Design method of building water supply and drainage system

Abstract

The application discloses a kind of design methods of building water supply and drainage system, it is related to the technical field of drainage system, including using BIM positive design method to draw out the distribution of building drainage system pipeline and drainage equipment, using numerical simulation method to measure drainage data, using analytic hierarchy process to construct judgment matrix after the drainage data is layered, calculate weight index, combine Kriging surrogate model and bat model, calculate the optimal arrangement mode of different function drainage pipeline and drainage equipment and the optimal number of fire hydrant.The design method of building water supply and drainage system can optimally arrange drainage equipment, realize the most rationalization, the most efficient use of drainage equipment to discharge building water and at the same time consider water circulation and material utilization maximization, while considering the influence of fire emergency on drainage system, corresponding disaster response measures required by the most favorable fire-fighting equipment arrangement is designed.

Description

Technical Field

[0001] This invention relates to the technical field of drainage systems, and more particularly to a design method for a building water supply and drainage system. Background Technology

[0002] In recent years, to ensure sanitary conditions within buildings, it is essential to design suitable drainage systems to effectively collect and discharge wastewater, preventing stagnation and water accumulation. The design of the drainage system must be compatible with the building's structure and layout, ensuring the pipe network effectively covers all areas within the building without compromising structural safety and aesthetics. Construction must adhere to relevant building drainage design codes and standards to ensure the quality and safety of the drainage system. The design should consider the impact of emergencies such as fires and natural disasters, incorporating corresponding disaster response and emergency handling measures to provide safe, efficient, and environmentally friendly drainage solutions for buildings.

[0003] Currently, Chinese invention patent application number CN2019102393455 discloses a sewage interception and storage drainage system and its drainage control method. Although this invention designs a special control method to reasonably control different rainfall, and the system realizes the discharge, transportation and treatment of clean water and dirty water at different time periods through only one pipeline, it can realize the separation of clean and dirty water and solve the problem of rainwater and sewage mixing that cannot be treated in old urban areas due to the lack of separate treatment for domestic sewage and rainwater. It greatly reduces the difficulty of construction, saves construction costs, and achieves efficient separation of clean and dirty water. However, the existing technology cannot optimize the layout of drainage equipment, realize the most rational and efficient use of drainage equipment to discharge water in buildings, and simultaneously take into account water circulation and material utilization. It cannot simultaneously consider the impact of sudden events such as fire and natural disasters on the drainage system, and design the most favorable fire-fighting equipment layout required for corresponding disaster response and emergency treatment measures. Summary of the Invention

[0004] The technical problem solved by this invention is that existing technologies cannot optimize the layout of drainage equipment, achieve the most rational and efficient use of drainage equipment to discharge water in buildings, and simultaneously maximize water circulation and material utilization. They also cannot simultaneously consider the impact of emergencies such as fires and natural disasters on the drainage system, and design the most advantageous fire-fighting equipment layout required for corresponding disaster response and emergency treatment measures.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a design method for a building water supply and drainage system, comprising the following steps:

[0006] Step S1: Use BIM forward design method to draw the distribution of building drainage system pipes and drainage equipment;

[0007] Step S2: Calculate drainage data using numerical simulation. The drainage data includes the water balance relationship between the water storage tank and the circulating water system under different rainfall amounts, the drainage volume range of drainage pipes with different functions under different rainfall amounts, the drainage efficiency of drainage pipes and drainage equipment with different functions after different layout methods, the maximum noise decibel of the drainage pipes affecting people in the building, and the total water flow of indoor fire hydrants in the building.

[0008] Step S3: After stratifying the drainage data using the analytic hierarchy process (AHP), construct a judgment matrix, calculate the weight index, and normalize the judgment matrix and weight index to obtain the initial input value.

[0009] Step S4: Combine the Kriging agent model with the bat model, and calculate the optimal layout of drainage pipes and drainage equipment and the optimal number of fire hydrants for different functions by taking into account the water pressure generated by the pipes at different building heights and the runoff volume of water on the building surface.

[0010] Preferably, step S1 includes:

[0011] Receive building information, deploy the drainage equipment required for the drainage system in the building's information model, the drainage equipment includes drainage pipes, sewers, inspection wells, drainage pumps and drain outlets, set parameters for the drainage equipment, establish a drainage system network in the building's information model, including combining and connecting drainage pipes, sewers, inspection wells, drainage pumps and drain outlets, and generate design documents including 3D model views, sectional views and construction drawings.

[0012] Preferably, step S2 includes:

[0013] By simulating precipitation and runoff under different rainfall conditions, the water supply demand of the building's circulating water system is defined as the outflow from the storage tank. The inflow, outflow, overflow, and losses of the storage tank are calculated to assess the water balance under different conditions, including:

[0014] Based on the building information model established in step S1, simulate precipitation events of different intensities and durations to set different precipitation conditions. Calculate the drainage volume range and water balance relationship of each pipe under various precipitation events according to the pipe attributes and precipitation conditions set in the model. The pipe attributes include pipe diameter and slope. Under the premise of controlling variables, simulate the drainage efficiency of drainage pipes and drainage equipment with different functions after different layout methods. Establish an acoustic model inside the building and a hydraulic model of the building's fire protection water system. Determine the noise generation characteristics of drainage pipes under different flow conditions. Simulate the propagation path and impact range of drainage pipe noise within the building. Calculate the maximum noise decibel value in different areas within the building, find the maximum noise decibel affecting people inside the building, and simulate the total water flow required for fire hydrants.

[0015] Preferably, the water storage tank receives rainfall within the service area. When the water storage tank is saturated and the rainfall exceeds the inflow, rainwater overflows. The inflow, infiltration, overflow, and water storage capacity of the water storage tank satisfy a water balance relationship. The mathematical expression for simulating the rainfall magnitude is as follows:

[0016] Q = kψqs;

[0017] Where Q is the amount of rainfall, k is the catchment coefficient, which is 1.5 when the water level is full and 0 when the water level is not full, ψ is the runoff coefficient, which ranges from 0.3 to 0.4, q is the design rainfall intensity, and s is the catchment area.

