Water conservancy project design earthwork volume measuring and calculating method based on BIM

Abstract

The invention specifically relates to a BIM-based hydraulic engineering design earthwork volume calculation method, and relates to the technical field of hydraulic engineering design, and the method comprises the steps: generating a cross-regional scheduling instruction through a high layer, and carrying out the coevolution process of intra-regional precise optimization and cost feedback iteration through a bottom layer until the overall total cost is converged, and obtaining an optimal cross-regional scheduling and intra-regional deployment scheme. According to the method, qualitative engineering constraints such as soil matching, construction time sequence and transport distance economy are converted into quantifiable transport network graph theory rules such as effective edge filtering, time sequence verification and flow limitation, and it is ensured that the measurement and calculation process strictly conforms to the actual construction logic; the risk that a deployment scheme is not feasible due to the fact that constraint consideration is not comprehensive in a traditional method is avoided from the source, and double improvement of measurement and calculation precision and construction adaptability is achieved.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering design technology, and in particular to a method for calculating earthwork volume in water conservancy engineering design based on BIM. Background Technology

[0002] In the design process of water conservancy projects (such as long-distance water transfer projects, reservoir and dam projects, and river regulation projects), the calculation and optimization of earthwork volume is one of the core links, and its accuracy and rationality directly affect the project investment, construction progress and project quality.

[0003] Traditional methods for calculating earthwork volume in water conservancy projects mainly include the grid method, triangular network method, and cross-section method. These methods have the following shortcomings: Traditional methods are difficult to accurately characterize the earthwork distribution characteristics under complex terrain conditions, and cannot effectively integrate multi-dimensional constraint information such as soil quality, haul distance, and construction sequence, resulting in deviations between the calculation results and actual construction needs. Most of these approaches only focus on the simple balance of earthwork volume, without fully considering actual engineering constraints such as soil quality matching (e.g., specific requirements for soil quality in the filling area), construction sequence (e.g., the logical relationship of excavation before backfilling), and transportation economy, which can easily lead to infeasible allocation plans.

[0004] In recent years, BIM technology has begun to be applied to earthwork volume measurement in water conservancy projects due to its advantages of visualization, parameterization, and collaboration. However, existing BIM-related methods still have shortcomings: on the one hand, there is no effective correlation mechanism between engineering constraints and BIM models, and it is difficult to quantify and integrate constraints into the measurement process; on the other hand, there is a lack of efficient parallel computing architecture for large-scale projects, which makes it impossible to balance measurement accuracy and computational efficiency.

[0005] Therefore, there is an urgent need for a method that can integrate BIM technology, accurately incorporate multi-dimensional engineering constraints, and efficiently solve large-scale earthwork volume measurement and allocation problems. Summary of the Invention

[0006] The purpose of this invention is to propose a BIM-based method for calculating earthwork volume in water conservancy engineering design in order to solve the above-mentioned problems.

[0007] To achieve the above objectives, the present invention adopts the following technical solution: BIM-based earthwork volume calculation methods for water conservancy engineering design include: By gridding the engineering area, extracting attributes, and constructing the transportation network topology, the physical engineering area is transformed into a mathematical model that can be processed by a computer. Transform engineering constraints into graph theory rules for transportation networks; Logical partitioning is performed based on terrain / segment, and a collaborative architecture is initialized between a high-level genetic algorithm scheduler and a low-level partition parallel accurate solution engine. Through a collaborative evolutionary process of high-level generation of cross-regional scheduling instructions, low-level parallel execution of precise optimization within regions, and cost feedback iteration, until the total global cost converges, the optimal cross-regional scheduling and intra-regional allocation scheme is obtained. After decoding and conflict verification of the optimal solution, it is integrated into a global earthwork allocation master plan, and the output is a visual engineering result.

[0008] Preferably, the process of transforming the physical engineering area into a computer-processable mathematical model through engineering area gridding, attribute extraction, and transportation network topology construction specifically includes: Based on the accuracy requirements of engineering design and the complexity of terrain, the grid type is selected; Each grid extends vertically, with the upper boundary being the design elevation for backfilling and the lower boundary being the design elevation for excavation, forming a closed columnar unit, which serves as the smallest unit for earthwork calculation. For each columnar unit, calculate and store the net earthwork volume, dominant soil type, spatial coordinates, and management attributes to form a standardized database.

