Method and device for predicting explosion risk based on self-adaptive fractal dimension according to working condition

Abstract

The application relates to a combustion and explosion risk prediction method and device based on a working condition self-adaptive fractal dimension, and particularly relates to the technical field of combustion and explosion safety. The method comprises the following steps: firstly, acquiring environment monitoring data and space structure data of a closed space; then, determining a flow field working condition in the closed space according to the environment monitoring data and the space structure data, the flow field working condition being used for determining a fractal dimension and a flame acceleration critical radius, the fractal dimension and the flame acceleration critical radius being self-adaptive to the turbulent intensity of the flow field working condition; using an overpressure prediction model to determine a combustion and explosion overpressure prediction result of a combustible mixture in the closed space according to the fractal dimension and the flame acceleration critical radius; and finally, determining a combustion and explosion risk grade corresponding to the closed space according to the combustion and explosion overpressure prediction result. The application can self-adaptively determine the flame propagation characteristics corresponding to the fluid working condition, predict the combustion and explosion overpressure, and further improve the combustion and explosion overpressure prediction accuracy.

Description

Technical Field

[0001] This application relates to the field of combustion and explosion safety technology, and in particular to a method and device for predicting combustion and explosion risks based on operating condition adaptive fractal dimension. Background Technology

[0002] With the rapid development of industrial production, urban underground spaces, energy storage and transportation, chemical plants and special enclosed compartments, enclosed spaces, due to poor ventilation and limited diffusion of media, are prone to rapid combustion and explosion once a flammable gas mixture is formed and encounters an ignition source. Predicting the risk of combustion and explosion can effectively improve the ability to prevent and control fires in enclosed spaces.

[0003] The relevant technologies mainly rely on the fixed fractal dimension of the physical process of flame propagation for combustion and explosion prediction. However, they ignore the changes in the critical radius of flame acceleration and the fractal dimension with the intensity of turbulence under different operating conditions. This makes it difficult to reflect the real flame acceleration effect under different operating conditions, resulting in insufficient accuracy in combustion and explosion risk prediction. Summary of the Invention

[0004] In view of this, this application provides a method and device for predicting combustion and explosion risks based on the operating condition adaptive fractal dimension. The main purpose is to improve the technical problem that related technologies mainly rely on the fixed fractal dimension of the flame propagation physical process for combustion and explosion prediction, which ignores the change of fractal dimension with turbulence intensity under different operating conditions, making it difficult to reflect the real flame acceleration effect under different operating conditions, thus leading to insufficient accuracy in combustion and explosion risk prediction.

[0005] Firstly, this application provides a method for predicting combustion and explosion risks based on operating condition adaptive fractal dimension, the method comprising:

[0006] Acquire environmental monitoring data and spatial structure data of confined spaces;

[0007] Based on environmental monitoring data and spatial structure data, the flow field conditions in the confined space are determined. The flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration. The fractal dimension and the critical radius for flame acceleration adapt to the turbulence intensity of the flow field conditions.

[0008] Using an overpressure prediction model, the prediction results of combustion and explosion overpressure of combustible mixtures in a confined space are determined based on fractal dimension and critical radius of flame acceleration.

[0009] Based on the prediction results of combustion and explosion overpressure, the combustion and explosion risk level corresponding to the confined space is determined.

[0010] Secondly, this application provides a combustion and explosion risk prediction device based on working condition adaptive fractal dimension, the device comprising:

[0011] The acquisition module is configured to acquire environmental monitoring data and spatial structure data of the enclosed space.

[0012] The first determining module is configured to determine the flow field conditions in the confined space based on environmental monitoring data and spatial structure data. The flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration. The fractal dimension and the critical radius for flame acceleration adapt to the turbulence intensity of the flow field conditions.

[0013] The prediction module is configured to use an overpressure prediction model to determine the combustion and explosion overpressure prediction results of a combustible mixture in a confined space based on the fractal dimension and the critical radius of flame acceleration.

[0014] The second determination module is configured to determine the explosion risk level of the confined space based on the explosion overpressure prediction results.

[0015] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method of the first aspect.

[0016] Fourthly, this application provides an electronic device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor executes the computer program to implement the method of the first aspect.

[0017] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method of the first aspect.