[0018] The mathematical expression for designing the intensity of a rainstorm is:

[0019] ;

[0020] Where P is the design return period, t is the rainfall time, and A, c, b, and m are parameters of the area where the building is located, which are calculated and determined based on local statistical data and design specifications.

[0021] The total volume of the water storage tank is determined by the inflow and outflow rates over a period of time, adjusted through water balance analysis. The mathematical expression for the total volume of the water storage tank is:

[0022] ;

[0023] in, This is the total volume of the water storage tank. The average inflow rate is the rainfall amount per unit time, which is determined by the simulated rainfall conditions in step S2. Let T be the average water demand per unit time, and T be the storage period.

[0024] Preferably, step S3 includes:

[0025] The Analytic Hierarchy Process (AHP) specifically includes:

[0026] A hierarchical structure model is established, which is divided into a target layer, a criterion layer, and an indicator layer from top to bottom. A judgment matrix is ​​constructed for each layer, including:

[0027] A judgment matrix is ​​constructed using numbers 1-9 and their corresponding reciprocals as scales. The target layer consists of weighted indicators. The criterion layer includes the water balance relationship of the water storage tank, the range of drainage volume values, drainage efficiency, maximum noise level (decibels), and total water flow of the fire hydrant. The indicator layer includes weighted indicators for water balance relationship, drainage volume range, drainage efficiency, maximum noise level (decibels), and total water flow of the fire hydrant. A judgment matrix is ​​constructed based on the scale values ​​and rules of the judgment matrix from the lower layer to the upper layer. The rules include:

[0028] When C i >C j At that time, C i With C j When the importance gap is the most important gap, the scale value is set to 1, C i With C j When the importance gap is the second most important gap, the scale value is set to 2, C i With C j When the importance gap is the third most important gap, the scale value is set to 3, C i With C j When the importance gap is the fourth most important gap, the scale value is set to 4, C i With C j When the importance gap is the fifth most important gap, the scale value is set to 5, C i With C j When the importance gap is the sixth most important gap, the scale value is set to 6, C i With C j When the importance gap is the seventh most important gap, the scale value is set to 7, C. i With C j When the importance gap is the eighth most important gap, the scale value is set to 8, C i With C j When the importance gap is the ninth most important gap, the scale value is set to 9;

[0029] When C i <C j At that time, C i With C j The scale value is C when the importance difference is equal. i >C j The reciprocal of the time scale value;

[0030] Among them, C i With C jThese include the water balance relationship of the water storage tank, the range of drainage volume, the drainage efficiency, the maximum noise level, the total water flow of the fire hydrant, the weight index of the water balance relationship, the weight index of the drainage volume range, the weight index of the drainage efficiency, the weight index of the maximum noise level, and the weight index of the total water flow of the fire hydrant.

[0031] The judgment matrix is ​​normalized sequentially. The normalized judgment matrix is ​​then summed row by row to obtain the same number of vectors as the judgment matrix. All vectors are concatenated into a matrix and then column normalized to obtain the eigenvectors of the matrix. The maximum eigenvalue of the concatenated matrix is ​​calculated based on the eigenvectors. The consistency of the vectors and the concatenated matrix is ​​then checked based on the maximum eigenvalue.

[0032] If the consistency test is passed, the weight indexes of water balance relationship, drainage volume range, drainage efficiency, maximum noise decibels and total water flow of fire hydrants are obtained according to the rules. All weight indexes are normalized in sequence to obtain the initial input values.

[0033] If the consistency check fails, the scale value is adjusted, and the judgment matrix is ​​normalized sequentially. The normalized judgment matrix is ​​then summed row by row to obtain the same number of vectors as the judgment matrix. All vectors are concatenated into a matrix and then column normalized to obtain the eigenvectors of the matrix. The maximum eigenvalue of the concatenated matrix is ​​calculated based on the eigenvectors, and the consistency check of the vectors and the concatenated matrix is ​​performed based on the maximum eigenvalue.

[0034] Preferably, the mathematical expression for the water pressure exerted on the pipes at different heights of the building is:

[0035] H;

[0036] Where p represents pressure, The density of water, It is the acceleration due to gravity. For height;

[0037] The volume of water accumulation on the building surface includes:

[0038] The surface runoff process is solved using the finite volume method to solve the two-dimensional shallow water equation. The vector form of the two-dimensional nonlinear shallow water equation is as follows:

[0039] ; ; ; ; ;

[0040] in, For variable vectors, For the water depth on the grid, The unit width flow rate in the x-direction, Let x represent the unit width flow rate in the y-direction, and let x be the horizontal axis of the Cartesian coordinate system, and y be the vertical axis. It is the acceleration due to gravity. For the flow velocity in the x direction, Let be the flow velocity in the y-direction. Let x be the flux in the x and y directions. These are vectors in the x and y directions. This is the source term vector, which includes the surface slope source term and the frictional resistance source term. Net rainfall rate This refers to the surface elevation. The roughness coefficient of the catchment surface is given by the following mathematical expression:

[0041] ;

[0042] in, denoted as Manning's coefficient for the catchment area.

[0043] Preferably, step S4 includes:

[0044] Combining the Kriging agent model with the bat model includes:

[0045] The BIM forward design method is used to measure known water pressure data points, and the water pressure distribution of each point inside the building is interpolated using the Kriging model, including water pressure changes at different heights. Based on the building shape, pipe slope and drainage system distribution modeled in step S1, the water flow situation on the building surface under different conditions is predicted.

[0046] The water pressure, the volume of water flowing onto the building surface, the weight index of water balance relationship, the weight index of drainage volume range, the weight index of drainage efficiency, the weight index of maximum noise decibels, and the weight index of total water flow of fire hydrants are used as input variables, and the optimal value is used as the output variable of the combined model.

[0047] The optimization objective is defined as the optimal layout of drainage pipes and drainage equipment with different functions, including the optimal number of fire hydrants. The parameters of the bat algorithm are set, including the number of drainage pipes and drainage equipment, water balance relationship, drainage efficiency, the range of audible noise decibels in the building, and the total water flow of fire hydrants.

