Method for predicting the spatiotemporal distribution of temperature field in local fires in tall, spacious wooden structures

Abstract

This invention discloses a method for predicting the spatiotemporal distribution of temperature field in localized fires in tall, spacious wooden structures. The method includes: dividing the main affected area of ​​hot smoke from a localized fire in a tall, spacious wooden structure into three regions: a plume region, an impact region, and a ceiling jet region; establishing temperature prediction models for the plume region, impact region, and ceiling jet region under localized fire conditions in tall, spacious wooden structures; establishing a time-correlation function for the transient stage influence of the temperature field; using the established time-correlation function to correct the steady-state temperature field, obtaining a spatiotemporal temperature field prediction model for the entire fire development process; and predicting the spatiotemporal distribution of the temperature field in localized fires in tall, spacious wooden structures based on the obtained spatiotemporal temperature field prediction model for the entire fire development process. This invention aims to provide a reference and evaluation method for predicting the fire temperature field and its fire safety design in tall, spacious wooden structures.

Description

Technical Field

[0001] This invention belongs to the field of building fire safety, and in particular relates to a predictive model for the spatiotemporal distribution of local fire temperature field in protected tall wooden structures. Background Technology

[0002] In recent years, with the further development of new engineered wood (such as laminated veneer timber, laminated glulam, and cross-laminated timber), heavy timber structures, represented by engineered wood, have seen rapid and widespread application. This has also greatly promoted the development of modern timber structures towards high-rise and super high-rise buildings, large spaces, and long spans. Tall, large-space timber structures (such as large stadiums, swimming pools, and exhibition halls) are highly favored due to their environmental friendliness and ability to provide vast usable spaces. However, due to the devastating impact of fire, the construction of tall, large-space timber structures was prohibited for a long period in the late 19th century, resulting in very limited research and basic understanding of their fire-prone characteristics. Tall, large-space timber structures are difficult to equip with effective fire-fighting facilities due to their height, are difficult to divide into fire compartments due to their large area, and have densely packed occupants, making evacuation difficult. Once a fire occurs, large amounts of toxic and hot smoke will be generated inside the space and spread rapidly throughout, posing a significant threat to the lives of those inside. Although novel fire design concepts, models, and performance-based fire protection designs proposed in recent years have made the development of fire safety for tall, large-scale spatial timber-framed buildings possible, research on their development and promotion is limited, the start was late, and data accumulation is significantly insufficient. This makes it difficult to support the development of standards and specifications and to guide safe application in engineering projects.

[0003] Compared to fires in small compartments, the temperature distribution in fires in tall, open-air timber-framed buildings is an extremely complex transient process. The large spatial area and high ceilings of these buildings result in lower smoke temperatures, ample airflow, complete combustion, and significant temperature gradients. Furthermore, the uncertainty of ventilation opening locations and the randomness of airflow make flame propagation unpredictable. Therefore, it is difficult to theoretically describe the time-varying temperature field of fires in tall, open-air timber-framed buildings. Based on published research, three methods exist for establishing temperature field models for fires in tall, open-air buildings: (i) Real-world fire testing: This method can describe a more realistic fire development process, but it is difficult to implement due to the large investment of manpower, resources, and funds, and the test results are only applicable to the tested structure, exhibiting significant limitations; (ii) Multi-region model-based theoretical methods: This method is mainly suitable for predicting the initial development stage of a fire; as the fire enters a stable phase, the accuracy of temperature field prediction decreases. In addition, this method is more often used to establish large-space spread fire models; (iii) Field model theory method (numerical simulation): Numerical simulation method can capture the entire combustion process and accurately calculate the spatiotemporal temperature field of tall buildings, but the uncertainty of input parameter values ​​and the variability of material properties lead to uncertain prediction results. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method for predicting the spatiotemporal distribution of temperature field in local fires in tall, spacious wooden structures more accurately.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0006] This invention first provides a method for predicting the spatiotemporal distribution of temperature field in localized fires in protected tall, open-air wooden structures, including:

[0007] The main affected area of ​​local fires in tall, spacious wooden structures is divided into three zones: the plume zone, the impact zone, and the ceiling jet zone.

