Dynamics simulation method suitable for fire extinguishing bag cluster air drop

Abstract

The invention discloses a dynamics simulation method suitable for fire extinguishing bag cluster air drop, and the method comprises the steps: building a fire extinguishing bag physical model, discretizing the physical model, simulating a fire extinguishing bag cluster, simulating and predicting real working conditions, and the method can accurately simulate the drop point distribution of fire extinguishing bags, optimize the fire extinguishing resource configuration, and improve the fire extinguishing efficiency. The putting strategy of the fire extinguishing bags can adapt to changeable meteorological environments, the putting strategy of the fire extinguishing bags is dynamically adjusted according to real-time meteorological data and fire scene changes, so that the fire extinguishing action can quickly respond to the changes of site conditions, and the flexibility and effectiveness of the fire extinguishing action are greatly improved through the real-time adjusting capacity; and powerful decision support is provided for firefighters.

Description

Technical Field

[0001] The present invention relates to the field of fire fighting technology, and specifically to a dynamic simulation method suitable for cluster airdrop of fire extinguishing bags by simulating the airdrop process of fire extinguishing bags to provide technical support for auxiliary decision-making and effect prediction of unmanned aerial vehicle fire extinguishing tasks, thereby improving fire extinguishing efficiency and safety. Background Art

[0002] In the prior art, the placement of fire extinguishing bags mainly relies on manual operation and simple physical calculations, and these methods have certain limitations in actual operation. For example, Chinese patent CN 118105652 A discloses a self-filling fire extinguishing bag group, which is composed of self-filling fire extinguishing bags, and the self-filling fire extinguishing bag includes a bag body with an internal space, and a fire extinguishing agent is encapsulated in the internal space, wherein the fire extinguishing bag group includes at least two, preferably at least four self-filling fire extinguishing bags, and adjacent self-filling fire extinguishing bags share a sealing edge and are connected to each other through the sealing edge, through holes are arranged in the sealing edge, and a center hole is arranged at or near the geometric center of the self-filling fire extinguishing bag group. In addition, a hydrophilic-hydrophobic gradient coating can be arranged on the bag body, so that the bag body is constructed to be one-way permeable from the outside of the bag body to the inside of the bag body. According to the self-filling fire extinguishing bag group, it is easy to form a continuous flame retardant belt and improve the fire extinguishing efficiency. In addition, due to its one-way water permeability, it can meet the flexible operation requirements of the fire-fighting aircraft and effectively avoid the overflow and leakage of the fire extinguishing agent. By making the fire extinguishing bag group with polylactic acid material, it meets the environmental protection requirements for forest fire fighting. In the actual operation process of this technical solution, although the fire extinguishing bag is operated in the form of a fire extinguishing bag group to achieve the fire extinguishing function, it is often difficult for the delivery personnel to accurately assess the number and delivery location of the required fire extinguishing bags, resulting in waste of resources or insufficient coverage. In addition, the existing delivery method fails to fully consider complex meteorological conditions, such as changes in wind speed and wind direction, which have a significant impact on the distribution of the landing points of the fire extinguishing bags.

[0003] Another example is a locomotive-coordinated dangerous area firefighting and rescue method based on image processing disclosed in Chinese patent CN 118012049A, which includes a rescue helicopter and an intelligent fire truck. The rescue helicopter is equipped with a pan-tilt image processing camera, a pan-tilt infrared imaging camera, a bomb thrower, an image transmission and communication module, an electric pulley block, and a laser ranging module. The intelligent fire truck is equipped with a pan-tilt image processing camera, a mechanical arm, an all-terrain track wheel, a ranging obstacle avoidance module, a bomb thrower, a hazardous goods temporary storage compartment, and an image transmission and communication module; the rescue helicopter is used to make an overall judgment on the fire scene, send the intelligent fire truck to the fire scene at a specific location, plan the aerial route and transmit the information to the intelligent fire truck and the ground terminal, transport hazardous materials and recover the intelligent fire truck, and complete the firefighting task of the main channel. Although this technical solution provides advanced aerial monitoring and guidance capabilities for the entire rescue process through a variety of sensors and equipment, there are still the following problems and shortcomings in the delivery process:

[0004] First, the placement accuracy is insufficient. Due to the lack of accurate simulation and prediction, the distribution of the fire extinguishing bags often does not meet expectations, resulting in poor fire extinguishing effects.

[0005] Second, unreasonable resource allocation and inability to accurately assess the number of fire extinguishing bags required may lead to waste of resources or failure to effectively control the fire;

[0006] Third, ignoring the impact of meteorological conditions: the existing delivery method fails to fully consider the impact of meteorological conditions such as wind speed and wind direction on the landing point of the fire extinguishing bag, resulting in unstable delivery effect;

[0007] Fourth, there is a lack of real-time adjustment capabilities. During the deployment process, existing technologies cannot be dynamically adjusted according to real-time meteorological data and changes in the fire scene, which reduces the flexibility and efficiency of firefighting.

