CN112800652B - Fire-resistant data determination method and device and electronic equipment - Google Patents
Fire-resistant data determination method and device and electronic equipment Download PDFInfo
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Abstract
The invention provides a method and a device for determining fire-resistant data and electronic equipment. The invention obtains the fire-resistant data of the floor by obtaining the preset floor model obtained by simulating the floor, determining the fire-resistant performance analysis model and solving the model, and has the advantages of simple operation and higher efficiency without manufacturing and experiment of floor samples. Furthermore, the invention does not need manual participation, and compared with a manual experiment mode, the invention can avoid the problem of inaccurate operation caused by manual participation and improve the accuracy of refractory data determination.
Description
Technical Field
The invention relates to the field of floor fire resistance research, in particular to a method and a device for determining fire resistance data and electronic equipment.
Background
With the continuous development of railway construction, more and more users ride rail transit vehicles, such as high-speed rail travel. In order to protect the travel safety of passengers, high-speed rails are required to have good fireproof performance. The floor on the high-speed rail is used as one of important fireproof partitions, and is very important for researching the fireproof performance of the floor.
In the study of the fire resistance of floors, fire resistance data of floors are generally obtained experimentally. Specifically, it is necessary to make a floor sample, then install a thermocouple on the floor sample, and burn the floor sample using a boiler, and obtain fire-resistant data through experimental data collected by the thermocouple during the combustion process. The above-described experimental procedure is complicated, making it inefficient to determine the fire resistance data of the floor.
Disclosure of Invention
In view of the above, the present invention provides a method and apparatus for determining fire resistance data, and an electronic device, so as to solve the problem that the efficiency of obtaining fire resistance data of a floor by an experimental method is low.
In order to solve the technical problems, the invention adopts the following technical scheme:
a method of determining refractory data for use in a processor, the method comprising:
acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model;
determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
and solving the fire resistance analysis model and the discretization result to obtain fire resistance data.
Optionally, determining a refractory performance analysis model corresponding to the preset floor model includes:
acquiring a preset heat transfer model;
acquiring experimental data of fire resistance of the floor;
and determining constraint conditions of the heat transfer model according to the floor fire resistance experimental data.
Optionally, determining the constraint condition of the heat transfer model according to the floor fire resistance experimental data comprises:
acquiring and determining thermal insulation constraint conditions of the heat transfer model according to thermal insulation boundary data in the floor fire resistance experimental data;
acquiring and determining a temperature boundary constraint condition of the heat transfer model according to temperature boundary data of a temperature node in the floor fire resistance experimental data;
and acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
Optionally, discretizing the preset floor model to obtain a discretization result, including:
and carrying out grid division processing on the preset floor model according to a preset grid division method to obtain a discretization result.
Optionally, solving the refractory performance analysis model and the discretized result to obtain refractory data, including:
and solving the refractory performance analysis model and the discretization result by using a preset solver to obtain refractory data.
Optionally, after performing a solving operation on the refractory performance analysis model and the discretized result, the method further includes:
obtaining a floor fire resistance experimental result;
and comparing the fire resistance data with the floor fire resistance experimental result to obtain a comparison result.
A refractory data determination device for use in a processor, the determination device comprising:
the floor model processing module is used for acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model;
the model determining module is used for determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
and the model solving module is used for carrying out solving operation on the refractory performance analysis model and the discretization result to obtain refractory data.
Optionally, the model determining module includes:
the model acquisition sub-module is used for acquiring a preset heat transfer model;
the test data acquisition sub-module is used for acquiring the floor fire resistance test data;
and the condition determining submodule is used for determining the constraint condition of the heat transfer model according to the floor fire resistance experimental data.
