Method, device and equipment for monitoring temperature field and predicting pressure relief cycle of cryogenic storage tanks

Abstract

The present application discloses a method, device and equipment for monitoring the temperature field and predicting the pressure relief cycle of a cryogenic storage tank, which relates to the technical field of safety monitoring of cryogenic storage tanks. The method comprises: generating a temperature field reduction model and a heat flow reduction model through simulation calculation and fitting. If it is necessary to monitor the temperature field and predict the pressure relief cycle, the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank are used as inputs, the real-time temperature field of the cryogenic storage tank is determined by the temperature field reduction model, and the real-time total heat flow of the outer wall of the cryogenic storage tank is determined by the heat flow reduction model. Based on the real-time monitoring value of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow of the outer wall, the real-time pressure relief cycle of the cryogenic storage tank is calculated. The present application can monitor the temperature field and predict the pressure relief cycle more in real time and accurately, effectively improving the safety and operation efficiency of the cryogenic storage tank.

Description

Technical Field

[0001] The present application relates to the technical field of safety monitoring of cryogenic storage tanks, and in particular to a method, device and equipment for temperature field monitoring and pressure relief cycle prediction of cryogenic storage tanks. Background Art

[0002] Cryogenic storage tanks are essential equipment for storing cryogenic liquids such as liquid oxygen and liquid nitrogen, and are widely used in industry, healthcare, and scientific research. Due to their limited insulation properties, cryogenic tanks can leak heat, leading to liquid evaporation and increased pressure. To ensure safety, cryogenic tanks require regular pressure relief, but excessively long or short pressure relief cycles can have adverse effects. Furthermore, an uneven temperature field can cause brittle fracture or deformation of the tank material due to thermal stress. Therefore, monitoring the temperature field of cryogenic tanks and predicting their pressure relief cycles are crucial.

[0003] In related technologies, numerical simulation methods are mostly used to monitor the temperature field of cryogenic storage tanks, but numerical simulation methods are time-consuming and have poor real-time performance. Empirical formula methods are mostly used to predict the pressure relief cycle of cryogenic storage tanks, but the accuracy of empirical formula methods is not high. Summary of the Invention

[0004] The purpose of this application is to provide a method, device and equipment for monitoring the temperature field and predicting the pressure relief cycle of cryogenic storage tanks, which overcomes the shortcomings of numerical simulation methods such as long time consumption, poor real-time performance and low accuracy of empirical formula methods, and monitors the temperature field and predicts the pressure relief cycle in a more real-time and accurate manner, effectively improving the safety and operation efficiency of cryogenic storage tanks.

[0005] To achieve the above objectives, this application provides the following solutions.

[0006] In a first aspect, the present application provides a method for monitoring the temperature field of a cryogenic storage tank and predicting a pressure relief cycle, the method comprising the following steps.

[0007] Obtain real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank.

[0008] Taking the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank as input, the temperature field reduced-order model is used to determine the real-time temperature field of the cryogenic storage tank, and the heat flow reduced-order model is used to determine the real-time total heat flow of the outer wall of the cryogenic storage tank.

[0009] Based on the real-time monitoring value of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow on the outer wall, the real-time pressure relief cycle of the cryogenic storage tank is calculated.

[0010] Among them, the establishment process of the temperature field reduction model and the heat flow reduction model includes: constructing a thermal simulation geometric parameterized model of the cryogenic storage tank; for each set of preset sample parameters, setting the boundary conditions of the thermal simulation geometric parameterized model based on the sample parameters to obtain the thermal simulation parameterized model, and performing simulation calculations based on the thermal simulation parameterized model to obtain the sample temperature field and the total heat flow of the sample outer wall of the cryogenic storage tank corresponding to the sample parameters; fitting the sample temperature fields corresponding to all groups of the sample parameters and each group of the sample parameters to generate the temperature field reduction model, fitting the total heat flow of the sample outer wall corresponding to all groups of the sample parameters and each group of the sample parameters to generate the heat flow reduction model; the sample parameters include sample values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank.

[0011] In the second aspect, the present application provides a cryogenic storage tank temperature field monitoring and pressure relief cycle prediction device, which includes: a processor and a liquid level sensor, a first temperature sensor, a second temperature sensor, a third temperature sensor and a pressure sensor communicated with the processor.

[0012] The liquid level sensor, the first temperature sensor, the second temperature sensor, the third temperature sensor and the pressure sensor are all installed on the cryogenic storage tank. The liquid level sensor is used to collect and obtain the real-time monitoring value of the liquid phase height of the cryogenic storage tank. The first temperature sensor is used to collect and obtain the real-time monitoring value of the liquid phase temperature of the cryogenic storage tank. The second temperature sensor is used to collect and obtain the real-time monitoring value of the gas phase temperature of the cryogenic storage tank. The third temperature sensor is used to collect and obtain the real-time monitoring value of the outer wall temperature of the cryogenic storage tank. The pressure sensor is used to collect and obtain the real-time monitoring value of the gas phase pressure of the cryogenic storage tank.

[0013] The processor is used to obtain real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank, execute the above-mentioned cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method, and determine the real-time temperature field and real-time pressure relief cycle of the cryogenic storage tank.

[0014] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method.

[0015] According to the specific embodiments provided in this application, this application has the following technical effects.