[0008] One of the important reasons for the above problems and shortcomings is that the existing technology lacks in-depth dynamic analysis and simulation of the fire extinguishing bag delivery process. The fire extinguishing bag is affected by multiple forces during the delivery process, including gravity, air resistance and lift, etc. The interaction of these forces is complex and difficult to accurately calculate using traditional methods. In addition, the existing technology fails to take into account the interaction between meteorological conditions and fire extinguishing bags, resulting in the inability to accurately predict the distribution of the landing points of the fire extinguishing bags. Therefore, the existing technology has obvious deficiencies in the accuracy of fire extinguishing bag delivery, the rationality of resource allocation, and the adaptability to meteorological conditions. There is an urgent need for a simulation method to improve the efficiency and effectiveness of fire extinguishing bag delivery. Summary of the invention

[0009] Purpose of the invention: In order to solve the shortcomings of the prior art, the present invention provides a dynamic simulation method suitable for the airdrop of cluster fire extinguishing bags. The method fully considers the influence of meteorological conditions such as wind speed and wind direction during the release of fire extinguishing bags to improve the stability, reliability and accuracy of the release effect. When multiple fire extinguishing bags are released at the same time, how to consider the mutual influence between the fire extinguishing bags, that is, the clustering effect, so as to more accurately predict the actual distribution of landing points, optimize resource allocation, provide auxiliary decision support, and optimize the airdrop process of fire extinguishing bags in a scientific and precise manner, thereby improving the effect and efficiency of forest fire fighting.

[0010] Technical solution: In order to achieve the above objectives, the present invention provides a dynamic simulation method for cluster airdrop of fire extinguishing bags, the specific steps of which include:

[0011] Step 1: Establish the physical model of the fire extinguishing bag

[0012] After analyzing the gravity, air resistance and lift that the fire extinguishing bag is subjected to during the delivery process, the fire extinguishing bag is regarded as a single particle. Based on the single particle three-degree-of-freedom equation in space, the dynamic equation of the fire extinguishing bag is established to describe its movement in space. In order to make the model more flexible to introduce the lift and drag coefficient, the dynamic equation is dimensionless processed using characteristic length, characteristic speed and characteristic time to simplify the calculation and enhance the universality of the model. The physical model of the fire extinguishing bag is established to simulate the movement characteristics of the fire extinguishing bag during the delivery process; the dimensionless processing simplifies the equation and improves the calculation efficiency. This processing not only helps to reveal the essence of the physical process, but also reduces the numerical error in the calculation.

[0013] Step 2: Discretization of physical models

[0014] In order to enable the physical model to process data on the computer, the continuous dynamic model is discretized in the time dimension. This process involves dividing time into multiple discrete intervals and calculating the state matrix s and control matrix u of the fire extinguishing bag in each interval. Through this discretization process, the model can provide detailed state information of the fire extinguishing bag at each discrete moment, laying the foundation for subsequent simulation and analysis.

[0015] Based on the actual physical process of the fire extinguishing bag, the control quantity, input quantity and initial conditions of the model are determined to conform to the actual physical situation. According to the actual physical situation, the range of each physical parameter is set. The falling trajectory and landing point of the fire extinguishing bag at a specific drop height are solved by using the discretization method. The continuous physical model is converted into a discrete form suitable for computer processing, so as to numerically solve the physical model of the fire extinguishing bag.

[0016] Step 3: Fire extinguishing bag cluster simulation

[0017] After obtaining the physical model after discretization, the process of simultaneously placing multiple fire-extinguishing bags is simulated. Given the initial height and placement speed, the physical model will generate the state matrix and control matrix corresponding to each fire-extinguishing bag according to the preset quantity. By simulating the placement process, the corresponding matrix value at each discrete moment is recorded and stored, and the placement trajectory, speed change and mutual aggregation effect of the fire-extinguishing bags are obtained. The simulation results will provide important data for analyzing the landing distribution and coverage effect of the fire-extinguishing bags.

[0018] Step 4: Simulation and prediction of actual working conditions

[0019] Python is used to perform simulation according to the basic test conditions. Based on the simulation results, the distribution area and density of the fire extinguishing bags are obtained and compared with the experimental data to verify the accuracy of the model. The verified model is used to predict the deployment of fire extinguishing bags under actual flight conditions. The final landing speed of the fire extinguishing bag cluster, the time required for landing, the center position of the cluster landing, and the area covered by the fire extinguishing bags are calculated and analyzed to generate a fire extinguishing bag landing distribution map.