[0008] Establish temperature prediction models for the plume zone, impact zone, and roof jet zone of tall, spacious wooden structures under localized fire conditions.

[0009] Establish a time correlation function for the transient effects of the temperature field; use the established time correlation function to correct the steady-state temperature field, and obtain a spatiotemporal temperature field prediction model for the entire fire development process;

[0010] Based on the obtained spatiotemporal temperature field prediction model of the entire fire development process, the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures is predicted.

[0011] This invention also provides a device for predicting the spatiotemporal distribution of temperature field in localized fires in tall, spacious wooden structures, comprising:

[0012] One or more processors;

[0013] Memory, used to store one or more programs;

[0014] When the one or more programs are executed by the one or more processors, the one or more processors implement the above-described method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures.

[0015] The present invention also provides a storage medium storing a computer program that, when executed by a processor, implements the method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures as described above.

[0016] Compared with the prior art, the beneficial effects of the present invention are:

[0017] This invention divides the main affected area of ​​hot smoke from fires in tall, spacious wooden structures into three regions: the plume zone, the impact zone, and the ceiling jet zone. By analyzing the distribution law of the temperature field and considering the influence of key factors, a spatiotemporal distribution model for the non-uniform temperature field in localized fires in tall, spacious wooden structures is proposed. Main advantages: (1) Consideration of key factors: This model comprehensively considers the influence of key factors such as space size, heat release rate, and fire growth type on the temperature field, enabling more accurate prediction of the spatiotemporal distribution of the non-uniform temperature field in any fire scenario and space size under localized fires in tall, spacious wooden structures; (2) Guidance for the layout of fire detectors and sprinkler systems: This model can predict the temperature distribution at any location in space, providing guidance and optimization suggestions for the installation and layout of fire detectors and sprinkler systems. This helps ensure that detectors can quickly detect the fire location and prompt the sprinkler system to respond rapidly when a fire occurs; (3) Flashover determination and prediction: This model can predict the highest temperature at the ceiling of the structure. Through this prediction result, it is possible to determine whether flashover has occurred and the conditions for its occurrence. Therefore, this model can be used to control flashover by controlling fire load, and to predict the induction time of flashover by using the highest temperature value at the ceiling. These advantages make this model valuable for predicting the spatiotemporal distribution of temperature fields in fires in tall, spacious wooden structures, guiding the placement of fire detectors and sprinkler systems, and identifying and predicting flashover. Attached Figure Description

[0018] Figure 1 A FDS model of a tall, spacious wooden structure building;

[0019] Figure 2A schematic diagram showing the division of hot smoke zones and temperature distribution in a fire in a tall, spacious wooden structure building.

[0020] Figure 3 The influence of different spatial areas on the temperature distribution along the centerline of the plume region (Z1) with a fixed spatial height;

[0021] Figure 4 For a given spatial area, the influence of different spatial heights on the temperature distribution along the centerline of the plume region (Z1);

[0022] Figure 5 Comparison of predicted and FDS simulated values ​​for the centerline temperature of the fire plume zone (Z1) in tall, spacious wooden structures;

[0023] Figure 6 The temperature distribution pattern in the impact zone (Z2);

[0024] Figure 7 For a given spatial height, the attenuation ratio curves of the ceiling jet region (Z3) corresponding to different spatial areas are shown.

[0025] Figure 8 For a given spatial area, the attenuation ratio curves of the ceiling jet zone (Z3) corresponding to different spatial heights are shown.

[0026] Figure 9 Comparison of model predictions and FDS simulations for the fire-prone roof jet zone (Z3) of tall, spacious wooden structures;

[0027] Figure 10 The effect of spatial area on the β value when the spatial height is constant;

[0028] Figure 11 The effect of spatial height on the β value for a given spatial area;

[0029] Figure 12 The influence of fire growth type on β value for a given fire source power;

[0030] Figure 13 The effect of fire source power on β value for a given growth type;

[0031] Figure 14 Comparison of predicted and FDS simulated temperatures in the roof jet zone (Z3) of a fire in a tall, spacious wooden building. Detailed Implementation

[0032] The present invention will now be described in detail with reference to the accompanying drawings:

[0033] This embodiment provides a method for predicting the spatiotemporal distribution of temperature field in a local fire in a tall, spacious wooden structure building, including the following steps:

[0034] Step 1: Divide the main affected area of ​​a localized fire in a tall, spacious wooden structure into three zones: plume zone Z1, impact zone Z2, and ceiling jet zone Z3; see [link / reference] Figure 2 The temperature at the centerline of the plume zone Z1 decreases continuously with increasing distance from the fire source, then remains constant in the impact zone Z2, and the temperature in the roof jet zone Z3 decreases continuously from the centerline of the fire source outwards.

