High-pressure storage tank hydrogen leakage diffusion analysis method

Abstract

The invention relates to the technical field of gas leakage detection, in particular to a high-pressure storage tank hydrogen leakage diffusion analysis method which comprises the steps that physical characteristics of hydrogen and interaction between the hydrogen and the environment can be accurately captured by building a physical model, and diffusion processes in different leakage scenes are simulated; the sensors are deployed to monitor key index parameters in real time, so that the real-time performance and reliability of data are ensured, potential leakage events can be quickly responded, and the possibility and consequences of accidents are reduced; by establishing a mapping relation between real-time monitoring data and physical model parameters, the model parameters can be dynamically adjusted according to the real-time data, and an output result is optimized; through quantitative evaluation and risk level classification, corresponding risk early warning signals are generated, potential safety hazards can be found in time, and necessary emergency response measures can be taken. The device is used for solving the technical problems of high-pressure storage tank hydrogen leakage diffusion simulation and real-time monitoring and early warning.

Description

Technical Field

[0001] The invention relates to the technical field of gas leakage detection, and in particular to a method for analyzing the diffusion of hydrogen leakage in a high-pressure storage tank. Background Art

[0002] Gas leak detection technology is a technical means specifically used to identify, monitor and measure accidental gas leaks. By developing and applying various advanced sensors and detection technologies, the concentration and leakage of hydrogen can be monitored in real time, and potential leakage risks can be discovered and dealt with in a timely manner.

[0003] Currently, hydrogen storage management and control still faces some challenges, including the following aspects: the complexity of gas leakage and diffusion simulation. The diffusion process after gas leakage is affected by many factors, including the physical properties of the gas, environmental conditions, and the characteristics of the leakage source, which makes it quite complicated to accurately simulate this process; the effective use of real-time monitoring data is insufficient. Although modern sensor technology can monitor environmental parameters in real time, how to effectively use these data to respond to potential leakage incidents in a timely manner and optimize simulation results is still a problem that needs to be solved; the risk assessment and early warning capabilities are insufficient. The existing risk assessment methods may be too simple or traditional and cannot accurately reflect the true risk status of complex systems. For example, in the field of hydrogen energy, due to the characteristics of hydrogen such as low density and fast diffusion, traditional risk assessment methods may not be able to effectively capture the risks of leakage and diffusion, and lack timely and effective early warning responses; in response to these challenges, corresponding solutions and technical means need to be adopted to improve the accuracy of hydrogen leakage and diffusion analysis. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose a method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank, comprising:

[0007] Step 1: Construct a physical model, which specifically includes analyzing the hydrogen leakage and diffusion phenomenon, simulating the tank structure by analyzing the structural characteristics of the high-pressure storage tank, and setting leakage conditions in combination with different leakage scenarios;

[0008] Step 2: According to the constructed physical model, select the numerical algorithm of the finite volume method to solve; collect data on historical leakage events, use the data on historical leakage events to verify the accuracy of the model, and perform sensitivity analysis and adjustment on the model parameters;

[0009] Step 3: Deploy sensors to monitor key indicator parameters in real time, namely wind speed, wind direction, ambient temperature, ambient humidity and hydrogen concentration; integrate the key indicator parameters monitored in real time into the physical model as the input conditions of the model; establish a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters; further dynamically adjust the physical model parameters to optimize the output results of the model;

[0010] Step 4: Obtain output results based on the physical model that integrates real-time environmental monitoring data, use statistical analysis methods to quantitatively evaluate and classify the risk levels of the physical model output results, and generate corresponding risk warning signals.

[0011] Furthermore, the analysis of hydrogen leakage and diffusion phenomena includes physical property parameters and meteorological condition parameters related to the environment in which hydrogen is located. Among them, the physical property parameters are specifically density, diffusion coefficient, thermal conductivity and flammable limit; the structural characteristics of high-pressure storage tanks are specifically material, thickness, weld strength, and safety valve setting; different leakage scenarios include small hole leakage and crack leakage.

[0012] Furthermore, the process of selecting the numerical algorithm of the finite volume method for solving includes:

[0013] For the flow process of hydrogen in the high-pressure storage tank and after leakage, a set of equations is established based on the law of conservation of mass, the law of conservation of momentum and the law of conservation of energy. The specific process is as follows:

[0014] The mass conservation equation:

[0015]

[0016] Where ρ represents hydrogen density, t represents time, and u, v, and w represent the velocity components in the x, y, and z directions, respectively. The mass conservation equation shows that within a control volume, the rate of change of hydrogen mass with time is equal to the net mass flow rate of hydrogen flowing into and out of the control volume in all directions.

[0017] Momentum conservation equation:

[0018]

[0019] In the formula, P represents the internal pressure of hydrogen, μ represents the dynamic viscosity of hydrogen, and reflects the friction characteristics inside hydrogen; the left side of the momentum conservation equation represents the rate of change of hydrogen momentum in the x direction with time and the convection term caused by the velocity gradient, and the right side of the momentum conservation equation represents the hydrogen pressure gradient force and viscosity force;

[0020] Energy conservation equation:

[0021]

[0022] Where h is enthalpy; is the material derivative, and k is thermal conductivity, which indicates the ability of hydrogen to conduct heat; T is the temperature of hydrogen; τ UV Represents the stress tensor; U and V are index symbols used to represent the component index of the tensor, where the values ​​of U and V are x, y, and z, respectively representing the directions of the three coordinate axes; represents viscous dissipation, which is the process of converting mechanical energy into thermal energy due to the viscosity of the fluid. U is the U component of the velocity vector, Indicates the rate of change of velocity in the V direction.

