Fire value simulation method and system for power compartment of urban utility tunnel

Abstract

The present invention relates to the technical field of safety assessment of urban infrastructure. Provided are a fire value simulation method and system for a power compartment of an urban utility tunnel. The method provided in the present invention comprises: constructing a three-dimensional physical model of a power compartment of a utility tunnel, dividing the model into sequentially adjacent regional segments, and performing meshing to obtain structural mesh models; on the basis of the structural mesh models of the regional segments, setting fire source positions, establishing a spatiotemporal evolution model for a fire temperature field, and acquiring air temperature field distribution data; mapping the air temperature field data to the structural mesh models, so as to obtain structural temperature fields, and performing transient thermal-structural coupling analysis to acquire strain field data and thermal stress field data; on the basis of the strain field data and the thermal stress field data, acquiring structural damage data of each mesh element, and defining a total damage variable; and presetting a dynamic threshold value for the total damage variable of the regional segments, and completing evaluation by means of a result of matching with a threshold value interval.

Description

Numerical Simulation Method and System for Fire in Power Cabin of Urban Integrated Utility Tunnel Technical Field

[0001] This invention relates to the field of safety management of urban integrated utility tunnels, specifically to a numerical simulation method and system for fires in the power compartments of urban integrated utility tunnels. Background Technology

[0002] With the acceleration of urbanization, the safe operation of urban integrated utility tunnels, as important underground infrastructure, is of paramount importance. The power compartment, a crucial component of the integrated utility tunnel, bears the heavy responsibility of urban power transmission. A fire in this compartment would not only cause enormous economic losses but could also trigger a chain reaction, threatening urban safety. Therefore, numerical simulation studies of fires in the power compartments of urban integrated utility tunnels are of great significance for preventing and mitigating fire disasters.

[0003] Currently, numerical simulation research on fires in power compartments of urban integrated utility tunnels mainly focuses on fire spread patterns and fire parameter distribution. Existing technology, with publication number CN111881621A, discloses a method and system for numerical simulation of fires in power compartments of urban integrated utility tunnels. This method establishes a physical model of the power compartment containing only internal cables, initializes the parameters of the physical model, establishes a fire simulation model based on the physical model, sets multiple measuring points and parameters for the fire simulation model, runs the fire simulation model and calculates preliminary fire numerical simulation results, and then uses a genetic optimization algorithm to obtain accurate fire numerical simulation results. This method can accurately perceive the spread pattern of fire smoke and the distribution of fire parameters within the power compartment of the integrated utility tunnel after a fire occurs, providing a technical basis for the structural design of the power compartment. The prior art, disclosed in publication number CN119313989A, presents a method for selecting the sealing of electrical compartments in underground utility tunnels based on fire conditions. This method utilizes FDS fire dynamics simulation software to construct full-size models of both sealed and unsealed electrical compartments, simulating fire spread under both models and recording extinction times and fire spread images to determine the fire evolution under different conditions. Based on the extinction times and fire spread images, the method selects whether to seal the compartment, thereby improving the safety and fire resistance of the electrical compartment in the underground utility tunnel.

[0004] However, existing technologies have the following shortcomings: First, existing fire numerical simulation methods mainly focus on fire spread patterns and fire parameter distribution, lacking analysis of the thermo-structural coupling response of utility tunnel power compartment structures under fire conditions; second, most existing methods use simplified models, failing to accurately simulate the multi-mechanism damage evolution process of complex structures under high-temperature environments; third, existing technologies lack quantitative assessment methods for the damage risk and safety status of steel structures in utility tunnel power compartments under fire conditions; finally, existing methods struggle to achieve differentiated safety assessments of different sections of utility tunnel power compartments, failing to provide precise decision support for utility tunnel operation and maintenance. These problems severely restrict the effectiveness and scientific rigor of fire prevention and safety management in urban integrated utility tunnel power compartments. The information disclosed in the background section is only for enhancing understanding of the background of this disclosure and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this invention is to provide a numerical simulation method and system for fires in the power compartment of an urban integrated utility tunnel, so as to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A numerical simulation method and system for fires in the power compartment of an urban integrated utility tunnel, comprising the following steps:

[0008] S1: Construct a three-dimensional physical model of the power compartment in the utility tunnel and obtain the material parameters of all steel structures in the utility tunnel. Divide the three-dimensional physical model of the power compartment into sequentially adjacent regions, mesh all regions, and obtain the structural mesh model of each region.

[0009] S2: Based on the structural grid model of the regional segment, the fire source location is set according to the actual risk points of the power compartment, and a fire temperature field spatiotemporal evolution model is established at the current fire source location. The fire temperature field spatiotemporal evolution model is run to obtain air temperature field distribution data.

[0010] S3: Map the air temperature field distribution data to the structural mesh model of each region to obtain the structural temperature field, and perform transient thermal-structural coupling analysis based on the structural temperature field to obtain the strain field data and thermal stress field data of the structural mesh model of each region.

