes and non-key nodes based on the logical relationship between different processes, process parameters, and the total construction period information of the construction process, and determining the time window of the basic unit includes: Determine the planned duration of each basic unit based on the process parameters; Based on the logical relationship between different processes, the planned duration of each basic unit and the total construction period information, the earliest time parameter of each basic unit is forward calculated, and the latest time parameter of each basic unit is reversely calculated; Determine the floating space according to the earliest time parameter and the latest time parameter of each basic unit, and regard the basic unit without floating space as the key node, and regard the basic unit with floating space as the non-key node; The earliest start time in the earliest time parameter is used as the lower limit of the time window, and the latest end time in the latest time parameter is used as the upper limit of the time window to determine the time window of each basic unit.

5. The method according to claim 1, wherein Determining the degree of satisfaction of the spatial constraint according to the geometric parameters of the basic unit includes: Get spatial constraint rules; Determining a degree of satisfaction of a space constraint of the basic unit according to the geometric parameters of the basic unit and the space constraint rule; The spatial constraint rules include at least: Gravity conduction constraint: The upper basic unit can only be started when the strength of the lower cast block meets the standard; Joint alignment constraint: The staggered distance between cast blocks at the same elevation in adjacent dam sections must not be less than the preset distance; Construction equipment constraint: The number of casting blocks constructed simultaneously within the coverage radius of the tower crane shall not exceed the preset number.

6. The method according to claim 1, characterized in that Determining the physical influence coefficient according to the physical parameters of the basic unit includes: The physical influence coefficient of the basic unit is calculated by the following formula: ； in, P i For the basic unit i The physical influence coefficient, f j For the j physical parameters, w j For the j The weight corresponding to each physical parameter, f j,min 、 f j,max For the j The minimum and maximum values ​​in the historical data corresponding to the physical parameters, m is the number of physical parameters.

7. The method according to claim 6, characterized in that The method further comprises: If the physical influence coefficient of the basic unit exceeds a preset threshold, refer to the following formula to update the time window upper limit of the basic unit according to the physical influence coefficient; T u ' = T u × (1 + k × P i )； in, P i For the basic unit i The physical influence coefficient, T u 、 T u ' are the upper limits of the time window before and after the update, k is the adjustment factor.

8. The method according to any one of claims 1 to 7, characterized in that The method further comprises: Acquiring monitoring data of the construction process; If a first basic unit that triggers a conflict rule is determined to exist according to the monitoring data, a second basic unit is determined among non-critical nodes at the same elevation as the first basic unit; A time window is updated according to the first basic unit and the second basic unit, and an adjustment scheme is generated based on the updated time window.

9. A dam dynamic growth visualization modeling device, characterized in that: The device comprises: A basic unit construction module is configured to divide the dam into a plurality of structural units according to the three-dimensional structure, divide the dam construction process into a plurality of process units according to the process, and determine the basic unit of the dam dynamic process based on the combination of the structural units and the process units; A time window determination module is configured to divide the basic unit into key nodes and non-key nodes based on the logical relationship between different processes, process parameters, and the total construction period information of the construction process, and determine the time window of the basic unit; the time window of the key node has no floating space, while the time window of the non-key node has floating space; a segmented growth plan matrix generation module configured to determine a degree of spatial constraint satisfaction according to geometric parameters of the basic unit, determine a physical influence coefficient according to physical parameters of the basic unit, and generate a segmented growth plan matrix according to the time window, spatial constraint satisfaction, and physical influence coefficient of the basic unit; a dynamic growth visualization model construction module, configured to bind the segmented growth plan matrix with the three-dimensional model of the dam to form a dynamic growth visualization model; an optimal basic unit combination processing module configured to obtain a plurality of dam characteristic data at a first time, process the dam characteristic data using a sequence model, and output an optimal basic unit combination at a second time based on a preset optimization target, and display the optimal basic unit combination through the dynamic growth visualization model; The process of processing the dam characteristic data using a sequence model and outputting an optimal basic unit combination at a second time based on a preset optimization target includes: Inputting the dam characteristic data into the sequence model, and outputting the dam characteristic prediction data at the second time through the sequence model; One or more basic unit combinations corresponding to the second time are determined according to the dam characteristic prediction data, and the basic unit combination with the shortest total construction period and the highest resource balance is selected as the optimal basic unit combination for the second time.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when the computer program is executed by a processor.

11. An electronic device, characterized in that: include: processor; as well as a memory for storing executable instructions of the processor; The processor is configured to perform the method according to any one of claims 1 to 8 by executing the executable instructions.

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