[0035] Step 2: Establish a Z1 temperature prediction model for the plume zone of tall, spacious wooden structures under localized fire conditions;

[0036] Step 3: Establish a Z2 temperature prediction model for the impact zone of tall, spacious wooden structures under localized fires;

[0037] Step 4: Establish a Z3 temperature prediction model for the roof jet zone of tall, spacious wooden structures under localized fire conditions;

[0038] Step 5: Establish the time correlation function of the transient stage of the temperature field, and use this function to correct the steady-state temperature field to obtain the spatiotemporal prediction model of the temperature field for the entire fire development process.

[0039] This invention utilizes FDS LES technology to simulate hundreds of scenarios considering variables such as building height, space area, heat release rate of the fire source, and fire growth type. Six levels were set for space height, space area, and heat release rate, and four levels were set for fire growth type. Combining these variables resulted in 864 simulation scenarios, as shown in Table 1.

[0040] Table 1 Summary of Simulated Operating Condition Parameters

[0041]

[0042] Combination Figure 1 The tall, open-plan wooden structure features 1500mm thick wooden wall panels on all four sides and a roof, with the inner walls covered by two layers of 12mm thick fire-resistant gypsum board. The floor is insulated, meaning no heat flows through it. Fires in tall, open-plan buildings are typically fuel-controlled fires. Therefore, a ventilation opening, one-third of the wall height and half the wall width, is installed at the bottom center of each wall to ensure that all fire scenarios are fuel-controlled. Figure 2-9 As shown. All vents are designed to open naturally, exhausting fumes via pressure differential. The density of the wooden walls is 640 kg / m³. 3 The thermal conductivity is 0.14 W / m·K, and the specific heat capacity is 2.85 kJ / kg·K. The density of the refractory gypsum board is 900 kg / m³. 3The thermal conductivity is 0.25 W / m·K, and the specific heat capacity is 1.45 kJ / kg·K. The square heat source is located in the center of the ground, and the heat release rate per unit area is set at 500 kW / m². 2 The initial values ​​for air temperature and pressure inside the building are set to T0 = 20℃ and P0 = 1 bar, respectively.

[0043] Step 1 is as follows:

[0044] Combination Figure 2 This invention, based on fluid, radiation, and convection theories, analyzes the movement patterns of hot smoke and divides the spatial temperature field into three zones: a plume zone (Z1), an impact zone (Z2), and a ceiling jet zone (Z3). In the plume zone (Z1), the temperature at the plume's centerline gradually decreases with increasing distance from the fire source. The interaction between the hot smoke and the sidewalls of tall, open-air buildings is minimal, meaning convective heat loss and heat conduction through the boundaries are insignificant. In the impact zone (Z2), the direction of movement of the hot smoke changes significantly after impacting the ceiling. In the ceiling jet zone (Z3), the hot smoke, almost parallel to the ceiling, rotates radially and forms a stratified flow below the ceiling, with the temperature gradually decreasing from the center outwards. Due to the obstruction of the wall surfaces, the hot smoke flows back and gradually accumulates and sinks, causing the temperature of the hot smoke near the ceiling to first increase and then decrease vertically. Therefore, it can be seen that the temperature field in a fire in a tall, open-air wooden structure building mainly consists of the temperature distribution in these three zones: the plume zone (Z1), the impact zone (Z2), and the ceiling jet zone (Z3). Therefore, the construction of the fire temperature field of tall, spacious wooden structures is essentially the construction of the temperature fields of these three regions separately.

