An optimization method for the overall building layout design based on building fire prevention requirements

Abstract

The present invention discloses an optimization method for the overall building plane design based on building fire prevention requirements, which includes constructing an initial building plane model and conducting data collection, performing a fire prevention and control simulation experiment on the initial model, setting up a data processing model for analysis and processing, optimizing the design of the initial model, and generating an optimal building plane optimization model. The present invention collects fire prevention facility data by constructing an initial building plane model, collects fire prevention and control data through experimental simulation, then sets up a data processing model to evaluate the effectiveness of fire prevention isolation belts, emergency channels, and fire facility points, and further comprehensively evaluates the fire prevention performance of the initial building plane model, and generates an optimization plan for the building model, so as to make refined adjustments to the building plane design, improve the efficiency of building model optimization, and reduce the risk of fire spread in the building in case of a fire by reasonably planning the system layout of building fire prevention facilities, and improve the fire prevention and control efficiency of the building.

Description

Technical Field

[0001] The present invention relates to the technical field of architectural design, and particularly to an optimization method for the overall building plan design based on building fire prevention requirements. Background Art

[0002] The overall building plan design not only affects construction safety and progress, but also directly relates to the final acceptance and use safety of buildings. Fire protection design occupies an important position in the overall building plan design, involving aspects such as fire truck passageways, personnel evacuation, elevated fire fighting, and fire blocking. Scientific and reasonable fire protection design can effectively control the spread of fire, ensuring that in case of a fire, firefighters can quickly reach the scene for effective fire fighting and personnel evacuation;

[0003] However, the existing technologies for optimizing the overall building plan design based on building fire prevention requirements have deficiencies in systematicness and refinement. Since building fire protection facilities include multiple prevention and control means such as fire isolation belts, emergency passages, and fire protection facility points, and there is a lack of systematic analysis and refined adjustment for fire protection facilities during the building plan design process, it will result in low optimization efficiency of the building plan design model and the resulting low fire prevention and control effectiveness of buildings;

[0004] In view of the above technical deficiencies, a solution is proposed. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies in the existing technologies, such as insufficient systematicness and refinement, low optimization efficiency of the building plan design model, and low fire prevention and control effectiveness of buildings. The present invention collects fire protection facility data through constructing an initial building plan model, and collects fire prevention and control data through experimental simulation. Then, a data processing model is set up to evaluate the effectiveness of fire isolation belts, emergency passages, and fire protection facility points, and further comprehensively evaluate the fire prevention performance of the initial building plan model, and generate an optimized building model plan, thereby making refined adjustments to the building plan design, improving the optimization efficiency of the building model, and reducing the risk of fire spread in the building in case of a fire by reasonably planning the system layout of building fire protection facilities, and improving the fire prevention and control effectiveness of buildings.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions:

[0007] An optimization method for the overall building plan design based on building fire prevention requirements, comprising the following steps:

[0008] Step 1, construct an initial building plan model and conduct data collection: collect fire protection facility data of the initial building plan model through the initial building plan model, and the fire protection facility data includes building parameters of fire isolation belts, emergency passages, and fire protection facility points;

[0009] Step 2, conduct a fire prevention and control simulation experiment on the initial building floor plan model: collect fire prevention and control data of the initial building floor plan model through the fire prevention and control simulation experiment;

[0010] Step 3, analyze and process the fire prevention facility data and the fire prevention and control data: set up a data processing model to analyze and process the fire prevention facility data and the fire prevention and control data, evaluate the effectiveness of the fire prevention isolation belt, the emergency passage and the fire fighting facility points, and then comprehensively evaluate the fire prevention performance of the initial building floor plan model by combining the fire prevention facility data and the fire prevention and control data, and generate an optimization plan for the building model;

[0011] Step 4, optimize the design of the initial building floor plan model: optimize the design of the initial building floor plan model through the model optimization management plan, so as to adjust the fire prevention facilities of the initial building floor plan model and obtain an optimized building floor plan model;

[0012] Step 5, generate the optimal optimized building floor plan model: cycle through the fire prevention and control simulation experiment by feeding back to Step 1, so as to refresh the optimized building floor plan model, and set a building cost threshold to obtain the optimal optimized building floor plan model within the preset building cost range.

[0013] Furthermore, the specific process of collecting and analyzing the fire prevention facility data of the initial building floor plan model is as follows:

[0014] Evaluate the effectiveness of the fire prevention isolation belt through the building parameters of the fire prevention isolation belt; the fire prevention isolation belt includes a firewall and a green belt; among them, the building parameters of the fire prevention isolation belt include the material fire resistance level and height of the firewall, and the area and width of the green belt;

[0015] Evaluate the effectiveness of the emergency passage through the building parameters of the emergency passage; the emergency passage includes an emergency evacuation passage and an emergency rescue passage; among them, the building parameters of the emergency passage include the route, width and height of the emergency evacuation passage, and the route and road surface bearing capacity of the emergency rescue passage;

[0016] Evaluate the effectiveness of the fire fighting facility points through the building parameters of the fire fighting facility points; the fire fighting facility points include fire hydrants, fire extinguishers and sprinkler nozzles; among them, the building parameters of the fire fighting facility points include the number and location of the fire fighting facility points.