[0011] S4: Based on the strain field data and thermal stress field data of the structural mesh model of the region segment, obtain the structural damage data of each mesh unit in the structural mesh model of the region segment, and define the total damage variable of each mesh unit through multi-mechanism damage;

[0012] S5: Set a dynamic threshold for the total damage variable of the region segment, set filtering conditions for the total damage variable of all grid cells in the region segment, obtain the total damage variable of the region segment, and complete the evaluation of all regions segment based on the matching results with the threshold interval.

[0013] Furthermore, the three-dimensional physical model of the utility tunnel power compartment is constructed based on the geometric parameters of the utility tunnel power compartment, including: tunnel length, cross-sectional dimensions, wall panel thickness, connectors, and support layout. The model is divided into sequentially adjacent equal-length segments along the length direction, with each segment being an independent analysis unit. Each segment is then individually meshed with a structured grid. The output structured grid model for each segment includes: the center coordinates of each grid unit and the material parameters of the steel structure of the grid unit. The material parameters of the steel structure at the center of the grid unit include: elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, specific heat capacity, yield strength, fracture strain value, creep damage friction reference stress, and fatigue SN curve.

[0014] Furthermore, based on the regional segment structure grid model and setting different fire source locations according to the actual risk points in the power compartment, a spatiotemporal evolution model of the fire temperature field is established for different fire source locations using the fire heat release rate. A non-uniform dynamic temperature rise model is used to describe the temperature changes with time and space to obtain the air temperature field, as shown in the following formula:

[0015]

[0016] in, For the first grid cells Temperature at any moment No. The center coordinates of each grid cell The initial temperature of the utility tunnel's electrical compartment. The maximum temperature rise in a fire, It is a time constant; It is a spatial distribution function;

[0017]

[0018] in, Coordinates of the fire source The diameter is determined by the heat effect of the fire source.

[0019] Furthermore, a spatiotemporal evolution model of the fire temperature field is established for different fire source locations based on the fire heat release rate, wherein the fire heat release rate adopts... The square fire growth model, the formula is as follows:

[0020]

[0021] in, For heat release rate, It is the fire growth coefficient.

[0022] Furthermore, the air temperature field distribution data is mapped onto the structural mesh model of each region using interpolation methods to obtain the structural temperature field. Specific steps include: solving the heat conduction equation to obtain the change in heat energy stored per unit time in the mesh cells obtained from the heat conduction equation; combining this with the initial temperature of the utility tunnel's power compartment, the internal temperature distribution of the steel structure is calculated, and the structural temperature field is constructed. The heat conduction equation is solved as follows:

[0023]

[0024] in, For grid cells The change in heat energy, For grid cells The density of steel structures, For grid cells Specific heat capacity of steel structures For grid cells The thermal conductivity of the steel structure, For the Laplace operator, air temperature field The gradient.

[0025] Furthermore, transient thermo-structural coupling analysis is performed using the finite element method based on the structural temperature field to obtain strain field data and thermal stress field data for each region of the structural mesh model. The strain field data and thermal stress field data include: the total strain tensor, plastic stress tensor, and thermal strain tensor of the mesh elements. Using the obtained total strain tensor, plastic stress tensor, and thermal strain tensor of the mesh elements, the plastic stress tensor and plastic strain tensor of the mesh elements are obtained. Specifically, the thermal strain tensor of the mesh element is obtained by multiplying the thermal expansion coefficient of the steel structure by the maximum change in structural temperature caused by the maximum temperature rise of the mesh element during a fire, as reflected by the structural temperature field. The plastic strain tensor of the mesh element is obtained by the difference between the total strain tensor and the thermal strain tensor of the mesh element. The plastic stress tensor of the mesh element is obtained by multiplying the plastic strain tensor by the elasticity matrix.

[0026] Furthermore, the structural damage data of each grid cell in the structural mesh model of the region segment includes: creep damage, plastic damage, and fatigue damage; for each grid cell... Solving the plastic stress tensor yields the von Mises stress. The formula for calculating creep damage is as follows:

[0027]

[0028] in, For grid cells creep damage, For grid cells The creep damage reference stress, The creep stress index is given by the following formula for calculating plastic damage:

[0029]

[0030] in, For grid cells Plastic damage, For grid cells The fracture strain value; the fatigue damage calculation formula is as follows:

[0031]

[0032] in, For grid cells fatigue damage, The total number of cycle categories with different stress amplitudes. For grid cells stress Rainflow counting was performed using the time history to obtain the first Number of cycles under the stress amplitude; To find the corresponding first SN curve for the fatigue parameters of the steel structure material. The number of cycles for each stress amplitude; the total damage variable for each mesh element is defined using multi-mechanism damage, as shown in the following formula:

[0033]

[0034] in, For grid cells Total damage variable, Let be the weight coefficient, and satisfy... .

