Method for constructing fire critical wind speed prediction model of ship navigation tunnel and system thereof

Abstract

The application discloses a method for constructing a prediction model of a critical wind speed of a ship navigation tunnel fire, which comprises the following steps: drawing a basic structure drawing of a ship tunnel by using drawing software, obtaining a structure model of the ship tunnel by adjusting size parameters of the basic structure drawing of the ship tunnel, confirming a maximum tonnage of a ship that can navigate in the tunnel and constructing a fire source ship model based on the structure model of the ship tunnel; confirming a range of fire source characteristics of the ship according to the maximum tonnage of the ship that can navigate in the tunnel, selecting different fire source working condition parameters according to the range of the fire source characteristics, importing the structure model of the ship tunnel and the fire source ship model into a fire simulation software, respectively performing fire simulation based on the different fire source working condition parameters to obtain a critical wind speed simulation data set, performing correlation analysis on the critical wind speed simulation data set and size parameters of the ship tunnel, screening out factors with a correlation coefficient greater than a set threshold value, and performing formula fitting on the critical wind speed simulation data set and the factors to obtain a critical wind speed prediction model. The prediction accuracy is effectively improved.

Description

Technical Field

[0001] This invention relates to a method and system for constructing a critical wind speed prediction model for fires in ship navigation tunnels, specifically applicable to the study of critical wind speed patterns in ship tunnels. Background Technology

[0002] Tunnel fires, due to their enclosed space, make it difficult for smoke and heat to disperse, easily causing severe casualties and property damage. Critical wind speed is a key parameter for ventilation control in tunnel fires, referring to the minimum longitudinal ventilation speed required to effectively prevent backflow of smoke. Currently, research on critical wind speeds in tunnel fires (i.e., the minimum ventilation speed required to prevent backflow or control smoke spread) mainly focuses on highway and railway tunnels. These two types of tunnels already have relatively mature fire wind speed models and ventilation system design specifications. However, due to the different dynamic characteristics and operating patterns of transportation vehicles, these research results cannot be directly applied to ship-navigated tunnels for the following fundamental differences:

[0003] 1. Significant differences in tunnel dimensions: Highway and railway tunnels have smaller cross-sections, typically arranged as single or double spans, and vehicles travel at high speeds, leading to rapid fire development and high smoke velocity. Ship navigation tunnels, designed to meet the needs of ship passage, have much larger cross-sections, usually long, non-circular irregular cross-sections, with more complex spatial ventilation characteristics and longer smoke diffusion paths.

[0004] 2. Tunnel Length and Structural Layout: Highway and railway tunnels are mostly several hundred meters to several kilometers long, and are mainly laid out linearly. Ship tunnels are much longer (often exceeding 1 kilometer) due to the need to avoid mountains and connect to waterways, which increases the difficulty of ventilation and fire control.

[0005] 3. Differences in altitude and slope: Railway and highway tunnels are usually located at low to medium altitudes on the ground or in mountainous areas, and are designed with limited longitudinal slopes to ensure traffic safety. Ship tunnels, on the other hand, need to connect to different water level sections, are often located close to the water surface, and have hydraulic connection sections. These topographical and fluid conditions will significantly affect the direction of flue gas flow and wind speed requirements.

[0006] 4. Differences in ventilation modes: Highway and railway tunnels mostly use forced longitudinal ventilation, transverse ventilation, or mixed ventilation systems, supplemented by mist fire suppression systems. Ship tunnels mostly rely on natural ventilation or limited mechanical ventilation. In the event of a fire, the ventilation power is weak, and smoke is prone to stagnation and backflow. They lack the ability to be forcibly controlled, and therefore rely more on accurate prediction of critical wind speed to assist in the formulation of effective ventilation control strategies.

[0007] 5. Different fire characteristics: Road and rail vehicles are self-propelled or electrically traction-driven, resulting in relatively concentrated fire sources and more consistent heat release rates. Ships are fuel-powered, have large structures, dispersed fire sources, and some ships pose a risk of transporting dangerous goods, making fire development more complex and the intensity and diffusion patterns of smoke release more uncertain.

[0008] 6. Impact of Water Bodies: Ship navigation tunnels are typically located near or underwater, and the water significantly affects the heat exchange between the temperature and airflow fields within the tunnels. Existing models do not adequately consider this factor. Therefore, there is an urgent need for a critical wind speed prediction method specifically for the fire characteristics of ship navigation tunnels to improve the targeting and effectiveness of fire prevention and control.

[0009] Existing technologies primarily focus on predicting critical fire wind speeds in highway and railway tunnels. Commonly used models include empirical formulas based on Froude number and heat release rate (such as the Thomas model and the Wu model) as well as CFD numerical simulation methods. These methods have been widely validated in highway and railway tunnels, but their direct application to tunnels navigable by ships may still have certain limitations. Summary of the Invention

[0010] The purpose of this invention is to overcome the problem of low accuracy in predicting critical wind speeds for ship navigation tunnels in the prior art, and to provide a method and system for constructing a critical wind speed prediction model for ship navigation tunnel fires that improves the accuracy of critical wind speed prediction.

[0011] To achieve the above objectives, the technical solution of the present invention is:

[0012] In a first aspect, the present invention provides a method for constructing a critical wind speed prediction model for fires in ship navigation tunnels, the method comprising the following steps:

[0013] Step 1: Use drafting software to create a basic structural drawing of the ship tunnel. By adjusting the dimensional parameters of the basic structural drawing of the ship tunnel, obtain the structural model of the ship tunnel. Based on the structural model of the ship tunnel, confirm the maximum tonnage ship that can navigate through the tunnel and construct a fire source ship model.

[0014] Step 2: Based on the maximum navigable tonnage of the ship, confirm the range of fire source characteristics on board. Select different fire source operating parameters according to the range of fire source characteristics. Import the structural model of the ship tunnel and the fire source ship model into the fire simulation software. Perform fire simulation based on different fire source operating parameters to obtain the critical wind speed simulation dataset.

[0015] Step 3: Perform correlation analysis between the critical wind speed simulation dataset and the size parameters of the ship tunnel, select factors with correlation coefficients greater than a set threshold, and fit them with the critical wind speed simulation dataset to obtain the critical wind speed prediction model.

[0016] In step one, a basic structural drawing of the ship tunnel is created using drafting software. Based on the basic structure of the ship tunnel, including the waterway at the bottom, pedestrian escape routes on both sides, and the arch at the top, a basic structural drawing of the ship tunnel is constructed, and a tunnel parameter adjustment model S for the basic structural drawing is constructed.

[0017] S={L,H t ,H,H w H r H g ,D,D r};

[0018] Where L is the tunnel length, H t H is the total height of the tunnel, and H is the navigable clearance of the tunnel. w To design the water depth, H r H is the height of the tunnel walkway. g D is the tunnel arch height, and D is the tunnel navigation clearance width. r This refers to the width of the pedestrian walkway on one side of the tunnel.

[0019] In the middle of the basic structural drawing of the ship tunnel, a fire source ship is set up, and a ship parameter adjustment model C is constructed:

[0020] C={ C t C L C W C H C D};

[0021] Among them, C t For ship tonnage, C L C represents the length of the ship. W For the ship's width, C H For the ship's height, C D This refers to the maximum draft of the vessel.

[0022] Based on the actual parameters of the tunnel, the tunnel parameter adjustment model S of the basic structure drawing is adjusted to obtain the structural model of the ship tunnel. Based on the structural model of the ship tunnel, the maximum tonnage ship that can navigate in the tunnel is identified. Based on the maximum tonnage ship that can navigate, the ship parameter adjustment model C is adjusted to obtain the fire source ship model.