[0017] Furthermore, the specific process of evaluating the effectiveness of the fire prevention isolation belt is as follows:

[0018] The fire prevention isolation belt includes a firewall and a green belt, and extract the contour lines of the firewall and the green belt through the initial building floor plan model;

[0019] Mark the number of firewalls as n1, and mark the fire resistance level and height of any firewall f as Rf and Hf in sequence; mark the number of green belts as n2, and mark the area and width of any green belt h as Sh and Lh in sequence.

[0020] Combine the fire resistance level Rf and height Hf of n1 firewalls f, and the area Sh and width Lh of n2 green belts h to obtain the effectiveness evaluation coefficient X1 of the fire separation belt.

[0021] Furthermore, the specific process for evaluating the effectiveness of the emergency passage is as follows:

[0022] The emergency passage includes an emergency evacuation passage and an emergency rescue passage. Extract and mark the total paths of the emergency evacuation passage and the emergency rescue passage from the initial building plane model.

[0023] Perform breakpoint segmentation on the total path of the emergency evacuation passage to obtain n3 emergency evacuation passages.

[0024] Mark the route length, width, and height of any emergency evacuation passage s as Gs, Ls, and Hs in sequence.

[0025] Combine the route length Gs, width Ls, and height Hs of the emergency evacuation passage s to obtain the effectiveness evaluation factor Ys of the emergency evacuation passage s. [[ID=2))

[0026] Perform breakpoint segmentation on the total path of the emergency rescue passage to obtain n4 emergency rescue passages.

[0027] Mark the route length and road surface bearing capacity of any emergency rescue passage j as Gj and Zj in sequence.

[0028] Combine the route length Gj and road surface bearing capacity Zj of the emergency rescue passage j to obtain the effectiveness evaluation factor Yj of the emergency rescue passage j.

[0029] Combine the effectiveness evaluation factor Ys of the emergency evacuation passage s, the effectiveness evaluation factor Yj of the emergency rescue passage j, and the number n3 of emergency evacuation passages and the number n4 of emergency rescue passages to obtain the effectiveness evaluation coefficient X2 of the emergency passage.

[0030] Furthermore, the specific process for evaluating the effectiveness of the fire protection facility points is as follows:

[0031] The fire protection facility points include fire hydrants, fire extinguishers, and sprinkler nozzles; among them, the building parameters of the fire protection facility points include the number and location of the fire protection facility points.

[0032] Mark the number of fire protection facility points as n5, mark the position and its coordinates of any fire protection facility point d as Wd(Xw, Yw), and mark the number of fire protection facility points d as Md;

[0033] Analyze the coincidence degree between the position Wd of the fire protection facility point d and the route of the emergency evacuation passage s:

[0034] When the position Wd of the fire protection facility point d is located on the total path of the emergency evacuation passage, it is determined that the position Wd of the fire protection facility point d is valid, set and mark the effective value Dyou of this fire protection facility point d as 1, and mark the shortest distance Dmin between the fire protection facility point d and the emergency evacuation passage as 0;

[0035] When the position Wd of the fire protection facility point d is not located on the total path of the emergency evacuation passage, measure the shortest distance Dmin between the fire protection facility point d and the emergency evacuation passage, and mark the effective value Dyou of this fire protection facility point d as 0;

[0036] Integrate and mark the effective value Dyou and the shortest distance Dmin as the reference dataset of the fire protection facility point d, and obtain the effectiveness evaluation coefficient X3 of the fire protection facility point through the reference dataset of the fire protection facility point d.

[0037] Furthermore, the specific process of collecting and analyzing fire prevention and control data is as follows:

[0038] Conduct fire prevention and control simulation experiments through computer fire simulation and simulation technology to collect fire prevention and control data of the initial building plane model; the fire prevention and control data includes the diffusion paths of toxic gases and smoke particles, as well as the heat transfer path;

[0039] Perform corresponding path regional imaging on the fire prevention and control data through RGB imaging technology, generate a first imaging picture for the diffusion path of toxic gases, generate a second imaging picture for the diffusion path of smoke particles, and generate a third imaging picture for the heat transfer path;

[0040] Mark the number of imaging areas of any imaging picture of the initial building plane model as m0, mark any imaging area of this imaging picture as z, mark the area of the imaging area z as Sz, and mark the RGB parameter vector of the imaging area z as , where Rz is the red component value, Gz is the green component value, and Bz is the blue component value;

[0041] Synthesize and obtain the fire risk assessment index Z0 through the combination of the RGB parameter vectors of the m0 imaging areas z corresponding to all imaging pictures.