[0048] By incorporating the Kriging model and the Gaussian function as part of the objective function, and combining them with the actual needs in construction engineering, a comprehensive objective function is defined.

[0049] Initialize the layout and function of drainage pipes and equipment. Update the layout of drainage pipes and equipment based on the current layout and function, and calculate a new objective function value. Calculate initial feature data based on the objective function, form a matrix from the initial feature data, calculate the covariance matrix of the matrix, obtain the correlation between the input variables, select surrogate points among the input variables (the surrogate points are the average attribute values ​​of the input variables respectively), adjust the water balance relationship and drainage efficiency based on the drainage volume, maximum noise level, and total fire hydrant water flow, update the optimal layout of drainage pipes and equipment, and repeat the above steps until a pre-set number of iterations is reached. Adjust the surrogate point density and model parameters to obtain the combined model with the highest unbiased estimate.

[0050] Preferably, the selection of agent points includes:

[0051] The attribute values ​​of the unknown arrangement are estimated by minimizing the sum of squared interpolation errors. The attribute values ​​of the surrogate points are obtained by weighted averaging. The weights of each input variable depend on the weighted average of the weights of the two most relevant input variables.

[0052] Preferably, by combining the Kriging proxy model with the bat model and considering the water pressure on pipes at different building heights and the runoff volume of water on the building surface, the optimal layout of drainage pipes and drainage equipment for different functions and the optimal number of fire hydrants are calculated, including:

[0053] The maximum noise decibel weight index and the total water flow weight index of fire hydrants in the input variables are replaced by the water pressure generated by the pipes at different building heights and the runoff volume of water on the building surface. All steps of combining the Kriging surrogate model and the bat model are iteratively executed to obtain the second combined model. The final result of the second combined model and the first combined model is used as input and put into the Kriging surrogate model. The output is defined as the optimal layout, and the optimal layout prediction result is obtained. The prediction result includes the optimal number of fire hydrants.

[0054] Preferably, the layout of drainage equipment is optimized based on the analysis results. Under the premise of meeting the actual safety and efficiency requirements, drainage pipes and equipment are arranged according to the geometric and spatial constraints of the building model.

[0055] The beneficial effects of this invention are: to optimize the layout of drainage equipment, to achieve the most rational and efficient use of drainage equipment to discharge water in buildings, and to maximize water circulation and material utilization at the same time, to take into account the impact of sudden fire events on the drainage system, and to design the most favorable fire-fighting equipment layout required for corresponding disaster response measures in combination with actual conditions. Attached Figure Description

[0056] Figure 1A basic flowchart illustrating a design method for a building water supply and drainage system according to an embodiment of the present invention;

[0057] Figure 2 This is a schematic diagram of a hierarchical structure model provided for one embodiment of the present invention. Detailed Implementation

[0058] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0059] Reference Figure 1 As an embodiment of the present invention, a design method for a building water supply and drainage system is provided, comprising the following steps:

[0060] Step S1: Use BIM forward design method to draw the distribution of building drainage system pipes and drainage equipment;

[0061] Step S2: Calculate drainage data using numerical simulation. Drainage data includes the water balance relationship between the water storage tank and the circulating water system under different rainfall amounts, the drainage volume range of drainage pipes with different functions under different rainfall amounts, the drainage efficiency of drainage pipes and drainage equipment with different functions after different layout methods, the maximum noise decibel of the drainage pipes affecting people in the building, and the total water flow of indoor fire hydrants in the building.

[0062] Step S3: After stratifying the drainage data using the analytic hierarchy process, construct a judgment matrix, calculate the weight index, normalize the judgment matrix and the weight index, and obtain the initial input value.

[0063] Step S4: Combine the Kriging agent model with the bat model, and calculate the optimal layout of drainage pipes and drainage equipment and the optimal number of fire hydrants for different functions by taking into account the water pressure generated by the pipes at different building heights and the runoff volume of water on the building surface.

[0064] By integrating BIM forward design, numerical simulation, analytic hierarchy process (AHP) and a novel hybrid intelligent algorithm, a closed-loop, data-driven design method for building water supply and drainage systems is proposed, encompassing design, analysis, decision-making, and optimization. This method solves the problems of traditional design methods that rely on experience and struggle to find global optimization.

[0065] Based on the BIM forward design method, 3D buildings and their initial drainage equipment distribution can be drawn. Combined with numerical simulation methods, simulated drainage data can be obtained, which can accurately obtain drainage data based on reality. The software is simple and convenient to use. The hierarchical analysis method can make the relationship between drainage data closer. By combining the relationship between data and using the Kriging surrogate model and the bat model, the optimal layout of drainage equipment can be obtained while predicting drainage data. This takes into account both water circulation and maximizing material utilization. It can also consider the impact of sudden fire events on the drainage system and design the most favorable fire-fighting equipment layout required for corresponding disaster response measures.

[0066] Step S1 includes:

[0067] Receive building information, lay out the drainage equipment required for the drainage system in the building's information model. The drainage equipment includes drainage pipes, sewers, inspection wells, drainage pumps, and drain outlets. Set parameters for the drainage equipment, establish a network of the drainage system in the building's information model, including combining and connecting drainage pipes, sewers, inspection wells, drainage pumps, and drain outlets, and generate design documents including 3D model views, sectional views, and construction drawings.

[0068] Drainage equipment setting parameters include pipe diameter, slope, and material. These parameters affect the system's flow rate, drainage speed, and performance. The system combines and connects drainage pipes, sewers, inspection wells, drainage pumps, and drain outlets. Examples include: water supply system zoning and supply pressure; drainage system selection; indoor fire hydrant water supply system zoning and supply pressure; indoor fire hydrant water supply system water consumption calculation; automatic sprinkler system type selection; pipe network calculation; equipment room layout; preliminary pipe routing design; and the layout of internal building wells. Furthermore, it is necessary to control the building's internal height and pre-integrate pipeline processing to ensure smooth network flow and compliance with design requirements. The drawings and models in the design documents can not only be used for design review but also serve as a reference for construction and maintenance.