[0023] Furthermore, the process of collecting data on historical leakage events, using the data on historical leakage events to verify the accuracy of the model, and performing sensitivity analysis and adjustment on the model parameters includes:

[0024] Assume that the data of historical hydrogen leakage events contains N leakage events, each of which includes leakage scene, environmental conditions, and leakage consequences;

[0025] The error indicator RMSE is used to evaluate the accuracy of the model:

[0026]

[0027] In the formula, represents the actual observed hydrogen concentration value of n0, represents the corresponding hydrogen concentration value obtained by model simulation, n0 represents the leakage event index, and N represents the number of leakage events;

[0028] Based on the RMSE results of the error index, the sensitivity analysis of the model parameters is carried out: by changing the value of each parameter one by one, observing the changes in the simulation results, calculating the change rate of the error index caused by the parameter change, and screening out sensitive parameters;

[0029] Use optimization algorithms to adjust the sensitive parameters of the model:

[0030] Using the gradient descent method, the error index RMSE is used as the optimization objective function and recorded as

[0031] The goal is to find a set of parameter values ​​such that the objective function minimize; among them, represents the vector containing all sensitive parameters to be adjusted;

[0032] Calculate the objective function with respect to the sensitive parameter vector Gradient The sensitive parameter update formula is:

[0033]

[0034] In the formula, represents the updated sensitive parameter, ι represents the learning rate, which controls the step size of each sensitive parameter update;

[0035] Sensitive parameters are updated by continuous iteration until the error index converges to the preset range. The new parameters obtained at this time are the optimized model parameters.

[0036] Furthermore, the process of deploying sensors to monitor key indicator parameters in real time includes:

[0037] In a certain area centered on the leakage source, multiple meteorological sensors are arranged in a grid or radial pattern, and the location coordinates of the meteorological sensors are defined as (xj, yj, zj); wherein j is the location coordinate index of the meteorological sensor, and j = 1, 2, ..., n1, where n1 represents the number of meteorological sensors;

[0038] The meteorological sensor measures wind speed, wind direction, ambient temperature and ambient humidity in real time. The wind speed, wind direction, ambient temperature and ambient humidity measured by the meteorological sensor in real time are marked respectively to obtain the wind speed wv j 、wind directionθ j 、Ambient temperature j And the ambient humidity j ;

[0039] Around the leak source, hydrogen concentration sensors are arranged at different heights and distances, and the position coordinates of the hydrogen concentration sensors are set as (x l ,y l ,z l ), wherein l is the position coordinate index of the hydrogen concentration sensor, and l=1, 2, ..., n2, n2 represents the number of hydrogen concentration sensors;

[0040] The hydrogen concentration sensor measures the hydrogen concentration at the location in real time, and marks the hydrogen concentration measured by the hydrogen concentration sensor in real time to obtain the hydrogen concentration Cl.

[0041] Furthermore, the key indicator parameters monitored in real time are integrated into the physical model as the input conditions of the model, including:

[0042] The key indicator parameters monitored by the sensor in real time are incorporated into the physical model as the input conditions for the model operation, as follows:

[0043] Step F1, integration of wind speed and wind direction:

[0044] For the entire leakage area, the wind speed and wind direction data measured by various meteorological sensors are combined, and the effective wind speed wv input into the model is determined by the weighted average method.eff and effective wind direction θ eff ; Among them, the calculation formula for effective wind speed is:

[0045]

[0046] Where W j is the weight coefficient, and When determining the weight coefficient, it is necessary to consider the distance between the sensor and the leak source. and the importance of the sensor location on the effect of hydrogen diffusion;

[0047] Convert the wind direction angle to a vector in Cartesian coordinates:

[0048]

[0049] In the formula, represents the wind direction vector;

[0050] The resultant wind direction vector for:

[0051]

[0052] Convert the resultant wind direction vector back to angle form to get the effective wind direction θ eff :

[0053]

[0054] In the formula, arctan represents the inverse tangent function, which is used to calculate the angle value corresponding to the synthetic wind direction vector. Represent the wind direction vector components in the y and x directions respectively;

[0055] Step F2, integration of temperature and humidity:

[0056] The effective temperature et is calculated using the weighted average method eff and effective humidity eh eff :

[0057]

[0058] Step F3, integration of hydrogen concentration:

[0059] In order to obtain the overall hydrogen concentration distribution trend of the leakage area, the data of each hydrogen concentration sensor are interpolated: the leakage area is divided into multiple grid cells, and for each grid cell center position (xgc, ygc, zgc), the hydrogen concentration C (xgc, ygc, zgc) at the position is calculated by the distance weighted inverse interpolation method;

[0060] Set the m hydrogen concentration sensors closest to the center position of the grid unit (xgc, ygc, zgc) to be numbered K1, K2, ..., K m , their distances from the center of the grid cell (xgc, ygc, zgc) are but:

[0061]

[0062] Wherein, i represents the hydrogen concentration sensor index, and i=1, 2,…, m.

[0063] Furthermore, a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters is established, and the process of further dynamically adjusting the physical model parameters includes:

[0064] Establish the mapping relationship between wind speed, wind direction and meteorological condition parameters:

[0065] Set the convection velocity vector in the model

[0066] The effective wind speed wv eff and effective wind direction θ eff Mapping into the model, we get:

[0067]

[0068] In the formula, They represent the components of the convection velocity vector in the model in the x and y directions respectively;

[0069] Establish a mapping relationship between temperature and physical characteristic parameters;

[0070] Establish the mapping relationship between humidity and physical characteristic parameters;

[0071] The hydrogen concentration distribution output by the model is defined as Compare with the actual hydrogen concentration distribution C(xgc,ygc,zgc) obtained by interpolating the hydrogen concentration sensor data;

[0072] Establish the error function E:

[0073]

[0074] In the formula, υ represents the total volume of the leakage area, and dυ represents the small change in the total volume;

[0075] According to the error function, an adaptive adjustment strategy is used to dynamically adjust the model parameters.