[0042] Furthermore, the specific process of comprehensively evaluating the fire prevention performance of the initial building plane model is as follows:

[0043] Control the fire risk by starting the fire prevention facilities through fire prevention and control simulation experiments, calculate and obtain the effectiveness evaluation coefficients of the fire prevention isolation belt, emergency passage and fire fighting facilities points in operation, and mark them as the effective operation coefficient Xr1 of the fire prevention isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage and the effective operation coefficient Xr3 of the fire fighting facilities points respectively;

[0044] Set the data calculation period Ts to calculate the fire risk assessment index Z0 regularly, so as to combine the effective operation coefficient Xr1 of the fire prevention isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage, the effective operation coefficient Xr3 of the fire fighting facilities points with the fire risk assessment index Z0 to obtain the fire prevention performance influence function F0;

[0045] Set the evaluation interval of the fire prevention performance influence function F0, and evaluate the fire prevention performance of the initial building plane model through interval comparison to generate corresponding optimization management signals.

[0046] Furthermore, the specific process of generating the building model optimization plan is as follows:

[0047] When receiving the optimization management signal, deeply analyze the effective operation coefficient Xr1 of the fire prevention isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage, and the effective operation coefficient Xr3 of the fire fighting facilities points;

[0048] Set the regulation thresholds of the fire prevention isolation belt, emergency passage and fire fighting facilities points respectively. By comparing the effective operation coefficients of the fire prevention isolation belt, emergency passage and fire fighting facilities points with their corresponding regulation thresholds, determine whether to optimize the fire prevention facilities, and obtain the corresponding optimization plan in combination with the optimization management signal level;

[0049] Integrate and mark the optimization plans of the fire prevention isolation belt, emergency passage and fire fighting facilities points as the building model optimization plan.

[0050] To sum up, due to the adoption of the above technical solutions, the beneficial effects of the present invention are:

[0051] The present invention collects fire prevention facility data by constructing an initial building plane model, collects fire prevention and control data through experimental simulation, then sets up a data processing model to evaluate the effectiveness of the fire prevention isolation belt, emergency passage and fire fighting facilities points, and further systematically evaluates the fire prevention performance of the initial building plane model, and generates a building model optimization plan, so as to make a refined adjustment to the building plane design, improve the efficiency of building model optimization, and reduce the risk of fire spread in the building in case of a fire by reasonably planning the system layout of building fire prevention facilities, and improve the building fire prevention and control efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The figure shows a schematic diagram of the steps of the overall process of the present invention;

[0053] Figure 2 The flowchart shows the data processing model of the present invention. Specific embodiments

[0054] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] Embodiment 1:

[0056] As Figure 1 - Figure 2 shown, an optimization method for the overall building plan design based on building fire protection requirements includes the following steps:

[0057] S1. Construct an initial building plane model and collect data: Collect the fire protection facility data of the initial building plane model through the initial building plane model;

[0058] The fire protection facility data includes the building parameters of fire separation belts, emergency channels, and fire protection facility points;

[0059] Perform the overall building plan design through AutoCAD to draw the initial building plane model, which includes the overall building plan, the horizontal cross-sectional view of the building floor, and the side elevation view of the building;

[0060] The initial building plane model is manually designed and drawn. During the drawing process, professional management personnel mark the corresponding area names, so as to extract the physical parameters of the corresponding areas from the initial building plane model, including position coordinates and dimensions, and scale them proportionally according to the model size to obtain the size parameters of the actual area. Among them, the one-dimensional scaling ratio between the preset actual area and the building model is e. When the size of the building model is m0, the size of the actual area is m1: ;

[0061] S1-1. The fire separation belt includes a firewall and a green belt; among them, the building parameters of the fire separation belt include the material fire resistance level and height of the firewall, and the area and width of the green belt;

[0062] Extract the contour lines of the firewall and the green belt through the initial building plane model;

[0063] Mark the number of firewalls as n1, and mark the material fire resistance level and height of any firewall f as Rf and Hf in sequence;

[0064] S1-2. The emergency passage includes an emergency evacuation passage and an emergency rescue passage. Among them, the building parameters of the emergency passage include the route, width and height of the emergency evacuation passage, and the route and road surface bearing capacity of the emergency rescue passage.

[0065] Extract and mark the total paths of the emergency evacuation passage and the emergency rescue passage from the initial building plane model.

[0066] S1-3. The fire protection facility points include fire hydrants, fire extinguishers and sprinkler nozzles. Among them, the building parameters of the fire protection facility points include the quantity and location of the fire protection facility points, that is, the quantity and location of the fire hydrants, fire extinguishers and sprinkler nozzles.

[0067] Mark the quantity of the fire protection facility points as n5, mark the location and its coordinates of any fire protection facility point d as Wd(Xw, Yw), and mark the quantity of the fire protection facility point d as Md.

[0068] S2. Conduct a fire prevention and control simulation experiment on the initial building plane model: Collect the fire prevention and control data of the initial building plane model through the fire prevention and control simulation experiment.

[0069] Conduct a fire prevention and control simulation experiment through the computer fire simulation and simulation technology in the existing building design, so as to collect the fire prevention and control data of the initial building plane model. Among them, the computer fire simulation and simulation technology is created based on the historical data of building fire prevention and control, and the actual fire development and spread situation is affected by multiple random factors. Therefore, the experimental simulation data is only used as an auxiliary reference at the building design level.