Optionally, the condition determining submodule includes:
the first determining unit is used for acquiring and determining the thermal insulation constraint condition of the heat transfer model according to the thermal insulation boundary data in the floor fire resistance experimental data;
the second determining unit is used for acquiring and determining the temperature boundary constraint condition of the heat transfer model according to the temperature boundary data of the temperature node in the floor fire resistance experimental data;
and the third determining unit is used for acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
An electronic device, comprising: a memory and a processor;
wherein the memory is used for storing programs;
the processor invokes the program and is configured to:
acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model;
determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
and solving the fire resistance analysis model and the discretization result to obtain fire resistance data.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a method and a device for determining fire-resistant data and electronic equipment. The invention obtains the fire-resistant data of the floor by obtaining the preset floor model obtained by simulating the floor, determining the fire-resistant performance analysis model and solving the model, and has the advantages of simple operation and higher efficiency without manufacturing and experiment of floor samples. Furthermore, the invention does not need manual participation, and compared with a manual experiment mode, the invention can avoid the problem of inaccurate operation caused by manual participation and improve the accuracy of refractory data determination.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic view of a prior art floor structure for a fire test;
FIG. 2 is a flow chart of a method for determining refractory data according to an embodiment of the present invention;
FIG. 3 is a schematic structural diagram of a preset floor model of a floor according to an embodiment of the present invention;
fig. 4 is a schematic view of a floor grid division scenario provided in an embodiment of the present invention;
FIG. 5 is a flow chart of another method for determining refractory data according to an embodiment of the present invention;
FIG. 6 is a schematic view of a boundary constraint provided by an embodiment of the present invention;
FIG. 7 is a convergence diagram showing the development of errors or time steps with the solving process in a nonlinear, transient or parametric solver according to an embodiment of the present invention;
FIG. 8 is a graph showing the comparison of the temperature change of the fire-receiving surface and the set standard temperature rise curve in the simulation provided by the embodiment of the invention;
FIG. 9 is a graph comparing the highest temperature curve and the average temperature curve of the back surface of the floor according to the embodiment of the invention;
FIG. 10 is a graph showing the temperature of the backfire face versus the constant temperature of 165 degrees Celsius provided by an embodiment of the present invention;
FIG. 11 is a schematic view of the temperature distribution inside the floor at several exemplary moments provided by embodiments of the present invention;
FIG. 12 is a graph of actual and standard temperature versus time provided by an embodiment of the present invention;
FIG. 13 is a graph showing the highest temperature of the backfire surface compared with the experimental value obtained by the experiment provided by the embodiment of the invention;
fig. 14 is a schematic structural view of a refractory data determining apparatus according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The consequences of a high-speed rail fire are very serious, while the fire resistance of floors, which are one of the important fire barriers, plays an important role in the development of the fire. A great deal of experimental study has been made on the structure of the high-speed railway floor at home, however, the inherent mechanism of the floor behavior in fire is still difficult to understand through these standard fire-resistant experiments.
Specifically, the process of the fire resistance experiment is as follows:
the floor sample is required to be manufactured, then a thermocouple is installed on the floor sample, the boiler is used for burning the floor sample, and the fire-resistant data is obtained through experimental data collected by the thermocouple in the burning process.
The whole process comprises the steps of manufacturing the floor sample, installing the thermocouple and burning the floor sample, and the process is complex, so that the efficiency of determining the fire-resistant data of the floor is low. In addition, in the experimental process, the experimental process is manually operated, and the problem of low accuracy of fire resistance data determination caused by manual operation errors is unavoidable. In addition, during the course of the experiment, the overall measurement data means that a large number of thermocouples are used and regularly arranged on the measurement face (refer specifically to fig. 1). Wherein thermocouple 1 represents a thermocouple measuring an average temperature, and thermocouple 2 represents a thermocouple measuring a highest temperature. In practice, thermocouples may be located at the quarter center position and at the center position of the floor sample.
However, as experiments are carried out, the plate is deformed and broken, the arrangement of thermocouples is seriously affected, and the conditions of falling, displacement and the like are generated. In addition, a large number of thermocouples can obviously enlarge gaps among layers, and greatly influence heat transfer among layers. The data collected by the thermocouple can be lost, or the collected data which is not in the original position can also cause lower accuracy of data collection, so that the accuracy of fire-resistant data determination is lower. In addition, in the experimental process, the situations of air leakage, fire bouncing and the like on the side surface of the actual experimental furnace exist, so that the accuracy of the experimental process is insufficient, and the accuracy of determining the fire-resistant data is lower.
In order to solve the problems of low accuracy and low efficiency, the inventor has found that if fire resistance data is obtained by an experimental method, the technical problems are inevitably encountered. If the floor model can be obtained in a simulation mode and is processed by using the controller or the processor, the whole process is realized by the controller or the processor, and the problems of low accuracy and low efficiency caused by experiments can be avoided without real experimental operation. In addition, the accuracy of the fire-resistant data obtained by the simulation mode in the invention can be verified by comparing the fire-resistant data obtained by the experiment with the fire-resistant data obtained by the simulation mode.
Specifically, on the basis of the above, the embodiment of the invention provides a method for determining refractory data, which is applied to a processor, and in addition, the method can also be a server, a controller and other devices.