[0023] In step two, the range of fire source characteristics on board is determined based on the maximum navigable tonnage of the vessel. The range of fire source characteristics for vessels of different tonnages is as follows:

[0024] C t ≤500 tons: heat release rate of the heat source is 2MW~50MW;

[0025] 500 tons < C t≤1000 tons: heat release rate of the heat source is 5 MW~120MW;

[0026] 1000 tons < C t ≤5000 tons: heat release rate of the heat source is 10 MW~200MW;

[0027] 5000 tons < C t ≤8000 tons: heat release rate of the heat source is 20 MW~260MW;

[0028] 8000 tons < C t ≤10,000 tons: heat release rate of the heat source is 50 MW to 300 MW.

[0029] Different fire source operating parameters are selected based on the range of fire source characteristics, corresponding to different fire source release rates Q: 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, unit: MW;

[0030] Based on different fire source parameters, the mesh size and fire source diameter of the simulation model under different conditions are determined by referring to the table below:

[0031] ;

[0032] The grid size and fire source diameter corresponding to different fire source operating conditions are input into the fire simulation software to simulate the fire conditions and obtain the critical wind speed simulation dataset.

[0033] In step three, the critical wind speed simulation dataset is correlated with the size parameters of the ship tunnel. The critical wind speed simulation datasets of multiple ship tunnels of different sizes are selected and their corresponding size parameters are correlated. At the same time, the heat release rate of the fire source in the critical wind speed simulation dataset and its corresponding critical wind speed are correlated to obtain the correlation coefficient between each set of data.

[0034] The dimensional parameters of the ship tunnel include: tunnel clearance height H, and tunnel total height H. t Design water depth H w 1. Tunnel navigation clearance width D; 2. Tunnel net cross-sectional perimeter L ZC The net cross-sectional area of ​​the tunnel is L S The space above the water surface within the cross-section of a tunnel is called the net cross-section.

[0035] Factors with correlation coefficients greater than a set threshold were selected and fitted with a formula to the critical wind speed simulation dataset: First, the parameters of different fire source conditions and their corresponding critical wind speed parameters were processed to be dimensionless, resulting in a dataset of dimensionless fire source heat release rate Q* and the corresponding dimensionless critical wind speed V. C * The data set was used, and factors with correlation coefficients greater than a set threshold were selected as relevant parameters. Simulation data showed that as the dimensionless heat release rate Q* increased, the dimensionless critical wind speed V... C * Increase it until it reaches the target. After remaining constant, the dimensionless heat release rate of the ignition source at its critical wind speed segment point is: ;

[0036] Using the two Q* and V mentioned above C * The dataset and relevant parameters are fitted together to obtain the critical wind speed prediction model;

[0037] ;

[0038] Among them, V C * L is the dimensionless critical wind speed; Q* is the dimensionless heat release rate of the ignition source; L ZC The net cross-sectional perimeter of the tunnel is defined as the space above the water surface within the tunnel's cross-section; H is the tunnel's navigation clearance; L ZC / 4H is the section coefficient; H t H is the total height of the tunnel. w To design the water depth, H w / H t The water body correction term is represented by α, which is the fitting coefficient. The maximum dimensionless critical wind speed; The dimensionless heat release rate of the fire source is the critical wind speed segment point.

[0039] The prediction model construction method further includes step four: Based on steps one and two, the dimensional parameters and critical wind speed simulation dataset of the ship tunnel S1 are obtained. These parameters and dataset are then input into the critical wind speed prediction model. First, the dimensionless heat release rate of the fire source at the segment points of the ship tunnel S1 is obtained. The maximum dimensionless critical wind speed of the ship tunnel S1 Then, the fitting coefficient α of the ship tunnel S1 is obtained to get the critical wind speed prediction model of the ship tunnel S1.

[0040] Secondly, the present invention provides a system for constructing a critical wind speed prediction model for fires in ship navigation tunnels, specifically including: a structural model construction module, a critical wind speed simulation module, and a data fitting module;

[0041] Structural Model Building Module: Used to create basic structural drawings of ship tunnels using drafting software. By adjusting the dimensional parameters of the basic structural drawings of ship tunnels, a structural model of the ship tunnel is obtained. Based on the structural model of the ship tunnel, the maximum tonnage of ships that can navigate through the tunnel is confirmed, and a fire source ship model is constructed.

[0042] Using drafting software, a basic structural drawing of a ship tunnel is created. Based on the basic structure of a ship tunnel, including the waterway at the bottom, pedestrian escape routes on both sides, and the arch at the top, a basic structural drawing of the ship tunnel is constructed, and a tunnel parameter adjustment model S is built for the basic structural drawing.

[0043] S={L,H t ,H,H w H r H g ,D,D r};

[0044] Where L is the tunnel length, H t H is the total height of the tunnel, and H is the navigable clearance of the tunnel. w To design the water depth, H r H is the height of the tunnel walkway. g D is the tunnel arch height, and D is the tunnel navigation clearance width. r This refers to the width of the pedestrian walkway on one side of the tunnel.

[0045] In the middle of the basic structural drawing of the ship tunnel, a fire source ship is set up, and a ship parameter adjustment model C is constructed:

[0046] C={ C t C L C W C H C D};

[0047] Among them, C t For ship tonnage, C L C represents the length of the ship. W For the ship's width, C H For the ship's height, C D This refers to the maximum draft of the vessel.

[0048] Based on the actual parameters of the tunnel, the tunnel parameter adjustment model S of the basic structure drawing is adjusted to obtain the structural model of the ship tunnel. Based on the structural model of the ship tunnel, the maximum tonnage ship that can navigate in the tunnel is identified. Based on the maximum tonnage ship that can navigate, the ship parameter adjustment model C is adjusted to obtain the fire source ship model.

[0049] Critical wind speed simulation module: used to determine the range of fire source characteristics on board based on the maximum navigable tonnage of the ship, select different fire source operating parameters according to the range of fire source characteristics, import the structural model of the ship tunnel and the fire source ship model into the fire simulation software, and perform fire simulation based on different fire source operating parameters to obtain the critical wind speed simulation dataset.

[0050] The range of fire source characteristics on board a vessel is determined based on its maximum navigable tonnage. The ranges of fire source characteristics for vessels of different tonnages are as follows:

[0051] C t ≤500 tons: heat release rate of the heat source is 2MW~50MW;

[0052] 500 tons < C t ≤1000 tons: heat release rate of the heat source is 5 MW~120MW;

[0053] 1000 tons < C t ≤5000 tons: heat release rate of the heat source is 10 MW~200MW;

[0054] 5000 tons < C t ≤8000 tons: heat release rate of the heat source is 20 MW~260MW;

[0055] 8000 tons < C t ≤10,000 tons: heat release rate of the heat source is 50 MW to 300 MW.

[0056] Different fire source operating parameters are selected based on the range of fire source characteristics, corresponding to different fire source release rates Q: 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, unit: MW;

[0057] Based on different fire source parameters, the mesh size and fire source diameter of the simulation model under different conditions are determined by referring to the table below:

[0058] ;

[0059] The grid size and fire source diameter corresponding to different fire source operating conditions are input into the fire simulation software to simulate the fire conditions and obtain the critical wind speed simulation dataset.

[0060] Data Fitting Module: This module performs correlation analysis between the critical wind speed simulation dataset and the dimensional parameters of the ship tunnel, filters out factors with correlation coefficients greater than a set threshold, and fits them with the critical wind speed simulation dataset to obtain a critical wind speed prediction model.

[0061] Correlation analysis was performed between the critical wind speed simulation dataset and the size parameters of the ship tunnel. Correlation analysis was performed on the critical wind speed simulation datasets of multiple ship tunnels of different sizes and their corresponding size parameters. At the same time, correlation analysis was performed on the heat release rate of the fire source and its corresponding critical wind speed in the critical wind speed simulation dataset to obtain the correlation coefficient between each set of data.

[0062] The dimensional parameters of the ship tunnel include: tunnel clearance height H, and tunnel total height H. t Design water depth H w 1. Tunnel navigation clearance width D; 2. Tunnel net cross-sectional perimeter L ZC The net cross-sectional area of ​​the tunnel is L S The space above the water surface within the cross-section of a tunnel is called the net cross-section.