[0035] Furthermore, for each region segment, the maximum value of the total damage variable across all its grid cells is selected and defined as the total damage variable for that region segment. A dynamic threshold for the total damage variable of the region segment is preset.

[0036]

[0037]

[0038] in, This is the lower limit of the damage threshold. This represents the upper limit of the damage threshold. This is an empirical coefficient. For yield strength, The modulus of elasticity is used; when the total damage variable is less than the lower limit of the damage threshold, the area to be evaluated is safe; when the total damage variable is greater than the lower limit of the damage threshold but less than the upper limit of the damage threshold, the area to be evaluated needs to be monitored regularly; when the total damage variable is greater than the upper limit of the damage threshold, the area needs to be inspected and reinforced.

[0039] Furthermore, the present invention also provides a numerical simulation system for fires in the power compartments of urban integrated utility tunnels for executing any of the above-mentioned numerical simulation methods for fires in the power compartments of urban integrated utility tunnels, comprising:

[0040] The structural discretization preprocessing module is used to construct a three-dimensional physical model of the power compartment in the utility tunnel and simultaneously obtain the material parameters of all steel structures within the utility tunnel. It divides the three-dimensional physical model of the power compartment into sequentially adjacent regions, performs meshing on all regions, and obtains the structural mesh model of each region.

[0041] Fire dynamics simulation module: used for structural mesh models based on regional segments, setting fire source locations according to actual risk points in the power compartment, establishing a spatiotemporal evolution model of the fire temperature field at the current fire source location, running the spatiotemporal evolution model of the fire temperature field, and obtaining air temperature field distribution data;

[0042] Thermal-structural coupling response module: used to map air temperature field distribution data to the structural mesh model of each region to obtain the structural temperature field, perform transient thermal-structural coupling analysis based on the structural temperature field, and obtain strain field data and thermal stress field data of the structural mesh model of each region.

[0043] Multi-mechanism damage quantification module: Used to obtain structural damage data of each grid cell in the structural grid model of the region segment based on strain field data and thermal stress field data of the structural grid model of the region segment, and to define the total damage variable of each grid cell through multi-mechanism damage;

[0044] Dynamic safety evaluation module: This module is used to preset dynamic thresholds for the total damage variable of a region segment, set filtering conditions for the total damage variable of all grid cells in the region segment, obtain the total damage variable of the region segment, and complete the evaluation of all regions segment based on the matching results with the threshold interval.

[0045] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention realizes a full-process simulation from fire dynamics to structural damage assessment, covering the entire process of fire impact, providing accurate fire risk assessment and early warning for utility tunnel power compartments, and overcoming the limitations of traditional methods that rely on physical experiments or simplified models; by comprehensively considering a multi-mechanism damage model that integrates creep, plasticity, and fatigue damage, the accuracy of the assessment is significantly improved, and it can comprehensively reflect the complex damage state of steel structures under fire conditions, providing a scientific basis for the safety assessment of utility tunnel power compartments; the safety assessment method based on setting dynamic thresholds according to material parameters enables the system to adapt to the assessment needs of different utility tunnel structures, improving the applicability and reliability of the assessment results; the system modules are clearly divided, including five functional modules: structural discretization preprocessing, fire dynamics simulation, thermo-structural coupling response analysis, multi-mechanism damage quantification, and dynamic safety assessment, which facilitates technology integration and functional expansion, and improves the practicality and adaptability of the method. Attached Figure Description

[0046] Figure 1 is a schematic diagram of the overall method flow of the present invention;

[0047] Figure 2 is a data diagram of air temperature distribution in the grid cell according to an embodiment of the present invention;

[0048] Figure 3 is a temperature distribution data diagram of the grid cell structure in an embodiment of the present invention;

[0049] Figure 4 is a multi-mechanism damage data diagram of the mesh element in an embodiment of the present invention;

[0050] Figure 5 is a schematic diagram of the system module flow of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0052] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0053] Example:

[0054] Please refer to Figures 1 to 4. This invention provides a technical solution:

[0055] A numerical simulation method for fires in the power compartment of an urban integrated utility tunnel, comprising the following steps:

[0056] S1: Construct a three-dimensional physical model of the power compartment in the utility tunnel and obtain the material parameters of all steel structures in the utility tunnel. Divide the three-dimensional physical model of the power compartment into sequentially adjacent regions, mesh all regions, and obtain the structural mesh model of each region.

[0057] In this embodiment, the three-dimensional physical model of the utility tunnel power compartment is constructed based on the geometric parameters of the utility tunnel power compartment. The geometric parameters include: the length of the utility tunnel, cross-sectional dimensions, wall panel thickness, connectors, and support layout. The model is divided into sequentially adjacent equal-length segments along the length direction. Each segment is an independent analysis unit, and each segment is separately meshed into a structured grid. The structured grid model of each segment is output, and the output structured grid model includes: the center coordinates of each grid unit and the material parameters of the steel structure of the grid unit. The material parameters of the steel structure at the center of the grid unit include: elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, specific heat capacity, yield strength, fracture strain value, creep damage reference stress, and fatigue SN curve.