[0076] Furthermore, based on the physical model that integrates the real-time environmental monitoring data, the output results are obtained, and the output results of the physical model are quantitatively evaluated and risk level classified using statistical analysis methods. The process of generating corresponding risk warning signals includes:

[0077] Obtain outputs based on physical models that integrate real-time environmental monitoring data That is, the predicted hydrogen concentration distribution;

[0078] Based on the predicted hydrogen concentration distribution, determine the hydrogen leakage area CR;

[0079] Set hydrogen concentration thresholds of different risk levels: C1 is set as the high-risk concentration threshold, and C2 is set as the medium-risk concentration threshold; where C1>C2;

[0080] For the hydrogen leakage area CR, calculate the average hydrogen concentration in the area Assume that there are nc monitoring points in the region CR, and obtain the hydrogen concentration CH at each monitoring point. o (where o represents the monitoring point index, and o = 1, 2, ..., nc), then

[0081] The average hydrogen concentration calculated based on The risk level of the hydrogen leakage area CR is classified to obtain the risk assessment result: The hydrogen leakage area is judged as a high-risk area and a high-risk warning signal is generated; if The hydrogen leakage area is judged as a medium-risk area and a medium-risk warning signal is generated; if The hydrogen leakage area is then determined to be a low-risk area, and a low-risk warning signal is generated;

[0082] Based on the risk assessment results, emergency response measures are taken, while changes in hydrogen concentration are continuously monitored and emergency response strategies are adjusted.

[0083] Compared with the existing technology, the advantages of the method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank provided by the present invention are:

[0084] 1. The present invention constructs a physical model by analyzing the hydrogen leakage and diffusion phenomenon and the structural characteristics of the high-pressure storage tank, and can construct a physical model that is closer to reality, providing a solid theoretical basis for subsequent numerical simulation and risk assessment; the finite volume method can accurately simulate the flow process of hydrogen in the high-pressure storage tank and after leakage, and obtain more specific and accurate physical quantity distribution and change rules; by collecting data from historical leakage events to verify the accuracy of the model, the reliability of the model under different working conditions and environmental conditions can be ensured; by performing sensitivity analysis and adjustment on the model parameters, the model performance can be optimized, providing a solid foundation for subsequent real-time analysis and risk assessment;

[0085] 2. The present invention can timely discover and respond to hydrogen leakage events by real-time monitoring of key indicator parameters such as wind speed, wind direction, ambient temperature, ambient humidity and hydrogen concentration; by integrating real-time monitoring data into the physical model as the input condition of the model, the model can reflect the current actual environmental conditions and improve the accuracy of the simulation; by establishing a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters, the model parameters can be further dynamically adjusted to optimize the model output results;

[0086] 3. The present invention can generate corresponding risk warning signals by using statistical analysis methods to quantitatively evaluate and classify the risk levels of the output results of the physical model, provide a scientific basis for decision makers, and take emergency response measures according to the risk warning signals, such as evacuating personnel and cutting off power supply, which can effectively reduce the losses caused by hydrogen leakage incidents.

[0087] In summary, the present invention forms a complete high-pressure storage tank hydrogen leakage and diffusion analysis system through accurate simulation, real-time monitoring, dynamic adjustment and optimization, risk assessment and early warning of hydrogen leakage and diffusion phenomena, comprehensively improves the safety management level and emergency response capability of industrial enterprises, provides strong protection for industrial safety, and ensures the normal implementation of a subsequent high-pressure storage tank hydrogen leakage and diffusion analysis method. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] Figure 1 The present invention provides a flow chart of a method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank. DETAILED DESCRIPTION

[0089] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the implementation regulations described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0090] Reference Figure 1 , a method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank, comprising:

[0091] Step 1: Construct a physical model, which specifically includes analyzing the hydrogen leakage and diffusion phenomenon, namely the physical property parameters and meteorological condition parameters related to the environment in which the hydrogen is located, simulating the tank structure by analyzing the structural characteristics of the high-pressure storage tank, and setting the leakage conditions in combination with different leakage scenarios; among which, the physical property parameters are specifically density, diffusion coefficient, thermal conductivity, and flammable limit, and the structural characteristics of the high-pressure storage tank are specifically material, thickness, weld strength, and safety valve setting. Different leakage scenarios include small hole leakage and crack leakage;

[0092] Step 2: According to the constructed physical model, the numerical algorithm of the finite volume method is selected for solution. The purpose of selecting the numerical algorithm of the finite volume method for solution is to numerically simulate the physical phenomena in the model, and then obtain more specific and accurate distribution and change laws of physical quantities; collect data on historical leakage events, use the data on historical leakage events to verify the accuracy of the model, and perform sensitivity analysis and adjustment on the model parameters;

[0093] Step 3: Deploy sensors to monitor key indicator parameters in real time, namely wind speed, wind direction, ambient temperature, ambient humidity and hydrogen concentration; integrate the key indicator parameters monitored in real time into the physical model as the input conditions of the model; establish a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters; further dynamically adjust the physical model parameters to optimize the output results of the model;

[0094] Step 4: Obtain output results based on the physical model that integrates real-time environmental monitoring data, use statistical analysis methods to quantitatively evaluate and classify the risk levels of the physical model output results, and generate corresponding risk warning signals.

[0095] See also Figure 1 The present invention provides a method for analyzing hydrogen leakage and diffusion of a high-pressure storage tank. In the step 1, the hydrogen leakage and diffusion phenomenon is analyzed, the tank structure is simulated by analyzing the structural characteristics of the high-pressure storage tank, and the leakage conditions are set in combination with different leakage scenarios. The steps of constructing a physical model include:

[0096] Step 101: Analyze the physical characteristic parameters:

[0097] Step B1: For hydrogen density,

[0098]

[0099] In the formula, ρ represents the density of hydrogen, P represents the internal pressure of hydrogen, M represents the molar mass of hydrogen, and R·T refers to the product of the ideal gas constant R and the hydrogen temperature T, which represents the thermodynamic state of hydrogen; it can be understood that the density of hydrogen is important for understanding its settling or rising trend after leakage;

[0100] Step B2: For the diffusion coefficient,

[0101]

[0102] In the formula, D represents the diffusion coefficient, D0 represents the diffusion coefficient under reference conditions, T1 represents the current hydrogen temperature, T0 represents the hydrogen reference temperature, P1 represents the current hydrogen internal pressure, P0 represents the hydrogen internal reference pressure, and α represents the temperature dependence coefficient; it can be understood that the diffusion coefficient reflects the diffusion ability of hydrogen molecules in the medium, which is related to factors such as the size of hydrogen molecules and the properties of the medium;

[0103] Step B3: For thermal conductivity, use Fourier's law to describe heat conduction:

[0104] q=-k·▽T,

[0105] In the formula, q is the heat flux density, k is the thermal conductivity, and ▽T is the hydrogen temperature gradient; it can be understood that the thermal conductivity of hydrogen affects its heat transfer during the leakage and diffusion process, and thus affects its state change;

[0106] Step B4: For the flammable limit, the flammable limit of hydrogen in air is [L low ,L up ]; among them, [L low ,L up ] is an empirical range, such as the lower flammable limit of hydrogen in air L low =4%, upper flammable limit L up =75%. If the hydrogen concentration is within this range, combustion or explosion may occur when encountering a fire source.