Referring to fig. 2, the method of determining refractory data may include:
s11, acquiring a preset floor model of the floor obtained through simulation operation, and discretizing the preset floor model to obtain a discretization result.
In practical application, the preset floor model is a CAD model. Specifically, the simulation uses CAD software 1:1 to build a three-dimensional geometric model, and the specific structure for building the three-dimensional geometric model can be referred to as FIG. 3. After the three-dimensional geometric model is established, the established three-dimensional aggregate model is imported into COMSOL.
The model floor is 3 m long and 4m wide, and is respectively an aluminum profile bottom plate, a draining plate, a sound absorbing material, carbon fibers, a sound insulation felt, a composite plywood and rubber floor cloth from the bottom surface (fire receiving surface) to the top surface (back fire surface). The layers were closely adhered without gaps, and the thickness dimension parameters of each layer are shown in table 1.
Table 1 geometric dimensions of preset floor models
The material parameters of the different layers in the floor are referred to in table 2.
Table 2 material parameter table
All materials in table 2 are considered isotropic, i.e. the thermal conductivity values are equal in the x, y, z directions for any material.
In another implementation manner of the present invention, the process of performing discretization processing on the preset floor model to obtain a discretization result may include:
and carrying out grid division processing on the preset floor model according to a preset grid division method to obtain a discretization result.
In practical application, as the floor structure is relatively regular, the simulation divides the components through the COMSOL custom grid. According to the difference of the calculation precision. The smaller the cell size, the greater the number of cells, the higher the cell quality, and also means longer calculation time.
Because the floor structure is flat, the transverse temperature gradient is not obvious in the longitudinal temperature gradient, and therefore, the simulation adopts a free quadrilateral sweeping grid to refine correspondingly in different layers. This approach can improve computational efficiency while simplifying meshing. The resulting grid division is shown in fig. 4, and the basic grid data is shown in table 3. Wherein, the unit mass is dimensionless, the value is between 0 and 1, 1 represents a positive unit (such as a regular tetrahedron and a regular hexahedron), and 0 represents a degraded unit. The data in table 3 illustrates that the grid used in the present simulation is relatively flat, but such grid quality is acceptable because lateral heat transfer is not the focus of the simulation.
TABLE 3 grid quality
| Description of the invention | Value of |
| Minimum unit mass | 0.003783 |
| Average unit mass | 0.009251 |
| Hexahedral unit | 6800 |
| Quadrilateral unit | 3700 |
| Edge unit | 628 |
| |
32 |
S12, determining a fire resistance analysis model corresponding to the preset floor model.
In practical applications, the refractory performance analysis model includes a heat transfer model and constraints of the heat transfer model.
Specifically, referring to fig. 5, step S12 may include:
s21, acquiring a preset heat transfer model.
The COMSOL "solid heat transfer" interface is used for modeling conductive, convective, and radiative heat transfer. By default, the solid heat transfer interface is active in all computing domains. All functions of other domain types including fluid domains are also provided.
The temperature equation defined in the solid domain corresponds to a differential form of fourier's law and may contain heat generated by a heat source or the like.
The interface is simulated by numerically solving the following partial differential equation, and the heat transfer equation on the solid medium and the interface thereof is as follows:
the equation is derived from the thermal equilibrium equation. Wherein ρ is the material density (kg/m) 3 )、C p The specific heat capacity (J/kg) of the material is fixed, T is the absolute temperature (K) of the material, u is the translational velocity vector (m/s) of the material, q is the heat flow (W/square meter) entering the material through heat conduction, and q is the heat flow (W/square meter) r Is radiant heat flow (W/. Square meter), Q is heat generation (W) in the material, S is second-order Picola-Kirchhoff stress tensor (Pa), alpha is heat diffusion coefficient (1/K), and V is temperature gradient。
For steady state problems, the temperature does not change over time, and therefore, the term in the equation for the time derivative can be eliminated. The first term on the right above is thermoelastic damping, representing the thermoelastic effect in a solid:
wherein, the operator
Is the derivative of the substance.
The above formula 1 is a heat transfer model in the embodiment of the present invention, and the heat transfer model is a heat transfer model corresponding to the floor in the embodiment.
S22, obtaining experimental data of the fire resistance of the floor.
In practical applications, the floor fire resistance test data may include thermal insulation boundary data, temperature boundary data of temperature nodes, and open boundary data. These data are those found by the skilled artisan in the course of the experiment.
