Arrangement optimization method of municipal drainage pipe network

Abstract

The invention relates to the technical field of pipe network arrangement optimization, and particularly discloses a municipal drainage pipe network arrangement optimization method comprising the following steps: S1, obtaining geographic space data, hydrogeological data, planned land data and current drainage facility data of a target area, and constructing a drainage pipe network optimization basic database; s2, on the basis of the basic database, layout constraint conditions of the drainage pipe network system are determined, and the constraint conditions comprise topographic slope constraint, burial depth limitation, a pipeline avoidance area, a planned catchment partition and a discharge port position; and S3, taking the lowest total cost of the whole life cycle of the pipe network as a first optimization target, and constructing a comprehensive cost model including construction cost, operation and maintenance cost and risk cost. According to the arrangement optimization method of the municipal drainage pipe network, dynamic hydraulic performance evaluation is performed on each scheme in the optimization iteration process, and the invalid calculation time is remarkably shortened.

Description

Technical Field

[0001] This invention relates to the field of pipeline layout optimization technology, specifically a method for optimizing the layout of municipal drainage pipelines. Background Technology

[0002] Municipal drainage networks are crucial urban infrastructure, and their layout and design directly impact urban flood control, environmental protection, and operational economy. Traditional drainage network design often relies on engineers' experience, employing a trial-and-error approach to compare solutions. This is not only time-consuming and labor-intensive but also fails to achieve the best technical and economic outcome from a holistic perspective. With the development of computer technology, optimization algorithm-based network layout design methods have emerged. These methods typically use network construction costs as the objective function, employing intelligent optimization algorithms to search for the lowest-cost pipe connection and diameter combinations, significantly improving design efficiency. In practical engineering, drainage networks must not only meet economic requirements but also ensure that no flooding or pipe overload occurs under design return period rainfall. Therefore, there is an urgent need for a layout optimization method that deeply integrates economic optimization with hydraulic performance assessment and enables real-time interaction. This method should identify and eliminate substandard solutions during the optimization process and feed hydraulic problem information back to the optimization algorithm, thereby achieving efficient and reliable intelligent network design.

[0003] Existing optimization methods have significant shortcomings: On the one hand, most methods treat hydraulic performance evaluation as a post-validation step, that is, they generate schemes based on cost first and then conduct hydraulic simulation verification, resulting in a large number of schemes with substandard hydraulic performance wasting computational resources; on the other hand, hydraulic simulation often requires running the entire rainfall process, and there is a lack of early identification and termination mechanisms for schemes with obvious serious hydraulic defects, resulting in unnecessary computational overhead. At the same time, there is a lack of effective information feedback between hydraulic simulation results and optimization algorithms, making it difficult to make targeted improvements based on hydraulic performance during the optimization process. Summary of the Invention

[0004] To solve the above-mentioned technical problems, the present invention provides: a method for optimizing the layout of municipal drainage pipe networks, comprising the following steps:

[0005] S1. Obtain geospatial data, hydrogeological data, planned land use data, and existing drainage facility data of the target area to construct a basic database for drainage network optimization;

[0006] S2. Based on the aforementioned basic database, determine the layout constraints of the drainage network system. The constraints include: terrain slope constraints, burial depth restrictions, pipeline avoidance areas, planned catchment areas, and discharge outlet locations.

[0007] S3. With the lowest total cost over the entire lifecycle of the pipeline network as the primary optimization objective, a comprehensive cost model is constructed that includes construction costs, operation and maintenance costs, and risk costs.

[0008] S4. Using the comprehensive cost model as the objective function and the layout constraints as constraints, an intelligent optimization algorithm is used to iteratively solve the problem and generate multiple preliminary pipeline layout schemes that meet the constraints.

[0009] S5. Perform hydraulic simulation evaluation on the multiple preliminary pipeline layout schemes to obtain the hydraulic performance indicators of each scheme under the preset design return period rainfall.

[0010] S6. Taking the hydraulic performance indicators meeting the design requirements as the second optimization objective, the preliminary pipeline layout scheme is screened and modified to obtain the Pareto optimal solution set.

[0011] S7. Based on the multi-criteria decision analysis method, select the final recommended scheme from the Pareto optimal solution set, and output the optimized pipeline layout diagram, pipe diameter, slope and node elevation.

[0012] Preferably, in step S3, the comprehensive cost model is expressed as:

[0013]

[0014] in, For total cost, The construction cost of the i-th pipe segment is... Its annual operation and maintenance costs, The present value factor. Let be the probability of the j-th risk event occurring. The corresponding risk loss cost.