[0045] Step 2 is as follows:

[0046] Combination Figure 3 and Figure 4 The influence of spatial parameters on the temperature distribution curve of the plume centerline in plume region Z1 was analyzed. FDS simulations showed that, under the same fire growth type and heat release rate, differences in spatial area and height had minimal impact on the temperature distribution of the plume centerline in region Z1, while the heat release rate of the fire source played a dominant role. Based on the classic axisymmetric plume McCaffrey model, a parameter fitting method was used to adjust the parameters, and a temperature model of the plume centerline in region Z1 was constructed for different heat release rates.

[0047]

[0048] Among them, T s T0 is the temperature at the centerline of the plume at a vertical distance z from the fire source (°C); Q is the heat release rate (kW); z is the vertical height from the fire source (m); k and η are dimensionless parameters, and their values ​​are shown in Table 2.

[0049] Table 2 shows the values ​​of dimensionless parameters k and η corresponding to different heat release rates.

[0050]

[0051] According to the classical axisymmetric plume theory, the cross-sectional temperature distribution at any height of the plume region Z1 is similar to that of an inverted axisymmetric cone, and its temperature distribution is generally assumed to be Gaussian. Based on the similarity principle of the plume model, the temperature distribution law of the cross-section of the plume region Z1 can be described as follows:

[0052]

[0053] Where, k s T is a dimensionless parameter. s ′ represents the cross-sectional temperature (°C) of the plume region (Z1); Pr is the Prandtl number of the air, with a value of 0.72; r is the horizontal distance (m) from a point on the cross-section of the plume region (Z1) to the centerline of the fire source; b is the half-width of the plume region, b = d(z + z0) / 2z0; d is the diameter of the fire source (m); z0 is the distance (m) between the virtual fire source and the actual fire source, z0 = 1.02d - 0.00524Q 2 / 5 .

[0054] Substituting equation (2) into equation (1), we can obtain the cross-sectional temperature of the plume region (Z1):

[0055]

[0056] Combination Figure 5 The temperature of the centerline of the plume zone Z1 corresponding to different heat release rate values ​​calculated by formula (3) is compared with the simulated value of FDS. The analysis shows that the predicted value and the simulated value are in good agreement. The theoretical prediction model established by this invention can accurately reflect the temperature distribution law of the centerline of the plume zone Z1 in fires in tall, spacious wooden structures.

[0057] Step 3 specifically involves:

[0058] Combination Figure 6 The temperature variation trend of the centerline of the plume zone Z1 was consistent under all simulated conditions. That is, with increasing vertical distance from the fire source, the centerline temperature first decreased rapidly and then remained constant. It can be seen that the centerline temperature rapidly decreases from the fire source towards the ceiling, and when it reaches the vicinity of the ceiling, the temperature approximately remains constant. Further analysis revealed that at the same spatial height, the range of constant centerline temperatures corresponding to different heat release rates is basically the same. In other words, the starting point of the constant temperature region is determined at a given spatial height and is independent of the magnitude of the heat release rate.

[0059] If the height of the plume region Z1 is defined as γH, then the height of the impact region Z2 is (1-γ)H. Then, by analyzing and summarizing the temperature data of the centerline of the plume region Z1 under all simulated conditions, the range of the impact region Z2 can be defined as 0.80H≤z≤H (i.e., γ=0.8). Thus, the centerline temperature of the impact region Z2 can be determined by equation (4):

[0060]

[0061] Step 4 specifically involves:

[0062] Combination Figure 7 and Figure 8 This paper analyzes the influence of spatial parameters on the temperature distribution curve of the roof jet region Z3. FDS simulations show that the temperature in the roof jet region Z3 gradually decreases from the center line outwards, and the spatial area and height have a significant impact on the temperature distribution. The construction of the temperature field model for the roof jet region Z3 should consider the influence of spatial parameters, and its temperature decay rate curve varies with different spatial areas and heights. Analysis of the temperature decay rate curve reveals that the size of the fire source area affects the temperature decay rate near the center line of the fire source in the roof jet region Z3. Temperature decay is slower within the fire source radius and faster outside the fire source radius. Therefore, this invention constructs temperature decay rate models for both within and outside the fire source radius.