[0018] By employing the above technical solution, this application provides a method and apparatus for predicting combustion and explosion risks based on adaptive fractal dimension under specific operating conditions. Compared with related technologies, this application first acquires environmental monitoring data and spatial structure data of a confined space; then, based on the environmental monitoring data and spatial structure data, it determines the flow field conditions within the confined space. The flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration, which adaptively change with the turbulence intensity of the flow field conditions; using an overpressure prediction model, it determines the combustion and explosion overpressure prediction results of the combustible mixture in the confined space based on the fractal dimension and the critical radius for flame acceleration; finally, based on the combustion and explosion overpressure prediction results, it determines the corresponding combustion and explosion risk level of the confined space. This allows for the detection of fluid conditions in the confined space by combining the actual detected environmental monitoring data and spatial structure data. The overpressure prediction model, based on the fractal dimension and the critical radius for flame acceleration corresponding to the flow field conditions, adaptively predicts the flame propagation characteristics under the fluid conditions, thereby improving the accuracy of combustion and explosion overpressure prediction.

[0019] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0020] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 A flowchart illustrating the combustion and explosion risk prediction method based on working condition adaptive fractal dimension provided in this application embodiment is shown.

[0023] Figure 2 This illustration shows an example of overpressure prediction using different models and experimental data under laminar flow conditions, provided by an embodiment of this application.

[0024] Figure 3 This illustration shows an example of overpressure prediction using different models and experimental data under turbulent conditions, provided in an embodiment of this application.

[0025] Figure 4 This illustration shows a schematic diagram of overpressure prediction under turbulent conditions using different models and experimental data, representing another example provided in an embodiment of this application.

[0026] Figure 5 A schematic diagram of the structure of the combustion and explosion risk prediction device based on the working condition adaptive fractal dimension provided in the embodiment of this application is shown. Detailed Implementation

[0027] To better understand the above-mentioned objectives, features, and advantages of this application, the solution of this application will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0028] To improve upon existing technologies that primarily rely on an idealized view of flame propagation physics and fix the fractal dimension for combustion and explosion prediction, neglecting the variations in fractal dimension with turbulence intensity under different operating conditions, and the flame acceleration effect caused by the evolution of folded morphology during flame propagation, this approach struggles to adapt to the flame propagation characteristics under varying operating conditions and reflect the true flame acceleration effect, leading to insufficient accuracy in combustion and explosion risk prediction. This embodiment provides a combustion and explosion risk prediction method based on an adaptive fractal dimension under operating conditions, such as... Figure 1 As shown, the method includes:

[0029] Step 101: Obtain environmental monitoring data and spatial structure data of the enclosed space.

[0030] In some embodiments, environmental monitoring data can be obtained by arranging sensors for gas, temperature, pressure, and wind speed within the confined space. This allows for the acquisition of real-time data on the overpressure affecting combustion and explosion within the confined space. Furthermore, spatial structure data can be obtained based on the corresponding design drawings, on-site measurements, or 3D modeling to assess the spatial structure of the confined space. Confined spaces may include enclosed or semi-enclosed spaces with small openings, limited ventilation, and poor gas diffusion, where combustible gases, vapors, or dust may accumulate. Examples include underground utility tunnels, energy storage chambers, cable tunnels, chemical processing rooms, mine roadways, and the interiors of storage tanks.

[0031] Correspondingly, environmental monitoring data may include parameters directly related to the risk of combustion and explosion, collected in real time within a confined space, such as the concentration of combustible gases (H2, CH4, oil and gas, combustible vapors, etc.), oxygen concentration, ambient temperature, ambient static pressure (initial pressure), internal airflow velocity, initial laminar flame velocity, and initial space temperature. Spatial structure data may include parameters such as the geometry of the confined space, its internal structure, and the distribution of obstacles, including initial space pressure, maximum space pressure, space dimensions (such as length, width, height, and equivalent spherical radius), the number of obstacles, obstacle locations, obstacle dimensions, wall roughness, and channel curvature.

[0032] Step 102: Based on environmental monitoring data and spatial structure data, determine the flow field conditions within the confined space. The flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration.

[0033] Among them, the fractal dimension and the critical radius for flame acceleration adapt to the turbulence intensity of the flow field conditions.