S23, determining constraint conditions of the heat transfer model according to the floor fire resistance experimental data.
Specifically, in the specific implementation process of step S23, the following steps may be included:
1) And acquiring and determining the thermal insulation constraint condition of the heat transfer model according to the thermal insulation boundary data in the floor fire resistance experimental data.
Specifically, in simulation, the side surface of the floor was plugged with a heat insulating material in the simulation, and the side wall of the model was set to be a heat insulating boundary condition, as shown in fig. 4 (1).
For a thermally insulating boundary, it is governed by the following equation:
-n·q＝0 (2)
equation (2) is a thermal insulation constraint of the heat transfer model in the embodiment of the present invention. Where n represents the surface normal vector and q is the surface heat flow. Equation (2) indicates that no heat flow flows out or in the surface. More intuitively, the normal temperature gradient at the boundary is zero. However, in order to achieve this, it is necessary to have the same temperature on both surfaces (the boundary of the calculation region and the bonding surface of the heat insulating cotton), and there is no heat transfer when there is no temperature difference. Substituting the heat transfer coefficient into solid heat transfer as a side boundary condition for iterative calculation.
2) And acquiring and determining the temperature boundary constraint condition of the heat transfer model according to the temperature boundary data of the temperature node in the floor fire resistance experimental data.
In particular, temperature nodes are often used to define temperature conditions at a location in a geometry, including temperature conditions at boundaries. The boundary condition is determined by the control equation t=t 0 And (3) representing. Wherein T is 0 The boundary temperature preset for the user can be a fixed value or an expression.
For the lower surface (fire surface) of the present model, the temperature thereof was considered to vary according to the standard temperature rise curve. Namely:
T 0 ＝345lg(8t+1)+T initiai (3)
wherein, formula 3 is a temperature boundary constraint condition of the heat transfer model in the embodiment of the invention. T (T) initial =25 ℃, t is the time unit in minutes (min).
3) And acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
In particular, for the upper surface of the mold (the backfire) an open boundary is provided, which boundary condition is typically used to simulate the heat flow on the open boundary. The heat flow will flow into or out of the boundary depending on the ambient temperature.
The upper surface of the floor in this simulation was exposed to air, and on this boundary was primarily air-to-board convective heat transfer cooling due to the low ambient temperature.
Further to transient simulation, it can be controlled by the following equation:
T＝T 0 when n.u < 0
-n.q=0, when n.u.gtoreq.0 (4)
Through the above steps, a constraint condition of a thermal insulation boundary (thermal insulation constraint condition), a constraint condition of a temperature boundary (temperature boundary constraint condition), and a constraint condition of an open boundary (open boundary constraint condition) are obtained. Specific boundaries may be seen in fig. 6.
And S13, solving the refractory performance analysis model and the discretization result to obtain refractory data.
In the actual use process, a preset solver, such as a COMSOL transient solver, is used for solving. This solver is used for the computational problem of domain variable variation over time. Among the heat transfer problems, it is used to calculate the heat transfer problem of temperature over time. And then the COMSOL transient solver can be used for solving the refractory performance analysis model and the discretization result to obtain refractory data. The fire resistance data in this embodiment may be floor surface temperature distribution data, temperature gradient inside the floor, and the like.
And in the process of solving and calculating, inputting the constructed geometric grid into a solid heat transfer physical field interface, setting the calculation time to be 30min, setting the iteration average step length to be 1min, and carrying out iteration solving by utilizing a Lagrange quadratic interpolation shape function to digitize a control equation. The convergence diagram of fig. 7 shows the progression of errors or time steps with the solution process in a nonlinear, transient or parametric solver. This graph shows the relationship of the inverse of the step size to the simulated time step, with the time step for a single iteration of the transient solver being longer as the inverse of the step size decreases. It can be seen that the simulation has converged to 0.1 by the time of the next 10 th time step, and the convergence speed is faster.
In this embodiment, the processor obtains a preset floor model of the floor obtained through simulation operation, discretizes the preset floor model to obtain a discretized result, and then determines a refractory performance analysis model corresponding to the preset floor model, so that the refractory performance analysis model and the discretized result can be solved to obtain refractory data. The invention obtains the fire-resistant data of the floor by obtaining the preset floor model obtained by simulating the floor, determining the fire-resistant performance analysis model and solving the model, and has the advantages of simple operation and higher efficiency without manufacturing and experiment of floor samples. Furthermore, the invention does not need manual participation, and compared with a manual experiment mode, the invention can avoid the problem of inaccurate operation caused by manual participation and improve the accuracy of refractory data determination.