[0016] The present application provides a method, device, and apparatus for monitoring the temperature field and predicting the pressure relief cycle of a cryogenic storage tank. The method first constructs a thermal simulation geometric parameterized model of the cryogenic storage tank. For each set of preset sample parameters (including sample values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, and outer wall temperature of the cryogenic storage tank), boundary conditions of the thermal simulation geometric parameterized model are set based on the sample parameters to obtain a thermal simulation parameterized model. Simulation calculations are then performed based on the thermal simulation parameterized model to obtain the sample temperature field and total heat flux of the sample outer wall of the cryogenic storage tank corresponding to the sample parameters. Fit all groups of sample parameters and the sample temperature field corresponding to each group of sample parameters to generate a temperature field reduction model. Fit all groups of sample parameters and the sample outer wall total heat flow corresponding to each group of sample parameters to generate a heat flow reduction model. After obtaining the temperature field reduction model and the heat flow reduction model, if it is necessary to monitor the temperature field and predict the pressure relief cycle, the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank can be obtained first. The real-time monitoring values ​​of temperature, gas phase temperature and outer wall temperature are used as input. The real-time temperature field of the cryogenic storage tank is determined by the temperature field reduction model, and the real-time total heat flow of the outer wall of the cryogenic storage tank is determined by the heat flow reduction model. Based on the real-time monitoring values ​​of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow of the outer wall, the real-time pressure relief cycle of the cryogenic storage tank is calculated. When monitoring the temperature field, there is no need for numerical simulation, which solves the problems of long time consumption and poor real-time performance of the numerical simulation method. The temperature field is monitored more in real time. When predicting the pressure relief cycle, the real-time outer wall heat flow can be determined first, and then the real-time pressure relief cycle can be further calculated. There is no need to rely entirely on empirical formulas for prediction, which solves the problem of low accuracy of the empirical formula method and more accurately predicts the pressure relief cycle. Since the temperature field can be monitored and the pressure relief cycle can be predicted more accurately in real time, the problem of brittle fracture or deformation of the tank material due to thermal stress caused by uneven temperature field can be avoided. At the same time, the problem of adverse effects caused by too long or too short pressure relief cycle can be avoided, which can effectively improve the safety and operation efficiency of cryogenic storage tanks. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 This is an application environment diagram of a method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief cycle provided in Example 1 of the present application.

[0019] Figure 2 A flow chart of a method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief cycle provided in Example 1 of the present application.

[0020] Figure 3 Schematic diagram of the digital twin technology route for a method for temperature field monitoring and pressure relief cycle prediction of a cryogenic storage tank provided in Example 1 of the present application.

[0021] Figure 4 Schematic diagram of the geometric model of the cryogenic storage tank provided in Example 1 of the present application.

[0022] Figure 5 Schematic diagram of the geometric parameters of the cryogenic storage tank provided in Example 1 of the present application.

[0023] Figure 6 Schematic diagram of the digital twin model for monitoring the temperature field of a cryogenic storage tank provided in Example 1 of the present application.

[0024] Figure 7 Schematic diagram of the digital twin model for predicting the pressure relief cycle of a cryogenic storage tank provided in Example 1 of the present application.

[0025] Figure 8 A schematic diagram of the structure of a computer device provided in Example 3 of the present application.

[0026] Reference numerals: 1 - outer tank model; 2 - inner tank model; 3 - vacuum sandwich model. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0028] Example 1.

[0029] The cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method provided in the embodiment of the present application can be applied to Figure 1In the application environment shown, the terminal communicates with the server via a network. The data storage system can store data that the server needs to process. The data storage system can be set up separately, integrated with the server, or located in the cloud or on other servers. The terminal can send pending monitoring and prediction requests to the server. After receiving the pending monitoring and prediction requests, the server obtains the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature, and gas phase pressure of the cryogenic storage tank. Using the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, and outer wall temperature of the cryogenic storage tank as input, the server determines the real-time temperature field of the cryogenic storage tank using a temperature field reduction model and determines the real-time total heat flow of the outer wall of the cryogenic storage tank using a heat flow reduction model. Based on the real-time monitoring values ​​of the gas phase pressure and the real-time total heat flow of the outer wall of the cryogenic storage tank, the server calculates the real-time pressure relief period of the cryogenic storage tank. The server can provide feedback to the terminal on the monitoring results of the real-time temperature field and real-time total heat flow of the outer wall in response to the monitoring and prediction requests, as well as the prediction results of the real-time pressure relief period.

[0030] In addition, in some embodiments, the cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method can also be implemented independently by a server or terminal. For example, the terminal can directly process the pending monitoring and prediction requests, or the server can obtain the pending monitoring and prediction requests from the data storage system and process the pending monitoring and prediction requests.

[0031] The terminals may include, but are not limited to, various desktop computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. The server may be implemented as a standalone server or a server cluster consisting of multiple servers, or as a cloud server.

[0032] In an exemplary embodiment, Figure 2 As shown, a method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief cycle is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The following steps are used as an example to illustrate the server.

[0033] Step S1, obtaining real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank.

[0034] In step S2, the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank are used as input, and the real-time temperature field of the cryogenic storage tank is determined using the temperature field reduction model, and the real-time total heat flow of the outer wall of the cryogenic storage tank is determined using the heat flow reduction model.

[0035] Step S3: Calculate the real-time pressure relief period of the cryogenic storage tank based on the real-time monitoring value of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow on the outer wall.

[0036] By implementing the above steps S1 to S3, this embodiment overcomes the shortcomings of the numerical simulation method, such as long time consumption, poor real-time performance, and low accuracy of the empirical formula method, and more real-time and accurate monitoring of the temperature field and prediction of the pressure relief cycle, effectively improving the safety and operation efficiency of the cryogenic storage tank.

[0037] With the development of digital twin technology, a new solution is provided for temperature field monitoring and pressure relief cycle prediction of cryogenic storage tanks. Figure 3 The digital twin-based cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method used in this embodiment is introduced in detail, including the following steps.

[0038] (1) Establish a thermal simulation parameterized model for cryogenic storage tanks. Use DOE (Design of Experiments) to generate training samples (including temperature field sample data and heat flow sample data). Use the static reduced-order model method to establish a temperature field reduced-order model. Use the response surface method to establish a heat flow reduced-order model. Reduce the computational complexity and connect different modules to build a digital twin model system.

[0039] (1) Thermal simulation parameterized model.

[0040] (1.1) Geometric model.