[0020] As a further preferred embodiment of the present invention, in step 1, the calculation process of establishing the single-particle space three-degree-of-freedom equation of the fire extinguishing bag is as follows:

[0021] Assume that the main forces on the fire extinguishing bag after being released include gravity, air resistance and lift. In order to simplify the problem, only the uniform direct wind in the horizontal direction is considered, and the changes in wind speed and wind direction in the vertical direction are ignored. The main assumptions are as follows:

[0022] (1) After the fire extinguishing bag is placed, its shape and mass distribution remain unchanged;

[0023] (2) Uniform air density;

[0024] (3) The acceleration due to gravity g is a constant;

[0025] (4) The horizontal wind is uniform direct current, that is, the wind speed W and wind direction remain unchanged;

[0026] (5) The movement of the fire extinguishing bag can be decomposed into components in three directions: X, Y, and Z;

[0027] Based on the above assumptions, the single particle kinetic equation can be obtained as follows:

[0028]

[0029] Where, m: the mass of the fire extinguishing bag, U: the speed of the fire extinguishing bag relative to the air, airspeed, The speed change rate of the fire extinguishing bag relative to the air, γ: the angle between the fire extinguishing bag speed and the horizontal plane, the pitch angle, The rate of change of the angle γ, ψ: the yaw angle of the fire extinguishing bag in the horizontal plane, The rate of change of the yaw angle ψ, D: drag, opposite to the airspeed direction of the fire extinguishing bag, L: lift, perpendicular to the airspeed direction of the fire extinguishing bag, φ: roll angle, X, Y, Z: coordinates of the fire extinguishing bag in space, The velocity components of the fire extinguishing bag in the X, Y, and Z directions, ground speed;

[0030] As a further preferred embodiment of the present invention, in step 1, the process of calculating the dimensionless processing of the kinetic model is as follows:

[0031] When performing dimensionless processing of dynamic models, appropriate characteristic quantities are usually selected to simplify the equations, making the coefficients and variables in the equations dimensionless, thereby facilitating the introduction of lift and drag coefficients and simplifying calculations and analysis. Dimensionless processing not only helps to reveal the essence of physical processes, but also reduces numerical errors in calculations and improves calculation efficiency.

[0032] Select characteristic quantity: characteristic velocity Feature distance Characteristic time t c =V c / g.

[0033] Based on the characteristic quantity, the dynamic model is dimensionlessly processed.

[0034]

[0035] Written in matrix form, that is:

[0036]

[0037] Among them, the dimensionless variable is, dimensionless airspeed v = U / V c , dimensionless wind speed w = W / V c , dimensionless spatial position x = X / L c ,y=Y / L c 、z=Z / L c , and dimensionless time τ = t / t c , lift coefficient C L =L / q ∞ , drag coefficient C D =D / q ∞ , It is dynamic pressure;

[0038] As a further preferred embodiment of the present invention, in step 2, the state quantity matrix s includes the position and speed information of the fire extinguishing bag.

[0039] As a further preferred embodiment of the present invention, in step 2, the control matrix u includes control inputs that affect the movement of the fire extinguishing bag, such as lift coefficient and roll angle.

[0040] As a further preferred embodiment of the present invention, in step 2, the calculation process of the discretization processing of the physical model is as follows:

[0041] (a) Based on the actual physical process of the fire extinguishing bag, determine the control quantity and input quantity in the model: In the dynamic system, the state quantity matrix s and the control matrix u are used to describe the system state and control input. For the above single particle dynamics model, the following state quantity matrix and control matrix are defined:

[0042]

[0043] (b) Determine the initial conditions of the model to match actual physical reality:

[0044] The initial value matrix,

[0045]

[0046] (c) According to the actual physical situation, set the range of each physical parameter:

[0047]

[0048] -φ max ≤φ≤φ max

[0049] (d) Using the time stepping method, the falling trajectory and landing point of the fire extinguishing bag at a specific drop height are solved. According to the recursive relationship, the discretization relationship can be obtained as follows:

[0050]

[0051] s N t N The state quantity at the moment, s N-1 t N-1 The state quantity at the time, Δt = t N -t N-1 is the time difference between two moments, is the state quantity change function;

[0052]

[0053] As a further preferred embodiment of the present invention, in step three, the clustering effect is based on standard clustering effect experimental data to physically correct the control variable range.

[0054] As a further preferred embodiment of the present invention, the control variable and φ max The value of is determined according to the aggregation effect experiment.