After the simulation, the fire-resistant data of the floor is obtained, but whether the fire-resistant data is accurate or not, and whether the fire-resistant data of the floor can be obtained in the following manner of the simulation, further verification is required, specifically, after step S13, the method may further include:
and obtaining a floor fire resistance experimental result, and comparing the fire resistance data with the floor fire resistance experimental result to obtain a comparison result.
Specifically, the three aspects of the fire face temperature, the back fire face temperature and the experimental comparison are compared, and the specific steps are as follows:
1. temperature of fire surface
In order to verify the accuracy of the simulated setting, the temperature change of the fire surface in the simulation is compared with a set standard temperature rise curve. Referring to fig. 8, the results show that the temperature of the fire receiving surface is substantially coincident with the standard temperature rise curve, and the average temperature and the maximum temperature of the fire receiving surface are also substantially coincident, which means that the numerical calculation has better stability and consistency in both space and time dimensions.
As can be seen from fig. 8, there is a certain difference between the ISO standard temperature rise curve preset at the start of the simulation and the simulated fire surface temperature curve, because the iteration needs a certain time to converge at the start of the simulation and the COMSOL needs to interpolate the function at the time of calculation. But this difference becomes smaller and smaller afterwards, almost negligible, and this simulation can be considered valid.
2. Back fire surface temperature
In order to simulate the measurement condition in the experiment, the simulation outputs the temperature trend of the back fire surface of the floor. The highest temperature profile of the floor backfire surface is also output and compared to the average temperature profile. Referring to fig. 9, the results show that the highest temperature curve substantially coincides with the average temperature curve. Because the ideal heat insulation around the plate is assumed in the simulation, the bottom is uniformly heated, and therefore, the temperature distribution of the backfire surface is also relatively uniform. This also indirectly means that the heat transfer inside the plate has the property of one-dimensional heat transfer, i.e. there is a significant temperature distribution only in the height direction. The lateral distribution of the temperature within the plate can be ignored in the subsequent analysis of the simulation results.
According to the fire-resistant failure criterion of the floor result, "heat insulation condition: the average temperature of the back surface exceeds the initial temperature of 140 ℃, or any point of the back surface, whether the fixed temperature measuring point or the movable temperature measuring point exceeds the initial temperature of 180 ℃, and the back surface temperature is compared with the constant temperature of 165 ℃, so that the back surface temperature is found to reach the heat insulation failure standard in 84 minutes, as shown in fig. 10. This means that during the fire-resistance test of the floor, if the floor structure is assumed to remain intact all the time and the upper surface is only heated by the lower surface, the insulation will fail for 84 minutes at most. Therefore, the experiment should be controlled to have an experiment time below this analog value.
Fig. 11 shows the temperature distribution inside the floor at several typical moments. The non-metal materials such as the sound insulation felt and the carbon fiber cotton have better heat insulation capacity compared with the aluminum profile underframe, the temperature firstly forms obvious temperature distribution in the aluminum profile bottom plate, and then the temperature is obviously reduced after the temperature reaches the backfire surface through the carbon fiber heat insulation material barrier.
3. Experimental comparison
Compared with a real floor structure, the simulated preset floor model has the advantages that the simulated preset floor model has the calculation accuracy and parameter acquisition limitation, and structures such as damping slurry, elastic supports, wood bones and shock pads are integrated into other adjacent structures to be simulated, so that the properties are considered to be the same as the integrated adjacent structures. This approximation ignores the effects of these structures, but the incorporated structures are relatively small and do not greatly affect the simulation results, so the simulation results are still meaningful. The actual floor contains a support structure, the actual dimensions being 4550mm long and 3255mm wide, which is large compared to the simulated floor (4000 mm x 3000 mm). However, since the plates are identical and the simulation results show that the temperature distribution has one-dimensional characteristics, the effect of the dimensions is substantially negligible.
The laboratory ambient temperature was 25 ℃ when the experiment was run, consistent with the initial temperature at the time of simulation. The experimental device is basically consistent with the simulation setting, and the results of the experimental device and the simulation setting can be compared. The experiment uses a plurality of temperature thermocouples on the back surface of the floor, and the distribution is shown in figure 1. It should be noted that fig. 1 is only a schematic diagram of the thermocouple arrangement, and in practical application, 9 thermocouples or other numbers of thermocouples may be provided. The actual temperature in the furnace was also compared with the standard temperature as shown in fig. 12.