[0069] It achieves the digitization and parametricization of design objects. It clarifies that the foundation of the design is to establish a digital twin model of the drainage system in the BIM environment, including geometric and physical attributes, providing a data foundation for all subsequent accurate simulation analysis and optimization.

[0070] Step S2 includes:

[0071] By simulating precipitation and runoff under different rainfall conditions, the water supply demand of the building's circulating water system is defined as the outflow from the storage tank. The inflow, outflow, overflow, and losses of the storage tank are calculated to assess the water balance under different conditions, including:

[0072] Based on the building information model established in step S1, simulate precipitation events of different intensities and durations to set different precipitation conditions. Calculate the drainage volume range and water balance relationship of each pipe under various precipitation events according to the pipe attributes and precipitation conditions set in the model. Pipe attributes include pipe diameter and slope. Under the premise of controlling variables, simulate the drainage efficiency of drainage pipes and equipment with different functions after different layout methods. Establish an acoustic model of the building interior and a hydraulic model of the building's fire protection water system. Determine the noise generation characteristics of drainage pipes under different flow conditions. Simulate the propagation path and impact range of drainage pipe noise within the building. Calculate the maximum noise decibel value in different areas within the building, find the maximum noise decibel affecting people within the building, and simulate the total water flow required for fire hydrants.

[0073] Drainage pipes with different functions include sewage pipes, rainwater pipes, ground drainage systems, kitchen drainage pipes, toilet drainage pipes, bathroom drainage pipes, floor drain condensate drainage pipes, and special facility drainage pipes.

[0074] A multi-dimensional system performance evaluation framework has been established. It expands the evaluation of design quality from a single drainage capacity to multiple dimensions such as water balance, drainage efficiency, acoustic comfort (noise), and fire safety (fire hydrant flow rate), making the design evaluation more comprehensive and scientific.

[0075] The water storage tank receives rainfall within its service area. When the tank is saturated and the rainfall exceeds the inflow, rainwater overflows. The inflow, infiltration, overflow, and storage capacity of the tank satisfy a water balance relationship. The mathematical expression for simulating rainfall magnitude is:

[0076] Q = kψqs;

[0077] Where Q is the amount of rainfall, k is the catchment coefficient, which is 1.5 when the water level is full and 0 when the water level is not full, ψ is the runoff coefficient, which ranges from 0.3 to 0.4, q is the design rainfall intensity, and s is the catchment area.

[0078] The mathematical expression for designing the intensity of a rainstorm is:

[0079] ;

[0080] Where P is the design return period, t is the rainfall time, and A, c, b, and m are parameters of the area where the building is located, which are calculated and determined based on local statistical data and design specifications.

[0081] The parameters were determined through statistical analysis based on official hydrological and meteorological data of the project location and the "Outdoor Drainage Design Standard".

[0082] The total volume of the water storage tank is determined by the inflow and outflow rates over a period of time, adjusted through water balance analysis. The mathematical expression for the total volume of the water storage tank is:

[0083] ;

[0084] in, This is the total volume of the water storage tank. The average inflow rate is the rainfall amount per unit time, which is determined by the simulated rainfall conditions in step S2. The average water demand per unit time is T, which is the storage period, set to 24 hours or 48 hours in this embodiment.

[0085] In specific calculations, the inflow process line under the design return period can be simulated based on the catchment surface information generated by the BIM model and the local rainfall spectrum. Combined with the water demand process line, the maximum required cumulative storage capacity can be obtained through hourly water balance calculations, which is then used as the design total volume V of the water storage tank. This method can more accurately match local rainfall characteristics and the actual water demand of the building.

[0086] This ensures the regional adaptability and economy of rainwater system design. By introducing a rainstorm intensity formula linked to local climate characteristics and a scientific method for calculating water storage tank volume, the design of rainwater harvesting and utilization systems is no longer arbitrary but closely integrated with local hydrological conditions and actual water demand.

[0087] Step S3 includes:

[0088] The Analytic Hierarchy Process (AHP) specifically includes:

[0089] Establish a hierarchical structure model, referring to Figure 2 The hierarchical model is divided into three layers from top to bottom: the target layer, the criterion layer, and the indicator layer. A judgment matrix is ​​constructed for each layer, including:

[0090] A judgment matrix is ​​constructed using numbers 1-9 and their corresponding reciprocals as scales. The target layer consists of weighted indicators. The criterion layer includes the water balance relationship of the water storage tank, the range of drainage volume values, drainage efficiency, maximum noise level (decibels), and total water flow of the fire hydrant. The indicator layer includes weighted indicators for water balance relationship, drainage volume range, drainage efficiency, maximum noise level (decibels), and total water flow of the fire hydrant. The judgment matrix is ​​constructed based on the scale values ​​of the judgment matrix from the lower layer to the upper layer and the rules. The rules include:

[0091] When C i >C j At that time, C i With C j When the importance gap is the most important gap, the scale value is set to 1, C i With C jWhen the importance gap is the second most important gap, the scale value is set to 2, C i With C j When the importance gap is the third most important gap, the scale value is set to 3, C i With C j When the importance gap is the fourth most important gap, the scale value is set to 4, C i With C j When the importance gap is the fifth most important gap, the scale value is set to 5, C i With C j When the importance gap is the sixth most important gap, the scale value is set to 6, C i With C j When the importance gap is the seventh most important gap, the scale value is set to 7, C. i With C j When the importance gap is the eighth most important gap, the scale value is set to 8, C i With C j When the importance gap is the ninth most important gap, the scale value is set to 9;

[0092] When C i <C j At that time, C i With C j The scale value is C when the importance difference is equal. i >C j The reciprocal of the time scale value;

[0093] Among them, C i With C j These include the water balance relationship of the water storage tank, the range of drainage volume, drainage efficiency, maximum noise level, total water flow of the fire hydrant, weight indicators for the water balance relationship, weight indicators for the range of drainage volume, weight indicators for drainage efficiency, weight indicators for maximum noise level, and weight indicators for total water flow of the fire hydrant.