[0070] The fire prevention and control data includes the diffusion paths of toxic gases and smoke particles during the combustion of the fire source, and the heat transfer path.

[0071] S3. Analyze and process the fire protection facility data and the fire prevention and control data: Set up a data processing model to analyze and process the fire protection facility data and the fire prevention and control data, evaluate the effectiveness of the fire prevention isolation belt, emergency passage and fire protection facility points, and then combine the fire protection facility data and the fire prevention and control data to comprehensively evaluate the fire prevention performance of the initial building plane model and generate an optimized building model plan.

[0072] S3-1. The specific process of analyzing the fire protection facility data of the initial building plane model is as follows:

[0073] S3-101. Evaluate the effectiveness of the fire prevention isolation belt through the building parameters of the fire prevention isolation belt. The fire prevention isolation belt includes a firewall and a green belt. Among them, the building parameters of the fire prevention isolation belt include the material fire resistance level and height of the firewall, and the area and width of the green belt.

[0074] The requirements for the general building plan design include the minimum threshold Rmin of the fire resistance level of the material of the firewall f. The fire resistance level Rf of the material of the firewall f is set and obtained according to the requirements for the general building plan design, and the fire resistance level Rf of the material is always higher than the minimum threshold Rmin;

[0075] The model height Hmf of the firewall f is obtained through the contour line of the firewall in the initial building plan model, and the height Hf of the firewall f is obtained by scaling up the model height Hmf proportionally: ;

[0076] The number of green belts is marked as n2, and the area and width of any one green belt h are marked as Sh and Lh in sequence;

[0077] The model area Smh and model width Lmh of the green belt h are obtained through the contour line of the green belt in the initial building plan model, and the area Sh and width Lh of the green belt h are obtained by scaling up the model area Smh and model width Lmh proportionally, where , ;

[0078] By combining the fire resistance level Rf and height Hf of n1 firewalls f, and the area Sh and width Lh of n2 green belts h, the effectiveness evaluation coefficient X1 of the fire separation belt is obtained:

[0079] ;

[0080] Among them, 、 、 、 are the conversion factor coefficients of the fire resistance level Rf, height Hf, area Sh and width Lh respectively, and 、 、 、 are all greater than 0. The conversion factor coefficient is a preset constant for converting the initial parameter value into the effectiveness evaluation coefficient. The preset value of the conversion factor coefficient is preset after being calculated through a large number of data experiments;

[0081] By combining the fire resistance level Rf and height Hf of the firewall f, the firewall effectiveness evaluation factor is obtained. When the fire resistance level Rf and height Hf of the firewall f are higher, the firewall effectiveness evaluation factor is higher; by combining the area Sh and width Lh of the green belt h, the green belt effectiveness evaluation factor is obtained. When the area Sh and width Lh of the green belt h are higher, the green belt effectiveness evaluation factor is higher;

[0082] Then, φ1 and φ2 are the weight factor coefficients of the firewall effectiveness evaluation factor and the green belt effectiveness evaluation factor respectively. The weight factor coefficients are obtained through presetting, and both φ1 and φ2 are greater than 0. When the firewall effectiveness evaluation factor and the green belt effectiveness evaluation factor are higher, the effectiveness evaluation coefficient X1 of the fire prevention isolation belt is higher, and the effective degree of the fire prevention isolation belt is higher.

[0083] S3-102. Analyze the building parameters of the emergency passage to evaluate the effectiveness of the emergency passage. The emergency passage includes an emergency evacuation passage and an emergency rescue passage. Among them, the building parameters of the emergency passage include the route, width, and height of the emergency evacuation passage, and the route and road surface bearing capacity of the emergency rescue passage.

[0084] S3-102-1. Perform breakpoint segmentation on the total path of the emergency evacuation passage. The breakpoints include the exit point, entry point, and intersection of the fork of the emergency evacuation passage, so as to obtain n3 emergency evacuation passages.

[0085] Mark the route length, width, and height of any emergency evacuation passage s as Gs, Ls, and Hs in sequence.

[0086] Combine the route length Gs, width Ls, and height Hs of the emergency evacuation passage s to obtain the effectiveness evaluation factor Ys of the emergency evacuation passage s: , where is the conversion factor coefficient of the emergency evacuation passage, and it is preset that is greater than 0.

[0087] S3-102-2. Perform breakpoint segmentation on the total path of the emergency rescue passage. The breakpoints include the exit point, entry point, and intersection of the fork of the emergency rescue passage, so as to obtain n4 emergency rescue passages.

[0088] Mark the route length and road surface bearing capacity of any emergency rescue passage j as Gj and Zj in sequence. The road surface bearing capacity Zj is obtained by conducting a bearing capacity experiment test on the road surface pouring material set according to the model to obtain the maximum pressure that the road surface can bear under the load, which is the road surface bearing capacity Zj.

[0089] Combine the route length Gj and road surface bearing capacity Zj of the emergency rescue passage j to obtain the effectiveness evaluation factor Yj of the emergency rescue passage j: , where is the conversion factor coefficient of the emergency evacuation passage, and it is preset that is greater than 0.