[0058] Specifically, in this embodiment, a 3D physical model of the utility tunnel's power compartment is constructed using 3D modeling software. The model is based on actual engineering dimensions. In this embodiment, a section of the utility tunnel with a length of 100 meters, a cross-sectional width of 2 meters, and a height of 3 meters is selected, including the layout of wall panels, connectors, and supports. The model is divided into sequentially adjacent equal-length segments along its length, with each segment serving as an independent analysis unit. In this embodiment, the segments are divided at 10-meter intervals. When initializing the structural parameters, all selected utility tunnel power compartments are made of the same steel material. The steel structural material parameters are input as follows: elastic modulus. Poisson's ratio ,density coefficient of thermal expansion thermal conductivity Specific heat capacity Yield strength fracture strain value Creep damage reference stress And fatigue SN curve; In this embodiment, a 10m section of the power compartment in the pipe gallery is selected for mesh generation. In the finite element preprocessing software, a mapped mesh generation is performed on each section, dividing it into 5 mesh units with a 2m interval. The center of each mesh unit is respectively , , , , Export the mesh model file for each region segment. The file must include: the number of each mesh cell, node coordinates, cell center coordinates, and the steel structure material parameters corresponding to each mesh cell.

[0059] Compared with existing techniques that treat the entire utility tunnel as a whole for meshing, this step divides the tunnel into sequentially adjacent segments before meshing. This reduces the size and computational complexity of individual models, making it possible to perform high-precision simulations of ultra-long utility tunnels with limited computing resources. Individual segments can be meshed as independent analysis units, laying the foundation for subsequent analysis.

[0060] S2: Based on the structural grid model of the regional segment, the fire source location is set according to the actual risk points of the power compartment, and a fire temperature field spatiotemporal evolution model is established at the current fire source location. The fire temperature field spatiotemporal evolution model is run to obtain air temperature field distribution data.

[0061] In this embodiment, based on the regional segment structure grid model, and according to the actual risk points in the power compartment, different fire source locations are set. For different fire source locations, a spatiotemporal evolution model of the fire temperature field is established through the fire heat release rate. A non-uniform dynamic temperature rise model is used to describe the temperature change with time and space to obtain the air temperature field. The formula is as follows:

[0062]

[0063] in, For the first grid cells Temperature at any moment No. The center coordinates of each grid cell The initial temperature of the utility tunnel's electrical compartment. The maximum temperature rise in a fire, The formula combines the exponential growth of time with the exponential decay of space, representing a classic and efficient mathematical abstraction of the spatiotemporal evolution of the fire temperature field. It directly determines the peak value of the temperature field; the larger the value, the higher the final temperature and the greater the threat to the structure. Control the rate of temperature rise. The smaller the value, the faster the temperature rises, the less time the material has to dissipate heat, and the more significant the thermal stress becomes. It is a spatial distribution function;

[0064]

[0065] in, Coordinates of the fire source The diameter affected by the heat source; Controlling the range of temperature effects, The larger the structure, the higher the temperature at locations furthest from the fire source, potentially leading to more extensive structural damage.

[0066] In this embodiment, a spatiotemporal evolution model of the fire temperature field is established for different fire source locations based on the fire heat release rate, wherein the fire heat release rate adopts... The square fire growth model, the formula is as follows:

[0067]

[0068] in, For heat release rate, It is the fire growth coefficient; It determines the speed at which the fire spreads and indirectly affects and The value of ; The larger the value, the faster the fire will be, leading to a rapid temperature rise.

[0069] In this embodiment, based on the power compartment risk assessment report, one or more potential fire source locations are identified and their coordinates are assigned. Set model parameters for each fire source scenario: initial temperature , , The fire source is located in the middle of the selected pipe gallery. place, , ; Perform the simulation to traverse the center coordinates of all grid cells at each time step Calculate its temperature Please refer to Figure 2: Output the air temperature field data of all grid cells at each time step. The specific spatiotemporal temperature distribution data of the grid cells is shown in Table 1 below.

[0070] Table 1: Air Temperature Distribution Data of Grid Cells

[0071] This step employs a combination of parametric and non-uniform dynamic temperature rise models, rather than relying on computationally expensive computational fluid dynamics (CFD) fire simulations. For assessments aimed at structural response, this model provides sufficient accuracy in the temperature field and captures key characteristics of temperature decay over time and space. By changing the fire source coordinates and the diameter of the heat-affected zone, fire scenarios of different locations and scales can be quickly simulated, providing crucial temperature load inputs for subsequent thermo-structural coupling analysis.