[0009] Preferably, the method further includes: Based on the traffic planning in the engineering construction organization design, all paths that can be used for earthwork transportation are abstracted into a weighted directed graph; Define the nodes and edges of the graph to form a complete transportation network: Node classification: Source point: The center point of all cut grid cells with positive net earthwork volume, or the entrance / exit of a concentrated cut area; Convergence point: The center point of all fill grid units with negative net earthwork volume, or the entrance / exit of concentrated fill areas (such as roadbeds and embankments); Transfer points: material storage yards and spoil heaps used for temporary earthwork stockpiling, as well as road intersections and transportation hubs; Definition of an edge: Each edge corresponds to an actual transportation segment, and its direction is consistent with the direction of traffic on the segment; Edge weights: Calculated using a composite cost function, the formula is as follows: .

[0010] Preferably, the process of transforming engineering constraints into graph theory rules for transportation networks specifically includes: Add soil tags to each source point; Add an allowable soil set for each sink point; An edge is marked as valid only if the soil label of the source point belongs to the allowed soil set of the sink point; otherwise, it is marked as invalid. Based on engineering experience or cost analysis, the maximum allowable transport distance is set. ; Iterate through all edges in the transportation network, calculate the shortest path length from the source to the sink, and if the shortest path length exceeds... If so, all edges between the source and sink are deleted directly, and invalid transport paths are removed from the network; When searching for a path, the optimization algorithm selects the path with the lowest weight. Add the earliest excavation time to each source point and the latest excavation completion time ; Add the earliest backfill time to each remittance point and the latest backfill completion time ; For the source point to the remittance point The transportation route must meet the following requirements: ; ; Among them, the source point to the remittance point The transportation time.

[0011] Preferably, the method further includes: Treat each partition as a supernode and calculate the total excavation volume for that partition. Total fill volume ; Define partition self-balancing coefficient The amount of excavation that needs to be processed within the partition is The permitted excavation volume transferred across regions is ; Similarly, the amount of fill that needs to be handled within each zone is... The permitted amount of fill material to be transferred across regions is ; In the transportation network, a flow restriction attribute is added to the cross-regional edge, so that the amount of earthwork transferred out of the cross-regional area cannot exceed [a certain limit]. The amount of earthwork transferred from other regions shall not exceed .

[0012] Preferably, the collaborative architecture of dividing logical partitions according to terrain / segment and initializing the high-level genetic algorithm scheduler and the low-level partition parallel accurate solution engine specifically includes: The partitioning is based on the following principles: Boundaries are defined by natural terrain boundaries; and by the jurisdiction of construction sections and project departments. Control the differences in the number of grid cells and the total amount of earthwork in each zone within a preset range; After the partitioning is completed, a unique identifier is assigned to each partition, and the management attributes of the grid cell are updated to clarify the partition to which each cell belongs; Design chromosome encoding rules for genetic algorithms: Chromosome length = number of partitions × number of partitions, each gene locus represents a region from which the chromosome length is calculated. Transfer to partition The proportion of earthwork volume; Constraints: Each partition All corresponding gene loci The sum of its possible values ​​is 1.

[0013] Preferably, the method further includes: Based on a parallel computing framework, an independent underlying computing engine is launched for each partition, and the number of engines equals the number of partitions K. Receive cross-regional scheduling instructions from the high-level scheduler, and within this region, solve a small-scale earthwork allocation optimization problem that considers all fine constraints; Configure an accurate solution algorithm for the underlying engine, using linear programming or minimum cost flow algorithm; Establish a communication interface between the high-level scheduler and the low-level engine.