[0090] S3-102-3, by combining the effectiveness evaluation factor Ys of the emergency evacuation passage s, the effectiveness evaluation factor Yj of the emergency rescue passage j, the number n3 of the emergency evacuation passages, and the number n4 of the emergency rescue passages, the effectiveness evaluation coefficient X2 of the emergency passage is obtained:

[0091] ;

[0092] Among them, by combining the number n3 of the emergency evacuation passages and the number n4 of the emergency rescue passages, the path smoothness factor is obtained. When the number n3 of the emergency evacuation passages and the number n4 of the emergency rescue passages are higher, the path smoothness factor is lower, indicating that the path smoothness is lower and there are more turns at the path corners, which means the path complexity is higher;

[0093] Then 、 and are the weight factor coefficients of the effectiveness evaluation factor Ys, the effectiveness evaluation factor Yj, and the path smoothness factor respectively, and 、 and are all greater than 0, ; when the effectiveness evaluation factor Ys, the effectiveness evaluation factor Yj, and the path smoothness factor are higher, the effectiveness evaluation coefficient X2 of the emergency passage is higher, and the effective degree of the emergency passage is evaluated higher;

[0094] S3-103, evaluate the effectiveness of the fire protection facility points through the analysis of the building parameters of the fire protection facility points; the fire protection facility points include fire hydrants, fire extinguishers, and sprinkler nozzles; among them, the building parameters of the fire protection facility points include the number and location of the fire protection facility points;

[0095] Calculate the coincidence degree between the location Wd of the fire protection facility point d and the route of the emergency evacuation passage s:

[0096] When the location Wd of the fire protection facility point d is on the total path of the emergency evacuation passage, it is determined that the location Wd of the fire protection facility point d is effective, and the effective value Dyou = 1 of the fire protection facility point d is set and marked, and the shortest distance Dmin between the fire protection facility point d and the emergency evacuation passage is marked as 0;

[0097] When the location Wd of the fire protection facility point d is not on the total path of the emergency evacuation passage, the shortest distance Dmin between the fire protection facility point d and the emergency evacuation passage is measured, and the effective value Dyou = 0 of the fire protection facility point d is marked; the shortest distance Dmin is obtained through the existing geometric function from a point to a line or obtained by directly measuring with a drawing software and then scaling up proportionally;

[0098] Integrate the effective value Dyou and the nearest distance Dmin as the reference dataset of the fire facility point d, and obtain the effectiveness evaluation coefficient X3 of the fire facility point through the reference dataset of the fire facility point d:

[0099] ;

[0100] Among them, by calculating the proportion of the cumulative value of the effective value Dyou in the number n5 of fire facility points, the coincidence factor coefficient of the fire facility point is obtained. The higher the proportion of the effective value Dyou, the more coincidence points there are between the fire facility point and the emergency evacuation passage, indicating that the position setting of the fire facility point is more effective and convenient for using the fire facility to control the fire during the emergency evacuation process;

[0101] By calculating the reciprocal of the average value of the nearest distance Dmin between the non - coincident fire facility points and the emergency evacuation passage, the distance factor coefficient is obtained. The higher the average value of the nearest distance Dmin, the lower the distance factor coefficient, indicating that the fire facility point is farther from the emergency evacuation passage, which means that the fire facility is not convenient to obtain for emergency use;

[0102] Then and are the weight factor coefficients of the coincidence factor coefficient and the distance factor coefficient respectively, and it is preset that and are both greater than 0, ; when the coincidence factor coefficient and the distance factor coefficient are higher, the effectiveness evaluation coefficient X3 of the fire facility point is higher, and the evaluation of the effectiveness degree of the fire facility point is better;

[0103] S3 - 2, the specific process of analyzing the fire prevention and control data is as follows:

[0104] Through the RGB imaging technology, perform corresponding path regional imaging on the fire prevention and control data. Generate the first imaging picture for the diffusion path of toxic gases, the second imaging picture for the diffusion path of smoke particles, and the third imaging picture for the heat transfer path;

[0105] Mark the number of imaging regions of any imaging picture of the initial building plane model as m0, mark any imaging region of this imaging picture as z, mark the area of the imaging region z as Sz, and mark the RGB parameter vector of the imaging region z as , where Rz is the red component value, Gz is the green component value, and Bz is the blue component value;

[0106] By combining the RGB parameter vectors of the m0 imaging regions z corresponding to all the imaging pictures, comprehensively obtain the fire risk assessment index Z0:

[0107] ;

[0108] Among them, , and are respectively the weight factor coefficients of the red component value Rz, the green component value Gz, and the blue component value Bz, and , and are preset through a large number of data experiments and measurements, and , and are all greater than 0. By combining with the RGB parameter vector of the imaging area z, the fire parameter risk degree of the imaging area z is evaluated. Furthermore, by combining with the area Sz of the imaging area z, the fire risk of any fire prevention and control parameter of the building model of m0 imaging areas is comprehensively evaluated;