[0063] On the one hand, regarding the area within the Z3 fire source radius of the ceiling jet zone, the temperature decay rate is described by an exponential function:

[0064]

[0065] Where, k c1 denoted as the temperature decay rate within the radius of the fire source; r is the horizontal distance (m) from a point in the Z3 jet zone of the ceiling to the centerline. It is a shape factor that is related to the area and height of a space.

[0066] Data fitting was performed on the FDS simulation results to obtain The values ​​are shown in Table 3:

[0067] Table 3. Corresponding to different spatial heights The value of

[0068]

[0069] Passing The value analysis shows that the spatial area has an effect on The value of has almost no effect. The value of is mainly determined by the spatial height. The temperature attenuation rate coefficient k within the radius of the fire source. c1It can be approximated as:

[0070] k c1 =exp(-7.16(r / H)) 2 (6)

[0071] On the other hand, for the area outside the Z3 fire source radius in the ceiling jet zone, the temperature decay rate curve can be described by the following exponential function:

[0072] k c2 =ξ+(1-ξ)exp(-λr) (7)

[0073] Where, k c2 ξ is the temperature decay rate outside the radius of the fire source; r is the horizontal distance (m) from a point in the roof jet zone Z3 to the center line; ξ and λ are shape coefficients related to the area and height of the space.

[0074] Similarly, the λ values ​​were obtained by fitting the FDS simulation results for different spatial dimensions, as shown in Table 4:

[0075] Table 4. Values ​​of λ for different spatial parameters

[0076]

[0077] The fitted value λ is less affected by the spatial area. Therefore, the λ values ​​for different areas at the same spatial height are averaged, and further fitted to obtain the formula for calculating λ that is only affected by the spatial height:

[0078] λ=0.28-0.008H (8)

[0079] The ξ values ​​were obtained by fitting the FDS simulation results for different spatial dimensions, as shown in Table 5:

[0080] Table 5. Values ​​of ξ for different spatial parameters

[0081]

[0082] FDS simulation results show that the value of ξ mainly depends on the spatial area and height. Through further fitting, the shape coefficient ξ can be approximated as:

[0083]

[0084] Thus, by multiplying equations (6) and (7) by equation (4), we can obtain the temperature distribution model of the roof jet region Z3:

[0085]

[0086] Combination Figure 9The predicted values ​​of the temperature distribution in the Z3 area of ​​the ceiling jet were compared with the simulation results of the FDS. The comparison showed that the model predictions and FDS simulations were in good agreement, indicating that the model can effectively predict the temperature distribution in the Z3 area of ​​the ceiling jet during the steady-state stage of a fire in a tall, spacious wooden structure building.

[0087] Step 5 specifically involves:

[0088] The aforementioned steady-state temperature field prediction model can only predict the temperature distribution during the steady-state stage (or fully developed stage) of a fire, which is insufficient to describe the entire process of actual fire temperature field development. In actual fire temperature fields, especially during the transient stage (or fire growth stage), the temperature field changes continuously over time. Since the evolution of the transient temperature field is related to fire escape time, flashover induction time, fire detection and alarm time, and the activation time of fire sprinkler systems and smoke extraction systems, accurately predicting the spatial temperature field evolution during the transient stage of a fire is crucial. For fires in tall, large-scale buildings, since the hot smoke contains most of the convective heat released by the fire source, the initial smoke motion characteristics directly affect the evolution of the spatial temperature field during the transient stage. Based on the initial smoke motion characteristics, the evolution of the spatial temperature field during the transient stage may be influenced by the fire growth type, heat release rate, spatial size, and spatial location.

[0089] For fires in tall, large-scale spatial buildings, the temperature-time curve at any point in the space can be obtained by correcting the steady-state temperature field using a time-dependent exponential function. The β value of the exponential function reflects the lag in temperature growth at locations outside the fire source. Therefore, different β values ​​can be used to describe the temperature-time curve trajectory at a specific point in any fire scenario.

[0090] f(t)=α-0.8exp(-βt)-0.2exp(-0.1βt) (11)

[0091] Where t is the duration of the fire (s), α is approximately 1, and β is the time lag coefficient that reflects the temperature growth rate.