[0014] Preferably, the optimal cross-regional scheduling and intra-regional allocation scheme is obtained through a collaborative evolutionary process involving high-level generation of cross-regional scheduling instructions, low-level parallel execution of precise intra-regional optimization, and cost feedback iteration, until the global total cost converges. This process specifically includes: Each underlying engine performs the following operations independently and in parallel: Clearly define the volume of earthwork to be transferred in from external sources and the volume of earthwork to be transferred out from external sources for this zone; The objective function is to minimize the total transportation cost within the region, and the constraints are determined accordingly. The total transportation cost within the area is calculated using linear programming or minimum cost flow algorithms. ; Based on the inter-regional transport volume in the dispatching instructions and the weight of the inter-regional transport routes, estimate the zoning. The total cost of cross-regional transportation; Each underlying engine will account for the total cost within the region. and total cost across regions As part of the total cost of partitioning This feedback is sent to the higher-level scheduler. The higher-level scheduler aggregates the total cost of all partitions and calculates the global total cost for the current chromosome. and will As the fitness value of that chromosome; The high-level scheduler selects, crosses over, and mutates chromosomes in the population according to the evolutionary rules of the genetic algorithm to generate the next generation of the population.

[0015] Preferably, the process of decoding and conflict verification of the optimal solution and integrating it into a global earthwork allocation master plan, outputting visual engineering results, specifically includes: Extract the cross-regional scheduling instructions corresponding to the optimal chromosome and determine the final transport volume between each region; Extract detailed allocation plans for each underlying engine within the region; Global conflict verification includes path conflict verification, temporal conflict verification, and soil matching conflict verification. The verified allocation plans for each zone are spliced ​​and integrated to form a global earthwork allocation master plan, clarifying the overall cut-fill balance, the inter-zone allocation relationship, and the grid-level allocation details.

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention transforms qualitative engineering constraints such as soil matching, construction sequence, and transportation distance economy into quantifiable transportation network graph theory rules such as effective edge filtering, time sequence verification, and flow restriction. This ensures that the calculation process strictly conforms to the actual construction logic, fundamentally avoiding the risk of infeasible allocation schemes caused by incomplete constraint consideration in traditional methods, and achieving a dual improvement in calculation accuracy and construction adaptability.

[0017] 2. This invention scientifically partitions large-scale earthwork problems into smaller sub-problems based on principles such as terrain continuity and management consistency. The underlying engine solves in parallel, while the high-level genetic algorithm optimizes collaboratively, transforming the computation time from exponential growth to near linear growth, efficiently meeting the timeliness requirements of engineering design. At the same time, it outputs various types of engineering results, including BIM 3D dynamic flow diagrams, bills of quantities / costs, and construction plans. The visualized model can be directly integrated with construction organization and management, completely solving the pain points of traditional methods that produce single results and theoretically optimal results that are difficult to implement, significantly improving the engineering application value of the calculation results. Attached Figure Description

[0018] Further details, features, and advantages of this application are disclosed in the following description of exemplary embodiments in conjunction with the accompanying drawings, in which: Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0019] Several embodiments of this application will now be described in more detail with reference to the accompanying drawings to enable those skilled in the art to implement this application. This application may be embodied in many different forms and for various purposes and should not be limited to the embodiments set forth herein. These embodiments are provided to make this application thorough and complete, and to fully convey the scope of this application to those skilled in the art. The embodiments described do not limit this application.

[0020] Unless otherwise defined, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It will be further understood that terms such as those defined in commonly used dictionaries shall be interpreted as having a meaning consistent with their meaning in the relevant field and / or the context of this specification, and shall not be interpreted in an idealized or overly formal sense unless expressly defined herein.

[0021] Example 1 Its specific implementation method is combined with the appendix Figure 1 Please provide a detailed explanation.

[0022] Appendix Figure 1 The flowchart of the earthwork volume calculation method for water conservancy engineering design based on BIM provided in the embodiments of the present invention shows the complete steps from converting the physical engineering area into a computer-processable mathematical model to decoding the optimal solution, checking for conflicts, and integrating it into a global earthwork allocation map, outputting visual engineering results.