[0072] S3: Map the air temperature field distribution data to the structural mesh model of each region to obtain the structural temperature field, and perform transient thermal-structural coupling analysis based on the structural temperature field to obtain the strain field data and thermal stress field data of the structural mesh model of each region.

[0073] Furthermore, the air temperature field distribution data is mapped onto the structural mesh model of each region using interpolation methods to obtain the structural temperature field. Specific steps include: solving the heat conduction equation to obtain the change in heat energy stored per unit time in the mesh cells obtained from the heat conduction equation; combining this with the initial temperature of the utility tunnel's power compartment, the internal temperature distribution of the steel structure is calculated, and the structural temperature field is constructed. The heat conduction equation is solved as follows:

[0074]

[0075] in, For grid cells The change in heat energy, For grid cells The density of steel structures, For grid cells Specific heat capacity of steel structures For grid cells The thermal conductivity of the steel structure, For the Laplace operator, air temperature field The gradient. Characterizing the thermal conductivity of materials, The larger the value, the faster the heat spreads in the structure, the more uniform the temperature distribution, and the more likely it is to reduce the thermal stress at local high-temperature points. Characterizing the material's ability to store heat, The higher the value, the more heat is required to raise the temperature of a unit mass of material by one degree, and the slower the temperature rises. and Together, they constitute the volumetric heat capacity, influencing the inertia of temperature changes. This formula is a combination of Fourier's law of heat conduction and the law of conservation of energy; it describes the relationship between the temperature change at any point inside an object over time and the inflow and outflow of heat due to spatial temperature gradients.

[0076] Please refer to Figure 3. The air temperature field distribution data is mapped to the structural grid model of each region through interpolation to obtain the structural temperature field. The thermal energy change data of each unit is obtained as shown in Table 2. Combined with the initial temperature of the power compartment of the pipe gallery, the internal temperature distribution of the steel structure is calculated as shown in Table 3.

[0077] Table 2: Changes in Thermal Energy of Grid Cells

[0078] Table 3: Temperature Distribution Data of Mesh Cell Structure

[0079] In this embodiment, transient thermo-structural coupling analysis is performed using the finite element method based on the structural temperature field to obtain strain field data and thermal stress field data for each region of the structural mesh model. The strain field data and thermal stress field data include: the total strain tensor, plastic stress tensor, and thermal strain tensor of the mesh elements. Using the obtained total strain tensor, plastic stress tensor, and thermal strain tensor of the mesh elements, the plastic stress tensor and plastic strain tensor of the mesh elements are obtained. The thermal strain tensor of the mesh elements is obtained by multiplying the thermal expansion coefficient of the steel structure by the maximum change in structural temperature caused by the maximum temperature rise of the mesh element during a fire, as reflected in the structural temperature field. The specific formula is as follows:

[0080]

[0081] The plastic strain tensor of a mesh element is obtained by the difference between the total strain tensor and the thermal strain tensor of the mesh element, as shown in the following formula:

[0082]

[0083] The plastic stress tensor of the mesh element is obtained by multiplying the plastic strain tensor by the elastic matrix, as shown in the following formula:

[0084]

[0085] in, It is an elastic matrix, composed of mesh elements. The material parameters of the steel structure of the grid cells, namely the elastic modulus and Poisson's ratio, are obtained. For grid cells The plastic stress tensor, For grid cells The total strain tensor, For grid cells thermal strain tensor For grid cells The plastic strain tensor For grid cells The coefficient of thermal expansion of steel structures, Mesh elements reflecting structural temperature conditions The maximum temperature rise caused by the fire results in the maximum change in structural temperature; this step clarifies the unidirectional coupling analysis strategy of first calculating the temperature field and then using the temperature field as a load for structural mechanical analysis; this is in contrast to the fully coupled approach that solves for both temperature and displacement fields simultaneously.

[0086] S4: Based on the strain field data and thermal stress field data of the structural mesh model of the region segment, obtain the structural damage data of each mesh unit in the structural mesh model of the region segment, and define the total damage variable of each mesh unit through multi-mechanism damage;

[0087] In this embodiment, the structural damage data of each grid cell in the structural mesh model of the region segment includes: creep damage, plastic damage, and fatigue damage; for the grid cells... Solving the plastic stress tensor yields the von Mises stress. The specific formula is as follows:

[0088]

[0089] in, The plastic stress tensor components are shown in Table 4 below. In this embodiment, transient thermo-structural coupling analysis is performed based on the structural temperature field to obtain the strain field data and thermal stress field data of the structural mesh model for each region.