[0109] Then refers to the weight factor coefficient of any fire prevention and control parameter, and is greater than 0. The fire prevention and control data include 3 fire prevention and control parameters, namely toxic gases, smoke particles, and heat transfer paths. The diffusion paths of the 3 fire prevention and control parameters respectively obtain the first imaging picture, the second imaging picture, and the third imaging picture, and the weight factor coefficients , and of the RGB component values of different imaging pictures have different preset values;

[0110] S3-3. The specific process of comprehensively evaluating the fire prevention performance of the initial building plane model is as follows:

[0111] Through the fire prevention and control simulation experiment, start the fire prevention facilities to control the fire risk, extract the data of the fire prevention facilities in the startup operation, substitute them into the calculation formulas of the effectiveness evaluation coefficient X1 of the fire prevention isolation belt, the effectiveness evaluation coefficient X2 of the emergency passage, and the effectiveness evaluation coefficient X3 of the fire fighting facility point, calculate and obtain the effectiveness evaluation coefficients of the fire prevention isolation belt, the emergency passage, and the fire fighting facility point in the startup operation, and mark them as the effective operation coefficient Xr1 of the fire prevention isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage, and the effective operation coefficient Xr3 of the fire fighting facility point respectively;

[0112] Set the data calculation period Ts to regularly calculate the fire risk assessment index Z0, so as to combine the effective operation coefficient Xr1 of the fire prevention isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage, the effective operation coefficient Xr3 of the fire fighting facility point with the fire risk assessment index Z0 to obtain the fire prevention performance influence function F0:

[0113] ;

[0114] Among them, is the fire prevention performance conversion coefficient, and Greater than 0; when the effective operation coefficient Xr1 of the fireproof isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage, and the effective operation coefficient Xr3 of the fire-fighting facility points are higher, and the fire risk assessment index Z0 is lower, the fireproof performance influence function F0 is higher, and thus the evaluated fireproof performance is better;

[0115] Set the evaluation interval of the fireproof performance influence function F0, and evaluate the fireproof performance of the initial building plane model through interval comparison;

[0116] There are U preset evaluation intervals of the fireproof performance influence function F0. Any one of the evaluation intervals is marked as Qu, where u is the subscript of the evaluation interval, and 0 < u ≤ U; when the fireproof performance influence function F0 is within the evaluation interval Qu, it is determined that the fireproof performance of the initial building plane model is Nu level, and an Nu-level optimization management signal is generated;

[0117] S4. Optimize the design of the initial building plane model: Optimize the design of the initial building plane model through the model optimization management plan, so as to adjust the fireproof facilities of the initial building plane model and obtain the optimized building plane model. The specific process is as follows:

[0118] When receiving the Nu-level optimization management signal, deeply analyze the effective operation coefficient Xr1 of the fireproof isolation belt, the effective operation evaluation coefficient Xr2 of the emergency passage, and the effective operation coefficient Xr3 of the fire-fighting facility points;

[0119] Respectively set the regulation thresholds of the fireproof isolation belt, the emergency passage, and the fire-fighting facility points. By comparing the effective operation coefficients of the fireproof isolation belt, the emergency passage, and the fire-fighting facility points with their corresponding regulation thresholds, determine whether to optimize the fireproof facilities, and obtain the corresponding optimization plan in combination with the optimization management signal level. The specific process is as follows:

[0120] Set the regulation threshold W1 of the fireproof isolation belt. When the effective operation coefficient Xr1 of the fireproof isolation belt is lower than the regulation threshold W1, optimize the setting of the fireproof isolation belt: When the level Nu of the optimization management signal is higher, the optimization amplitude of the fireproof isolation belt is higher, including improving the material fire resistance level and height of the firewall, and expanding the area and width of the green belt. The specific improvement amplitude is set through the level Nu of the optimization management signal and in combination with the actual situation. For example, when the material fire resistance level of the firewall cannot be further improved, no treatment is made, and a new firewall can be set separately or the height of the existing firewall can be increased;

[0121] Set the control threshold W2 for the emergency passage. When the effective operation coefficient Xr2 of the emergency passage is lower than the control threshold W2, optimize the setting of the emergency passage: the higher the level Nu of the optimization management signal, the higher the optimization amplitude of the emergency passage, including improving the path smoothness of the emergency evacuation passage and the emergency rescue passage, reducing the number of path corners, and lowering the channel complexity;

[0122] Set the control threshold W3 for the fire protection facility points. When the effective operation coefficient Xr3 of the fire protection facility points is lower than the control threshold W3, optimize the setting of the fire protection facility points: the higher the level Nu of the optimization management signal, the higher the optimization amplitude of the fire protection facility points, including improving the quantity and position of fire hydrants, fire extinguishers and sprinkler nozzles, avoiding the setting of fire protection facility points at inefficient positions, and increasing the number of fire protection facility points within the range of building cost control;

[0123] Integrate and mark the optimization schemes of the fireproof isolation belt, emergency passage and fire protection facility points as the building model optimization scheme, and optimize the initial building plane model through the building model optimization scheme to continuously increase the value of the fire protection performance influence function F0;

[0124] S5. Generate the optimal building plane optimization model: Through feedback to step one, conduct the fire prevention and control simulation experiment in a loop, thereby refreshing the building plane optimization model, and set the building cost threshold to obtain the optimal building plane optimization model within the preset building cost range;

[0125] Among them, the optimal building plane optimization model refers to the building plane optimization model corresponding to the highest fire protection performance value obtained through multiple optimization designs.