[0015] Preferably, in step S4, the intelligent optimization algorithm is a genetic algorithm or a particle swarm optimization algorithm; the process of generating a preliminary pipeline layout scheme includes: using graph theory to abstract the drainage area into a network topology structure composed of nodes and edges, and using the intelligent optimization algorithm to perform parallel optimization search on the connection relationship and pipe diameter combination of the network topology structure.

[0016] Preferably, when using intelligent optimization algorithms for iterative solutions, an adaptive mutation strategy is introduced. When the population evolution gets stuck in a local optimum, the mutation probability is increased to escape the local optimum.

[0017] Preferably, in step S5, the hydraulic simulation evaluation adopts an embedded real-time monitoring and adaptive interruption mechanism, specifically including the following steps:

[0018] S5.1 Simulation Initialization and Monitor Configuration:

[0019] An independent hydraulic simulation process is created for each preliminary pipeline layout scheme, and a real-time hydraulic performance monitor is synchronously embedded in the process. This monitor is preloaded with key performance thresholds and risk assessment rules.

[0020] S5.2 Dynamic Simulation and Real-Time Indicator Tracking:

[0021] Using the designed rainfall process curve as input, a non-steady flow dynamic simulation is performed. The real-time monitor performs the following operations at each calculation time step or every N time steps of the simulation:

[0022] a. Status capture: Capture the instantaneous hydraulic status of all pipes and manholes in real time from the simulation engine memory;

[0023] b. Calculation of process indicators: Based on the instantaneous state, calculate and update process performance indicators, including: a list of pipe sections with excessive filling degree, a list of pipe sections with unqualified flow velocity, and the cumulative overflow of each inspection well;

[0024] c. Risk warning judgment: Based on preset rules, determine whether a "catastrophic hydraulic failure" warning has been triggered;

[0025] S5.3, Adaptive Analog Interrupt:

[0026] If the real-time monitor detects that more than a preset proportion of pipe segments simultaneously experience serious hydraulic violations, it immediately sends a command to the simulation engine to interrupt the simulation process of the current scheme.

[0027] S5.4, Structured Result Output:

[0028] After the simulation process terminates, the real-time monitor integrates all process performance indicators and generates a structured hydraulic performance evaluation report object. This report object includes: simulation status, summary of core performance indicators, a list of problem pipe sections sorted by severity of violations, and a comprehensive hydraulic performance score. If the simulation is interrupted, the score is recorded as the preset lower limit of non-compliance.

[0029] Preferably, in step S5.2, the triggering rule for the "catastrophic hydraulic failure" early warning includes: for any pre-set critical infrastructure node, the water level in its inspection well exceeds the road surface elevation at its location within M consecutive calculation time steps.

[0030] Preferably, in step S6, the process of screening and modifying the preliminary pipeline layout scheme specifically includes:

[0031] Based on the comprehensive hydraulic performance scores of each scheme output in step S5.4, a preliminary screening is conducted, and schemes with scores below the passing line are eliminated.

[0032] The qualified solutions and their comprehensive cost model calculation results are input together into a multi-objective optimization algorithm to perform Pareto front search;

[0033] When optimizing the algorithm to generate a new generation of solutions, the system performs local optimization searches on the pipe diameter and slope of the corresponding network area based on the list of problem pipe segments in the hydraulic performance evaluation report of the historical solutions.

[0034] Preferably, in step S7, the multi-criteria decision analysis method is the analytic hierarchy process (AHP), and the decision criteria include economic criteria, hydraulic efficiency criteria, construction feasibility criteria, and environmental adaptability criteria. The data for the hydraulic efficiency criteria are directly derived from the hydraulic performance evaluation report object output in step S5.4.

[0035] This invention provides a method for optimizing the layout of municipal drainage pipe networks. It has the following beneficial effects:

[0036] This invention introduces embedded real-time hydraulic monitoring and an adaptive interruption mechanism to dynamically evaluate the hydraulic performance of each scheme during the optimization iteration process, significantly reducing invalid computation time. It establishes a closed-loop feedback link between hydraulic performance data and optimization algorithms, using detailed information such as the "problem pipe segment list" identified in the simulation as heuristic knowledge to guide subsequent iterations in targeted searches and corrections. This enables the optimization algorithm to more intelligently avoid performance bottlenecks, achieving efficient collaborative optimization of economic and hydraulic performance objectives on the Pareto front. Based on multi-criteria decision-making, it outputs a comprehensive optimal solution, ensuring not only the flood control safety and operational reliability of the pipeline system but also significantly improving the automation level and computational resource utilization efficiency of the overall design process. This provides strong technical support for the scientific planning and rapid design of complex drainage systems. Detailed Implementation