[0090] Table 4: Data from Thermal-Structural Coupling Analysis

[0091] The formula for calculating creep damage is as follows:

[0092]

[0093] in, For grid cells creep damage, For grid cells The creep damage reference stress, Creep stress index: A variation of the classical creep law, assuming that the damage accumulation rate is related to the stress... The stress is directly proportional to the power; at high temperatures, even if the stress is below the yield strength, it will still fail due to creep after a long period of time. and These are the creep performance parameters of the material, obtained through high-temperature creep tests; The larger the value, the more sensitive the material is to stress, and the faster the creep damage accumulates under high stress; the formula for calculating plastic damage is as follows:

[0094]

[0095] in, For grid cells Plastic damage, For grid cells The fracture strain value; using the simple ratio of maximum plastic strain to fracture strain, it intuitively reflects the degree to which the material is close to fracture due to excessive deformation; It is a ductility index of the material; the smaller the value, the more brittle the material, and the more prone it is to plastic damage. The fatigue damage calculation formula is as follows:

[0096]

[0097] in, For grid cells fatigue damage, The total number of cycle categories with different stress amplitudes. For grid cells stress Rainflow counting was performed using the time history to obtain the first Number of cycles under the stress amplitude; To find the corresponding first SN curve for the fatigue parameters of the steel structure material. The number of cycles for each stress amplitude is used; the linear accumulation rule, although approximate, is widely accepted in engineering for assessing damage caused by stress fluctuations. The total damage variable for each mesh element is defined using multi-mechanism damage, as shown in the following formula:

[0098]

[0099] in, For grid cells Total damage variable, Let be the weight coefficient, and satisfy... .

[0100] In this embodiment, , Please refer to Figure 4: The multi-mechanism damage evaluation data for the five grid cells of the area to be identified is shown in Table 5 below:

[0101] Table 5: Multi-mechanism damage data for mesh cells

[0102] This step comprehensively considers three damage mechanisms that may occur simultaneously or sequentially under fire conditions: creep, plasticity, and fatigue, rather than a single plasticity damage criterion. The creep effects on steel structures at high temperatures and the fatigue effects under cyclic loading cannot be ignored. Each damage variable has a clear physical definition and calculation path, determined through weighting coefficients. Based on material properties and engineering experience, the contribution of different damage mechanisms to the total damage can be adjusted; the complex mechanical response can be quantified into an intuitive damage index that can be used for safety assessment, realizing the evaluation from simulation.

[0103] S5: Set a dynamic threshold for the total damage variable of the region segment, set filtering conditions for the total damage variable of all grid cells in the region segment, obtain the total damage variable of the region segment, and complete the evaluation of all regions segment based on the matching results with the threshold interval.

[0104] In this embodiment, for each region segment, the maximum value of the total damage variable in all its grid cells is selected and calibrated as the total damage variable of that region segment, and a preset dynamic threshold for the total damage variable of the region segment is set.

[0105]

[0106]

[0107] in, This is the lower limit of the damage threshold. This represents the upper limit of the damage threshold. This is an empirical coefficient. For yield strength, The modulus of elasticity is used; when the total damage variable is less than the lower limit of the damage threshold, the area to be evaluated is safe; when the total damage variable is greater than the lower limit of the damage threshold but less than the upper limit of the damage threshold, the area to be evaluated needs to be monitored regularly; when the total damage variable is greater than the upper limit of the damage threshold, the area needs to be inspected and reinforced.

[0108] In this embodiment, a filtering condition is set for the total damage variable of all grid cells in the region segment. The filtering condition is: the maximum value of the total damage variable of the grid cells is taken as the total damage variable of the region segment, that is... Greater than It needs to be inspected and reinforced;

[0109] Traverse all grid cells within a region The maximum value is taken as the representative damage value for that area; based on project experience and specifications, an empirical coefficient is determined. ; Utilizing the materials in this section and Calculate the dynamic threshold; It is the theoretical value of strain when a material yields. It is a dimensionless quantity that reflects the maximum elastic deformation capacity that a material can withstand before failure. Using this as a benchmark to set the damage threshold means linking damage to the material's inherent deformation capacity. This threshold can automatically adapt to steels of different strengths and stiffnesses, making the evaluation criteria more versatile and accurate.

[0110] Referring to Figure 5, the present invention also provides a numerical simulation system for fires in the power compartments of urban integrated utility tunnels, used to execute any of the above-mentioned numerical simulation methods for fires in the power compartments of urban integrated utility tunnels, including:

[0111] The structural discretization preprocessing module is used to construct a three-dimensional physical model of the power compartment in the utility tunnel and simultaneously obtain the material parameters of all steel structures within the utility tunnel. It divides the three-dimensional physical model of the power compartment into sequentially adjacent regions, performs meshing on all regions, and obtains the structural mesh model of each region.

[0112] Fire dynamics simulation module: used for structural mesh models based on regional segments, setting fire source locations according to actual risk points in the power compartment, establishing a spatiotemporal evolution model of the fire temperature field at the current fire source location, running the spatiotemporal evolution model of the fire temperature field, and obtaining air temperature field distribution data;

[0113] Thermal-structural coupling response module: used to map air temperature field distribution data to the structural mesh model of each region to obtain the structural temperature field, perform transient thermal-structural coupling analysis based on the structural temperature field, and obtain strain field data and thermal stress field data of the structural mesh model of each region.