[0063] Factors with correlation coefficients greater than a set threshold were selected and fitted with a formula to the critical wind speed simulation dataset: First, the parameters of different fire source conditions and their corresponding critical wind speed parameters were processed to be dimensionless, resulting in a dataset of dimensionless fire source heat release rate Q* and the corresponding dimensionless critical wind speed V. C * The data set was used, and factors with correlation coefficients greater than a set threshold were selected as relevant parameters. Simulation data showed that as the dimensionless heat release rate Q* increased, the dimensionless critical wind speed V... C * Increase it until it reaches the target. After remaining constant, the dimensionless heat release rate of the ignition source at its critical wind speed segment point is: ;

[0064] Using the two Q* and V mentioned above C * The dataset and relevant parameters are fitted together to obtain the critical wind speed prediction model;

[0065] ;

[0066] Among them, V C * L is the dimensionless critical wind speed; Q* is the dimensionless heat release rate of the ignition source; L ZC The net cross-sectional perimeter of the tunnel is defined as the space above the water surface within the tunnel's cross-section; H is the tunnel's navigation clearance; L ZC / 4H is the section coefficient; Ht H is the total height of the tunnel. w To design the water depth, H w / H t The water body correction term is represented by α, which is the fitting coefficient. The maximum dimensionless critical wind speed; The dimensionless heat release rate of the fire source is the critical wind speed segment point.

[0067] The prediction model construction method further includes step four, which uses a structural model construction module and a critical wind speed simulation module to obtain the dimensional parameters of the ship tunnel S1 and the critical wind speed simulation dataset of the ship tunnel S1. The dimensional parameters and critical wind speed simulation dataset of the ship tunnel S1 are then input into the critical wind speed prediction model. First, the dimensionless heat release rate of the fire source at the segment points of the ship tunnel S1 is obtained. The maximum dimensionless critical wind speed of the ship tunnel S1 Then, the fitting coefficient α of the ship tunnel S1 is obtained to get the critical wind speed prediction model of the ship tunnel S1.

[0068] Thirdly, the present invention provides a device for constructing a critical wind speed prediction model for fires in ship navigation tunnels, including a memory and a processor. The memory is used to store computer program code and transmit the computer program code to the processor.

[0069] The processor is used to execute the aforementioned method for constructing a critical wind speed prediction model for ship navigation tunnel fires according to instructions in the computer program code.

[0070] Fourthly, the present invention provides a computer program product, including a computer program that is executed by a processor to construct the aforementioned method for predicting critical wind speeds for fires in ship navigation tunnels.

[0071] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0072] 1. The present invention provides a method for constructing a critical wind speed prediction model for fires in ship navigation tunnels. By constructing a basic structural drawing of the ship tunnel with adjustable parameters, the size parameters of the ship tunnel and the size parameters of the fire source ship in the middle of the tunnel can be adjusted, which effectively simplifies the modeling process and enables the rapid acquisition of the structural model of the ship tunnel and the fire source ship model.

[0073] 2. The present invention provides a method for constructing a critical wind speed prediction model for fires in ship-navigable tunnels. Based on the maximum tonnage of the ship that can navigate, the method determines the range of fire source characteristics on board, sets different fire conditions within the range of fire source characteristics, then looks up the simulation parameters for each condition in a table, and directly calculates the critical wind speed based on the simulation parameters.

[0074] 3. In the method for constructing a critical wind speed prediction model for fires in ship navigation tunnels, the characteristics of ship navigation tunnels are considered. Correlation analysis of the data is performed to identify factors with high correlation to critical wind speed, and formula fitting is performed to optimize the calculation formula for critical wind speed.

[0075] 4. The present invention provides a method for constructing a critical wind speed prediction model for fires in ship navigation tunnels. Based on different tunnels, fire simulations are performed through steps one and two. Then, a critical wind speed prediction model for an individual tunnel is obtained based on the fire simulation data. This method has high specificity and high prediction accuracy.

[0076] 5. The present invention provides a system for constructing a critical wind speed prediction model for fires in ship navigation tunnels, comprising: a structural model construction module, a critical wind speed simulation module, and a data fitting module. This system is used to implement the steps of the method for constructing a critical wind speed prediction model for fires in ship navigation tunnels provided in any of the above technical solutions. Therefore, this system simultaneously includes all the beneficial effects of the method for constructing a critical wind speed prediction model for fires in ship navigation tunnels provided in any of the above technical solutions, which will not be elaborated further here.

[0077] 6. The device for constructing a critical wind speed prediction model for ship navigation tunnel fires according to the present invention includes a processor and a memory. The memory is used to store computer program code and transmit the computer program code to the processor. The processor is used to execute the method for constructing a critical wind speed prediction model for ship navigation tunnel fires provided in any of the above-mentioned technical solutions according to the instructions in the computer program code. Therefore, this device simultaneously includes all the beneficial effects of the method for constructing a critical wind speed prediction model for ship navigation tunnel fires provided in any of the above-mentioned technical solutions, which will not be elaborated further here.

[0078] 7. The present invention provides a computer program product, which, when executed by a processor, implements the steps of the method for constructing a critical wind speed prediction model for ship navigation tunnel fires as provided in any of the above-described technical solutions. Therefore, this computer program product simultaneously includes all the beneficial effects of the method for constructing a critical wind speed prediction model for ship navigation tunnel fires as provided in any of the above-described technical solutions, which will not be elaborated further here. Attached Figure Description

[0079] Figure 1 This is a flowchart of the method of the present invention.

[0080] Figure 2 This is a schematic diagram of the basic structure of the ship tunnel in Example 1.

[0081] Figure 3 This is a schematic diagram of the dimensions of the tunnel parameter adjustment model S, which is the basic structural drawing of Example 1.

[0082] Figure 4This is a schematic diagram of the fire source ship model of Example 1.

[0083] Figure 5 These are schematic cross-sectional views of three typical ship tunnels in Example 2.

[0084] Figure 6 This is a screenshot of part of the simulation results from the FDS fire simulation software in Example 2.

[0085] Figure 7 This is a graph showing the dimensionless parameter fitting analysis of Example 2.

[0086] Figure 8 This is a structural diagram of the system of the present invention.

[0087] Figure 9 This is a schematic diagram of the structure of the device of the present invention. Detailed Implementation

[0088] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0089] Example 1:

[0090] See Figures 1 to 4 A method for constructing a critical wind speed prediction model for fires in ship navigation tunnels, the method comprising the following steps:

[0091] Step 1: Use drafting software to create a basic structural drawing of the ship tunnel. By adjusting the dimensional parameters of the basic structural drawing of the ship tunnel, obtain the structural model of the ship tunnel. Based on the structural model of the ship tunnel, confirm the maximum tonnage ship that can navigate through the tunnel and construct a fire source ship model.

[0092] Step 2: Based on the maximum navigable tonnage of the ship, confirm the range of fire source characteristics on board. Select different fire source operating parameters according to the range of fire source characteristics. Import the structural model of the ship tunnel and the fire source ship model into the fire simulation software. Perform fire simulation based on different fire source operating parameters to obtain the critical wind speed simulation dataset.

[0093] Step 3: Perform correlation analysis between the critical wind speed simulation dataset and the size parameters of the ship tunnel, select factors with correlation coefficients greater than a set threshold, and fit them with the critical wind speed simulation dataset to obtain the critical wind speed prediction model.

[0094] In step one, drafting software is used to create a basic structural drawing of the ship tunnel. (See [link]). Figure 2 Based on the basic structure of a ship tunnel, including the waterway at the bottom, pedestrian escape routes on both sides, and the arched roof at the top, construct the basic structural drawing of the ship tunnel. See [reference needed]. Figure 3 Construct a tunnel parameter adjustment model S for basic structural mapping:

[0095] S={L,H t ,H,H w H r H g ,D,D r};

[0096] Where L is the tunnel length, H t H is the total height of the tunnel, and H is the navigable clearance of the tunnel. w To design the water depth, H r H is the height of the tunnel walkway. g D is the tunnel arch height, and D is the tunnel navigation clearance width. r This refers to the width of the pedestrian walkway on one side of the tunnel.