[0023] In this embodiment, it includes: By gridding the engineering area, extracting attributes, and constructing the transportation network topology, the physical engineering area is transformed into a computer-processable mathematical model containing information such as earthwork volume, soil quality, and transportation costs. Specifically, it includes: Based on the engineering design accuracy requirements (such as 10m×10m, 20m×20m) and terrain complexity, the following grid types are selected: square regular grids are used in areas with gentle terrain, and triangular mesh (TIN) is used to divide areas with drastic terrain undulations into irregular grids. Each grid extends vertically (Z-axis), with the upper boundary being the design elevation for backfilling and the lower boundary being the design elevation for excavation, forming a closed columnar unit, which serves as the smallest unit for earthwork calculation. For each columnar unit, the net earthwork volume, dominant soil type, spatial coordinates, and management attributes are calculated and stored using topographic survey data, geological reports, etc., forming a standardized database. Net earthwork volume: Calculated by the volume of the column. Positive values ​​indicate excavation (which needs to be transported out), negative values ​​indicate fill (which needs to be purchased / transferred in), and zero values ​​indicate no earthwork.

[0024] Dominant soil type: determined according to the geological exploration report, such as clay, sand, silt, rock, etc., and its physical and mechanical parameters (such as compaction coefficient, moisture content, bearing capacity) are stored together.

[0025] Spatial coordinates: Record the three-dimensional coordinates (X, Y, Z) of the center point of the columnar unit, which serve as the basis for subsequent calculations of transport distance and elevation difference.

[0026] Management attributes: The labeling unit includes the construction section, administrative division, and terrain zoning (such as piedmont area, plain area, river valley area), which provides a basis for subsequent zoning calculations.

[0027] Based on the traffic planning (including temporary construction roads, existing highways, railways, and river navigation routes) in the engineering construction organization design, all paths that can be used for earthwork transportation are abstracted into a weighted directed graph. Define the nodes and edges of the graph to form a complete transportation network: Node classification: SourceNode: The center point of all cut grid cells with positive net earthwork volume, or the entrance / exit of a concentrated cut area (such as a material yard).

[0028] SinkNode: The center point of all fill grid cells with negative net earthwork volume, or the entrance / exit of concentrated fill areas (such as roadbeds and embankments).

[0029] Transfer Node: A storage yard or spoil heap used for temporary earthwork stockpiling, as well as road intersections and transportation hubs (such as docks and loading / unloading points).

[0030] Definition of an edge: Each edge corresponds to an actual transportation segment, and the direction is consistent with the traffic direction of the segment (e.g., a one-way road is a one-way edge, and a two-way road is a two-way edge). Edge weights (transportation costs): Calculated using a composite cost function, the formula is as follows. Specific examples are as follows: ; The actual length of the road segment (unit: km); The basic freight rate per unit distance for this road type; This refers to the slope coefficient; This refers to the road grade coefficient; This refers to the traffic congestion coefficient. Store node, edge, and weight information as graph structure data (such as adjacency matrix and edge table) to support subsequent constraint overlay and path search.

[0031] Engineering constraints such as soil matching, haulage distance economy, construction sequence, and zonal cut-fill balance are transformed into graph theory rules for the transportation network (such as effective edge filtering, time sequence verification, and flow restriction) to ensure that optimization conforms to the actual construction situation. Specifically, it includes: Soil matching constraint transformation: Operational logic: Different fill areas (such as roadbed, embankment, and greening cover soil) have specific requirements for soil quality (such as roadbed requiring sandy soil with a compaction coefficient ≥ 0.95, and greening cover soil requiring fertile loam), so it is necessary to limit the matching between excavated soil quality and fill requirements; Add soil tags (such as labels) to each source point (excavation unit). Corresponding sandy soil Corresponding clay, Corresponding rocks); Add a permissible soil set (e.g., sink) for each sink point (fill unit). allow{ , }, Exchange Point allow{ }); Add a soil compatibility attribute to the edges of the transportation network: the corresponding edge is marked as a valid edge only if the soil label of the source node belongs to the allowed soil set of the sink node; otherwise, it is marked as an invalid edge and will be automatically filtered in subsequent optimization calculations. Transformation of transport distance and economic constraints: There is an economical transport distance threshold for earthwork transportation (e.g., if the transportation cost exceeds 30km, it is more cost-effective to purchase earthwork from outside sources). The transport range needs to be controlled through constraints to ensure the economic efficiency of the plan. Based on engineering experience or cost analysis, the maximum allowable transport distance is set. ; Traverse all edges in the transportation network and calculate the shortest path length from the source to the sink (based on the sum of the actual edge lengths). If the shortest path length exceeds... If so, all edges between the source and sink are deleted directly, and invalid transport paths are removed from the network; Economic constraints are naturally reflected in the weights of the edges (transportation costs): when searching for paths, the optimization algorithm will prioritize the path with the smallest weight (lowest cost) without adding any additional constraints. Construction sequence constraint conversion: Operational logic: Earthwork construction must follow the time sequence requirements such as excavation before backfilling and zoned sequential operations (e.g., river channel excavation must be completed in a certain area before embankment backfilling can be carried out; excavation in a certain section must be completed in the third quarter before earthwork can be transported to other sections in the fourth quarter). Construction feasibility must be ensured through time constraints. Add the earliest excavation time to each source point (excavation unit). and the latest excavation completion time (Determined by the construction schedule, accurate to the month / week); Add the earliest backfill time to each sink point (fill unit). and the latest backfill completion time ; Define the timing constraint function: for the source point to the remittance point The transportation route must meet the following requirements: ; ; Among them, the source point to the remittance point The transportation time is calculated from the shortest path length and the transportation speed; In the optimization calculation, a timing verification step is added: for each candidate transportation path, the timing constraints are first verified to see if they are met. If they are met, the path is retained; otherwise, it is discarded.