[0092] The values ​​of α and β were obtained by fitting the temperature-time curves of each point in the structural space under all simulated conditions using the exponential function (11). Preliminary analysis shows that the value of α is only related to the fire growth type and the heat release rate, as shown in Table 6:

[0093] Table 6. α values ​​corresponding to different fire growth types and heat release rates.

[0094]

[0095] Combination Figure 10 and Figure 11Analysis shows that the differences in spatial area and height have almost no effect on the value of β, and the influence of spatial area and height can be ignored in determining the value of β.

[0096] Combination Figure 12 and Figure 13 The relationship between the β value and the distance from the fire source centerline is presented for different fire growth types (slow fire, medium fire, fast fire, and extremely fast fire). As the distance from the fire source centerline increases, the β value initially decreases rapidly and then stabilizes. Specifically, the faster the fire grows, the more significant the decrease in β value near the fire source centerline. Furthermore, the lower the heat release rate, the more significant the difference in β value near the fire source centerline. At the same distance from the fire source centerline, the β value gradually decreases with increasing heat release rate.

[0097] The growth phase of the heat release rate curve is represented by the t-phase of an unsteady-state fire model. 2 The development model assumes that the heat release rate of a fire is proportional to the square of time. Therefore, the expression for the heat release rate of a fire is:

[0098]

[0099] In the formula, t is the fire duration (s), and a is the fire growth coefficient (kW / s). 2 ), Q max denoted as , where b is the maximum heat release rate of the fire (MW), and b is the rate of decay of the heat release rate during the decay phase (MW / s).

[0100] The NFPA 240M "Standard of Smoke and Heat Venting" compiled by the National Fire Protection Association (NFPA) summarizes the fire growth coefficients for typical combustible materials and building types, and classifies fires into slow-moving, medium-moving, fast-moving, and extremely fast-moving fires based on the magnitude of the fire growth coefficient. Table 7 summarizes the fire growth coefficient 'a' for typical combustible materials and building types.

[0101] Table 7 Fire Growth Coefficient and Fire Types

[0102]

[0103] Note: t a The time (s) required for the fire heat release rate to reach 1 MW is given. Furthermore, differences in spatial area and height have almost no effect on the value of β, but are mainly influenced by the combined effects of fire growth type and heat release rate. Based on the FDS simulation results, a new parametric equation is established using parametric analysis, expressing the β value as a function of spatial location and key influencing factors (fire growth type and heat release rate):

[0104] β=mr n(13)

[0105] Where r is the horizontal distance (m) from a point in space to the centerline of the fire source; m and n are factors that depend on the fire growth type and heat release rate, as shown in Tables 8 and 9:

[0106] Table 8. Values ​​of m corresponding to different fire growth types and heat release rates.

[0107]

[0108] Table 9. Values ​​of n corresponding to different fire growth types and heat release rates.

[0109]

[0110] Multiplying the time-varying temperature correction function (11) by the temperature prediction formula (10) for the roof jet region Z3 of the steady-state temperature field, we can obtain the time-varying temperature prediction model for the roof jet region Z3 of tall, spacious wooden structures:

[0111]

[0112] Combination Figure 14 While maintaining a space area of ​​A = 1000m² 2 With a fixed space height H = 15m, the Z3 temperature rise curves of the ceiling jet zone for different fire growth types (slow fire and fast fire), heat release rates (Q = 2MW and 25MW), and centerline distances (r = 0m, 3m, 15m) predicted by equation (14) were compared with the FDS simulation results. The comparison results show that the model's predicted values ​​and the FDS simulation results are in good agreement at different distances from the fire source centerline, especially in the transient stage. Therefore, under suitable fire scenarios, the prediction model proposed in this invention can accurately predict the fire smoke temperature field under local fires in tall, spacious wooden structures.