The actual temperature curve in the furnace basically accords with the standard temperature rise curve in the experiment, but the actual temperature in the furnace has certain fluctuation after 10 minutes. However, the fluctuation was small and did not exceed 5% of the standard temperature, and it was considered that the boundary conditions at the time of the experiment were consistent with the boundary conditions of the simulation.
In summary, the average temperature and the highest temperature of the backfire surface, which are measured through experiments, are basically consistent with the analog value, slightly higher, and the difference between the average temperature and the highest temperature is not more than 8% of the experimental value before 30 minutes, so that the backfire surface has higher consistency. The overall height is higher because the experimental device cannot achieve good sealing, and a certain penetrating support structure exists in the floor structure. On the one hand, the overflowed hot gas directly heats the floor surface, and on the other hand, the heat is more rapidly transferred upwards through the support structure with higher heat conductivity coefficient. This allows the temperature of the backfire face to rise faster in the experiment. In addition, the average value of the temperature of the backfire surface is obtained by averaging the temperature values measured by 9 thermocouples in the experiment, and the analog average value is obtained by integrating the temperature of the whole plane and then averaging, so that certain errors can be caused by different statistical modes of the two.
Referring to fig. 13, the highest temperature of the back surface measured experimentally is compared with the experimental value. It can be seen that the experimentally measured highest temperature of the backfire surface deviates significantly from the simulated backfire surface temperature. The highest temperature in the experiment is mostly measured by thermocouples at the edge of the floor, and the influence of high-temperature gas leakage in the furnace on the temperature of the backfire surface is obvious.
At the same time, it can be seen that the highest temperature of the backfire surface rises rapidly after 30min. Indicating that the floor bottom structure has been destroyed at this time, the flame in the furnace directly heats the floor backfire material so that it heats up rapidly. The phenomena of smoke emission, fire jump and the like exist in combination experiments, and the floor is considered to be fireproof and invalid at the moment. Compared with the simulation that the fire resistance of the floor structure is judged only according to the temperature rise of the backfire surface, the failure time obtained by the experiment is less than half of that obtained by the simulation, which shows that the physical and chemical changes of the floor material at high temperature have great influence on the fire resistance of the floor.
In summary, the embodiment of the invention is based on the operation and design background of the high-speed train, and is researched aiming at the fire resistance of the floor structure of the high-speed train. The research is mainly based on numerical simulation, and the fire resistance of the high-speed train bottom plate structure is researched. And compared with the fire resistance test results of the actual floor structure.
And modeling and calculating the thermal behavior of the floor structure under a standard fire source by using COMSOL multiple physical field simulation software according to a heat transfer basic equation.
The calculation result shows that the established simulation model has better stability and accuracy. Without consideration of the physical and chemical changes in the flooring material at high temperatures, the simulated floor backfire will exceed the initial temperature 165 ℃ at 84mi n and may in turn be judged as fire-resistant failure.
Compared with an aluminum profile underframe, nonmetallic materials such as a sound insulation felt, carbon fiber cotton and the like have better heat insulation capacity, the temperature firstly forms obvious temperature distribution in the aluminum profile underframe, then is blocked by the carbon fiber heat insulation material, and the temperature is obviously reduced after reaching a backfire surface.
By comparing the floor fire-resistant simulation result with the floor fire-resistant experiment result, the simulation within 30min has better reproduction capability to actual conditions, but the temperature of the backfire surface obtained by the experiment is relatively higher and rapidly rises after 30min, which proves that the side surface of the actual experiment furnace has the conditions of air leakage, fire jump and the like, and the physical and chemical changes of the floor material caused by high temperature have great influence on the fire resistance of the floor. The fire resistance of the actual floor structure was about 30 minutes.
Alternatively, on the basis of the embodiment of the above-described refractory data determining method, another embodiment of the present invention provides a refractory data determining apparatus, applied to a processor, with reference to fig. 14, including:
the floor model processing module 11 is used for acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model;
the model determining module 12 is used for determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
and the model solving module 13 is used for carrying out solving operation on the fire resistance analysis model and the discretization result to obtain fire resistance data.
Further, the model determination module includes:
the model acquisition sub-module is used for acquiring a preset heat transfer model;
the test data acquisition sub-module is used for acquiring the floor fire resistance test data;
and the condition determining submodule is used for determining the constraint condition of the heat transfer model according to the floor fire resistance experimental data.