[0034] Specifically, flow field conditions refer to the flow state of a combustible mixture (such as H2 / Air premixed gas) within a confined space. This characterizes the degree of orderliness / turbulence in gas flow, influencing flame propagation speed, flame morphology, and combustion intensity. Flow field conditions can include laminar flow and turbulent flow. Laminar flow refers to a scenario where the gas in the space flows in a layered and orderly manner, without obvious vortex mixing, with stable flow velocity and no significant velocity fluctuations. The flame surface is smooth and flat, the combustion rate is stable, and the overpressure growth is gradual. This often occurs in scenarios with simple spatial structures, no obstacles, and low flow velocities. Turbulent flow refers to a scenario where the gas in the space has strong vortices, velocity fluctuations, and mixing. The magnitude and direction of the flow velocity change randomly, the flame is torn and folded by the vortices, the surface area is significantly enlarged, the combustion rate increases sharply, and the overpressure growth is rapid. This is the mainstream flow field condition in most complex confined spaces (such as pipe racks and energy storage chambers).

[0035] In some embodiments, flow medium parameters, such as average flow velocity and gas density, can be extracted from environmental monitoring data to calculate the Reynolds number. Then, the working conditions of the Reynolds number division can be corrected and verified by combining spatial structure data, and finally the flow field working conditions of the gas flow in the closed space can be determined.

[0036] Specifically, the fractal dimension can be calculated based on spatial structure data and adaptively varies with the turbulence intensity under different flow field conditions. It can serve as a quantitative parameter characterizing the complexity of the internal structure of a confined space, the density of obstacle distribution, and the irregularity of the wall surface. The larger the value, the denser the distribution of obstacles (pipes, supports, etc.) and the more irregular the structure within the space, resulting in stronger disturbances to airflow and flame propagation, directly affecting the flame acceleration effect and overpressure growth rate. The critical radius for flame acceleration can be defined as the critical flame radius at which a combustible mixture flame transitions from stable propagation to accelerated propagation. It adaptively varies with the turbulence intensity under different flow field conditions. For example, under turbulent conditions, due to strong airflow disturbances, the flame is easily torn and wrinkled, resulting in a lower critical radius for flame acceleration and an earlier entry into the acceleration phase. Under laminar flow conditions, the critical radius for flame acceleration is higher, and flame acceleration is slower.

[0037] Step 103: Using the overpressure prediction model, determine the overpressure prediction results of the combustion and explosion of the combustible mixture in the confined space based on the fractal dimension and the critical radius of flame acceleration.

[0038] Among them, the overpressure prediction model is used to predict the overpressure change rate of combustible mixtures based on the fractal dimension corresponding to the spatial structure data and the critical radius of flame acceleration corresponding to the flow field conditions. The fractal dimension and the critical radius of flame acceleration adapt to the turbulence intensity of the flow field conditions.

[0039] Correspondingly, the overpressure prediction model can be a quantitative model for predicting the overpressure of a combustible mixture in a confined space. It can predict the rate of overpressure change in a confined space over a period of time, forming the overpressure prediction result. The rate of overpressure change refers to the rate of pressure change in a confined space over time, which is a key indicator for measuring the intensity of the combustion and explosion. The larger the rate of overpressure change, the faster the combustion and explosion pressure rises, and the higher the risk of damage to the structure of the confined space. The overpressure prediction result can include a set of key parameters in the combustion and explosion process of a combustible mixture in a confined space, such as the rate of overpressure change, peak overpressure, and explosion index, calculated by the overpressure prediction model.

[0040] In some embodiments, the critical radius of flame acceleration and the fractal dimension can be determined based on the flow field conditions. Then, the critical radius and the fractal dimension are imported into the combustion and explosion overpressure prediction model. The overpressure prediction model can calculate the overpressure change rate of the combustible mixture based on the current spatial structure data, the fractal dimension and the critical radius of flame acceleration calculated from the flow field conditions, as well as the real-time detected environmental monitoring data and spatial structure data, and generate combustion and explosion overpressure prediction results to adapt to the flow field conditions of the confined space, thereby improving the accuracy of combustion and explosion risk prediction.

[0041] Step 104: Determine the explosion risk level of the confined space based on the explosion overpressure prediction results.

[0042] In some embodiments, based on the actual engineering requirements corresponding to the confined space and the critical overpressure of the structural bearing capacity calculated by combining the spatial structure data, the peak overpressure in the predicted overpressure of combustion and explosion can be compared with the critical overpressure to determine the current level of combustion and explosion risk. This is used to assess the probability and extent of damage of combustion and explosion accidents in confined spaces, so as to facilitate combustion and explosion prevention and control.