[0114] Multi-mechanism damage quantification module: Used to obtain structural damage data of each grid cell in the structural grid model of the region segment based on strain field data and thermal stress field data of the structural grid model of the region segment, and to define the total damage variable of each grid cell through multi-mechanism damage;

[0115] Dynamic safety evaluation module: This module is used to preset dynamic thresholds for the total damage variable of a region segment, set filtering conditions for the total damage variable of all grid cells in the region segment, obtain the total damage variable of the region segment, and complete the evaluation of all regions segment based on the matching results with the threshold interval.

[0116] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention realizes a full-process simulation from fire dynamics to structural damage assessment, covering the entire process of fire impact, providing accurate fire risk assessment and early warning for utility tunnel power compartments, and overcoming the limitations of traditional methods that rely on physical experiments or simplified models; by comprehensively considering a multi-mechanism damage model that integrates creep, plasticity, and fatigue damage, the accuracy of the assessment is significantly improved, and it can comprehensively reflect the complex damage state of steel structures under fire conditions, providing a scientific basis for the safety assessment of utility tunnel power compartments; the safety assessment method based on setting dynamic thresholds according to material parameters enables the system to adapt to the assessment needs of different utility tunnel structures, improving the applicability and reliability of the assessment results; the system modules are clearly divided, including five functional modules: structural discretization preprocessing, fire dynamics simulation, thermo-structural coupling response analysis, multi-mechanism damage quantification, and dynamic safety assessment, which facilitates technology integration and functional expansion, and improves the practicality and adaptability of the method.

[0117] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0118] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0119] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0120] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for fire numerical simulation of an urban utility tunnel power cabin, characterized in that, The specific steps include: S1: Construct a three-dimensional physical model of the power compartment in the utility tunnel and obtain the material parameters of all steel structures in the utility tunnel. Divide the three-dimensional physical model of the power compartment into sequentially adjacent regions, mesh all regions, and obtain the structural mesh model of each region. S2: Based on the structural grid model of the regional segment, the fire source location is set according to the actual risk points of the power compartment, and a fire temperature field spatiotemporal evolution model is established at the current fire source location. The fire temperature field spatiotemporal evolution model is run to obtain air temperature field distribution data. S3: Map the air temperature field distribution data to the structural mesh model of each region to obtain the structural temperature field, and perform transient thermal-structural coupling analysis based on the structural temperature field to obtain the strain field data and thermal stress field data of the structural mesh model of each region. S4: Based on the strain field data and thermal stress field data of the structural mesh model of the region segment, obtain the structural damage data of each mesh unit in the structural mesh model of the region segment, and define the total damage variable of each mesh unit through multi-mechanism damage; S5: Set a dynamic threshold for the total damage variable of the region segment, set filtering conditions for the total damage variable of all grid cells in the region segment, obtain the total damage variable of the region segment, and complete the evaluation of all regions segment based on the matching results with the threshold interval. 2.The method according to claim 1, wherein: The three-dimensional physical model of the utility tunnel power compartment is constructed based on the geometric parameters of the utility tunnel power compartment, including: tunnel length, cross-sectional dimensions, wall panel thickness, connectors, and support layout. The model is divided into sequentially adjacent equal-length segments along the length direction, with each segment being an independent analysis unit. Each segment is separately meshed using a structured mesh. The output structured mesh model of each segment includes: the center coordinates of each mesh unit and the material parameters of the steel structure of the mesh unit. The material parameters of the steel structure at the center of the mesh unit include: elastic modulus, Poisson's ratio, density, coefficient of thermal expansion, thermal conductivity, specific heat capacity, yield strength, fracture strain value, creep damage friction reference stress, and fatigue SN curve.

3. The method according to claim 2, wherein the method is characterized by: Based on the regional segment structure grid model, and according to the actual risk points in the power compartment, different fire source locations are set. For different fire source locations, a spatiotemporal evolution model of the fire temperature field is established through the fire heat release rate. A non-uniform dynamic temperature rise model is used to describe the temperature change with time and space to obtain the air temperature field. The formula is as follows: wherein For the first A grid cell temperature at the time, 1st a grid cell center coordinate, For the initial temperature of the pipe gallery power cabin, for the maximum temperature rise of the fire, for the time constant; It is a spatial distribution function; wherein For the fire source coordinates, The diameter is determined by the heat effect of the fire source.

4. The method according to claim 3, wherein the method is characterized by: A spatiotemporal evolution model of the fire temperature field was established for different fire source locations based on the fire heat release rate, where the fire heat release rate adopted... The square fire growth model, the formula is as follows: wherein, for heat release rate, It is the fire growth coefficient.