Further, the condition determination submodule includes:
the first determining unit is used for acquiring and determining the thermal insulation constraint condition of the heat transfer model according to the thermal insulation boundary data in the floor fire resistance experimental data;
the second determining unit is used for acquiring and determining the temperature boundary constraint condition of the heat transfer model according to the temperature boundary data of the temperature node in the floor fire resistance experimental data;
and the third determining unit is used for acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
Further, the floor model processing module is specifically configured to:
and carrying out grid division processing on the preset floor model according to a preset grid division method to obtain a discretization result.
Further, the model solving module is specifically configured to:
and solving the refractory performance analysis model and the discretization result by using a preset solver to obtain refractory data.
Further, the method further comprises the following steps:
and the comparison module is used for obtaining the floor fire resistance experimental result, and comparing the fire resistance data with the floor fire resistance experimental result to obtain a comparison result.
In this embodiment, the processor obtains a preset floor model of the floor obtained through simulation operation, discretizes the preset floor model to obtain a discretized result, and then determines a refractory performance analysis model corresponding to the preset floor model, so that the refractory performance analysis model and the discretized result can be solved to obtain refractory data. The invention obtains the fire-resistant data of the floor by obtaining the preset floor model obtained by simulating the floor, determining the fire-resistant performance analysis model and solving the model, and has the advantages of simple operation and higher efficiency without manufacturing and experiment of floor samples. Furthermore, the invention does not need manual participation, and compared with a manual experiment mode, the invention can avoid the problem of inaccurate operation caused by manual participation and improve the accuracy of refractory data determination.
It should be noted that, in the working process of each module, sub-module and unit in this embodiment, please refer to the corresponding description in the above embodiment, and the description is omitted here.
Optionally, on the basis of the embodiment of the method and the device for determining refractory data, another embodiment of the present invention provides an electronic device, including: a memory and a processor;
wherein the memory is used for storing programs;
the processor invokes the program and is configured to:
acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model;
determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
and solving the fire resistance analysis model and the discretization result to obtain fire resistance data.
Further, determining a refractory performance analysis model corresponding to the preset floor model, including:
acquiring a preset heat transfer model;
acquiring experimental data of fire resistance of the floor;
and determining constraint conditions of the heat transfer model according to the floor fire resistance experimental data.
Further, determining constraints of the heat transfer model according to the floor fire resistance experimental data includes:
acquiring and determining thermal insulation constraint conditions of the heat transfer model according to thermal insulation boundary data in the floor fire resistance experimental data;
acquiring and determining a temperature boundary constraint condition of the heat transfer model according to temperature boundary data of a temperature node in the floor fire resistance experimental data;
and acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
Further, discretizing the preset floor model to obtain a discretization result, including:
and carrying out grid division processing on the preset floor model according to a preset grid division method to obtain a discretization result.
Further, the solution operation is performed on the refractory performance analysis model and the discretization result to obtain refractory data, including:
and solving the refractory performance analysis model and the discretization result by using a preset solver to obtain refractory data.
Further, after solving the refractory performance analysis model and the discretization result, the method further includes:
obtaining a floor fire resistance experimental result;
and comparing the fire resistance data with the floor fire resistance experimental result to obtain a comparison result.
In this embodiment, the processor obtains a preset floor model of the floor obtained through simulation operation, discretizes the preset floor model to obtain a discretized result, and then determines a refractory performance analysis model corresponding to the preset floor model, so that the refractory performance analysis model and the discretized result can be solved to obtain refractory data. The invention obtains the fire-resistant data of the floor by obtaining the preset floor model obtained by simulating the floor, determining the fire-resistant performance analysis model and solving the model, and has the advantages of simple operation and higher efficiency without manufacturing and experiment of floor samples. Furthermore, the invention does not need manual participation, and compared with a manual experiment mode, the invention can avoid the problem of inaccurate operation caused by manual participation and improve the accuracy of refractory data determination.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method of determining refractory data for use in a processor, the method comprising:
acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model; wherein the preset floor model comprises a plurality of layers, and the materials of each layer are different;
determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
solving the fire resistance analysis model and the discretization result to obtain fire resistance data;
wherein, the heat transfer model is:
ρ is the material density, C p The constant pressure specific heat capacity of the material is obtained, T is the absolute temperature of the material, u is the translational velocity vector of the material, q is the heat flow entering the material through heat conduction, and q r For radiation heat flow, Q is heat generation in the material, S is second-order Picola-Kirchhoff stress tensor, alpha is a thermal diffusion coefficient, and T is a temperature gradient;
the constraint conditions of the heat transfer model are as follows: -n·q=0, n represents the surface normal vector and q is the surface heat flow.