[0043] Compared with related technologies, this embodiment first acquires environmental monitoring data and spatial structure data of a confined space; then, based on the environmental monitoring data and spatial structure data, it determines the flow field conditions within the confined space. These flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration, which adaptively change with the turbulence intensity of the flow field conditions. Using an overpressure prediction model, it determines the combustion and explosion overpressure prediction results for the combustible mixture in the confined space based on the fractal dimension and the critical radius for flame acceleration. Finally, based on the combustion and explosion overpressure prediction results, it determines the corresponding combustion and explosion risk level of the confined space. This approach combines the actually detected environmental monitoring data and spatial structure data to detect the fluid conditions in the confined space. The overpressure prediction model, based on the fractal dimension and the critical radius for flame acceleration corresponding to the flow field conditions, adaptively predicts the flame propagation characteristics under the fluid conditions, thereby improving the accuracy of combustion and explosion overpressure prediction.

[0044] Furthermore, as a refinement and extension of the specific implementation of the above embodiments, in order to fully illustrate the implementation of this embodiment, step 103 may optionally include: determining the fractal dimension and the critical radius of flame acceleration based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions; correcting the flame surface area and laminar flame velocity corresponding to the combustible mixture based on the fractal dimension and the critical radius of flame acceleration; and generating an overpressure prediction curve based on the flame surface area and laminar flame velocity using an overpressure prediction model, as the result of the combustion and explosion overpressure prediction.

[0045] In some embodiments, since the flame itself is unstable and wrinkled due to turbulent disturbances, the turbulence intensity and laminar flame velocity corresponding to the current flow field condition can be calculated first. Then, the fractal dimension and critical radius of flame acceleration can be obtained by combining experimental experience to correct the flame surface area and laminar flame velocity corresponding to the combustible mixture under different flow field conditions. Based on the corrected flame surface area and laminar flame velocity, an overpressure prediction curve is generated using an overpressure prediction model, thereby realizing adaptive adjustment of flame surface area and laminar flame velocity under different flow field conditions, and thus improving the accuracy of combustion and explosion overpressure prediction.

[0046] Optionally, the fractal dimension and critical radius for flame acceleration can be determined based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions. Specifically, this may include: using a preset empirical formula to calculate the fractal dimension and critical radius for flame acceleration based on the turbulence intensity and laminar flame velocity. The preset empirical formula is constructed based on the empirical fitting index and the empirical correction coefficient.

[0047] For example, a preset empirical formula can be expressed as:

[0048]

[0049]

[0050] In the formula, It can represent the fractal dimension corresponding to the flow field condition. It can represent the empirical fit index corresponding to the fractal dimension. It can represent the empirical correction coefficient corresponding to the fractal dimension; It can represent the critical radius for flame acceleration corresponding to the flow field condition. It can represent the empirical fit index corresponding to the fractal dimension. This can represent the empirical correction coefficient corresponding to the fractal dimension. Among them, the empirical fitting index and the empirical correction coefficient can be obtained by fitting a large amount of experimental data on combustion and explosion in a confined space, and are used to characterize the influence weights of turbulent pulsation velocity and laminar combustion velocity on the characteristic time of flame development and critical radius.

[0051] Optionally, based on the fractal dimension and the critical radius of flame acceleration, the flame surface area and laminar flame velocity corresponding to the combustible mixture are corrected. Specifically, this may include: determining the flame surface area corresponding to the combustible mixture based on the critical radius of flame acceleration and the fractal dimension; and correcting the initial laminar flame velocity in the environmental monitoring data based on the pressure correction coefficient and temperature correction coefficient corresponding to the confined space to determine the laminar flame velocity corresponding to the combustible mixture.

[0052] Specifically, the actual flame surface area is wrinkled due to the flame's inherent instability and turbulent disturbances, which can be corrected by introducing the flame acceleration critical radius rc and the fractal dimension D. (Flame surface area) The corresponding surface area correction formula can be expressed as:

[0053] ;

[0054] Where rf is the flame radius, rc is the critical radius for flame acceleration, and rc can be used to represent the initial scale of flame acceleration.

[0055] Correspondingly, the laminar flame velocity is affected by space pressure and space temperature. The corresponding correction formula can be expressed as:

[0056] ;

[0057] Where m can represent the pressure correction factor and n can represent the temperature correction factor. The pressure correction factor and temperature correction factor can be adaptively modified according to the composition of the combustible mixture. For example, if the combustible mixture is hydrogen, then m can be 1.26 and n can be 0.26. It can represent the initial laminar flame velocity. It can represent the current spatial temperature. It can represent the initial space temperature. It can indicate overpressure. It can represent the initial spatial pressure.