[0097] In the middle of the basic structural drawing of the ship tunnel, a fire source ship is set up, and a ship parameter adjustment model C is constructed:

[0098] C={ C t C L C W C H C D};

[0099] Among them, C t For ship tonnage, C L C represents the length of the ship. W For the ship's width, C H For the ship's height, C D This refers to the maximum draft of the vessel.

[0100] Based on the actual tunnel parameters, the tunnel parameter adjustment model S, derived from the foundation structure drawing, is used to obtain the structural model of the ship tunnel. (See [reference]). Figure 4 Based on the structural model of the ship tunnel, the maximum tonnage ship that can navigate inside the tunnel is identified. Based on the maximum tonnage ship that can navigate, the ship parameters of model C are adjusted to obtain the fire source ship model.

[0101] Since the water level in ship tunnels remains constant, the internal characteristics of the tunnels are basically the same, and the elevation remains constant, allowing for the creation of a unified model. This enables the rapid construction of structural models of ship tunnels, effectively improving simulation efficiency.

[0102] In step two, the range of fire source characteristics on board is determined based on the maximum navigable tonnage of the vessel. The range of fire source characteristics for vessels of different tonnages is as follows:

[0103] C t ≤500 tons: heat release rate of the heat source is 2MW~50MW;

[0104] 500 tons < C t≤1000 tons: heat release rate of the heat source is 5 MW~120MW;

[0105] 1000 tons < C t ≤5000 tons: heat release rate of the heat source is 10 MW~200MW;

[0106] 5000 tons < C t ≤8000 tons: heat release rate of the heat source is 20 MW~260MW;

[0107] 8000 tons < C t ≤10,000 tons: heat release rate of the heat source is 50 MW to 300 MW.

[0108] Different fire source operating parameters are selected based on the range of fire source characteristics, corresponding to different fire source release rates Q: 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, unit: MW;

[0109] Based on different fire source parameters, the mesh size and fire source diameter of the simulation model under different conditions are determined by referring to the table below:

[0110] ;

[0111] The grid size and fire source diameter corresponding to different fire source operating conditions are input into the fire simulation software to simulate the fire conditions and obtain the critical wind speed simulation dataset.

[0112] The dimensions of tunnels are far larger than those of highway tunnels, and the fire hazard of ships is much greater than that of cars, resulting in different magnitudes of parameters in the simulation. The large distances between ships prevent cascading fires, thus the design of the simulation model is more consistent with real-world fire scenarios.

[0113] In step three, the critical wind speed simulation dataset is correlated with the size parameters of the ship tunnel. The critical wind speed simulation datasets of multiple ship tunnels of different sizes are selected and their corresponding size parameters are correlated. At the same time, the heat release rate of the fire source in the critical wind speed simulation dataset and its corresponding critical wind speed are correlated to obtain the correlation coefficient between each set of data.

[0114] The dimensional parameters of the ship tunnel include: tunnel clearance height H, and tunnel total height H. t Design water depth H w 1. Tunnel navigation clearance width D; 2. Tunnel net cross-sectional perimeter L ZC The net cross-sectional area of ​​the tunnel is L S The space above the water surface within the cross-section of a tunnel is called the net cross-section.

[0115] Factors with correlation coefficients greater than a set threshold were selected and fitted with a formula to the critical wind speed simulation dataset: First, the parameters of different fire source conditions and their corresponding critical wind speed parameters were processed to be dimensionless, resulting in a dataset of dimensionless fire source heat release rate Q* and the corresponding dimensionless critical wind speed V. C * The data set was used, and factors with correlation coefficients greater than a set threshold were selected as relevant parameters. Simulation data showed that as the dimensionless heat release rate Q* increased, the dimensionless critical wind speed V... C * Increase it until it reaches the target. After remaining constant, the dimensionless heat release rate of the ignition source at its critical wind speed segment point is: ;

[0116] Using the two Q* and V mentioned above C * The dataset and relevant parameters are fitted together to obtain the critical wind speed prediction model;

[0117] ;

[0118] Among them, V C * L is the dimensionless critical wind speed; Q* is the dimensionless heat release rate of the ignition source; L ZC The net cross-sectional perimeter of the tunnel is defined as the space above the water surface within the tunnel's cross-section; H is the tunnel's navigation clearance; L ZC / 4H is the section coefficient; H t H is the total height of the tunnel. w To design the water depth, H w / H t The water body correction term is represented by α, which is the fitting coefficient. The maximum dimensionless critical wind speed; The dimensionless heat release rate of the fire source is the critical wind speed segment point.

[0119] a. Introducing a water body impact term improves prediction accuracy. Existing highway and railway tunnel models do not consider the thermophysical and aerodynamic disturbances caused by water as the underlying surface, while this formula incorporates a water body impact term. It explicitly considers the amplification or disturbance effect of the presence of water on the buoyancy of the thermal plume, and corrects the thermo-aerodynamic coupling relationship in the flue gas development path, making it more suitable for actual fire scenarios in ship tunnels.

[0120] b. Maintaining a common heat release control method facilitates compatibility with existing models. The first two items continue the common LI fire critical wind speed modeling method, which makes this model still have good comparability and engineering promotion, and facilitates docking with existing systems.

[0121] c. Structural parameter ratio processing improves adaptability and scale compatibility. This formula uses H... w / H t The ratio form used as a correction variable differs from the absolute values ​​of parameters such as tunnel height and width in traditional models. Ratio processing offers better scale independence and, combined with the characteristics of ship tunnels, is more applicable to ship tunnel projects with different cross-sectional dimensions, making it more versatile.

[0122] The prediction model construction method further includes step four: Based on steps one and two, the dimensional parameters and critical wind speed simulation dataset of the ship tunnel S1 are obtained. These parameters and dataset are then input into the critical wind speed prediction model. First, the dimensionless heat release rate of the fire source at the segment points of the ship tunnel S1 is obtained. The maximum dimensionless critical wind speed of the ship tunnel S1 Then, the fitting coefficient α of the ship tunnel S1 is obtained to get the critical wind speed prediction model of the ship tunnel S1.

[0123] Example 2:

[0124] See Figures 5 to 7 Step 1: Use drafting software to create the basic structural drawing of the ship tunnel. Based on the basic structure of the ship tunnel, including the waterway at the bottom, pedestrian escape passages on both sides, and the arch at the top, construct the basic structural drawing of the ship tunnel and build the tunnel parameter adjustment model S for the basic structural drawing.

[0125] S={L,H t ,H,H w H r H g ,D,D r};

[0126] In the middle of the basic structural drawing of Ship Tunnel I, a fire source ship is set up, and a ship parameter adjustment model C is constructed:

[0127] C={ C t C L C W C H C D};

[0128] Among them, C t For ship tonnage, C L C represents the length of the ship. W For the ship's width, C H For the ship's height, C D This refers to the maximum draft of the vessel.

[0129] SeeFigure 5 Three typical ship tunnels were selected to construct structural models of the ship tunnels:

[0130] Ship Tunnel I (such as the Silin Navigation Tunnel on the Second Line of the Wujiang River): Tunnel length L is 2200m, and total tunnel height H t The tunnel has a navigable clearance height H of 20m and a design water depth H. w The tunnel walkway height H is 5.5 m. r The height is 7.7m, and the tunnel arch height is H. g The tunnel width is 4.7m, the navigable clearance width D is 16m, and the width of the pedestrian walkway on one side of the tunnel is D. r The length is 1.5m; the net cross-sectional perimeter L of the tunnel is obtained from the structural model. ZC The length is 56.91m and the net cross-sectional area of ​​the tunnel is L. S It is 238.03m 2 The space above the water surface within the cross-section of a tunnel is called the net cross-section.

[0131] Fire source parameters for Ship Tunnel I: Ship tonnage C t It is a 1000-ton class vessel with a length of C. L The length is 57m, and the ship's width is C. W The height is 10.8m, and the ship's height is C. H The maximum draft of the ship is 10.5m. D It is 2.5m.