[0107] Step 102: Analyze the meteorological condition parameters and use the formula to reflect the meteorological conditions:

[0108] Y=a·wv f +c·cos(I·(θ)-e),

[0109] In the formula, Y represents the meteorological condition parameter, wv, θ represent wind speed and wind direction respectively, a, f, c, I are all constants, a, f control the influence of wind speed wv on meteorological condition parameter Y, c controls the influence of direction θ on meteorological condition parameter Y, I is used to adjust the periodic change of wind direction influence, e is the direction offset, which is used to adjust the sensitivity of the formula to wind direction;

[0110] Step 103: For the strength analysis of the high-pressure storage tank material, assume that the internal pressure of the high-pressure storage tank is P In , according to Laplace's formula:

[0111]

[0112] In the formula, σ1 represents the stress of the high-pressure storage tank wall, sr represents the radius of the high-pressure storage tank, and wt represents the wall thickness of the high-pressure storage tank; it can be understood that by analyzing the Laplace formula, the structural stability of the tank under different pressures can be evaluated, thereby determining possible leakage points;

[0113] Step 104: For the weld strength analysis of the high-pressure storage tank, assuming that the shear force borne by the weld is WF and the cross-sectional area of ​​the weld is WA, the shear stress of the weld is:

[0114]

[0115] Where, σ2 represents the shear stress of the weld;

[0116] When σ2 exceeds the allowable shear stress of the weld material, cracks may appear in the weld, causing leakage;

[0117] Step 105, use a pilot-operated safety valve for setting: the pilot-operated safety valve is composed of a main valve and a pilot valve, and the opening pressure Popen is related to the spring stiffness sp of the pilot valve and the piston area pa of the main valve, wherein the opening pressure is expressed as:

[0118]

[0119] Where P set represents the set pressure of the safety valve, and dp represents the displacement of the pilot valve core; it is understandable that this formula can be used to determine the reasonable setting parameters of the safety valve and the impact on the leakage after the safety valve is opened;

[0120] Step 106: For small hole leakage, the small hole leakage flow rate is calculated using the formula:

[0121]

[0122] In the formula, Q1 represents the leakage flow of the small hole, represents the flow coefficient of the small hole, AQ1 represents the area of ​​the small hole, ΔP=P In -P Ot , P In is the internal pressure of the high pressure tank, P Ot is the external pressure on the high-pressure storage tank, and ρ represents the density of hydrogen;

[0123] Step 107: For crack leakage, calculate the crack leakage flow rate using the formula:

[0124]

[0125] Where Q2 represents the crack leakage flow rate, represents the flow coefficient of the crack, cw represents the crack width, and cl represents the crack length.

[0126] See also Figure 1 The present invention provides a method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank. In the second step, according to the constructed physical model, a numerical algorithm of the finite volume method is selected for solving; data of historical leakage events are collected, the accuracy of the model is verified by using the data of historical leakage events, and sensitivity analysis and adjustment of model parameters are performed, including:

[0127] Step 201: For the flow process of hydrogen in the high-pressure storage tank and after leakage, a set of equations is established based on the law of conservation of mass, the law of conservation of momentum and the law of conservation of energy. The specific process is as follows:

[0128] The mass conservation equation:

[0129]

[0130] Where ρ represents hydrogen density, t represents time, and u, v, and w represent the velocity components in the x, y, and z directions, respectively. The mass conservation equation shows that within a control volume, the rate of change of hydrogen mass with time is equal to the net mass flow rate of hydrogen flowing into and out of the control volume in all directions.

[0131] Momentum conservation equation:

[0132]

[0133] In the formula, P represents the internal pressure of hydrogen, μ represents the dynamic viscosity of hydrogen, and reflects the friction characteristics inside hydrogen; the left side of the momentum conservation equation represents the rate of change of hydrogen momentum in the x direction with time and the convection term caused by the velocity gradient, and the right side of the momentum conservation equation represents the hydrogen pressure gradient force and viscosity force;

[0134] Energy conservation equation:

[0135]

[0136] In the formula, h is enthalpy, which is a thermodynamic state function that combines internal energy and flow work. During the leakage and diffusion process of hydrogen, heat exchange will occur with the surrounding environment. Enthalpy can be directly related to the transfer of heat. When hydrogen exchanges heat with the outside world, the change in enthalpy directly reflects the impact of this energy exchange on the overall energy state of hydrogen, which helps to accurately describe the energy change of hydrogen under different conditions (such as different temperatures, pressures and flow states) in the energy conservation equation; is the material derivative, and k is thermal conductivity, which indicates the ability of hydrogen to conduct heat; T is the temperature of hydrogen; τ UV represents the stress tensor, which is a second-order tensor with nine components corresponding to stresses in different directions (e.g., τ xx represents the normal stress in the x direction, τ xy represents the shear stress in the x direction); U, V are index symbols used to represent the component index of the tensor, where the values ​​of U, V are x, y, and z, respectively representing the directions of the three coordinate axes; represents viscous dissipation, which is the process of converting mechanical energy into thermal energy due to the viscosity of the fluid. U is the U component of the velocity vector, It represents the rate of change of velocity in the V direction. When U and V take different values, this term will correspond to the viscous dissipation in different directions.