[0032] Transformation of cut-fill balance constraints in different zones: To reduce cross-regional transportation costs, each zone should prioritize achieving internal fill-cut balance, and cross-regional allocation should only be carried out when internal needs cannot be met. The proportion of earthwork flow inside and outside the zone needs to be controlled by constraints.

[0033] Treat each partition as a supernode and calculate the total excavation volume for that partition. Total fill volume ; Define partition self-balancing coefficient The amount of excavation that needs to be processed within the partition is The permitted excavation volume transferred across regions is ; Similarly, the amount of fill that needs to be handled within each zone is... The permitted amount of fill material to be transferred across regions is ; In the transportation network, a flow restriction attribute is added to the cross-regional edge, so that the amount of earthwork transferred out of the cross-regional area cannot exceed [a certain limit]. The amount of earthwork transferred from other regions shall not exceed This serves as a flow constraint for subsequent optimization calculations.

[0034] Logical partitioning is performed based on terrain / sections, and a collaborative architecture of a high-level genetic algorithm scheduler and a low-level partition parallel accurate solution engine is initialized, laying the foundation for solving large-scale problems. Specifically, it includes: The partitioning should be based on the following principles to ensure the independence and rationality of each partition: The principle of terrain continuity: Use natural terrain boundaries (such as ridges, rivers, and gullies) as boundaries to avoid splitting complete terrain units into different zones; Principle of Management Consistency: Prioritize division according to construction sections and project department jurisdiction to facilitate subsequent construction organization and coordination; Scale balance principle: Control the difference in the number of grid cells and the total amount of earthwork in each zone within a preset range (±20%) to ensure balanced parallel computing load; After the partitioning is completed, a unique identifier is assigned to each partition, and the management attributes of the grid cell are updated to clarify the partition to which each cell belongs; High-level global scheduler initialization: Genetic Algorithm (GA) is chosen as the high-level scheduling algorithm (it can also be replaced by metaheuristic algorithms such as particle swarm optimization and simulated annealing). Its core function is to generate cross-regional earthwork scheduling strategies, rather than specific grid-level allocation schemes. Design chromosome encoding rules for genetic algorithms: Chromosome length = number of partitions × number of partitions, each gene locus represents a region from which the chromosome length is calculated. Move to partition The proportion of earthwork volume; For example, gene locus A value of 0.3 indicates that the partition will be... 30% of the surplus excavation volume was transferred to the zone. ; gene locus The value is 0.7, indicating a partition. 70% of the surplus excavation volume is used internally.

[0035] Constraints: Each partition All corresponding gene loci (j=1) The sum of the values ​​of K) is 1, ensuring that all the surplus excavation volume of the partition is allocated. Initialize the genetic algorithm parameters: population size (e.g., 50-100 chromosomes), crossover probability (e.g., 0.6-0.8), mutation probability (e.g., 0.01-0.05), maximum number of iterations (e.g., 100-200 times), and convergence threshold (e.g., the global total cost change rate is <0.5% for 10 consecutive generations).