[0058] Optionally, if the combustion and explosion process in a confined space is an adiabatic compression process, the space temperature and space pressure satisfy the following condition: Based on pressure and temperature correction factors, the laminar flame velocity is substituted. The corresponding corrected formula yields the simplified formula for the laminar flame velocity as follows:

[0059] .

[0060] Optionally, an overpressure prediction model can be constructed based on the surface area correction formula, the simplified formula for laminar flame velocity, the mass burn rate equation, and the burned volume fraction equation.

[0061] For example, assuming the flame thickness is negligible (e.g., a thin flame), the mass burn rate is determined by the flame surface area and the combustion rate, and the mass burn rate equation can be expressed as:

[0062] ;

[0063] in, It can indicate the mass of material already burned. It can represent the mass combustion rate, where ρu is the density of unburned gas;

[0064] Furthermore, based on the surface area correction formula, the corrected... Substituting into the mass flammability equation, we obtain the corrected mass flammability:

[0065] .

[0066] In some embodiments, for a confined space, the overpressure change rate is related to the volumetric combustion rate. The larger the burned volume of the combustible mixture, the more combustible mixture participates in the heat release of combustion, the more drastic the temperature rise and the faster the pressure rise within the space, and the greater the peak overpressure and the overpressure change rate. The relationship between the overpressure change rate and the volumetric combustion rate can be expressed as follows:

[0067] ;

[0068] in, Where V is the rate of change of overpressure and V is the volume of space. The volume of the burned material. The rate of change of burned volume. It can represent the density of an unburned combustible mixture. This can represent the density of burned gas. For thin flames, Substituting the values, we can obtain the expression for the rate of change of overpressure as follows:

[0069] .

[0070] Furthermore, the flame surface area can be... The corresponding surface area correction formula is then substituted into the expression for the rate of change of overpressure. For example, if the confined space is approximated as a spherical space, its volume can be expressed as... From this, we can obtain the expression for the overpressure change rate corresponding to the spherical space:

[0071] .

[0072] Specifically, considering the relationship between flame radius and burned volume fraction, the larger the flame radius, the larger the burned volume fraction. It can be represented as:

[0073] ;

[0074] We can obtain:

[0075] .

[0076] Will Substituting the expression for the rate of change of overpressure corresponding to the spherical space, we get:

[0077] ;

[0078] It can also be written as:

[0079] ;

[0080] Meanwhile, considering the relationship between the burned volume fraction and the space pressure, according to the thermodynamic model, the burned volume fraction is related to the space pressure, and can also be approximately expressed as:

[0081] ;

[0082] In the formula, It can represent the specific heat ratio corresponding to a combustible mixture;

[0083] The expression for the relationship between the burned volume fraction and the space pressure can be derived as follows:

[0084] ;

[0085] Furthermore, by substituting the expressions for the burned volume fraction and space pressure, and the simplified formula for laminar flame velocity, into the expression for the overpressure change rate corresponding to the spherical space, the expression corresponding to the overpressure prediction model can be obtained as follows:

[0086]

[0087]

[0088] .

[0089] Optionally, an overpressure prediction model can be used to generate an overpressure prediction curve based on the flame surface area and laminar flame velocity. Specifically, this may include: determining the initial monitoring data corresponding to the confined space based on the flame surface area, laminar flame velocity, environmental monitoring data, and spatial structure data; inputting the initial monitoring data into the overpressure prediction model; solving the overpressure prediction model through numerical integration based on the flame surface area and laminar flame velocity; calculating the combustion and explosion overpressure at each time step; and generating an overpressure prediction curve.

[0090] In some embodiments, initial detection data can be selected from real-time environmental monitoring data and spatial structure data, input into the overpressure prediction model, and generated through integral solving to produce an overpressure prediction curve showing the change of combustion overpressure in a confined space over time. The initial detection data can be the initial parameters of the expression corresponding to the overpressure prediction model, which can be adjusted according to the spatial morphology. The initial detection data may include data such as the initial spatial pressure, maximum spatial pressure, spatial dimensions, fractal dimension, critical radius for flame acceleration, initial laminar flame velocity, specific heat ratio, pressure correction coefficient, and temperature correction coefficient of the confined space.