[0037] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] In a first embodiment, the present invention provides a technical solution: a method for optimizing the layout of a municipal drainage pipe network, comprising the following steps:

[0039] S1. Data Preparation and Model Initialization:

[0040] S1.1, Basic Database Construction:

[0041] We obtained geospatial data of 30 square kilometers of the new urban area from the planning department, including topographic maps, land use planning maps and geological exploration reports with an accuracy of 1:500. We used the geographic information system to extract digital elevation models, identify natural water catchment lines, and enter the locations of existing river channels and planned water outlets as mandatory constraint points into the database.

[0042] S1.2, Constraints Determined:

[0043] According to drainage design standards, the layout constraints are set as follows: the minimum burial depth of the pipeline is 1.2 meters, the maximum burial depth is no more than 6 meters, and it avoids the planned subway lines and underground integrated pipe corridor areas. Based on the water catchment direction automatically generated by the digital elevation model, 8 main water catchment zones are initially divided, and the locations of 3 planned discharge outlets are fixed.

[0044] S1.3, Cost Model Establishment:

[0045] A total cost calculation model for the entire life cycle of the pipeline network is established, which consists of three parts:

[0046] Construction cost: Establish a table showing the correspondence between pipe diameter, length, and construction cost based on local engineering quota standards;

[0047] Operation and maintenance costs: estimated as a percentage of construction costs, taking into account the present value over the pipeline's lifespan;

[0048] Risk cost: calculated by multiplying the estimated flooding loss by the probability of occurrence;

[0049] Adding these three cost components together yields the total cost assessment for each option.

[0050] S1.3, Generate preliminary layout scheme:

[0051] An improved genetic algorithm is used as the optimization engine:

[0052] Coding design: The pipeline layout is coded as a string of numbers, with each pipe segment represented by an upstream node number, a downstream node number, a pipe diameter code, and a slope code;

[0053] Initial population: Randomly generate 200 individual schemes that satisfy the minimum burial depth and connection logic;

[0054] Iterative optimization: Using the reciprocal of the total cost as the fitness evaluation standard, the algorithm is run to perform selection, crossover, and mutation operations. When the optimal fitness improvement is less than 2% for 10 consecutive generations, the mutation probability is increased from 5% to 15%, and then restored after 3 generations.

[0055] After 80 iterations, the algorithm converged and output 50 preliminary pipeline layout schemes with relatively good cost.

[0056] S2, Embedded Real-Time Hydraulic Simulation and Evaluation:

[0057] S2.1 Simulation Initialization and Monitor Configuration:

[0058] For 50 preliminary schemes, 50 hydraulic simulation processes were launched in parallel. During the initialization of each process, a real-time hydraulic performance monitor was synchronously implanted.

[0059] The monitor loads configuration parameters and sets performance thresholds: maximum allowable fill level is 0.85, minimum allowable flow rate is 0.6 m / s, and maximum allowable flow rate is 5.0 m / s;

[0060] Set catastrophic failure warning rules:

[0061] Rule 1: If the water level at a node in front of a high-speed railway station exceeds its road surface elevation within three consecutive calculation time steps, an early warning will be triggered.

[0062] Rule 2: If the total overflow of the system suddenly increases by more than 5,000 cubic meters within a single time step;

[0063] The monitor allocates storage space in memory to record process indicator data;

[0064] S2.2 Dynamic Simulation and Real-time Tracking:

[0065] The input is a design rainfall event that occurs once every 50 years and lasts for 2 hours, with the total simulation duration set to 6 hours.

[0066] The hydraulic simulation engine performs calculations in 1-minute time steps. At the end of each time step, the monitor acquires real-time hydraulic status data for all pipes and nodes.

[0067] Real-time calculation process: The monitor traverses all pipes, records the pipe segment numbers and current values ​​where the fill degree exceeds 0.75, records the pipe segment numbers where the flow rate does not meet the requirements, and accumulates the overflow data of each node.

[0068] Real-time early warning judgment: Check rule one every 3 time steps, and check rule two at each time step;

[0069] S2.3, Adaptive Analog Interrupt:

[0070] Simulation of Scheme 7: At the 45th minute, the monitor detected that the water level at the high-speed railway station square node had exceeded the road surface for 3 consecutive minutes, triggering a catastrophic hydraulic failure warning. The monitor immediately sent an interrupt command to forcibly terminate the simulation process of this scheme.