[0132] Ship Tunnel II: Tunnel length L is 15.3m, and total tunnel height H t The tunnel has a navigable clearance height H of 31m and a design water depth H of 22.5m. w The tunnel walkway height is 8.5 m. r The tunnel arch is 9.5m high, and the tunnel arch height is H. g The tunnel width is 13.5m, the navigable clearance width D is 26m, and the width of the pedestrian walkway on one side of the tunnel is D. r The length is 2m; the net cross-sectional perimeter L of the tunnel is obtained from the structural model. ZC The length is 94.10m and the net cross-sectional area of ​​the tunnel is L. S It is 604.25m 2 .

[0133] Fire source parameters for Ship Tunnel II: Ship tonnage C t It is an 8000-ton class vessel with a length of C. L The length is 130m, and the ship's width is C. W The height is 16.3m, and the ship's height is C. H The maximum draft of the ship is 15m, C. D It is 5.5m.

[0134] Ship Tunnel III (such as the Three Gorges New Channel Tunnel): Tunnel length L is 1000m, and total tunnel height H t The tunnel's navigable clearance height H is 65.3m, and the design water depth H is 25.3m. w The tunnel walkway height is 41 m. r The tunnel arch is 45.5m high, and the tunnel arch height is H. g The tunnel width is 11.6m, the navigable clearance width D is 25m, and the width of the pedestrian walkway on one side of the tunnel is D. r The length is 4.5m; the net cross-sectional perimeter L of the tunnel is obtained from the structural model. ZC The length is 103.33m and the net cross-sectional area of ​​the tunnel is L. S It is 510.01m 2 .

[0135] Fire source parameters for Ship Tunnel III: Ship tonnage C t It is a 10,000-ton class vessel with a length of C. L The length is 130m, and the ship's width is C. W The height is 22m, and the ship's height is C. H The maximum draft of the vessel is 16.3m, and the maximum draft C is... D It is 5.5m.

[0136] Step 2: Based on the maximum navigable tonnage of the ship, confirm the range of fire source characteristics on board. Select different fire source operating parameters according to the range of fire source characteristics. Import the structural model of the ship tunnel and the fire source ship model into the fire simulation software. Perform fire simulation based on different fire source operating parameters to obtain the critical wind speed simulation dataset.

[0137] The structural models of three typical ship tunnels correspond to the range of shipboard fire source characteristics and the selection of simulation conditions:

[0138] Ignition characteristics of Ship Tunnel I:

[0139] The vessel type is a 1000-ton small cargo ship or barge. A typical fire scenario is an engine room fire, with the heat source primarily coming from marine diesel fuel, lubricating oil, and related electrical equipment. Due to the limited fuel reserves of this type of vessel (usually no more than 20 tons) and the relatively enclosed engine room space, the scale of the fire is limited by the cabin volume, equipment density, and ventilation conditions. Therefore, the heat release rate is generally in the low to medium intensity range.

[0140] Estimated HRR range: 5 MW to 120MW;

[0141] Experimental setup: Twelve typical HRR conditions of 5 MW, 10 MW, 20 MW, 30 MW, 40 MW, 50 MW, 60 MW, 70 MW, 80 MW, 90 MW, 100 MW, and 120 MW were selected to simulate the development process and thermal smoke diffusion characteristics of light to moderate intensity cabin fires.

[0142] Ignition characteristics of Ship Tunnel II:

[0143] This level of tunnel design serves medium to large vessels of 8,000 tons, commonly found on bulk carriers, product tankers, or chemical tankers. These vessels have significantly increased fuel reserves, reaching several thousand tons, and the cargo contents are highly flammable. In the event of a fire, it often involves the cargo hold area or oil tanks, characterized by a large ignition source, rapid development, high heat intensity, and even the risk of explosion.

[0144] Estimated HRR range: approximately 20–260 MW;

[0145] Experimental setup: Seventeen heat release rate conditions were set up, namely 20 MW, 30 MW, 40 MW, 50 MW, 60 MW, 70 MW, 80 MW, 90 MW, 100 MW, 120 MW, 140 MW, 160 MW, 180 MW, 200 MW, 220 MW, 240 MW, and 260 MW, covering fire scenarios from medium to high intensity, simulating typical situations that may affect multiple compartments or trigger chain reactions.

[0146] Ignition characteristics of Ship Tunnel III:

[0147] The tunnel is designed to accommodate vessels of up to 10,000 tons, primarily including large oil tankers, liquefied natural gas (LNG) carriers, and chemical tankers—ships carrying high-risk materials. These vessels are typically equipped with multiple large oil tanks or gas cylinders, with a total fuel capacity exceeding 10,000 tons. In the event of a fire, they would experience extremely high heat release rates, prolonged combustion times, and violent explosive impacts, posing significant challenges to the tunnel's structure and ventilation system.

[0148] Estimated HRR range: approximately 50–300 MW;

[0149] Experimental setup: Sixteen fire scenarios were set up, specifically 50 MW, 60 MW, 70 MW, 80 MW, 90 MW, 100 MW, 120 MW, 140 MW, 160 MW, 180 MW, 200 MW, 220 MW, 240 MW, 260 MW, 280 MW, and 300 MW, to cover fire dynamics response and safety criticality analysis from large-scale combustion to extreme accident scenarios.

[0150] Based on different fire source operating parameters, the mesh size and fire source diameter of the simulation model under different operating conditions are determined by referring to the table. The mesh size and fire source diameter corresponding to different fire source operating parameters are then input into the fire simulation software FDS to simulate the fire conditions and obtain the critical wind speed simulation dataset.

[0151] See Figure 6 The structural model of the ship tunnel was imported into the FDS fire simulation software. The cross-sectional direction of the navigation tunnel was set as the X-axis, the longitudinal direction as the Y-axis, and the gravity direction as the Z-axis. A ship of the corresponding size was placed in the most unfavorable position for smoke diffusion in the navigation tunnel fire—the center of the tunnel. Based on the actual situation, the initial ambient temperature inside the tunnel was set to 20℃, and the initial pressure was set to 101.325kPa. The main structure of the tunnel is concrete, and the material property is set to Concrete, which basically does not participate in the combustion reaction in a fire. The surface type can be set to Inert. The tunnel entrance or exit is defined as an open surface. Some areas of the ship involved in the accident react with combustion, and the property is set to Burner. The actual fire source power is described by adjusting parameters such as the burning area and the heat release power per unit area. The simulation run time is set to 600s.

[0152] The accuracy of simulation results is mainly affected by the grid size. With a given computer performance, a smaller grid size results in a more accurate simulation, closely resembling the actual fire, but also increases the simulation time. Current research on the selection of FDS grid size demonstrates a significant relationship between the grid size and the characteristic diameter of the fire source; generally, it is taken as 1 / 16 to 1 / 4 of the equivalent diameter of the fire source. The formula for calculating the equivalent diameter D* of the fire source is:

[0153] ;

[0154] Where Q is the heat release rate of the ignition source, in kW; ρ0 is the air density, taken as 1.205 kg / m³. 3 C P The specific heat of air at constant pressure is taken as 1.005 kJ / (kg·K); T0 is the ambient temperature, taken as 293.15 K; g is the acceleration due to gravity, taken as 9.8 m / s². 2 .

[0155] Taking into account factors such as the accuracy, stability, and computational cost of numerical simulation, the final model mesh sizes for different fire heat release rates are shown in the table below:

[0156] ;

[0157] Step 3: Perform a correlation analysis between the critical wind speed simulation datasets of three typical ship tunnels and the dimensional parameters of the ship tunnels.