[0041] This embodiment constructs a geometric model of a cryogenic storage tank based on its actual structure. The geometric model consists of three parts: an inner tank model, an outer tank model, and a vacuum interlayer model. The vacuum interlayer model is located between the inner and outer tank models. The inner tank model stores liquid (i.e., liquid phase) and gas (i.e., gas phase). The vacuum interlayer model is simplified to an isotropic thermal conductive material.

[0042] Preferably, the geometric model of the cryogenic storage tank is reasonably simplified according to the geometric characteristics, physical properties and simulation analysis type of the cryogenic storage tank. Since the cryogenic storage tank is a symmetrical structure, in order to simplify the geometric model, only the geometric model of 1 / 4 of the cryogenic storage tank is established for finite element simulation analysis. The model simplification is specifically as follows: the geometric model of the cryogenic storage tank is the geometric model of 1 / 4 of the cryogenic storage tank divided by the symmetry plane. The geometric model is as follows: Figure 4 As shown, Figure 4In the figure, 1 is the outer tank model, 2 is the inner tank model, and 3 is the vacuum interlayer model.

[0043] (1.2) Model parameterization.

[0044] Parametric modeling can achieve rapid modeling and batch simulation calculations to improve efficiency. At the same time, generating temperature field reduced-order models and heat flow reduced-order models also requires parameterization of inputs and outputs. Therefore, parametric modeling is used to parameterize the geometric parameters, material parameters, and boundary conditions of the geometric model of the cryogenic storage tank to achieve rapid modeling and batch simulation calculations to improve efficiency.

[0045] (1.2.1) Geometric parameterization.

[0046] In this embodiment, the geometric parameters and material parameters of the geometric model are set to perform geometric parameterization to obtain a thermal simulation geometric parameterized model of the cryogenic storage tank, such as Figure 5 As shown, the geometric parameters include the thickness, length and inner diameter of the inner tank model and the thickness, length and outer diameter of the outer tank model, and the material parameters include the first thermal conductivity of the inner tank model, the second thermal conductivity of the outer tank model and the third thermal conductivity of the vacuum interlayer model.

[0047] The thermal conductivity of the inner tank model and the thermal conductivity of the outer tank model adopt the thermal conductivity of the tank material itself, and the thermal conductivity of the vacuum interlayer model adopts the apparent thermal conductivity. Specifically, the daily evaporation rate of the cryogenic storage tank when the filling rate is 90% is obtained through experiments, and the total heat flow of the outer wall is further calculated by the daily evaporation rate and the latent heat of vaporization of the medium (that is, the liquid in the cryogenic storage tank, generally liquid oxygen, liquid nitrogen and other cryogenic liquids). The apparent thermal conductivity of the vacuum interlayer model is continuously adjusted and simulation calculations are performed until the total heat flow of the outer wall obtained by simulation calculation is equal to or close to the total heat flow of the outer wall obtained by experiment (that is, the difference is less than the preset difference). The apparent thermal conductivity of the vacuum interlayer model at this time is used as the thermal conductivity of the vacuum interlayer model during simulation.

[0048] (1.2.2) Parameterization of boundary conditions.

[0049] The boundary conditions and simulation calculation results are parameterized respectively as input parameters and output parameters for generating training samples of temperature field reduced-order model and heat flow reduced-order model.

[0050] When parameterizing boundary conditions, the required data include: liquid phase height, liquid phase temperature, gas phase temperature, and outer wall temperature. In this embodiment, the data required include: liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature, inner tank length, inner tank inner diameter, inner tank thickness, outer tank length, outer tank outer diameter, and outer tank thickness. The value ranges of the relevant parameters are shown in Table 1. Specifically, the value range of the liquid phase height is 0 to 2540 mm, the value range of the liquid phase temperature is -196°C to 0°C, the value range of the gas phase temperature is -196°C to 0°C, and the value range of the outer wall temperature is -40°C to 40°C.

[0051] Table 1 Parameter value range

[0052]

[0053] The boundary conditions are specifically set as follows: the temperature of the outer surface of the outer tank of the cryogenic storage tank is set to the outer wall temperature (or ambient temperature), the temperature of the surface in contact between the inner tank and the liquid is set to the liquid phase temperature, and the temperature of the surface in contact between the inner tank and the gas is set to the gas phase temperature.

[0054] After completing the boundary condition setting, a thermal simulation parameterized model of the cryogenic storage tank can be generated. Simulation calculations are performed based on the thermal simulation parameterized model. The simulation calculation results obtained can include temperature distribution (i.e., temperature field), total heat flux of the outer wall, and heat flow conditions. Subsequently, the evaporation amount of the liquid can be calculated through the total heat flux of the outer wall of the cryogenic storage tank and the latent heat of vaporization of the medium, thereby calculating the daily evaporation rate of the cryogenic storage tank and further predicting the pressure relief cycle of the cryogenic storage tank.

[0055] Here, the input parameters and output parameters of the training samples are explained: for the temperature field reduced-order model, the training samples are the temperature field sample data, the input parameters of the temperature field sample data are the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature, and the output parameter is the temperature field; for the heat flow reduced-order model, the training samples are the heat flow sample data, the input parameters of the heat flow sample data are the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature, and the output parameter is the total heat flow of the outer wall.

[0056] (2) Generate training samples.

[0057] This embodiment uses DOE experiments to generate training samples, which include temperature field sample data and heat flow sample data. Subsequently, based on the temperature field sample data, a static reduced-order model method is used to establish a temperature field reduced-order model, and based on the heat flow sample data, a response surface method is used to establish a heat flow reduced-order model, thereby reducing computational complexity. Specifically, through DOE experiments, the values ​​of the boundary conditions of the thermal simulation geometric parameterized model of the cryogenic storage tank are reasonably designed to generate multiple thermal simulation parameterized models, each value of the boundary condition corresponds to a thermal simulation parameterized model, and then batch simulation calculations are performed to quickly obtain sufficient training samples required to generate the temperature field reduced-order model and the heat flow reduced-order model. Then, artificial intelligence learning (such as machine learning) is used to process the training samples to obtain the temperature field reduced-order model and the heat flow reduced-order model, thereby reducing computational complexity and significantly reducing computational time. Specifically, the static reduced-order model method is used to establish the temperature field reduced-order model, and the response surface method is used to establish the heat flow reduced-order model.