[0055] As a further preferred embodiment of the present invention, the control variable and φmax Function of the change in aggregation effect:

[0056]

[0057] R 2 =0.996

[0058] The coverage area can be modified by setting the control quantity φ, defining φ max is the horizontal dispersion strength, by adjusting φ max The size of is consistent with the test results, and the quadratic function is used for fitting to obtain:

[0059] φ max =-2.2804×10 -6 h 2 +1.1352×10 -3 h+8.3602×10 -1

[0060] R 2 =0.941

[0061] Due to the different landing aggregation states, there are differences in the lift coefficients when landing. The landing lift coefficients corresponding to different launch heights are inconsistent, and the aggregation effect affects the aerodynamic force.

[0062] As a further preferred embodiment of the present invention, the control variable includes the time required for the equilibrium speed, and the time of free fall is analyzed, and it is easy to obtain This is the shortest falling time, and the actual falling time of the fire extinguishing bag is longer than t f ,

[0063] Therefore, if t f Within the time, the speed of the fire extinguishing bag affected by the resistance has reached equilibrium, so during the actual longer time of the fire extinguishing bag falling, the fire extinguishing bag has also reached equilibrium, and the model can be simplified, that is:

[0064]

[0065] Assume that the integration time is the free fall time t f , then, if in the integral free fall time t f Within the time, the speed of the fire extinguishing bag has reached a balance, and the gravity and lift have also reached a balance.

[0066] Beneficial effects: Compared with the prior art, the dynamic simulation method for cluster airdrop of fire extinguishing bags described in the present invention has the following advantages:

[0067] (1) Accurate simulation of the distribution of fire extinguishing bag drop points: By establishing a single-particle dynamics model and performing dimensionless and discretization processing on it, the motion trajectory of the fire extinguishing bag in a complex wind field can be accurately simulated. This simulation not only takes into account the lift resistance of the fire extinguishing bag itself, but also takes into account the aggregation effect between the fire extinguishing bags, so that the simulation results are closer to the actual situation. Compared with the existing technology, this accurate simulation capability significantly improves the accuracy of fire extinguishing bag placement, ensures that the fire extinguishing agent can evenly cover the target area, and effectively improves the fire extinguishing efficiency;

[0068] (2) Optimize the allocation of fire-fighting resources: Accurately evaluate the number of fire-fighting bags required in different fire scenarios based on simulation results, thereby achieving optimal allocation of resources. This optimization not only avoids waste of resources, but also ensures the most effective fire-fighting coverage when resources are limited. Compared with existing technologies, scientific calculations replace rough estimates based on experience, making resource allocation more reasonable and efficient.

[0069] (3) Adaptability to changing weather conditions: The simulation process fully considers the changes in weather conditions such as wind speed and wind direction, so that the deployment strategy of fire extinguishing bags can adapt to the changing weather environment. This adaptability is lacking in the existing technology. It makes the deployment of fire extinguishing bags no longer restricted by specific weather conditions, improves the flexibility and success rate of fire fighting operations, and provides a reliable deployment strategy even when the wind speed and wind direction change greatly, ensuring that the fire extinguishing bags can effectively cover the fire scene.

[0070] (4) Provide decision-making assistance and real-time adjustment capabilities: The simulation tool can provide real-time decision-making assistance for firefighters. Through the simulation results, firefighters can intuitively understand the expected landing point and coverage of the fire extinguishing bag, so as to formulate a more accurate fire-fighting plan. In addition, this technical solution also allows the dynamic adjustment of the fire extinguishing bag delivery strategy according to real-time meteorological data and changes in the fire scene, so that the fire-fighting operation can quickly respond to changes in the on-site situation. Compared with the existing technology, this real-time adjustment capability greatly improves the flexibility and effectiveness of the fire-fighting operation and provides strong decision-making support for firefighters. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1 It is a schematic diagram of the definition of physical quantities related to the three-degree-of-freedom equation of a single-particle space of a fire extinguishing bag;

[0072] Figure 2 This is the fire extinguishing bag falling speed analysis diagram;

[0073] Figure 3 for Schematic diagram of changes with release height;

[0074] Figure 4 is φ maxSchematic diagram of changes with release height;

[0075] Figure 5 This is a simulation diagram of the landing point distribution results. DETAILED DESCRIPTION

[0076] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments.

[0077] The present invention discloses a dynamic simulation method for cluster airdrop of fire extinguishing bags, the steps of which include: establishing a physical model of fire extinguishing bags, discretizing the physical model, simulating and simulating clusters of fire extinguishing bags and predicting actual working conditions. The method can accurately simulate the distribution of fire extinguishing bag drop points, optimize the allocation of fire extinguishing resources, and the fire extinguishing bag delivery strategy can adapt to changing meteorological environments, and effectively provide auxiliary decision-making and real-time adjustment capabilities.