[0126] In summary, the present invention collects fire protection facility data by constructing an initial building plane model, collects fire prevention and control data through experimental simulation, then sets a data processing model to evaluate the effectiveness of the fireproof isolation belt, emergency passage and fire protection facility points, and further comprehensively evaluates the fire protection performance of the initial building plane model, and generates a building model optimization scheme, thereby making refined adjustments to the building plane design, improving the building model optimization efficiency, and reducing the risk of fire spread in the building in case of a fire by reasonably planning the layout of building fire protection facilities, and improving the fire prevention and control efficiency of the building.

[0127] The setting of the size of the interval and threshold is for the convenience of comparison. Regarding the size of the threshold, it depends on the amount of sample data and the number of base numbers set by those skilled in the art for each group of sample data; as long as it does not affect the proportional relationship between the parameters and the quantified values.

[0128] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data for software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation;

[0129] The above is only the preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the technical field, within the technical scope disclosed by the present invention, according to the technical solution and inventive concept of the present invention, makes equivalent substitutions or changes, and all should be covered within the protection scope of the present invention.

Claims

1. A method for optimizing building master plan design based on building fire protection requirements, characterized by: The following steps are involved: Step 1: Construct an initial building plane model and collect data: collect fire protection facility data of the initial building plane model through the initial building plane model. The fire protection facility data includes building parameters of fire isolation zones, emergency passages, and fire protection facility points; Step 2: Conduct a fire prevention and control simulation experiment on the initial building plane model: collect fire prevention and control data of the initial building plane model through the fire prevention and control simulation experiment; Step 3: Analyze and process fire prevention facility data and fire prevention and control data: Set up a data processing model to analyze and process fire prevention facility data and fire prevention and control data, evaluate the effectiveness of fire isolation zones, emergency passages, and firefighting facilities, and then, by combining fire prevention facility data with fire prevention and control data, comprehensively evaluate the fire protection performance of the initial building plan model and generate a building model optimization plan; Step 4: Optimize the design of the initial building plane model: Optimize the design of the initial building plane model through the model optimization management solution, thereby adjusting the fire protection facilities of the initial building plane model and obtaining an optimized building plane model; Step 5: Generate the optimal building plane optimization model: By feeding back to step 1, the fire prevention and control simulation experiment is circulated to refresh the building plane optimization model, and the building cost threshold is set to obtain the optimal building plane optimization model within the preset building cost range.

2. The method for optimizing building master plan design based on building fire protection requirements according to claim 1, characterized in that: The specific process of collecting and analyzing the fire protection facility data of the initial building plan model is as follows: The effectiveness of fire barriers is evaluated by analyzing their architectural parameters. Fire barriers include fire walls and green belts. The architectural parameters of fire barriers include the fire resistance rating and height of the fire walls, and the area and width of the green belts. The effectiveness of emergency passages is evaluated through architectural parameter analysis of emergency passages; emergency passages include emergency evacuation passages and emergency rescue passages; the architectural parameters of emergency passages include the route, width, and height of emergency evacuation passages, as well as the route and pavement bearing capacity of emergency rescue passages; The effectiveness of fire protection facilities is evaluated through analysis of their architectural parameters; fire protection facilities include fire hydrants, fire extinguishers, and sprinkler nozzles; among which, the architectural parameters of fire protection facilities include the number and location of fire protection facilities.

3. The method for optimizing building master plan design based on building fire protection requirements according to claim 2, characterized in that: The specific process for evaluating the effectiveness of firebreaks is as follows: The fire isolation zone includes a fire wall and a green belt. The outlines of the fire wall and the green belt are extracted through the initial building plane model. The number of firewalls is marked as n1, and the fire resistance level and height of any firewall f are marked as Rf and Hf respectively; the number of green belts is marked as n2, and the area and width of any green belt h are marked as Sh and Lh respectively; The effectiveness evaluation coefficient X1 of the fire isolation zone is obtained by combining the material fire resistance level Rf and height Hf of n1 fire walls f and the area Sh and width Lh of n2 green belts h.