[0158] Using Spearman correlation analysis, the critical wind speed and heat release rate (HRR) of the navigable tunnel, as well as other tunnel characteristic parameters (tunnel navigable clearance H, tunnel total height H), are analyzed. t Design water depth H w 1. Tunnel navigation clearance width D; 2. Tunnel net cross-sectional perimeter L ZC The net cross-sectional area of ​​the tunnel is L S Correlation analysis was performed, and the observed values ​​of each characteristic parameter were sorted from smallest to largest and assigned ranks. For identical values, the average rank was used if any pairs of values ​​existed. The difference d between the ranks of each pair of observations was calculated. i =R X,i -R r,i Calculate the sum of squares. Substitute the rank differences into the following formula to calculate the Spearman coefficient.

[0159] ;

[0160] Where, d i Let n be the difference between the ranks of the two variables in the i-th sample; n is the total number of samples. This represents the sum of squares of the grade differences. Finally, a significance test is performed, using a t-test or by consulting a table to determine if ρ is significant; typically, a p-value is given, and if p < 0.05, the correlation is significant. The correlation between the critical wind speed of navigation tunnels and relevant influencing parameters was analyzed, as shown in the table below:

[0161] ;

[0162] Factors with correlation coefficients greater than a set threshold are selected and fitted with a formula to obtain a critical wind speed prediction model from the critical wind speed simulation dataset.

[0163] The table data shows that the correlation coefficient between critical wind speed and the heat release rate of the ignition source is 0.772, and the correlation is significant at the 0.01 level (two-tailed), indicating a strong positive correlation between the two; that is, the higher the heat release rate of the ignition source, the higher the critical wind speed. The correlation coefficient between critical wind speed and clearance height, total tunnel height, design water depth, and net cross-sectional perimeter is -0.588, and the correlation is significant at the 0.05 level (two-tailed), indicating a negative correlation; as clearance height and perimeter increase, critical wind speed decreases. However, the correlation coefficients between critical wind speed and clearance width and net cross-sectional area are both -0.166, with significance levels greater than 0.05, meaning the correlations are not significant. In summary, critical wind speed is mainly affected by the heat release rate of the ignition source, clearance height, and cross-sectional perimeter, showing a strong positive correlation with the heat release rate of the ignition source, and a significant negative correlation with clearance height, total tunnel height, design water depth, and cross-sectional perimeter.

[0164] The aforementioned Spearman correlation analysis showed that the critical wind speed was more significantly correlated with the tunnel's net cross-sectional perimeter and clearance height compared to other characteristic values. Therefore, a dimensionless cross-sectional coefficient L was introduced. ZC / 4H is the net cross-sectional perimeter L ZC The ratio to four times the clearance height H.

[0165] The influence of the underlying surface on the critical wind speed of the water body:

[0166] In ship-navigable tunnels, the underlying surface is typically natural or artificial water, exhibiting significant thermophysical and aerodynamic differences compared to the rigid solid surfaces of traditional land tunnels, which are primarily composed of concrete or asphalt. The presence of water has a crucial impact on the smoke plume structure, buoyancy velocity, near-surface heat exchange, and airflow organization during the development of tunnel fires, thereby altering the formation mechanism of the critical wind speed for fires.

[0167] Changes in heat release and heat exchange: The high specific heat capacity and latent heat absorption capacity of water bodies lead to enhanced heat diffusion capacity in the bottom area, limiting heat convection below the fire source, resulting in more significant upward accumulation of heat, which in turn changes the plume's rising shape.

[0168] Enhanced absorption of radiative heat: Unlike solid underlying surfaces, water surfaces have low reflectivity to radiative heat from fire sources. A large amount of heat is absorbed by the water and used for evaporation, resulting in a reduced temperature gradient at the bottom and weakening the bottom thrust of the plume.

[0169] The disturbance effect caused by evaporative cooling: After the fire source heats the water surface, a water vapor disturbance zone is formed, which disrupts the flow structure of the main plume, induces bottom vortex and enhanced turbulence, and inhibits the stable flow of flue gas.

[0170] Enhanced air boundary layer slip effect: The smooth surface of the water body and the low fluid friction reduce the thickness of the air boundary layer close to the water surface, reduce the shear force formed by the bottom wind field, and make the flue gas more likely to swirl and flow backward.

[0171] Therefore, this invention introduces a water body correction factor. Eliminate the influence of underlying surface water on critical wind speed; H t H is the total height of the tunnel. w To design the water depth, H w / H t The water body correction term is represented by α, which is the fitting coefficient.

[0172] In tunnel fire research, to eliminate the interference of physical dimensions on the analysis results and achieve cross-scale data comparability, it is necessary to reconstruct key parameters in a dimensionless manner:

[0173] ;

[0174] Among them, V C * V is the dimensionless critical wind speed. C Critical wind speed, m / s; Q* is the dimensionless ignition heat release rate; Q is the ignition heat release rate, kW; Q is the ignition heat release rate, kW; ρ0 is the air density, taken as 1.205 kg / m³. 3 C P The specific heat of air at constant pressure is taken as 1.005 kJ / (kg·K); T0 is the ambient temperature, taken as 293.15 K; g is the acceleration due to gravity, taken as 9.8 m / s². 2 H represents the tunnel's navigation clearance height.

[0175] Simulation data show that as the dimensionless heat release rate Q* of the fire source increases, the dimensionless critical wind speed V... C * Increase it until it reaches the target. After remaining constant, the dimensionless heat release rate of the ignition source at its critical wind speed segment point is: ;

[0176] See Figure 7 Using data from three typical ship tunnels, the overall fitting coefficient α was found to be 0.6252.

[0177] The data from three typical ship tunnels were fitted separately, and the calculation results were compared to obtain the following results:

[0178] Ship Tunnel I: Total height H of the tunnel t The tunnel has a navigable clearance height H of 20m and a design water depth H. w The tunnel is 5.5 m long, and the net cross-sectional perimeter L is... ZC The length is 56.91m; the fitting coefficient α for ship tunnel I is 0.8927. This simulation result improves accuracy by 14.24% compared to the result obtained using the dry LI formula.

[0179] Ship Tunnel II: Total height H of the tunnel t The tunnel has a navigable clearance height H of 31m and a design water depth H of 22.5m. w The tunnel is 8.5 m long, and the net cross-sectional perimeter L is... ZC The depth is 94.10m; the fitting coefficient α for Ship Tunnel II is 0.8954. This simulation result improves accuracy by 9.5% compared to the result obtained using the dry LI formula.

[0180] Ship Tunnel III: Total height H of the tunnel t The tunnel's navigable clearance height H is 65.3m, and the design water depth H is 25.3m. w The length is 41 m, and the net cross-sectional perimeter of the tunnel is L. ZC The depth is 103.33m; the fitting coefficient α for ship tunnel III is 0.3910. This simulation result improves accuracy by 4.3% compared to the result obtained using the dry LI formula.

[0181] The LI formula is the critical wind speed formula published in: Li, YZ and H. Ingason, Effect of cross section on critical velocity in longitudinally ventilated tunnel fires[J]. Fire Safety Journal, 2017. 91: 303-311.

[0182] Example 3:

[0183] See Figure 8 A system for constructing a critical wind speed prediction model for fires in ship navigation tunnels, specifically including: a structural model construction module, a critical wind speed simulation module, and a data fitting module;

[0184] Structural Model Building Module: Used to create basic structural drawings of ship tunnels using drafting software. By adjusting the dimensional parameters of the basic structural drawings of ship tunnels, a structural model of the ship tunnel is obtained. Based on the structural model of the ship tunnel, the maximum tonnage of ships that can navigate through the tunnel is confirmed, and a fire source ship model is constructed.

[0185] Using drafting software, a basic structural drawing of a ship tunnel is created. Based on the basic structure of a ship tunnel, including the waterway at the bottom, pedestrian escape routes on both sides, and the arch at the top, a basic structural drawing of the ship tunnel is constructed, and a tunnel parameter adjustment model S is built for the basic structural drawing.

[0186] S={L,H t ,H,H w H r H g ,D,D r};

[0187] Where L is the tunnel length, H t H is the total height of the tunnel, and H is the navigable clearance of the tunnel. w To design the water depth, H r H is the height of the tunnel walkway. g D is the tunnel arch height, and D is the tunnel navigation clearance width. r This refers to the width of the pedestrian walkway on one side of the tunnel.