[0113] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for predicting the spatiotemporal distribution of temperature field in a localized fire in a protected, tall, open-air wooden structure building, characterized in that, include: The main affected area of ​​local fires in tall, spacious wooden structures is divided into three zones: the plume zone, the impact zone, and the ceiling jet zone. Establish temperature prediction models for the plume zone, impact zone, and roof jet zone of tall, spacious wooden structures under localized fire conditions. Establish a time correlation function for the transient effects of the temperature field; use the established time correlation function to correct the steady-state temperature field, and obtain a spatiotemporal temperature field prediction model for the entire fire development process; Based on the obtained spatiotemporal temperature field prediction model of the entire fire development process, the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures is predicted. In the step of dividing the main affected area of ​​localized fire smoke in a tall, spacious wooden structure building into three zones—the plume zone, the impact zone, and the ceiling jet zone—the impact zone is located above the plume zone, and the ceiling jet zone is located on both sides of the impact zone; the height of the plume zone is [missing information]. γH The height of the impact zone is (1- γ ) H The width of the impact zone is d ( γH +z 0) / 2 z 0, where γ =0.8, where H is the internal height of the wooden structure. d The diameter of the fire source, z 0 represents the distance between the virtual fire source and the actual fire source. z 0 = 1.02 d -0.00524 Q 2 / 5 .

2. The method for predicting the spatiotemporal distribution of temperature field in local fires in tall, spacious wooden structures according to claim 1, characterized in that, In the steps of establishing temperature prediction models for the plume zone, impact zone, and roof jet zone of tall, spacious wooden structures under localized fires, the established temperature prediction model for the plume zone is as follows: in, T s ´ Temperature of the cross-section of the plume region; T 0 represents the indoor air temperature; Q denoted as heat release rate; z represents the vertical height from the fire source. k and η To be related to the heat release rate Q Relevant dimensionless parameters; r The horizontal distance from a point on the cross-section of the plume region to the centerline of the fire source; b The width of the feather region. b=d ( z+ z 0 ) / 2 z 0 , d The diameter of the fire source, z 0 represents the distance between the virtual fire source and the actual fire source. z 0 = 1.02 d -0.00524 Q 2 / 5 ; The established temperature prediction model for the impact zone is as follows: in, T i The centerline temperature of the impact zone; The established temperature prediction model for the roof jet zone is as follows: in, T c Temperature of the jet stream area in the ceiling; r The horizontal distance from a point in the roof jet zone to the centerline; ξ and λ It is a shape factor that is related to the area and height of a space.

3. The method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures according to claim 2, characterized in that, Dimensionless parameters k and η With heat release rate Q The correspondence is as follows: 。 4. The method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures according to claim 3, characterized in that, Shape factor λ and ξ They are respectively: Where A represents the area of ​​the space.

5. The method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures according to claim 3, characterized in that, A time correlation function is established to assess the transient effects of the temperature field. This function is then used to correct the steady-state temperature field, resulting in a spatiotemporal temperature field prediction model for the entire fire development process. This model includes: Establish the time-dependent function of the transient effects of the temperature field: in, f(t) This is a temperature correction function; t Duration of the fire; α This is a correction factor for the temperature amplitude; β To reflect the time lag factor of the temperature growth rate; Different fire growth types and heat release rates correspond to α value ； By correcting the steady-state temperature field using the established time correlation function, a spatiotemporal temperature field prediction model for the entire fire development process is obtained: in, T (r,t) t represents the temperature of the roof jet zone; r represents the horizontal distance to the center line of the fire source; and t represents the fire time.

6. The method for predicting the spatiotemporal distribution of temperature field in local fires in tall, spacious wooden structures according to claim 5, is characterized in that, Time lag coefficient reflecting the temperature growth rate β for: in, m and n It is a factor that depends on the fire growth type and the heat release rate.

7. The method for predicting the spatiotemporal distribution of temperature field in local fires in tall, spacious wooden structures according to claim 6, characterized in that, Factors dependent on fire growth type and heat release rate m and n The possible values ​​are as follows: Different fire growth types and heat release rates correspond to m The value of ； Different fire growth types and heat release rates correspond to n The value of 。 8. A device for predicting the spatiotemporal distribution of temperature field in a localized fire in a tall, spacious wooden structure building, characterized in that... include: One or more processors; Memory, used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures as described in any one of claims 1-7.

9. A storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for predicting the spatiotemporal distribution of local fire temperature field in tall, spacious wooden structures as described in any one of claims 1 to 7.

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