[0094] The judgment matrix is ​​normalized sequentially. The normalized judgment matrix is ​​then summed row by row to obtain the same number of vectors as the judgment matrix. All vectors are concatenated into a matrix and then column normalized to obtain the eigenvectors of the matrix. The maximum eigenvalue of the concatenated matrix is ​​calculated based on the eigenvectors. The consistency between the vectors and the concatenated matrix is ​​then checked based on the maximum eigenvalue.

[0095] If the consistency test is passed, the weight indexes of water balance relationship, drainage volume range, drainage efficiency, maximum noise decibel, and total water flow of fire hydrants are obtained according to the rules. All weight indexes are normalized in sequence to obtain the initial input values.

[0096] If the consistency check fails, the scale value is adjusted, and the judgment matrix is ​​normalized sequentially. The normalized judgment matrix is ​​then summed row by row to obtain the same number of vectors as the judgment matrix. All vectors are concatenated into a matrix and then column normalized to obtain the eigenvectors of the matrix. The maximum eigenvalue of the concatenated matrix is ​​calculated based on the eigenvectors, and the consistency check between the vectors and the concatenated matrix is ​​performed based on the maximum eigenvalue.

[0097] It achieves the quantification and weight allocation of design objectives. By using the analytic hierarchy process (AHP), it transforms multiple complex and even conflicting design objectives (such as efficiency, noise, and cost) into computable weights, thus pointing the way for subsequent optimization algorithms and solving the "gut feeling" problem in multi-objective decision-making.

[0098] The water pressure exerted on pipes at different building heights, using ordinary external drainage and gravity flow, is mathematically expressed as follows:

[0099] H;

[0100] Where p represents pressure, The density of water, It is the acceleration due to gravity. For height;

[0101] The standard water pressure on the top floor of a typical high-rise building is 2 kg / m². From the 1st to the 6th floor, the water pressure ranges from 1.5 to 3 kg / m², which falls within the scope of municipal water supply. In high-rise buildings, the water pressure increases by 1 kg / m² for every 3-4 floors descending. For example, in a 25-story building, the water pressure on the 5th floor is 2 kg / m². For residential buildings with a floor height not exceeding 3.5 meters, the required water supply system pressure can be calculated starting from approximately 0.1 MPa on the first floor, increasing by 0.04 MPa for each additional floor from the second floor onwards. This rule of thumb provides a general method for pressure estimation. Secondary pressurized zoned water supply systems in high-rise residential buildings need to meet certain water pressure standards. For example, the water pressure for a single-story house is 0.1 MPa, the second floor requires an additional 0.02 MPa, and each of the third to sixth floors requires an additional 0.04 MPa. The water supply pressure at the entrance pipe of a residential building should not exceed 0.35 MPa. For domestic water supply systems in buildings with a height not exceeding 100 meters, vertically zoned parallel water supply or zoned pressure reduction water supply methods are recommended.

[0102] The volume of water accumulation on the building surface includes:

[0103] The surface runoff process is solved using the finite volume method to solve the two-dimensional shallow water equations. Neglecting kinematic viscosity, turbulent viscosity, wind stress, and Coriolis forces, the vector form of the two-dimensional nonlinear shallow water equations is as follows:

[0104] ; ; ; ; ;

[0105] in, For variable vectors, For the water depth on the grid, The unit width flow rate in the x-direction, Let x represent the unit width flow rate in the y-direction, and let x be the horizontal axis of the Cartesian coordinate system, and y be the vertical axis. It is the acceleration due to gravity. For the flow velocity in the x direction, Let be the flow velocity in the y-direction. Let x be the flux in the x and y directions. These are vectors in the x and y directions. This is the source term vector, which includes the surface slope source term and the frictional resistance source term. Net rainfall rate This refers to the surface elevation. Let be the surface roughness coefficient of the catchment area. The mathematical expression for the surface roughness coefficient of the catchment area is:

[0106] ;

[0107] in, denoted as Manning's coefficient for the catchment area.

[0108] It provides the mathematical modeling foundation for key physical processes. It clarifies the core physical equations underlying the calculation of the system's hydraulic performance (water pressure, surface runoff), ensuring the scientific rigor and accuracy of the numerical simulation.

[0109] Step S4 includes:

[0110] Combining the Kriging agent model with the bat model includes:

[0111] The known water pressure data points are measured using the BIM forward design method. The water pressure distribution of each point inside the entire building is interpolated using the Kriging model, including water pressure changes at different heights. Based on the building shape, pipe slope and drainage system distribution modeled in step S1, the water flow situation on the building surface under different conditions is predicted.

[0112] The input variables are water pressure, the volume of water flowing onto the building surface, the weight index of water balance relationship, the weight index of drainage volume range, the weight index of drainage efficiency, the weight index of maximum noise decibels, and the weight index of total water flow of fire hydrants. The optimal value is used as the output variable of the combined model.

[0113] The optimization objective is clearly defined as the optimal layout of drainage pipes and equipment with different functions, including the optimal number of fire hydrants. The parameters of the bat algorithm are set, including the number of drainage pipes and equipment, water balance relationship, drainage efficiency, the range of audible noise decibels in the building, and the total water flow of fire hydrants.

[0114] The optimization objective is defined as the optimal layout of drainage pipes and drainage equipment with different functions, including the optimal number of fire hydrants. The parameters of the bat algorithm are set, including the number of drainage pipes and drainage equipment, water balance relationship, drainage efficiency, the range of audible noise decibels in the building, and the total water flow of fire hydrants.

[0115] By incorporating the Kriging model and the Gaussian function as part of the objective function, and combining them with the actual needs in construction engineering, a comprehensive objective function is defined.

[0116] Practical needs in building engineering include minimizing water pressure variations, maximizing water storage efficiency, or minimizing the investment cost of fire protection facilities.