[0071] Simulation of Scheme 23: At the 90th minute, the monitor found that more than 35% of the pipe sections had a fill rate greater than 0.95 at the same time, which was judged as a risk of system-wide paralysis, and an interrupt command was sent.

[0072] Simulation of Scheme 15: No warning was triggered throughout the simulation, the overall hydraulic condition was good, and the monitor allowed it to run for a full 6 hours;

[0073] S2.4, Structured Result Output:

[0074] After the simulation process terminates, the monitor summarizes all process data;

[0075] For a successfully completed scheme: calculate the final performance indicators, including the global maximum fill degree, minimum flow velocity, and total overflow, and calculate the comprehensive hydraulic performance score based on the weighted average of each indicator, with a maximum score of 100 points;

[0076] For interrupted schemes: mark the simulation status as "interrupted" in the report, record the maximum fullness in the core performance indicators as exceeding 1.0, record the total overflow as incomplete, clearly indicate the specific node and time of the overflow in the problem list, and directly assign a comprehensive hydraulic performance score of 20 points;

[0077] Ultimately, 50 structured evaluation reports were generated, each clearly reflecting the hydraulic performance of the scheme;

[0078] S3. Multi-objective optimization and solution decision-making:

[0079] S3.1 Filtering, Revision, and Pareto Front Search:

[0080] Preliminary screening: All schemes with a comprehensive hydraulic score below 60 were directly eliminated, leaving 28 qualified schemes;

[0081] Construct a multi-objective optimization problem: take economic indicators and hydraulic performance indicators as two objectives to be optimized, use these 28 schemes as the initial population, and restart the multi-objective optimization algorithm;

[0082] Targeted correction: When generating mutated offspring in the new population, the algorithm refers to the list of problematic pipe segments in the parent scheme evaluation report. If a certain pipe segment frequently appears in the problem list, the pipe diameter of that pipe segment will be adjusted first when generating mutated offspring. This heuristic correction improves search efficiency.

[0083] After 40 iterations, a set of Pareto optimal solutions was obtained, consisting of 15 schemes. These schemes are distributed on the Pareto front from the lowest cost to the best performance.

[0084] S3.2 Multi-criteria decision-making and output:

[0085] A multi-criteria decision analysis method was adopted for the final decision, and four decision criteria were set: economy, hydraulic efficiency, construction difficulty, and environmental impact, and weights were assigned to each criterion.

[0086] Calculate the standardized scores of the 15 Pareto solutions under each criterion, and calculate their proximity to the ideal solution;

[0087] Option 42 was selected as the final recommended option due to its excellent hydraulic performance, reasonable cost, and balanced performance in terms of construction and environmental impact.

[0088] The system automatically outputs detailed construction drawings, bill of quantities, and hydraulic process lines for key nodes of the final design.

[0089] S4. Deliverables and System Integration:

[0090] Digital delivery:

[0091] The geometric information, attribute data, and hydraulic simulation results of the final solution are imported into the urban water affairs geographic information system to form a digital twin base model, providing a data foundation for subsequent intelligent drainage operation and maintenance management.

[0092] Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art and related fields based on the embodiments of the present invention without inventive effort should fall within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described and explained in the present invention, unless otherwise specified or limited, shall be implemented according to conventional means in the art.

Claims

1. A method for optimizing the layout of a municipal drainage pipe network, characterized in that, Includes the following steps: S1. Obtain geospatial data, hydrogeological data, planned land use data, and existing drainage facility data of the target area to construct a basic database for drainage network optimization; S2. Based on the aforementioned basic database, determine the layout constraints of the drainage network system. The constraints include: terrain slope constraints, burial depth restrictions, pipeline avoidance areas, planned catchment areas, and discharge outlet locations. S3. With the lowest total cost over the entire lifecycle of the pipeline network as the primary optimization objective, a comprehensive cost model is constructed that includes construction costs, operation and maintenance costs, and risk costs. S4. Using the comprehensive cost model as the objective function and the layout constraints as constraints, an intelligent optimization algorithm is used to iteratively solve the problem and generate multiple preliminary pipeline layout schemes that meet the constraints. S5. Perform hydraulic simulation evaluation on the multiple preliminary pipeline layout schemes to obtain the hydraulic performance indicators of each scheme under the preset design return period rainfall. S6. Taking the hydraulic performance indicators meeting the design requirements as the second optimization objective, the preliminary pipeline layout scheme is screened and modified to obtain the Pareto optimal solution set. S7. Based on the multi-criteria decision analysis method, select the final recommended scheme from the Pareto optimal solution set, and output the optimized pipeline layout diagram, pipe diameter, slope and node elevation.