[0058] The DOE experiment uses the Latin Hypercube Sampling Design method to generate multiple sets of sample parameters. This method is a stratified sampling technique that approximates random sampling from a multivariate parameter distribution. Each set of sample parameters includes sample values ​​for liquid height, liquid temperature, vapor temperature, and external wall temperature. These sets of sample parameters are organized and entered into an Excel spreadsheet and saved in CSV format. This serves as input parameter data for training samples for the temperature field and heat flux reduction models. As an example, the ANSYS ResponseSurface module can be used to design a DOE experiment and establish multiple sets of sample parameters.

[0059] For each set of sample parameters, the boundary conditions of the thermal simulation geometric parameterized model of the cryogenic storage tank are set based on the sample parameters, the thermal simulation parameterized model is generated, and the thermal simulation parameterized model is used for simulation calculation to obtain the sample temperature field and the total heat flow of the sample outer wall corresponding to each set of sample parameters. Similarly, the sample temperature field and the total heat flow of the sample outer wall corresponding to each set of sample parameters are sorted out, input into an EXCEL table, and saved in CSV format as the output parameter data of the training samples of the temperature field reduced-order model and the heat flow reduced-order model, thereby completing the generation of training samples.

[0060] In this embodiment, the generation of training samples can be completed using simulation software. As an example, the generation of training samples can be achieved with the help of the StaticROMPreprocesing plug-in of ANSYS. The StaticROM Pre item is inserted in the Solution, and its properties are set. The input parameters are selected as liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature, and the output parameters are selected as temperature field or total heat flux of the outer wall.

[0061] Specifically, for temperature field sample data, in ANSYS, the generation of temperature field sample data requires the help of the StaticROM Preprocesing plug-in. Therefore, before generating temperature field sample data, you should first install the StaticROM Preprocesing plug-in in ANSYS Workbench, and then parameterize the liquid height, liquid temperature, gas temperature, and outer wall temperature in the boundary conditions in the Mechanical module, as well as the maximum, average, and minimum values ​​in the temperature field. Finally, insert the StaticROM Pre item in the Solution, and set the file directory, input parameters, and output parameters in the property card of the StaticROM Pre item. Select liquid height, liquid temperature, gas temperature, and outer wall temperature as input parameters, and select temperature field as output parameters. After running the calculation, temperature field sample data in a certain format will be generated in the set file directory.

[0062] (3) Establish a digital twin model system.

[0063] (3.1) Generate a reduced-order model of the temperature field.

[0064] The temperature field reduced-order model is used to monitor the overall temperature of the cryogenic storage tank, including the minimum temperature, maximum temperature and average temperature.

[0065] To generate a temperature field reduced-order model, it is necessary to prepare a certain amount of temperature field sample data in a certain format, and then use artificial intelligence learning to process the temperature field sample data to generate a temperature field reduced-order model. After obtaining the temperature field sample data, the static reduced-order model method can be used to establish the temperature field reduced-order model.

[0066] The generation of the temperature field reduced-order model can be completed using simulation software. As an example, the generation of the temperature field reduced-order model can be done with the help of ANSYS Twin Builder software. ANSYS Twin Builder software is included in the ANSYS Electronics software package. Therefore, you need to install ANSYS Electronics first, then import the temperature field sample data into the Static ROM Builder module in ANSYS Twin Builder. In the Build tab, select the temperature field sample data, perform the reduction calculation, and generate the temperature field reduced-order model. Finally, in the Evaluate tab, save the temperature field reduced-order model and output the temperature field reduced-order model to ANSYS Twin Builder.

[0067] Because ANSYS Twin Builder is system simulation software, it is generally compatible with the FMI (Functional Mockup Interface) model interface specification. In the ANSYS Twin Builder project management window, locate the Generate Rom Models item and right-click to export the FMU (Functional Mockup Unit) model. This will export the reduced-order temperature field model as an FMU model. The FMU model complies with the FMI interface specification and can be used in other system simulation software, facilitating the subsequent construction of the digital twin model system in Simulink in this embodiment.

[0068] (3.2) Generate a reduced-order heat flow model.

[0069] Generating a heat flow reduction model requires preparing a certain amount of heat flow sample data in a certain format, and then using artificial intelligence learning to process the heat flow sample data to generate a heat flow reduction model. After obtaining the heat flow sample data, the response surface method can be used to establish a heat flow reduction model.

[0070] The generation of the heat flux reduced-order model can be completed using simulation software. As an example, the generation of the heat flux reduced-order model can be achieved with the help of the Response Surface ROM module in ANSYS Twin Builder. Heat flux sample data is imported into the ResponseSurface ROM module to generate the heat flux reduced-order model.

[0071] The Response Surface ROM module generates a heat flux reduced-order model based on response surface theory (also known as response surface methodology). The basic principle of response surface theory is to use an approximate function that is easy to calculate and approximates the true response function to approximate the true response function. The approximate function is generally a polynomial function. The approximate function is obtained by selecting a certain number of heat flux sample data and using iterative calculations. The more heat flux sample data, the more accurate the approximate function. However, the more heat flux sample data, the greater the computational cost. Therefore, a reasonable number of heat flux sample data should be selected in actual calculations.

[0072] Because ANSYS Twin Builder is system simulation software, it is generally compatible with the FMI model interface specification. In the ANSYS Twin Builder project management window, locate the Generate Rom Models item and right-click to export the FMU model. This will export the reduced-order heat flow model as an FMU model. The FMU model complies with the FMI interface specification and can be used in other system simulation software, facilitating the subsequent construction of the digital twin model system in Simulink in this embodiment.

[0073] (3.3) Build a digital twin model system.

[0074] (3.3.1) Temperature field monitoring digital twin model.