[0117] The process of defining the objective function specifically includes:

[0118] The Kriging model is used as the surrogate objective function of the bat optimization algorithm, and the specific combination method is as follows:

[0119] Using each weighted index as a coefficient, the drainage data are normalized to construct a comprehensive performance evaluation function. The mathematical expression of the comprehensive performance evaluation function is as follows:

[0120] ;

[0121] in, Let d be the comprehensive performance evaluation function, where d is an unknown. For the nth weighted index, This is the nth drainage data item;

[0122] An initial drainage system layout scheme d is generated using the Latin hypercube sampling method. A complete numerical simulation is then performed on each scheme to obtain its corresponding true comprehensive performance evaluation value. ;

[0123] Using initial sample data (d, Training a Kriging surrogate model can approximate the performance evaluation value of any arrangement scheme d at a very high speed.

[0124] The fast Kriging surrogate model is used as the objective function of the Bat Algorithm. The Bat Algorithm quickly finds the optimal solution on the Kriging surrogate model through iterative search, without having to call the time-consuming comprehensive performance evaluation function in each iteration.

[0125] After the bat algorithm has run for a certain number of generations, the current optimal solution can be subjected to a real numerical simulation, and the new sample points obtained can be added to the training set to update the Kriging model and improve its accuracy in key regions.

[0126] Repeat the training and iterative search steps until the convergence condition is met or the maximum number of iterations is reached.

[0127] Initialize the layout and function of drainage pipes and equipment. Update the layout of drainage pipes and equipment based on the current layout and function, and calculate the new objective function value. Calculate the initial feature data based on the objective function, form a matrix from the initial feature data, calculate the covariance matrix of the matrix, obtain the correlation between input variables, select surrogate points among the input variables (the surrogate points are the average attribute values ​​of the input variables respectively), adjust the water balance relationship and drainage efficiency based on the drainage volume, maximum noise level, and total fire hydrant water flow, update the optimal layout of drainage pipes and equipment, and repeat the above steps until the pre-set number of iterations is reached. Adjust the surrogate point density and model parameters to obtain the combined model with the highest unbiased estimate.

[0128] It provides a core, efficient optimization solution engine. By transforming computationally expensive numerical simulation problems into computationally inexpensive surrogate model optimization problems, it greatly improves the efficiency of finding the global optimum, making it possible to comprehensively optimize complex drainage systems and improve prediction accuracy and optimization performance.

[0129] The selection of agent points includes:

[0130] The attribute values ​​of the unknown arrangement are estimated by minimizing the sum of squared interpolation errors. The attribute values ​​of the surrogate points are obtained by weighted averaging. The weights of each input variable depend on the weighted average of the weights of the two most relevant input variables.

[0131] A technical detail in the construction of the surrogate model is refined, aiming to improve the accuracy of attribute estimation of surrogate points through a specific weighting method, thereby enhancing the local prediction accuracy of the Kriging surrogate model.

[0132] By combining the Kriging proxy model with the bat model, and taking into account the water pressure on pipes at different building heights and the runoff volume of water on the building surface, the optimal layout of drainage pipes and drainage equipment for different functions, as well as the optimal number of fire hydrants, are calculated, including:

[0133] The maximum noise decibel weight index and the total water flow weight index of fire hydrants are replaced by the water pressure generated by the pipes at different building heights and the runoff volume of water on the building surface. All steps of combining the Kriging surrogate model and the bat model are iteratively executed to obtain the second combined model. The final result of the second combined model and the first combined model is used as input and put into the Kriging surrogate model. The output is defined as the optimal layout, and the optimal layout prediction result is obtained, which includes the optimal number of fire hydrants.

[0134] The steps for calculating the optimal layout and the optimal number of fire hydrants specifically include the first stage of optimization, the second stage of optimization, and the final decision:

[0135] The first stage of optimization includes: using the comprehensive performance evaluation function as the objective function, obtaining the first candidate optimal solution set;

[0136] The second stage of optimization includes: modifying the optimization objective to maximize drainage efficiency and minimize system water pressure fluctuations as the main objectives, and obtaining a second set of candidate optimal solutions;

[0137] The final decision-making process includes: cross-validating and evaluating the performance of all schemes in the first and second candidate optimal solution sets; and using the TOPSIS decision analysis method to select the final optimal layout and number of fire hydrants that perform best across all indicators from the first and second candidate optimal solution sets.

[0138] An iterative optimization strategy for handling multi-objective conflicts is proposed. By optimizing in stages with different focuses, a more robust and balanced design scheme can be obtained, avoiding the "partiality" phenomenon caused by single-objective optimization and improving the overall performance of the final scheme.

[0139] Based on the analysis results, optimize the layout of drainage equipment. Under the premise of meeting the actual safety and efficiency requirements, arrange drainage pipes and equipment according to the geometric and spatial constraints of the building model.

[0140] Ensure that the pipeline layout is reasonable and compact, and that the equipment locations are convenient for maintenance and operation. Integrate the drainage system with other building systems (such as water supply and electrical systems) to ensure coordination and compatibility between the systems.

[0141] BIM features enable the sharing of data and models with other members of the building team, such as structural and electrical engineers, facilitating interdisciplinary collaboration. Continuous updating and management of the BIM model during the design, construction, and operation phases, along with recording changes and updates, ensures the consistency and accuracy of design data.

[0142] By following the steps above, using BIM to design building drainage systems can improve design efficiency, reduce design error rates, and support the needs of design optimization and overall project management.

[0143] Drainage pipe optimization includes:

[0144] It shall meet the requirements of various professional design specifications and construction acceptance specifications, and follow the following rules:

[0145] Unpressurized pipes give way to pressurized pipes, low-pressure pipes give way to high-pressure pipes, single pipes give way to multi-pipe systems, water pipes give way to air ducts, equipment professionals give way to building structure professionals, small pipes give way to large pipes, temporary pipelines give way to permanent pipelines, metals give way to non-metals, and cable trays should be heat- and water-proofed and have fewer accessories to give way to pipes with more accessories.

[0146] Drainage equipment optimization includes:

[0147] Based on fulfilling the original design intent, optimize the pipes, cable trays, etc. of this specialty, and arrange them reasonably according to the engineering characteristics of the pipes, cable trays, etc. of this specialty, so as to achieve the degree that the functions of each specialty do not affect each other and the construction methods are feasible.