[0137] Step 202: Set the data of historical hydrogen leakage events to include N leakage events, each leakage event including leakage scene, environmental conditions, and leakage consequences;

[0138] Step 203: Use the error indicator RMSE to evaluate the accuracy of the model:

[0139]

[0140] In the formula, represents the actual observed hydrogen concentration value of n0, represents the corresponding hydrogen concentration value obtained by model simulation, n0 represents the leakage event index, and N represents the number of leakage events; it can be understood that the error index RMSE measures the average size of the error between the simulated value and the actual value, and is more sensitive to larger errors;

[0141] Step 204: Based on the error index RMSE result, perform a sensitivity analysis of the model parameters to determine the model parameters that have a greater impact on the simulation results: by changing the value of each parameter one by one, observing the change of the simulation results, calculating the change rate of the error index caused by the parameter change, and screening out sensitive parameters, wherein the model parameters include physical property parameters (density, diffusion coefficient, thermal conductivity, and flammable limit) and meteorological condition parameters. Sensitive parameters (i.e., parameters with higher sensitivity) have a significant impact on the model results and are the focus of adjustment. For example, for the diffusion coefficient D in the physical property parameters, calculate the change ΔRMSE of the error index RMSE when the diffusion coefficient changes ΔD, then the sensitivity ψ of the diffusion coefficient is D :

[0142]

[0143] Step 205: Use optimization algorithm to adjust the sensitive parameters of the model:

[0144] Using the gradient descent method, the error index RMSE is used as the optimization objective function and recorded as

[0145] The goal is to find a set of parameter values ​​such that the objective function minimize; among them, represents the vector containing all sensitive parameters to be adjusted;

[0146] Calculate the objective function with respect to the sensitive parameter vector Gradient The sensitive parameter update formula is:

[0147]

[0148] In the formula, represents the updated sensitive parameter, ι represents the learning rate, which controls the step size of each sensitive parameter update;

[0149] By continuously iteratively updating sensitive parameters until the error index converges to the preset range, the new parameters obtained at this time are the optimized model parameters, which can improve the model's simulation accuracy of the hydrogen leakage and diffusion process; it is understandable that through the historical data collection and model verification process, it can be ensured that the constructed physical model has high accuracy and reliability under different working conditions and environmental conditions, providing a solid foundation for subsequent real-time analysis and risk assessment.

[0150] See also Figure 1The present invention provides a method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank. In the step three, sensors are deployed to monitor key indicator parameters in real time, and the key indicator parameters monitored in real time are integrated into a physical model as input conditions of the model; a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters is established; and the physical model parameters are further dynamically adjusted to optimize the output results of the model. The steps include:

[0151] Step 301: According to the topography of the leakage site and the possible diffusion range of hydrogen, multiple meteorological sensors are arranged in a grid or radial pattern in a certain area centered on the leakage source, and the position coordinates of the meteorological sensors are defined as (xj, yj, zj); wherein j is the position coordinate index of the meteorological sensor, and j=1, 2, ..., n1, where n1 represents the number of meteorological sensors;

[0152] Step 302: The meteorological sensor measures the wind speed, wind direction, ambient temperature and ambient humidity in real time, and marks the wind speed, wind direction, ambient temperature and ambient humidity measured by the meteorological sensor in real time to obtain the wind speed wv j 、wind directionθ j 、Ambient temperature j And the ambient humidity j ;

[0153] Step 303: hydrogen concentration sensors are arranged at different heights and distances around the leakage source, focusing on areas where hydrogen may spread to, areas near sensitive facilities, etc., and the position coordinates of the hydrogen concentration sensors are set as (x l ,y l ,z l ), wherein l is the position coordinate index of the hydrogen concentration sensor, and l=1, 2, ..., n2, n2 represents the number of hydrogen concentration sensors;

[0154] Step 304: The hydrogen concentration sensor measures the hydrogen concentration at the location in real time, and marks the hydrogen concentration measured by the hydrogen concentration sensor in real time to obtain the hydrogen concentration Cl;

[0155] Step 305: Incorporate the key indicator parameters monitored by the sensor in real time into the physical model (the key indicator parameters include wind speed, wind direction, ambient temperature, ambient humidity and hydrogen concentration) as input conditions for the model operation so that the model can reflect the current actual environmental conditions, as follows:

[0156] Step F1, integration of wind speed and wind direction:

[0157] For the entire leakage area, the wind speed and wind direction data measured by various meteorological sensors are combined, and the effective wind speed wv input into the model is determined by the weighted average method. effand effective wind direction θ eff ; Among them, the calculation formula for effective wind speed is:

[0158]

[0159] Where W j is the weight coefficient, and When determining the weight coefficient, it is necessary to consider the distance between the sensor and the leak source. and the importance of the sensor location on the effect of hydrogen diffusion;

[0160] Convert the wind direction angle to a vector in Cartesian coordinates:

[0161]

[0162] In the formula, represents the wind direction vector;

[0163] The resultant wind direction vector for:

[0164]

[0165] Convert the resultant wind direction vector back to angle form to get the effective wind direction θ eff :

[0166]

[0167] In the formula, arctan represents the inverse tangent function, which is used to calculate the angle value corresponding to the synthetic wind direction vector. Represent the wind direction vector components in the y and x directions respectively;

[0168] Step F2, integration of temperature and humidity:

[0169] The effective temperature et is calculated using the weighted average method eff and effective humidity eh eff :

[0170]

[0171] Step F3, integration of hydrogen concentration:

[0172] In order to obtain the overall hydrogen concentration distribution trend of the leakage area, the data of each hydrogen concentration sensor are interpolated: the leakage area is divided into multiple grid cells, and for each grid cell center position (xgc, ygc, zgc), the hydrogen concentration C (xgc, ygc, zgc) at the position is calculated by the distance weighted inverse interpolation method;

[0173] Set the m hydrogen concentration sensors closest to the center position of the grid unit (xgc, ygc, zgc) to be numbered K1, K2, ..., K m (m represents the number of hydrogen concentration sensors, and m≤n2), and their distances from the center of the grid unit (xgc, ygc, zgc) are but:

[0174]

[0175] Wherein, i represents the hydrogen concentration sensor index, and i=1,2,…,m;

[0176] Step 306: Establish a mapping relationship between wind speed, wind direction and meteorological condition parameters:

[0177] In physical models, meteorological conditions usually affect the convective transport of hydrogen. The convective velocity vector in the model is set to

[0178] The effective wind speed wv eff and effective wind direction θ eff Mapping into the model, we get:

[0179]

[0180] In the formula, They represent the components of the convection velocity vector in the model in the x and y directions, respectively, and are used for the subsequent calculation of the convection transport of hydrogen in the model;

[0181] Step 307: Establish a mapping relationship between temperature and physical characteristic parameters:

[0182] The relationship between the diffusion coefficient D and temperature is expressed as:

[0183]

[0184] In the formula, represents the diffusion coefficient at standard temperature et0, and η is an exponent related to gas properties;

[0185] Step 308: Establish a mapping relationship between humidity and physical characteristic parameters:

[0186] Humidity affects some physical properties of hydrogen-air mixtures, such as thermal conductivity; a linear relationship between humidity and thermal conductivity k is assumed:

[0187] k=k0+ω(eheff-eh0),

[0188] In the formula, k0 represents the thermal conductivity under standard humidity eh0, and ω represents the coefficient of humidity on thermal conductivity;

[0189] Step 309: define the hydrogen concentration distribution output by the model as Compare with the actual hydrogen concentration distribution C(xgc,ygc,zgc) obtained by interpolating the hydrogen concentration sensor data;

[0190] Step 310: Establish error function E:

[0191]

[0192] In the formula, υ represents the total volume of the leakage area, and dυ represents the small change in the total volume;

[0193] Step 311: According to the error function, the model parameters are dynamically adjusted using an adaptive adjustment strategy:

[0194] For the diffusion coefficient D, if the error function E is large, it means that the model diffusion process is not accurately simulated. The diffusion coefficient is adjusted according to the following formula:

[0195]

[0196] Where D' represents the diffusion coefficient after adaptive adjustment; β represents the adjustment step factor to ensure the stability and convergence of the adjustment process; is the partial derivative of the error function with respect to the diffusion coefficient;

[0197] Dynamic adjustment of flammable limits: mark the initial lower flammable limit and upper flammable limit as Llow0 and Lup0 respectively; based on the effective temperature et in the real-time monitoring data eff and effective humidity eh eff , use the formula for dynamic adjustment:

[0198] Llow1=Llow0+γ1(eteff-et0)+γ2(eheff-eh0),

[0199] Lup1=Lup0+δ1(eteff-et0)+δ2(eheff-eh0),

[0200] Wherein, Llow1 and Lup1 represent the dynamically adjusted lower and upper flammable limits, γ1 and γ2 represent the temperature and humidity influencing factors of the lower flammable limit, and δ1 and δ2 represent the temperature and humidity influencing factors of the upper flammable limit. It can be understood that the flammable limit is affected by environmental factors such as temperature and humidity, that is, the effective temperature and effective humidity in the real-time monitoring data will change the flammable limit of hydrogen.

[0201] See also Figure 1The present invention provides a method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank. In step 4, the output result is obtained based on a physical model integrating real-time environmental monitoring data, and the output result of the physical model is quantitatively evaluated and risk level classified using a statistical analysis method. The step of generating a corresponding risk warning signal includes:

[0202] Step 401: Obtain output results based on a physical model integrating real-time environmental monitoring data That is, the predicted hydrogen concentration distribution;

[0203] Step 402: Determine the hydrogen leakage region CR based on the predicted hydrogen concentration distribution;

[0204] Step 403, setting hydrogen concentration thresholds of different risk levels: C1 is set as a high risk concentration threshold (for example, a certain proportion of the lower explosion limit concentration of hydrogen, assuming 50% of the lower explosion limit concentration, which can be adjusted according to actual conditions), and C2 is set as a medium risk concentration threshold; wherein C1>C2;

[0205] Step 404: For the hydrogen leakage region CR, calculate the average hydrogen concentration in the region Assume that there are nc monitoring points in the region CR, and obtain the hydrogen concentration CH at each monitoring point. o (where o represents the monitoring point index, and o = 1, 2, ..., nc), then

[0206] Step 405: calculate the average hydrogen concentration The risk level of the hydrogen leakage area CR is classified to obtain the risk assessment result: The hydrogen leakage area is judged as a high-risk area, and a high-risk warning signal is generated. The high-risk warning signal indicates that hydrogen leakage in this area may cause explosion, serious casualties and property losses and other serious consequences; if The hydrogen leakage area is judged as a medium-risk area, and a medium-risk warning signal is generated. The medium-risk warning signal indicates that although the hydrogen concentration has not yet reached the level that is extremely likely to cause an explosion, it may cause certain damage to personnel health and equipment; if The hydrogen leakage area is then judged as a low-risk area, and a low-risk warning signal is generated. The low-risk warning signal indicates that the hydrogen leakage in this area currently has little impact on personnel, property and the environment, but continuous monitoring is still required to prevent the situation from deteriorating;

[0207] Step 406: Based on the risk assessment results, emergency response measures are taken, while continuously monitoring the changes in hydrogen concentration and adjusting the emergency response strategy, including: for high-risk warning signals, emergency measures need to be taken immediately, such as evacuating personnel, cutting off power, etc.; for medium-risk warning signals, it is necessary to strengthen monitoring and take some preventive measures such as strengthening ventilation, etc.