[0078] Example 1

[0079] Step 1: Establish the physical model of the fire extinguishing bag

[0080] First, after analyzing the gravity, air resistance and lift that the fire extinguishing bag is subjected to during the release process, the fire extinguishing bag is regarded as a single particle. Based on the single particle space three-degree-of-freedom equation, the dynamic equation of the fire extinguishing bag is established to describe its movement in space. In order to make the model more flexible to introduce the lift and drag coefficient, the calculation process of the single particle space three-degree-of-freedom equation of the fire extinguishing bag is established as follows:

[0081] Assume that the main forces on the fire extinguishing bag after being released include gravity, air resistance and lift. In order to simplify the problem, only the uniform direct wind in the horizontal direction is considered, and the changes in wind speed and wind direction in the vertical direction are ignored. The main assumptions are as follows:

[0082] (1) After the fire extinguishing bag is placed, its shape and mass distribution remain unchanged;

[0083] (2) Uniform air density;

[0084] (3) The acceleration due to gravity g is a constant;

[0085] (4) The horizontal wind is uniform direct current, that is, the wind speed W and wind direction remain unchanged;

[0086] (5) The movement of the fire extinguishing bag can be decomposed into components in three directions: X, Y, and Z;

[0087] Based on the above assumptions, the single particle kinetic equation can be obtained as follows:

[0088]

[0089] Where, m: the mass of the fire extinguishing bag, U: the speed of the fire extinguishing bag relative to the air, airspeed, The speed change rate of the fire extinguishing bag relative to the air, γ: the angle between the fire extinguishing bag speed and the horizontal plane, the pitch angle, The rate of change of the angle γ, ψ: the yaw angle of the fire extinguishing bag in the horizontal plane, ψ: the rate of change of the yaw angle ψ, D: drag, opposite to the airspeed direction of the fire extinguishing bag, L: lift, perpendicular to the airspeed direction of the fire extinguishing bag, φ: roll angle, X, Y, Z: the coordinates of the fire extinguishing bag in space, The velocity components of the fire extinguishing bag in the X, Y, and Z directions, the ground speed, and the definitions of related physical quantities are as follows: Figure 1 shown.

[0090] Then, the dynamic equations were dimensionally processed using characteristic length, characteristic velocity, and characteristic time to simplify the calculation and enhance the universality of the model. A physical model of the fire extinguishing bag was established to simulate the motion characteristics of the fire extinguishing bag during the release process. The dimensionless processing simplified the equations and improved the calculation efficiency. This processing not only helps to reveal the essence of the physical process, but also reduces the numerical errors in the calculation.

[0091] The calculation process of dimensionless treatment of the kinetic model is as follows:

[0092] When performing dimensionless processing of dynamic models, appropriate characteristic quantities are usually selected to simplify the equations, making the coefficients and variables in the equations dimensionless, thereby facilitating the introduction of lift and drag coefficients and simplifying calculations and analysis. Dimensionless processing not only helps to reveal the essence of physical processes, but also reduces numerical errors in calculations and improves computational efficiency.

[0093] Select characteristic quantity: characteristic velocity Feature distance Characteristic time t c =V c / g.

[0094] Based on the characteristic quantity, the dynamic model is dimensionlessly processed.

[0095]

[0096] Written in matrix form, that is,

[0097]

[0098] Among them, the dimensionless variable is, dimensionless airspeed v = U / V c , dimensionless wind speed W = W / V c , dimensionless spatial position x = X / L c ,y=Y / L c 、z=Z / L c , and dimensionless time τ = t / t c , lift coefficient C L =L / q ∞, drag coefficient C D =D / q ∞ , It is dynamic pressure;

[0099] In this embodiment, the basic physical quantities of the fire extinguishing bag are:

[0100]

[0101]

[0102] From this calculation, the relevant eigenvalues ​​are:

[0103]

[0104] Step 2: Discretization of physical models

[0105] In order to enable the physical model to process data on the computer, the continuous dynamic model is discretized in the time dimension. This process involves dividing time into multiple discrete intervals and calculating the state matrix s and control matrix u of the fire extinguishing bag in each interval; the state matrix s contains the position and velocity information of the fire extinguishing bag, and the control matrix u contains the control inputs that affect the movement of the fire extinguishing bag, such as the lift coefficient and the roll angle. Through this discretization process, the model can provide detailed state information of the fire extinguishing bag at each discrete moment, laying the foundation for subsequent simulation and analysis;

[0106] The calculation process of the discretization of the physical model is as follows:

[0107] (a) Based on the actual physical process of the fire extinguishing bag, determine the control quantity and input quantity in the model:

[0108] In a dynamic system, the state matrix s and control matrix u are used to describe the system state and control input. For the above single-particle dynamics model, the following state matrix and control matrix are defined:

[0109]

[0110] (b) Determine the initial conditions of the model to match actual physical reality:

[0111] The initial value matrix,

[0112]