[0036] Based on parallel computing frameworks (such as Spark, Hadoop, or custom multi-threaded frameworks), start an independent underlying computing engine for each partition, with the number of engines equal to the number of partitions K; The core function of each underlying engine is to receive cross-regional scheduling instructions from the higher-level scheduler and, within its own region, solve a small-scale earthwork allocation optimization problem that considers all fine constraints (soil quality, transport distance, time sequence, flow rate). Configure accurate solution algorithms for the underlying engine: Since the problem size is greatly reduced after partitioning (e.g., the number of grid cells in a single partition is 1000~5000), linear programming (LP) or minimum cost flow (MCF) algorithms can be used to ensure that the optimization result within the partition is the theoretical optimal solution; Establish a communication interface between the high-level scheduler and the low-level engine: Downlink interface: The higher-level scheduler sends cross-region scheduling instructions to each lower-level engine; Uplink interface: The underlying engine feeds back the optimization results within the region to the upper-level scheduler (such as the total transportation cost within the region, the actual amount of cross-regional transportation demand met, and unused excavation / filling resources).

[0037] Through a collaborative evolutionary process of generating cross-regional scheduling instructions at the high level, performing precise optimization within the region in parallel at the low level, and iterating with cost feedback, until the total global cost converges, the optimal cross-regional scheduling and intra-regional allocation scheme is obtained. Specifically, it includes: The high-level global scheduler generates the population for the current iteration (i.e., a batch of cross-regional scheduling instruction schemes) according to the genetic algorithm process. The high-level scheduler synchronously sends the scheduling instructions corresponding to the same chromosome to all the underlying computing engines; Each underlying engine performs the following operations independently and in parallel: Analysis of dispatch instructions: Clarify the volume (type and scale) of earthwork to be transferred in from outside the area and the volume (type and scale) of earthwork to be transferred out from outside the area. Construct an intra-regional optimization model: with the objective function being the minimum total transportation cost within the region, and the constraints include: soil matching constraints, transportation distance constraints, time series constraints, and intra-regional cut-fill balance constraints (including inter-regional transfer in / out volumes). The solution employs precise algorithms: using linear programming or minimum cost flow algorithms, it calculates detailed plans for each excavation grid cell within the area, including which fill grid cell the excavated earth will be transferred to, which transportation route it will take, and the transportation time window, and also calculates the total transportation cost within the area. ( (for partition numbering) Calculate inter-regional transportation costs Based on the inter-regional transport volume in the dispatching instructions, and combined with the weight (cost) of the inter-regional transport routes, estimate the zoning costs. The total cost of cross-regional transportation; Each underlying engine will account for the total cost within the region. and total cost across regions As part of the total cost of partitioning This feedback is sent to the higher-level scheduler. The higher-level scheduler aggregates the total cost of all partitions and calculates the global total cost for the current chromosome. and will This serves as the fitness value for that chromosome (the higher the fitness, the better the scheme). The high-level scheduler selects chromosomes in the population according to the evolutionary rules of the genetic algorithm (retaining chromosomes with high fitness), crossovers (exchanging some gene positions to generate new chromosomes), and mutates (randomly modifying some gene positions to increase population diversity) to generate the next generation of the population. Proceed to the next iteration until any of the following convergence conditions are met: Total cost The rate of change over N consecutive generations (e.g., 10 generations) is less than a preset threshold ε (e.g., 0.5%). ; The number of iterations has reached the preset maximum number of iterations; If convergence is not achieved, return to the iteration step; if convergence is achieved, stop the iteration and select the chromosome with the highest fitness (lowest total global cost) in the current population as the optimal high-level scheduling scheme.