[0208] In the embodiment of the present invention, by conducting a detailed analysis of hydrogen characteristics (such as density, diffusion coefficient, thermal conductivity, flammable limit) and meteorological condition parameters of the environment (such as wind speed and wind direction), it is possible to have a more comprehensive understanding of the behavior of hydrogen after leakage. By analyzing the structural characteristics of the high-pressure storage tank (such as material, thickness, weld strength, safety valve setting) and simulating the tank structure, it is possible to predict leakage conditions under different leakage scenarios (such as small hole leakage, crack leakage), providing a basis for risk assessment. Based on the law of conservation of mass, the law of conservation of momentum, and the law of conservation of energy, a group of equations is established, which can accurately describe the flow process of hydrogen in the high-pressure storage tank and after leakage. By collecting data from historical leakage events to verify the accuracy of the model and performing sensitivity analysis and adjustment on the model parameters, the model can be further optimized to improve the simulation results. The reliability of the results is improved. By deploying sensors to monitor key indicator parameters such as wind speed, wind direction, ambient temperature, ambient humidity, and hydrogen concentration in real time, field data can be obtained in real time to provide accurate input conditions for the model. By integrating the key indicator parameters monitored in real time into the physical model as the input conditions of the model, the model can be closer to the actual environmental conditions and the accuracy of the simulation can be improved. By establishing a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters, and dynamically adjusting the physical model parameters, the model can be further optimized so that it can maintain a high accuracy under different working conditions and environmental conditions. By using statistical analysis methods to quantitatively evaluate the output results of the physical model and classify the risk level, a corresponding risk warning signal can be generated to provide decision support for emergency response. In summary, the examples of the present invention involve data processing, comprehensive analysis, and intelligent adjustment decisions to solve the technical problems of high-pressure storage tank hydrogen leakage diffusion simulation and real-time monitoring and warning. In actual situations, more data and context information may be needed to make specific decisions and optimization plans.

[0209] In addition, the formulas involved in the above are all calculated by removing dimensions and taking their numerical values. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The proportional coefficient in the formula and the various preset thresholds in the analysis process are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data; the size of the proportional coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the proportional coefficient depends on the amount of sample data and the preliminary setting of the corresponding processing coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0210] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically based on the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0211] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0212] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD ROM, optical storage, etc.) containing computer-usable program code.

[0213] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0214] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0215] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0216] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0217] Finally: The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for analyzing the leakage and diffusion of hydrogen in a high-pressure storage tank, characterized in that: Step 1: Construct a physical model, which specifically includes analyzing the hydrogen leakage and diffusion phenomenon, simulating the tank structure by analyzing the structural characteristics of the high-pressure storage tank, and setting leakage conditions in combination with different leakage scenarios; Step 2: According to the constructed physical model, select the numerical algorithm of the finite volume method to solve; collect data on historical leakage events, use the data on historical leakage events to verify the accuracy of the model, and perform sensitivity analysis and adjustment on the model parameters; Step 3: Deploy sensors to monitor key indicator parameters in real time, namely wind speed, wind direction, ambient temperature, ambient humidity and hydrogen concentration; integrate the key indicator parameters monitored in real time into the physical model as the input conditions of the model; establish a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters; further dynamically adjust the physical model parameters to optimize the output results of the model; Step 4: Obtain output results based on the physical model that integrates real-time environmental monitoring data, use statistical analysis methods to quantitatively evaluate and classify the risk levels of the physical model output results, and generate corresponding risk warning signals.

2. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 1, characterized in that: In step one, the analysis of hydrogen leakage and diffusion phenomena includes physical property parameters and meteorological condition parameters related to the environment in which the hydrogen is located, wherein the physical property parameters specifically include density, diffusion coefficient, thermal conductivity and flammable limit; the structural characteristics of the high-pressure storage tank specifically include material, thickness, weld strength, and safety valve setting; and different leakage scenarios include small hole leakage and crack leakage.

3. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 1, characterized in that: In the step 2, the process of selecting the numerical algorithm of the finite volume method for solving includes: For the flow process of hydrogen in the high-pressure storage tank and after leakage, a set of equations is established based on the law of conservation of mass, the law of conservation of momentum and the law of conservation of energy. The specific process is as follows: The mass conservation equation: Where ρ represents hydrogen density, t represents time, and u, v, and w represent the velocity components in the x, y, and z directions, respectively. The mass conservation equation shows that within a control volume, the rate of change of hydrogen mass with time is equal to the net mass flow rate of hydrogen flowing into and out of the control volume in all directions. Momentum conservation equation: In the formula, P represents the internal pressure of hydrogen, μ represents the dynamic viscosity of hydrogen, and reflects the friction characteristics inside hydrogen; the left side of the momentum conservation equation represents the rate of change of hydrogen momentum in the x direction with time and the convection term caused by the velocity gradient, and the right side of the momentum conservation equation represents the hydrogen pressure gradient force and viscosity force; Energy conservation equation: Where h is enthalpy; is the material derivative, and k is thermal conductivity, which indicates the ability of hydrogen to conduct heat; T is the temperature of hydrogen; τ UV Represents the stress tensor; U and V are index symbols used to represent the component index of the tensor, where the values ​​of U and V are x, y, and z, respectively representing the directions of the three coordinate axes; represents viscous dissipation, which is the process of converting mechanical energy into thermal energy due to the viscosity of the fluid. U is the U component of the velocity vector, Indicates the rate of change of velocity in the V direction.

4. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 1, characterized in that: In step 2, the process of collecting data of historical leakage events, using the data of historical leakage events to verify the accuracy of the model, and performing sensitivity analysis and adjustment on the model parameters includes: Assume that the data of historical hydrogen leakage events contains N leakage events, each of which includes leakage scene, environmental conditions, and leakage consequences; The error indicator RMSE is used to evaluate the accuracy of the model: In the formula, represents the actual observed hydrogen concentration value of n0, represents the corresponding hydrogen concentration value obtained by model simulation, n0 represents the leakage event index, and N represents the number of leakage events; Based on the RMSE results of the error index, the sensitivity analysis of the model parameters is carried out: by changing the value of each parameter one by one, observing the changes in the simulation results, calculating the change rate of the error index caused by the parameter change, and screening out sensitive parameters; Use optimization algorithms to adjust the sensitive parameters of the model: Using the gradient descent method, the error index RMSE is used as the optimization objective function and recorded as The goal is to find a set of parameter values ​​such that the objective function minimize; among them, represents the vector containing all sensitive parameters to be adjusted; Calculate the objective function with respect to the sensitive parameter vector Gradient The sensitive parameter update formula is: In the formula, represents the updated sensitive parameter, ι represents the learning rate, which controls the step size of each sensitive parameter update; Sensitive parameters are updated by continuous iteration until the error index converges to the preset range. The new parameters obtained at this time are the optimized model parameters.

5. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 1, characterized in that: In step 3, the process of deploying sensors to monitor key indicator parameters in real time includes: In a certain area centered on the leakage source, multiple meteorological sensors are arranged in a grid or radial pattern, and the location coordinates of the meteorological sensors are defined as (xj, yj, zj); wherein j is the location coordinate index of the meteorological sensor, and j = 1, 2, ..., n1, where n1 represents the number of meteorological sensors; The meteorological sensor measures wind speed, wind direction, ambient temperature and ambient humidity in real time. The wind speed, wind direction, ambient temperature and ambient humidity measured by the meteorological sensor in real time are marked respectively to obtain the wind speed wv j 、wind directionθ j 、Ambient temperature j And the ambient humidity j ; Around the leak source, hydrogen concentration sensors are arranged at different heights and distances, and the position coordinates of the hydrogen concentration sensors are set as (x l ,y l ,z l ), wherein l is the position coordinate index of the hydrogen concentration sensor, and l=1, 2, ..., n2, n2 represents the number of hydrogen concentration sensors; The hydrogen concentration sensor measures the hydrogen concentration at the location in real time, and marks the hydrogen concentration measured by the hydrogen concentration sensor in real time to obtain the hydrogen concentration Cl.

6. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 5, characterized in that: In step 3, the process of integrating the key indicator parameters monitored in real time into the physical model as the input conditions of the model includes: The key indicator parameters monitored by the sensor in real time are incorporated into the physical model as the input conditions for the model operation, as follows: Step F1, integration of wind speed and wind direction: For the entire leakage area, the wind speed and wind direction data measured by various meteorological sensors are combined, and the effective wind speed wv input into the model is determined by the weighted average method. eff and effective wind direction θ eff ; Among them, the calculation formula for effective wind speed is: Where W j is the weight coefficient, and When determining the weight coefficient, it is necessary to consider the distance between the sensor and the leak source. and the importance of the sensor location on the effect of hydrogen diffusion; Convert the wind direction angle to a vector in Cartesian coordinates: In the formula, represents the wind direction vector; The resultant wind direction vector for: Convert the resultant wind direction vector back to angle form to get the effective wind direction θ eff : In the formula, arctan represents the inverse tangent function, which is used to calculate the angle value corresponding to the synthetic wind direction vector. Represent the wind direction vector components in the y and x directions respectively; Step F2, integration of temperature and humidity: The effective temperature et is calculated using the weighted average method eff and effective humidity eh eff : Step F3, integration of hydrogen concentration: In order to obtain the overall hydrogen concentration distribution trend of the leakage area, the data of each hydrogen concentration sensor are interpolated: the leakage area is divided into multiple grid cells, and for each grid cell center position (xgc, ygc, zgc), the hydrogen concentration C (xgc, ygc, zgc) at the position is calculated by the distance weighted inverse interpolation method; Set the m hydrogen concentration sensors closest to the center position of the grid unit (xgc, ygc, zgc) to be numbered K1, K2, ..., K m , their distances from the center of the grid cell (xgc, ygc, zgc) are but: Wherein, i represents the hydrogen concentration sensor index, and i=1, 2,…, m.

7. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 6, characterized in that: In step 3, a mapping relationship between the key indicator parameters monitored in real time and the constructed physical model parameters is established, and the process of further dynamically adjusting the physical model parameters includes: Establish the mapping relationship between wind speed, wind direction and meteorological condition parameters: Set the convection velocity vector in the model The effective wind speed wv eff and effective wind direction θ eff Mapping into the model, we get: In the formula, They represent the components of the convection velocity vector in the model in the x and y directions respectively; Establish a mapping relationship between temperature and physical characteristic parameters; Establish the mapping relationship between humidity and physical characteristic parameters; The hydrogen concentration distribution output by the model is defined as Compare with the actual hydrogen concentration distribution C(xgc,ygc,zgc) obtained by interpolating the hydrogen concentration sensor data; Establish the error function E: In the formula, υ represents the total volume of the leakage area, and dυ represents the small change in the total volume; According to the error function, an adaptive adjustment strategy is used to dynamically adjust the model parameters.

8. A method for analyzing hydrogen leakage and diffusion in a high-pressure storage tank according to claim 7, characterized in that: In step 4, the process of obtaining output results based on the physical model integrating real-time environmental monitoring data, and using statistical analysis methods to quantitatively evaluate and classify the risk levels of the output results of the physical model to generate corresponding risk warning signals includes: Obtain outputs based on physical models that integrate real-time environmental monitoring data That is, the predicted hydrogen concentration distribution; Based on the predicted hydrogen concentration distribution, determine the hydrogen leakage area CR; Set hydrogen concentration thresholds of different risk levels: C1 is set as the high-risk concentration threshold, and C2 is set as the medium-risk concentration threshold; where C1>C2; For the hydrogen leakage area CR, calculate the average hydrogen concentration in the area Assume that there are nc monitoring points in the region CR, and obtain the hydrogen concentration CH at each monitoring point. o (where o represents the monitoring point index, and o = 1, 2, ..., nc), then The average hydrogen concentration calculated based on The risk level of the hydrogen leakage area CR is classified to obtain the risk assessment result: The hydrogen leakage area is judged as a high-risk area and a high-risk warning signal is generated; if The hydrogen leakage area is judged as a medium-risk area and a medium-risk warning signal is generated; if The hydrogen leakage area is then determined to be a low-risk area, and a low-risk warning signal is generated; Based on the risk assessment results, emergency response measures are taken, while changes in hydrogen concentration are continuously monitored and emergency response strategies are adjusted.

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