[0091] For example, the combustible mixture is a hydrogen / air (H2 / Air) premixed combustible mixture with an equivalence ratio of φWhen the value is 1.0 and the flow field condition is laminar, the predicted value is based on time. t / ms is the horizontal axis, with overpressure P The overpressure prediction curve with / MPa as the vertical axis is shown below. Figure 2 As shown, the overpressure prediction curves for different models and experimental data under laminar flow conditions are illustrated, including those using the original model and those using varying models. Models, Nishihara model, Li model, overpressure prediction model of this embodiment, and prediction results corresponding to experimental data. Accordingly, the combustible mixture is a hydrogen / air premixed combustible mixture with an equivalence ratio of... φ For turbulent conditions with a value of 1.0 and turbulence intensities of 0.89 m / s and 2.66 m / s, the predicted overpressure curves are as follows: Figure 3 , 4 As shown in the figure, the overpressure prediction model in this embodiment has the highest fit with the experimental data and its accuracy is better than other comparative models.

[0092] Optionally, step 104 may specifically include: extracting the overpressure peak value of the confined space from the overpressure prediction results of combustion and explosion; determining the critical overpressure of the confined space based on the spatial structure data; determining the risk classification rule corresponding to the confined space based on the critical overpressure; and determining the combustion and explosion risk level corresponding to the overpressure peak value of the confined space according to the risk classification rule.

[0093] In some embodiments, the critical overpressure that the confined space structure can withstand can be determined based on the spatial structure data of the confined space, such as material strength and geometric dimensions. Multiple risk levels are divided based on the critical overpressure, risk classification rules are constructed, and the predicted overpressure peak value is matched with the risk classification rules to determine the current explosion risk level of the confined space.

[0094] Optionally, the overpressure rise rate and overpressure duration can be extracted from the overpressure prediction results; and the risk classification rules for the confined space can be determined based on the critical rate corresponding to the overpressure rise rate and the critical time corresponding to the overpressure duration.

[0095] Optionally, after step 104, the method of this embodiment may further include: determining the graded prevention and control strategy corresponding to the level of fire and explosion risk, and adjusting the spatial structure of the enclosed space according to the graded prevention and control strategy.

[0096] Among these, the tiered prevention and control strategy refers to pre-set explosion suppression and safety management plans based on different explosion risk levels (such as low, medium, high, and extremely high risk). These plans include a combination of measures such as structural adjustments, flow field optimization, explosion venting and suppression, enhanced ventilation, and monitoring and early warning, used to specifically reduce the probability of explosion and overpressure hazards. Specifically, spatial structural adjustments can be made to the distribution of obstacles, cross-sectional dimensions, internal component layout, and pressure relief structures in confined spaces to reduce fractal dimension, weaken turbulent disturbances, and suppress flame acceleration, thereby reducing the peak explosion overpressure and improving the safety performance of confined spaces.

[0097] Optionally, the risk level can be integrated with overpressure prediction results, spatial structure information, and flow field condition information to form a combustion and explosion risk assessment result. After implementing prevention and control measures according to the graded prevention and control strategy, environmental monitoring data and spatial structure data can be reacquired, and flow field condition determination, fractal dimension and flame acceleration critical radius calculation, overpressure numerical integration solution, and combustion and explosion risk level determination can be performed again to achieve closed-loop assessment and control of combustion and explosion risk.

[0098] Compared with related technologies, this embodiment can determine the fractal dimension and critical radius of flame acceleration based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions. Based on the fractal dimension and critical radius of flame acceleration, the flame surface area and laminar flame velocity corresponding to the combustible mixture are corrected. Finally, using the overpressure prediction model, an overpressure prediction curve is generated based on the flame surface area and laminar flame velocity. By introducing the fractal dimension and critical radius that adapt to the turbulence intensity, the degree of flame surface wrinkling and the flame acceleration initiation conditions are dynamically expressed in the overpressure prediction model, which significantly improves the prediction accuracy of gas combustion and explosion overpressure in confined spaces and broadens the applicable range of conditions.

[0099] Furthermore, embodiments of this application provide a combustion and explosion risk prediction device based on operating condition adaptive fractal dimension, such as... Figure 5 As shown, the device includes: an acquisition module 31, a first determination module 32, a prediction module 33, and a second determination module 34.