[0188] In the middle of the basic structural drawing of the ship tunnel, a fire source ship is set up, and a ship parameter adjustment model C is constructed:

[0189] C={ C t C L C W C H C D};

[0190] Among them, C t For ship tonnage, C L C represents the length of the ship. W For the ship's width, C H For the ship's height, C D This refers to the maximum draft of the vessel.

[0191] Based on the actual parameters of the tunnel, the tunnel parameter adjustment model S of the basic structure drawing is adjusted to obtain the structural model of the ship tunnel. Based on the structural model of the ship tunnel, the maximum tonnage ship that can navigate in the tunnel is identified. Based on the maximum tonnage ship that can navigate, the ship parameter adjustment model C is adjusted to obtain the fire source ship model.

[0192] Critical wind speed simulation module: used to determine the range of fire source characteristics on board based on the maximum navigable tonnage of the ship, select different fire source operating parameters according to the range of fire source characteristics, import the structural model of the ship tunnel and the fire source ship model into the fire simulation software, and perform fire simulation based on different fire source operating parameters to obtain the critical wind speed simulation dataset.

[0193] The range of fire source characteristics on board a vessel is determined based on its maximum navigable tonnage. The ranges of fire source characteristics for vessels of different tonnages are as follows:

[0194] C t ≤500 tons: heat release rate of the heat source is 2MW~50MW;

[0195] 500 tons < C t ≤1000 tons: heat release rate of the heat source is 5 MW~120MW;

[0196] 1000 tons < C t≤5000 tons: heat release rate of the heat source is 10 MW~200MW;

[0197] 5000 tons < C t ≤8000 tons: heat release rate of the heat source is 20 MW~260MW;

[0198] 8000 tons < C t ≤10,000 tons: heat release rate of the heat source is 50 MW to 300 MW.

[0199] Different fire source operating parameters are selected based on the range of fire source characteristics, corresponding to different fire source release rates Q: 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, unit: MW;

[0200] Based on different fire source operating parameters, refer to the table to confirm the mesh size and fire source diameter of the simulation model under different operating conditions;

[0201] The grid size and fire source diameter corresponding to different fire source operating conditions are input into the fire simulation software to simulate the fire conditions and obtain the critical wind speed simulation dataset.

[0202] Data Fitting Module: This module performs correlation analysis between the critical wind speed simulation dataset and the dimensional parameters of the ship tunnel, filters out factors with correlation coefficients greater than a set threshold, and fits them with the critical wind speed simulation dataset to obtain a critical wind speed prediction model.

[0203] Correlation analysis was performed between the critical wind speed simulation dataset and the size parameters of the ship tunnel. Correlation analysis was performed on the critical wind speed simulation datasets of multiple ship tunnels of different sizes and their corresponding size parameters. At the same time, correlation analysis was performed on the heat release rate of the fire source and its corresponding critical wind speed in the critical wind speed simulation dataset to obtain the correlation coefficient between each set of data.

[0204] The dimensional parameters of the ship tunnel include: tunnel clearance height H, and tunnel total height H. t Design water depth H w 1. Tunnel navigation clearance width D; 2. Tunnel net cross-sectional perimeter L ZC The net cross-sectional area of ​​the tunnel is L S The space above the water surface within the cross-section of a tunnel is called the net cross-section.

[0205] Factors with correlation coefficients greater than a set threshold were selected and fitted with a formula to the critical wind speed simulation dataset: First, the parameters of different fire source conditions and their corresponding critical wind speed parameters were processed to be dimensionless, resulting in a dataset of dimensionless fire source heat release rate Q* and the corresponding dimensionless critical wind speed V. C * The data set was used, and factors with correlation coefficients greater than a set threshold were selected as relevant parameters. Simulation data showed that as the dimensionless heat release rate Q* increased, the dimensionless critical wind speed V... C * Increase it until it reaches the target. After remaining constant, the dimensionless heat release rate of the ignition source at its critical wind speed segment point is: ;

[0206] Using the two Q* and V mentioned above C * The dataset and relevant parameters are fitted together to obtain the critical wind speed prediction model;

[0207] ;

[0208] Among them, V C * L is the dimensionless critical wind speed; Q* is the dimensionless heat release rate of the ignition source; L ZC The net cross-sectional perimeter of the tunnel is defined as the space above the water surface within the tunnel's cross-section; H is the tunnel's navigation clearance; L ZC / 4H is the section coefficient; H t H is the total height of the tunnel. w To design the water depth, H w / H t The water body correction term is represented by α, which is the fitting coefficient. The maximum dimensionless critical wind speed; The dimensionless heat release rate of the fire source is the critical wind speed segment point.

[0209] The prediction model construction method further includes step four, which uses a structural model construction module and a critical wind speed simulation module to obtain the dimensional parameters of the ship tunnel S1 and the critical wind speed simulation dataset of the ship tunnel S1. The dimensional parameters and critical wind speed simulation dataset of the ship tunnel S1 are then input into the critical wind speed prediction model. First, the dimensionless heat release rate of the fire source at the segment points of the ship tunnel S1 is obtained. The maximum dimensionless critical wind speed of the ship tunnel S1 Then, the fitting coefficient α of the ship tunnel S1 is obtained to get the critical wind speed prediction model of the ship tunnel S1.

[0210] Example 4:

[0211] SeeFigure 9 A device for constructing a critical wind speed prediction model for fires in ship navigation tunnels includes a memory and a processor. The memory is used to store computer program code and transmit the computer program code to the processor. The processor is used to execute the aforementioned method for constructing a critical wind speed prediction model for fires in ship navigation tunnels according to the instructions in the computer program code.

[0212] Example 5:

[0213] A computer program product includes a computer program that is executed by a processor to construct the aforementioned method for predicting critical wind speeds for fires in ship navigation tunnels.

Claims

1. A method for constructing a ship navigation tunnel fire critical wind speed prediction model, characterized in that: The construction method of the prediction model comprises the following steps: Step one: a basic structure drawing of a ship tunnel is made by using a drawing software, a structure model of the ship tunnel is obtained by adjusting size parameters of the basic structure drawing of the ship tunnel, and a maximum tonnage of a ship that can navigate in the tunnel is determined based on the structure model of the ship tunnel, and a fire source ship model is constructed; Step two: a range of fire source features on the ship is determined according to the maximum tonnage of the ship that can navigate in the tunnel, different fire source working condition parameters are selected according to the range of the fire source features, the structure model of the ship tunnel and the fire source ship model are imported into a fire simulation software, and critical wind speed simulation data sets are obtained by performing fire simulation based on the different fire source working condition parameters; Step three: correlation analysis is performed on the critical wind speed simulation data sets and size parameters of the ship tunnel, factors with a correlation coefficient greater than a set threshold are selected, formula fitting is performed on the critical wind speed simulation data sets and the selected factors, and a critical wind speed prediction model is obtained; The factors with correlation coefficients greater than a set threshold value are screened out and formula fitting is performed on the critical wind speed simulation data set: first, the different fire source working condition parameters and the corresponding critical wind speed parameters are dimensionless processed to obtain a dimensionless fire source heat release rate Q * data set and a corresponding dimensionless critical wind speed V C * data set, then the factors with absolute values of correlation coefficients greater than a set threshold value are selected as the correlation parameters; simulation data shows that with the increase of the dimensionless fire source heat release rate Q *, the dimensionless critical wind speed V C * first increases until it reaches and then remains unchanged, and the dimensionless fire source heat release rate of the critical wind speed segmentation point is ; The two above-mentioned data sets are used to perform data fitting with the relevant parameters to obtain a critical wind speed prediction model. Q *and V C * The data set and the relevant parameters are used to perform data fitting to obtain a critical wind speed prediction model. ； where V C * is the dimensionless critical wind speed; Q is the dimensionless heat release rate of the fire source; L ZC The tunnel net section perimeter, the space above the water surface in the tunnel cross section is called the net section; H The tunnel navigation net height; L ZC / 4H The section coefficient; H t The tunnel total height, H w The design water depth, H w / H t The water body correction term; α The fitting coefficient; The maximum dimensionless critical wind speed; The dimensionless heat release rate of the critical wind speed segmentation point; Step 4 targets ship tunnels S 1 By following steps one and two, the ship tunnel is obtained. S 1 Dimensions and ship tunnels S 1 The critical wind speed simulation dataset will be used for ship tunnels. S 1 The dimensional parameters and critical wind speed simulation dataset are input into the critical wind speed prediction model. First, the ship tunnel is obtained. S 1 The dimensionless heat release rate of the fire source at the segment point is Harbor ship tunnel S 1 Maximum dimensionless critical wind speed Then calculate the ship tunnel. S 1 Fit coefficient α Obtain the ship tunnel S 1 Critical wind speed prediction model.