[0038] After decoding and conflict verification of the optimal solution, it is integrated into a global earthwork allocation master plan, and outputs engineering results such as a visualization model, a bill of quantities / costs, and a construction plan to support actual construction. Specifically, it includes: Decode the optimal high-level scheduling scheme: extract the cross-regional scheduling instructions corresponding to the optimal chromosome, and clarify the final transportation volume (type, scale, direction) between each region. Extract detailed allocation plans within each underlying engine area, including earthwork flow direction, transportation path, transportation time, and workload for each grid cell; Global conflict check: Route conflict verification: Check whether there is a road occupation conflict between cross-regional transportation routes and intra-regional transportation routes (such as the transportation flow of a temporary road exceeding its capacity at the same time). If a conflict exists, it can be resolved by fine-tuning the transportation time window (such as off-peak transportation). Timing conflict check: Check whether the earthwork transported across regions meets the timing requirements of the filling area (e.g., whether the earthwork transported is after the earliest backfilling time of the filling area). If there is a conflict, adjust the timing of cross-regional transportation. Soil quality matching conflict verification: Re-verify whether the soil quality of the cross-regional earthwork transported meets the requirements of the filling area to ensure that there is no illegal allocation; The verified allocation plans for each zone are spliced ​​and integrated to form a global earthwork allocation master plan, clarifying: Global cut-and-fill balance: total cut volume, total fill volume, total volume of inter-regional transport, and total volume of purchased / discarded waste.

[0039] Inter-regional transport relationships: the amount of transported in / out, the direction of transport, and the main transport routes for each region.

[0040] Grid-level allocation details: which fill grid the earthwork from each cut grid will flow to, and the corresponding amount of work, transportation costs, and transportation time.

[0041] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0042] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

[0043] It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely for distinguishing one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0044] It should be understood that in the various embodiments of this application, the order of the above-mentioned processes does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0045] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0046] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0047] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0048] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0049] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0050] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A method for calculating earthwork volume in water conservancy engineering design based on BIM, characterized in that, include: By gridding the engineering area, extracting attributes, and constructing the transportation network topology, the physical engineering area is transformed into a mathematical model that can be processed by a computer. Transform engineering constraints into graph theory rules for transportation networks; Logical partitioning is performed based on terrain / segment, and a collaborative architecture is initialized between a high-level genetic algorithm scheduler and a low-level partition parallel accurate solution engine. Through a collaborative evolutionary process of generating cross-regional scheduling instructions at the high level, performing precise optimization within the region in parallel at the low level, and iterating with cost feedback, until the total global cost converges, the optimal cross-regional scheduling and intra-regional allocation scheme is obtained. After decoding and conflict verification of the optimal solution, it is integrated into a global earthwork allocation master plan, and the output is a visual engineering result.

2. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 1, characterized in that, By gridding the engineering area, extracting attributes, and constructing the transportation network topology, the physical engineering area is transformed into a computer-processable mathematical model, specifically including: Based on the accuracy requirements of engineering design and the complexity of terrain, the grid type is selected; Each grid extends vertically, with the upper boundary being the design elevation for backfilling and the lower boundary being the design elevation for excavation, forming a closed columnar unit, which serves as the smallest unit for earthwork calculation. For each columnar unit, calculate and store the net earthwork volume, dominant soil type, spatial coordinates, and management attributes to form a standardized database.

3. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 2, characterized in that, Also includes: Based on the traffic planning in the engineering construction organization design, all paths that can be used for earthwork transportation are abstracted into a weighted directed graph; Define the nodes and edges of the graph to form a complete transportation network: Node classification: Source point: The center point of all cut grid cells with positive net earthwork volume, or the entrance / exit of a concentrated cut area; Convergence point: The center point of all fill grid units with negative net earthwork volume, or the entrance / exit of concentrated fill areas (such as roadbeds and embankments); Transfer points: material storage yards and spoil heaps used for temporary earthwork stockpiling, as well as road intersections and transportation hubs; Definition of an edge: Each edge corresponds to an actual transportation segment, and its direction is consistent with the direction of traffic on the segment; Edge weights: Calculated using a composite cost function, the formula is as follows: .

4. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 1, characterized in that, Transforming engineering constraints into graph theory rules for transportation networks, specifically including: Add soil tags to each source point; Add an allowable soil set for each sink point; An edge is marked as valid only if the soil label of the source point belongs to the allowed soil set of the sink point; otherwise, it is marked as invalid. Based on engineering experience or cost analysis, the maximum allowable transport distance is set. ; Iterate through all edges in the transportation network, calculate the shortest path length from the source to the sink, and if the shortest path length exceeds... If so, all edges between the source and sink are deleted directly, and invalid transport paths are removed from the network; When searching for a path, the optimization algorithm selects the path with the lowest weight. Add the earliest excavation time to each source point and the latest excavation completion time ; Add the earliest backfill time to each remittance point and the latest backfill completion time ; For the source point to the remittance point The transportation route must meet the following requirements: ； ； Among them, the source point to the remittance point The transportation time.

5. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 4, characterized in that, Also includes: Treat each partition as a supernode and calculate the total excavation volume for that partition. Total fill volume ; Define partition self-balancing coefficient The amount of excavation that needs to be processed within the partition is The permitted excavation volume transferred across regions is ; Similarly, the amount of fill that needs to be handled within each zone is... The permitted amount of fill material to be transferred across regions is ; In the transportation network, a flow restriction attribute is added to the cross-regional edge, so that the amount of earthwork transferred out of the cross-regional area cannot exceed [a certain limit]. The amount of earthwork transferred from other regions shall not exceed .

6. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 1, characterized in that, Logical partitioning based on terrain / segment, initializing the collaborative architecture of a high-level genetic algorithm scheduler and a low-level partition parallel accurate solution engine, specifically including: The partitioning is based on the following principles: Boundaries are defined by natural terrain boundaries; and by the jurisdiction of construction sections and project departments. Control the differences in the number of grid cells and the total amount of earthwork in each zone within a preset range; After the partitioning is completed, a unique identifier is assigned to each partition, and the management attributes of the grid cell are updated to clarify the partition to which each cell belongs; Design chromosome encoding rules for genetic algorithms: Chromosome length = number of partitions × number of partitions, each gene locus represents a region from which the chromosome length is calculated. Move to partition The proportion of earthwork volume; Constraints: Each partition All corresponding gene loci The sum of its possible values ​​is 1.

7. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 6, characterized in that, Also includes: Based on a parallel computing framework, an independent underlying computing engine is launched for each partition, and the number of engines equals the number of partitions K. Receive cross-regional scheduling instructions from the high-level scheduler, and within this region, solve a small-scale earthwork allocation optimization problem that considers all fine constraints; Configure an accurate solution algorithm for the underlying engine, using linear programming or minimum cost flow algorithm; Establish a communication interface between the high-level scheduler and the low-level engine.

8. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 1, characterized in that, Through a collaborative evolutionary process involving high-level generation of cross-regional scheduling instructions, low-level parallel execution of precise intra-regional optimization, and cost feedback iteration, until the global total cost converges, the optimal cross-regional scheduling and intra-regional allocation scheme is obtained, specifically including: Each underlying engine performs the following operations independently and in parallel: Clearly define the volume of earthwork to be transferred in from external sources and the volume of earthwork to be transferred out from external sources for this zone; The objective function is to minimize the total transportation cost within the region, and the constraints are determined accordingly. The total transportation cost within the area is calculated using linear programming or minimum cost flow algorithms. ; Based on the inter-regional transport volume in the dispatching instructions and the weight of the inter-regional transport routes, estimate the zoning. The total cost of cross-regional transportation; Each underlying engine will account for the total cost within the region. and total cost across regions As part of the total cost of partitioning This feedback is sent to the higher-level scheduler. The higher-level scheduler aggregates the total cost of all partitions and calculates the global total cost for the current chromosome. and will As the fitness value of that chromosome; The high-level scheduler selects, crosses over, and mutates chromosomes in the population according to the evolutionary rules of the genetic algorithm to generate the next generation of the population.

9. The method for calculating earthwork volume in water conservancy engineering design based on BIM according to claim 1, characterized in that, After decoding and conflict verification of the optimal solution, it is integrated into a global earthwork allocation master plan, outputting visual engineering results, specifically including: Extract the cross-regional scheduling instructions corresponding to the optimal chromosome and determine the final transport volume between each region; Extract detailed allocation plans for each underlying engine within the region; Global conflict verification includes path conflict verification, temporal conflict verification, and soil matching conflict verification. The verified allocation plans for each zone are spliced ​​and integrated to form a global earthwork allocation master plan, clarifying the overall cut-fill balance, the inter-zone allocation relationship, and the grid-level allocation details.

Images