2. The method according to claim 1, wherein determining the refractory performance analysis model corresponding to the preset floor model includes:
acquiring a preset heat transfer model;
acquiring experimental data of fire resistance of the floor;
and determining constraint conditions of the heat transfer model according to the floor fire resistance experimental data.
3. The method of determining according to claim 2, wherein determining constraints of the heat transfer model based on the floor fire resistance experimental data comprises:
acquiring and determining thermal insulation constraint conditions of the heat transfer model according to thermal insulation boundary data in the floor fire resistance experimental data;
acquiring and determining a temperature boundary constraint condition of the heat transfer model according to temperature boundary data of a temperature node in the floor fire resistance experimental data;
and acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
4. The method according to claim 1, wherein discretizing the predetermined floor model to obtain a discretized result includes:
and carrying out grid division processing on the preset floor model according to a preset grid division method to obtain a discretization result.
5. The method of determining according to claim 1, wherein solving the refractory performance analysis model and the discretized results to obtain refractory data comprises:
and solving the refractory performance analysis model and the discretization result by using a preset solver to obtain refractory data.
6. The method according to claim 1, further comprising, after solving the refractory performance analysis model and the discretized result, after obtaining refractory data:
obtaining a floor fire resistance experimental result;
and comparing the fire resistance data with the floor fire resistance experimental result to obtain a comparison result.
7. A refractory data determining apparatus, for use with a processor, the determining apparatus comprising:
the floor model processing module is used for acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model; wherein the preset floor model comprises a plurality of layers, and the materials of each layer are different;
the model determining module is used for determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
the model solving module is used for carrying out solving operation on the fire resistance analysis model and the discretization result to obtain fire resistance data;
wherein, the heat transfer model is:
ρ is the material density, C p The constant pressure specific heat capacity of the material is obtained, T is the absolute temperature of the material, u is the translational velocity vector of the material, q is the heat flow entering the material through heat conduction, and q r For radiation heat flow, Q is heat generation in the material, S is second-order Picola-Kirchhoff stress tensor, alpha is a thermal diffusion coefficient, and T is a temperature gradient;
the constraint conditions of the heat transfer model are as follows: -n·q=0, n represents the surface normal vector and q is the surface heat flow.
8. The determination device according to claim 7, wherein the model determination module includes:
the model acquisition sub-module is used for acquiring a preset heat transfer model;
the test data acquisition sub-module is used for acquiring the floor fire resistance test data;
and the condition determining submodule is used for determining the constraint condition of the heat transfer model according to the floor fire resistance experimental data.
9. The determination apparatus according to claim 8, wherein the condition determination submodule includes:
the first determining unit is used for acquiring and determining the thermal insulation constraint condition of the heat transfer model according to the thermal insulation boundary data in the floor fire resistance experimental data;
the second determining unit is used for acquiring and determining the temperature boundary constraint condition of the heat transfer model according to the temperature boundary data of the temperature node in the floor fire resistance experimental data;
and the third determining unit is used for acquiring and determining the open boundary constraint condition of the heat transfer model according to the open boundary data in the floor fire resistance experimental data.
10. An electronic device, comprising: a memory and a processor;
wherein the memory is used for storing programs;
the processor invokes the program and is configured to:
acquiring a preset floor model of the floor obtained through simulation operation, and performing discretization on the preset floor model to obtain a discretization result; the preset floor model is a CAD model; wherein the preset floor model comprises a plurality of layers, and the materials of each layer are different;
determining a fire resistance analysis model corresponding to the preset floor model; the refractory performance analysis model comprises a heat transfer model and constraint conditions of the heat transfer model;
solving the fire resistance analysis model and the discretization result to obtain fire resistance data;
wherein, the heat transfer model is:
ρ is the material density, C p The constant pressure specific heat capacity of the material is obtained, T is the absolute temperature of the material, u is the translational velocity vector of the material, q is the heat flow entering the material through heat conduction, and q r For radiation heat flow, Q is heat generation in the material, S is second-order Picola-Kirchhoff stress tensor, alpha is a thermal diffusion coefficient, and T is a temperature gradient;
the constraint conditions of the heat transfer model are as follows: -n·q=0, n represents the surface normal vector and q is the surface heat flow.
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