[0100] The acquisition module 31 is configured to acquire environmental monitoring data and spatial structure data of the enclosed space;

[0101] The first determining module 32 is configured to determine the flow field conditions in the confined space based on environmental monitoring data and spatial structure data. The flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration. The fractal dimension and the critical radius for flame acceleration adapt to the turbulence intensity of the flow field conditions.

[0102] Prediction module 33 is configured to use an overpressure prediction model to determine the combustion and explosion overpressure prediction results of a combustible mixture in a confined space based on the fractal dimension and the critical radius of flame acceleration.

[0103] The second determining module 34 is configured to determine the explosion risk level corresponding to the confined space based on the explosion overpressure prediction results.

[0104] In some embodiments, the prediction module 33 is specifically configured to determine the fractal dimension and the critical radius of flame acceleration based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions; correct the flame surface area and laminar flame velocity corresponding to the combustible mixture based on the fractal dimension and the critical radius of flame acceleration; and generate an overpressure prediction curve based on the flame surface area and laminar flame velocity using an overpressure prediction model, as the result of the combustion and explosion overpressure prediction.

[0105] In some embodiments, the prediction module 33 is specifically configured to use a preset empirical formula to calculate the fractal dimension and the critical radius of flame acceleration based on the turbulence intensity and the laminar flame velocity. The preset empirical formula is constructed based on the empirical fitting index and the empirical correction coefficient.

[0106] In some embodiments, the prediction module 33 is specifically configured to determine the flame surface area corresponding to the combustible mixture based on the flame acceleration critical radius and fractal dimension; and to correct the initial laminar flame velocity in the environmental monitoring data based on the pressure correction coefficient and temperature correction coefficient corresponding to the confined space, thereby determining the laminar flame velocity corresponding to the combustible mixture.

[0107] In some embodiments, the prediction module 33 is specifically configured to determine the initial monitoring data corresponding to the confined space based on environmental monitoring data and spatial structure data; input the initial monitoring data into the overpressure prediction model; solve the overpressure prediction model by numerical integration based on the flame surface area and laminar flame velocity; calculate the combustion and explosion overpressure at each time step by time; and generate an overpressure prediction curve.

[0108] In some embodiments, the second determining module 34 is specifically configured to extract the overpressure peak value of the confined space from the combustion and explosion overpressure prediction results; determine the critical overpressure of the confined space based on the spatial structure data; determine the risk classification rule corresponding to the confined space based on the critical overpressure; and determine the combustion and explosion risk level corresponding to the overpressure peak value of the confined space according to the risk classification rule.

[0109] In some embodiments, the second determining module 34 is further configured to determine the graded prevention and control strategy corresponding to the level of fire and explosion risk, and adjust the spatial structure of the enclosed space according to the graded prevention and control strategy.

[0110] It should be noted that other corresponding descriptions of the functional units involved in the combustion and explosion risk prediction device based on the adaptive fractal dimension of the working conditions provided in this application embodiment can be found in the following references. Figure 1 The corresponding description in [the document] will not be repeated here.

[0111] Based on the above, Figure 1As illustrated in the example, correspondingly, embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described... Figure 1 The example method shown.

[0112] Based on the above, Figure 1 As illustrated, correspondingly, embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the above-described... Figure 1 The example method shown.

[0113] Based on this understanding, the technical solutions of the embodiments of this application can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0114] Based on the above, Figure 1 The method shown, and Figure 5 To achieve the above objectives, the present application also provides an electronic device, comprising a storage medium and a processor; the storage medium for storing a computer program; and the processor for executing the computer program to implement the above-described virtual device embodiments. Figure 1 The method shown.

[0115] Optionally, the aforementioned electronic device may also include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, an input unit, etc.

[0116] Those skilled in the art will understand that the physical device structure provided in this embodiment does not constitute a limitation on the physical device, and may include more or fewer components, or combine certain components, or have different component arrangements.

[0117] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0118] Through the above description of the embodiments, those skilled in the art will clearly understand that this application can be implemented using software plus necessary general-purpose hardware platforms, or it can be implemented in hardware. The embodiments of this application can determine the fractal dimension and the critical radius of flame acceleration based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions. Based on the fractal dimension and the critical radius of flame acceleration, the flame surface area and laminar flame velocity corresponding to the combustible mixture are corrected. Finally, an overpressure prediction curve is generated based on the flame surface area and laminar flame velocity using an overpressure prediction model. By introducing a fractal dimension and critical radius that adaptively vary with turbulence intensity, the degree of flame surface wrinkling and the initial conditions of flame acceleration are dynamically expressed in the overpressure prediction model, significantly improving the prediction accuracy of overpressure in confined space gas combustion and explosion, and broadening the applicable range of conditions.