[0113] (c) According to the actual physical situation, set the range of each physical parameter:

[0114]

[0115] -φ max ≤φ≤φmax

[0116] (d) Using the time stepping method, the falling trajectory and landing point of the fire extinguishing bag at a specific drop height are solved. According to the recursive relationship, the discretization relationship can be obtained as follows:

[0117]

[0118] s N t N The state quantity at the moment, s N-1 t N-1 The state quantity at the time, Δt = t N -t N-1 The time difference between two moments. is the state quantity change function,

[0119]

[0120] Step 3: Fire extinguishing bag cluster simulation

[0121] After obtaining the physical model after discretization, the process of simultaneously placing multiple fire-extinguishing bags is simulated. Given the initial height and placement speed, the physical model will generate the state matrix and control matrix corresponding to each fire-extinguishing bag according to the preset quantity. By simulating the placement process, the corresponding matrix value at each discrete moment is recorded and stored, and the placement trajectory, speed change and mutual aggregation effect of the fire-extinguishing bags are obtained. The simulation results will provide important data for analyzing the landing distribution and coverage effect of the fire-extinguishing bags.

[0122] According to experimental data, different initial heights correspond to different landing aggregation states. When the drop height is low, the distance between the fire extinguishing bags is small when they land; when the drop height is high, the distance between the fire extinguishing bags is large when they land. If the landing speed is known and it is assumed that the fire extinguishing bags have reached a balance between gravity and aerodynamic lift when they land, the lift coefficient when they land can be calculated.

[0123] Given that the weight is 0.27 kg, the characteristic area is 0.08 × 0.165 = 0.0132 m 2 According to the balance of gravity and lift, we can get mg = 0.5ρV 2 SC L ; From this we can see that the lift coefficient is C L =mg / 0.5ρV 2 S.

[0124] Calculations show that the lift coefficients at different landing heights are different. Due to the different landing aggregation states, the lift coefficients at landing are different, indicating that the aggregation effect affects the aerodynamic force.

[0125] The above inference is valid only if the fire extinguisher bag has reached a balance between gravity and aerodynamic lift when it lands. Figure 2 As shown, this problem can be transformed into whether the speed of the fire extinguishing bag no longer changes at the end of the landing. If the speed of the fire extinguishing bag no longer changes, it means that the fire extinguishing bag has reached a balance between gravity and aerodynamic lift.

[0126] It takes time to reach equilibrium speed. By analyzing the time of free fall, we can easily get This is the shortest falling time, and the actual falling time of the fire extinguishing bag is longer than t f , therefore, if t f Within the time, the speed of the fire extinguishing bag affected by the resistance has reached equilibrium, so during the actual longer time of the fire extinguishing bag falling, the fire extinguishing bag has also reached equilibrium, and the model can be simplified, that is:

[0127]

[0128] The above equation can be solved analytically and numerically. This report adopts the numerical solution method, assuming that the integration time is the free fall time t f , then, if in the integral free fall time t f If the speed of the fire extinguishing bag is close to the speed measured in the experiment, the speed is considered to be balanced.

[0129] The calculated results are shown in Table 1. It can be seen from Table 1 that the simulation results are close to the experimental results. Therefore, during the free fall time, the speed of the fire extinguishing bag has reached equilibrium, and the gravity and lift have also reached equilibrium. Therefore, the aggregation effect exists, which further affects the actual lift coefficient of a single fire extinguishing bag at different positions.

[0130] Table 1. Velocity simulation of free fall volume integral over time

[0131]

[0132] Then, the lift coefficient in the original code is optimized, and the results are shown in Table 2. The simulated final velocity is basically consistent with the experimentally measured final velocity.

[0133] Table 2 Simulation of final velocity and falling time

[0134]

[0135] Thus, we get the control variable and φ max A function that changes with height (clustering effect), such as Figure 3 Shown Schematic diagram of changes with release height;

[0136]

[0137] R 2 =0.996

[0138] The coverage area can be modified by setting the control quantity φ, defining φ max is the horizontal dispersion strength, by adjusting φ max The size of the test results is consistent with the test results, such as Figure 4 Shown is φ max The schematic diagram of the change with the release height is fitted with a quadratic function to obtain:

[0139] φ max =-2.2804×10 -6 h 2 +1.1352×10 -3 h+8.3602×10 -1

[0140] R 2 =0.941;

[0141] Due to the different landing aggregation states, the lift coefficients at landing are different. The landing lift coefficients corresponding to different launch heights are inconsistent, and the aggregation effect affects the aerodynamic force.