[0075] In Simulink, use the FMU Import module to import the FMU model file corresponding to the temperature field reduced-order model to generate a temperature field ROM (Reduced Order Model) module. Use the From Snapsheet module to import the data table generated by the sensor (including the real-time values ​​of liquid height, liquid temperature, gas temperature, and outer wall temperature). Use the temperature field ROM module to determine the temperature field, and use an oscilloscope to display the temperature field results. Connect each module to build a digital twin simulation model, that is, a temperature field monitoring digital twin model, such as Figure 6 shown.

[0076] (3.3.2) Digital twin model for pressure relief cycle prediction.

[0077] In Simulink, use the FMU Import module to import the FMU model file corresponding to the heat flow reduced-order model to generate a heat flow ROM module. Furthermore, combine it with the pressure relief cycle prediction module (including daily evaporation rate calculation and pressure relief cycle calculation), use the From Snapsheet module to import the data table generated by the sensor (including real-time values ​​of liquid phase height, liquid phase temperature, gas phase temperature, outer wall surface temperature, and gas phase pressure), determine the total heat flow on the outer wall through the heat flow ROM module, and predict the pressure relief cycle through the pressure relief cycle prediction module. Connect each module to build a digital twin simulation model, namely the pressure relief cycle prediction digital twin model, as shown in the figure. Figure 7 shown.

[0078] This embodiment connects different modules such as sensor data acquisition, heat flow reduction model, temperature field reduction model, daily evaporation rate calculation, and pressure relief cycle calculation to build a digital twin model system for cryogenic storage tanks. The digital twin model system includes a temperature field monitoring digital twin model and a pressure relief cycle prediction digital twin model. Subsequently, temperature field monitoring and pressure relief cycle prediction are completed based on the digital twin model system of the cryogenic storage tank.

[0079] At this time, in this embodiment, the process of establishing the temperature field reduced-order model and the heat flux reduced-order model includes the following steps.

[0080] (1) Construct a thermal simulation geometric parameterized model of a cryogenic storage tank.

[0081] Constructing a thermal simulation geometric parametric model of a cryogenic storage tank specifically includes: constructing a geometric model of the cryogenic storage tank, the geometric model including an inner tank model, an outer tank model, and a vacuum interlayer model located between the inner tank model and the outer tank model; setting geometric parameters and material parameters of the geometric model to obtain a thermal simulation geometric parametric model of the cryogenic storage tank, the geometric parameters including the thickness, length and inner diameter of the inner tank model and the thickness, length and outer diameter of the outer tank model, and the material parameters including the first thermal conductivity of the inner tank model, the second thermal conductivity of the outer tank model, and the third thermal conductivity of the vacuum interlayer model.

[0082] Among them, constructing the geometric model of the cryogenic storage tank specifically includes: constructing the geometric model of a quarter cryogenic storage tank, where a quarter cryogenic tank is a portion of the cryogenic tank determined after the cryogenic tank is evenly divided along the axial direction and the circumferential direction of the cryogenic tank. Specifically, the cryogenic tank is evenly divided along the axial direction to obtain two half cryogenic tanks, and one half cryogenic tank is evenly divided along the circumferential direction to obtain two quarter cryogenic tanks. The above-mentioned dividing process is only a hypothetical dividing process for clearly expressing the quarter cryogenic tank, and it is not a real dividing process of the cryogenic tank.

[0083] Among them, the first thermal conductivity coefficient is the thermal conductivity coefficient of the material used for the inner tank model, the second thermal conductivity coefficient is the thermal conductivity coefficient of the material used for the outer tank model, and the method for determining the third thermal conductivity coefficient includes: randomly determining multiple initial thermal conductivity coefficients; for each initial thermal conductivity coefficient, obtaining the experimental value of the total heat flow of the outer wall of the cryogenic storage tank determined by experiment under simulation parameters, determining the initial thermal simulation geometric parameterized model corresponding to the initial thermal conductivity coefficient, setting the boundary conditions of the initial thermal simulation geometric parameterized model based on the simulation parameters, obtaining the initial thermal simulation parameterized model, using the initial thermal simulation parameterized model to perform simulation calculations, and obtaining the simulation value of the total heat flow of the outer wall of the cryogenic storage tank corresponding to the initial thermal conductivity coefficient, and selecting the initial thermal conductivity coefficient with the smallest difference between the experimental value and the simulation value of the total heat flow of the outer wall as the third thermal conductivity coefficient. The simulation parameters include the simulation values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank.

[0084] If the minimum difference is not less than the preset difference, this embodiment selects multiple initial thermal conductivities again and performs calculations again until the minimum difference is less than the preset difference. At this time, the initial thermal conductivity with the smallest difference is selected as the third thermal conductivity.

[0085] (2) For each set of preset sample parameters, the boundary conditions of the thermal simulation geometric parameterized model are set based on the sample parameters to obtain the thermal simulation parameterized model. Simulation calculations are then performed based on the thermal simulation parameterized model to obtain the sample temperature field and total heat flux of the sample outer wall of the cryogenic storage tank corresponding to the sample parameters. The sample parameters include the sample values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, and outer wall temperature of the cryogenic storage tank.

[0086] The method for determining the sample parameters includes: obtaining the value ranges of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank; using the Latin hypercube sampling method to perform multiple samplings within the value ranges of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank, each sampling obtaining a set of sample parameters, and obtaining multiple sets of sample parameters through multiple samplings.

[0087] The boundary conditions of the thermal simulation geometric parameterized model are set based on the sample parameters to obtain the thermal simulation parameterized model, specifically including: determining the positions of the liquid and gas in the inner tank model based on the sample value of the liquid phase height of the cryogenic storage tank, setting the outer surface temperature of the outer tank model to the sample value of the outer wall temperature of the cryogenic storage tank, setting the temperature of the contact surface between the inner tank model and the liquid in the inner tank model to the sample value of the liquid phase temperature of the cryogenic storage tank, and setting the temperature of the contact surface between the inner tank model and the gas in the inner tank model to the sample value of the gas phase temperature of the cryogenic storage tank.