5. The method according to claim 3, wherein the method is characterized by: The structural temperature field is obtained by mapping air temperature field distribution data onto the structural mesh model of each region using interpolation methods. Specific steps include: solving the heat conduction equation to obtain the change in heat energy stored per unit time in the mesh cells obtained from the heat conduction equation; combining this with the initial temperature of the utility tunnel's power compartment, calculating the internal temperature distribution of the steel structure, and constructing the structural temperature field; the heat conduction equation is solved as follows: wherein, for grid cells the amount of change in thermal energy, for grid cells density of the steel structure, for grid cells Specific heat capacity of steel structure, for grid cells the thermal conductivity of the steel structure of the for the Laplacian, for air temperature field The gradient.

6. The method according to claim 5, wherein the method is characterized by: Transient thermo-structural coupling analysis was performed using the finite element method based on the structural temperature field to obtain strain field data and thermal stress field data for each region of the structural mesh model. The strain field data and thermal stress field data include: the total strain tensor, plastic stress tensor, and thermal strain tensor of the mesh elements. Using the obtained total strain tensor, plastic stress tensor, and thermal strain tensor of the mesh elements, the plastic stress tensor and plastic strain tensor of the mesh elements were obtained. Specifically, the thermal strain tensor of the mesh element was obtained by multiplying the thermal expansion coefficient of the steel structure by the maximum change in structural temperature caused by the maximum temperature rise of the mesh element during a fire, as reflected by the structural temperature field. The plastic strain tensor of the mesh element was obtained by the difference between the total strain tensor and the thermal strain tensor of the mesh element. The plastic stress tensor of the mesh element was obtained by multiplying the plastic strain tensor by the elasticity matrix.

7. The method according to claim 6, wherein the method is characterized by: The structure damage data of each grid unit in the structure grid model of the regional segment includes creep damage, plastic damage and fatigue damage. The von Mises stress is obtained by solving the plastic stress tensor of the grid unit The creep damage calculation formula is as follows: wherein for grid cells creep damage, for grid cells creep damage reference stress, The creep stress index is given by the following formula for calculating plastic damage: wherein, for grid cells plastic damage, for grid cells The fracture strain value; the fatigue damage calculation formula is as follows: wherein for grid cells fatigue damage, the total number of cycles for different stress amplitudes, for grid cells corresponding forces The time history is used to perform rainflow counting to obtain the number of cycles at a given stress amplitude; For the fatigue S-N curve of the steel structural material parameter, the corresponding 1st The number of cycles for each stress amplitude; the total damage variable for each mesh element is defined using multi-mechanism damage, as shown in the following formula: wherein, for grid cells total damage variable of the patient, where w is a weight coefficient, and satisfies 。 8. The method according to claim 7, wherein the method is characterized by: For each region segment, the maximum value of the total damage variable across all its grid cells is selected and defined as the total damage variable for that region segment. A preset dynamic threshold for the total damage variable of the region segment is also defined. ； ； wherein, lower limit of the damage threshold, for the upper damage threshold, for the empirical coefficient, for the yield strength, The modulus of elasticity is used; when the total damage variable is less than the lower limit of the damage threshold, the area to be evaluated is safe; when the total damage variable is greater than the lower limit of the damage threshold but less than the upper limit of the damage threshold, the area to be evaluated needs to be monitored regularly; when the total damage variable is greater than the upper limit of the damage threshold, the area needs to be inspected and reinforced.

9. A utility tunnel power vault fire numerical simulation system for urban utility tunnels, characterized in that: A numerical simulation system for fires in the power compartment of an urban integrated utility tunnel is used to execute the numerical simulation method for fires in the power compartment of an urban integrated utility tunnel as described in any one of claims 1-8, comprising: The structural discretization preprocessing module is used to construct a three-dimensional physical model of the power compartment in the utility tunnel and simultaneously obtain the material parameters of all steel structures within the utility tunnel. It divides the three-dimensional physical model of the power compartment into sequentially adjacent regions, performs meshing on all regions, and obtains the structural mesh model of each region. Fire dynamics simulation module: used for structural mesh models based on regional segments, setting fire source locations according to actual risk points in the power compartment, establishing a spatiotemporal evolution model of the fire temperature field at the current fire source location, running the spatiotemporal evolution model of the fire temperature field, and obtaining air temperature field distribution data; Thermal-structural coupling response module: used to map air temperature field distribution data to the structural mesh model of each region to obtain the structural temperature field, perform transient thermal-structural coupling analysis based on the structural temperature field, and obtain strain field data and thermal stress field data of the structural mesh model of each region. Multi-mechanism damage quantification module: Used to obtain structural damage data of each grid cell in the structural grid model of the region segment based on strain field data and thermal stress field data of the structural grid model of the region segment, and to define the total damage variable of each grid cell through multi-mechanism damage; The dynamic security evaluation module is used for presetting a dynamic threshold of total damage variable of a region segment, setting a screening condition for the total damage variable of all grid units of the region segment, obtaining the total damage variable of the region segment, and completing evaluation of all region segments based on a matching result with the threshold interval.

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