[0142] Step 4: Simulation and prediction of actual working conditions

[0143] Python is used to perform simulation according to the basic test conditions. Based on the simulation results, the distribution area and density of the fire extinguishing bags are obtained and compared with the experimental data to verify the accuracy of the model. The verified model is used to predict the deployment of fire extinguishing bags under actual flight conditions. The final landing speed of the fire extinguishing bag cluster, the time required for landing, the center position of the cluster landing, and the area covered by the fire extinguishing bags are calculated and analyzed to generate a fire extinguishing bag landing distribution map.

[0144] Four typical working conditions of the basic experiment were simulated, with the drop heights being 50m, 100m, 200m and 300m respectively. Figure 5 As shown in the figure, the distribution results of the fire extinguishing bag drop points at different heights are shown. It can be seen from the figure that the drop points are Gaussian in distribution, with high in the middle and low around. As the height increases, the drop points gradually disperse, the coverage area increases, and the coverage density decreases. These results are consistent with the experimental results.

[0145] The quantitative comparison of the simulation results and the experimental results is shown in Tables 3 and 4. The two key parameters, terminal velocity (Table 3) and coverage area (Table 4), are selected for comparison. As shown in Tables 3 and 4, the overall relative error between the theoretical simulation results and the experimental measurements is <10%. The relative error decreases with the increase of the drop height because the base of the relative error is larger. Comprehensively evaluated, the dynamic simulation model proposed in this study can have a good simulation effect on the landing of the fire extinguishing bag.

[0146] Table 3 Comparison of simulation results and experimental results of terminal velocity of fire extinguishing bag

[0147]

[0148] Table 4 Comparison of simulation results and experimental results of fire extinguishing bag landing area coverage

[0149]

[0150] The above is the data of fire extinguishing bag deployment under real flight conditions predicted by the model verified by actual operation.

[0151] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable technicians familiar with the technical field to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent transformation or modification made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. A dynamic simulation method suitable for cluster airdrop of fire extinguishing bags, characterized by: The specific steps of this method include: Step 1: Establish the physical model of the fire extinguishing bag After analyzing the gravity, air resistance and lift that the fire-extinguishing bag is subjected to during the delivery process, the fire-extinguishing bag is regarded as a single particle. Based on the single particle space three-degree-of-freedom equation, the dynamic equation of the fire-extinguishing bag is established. The dynamic equation is dimensionless using characteristic length, characteristic velocity and characteristic time to simplify the calculation and enhance the universality of the model. The physical model of the fire-extinguishing bag is established to simulate the motion characteristics of the fire-extinguishing bag during the delivery process. Step 2: Discretization of physical models In order to enable the physical model to be processed on a computer, the continuous dynamic model is discretized in the time dimension. This process involves dividing the time into multiple discrete intervals and calculating the state matrix s and control matrix u of the fire extinguishing bag in each interval. Step 3: Fire extinguishing bag cluster simulation After obtaining the physical model after discretization, the process of simultaneously placing multiple fire extinguishing bags is simulated. Given the initial height and placement speed, the physical model will generate the state matrix and control matrix corresponding to each fire extinguishing bag according to the preset quantity. By simulating the placement process, the corresponding matrix value at each discrete moment is recorded and stored, and the placement trajectory, speed change and mutual aggregation effect of the fire extinguishing bags are obtained. Step 4: Simulation and prediction of actual working conditions Python is used to perform simulation according to the basic test conditions. Based on the simulation results, the distribution area and density of the fire extinguishing bags are obtained and compared with the experimental data to verify the accuracy of the model. The verified model is used to predict the deployment of fire extinguishing bags under actual flight conditions. The final landing speed of the fire extinguishing bag cluster, the time required for landing, the center position of the cluster landing, and the area covered by the fire extinguishing bags are calculated and analyzed to generate a fire extinguishing bag landing distribution map.

2. A dynamic simulation method suitable for cluster airdrop of fire extinguishing bags according to claim 1, characterized in that: In step 1, the calculation process of establishing the single-particle space three-degree-of-freedom equation of the fire extinguishing bag is as follows: Assume that the main forces on the fire extinguishing bag after being released include gravity, air resistance and lift. In order to simplify the problem, only the uniform direct wind in the horizontal direction is considered, and the changes in wind speed and wind direction in the vertical direction are ignored. The main assumptions are as follows: (1) After the fire extinguishing bag is placed, its shape and mass distribution remain unchanged; (2) Uniform air density; (3) The acceleration due to gravity g is a constant; (4) The horizontal wind is uniform direct current, that is, the wind speed W and wind direction remain unchanged; (5) The movement of the fire extinguishing bag can be decomposed into components in three directions: X, Y, and Z; Based on the above assumptions, the single particle kinetic equation can be obtained as follows: Where, m: the mass of the fire extinguishing bag, U: the speed of the fire extinguishing bag relative to the air, airspeed, The speed change rate of the fire extinguishing bag relative to the air, γ: the angle between the fire extinguishing bag speed and the horizontal plane, the pitch angle, The rate of change of the angle γ, ψ: the yaw angle of the fire extinguishing bag in the horizontal plane, The rate of change of the yaw angle ψ, D: drag, opposite to the airspeed direction of the fire extinguishing bag, L: lift, perpendicular to the airspeed direction of the fire extinguishing bag, φ: roll angle, X, Y, Z: coordinates of the fire extinguishing bag in space, The velocity components of the fire extinguishing bag in the X, Y, and Z directions, and the ground speed.