[0088] (3) Fit the sample temperature fields corresponding to all groups of sample parameters and each group of sample parameters to generate a temperature field reduced-order model; fit the total heat flux of the sample outer wall corresponding to all groups of sample parameters and each group of sample parameters to generate a heat flux reduced-order model.

[0089] The sample temperature fields corresponding to all groups of sample parameters and each group of sample parameters are fitted to generate a temperature field reduced-order model, and the total heat flux of the sample outer wall corresponding to all groups of sample parameters and each group of sample parameters are fitted to generate a heat flux reduced-order model, specifically including: taking the sample temperature fields corresponding to all groups of sample parameters and each group of sample parameters as input, fitting using the static reduced-order model method to generate a temperature field reduced-order model; taking the sample temperature fields corresponding to all groups of sample parameters and each group of sample parameters as input, fitting using the response surface method to generate a heat flux reduced-order model.

[0090] (2) Collecting the operating data of the cryogenic storage tank in real time through sensors.

[0091] In this embodiment, the operating data of the cryogenic storage tank is collected in real time through sensors and uploaded to the cloud as input data for the temperature field reduction model and the heat flow reduction model. The operating data includes: liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure.

[0092] (3) The daily evaporation rate is calculated based on the total heat flux of the outer wall and the latent heat of vaporization of the medium calculated in real time by the heat flux reduction model. The pressure relief period is predicted using the ideal gas state equation using the daily evaporation rate and gas phase pressure.

[0093] Since the heat flux reduction model outputs the total heat flux of the outer wall, the daily evaporation rate also needs to be calculated. In the digital twin model system, the MATLAB Function module can be used to calculate the daily evaporation rate.

[0094] The calculation formula of daily evaporation rate is shown in the following formula (1).

[0095] (1).

[0096] In formula (1), is the daily evaporation rate of the medium, in % / d (i.e. day); is the real-time total heat flux on the outer wall, in J / S; is the latent heat of vaporization of the medium, in J / kg; is the density of the medium, in kg / m 3 ; is the effective volume of the cryogenic storage tank, in m 3 .

[0097] Based on the daily evaporation rate of the cryogenic storage tank, conservatively assuming that the gas phase volume of the cryogenic storage tank remains unchanged, and using the ideal gas state equation, the calculation formula for the pressure relief period of the cryogenic storage tank is derived. The calculation formula for the pressure relief period is shown in Equation (2). In the digital twin model system, the calculation process of Equation (2) can be implemented using the MATLAB Function module in Simulink to predict the pressure relief period.

[0098] The calculation formula of the real-time pressure relief cycle is shown in the following formula (2).

[0099] (2).

[0100] In formula (2), is the real-time pressure relief period of the gas, in d; is the discharge pressure, in Pa; is the real-time monitoring value of the gas phase pressure of the cryogenic storage tank, in Pa; is the real-time gas phase volume of the cryogenic storage tank, in m 3 ; is the gas molecular mass corresponding to the medium, in g / mol. For example, if the medium is liquid nitrogen, then it is the gas molecular mass of nitrogen; is the gas constant, which is 8.31 J / (mol·K); It is the real-time monitoring value of the gas phase temperature of the cryogenic storage tank, in K.

[0101] At this time, in this embodiment, the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank are obtained, and the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank are used as input. The temperature field reduction model is used to determine the real-time temperature field of the cryogenic storage tank, and the heat flow reduction model is used to determine the real-time total heat flow of the outer wall of the cryogenic storage tank. Based on the real-time monitoring value of the gas phase pressure and the real-time total heat flow of the outer wall of the cryogenic storage tank, the real-time pressure relief cycle of the cryogenic storage tank is calculated.

[0102] Based on the real-time monitoring value of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow on the outer wall, the real-time pressure relief cycle of the cryogenic storage tank is calculated, specifically including: based on the real-time total heat flow on the outer wall, the daily evaporation rate is calculated, specifically calculated by formula (1); based on the real-time monitoring value of the gas phase pressure of the cryogenic storage tank and the daily evaporation rate, the real-time pressure relief cycle of the cryogenic storage tank is calculated, specifically calculated by formula (2).

[0103] The method for determining the real-time gas phase volume of a cryogenic storage tank includes: using the real-time monitoring value of the liquid phase height of the cryogenic storage tank as input, and using a gas phase volume reduction model to determine the real-time gas phase volume of the cryogenic storage tank, wherein the process of establishing the gas phase volume reduction model includes: obtaining multiple sample liquid phase heights, and for each sample liquid phase height, determining the sample gas phase volume of the cryogenic storage tank corresponding to the sample liquid phase height through three-dimensional modeling (i.e., modeling in three-dimensional modeling software, specifically in the three-dimensional modeling software, filling gas in the inner tank model based on the sample liquid phase height to determine the gas volume), fitting all sample liquid phase heights and the sample gas phase volumes corresponding to each sample liquid phase height to generate a gas phase volume reduction model.

[0104] Among them, all sample liquid phase heights and the sample gas phase volume corresponding to each sample liquid phase height are fitted to generate a gas phase volume reduced-order model, specifically including: taking all sample liquid phase heights and the sample gas phase volume corresponding to each sample liquid phase height as input, using the response surface method to perform fitting to generate a gas phase volume reduced-order model.

[0105] This embodiment provides a method for temperature field monitoring and pressure relief cycle prediction of a cryogenic storage tank based on digital twins, comprising the following steps: establishing a thermal simulation parameterized model of the cryogenic storage tank, generating training samples using DOE experiments, establishing a temperature field reduction model using a static order reduction model method, and establishing a heat flow reduction model using a response surface method to reduce computational complexity. The liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature, and gas phase pressure of the cryogenic storage tank are collected in real time by sensors, a temperature field is generated by the temperature field reduction model, and temperature field monitoring is completed. The total heat flow of the outer wall is generated by the heat flow reduction model, and the daily evaporation rate is calculated based on the total heat flow of the outer wall and the latent heat of vaporization of the medium. The pressure relief cycle is further predicted using the ideal gas state equation to complete the pressure relief cycle prediction, thereby achieving real-time monitoring of the temperature field and real-time prediction of the pressure relief cycle. This solves the problems of long time consumption and poor real-time performance of the numerical simulation method and low accuracy of the empirical formula method, effectively improving the safety and operating efficiency of the cryogenic storage tank, and reducing the loss and cost of cryogenic liquid caused by the pressure relief operation.