4. The method for optimizing building master plan design based on building fire protection requirements according to claim 3, characterized in that: The specific process of evaluating the effectiveness of emergency channels is as follows: Emergency passages include emergency evacuation passages and emergency rescue passages. The total paths of emergency evacuation passages and emergency rescue passages are extracted and marked through the initial building plane model. The total path of the emergency evacuation channel is divided into breakpoints to obtain n3 emergency evacuation channels; Mark the length, width and height of any emergency evacuation passage s as Gs, Ls and Hs respectively; The effectiveness evaluation factor Ys of the emergency evacuation channel s is obtained by combining the route length Gs, width Ls and height Hs of the emergency evacuation channel s; The total path of the emergency rescue channel is divided into breakpoints to obtain n4 emergency rescue channels; The route length and road bearing capacity of any emergency rescue channel j are marked as Gj and Zj respectively; The effectiveness evaluation factor Yj of emergency rescue channel j is obtained by combining the route length Gj of emergency rescue channel j and the road bearing capacity Zj; The effectiveness evaluation coefficient X2 of the emergency channel is obtained by combining the effectiveness evaluation factor Ys of the emergency evacuation channel s, the effectiveness evaluation factor Yj of the emergency rescue channel j, the number n3 of the emergency evacuation channels, and the number n4 of the emergency rescue channels.

5. The method for optimizing building master plan design based on building fire protection requirements according to claim 4, characterized in that: The specific process of evaluating the effectiveness of fire protection facilities is as follows: Fire protection facilities include fire hydrants, fire extinguishers and sprinklers; the building parameters of fire protection facilities include the number and location of fire protection facilities; The number of firefighting facilities is marked as n5, the position and coordinates of any firefighting facility point d are marked as Wd (Xw, Yw), and the number of firefighting facility points d is marked as Md; Analyze the overlap between the location Wd of the fire protection facility point d and the route of the emergency evacuation channel s: When the location Wd of the fire-fighting facility point d is located on the total path of the emergency evacuation passage, the location Wd of the fire-fighting facility point d is determined to be valid, and the valid value Dyou of the fire-fighting facility point d is set and marked as 1, and the minimum distance Dmin between the fire-fighting facility point d and the emergency evacuation passage is marked as 0; When the location Wd of the fire-fighting facility point d is not located on the total path of the emergency evacuation passage, the minimum distance Dmin between the fire-fighting facility point d and the emergency evacuation passage is calculated, and the effective value Dyou of the fire-fighting facility point d is marked as 0; The effective value Dyou and the nearest distance Dmin are integrated and marked as the reference number set of the fire facility point d, and the effectiveness evaluation coefficient X3 of the fire facility point is obtained through the reference number set of the fire facility point d.

6. The method for optimizing building master plan design based on building fire protection requirements according to claim 5, characterized in that: The specific process of collecting and analyzing fire prevention and control data is as follows: Fire prevention and control simulation experiments are conducted using computer fire simulation technology to collect fire prevention and control data for the initial building plane model. Fire prevention and control data includes the diffusion paths of toxic gases and smoke particles, as well as heat transfer paths. Fire prevention and control data is imaged using RGB imaging technology to generate corresponding path regionalization images. The diffusion path of toxic gases is generated as image number one, the diffusion path of smoke particles is generated as image number two, and the heat transfer path is generated as image number three. The number of display areas of any display image of the initial model of the building plane is marked as m0, any display area of the display image is marked as z, the area of the display area z is marked as Sz, and the RGB parameter vector of the display area z is marked as , where Rz is the red component value, Gz is the green component value, and Bz is the blue component value; The fire risk assessment index Z0 is obtained comprehensively by combining the RGB parameter vectors of the m0 display areas z corresponding to all the display images.

7. The method for optimizing building master plan design based on building fire protection requirements according to claim 6, characterized in that: The specific process of comprehensively evaluating the fire performance of the initial building plane model is as follows: Fire prevention facilities are activated through fire prevention and control simulation experiments to control fire risks. The effectiveness evaluation coefficients of fire isolation zones, emergency passages, and firefighting facilities that are in operation are calculated and obtained, and marked as the effective operation coefficient Xr1 of fire isolation zones, the effective operation coefficient Xr2 of emergency passages, and the effective operation coefficient Xr3 of firefighting facilities. The data calculation period Ts is set to perform regular calculations on the fire risk assessment index Z0, thereby obtaining the fire performance impact function F0 by combining the effective operation coefficient Xr1 of the fire isolation zone, the effective operation coefficient Xr2 of the emergency passage, and the effective operation coefficient Xr3 of the fire protection facility with the fire risk assessment index Z0; The evaluation interval of the fire performance impact function F0 is set, and the fire performance of the initial building plane model is evaluated through interval comparison to generate the corresponding optimization management signal.

8. The method for optimizing building master plan design based on building fire protection requirements according to claim 7, characterized in that: The specific process of generating the building model optimization solution is as follows: When receiving the optimization management signal, the effective operation coefficient Xr1 of the fire isolation zone, the effective operation coefficient Xr2 of the emergency passage, and the effective operation coefficient Xr3 of the fire protection facility point are deeply analyzed; The control thresholds of fire isolation zones, emergency passages and firefighting facilities are set separately. By comparing the effective operation coefficients of fire isolation zones, emergency passages and firefighting facilities with their corresponding control thresholds, it is determined whether the fire protection facilities should be optimized, and the corresponding optimization plan is obtained in combination with the optimization management signal level. The optimization plans for fire isolation zones, emergency passages, and fire-fighting facilities are integrated and marked as building model optimization plans.

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