[0119] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the term "comprising" or any other variations thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0120] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for predicting the risk of explosion based on the self-adaptive fractal dimension of the working condition, characterized in that, include: Acquire environmental monitoring data and spatial structure data of confined spaces; Based on the environmental monitoring data and spatial structure data, the flow field conditions within the enclosed space are determined. These flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration. The fractal dimension and the critical radius for flame acceleration adaptively change with the turbulence intensity of the flow field conditions. Using the overpressure prediction model, the combustion and explosion overpressure prediction results of the combustible mixture in the confined space are determined based on the fractal dimension and the critical radius of flame acceleration. Based on the predicted overpressure of the combustion and explosion, the combustion and explosion risk level corresponding to the confined space is determined.

2. The method of claim 1, wherein, The method of using an overpressure prediction model to determine the combustion and explosion overpressure prediction result of the combustible mixture in the confined space based on the fractal dimension and the critical radius of flame acceleration includes: The fractal dimension and critical radius for flame acceleration are determined based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions. Based on the fractal dimension and the critical radius for flame acceleration, the flame surface area and laminar flame velocity corresponding to the combustible mixture are corrected. Using the overpressure prediction model, an overpressure prediction curve is generated based on the flame surface area and laminar flame velocity, which serves as the combustion and explosion overpressure prediction result.

3. The method of claim 2, wherein, The determination of the fractal dimension and the critical radius for flame acceleration based on the turbulence intensity and laminar flame velocity corresponding to the flow field conditions includes: Using a preset empirical formula, the fractal dimension and the critical radius for flame acceleration are calculated based on the turbulence intensity and the laminar flame velocity. The preset empirical formula is constructed based on the empirical fitting index and the empirical correction coefficient.

4. The method of claim 2, wherein, The step of correcting the flame surface area and laminar flame velocity corresponding to the combustible mixture based on the fractal dimension and the critical radius for flame acceleration includes: The flame surface area corresponding to the combustible mixture is determined based on the critical radius of flame acceleration and the fractal dimension. Based on the pressure correction coefficient and temperature correction coefficient corresponding to the confined space, the initial laminar flame velocity in the environmental monitoring data is corrected to determine the laminar flame velocity corresponding to the combustible mixture.

5. The method of claim 2, wherein, The process of generating an overpressure prediction curve using the overpressure prediction model based on the flame surface area and laminar flame velocity includes: Based on the environmental monitoring data and spatial structure data, the initial monitoring data corresponding to the enclosed space is determined; The initial monitoring data is input into the overpressure prediction model. Based on the flame surface area and laminar flame velocity, the overpressure prediction model is solved by numerical integration. The combustion and explosion overpressure at each time step is calculated to generate the overpressure prediction curve.

6. The method of claim 2, wherein, The step of determining the explosion risk level of the confined space based on the explosion overpressure prediction result includes: Extract the peak overpressure of the confined space from the predicted overpressure of the combustion and explosion; The critical overpressure of the confined space is determined based on the spatial structure data, and the risk classification rules corresponding to the confined space are determined based on the critical overpressure. According to the risk classification rules, the explosion risk level corresponding to the overpressure peak of the confined space is determined.

7. The method of claim 1, wherein, The method further includes: Determine the graded prevention and control strategy corresponding to the explosion risk level, and adjust the spatial structure of the enclosed space according to the graded prevention and control strategy.

8. A device for predicting the risk of explosion based on the self-adaptive fractal dimension of the working condition, characterized in that, include: The acquisition module is configured to acquire environmental monitoring data and spatial structure data of the enclosed space. The first determining module is configured to determine the flow field conditions within the enclosed space based on the environmental monitoring data and spatial structure data. The flow field conditions are used to determine the fractal dimension and the critical radius for flame acceleration. The fractal dimension and the critical radius for flame acceleration adapt to the turbulence intensity of the flow field conditions. The prediction module is configured to use an overpressure prediction model to determine the combustion and explosion overpressure prediction result of the combustible mixture in the confined space based on the fractal dimension and the critical radius of flame acceleration. The second determining module is configured to determine the explosion risk level corresponding to the confined space based on the explosion overpressure prediction result.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

10. An electronic device comprising a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 7.

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