[0106] This embodiment uses digital twin technology to establish a temperature field reduction model and a heat flow reduction model for the cryogenic storage tank, and constructs a daily evaporation rate calculation formula and a pressure relief cycle calculation formula. Therefore, the temperature field, total heat flow of the outer wall, daily evaporation rate and pressure relief cycle of the cryogenic storage tank can be calculated quickly and in real time, overcoming the shortcomings of traditional numerical simulation methods such as long time consumption, poor real-time performance and inaccurate calculation of empirical formula methods.

[0107] The present application also provides an application scenario, which applies the above-mentioned cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method. Specifically, the cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method provided in this embodiment can be applied in the cryogenic storage tank operation scenario. The cryogenic storage tank operation scenario includes a prediction link and an operation link. The prediction link is used to determine the temperature field and pressure relief cycle of the cryogenic storage tank, and the operation link is used to control the operation of the cryogenic storage tank based on the temperature field and pressure relief cycle. The cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method provided in this embodiment belongs to the prediction link.

[0108] Example 2.

[0109] This embodiment provides a cryogenic tank temperature field monitoring and pressure relief cycle prediction device, which includes: a processor and a liquid level sensor, a first temperature sensor, a second temperature sensor, a third temperature sensor and a pressure sensor that are communicatively connected to the processor.

[0110] The liquid level sensor, the first temperature sensor, the second temperature sensor, the third temperature sensor and the pressure sensor are all installed on the cryogenic storage tank. The liquid level sensor is used to collect the real-time monitoring value of the liquid phase height of the cryogenic storage tank, the first temperature sensor is used to collect the real-time monitoring value of the liquid phase temperature of the cryogenic storage tank, the second temperature sensor is used to collect the real-time monitoring value of the gas phase temperature of the cryogenic storage tank, the third temperature sensor is used to collect the real-time monitoring value of the outer wall temperature of the cryogenic storage tank, and the pressure sensor is used to collect the real-time monitoring value of the gas phase pressure of the cryogenic storage tank.

[0111] The processor is used to obtain real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank, execute the cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method described in Example 1, and determine the real-time temperature field and real-time pressure relief cycle of the cryogenic storage tank.

[0112] Example 3.

[0113] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for monitoring the temperature field of a cryogenic storage tank and predicting a pressure relief cycle is implemented.

[0114] Those skilled in the art will understand that Figure 8 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0115] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief cycle in Example 1 is implemented.

[0116] Example 4.

[0117] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which, when executed by a processor, implements the method for monitoring the temperature field of a cryogenic storage tank and predicting a pressure relief cycle in Example 1.

[0118] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0119] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief cycle, characterized in that: The cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method includes: Obtain real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank; Taking the real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank as input, the temperature field reduction model is used to determine the real-time temperature field of the cryogenic storage tank, and the heat flow reduction model is used to determine the real-time total heat flow of the outer wall of the cryogenic storage tank; Calculating a real-time pressure relief cycle of the cryogenic storage tank based on the real-time monitored value of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow on the outer wall; Among them, the establishment process of the temperature field reduction model and the heat flow reduction model includes: constructing a thermal simulation geometric parameterized model of the cryogenic storage tank; for each set of preset sample parameters, setting the boundary conditions of the thermal simulation geometric parameterized model based on the sample parameters to obtain the thermal simulation parameterized model, and performing simulation calculations based on the thermal simulation parameterized model to obtain the sample temperature field and the total heat flow of the sample outer wall of the cryogenic storage tank corresponding to the sample parameters; fitting the sample temperature fields corresponding to all groups of the sample parameters and each group of the sample parameters to generate the temperature field reduction model, fitting the total heat flow of the sample outer wall corresponding to all groups of the sample parameters and each group of the sample parameters to generate the heat flow reduction model; the sample parameters include sample values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank; Based on the real-time monitoring value of the gas phase pressure of the cryogenic storage tank and the real-time total heat flow on the outer wall, the real-time pressure relief cycle of the cryogenic storage tank is calculated, specifically including: Calculating a daily evaporation rate based on the real-time total heat flux of the outer wall; Calculating a real-time pressure relief cycle of the cryogenic storage tank based on the real-time monitored value of the gas phase pressure of the cryogenic storage tank and the daily evaporation rate; The calculation formula of the daily evaporation rate is: ； in, is the daily evaporation rate of the medium; is the real-time total heat flux on the outer wall; is the latent heat of vaporization of the medium; is the density of the medium; is the effective volume of the cryogenic storage tank; The calculation formula of the real-time pressure relief period is: ； in, It is the real-time pressure relief cycle of gas; To release pressure; It is the real-time monitoring value of the gas phase pressure of the cryogenic storage tank; is the real-time gas phase volume of the cryogenic storage tank; is the gas molecular mass corresponding to the medium; is the gas constant; It is the real-time monitoring value of the gas phase temperature of the cryogenic storage tank.

2. The method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief period according to claim 1, characterized in that: Construct a parameterized geometric model for thermal simulation of cryogenic storage tanks, including: Constructing a geometric model of a cryogenic storage tank; the geometric model includes an inner tank model, an outer tank model, and a vacuum interlayer model located between the inner tank model and the outer tank model; The geometric parameters and material parameters of the geometric model are set to obtain a thermal simulation geometric parameterized model of the cryogenic storage tank; the geometric parameters include the thickness, length and inner diameter of the inner tank model and the thickness, length and outer diameter of the outer tank model; the material parameters include the first thermal conductivity of the inner tank model, the second thermal conductivity of the outer tank model and the third thermal conductivity of the vacuum interlayer model.