2. The method for optimizing the layout of a municipal drainage pipe network according to claim 1, characterized in that, In step S3, the comprehensive cost model is expressed as follows: in, For total cost, The construction cost of the i-th pipe segment is... Its annual operation and maintenance costs, It is the present value factor. Let be the probability of the j-th risk event occurring. The corresponding risk loss cost.

3. The method for optimizing the layout of a municipal drainage pipe network according to claim 1, characterized in that, In step S4, the intelligent optimization algorithm is a genetic algorithm or a particle swarm optimization algorithm; The process of generating a preliminary pipeline layout scheme includes: using graph theory to abstract the drainage area into a network topology structure composed of nodes and edges, and using the intelligent optimization algorithm to perform parallel optimization search on the connection relationship and pipe diameter combination of the network topology structure.

4. The method for optimizing the layout of a municipal drainage pipe network according to claim 1, characterized in that, When using intelligent optimization algorithms for iterative solutions, an adaptive mutation strategy is introduced. When the population evolution gets stuck in a local optimum, the mutation probability is increased to escape the local optimum.

5. The method for optimizing the layout of a municipal drainage pipe network according to claim 1, characterized in that, In step S5, the hydraulic simulation evaluation adopts an embedded real-time monitoring and adaptive interruption mechanism, specifically including the following steps: S5.1 Simulation Initialization and Monitor Configuration: An independent hydraulic simulation process is created for each preliminary pipeline layout scheme, and a real-time hydraulic performance monitor is synchronously embedded in the process. This monitor is preloaded with key performance thresholds and risk assessment rules. S5.2 Dynamic Simulation and Real-Time Indicator Tracking: Using the designed rainfall process curve as input, a non-steady flow dynamic simulation is performed. The real-time monitor performs the following operations at each calculation time step or every N time steps of the simulation: a. Status capture: Capture the instantaneous hydraulic status of all pipes and manholes in real time from the simulation engine memory; b. Calculation of process indicators: Based on the instantaneous state, calculate and update process performance indicators, including: a list of pipe sections with excessive filling degree, a list of pipe sections with unqualified flow velocity, and the cumulative overflow of each inspection well; c. Risk warning judgment: Based on preset rules, determine whether a "catastrophic hydraulic failure" warning has been triggered; S5.3, Adaptive Analog Interrupt: If the real-time monitor detects that more than a preset proportion of pipe segments simultaneously experience serious hydraulic violations, it immediately sends a command to the simulation engine to interrupt the simulation process of the current scheme. S5.4, Structured Result Output: After the simulation process terminates, the real-time monitor integrates all process performance indicators and generates a structured hydraulic performance evaluation report object. This report object includes: simulation status, summary of core performance indicators, a list of problem pipe sections sorted by severity of violations, and a comprehensive hydraulic performance score. If the simulation is interrupted, the score is recorded as the preset lower limit of non-compliance.

6. The method for optimizing the layout of a municipal drainage pipe network according to claim 5, characterized in that, In step S5.2, the triggering rule for the "catastrophic hydraulic failure" early warning includes: for any pre-set critical infrastructure node, the water level in its inspection well exceeds the road surface elevation at its location within M consecutive calculation time steps.

7. The method for optimizing the layout of a municipal drainage pipe network according to claim 1, characterized in that, In step S6, the process of screening and revising the preliminary pipeline layout scheme specifically includes: Based on the comprehensive hydraulic performance scores of each scheme output in step S5.4, a preliminary screening is conducted, and schemes with scores below the passing line are eliminated. The qualified solutions and their comprehensive cost model calculation results are input together into a multi-objective optimization algorithm to perform Pareto front search; When optimizing the algorithm to generate a new generation of solutions, the system performs local optimization searches on the pipe diameter and slope of the corresponding network area based on the list of problem pipe segments in the hydraulic performance evaluation report of the historical solutions.

8. The method for optimizing the layout of a municipal drainage pipe network according to claim 1, characterized in that, In step S7, the multi-criteria decision analysis method is the analytic hierarchy process (AHP). The decision criteria include economic criteria, hydraulic efficiency criteria, construction feasibility criteria, and environmental adaptability criteria. The data for the hydraulic efficiency criteria are directly derived from the hydraulic performance evaluation report object output in step S5.4.

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