[0148] Optimize the routing of various professional pipelines to meet the elevation requirements of regional electromechanical pipelines, while also meeting the requirements for construction and installation space as well as subsequent inspection and maintenance space.

[0149] The pipeline layout should be clear, reasonable, neat and aesthetically pleasing.

[0150] This ensures the engineering feasibility of the optimization results. It emphasizes the final implementation of the theoretically optimal solution derived from the algorithm, while meeting real-world safety and space constraints, thus bridging the final gap between theoretical optimization and actual construction drawings.

[0151] This invention, based on the BIM forward design method, can draw 3D buildings and the initial distribution of drainage equipment. Combined with numerical simulation methods, it obtains simulated drainage data, which can accurately obtain drainage data based on reality. The software is simple and convenient to use. The hierarchical analysis method can make the relationship between drainage data closer. Through the relationship between data, using the combination of Kriging surrogate model and bat model, the optimal layout of drainage equipment can be obtained while predicting drainage data. It also takes into account water circulation and maximizing material utilization, and can consider the impact of sudden fire events on the drainage system. Based on reality, it designs the most favorable fire-fighting equipment layout required for corresponding disaster response measures.

[0152] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0153] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A design method for a building water supply and drainage system, characterized in that, Includes the following steps: Step S1: Use BIM forward design method to draw the distribution of building drainage system pipes and drainage equipment; Step S2: Calculate drainage data using numerical simulation. The drainage data includes the water balance relationship between the water storage tank and the circulating water system under different rainfall amounts, the drainage volume range of drainage pipes with different functions under different rainfall amounts, the drainage efficiency of drainage pipes and drainage equipment with different functions after different layout methods, the maximum noise decibel of the drainage pipes affecting people in the building, and the total water flow of indoor fire hydrants in the building. Step S3: After stratifying the drainage data using the analytic hierarchy process (AHP), construct a judgment matrix, calculate the weight index, and normalize the judgment matrix and weight index to obtain the initial input value. Step S4: Combine the Kriging agent model with the bat model, and combine the water pressure on the pipes at different building heights with the runoff volume of water on the building surface to calculate the optimal layout of drainage pipes and drainage equipment with different functions and the optimal number of fire hydrants. Step S4 includes: Combining the Kriging agent model with the bat model includes: The BIM forward design method is used to measure known water pressure data points, and the water pressure distribution of each point inside the building is interpolated using the Kriging model, including water pressure changes at different heights. Based on the building shape, pipe slope and drainage system distribution modeled in step S1, the water flow situation on the building surface under different conditions is predicted. The water pressure, the volume of water flowing onto the building surface, the weight index of water balance relationship, the weight index of drainage volume range, the weight index of drainage efficiency, the weight index of maximum noise decibels, and the weight index of total water flow of fire hydrants are used as input variables, and the optimal value is used as the output variable of the combined model. The optimization objective is defined as the optimal layout of drainage pipes and drainage equipment with different functions, including the optimal number of fire hydrants. The parameters of the bat algorithm are set, including the number of drainage pipes and drainage equipment, water balance relationship, drainage efficiency, the range of audible noise decibels in the building, and the total water flow of fire hydrants. By incorporating the Kriging model and the Gaussian function as part of the objective function, and combining them with the actual needs in construction engineering, a comprehensive objective function is defined. Initialize the layout and function of drainage pipes and equipment. Update the layout of drainage pipes and equipment based on the current layout and function, and calculate a new objective function value. Calculate the initial feature data based on the objective function, form a matrix from the initial feature data, calculate the covariance matrix of the matrix, obtain the correlation between the input variables, select surrogate points among the input variables, and the surrogate points are the average attribute values ​​of the input variables respectively. Adjust the water balance relationship and drainage efficiency based on the drainage volume, maximum noise decibels, and total fire hydrant water flow. Update the optimal layout of the drainage pipes and equipment. Repeat the above steps until the pre-set number of iterations is reached. Adjust the surrogate point density and model parameters to obtain the combined model with the highest unbiased estimate. The maximum noise decibel weight index and the total water flow weight index of fire hydrants in the input variables are replaced by the water pressure generated by the pipes at different building heights and the runoff volume of water on the building surface. All steps of combining the Kriging surrogate model and the bat model are iteratively executed to obtain the second combined model. The final result of the second combined model and the first combined model is used as input and put into the Kriging surrogate model. The output is defined as the optimal layout, and the optimal layout prediction result is obtained. The prediction result includes the optimal number of fire hydrants.

2. The design method for a building water supply and drainage system as described in claim 1, characterized in that, Step S1 includes: Receive building information, deploy the drainage equipment required for the drainage system in the building's information model, the drainage equipment includes drainage pipes, sewers, inspection wells, drainage pumps and drain outlets, set parameters for the drainage equipment, establish a drainage system network in the building's information model, including combining and connecting drainage pipes, sewers, inspection wells, drainage pumps and drain outlets, and generate design documents including 3D model views, sectional views and construction drawings.

3. The design method for a building water supply and drainage system as described in claim 2, characterized in that, Step S2 includes: By simulating precipitation and runoff under different rainfall conditions, the water supply demand of the building's circulating water system is defined as the outflow from the storage tank. The inflow, outflow, overflow, and losses of the storage tank are calculated to assess the water balance under different conditions, including: Based on the building information model established in step S1, simulate precipitation events of different intensities and durations to set different precipitation conditions. Calculate the drainage volume range and water balance relationship of each pipe under various precipitation events according to the pipe attributes and precipitation conditions set in the model. The pipe attributes include pipe diameter and slope. Under the premise of controlling variables, simulate the drainage efficiency of drainage pipes and drainage equipment with different functions after different layout methods. Establish an acoustic model inside the building and a hydraulic model of the building's fire protection water system. Determine the noise generation characteristics of drainage pipes under different flow conditions. Simulate the propagation path and impact range of drainage pipe noise within the building. Calculate the maximum noise decibel value in different areas within the building, find the maximum noise decibel affecting people inside the building, and simulate the total water flow required for fire hydrants.