2. The method according to claim 1, wherein the method is characterized by: In step one, the basic structure drawing of the ship tunnel is made by using the drawing software, the basic structure of the ship tunnel includes a waterway at the bottom, escape passages for people at both sides, and an arch at the top, the basic structure drawing of the ship tunnel is constructed, a tunnel parameter adjustment model S of the basic structure drawing is constructed, S={ L , H t , H , H w , H r , H g , D , D r }； wherein, L is the length of the tunnel, H t is the total height of the tunnel, H is the net height of the tunnel for navigation, H w is the design water depth, H r is the height of the tunnel sidewalk, H g is the vault height of the tunnel, D is the net width of the tunnel for navigation, D r is the width of the tunnel single sidewalk; In the basic structure drawing of the ship tunnel, a fire source ship is arranged in the middle, and a ship parameter adjustment model C is constructed, C={ C t , C L , C W , C H , C D}； wherein, C t L is the length of the ship, C L L is the length of the ship, C W L is the length of the ship, C H L is the length of the ship, C D L is the length of the ship, The tunnel parameter adjustment model S of the basic structure drawing is adjusted according to actual parameters of the tunnel, the structure model of the ship tunnel is obtained, the maximum tonnage of the ship that can navigate in the tunnel is determined based on the structure model of the ship tunnel, and the fire source ship model is obtained by adjusting the ship parameter adjustment model C according to the maximum tonnage of the ship that can navigate in the tunnel.

3. The method according to claim 1, characterized in that: In step two, the range of the fire source features on the ship is determined according to the maximum tonnage of the ship that can navigate in the tunnel, the range of the fire source features of different tonnage ships is as follows: C t ≤ 500 tons: fire heat release rate of 2 MW to 50 MW; 500 tons < C t ≤1000 tons: heat release rate of the heat source is 5 MW~120MW; 1000 tons < C t ≤5000 tons: heat release rate of the heat source is 10 MW~200MW; 5000 tons < C t ≤8000 tons: heat release rate of the heat source is 20 MW~260MW; 8000 tons < C t ≤10,000 tons: heat release rate of the heat source is 50 MW to 300 MW.

4. The method according to claim 3, characterized in that: In the second step, different fire source working condition parameters are selected according to the range of fire source characteristics, corresponding to different fire source release rates Q : 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, unit: MW; According to different fire source working condition parameters, the grid size and the fire source diameter size of the simulation model under different working conditions are determined by referring to a table, and the table is as follows: ； The grid size and the fire source diameter size corresponding to different fire source working condition parameters are respectively input into the fire simulation software to simulate the fire working condition, and the critical wind speed simulation data sets are obtained.

5. The method according to claim 1, wherein the method is characterized in that: In step three, correlation analysis is performed on the critical wind speed simulation data sets and the size parameters of the ship tunnel, correlation analysis is performed on the critical wind speed simulation data sets and the size parameters of the ship tunnel of multiple ship tunnels with different sizes, correlation analysis is also performed on the heat release rate of the fire source in the critical wind speed simulation data sets and the corresponding critical wind speed, and the correlation coefficients between each group of data are obtained. The size parameters of the ship tunnel include: tunnel navigation net height H , tunnel total height H t , design water depth H w , tunnel navigation net width D , tunnel net section perimeter L ZC , tunnel net section area L S The space above the water surface in the tunnel cross section is called the net section.

6. A ship navigation tunnel fire critical wind speed prediction model construction system, characterized in that, The system is used to perform the ship tunnel fire critical wind speed prediction model construction method according to any one of claims 1 to 5, and specifically comprises a structure model construction module, a critical wind speed simulation module, a data fitting module, and a critical wind speed prediction model construction module; The structure model construction module is used to make a basic structure drawing of a ship tunnel by using a drawing software, obtain a structure model of the ship tunnel by adjusting size parameters of the basic structure drawing of the ship tunnel, determine a maximum tonnage of a ship that can navigate in the tunnel based on the structure model of the ship tunnel, and construct a fire source ship model. The critical wind speed simulation module is configured to confirm a range of fire source characteristics of a ship according to a maximum tonnage of a navigable ship, select different fire source working condition parameters according to the range of the fire source characteristics, import a structural model of a ship tunnel and a fire source ship model into a fire simulation software, and perform fire simulation based on the different fire source working condition parameters to obtain a critical wind speed simulation data set; The data fitting module is configured to perform correlation analysis on the critical wind speed simulation data set and size parameters of the ship tunnel, filter out factors with a correlation coefficient greater than a set threshold, and perform formula fitting on the critical wind speed simulation data set to obtain a critical wind speed prediction model. The factors with correlation coefficients greater than a set threshold value are screened out and formula fitting is performed on the critical wind speed simulation data set: first, the different fire source working condition parameters and the corresponding critical wind speed parameters are dimensionless processed to obtain a dimensionless fire source heat release rate Q * data set and a corresponding dimensionless critical wind speed V C * data set, then factors with absolute values of correlation coefficients greater than a set threshold value are selected as relevant parameters; simulation data shows that with the increase of dimensionless fire source heat release rate Q *, the dimensionless critical wind speed V C * first increases until reaching , and then remains unchanged, and the dimensionless fire source heat release rate of the critical wind speed segmentation point is ; The two above-mentioned data sets are used to perform data fitting with the relevant parameters to obtain a critical wind speed prediction model. Q *and V C * The data set and the relevant parameters are used to perform data fitting to obtain a critical wind speed prediction model. ； wherein, V C * is the dimensionless critical wind speed; Q is the dimensionless heat release rate of the fire source; L ZC is the net cross-sectional perimeter of the tunnel, the space above the water surface within the cross section of the tunnel being referred to as the net cross section; H is the net height of the tunnel; L ZC / 4H is the section coefficient; H t is the total height of the tunnel, H w is the design water depth, H w / H t is the water body correction term; α is the fitting coefficient; is the maximum dimensionless critical wind speed; is the dimensionless heat release rate of the fire source at the segment point of the critical wind speed; The critical wind speed prediction model construction module: for the ship tunnel S 1 Through the structure model construction module, the critical wind speed simulation module, the size parameters and the critical wind speed simulation dataset of the ship tunnel S 1 are obtained. S 1 The size parameters and the critical wind speed simulation dataset of the ship tunnel S 1 are input into the critical wind speed prediction model, first, the dimensionless heat release rate of the ship tunnel S 1 is obtained at the segmentation point , and the maximum dimensionless critical wind speed S 1 of the ship tunnel is obtained, then the fitting coefficient S 1 of the ship tunnel α is obtained, and the critical wind speed prediction model of the ship tunnel S 1 is obtained.

7. A ship navigation tunnel fire critical wind speed prediction model construction device, characterized by, The computer program is executed by the processor to perform the ship tunnel fire critical wind speed prediction model construction method according to any one of claims 1 to 5. The computer program is executed by the processor to perform the ship tunnel fire critical wind speed prediction model construction method according to any one of claims 1 to 5.

8. A computer program product comprising a computer program, characterized in that, ​

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