3. A dynamic simulation method suitable for cluster airdrop of fire extinguishing bags according to claim 1, characterized in that: In step 1, the calculation process of dimensionless treatment of the kinetic model is as follows: When performing dimensionless processing of the dynamic model, appropriate characteristic quantities are usually selected to simplify the equations, making the coefficients and variables in the equations dimensionless, thereby facilitating the introduction of lift and drag coefficients and simplifying calculations and analysis. Select characteristic quantity: characteristic velocity Feature distance Characteristic time t c =V c / g; Based on the characteristic quantity, the dynamic model is dimensionlessly processed. Written in matrix form, that is, Among them, the dimensionless variable is, dimensionless airspeed v = U / V c , dimensionless wind speed w = W / V c , dimensionless spatial position x = X / L c ,y=Y / L c 、z=Z / L c , and dimensionless time τ = t / t c , lift coefficient C L =D / q ∞ , drag coefficient C D =D / q ∞ , It's dynamic pressure.

4. The method for dynamic simulation of cluster airdrop of fire extinguishing bags according to claim 1, characterized in that: In step 2, the state matrix s contains the position and speed information of the fire extinguishing bag.

5. The method for dynamic simulation of cluster airdrop of fire extinguishing bags according to claim 1 is characterized in that: In step 2, the control matrix u includes control inputs that affect the movement of the fire extinguishing bag, such as lift coefficient and roll angle.

6. The dynamic simulation method for cluster airdrop of fire extinguishing bags according to claim 1 is characterized in that: In step 2, the calculation process of the discretization of the physical model is as follows: (a) Based on the actual physical process of the fire extinguishing bag, determine the control quantity and input quantity in the model: In the dynamic system, the state quantity matrix s and the control matrix y are used to describe the system state and control input. For the above single particle dynamics model, the following state quantity matrix and control matrix are defined: (b) Determine the initial conditions of the model to match actual physical reality: The initial value matrix, (c) According to the actual physical situation, set the range of each physical parameter: -f max ≤φ≤φ max (d) Using the time stepping method, the falling trajectory and landing point of the fire extinguishing bag at a specific drop height are solved. According to the recursive relationship, the discretization relationship can be obtained as follows: s N t N The state quantity at the moment, s N-1 t N-1 The state quantity at the time, Δt = t N -t N-1 is the time difference between two moments, is the state quantity change function; 7. The method for dynamic simulation of cluster airdrop of fire extinguishing bags according to claim 1, characterized in that: In step three, the clustering effect is physically modified on the control variable range based on the standard clustering effect experimental data.

8. A dynamic simulation method for cluster airdrop of fire extinguishing bags according to claim 7, characterized in that: Control variables and φ max The value of is determined based on the aggregation effect experiment.

9. A dynamic simulation method for cluster airdrop of fire extinguishing bags according to claim 8, characterized in that: Control variables and φ max Function of the change in aggregation effect: R 2 ＝0.996 The coverage area can be modified by setting the control quantity φ, defining φ max is the horizontal dispersion strength, by adjusting φ max The size of is consistent with the test results, and the quadratic function is used for fitting to obtain: φ max =-2.2804×10 -6 h 2 +1.1352×10 -3 h+8.3602×10 -1 R 2 ＝0.941 Due to the different landing aggregation states, there are differences in the lift coefficients when landing. The landing lift coefficients corresponding to different launch heights are inconsistent, and the aggregation effect affects the aerodynamic force.

10. The method for dynamic simulation of cluster airdrop of fire extinguishing bags according to claim 7, characterized in that: The control variables include the time required for balancing the speed and analyzing the free fall time, which can be easily obtained This is the shortest falling time, and the actual falling time of the fire extinguishing bag is longer than t f ; Therefore, if t f Within the time, the speed of the fire extinguishing bag affected by the resistance has reached equilibrium, so during the actual longer time of the fire extinguishing bag falling, the fire extinguishing bag has also reached equilibrium, and the model can be simplified, that is: Assume that the integration time is the free fall time t f , then, if in the integral free fall time t f Within the time, the speed of the fire extinguishing bag has reached a balance, and the gravity and lift have also reached a balance.

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