4. The design method for a building water supply and drainage system as described in claim 3, characterized in that: The water storage tank receives rainfall within its service area. When the tank is saturated and the rainfall exceeds the inflow, rainwater overflows. The inflow, infiltration, overflow, and storage capacity of the tank satisfy a water balance relationship. The mathematical expression for simulating the rainfall magnitude is as follows: Q = kψqs; Where Q is the amount of rainfall, k is the catchment coefficient, which is 1.5 when the water level is full and 0 when the water level is not full, ψ is the runoff coefficient, which ranges from 0.3 to 0.4, q is the design rainfall intensity, and s is the catchment area. The mathematical expression for designing the intensity of a rainstorm is: ； Where P is the design return period, t is the rainfall time, and A, c, b, and m are parameters of the area where the building is located, which are calculated and determined based on local statistical data and design specifications. The total volume of the water storage tank is determined by the inflow and outflow rates over a period of time, adjusted through water balance analysis. The mathematical expression for the total volume of the water storage tank is: ； in, This is the total volume of the water storage tank. The average inflow rate is the rainfall amount per unit time, which is determined by the simulated rainfall conditions in step S2. Let T be the average water demand per unit time, and T be the storage period.

5. The design method for a building water supply and drainage system as described in claim 4, characterized in that, Step S3 includes: The Analytic Hierarchy Process (AHP) specifically includes: A hierarchical structure model is established, which is divided into a target layer, a criterion layer, and an indicator layer from top to bottom. A judgment matrix is ​​constructed for each layer, including: A judgment matrix is ​​constructed using numbers 1-9 and their corresponding reciprocals as scales. The target layer consists of weighted indicators. The criterion layer includes the water balance relationship of the water storage tank, the range of drainage volume values, drainage efficiency, maximum noise level (decibels), and total water flow of the fire hydrant. The indicator layer includes weighted indicators for water balance relationship, drainage volume range, drainage efficiency, maximum noise level (decibels), and total water flow of the fire hydrant. A judgment matrix is ​​constructed based on the scale values ​​and rules of the judgment matrix from the lower layer to the upper layer. The rules include: When C i >C j At that time, C i With C j When the importance gap is the most important gap, the scale value is set to 1, C i With C j When the importance gap is the second most important gap, the scale value is set to 2, C i With C j When the importance gap is the third most important gap, the scale value is set to 3, C i With C j When the importance gap is the fourth most important gap, the scale value is set to 4, C i With C j When the importance gap is the fifth most important gap, the scale value is set to 5, C i With C j When the importance gap is the sixth most important gap, the scale value is set to 6, C i With C j When the importance gap is the seventh most important gap, the scale value is set to 7, C. i With C j When the importance gap is the eighth most important gap, the scale value is set to 8, C i With C j When the importance gap is the ninth most important gap, the scale value is set to 9; When C i <C j At that time, C i With C j The scale value is C when the importance difference is equal. i >C j The reciprocal of the time scale value; Among them, C i With C j These include the water balance relationship of the water storage tank, the range of drainage volume, the drainage efficiency, the maximum noise level, the total water flow of the fire hydrant, the weight index of the water balance relationship, the weight index of the drainage volume range, the weight index of the drainage efficiency, the weight index of the maximum noise level, and the weight index of the total water flow of the fire hydrant. The judgment matrix is ​​normalized sequentially. The normalized judgment matrix is ​​then summed row by row to obtain the same number of vectors as the judgment matrix. All vectors are concatenated into a matrix and then column normalized to obtain the eigenvectors of the matrix. The maximum eigenvalue of the concatenated matrix is ​​calculated based on the eigenvectors. The consistency of the vectors and the concatenated matrix is ​​then checked based on the maximum eigenvalue. If the consistency test is passed, the weight indexes of water balance relationship, drainage volume range, drainage efficiency, maximum noise decibels and total water flow of fire hydrants are obtained according to the rules. All weight indexes are normalized in sequence to obtain the initial input values. If the consistency check fails, the scale value is adjusted, and the judgment matrix is ​​normalized sequentially. The normalized judgment matrix is ​​then summed row by row to obtain the same number of vectors as the judgment matrix. All vectors are concatenated into a matrix and then column normalized to obtain the eigenvectors of the matrix. The maximum eigenvalue of the concatenated matrix is ​​calculated based on the eigenvectors, and the consistency check of the vectors and the concatenated matrix is ​​performed based on the maximum eigenvalue.

6. The design method for a building water supply and drainage system as described in claim 5, characterized in that, The mathematical expression for the water pressure exerted on the pipes at different heights of the building is: H； Where p is pressure, The density of water, It is the acceleration due to gravity. For height; The volume of water accumulation on the building surface includes: The surface runoff process is solved using the finite volume method to solve the two-dimensional shallow water equation. The vector form of the two-dimensional nonlinear shallow water equation is as follows: ； ； ； ； ； in, For variable vectors, For the water depth on the grid, The unit width flow rate in the x-direction, Let x represent the unit width flow rate in the y-direction, and let x be the horizontal axis of the Cartesian coordinate system, and y be the vertical axis. It is the acceleration due to gravity. For the flow velocity in the x direction, Let be the flow velocity in the y-direction. Let x be the flux in the x and y directions. These are vectors in the x and y directions. This is the source term vector, which includes the surface slope source term and the frictional resistance source term. Net rainfall rate This refers to the surface elevation. The roughness coefficient of the catchment surface is given by the following mathematical expression: ； in, denoted as Manning's coefficient for the catchment area.

7. The design method for a building water supply and drainage system as described in claim 6, characterized in that: The selection of agent points includes: The attribute values ​​of the unknown arrangement are estimated by minimizing the sum of squared interpolation errors. The attribute values ​​of the surrogate points are obtained by weighted averaging. The weights of each input variable depend on the weighted average of the weights of the two most relevant input variables.

8. The design method for a building water supply and drainage system as described in claim 7, characterized in that: Based on the analysis results, optimize the layout of drainage equipment. Under the premise of meeting the actual safety and efficiency requirements, arrange drainage pipes and equipment according to the geometric and spatial constraints of the building model.

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