3. The method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief period according to claim 2, characterized in that: Constructing a geometric model of the cryogenic storage tank, specifically comprising: constructing a geometric model of a quarter of the cryogenic storage tank; the quarter cryogenic tank being a portion of the cryogenic storage tank determined by evenly dividing the cryogenic storage tank along the axial direction and the circumferential direction of the cryogenic storage tank; The first thermal conductivity is the thermal conductivity of the material used for the inner tank model; The second thermal conductivity is the thermal conductivity of the material used for the outer tank model; The method for determining the third thermal conductivity coefficient includes: randomly determining multiple initial thermal conductivities; for each of the initial thermal conductivities, obtaining an experimental value of the total heat flow of the outer wall of the cryogenic storage tank determined by experiments under simulation parameters, determining an initial thermal simulation geometric parameterized model corresponding to the initial thermal conductivity coefficient, setting boundary conditions of the initial thermal simulation geometric parameterized model based on the simulation parameters to obtain an initial thermal simulation parameterized model, performing simulation calculations using the initial thermal simulation parameterized model to obtain a simulation value of the total heat flow of the outer wall of the cryogenic storage tank corresponding to the initial thermal conductivity coefficient, and selecting the initial thermal conductivity coefficient with the smallest difference between the experimental value and the simulation value of the total heat flow of the outer wall as the third thermal conductivity coefficient; the simulation parameters include the simulation values ​​of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank.

4. The method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief period according to claim 1, characterized in that: The method for determining the sample parameters includes: obtaining the value ranges of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank; using the Latin hypercube sampling method to perform multiple samplings within the value ranges of the liquid phase height, liquid phase temperature, gas phase temperature and outer wall temperature of the cryogenic storage tank, and each sampling obtains a set of sample parameters.

5. The method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief period according to claim 2, characterized in that: The boundary conditions of the thermal simulation geometric parameterized model are set based on the sample parameters to obtain a thermal simulation parameterized model, specifically including: determining the positions of the liquid and gas in the inner tank model based on the sample value of the liquid phase height of the cryogenic storage tank, setting the outer surface temperature of the outer tank model to the sample value of the outer wall temperature of the cryogenic storage tank, setting the temperature of the contact surface between the inner tank model and the liquid in the inner tank model to the sample value of the liquid phase temperature of the cryogenic storage tank, and setting the temperature of the contact surface between the inner tank model and the gas in the inner tank model to the sample value of the gas phase temperature of the cryogenic storage tank.

6. The method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief period according to claim 1, characterized in that: Fitting the sample temperature fields corresponding to all groups of sample parameters and each group of sample parameters to generate the temperature field reduced-order model, and fitting the total heat flux of the sample outer wall corresponding to all groups of sample parameters and each group of sample parameters to generate the heat flux reduced-order model, specifically including: Taking all groups of sample parameters and the sample temperature field corresponding to each group of sample parameters as input, a static reduced-order model method is used for fitting to generate the temperature field reduced-order model; The total heat flux of the sample outer wall corresponding to all groups of sample parameters and each group of sample parameters is used as input, and the response surface method is used for fitting to generate the heat flux reduced-order model.

7. The method for monitoring the temperature field of a cryogenic storage tank and predicting the pressure relief period according to claim 1, characterized in that: A method for determining the real-time gas phase volume of a cryogenic storage tank includes: using a real-time monitored value of the liquid phase height of the cryogenic storage tank as input, and determining the real-time gas phase volume of the cryogenic storage tank using a gas phase volume reduction model; wherein the process of establishing the gas phase volume reduction model includes: obtaining a plurality of sample liquid phase heights, and for each of the sample liquid phase heights, determining the sample gas phase volume of the cryogenic storage tank corresponding to the sample liquid phase height by means of three-dimensional modeling; fitting all the sample liquid phase heights and the sample gas phase volume corresponding to each of the sample liquid phase heights to generate the gas phase volume reduction model; Among them, fitting all the sample liquid phase heights and the sample gas phase volumes corresponding to each of the sample liquid phase heights to generate the gas phase volume reduced-order model specifically includes: taking all the sample liquid phase heights and the sample gas phase volumes corresponding to each of the sample liquid phase heights as input, using the response surface method to perform fitting to generate the gas phase volume reduced-order model.

8. A cryogenic storage tank temperature field monitoring and pressure relief cycle prediction device, characterized in that: The cryogenic storage tank temperature field monitoring and pressure relief cycle prediction device includes: a processor and a liquid level sensor, a first temperature sensor, a second temperature sensor, a third temperature sensor and a pressure sensor connected to the processor in communication; The liquid level sensor, the first temperature sensor, the second temperature sensor, the third temperature sensor and the pressure sensor are all installed on the cryogenic storage tank. The liquid level sensor is used to collect and obtain a real-time monitoring value of the liquid phase height of the cryogenic storage tank. The first temperature sensor is used to collect and obtain a real-time monitoring value of the liquid phase temperature of the cryogenic storage tank. The second temperature sensor is used to collect and obtain a real-time monitoring value of the gas phase temperature of the cryogenic storage tank. The third temperature sensor is used to collect and obtain a real-time monitoring value of the outer wall temperature of the cryogenic storage tank. The pressure sensor is used to collect and obtain a real-time monitoring value of the gas phase pressure of the cryogenic storage tank. The processor is used to obtain real-time monitoring values ​​of the liquid phase height, liquid phase temperature, gas phase temperature, outer wall temperature and gas phase pressure of the cryogenic storage tank, execute the cryogenic storage tank temperature field monitoring and pressure relief cycle prediction method described in any one of claims 1-7, and determine the real-time temperature field and real-time pressure relief cycle of the cryogenic storage tank.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method for temperature field monitoring and pressure relief cycle prediction of a cryogenic storage tank according to any one of claims 1 to 7.

Images