Method for Controlling Pipeline Cold Quantity Loss during Liquid Nitrogen Explosion Suppression and Fire Extinguishing Process

Abstract

The present invention discloses a method for controlling the cold energy loss of pipelines during the liquid nitrogen explosion suppression and fire extinguishing process, which relates to the technical field of fire pipelines. The method includes: collecting and analyzing a conveying structure data set and a pipeline application environment data set, generating a throttling effect model and a heat and mass transfer characteristic model for coupled solution and verification and optimization, establishing a pipeline temperature gradient-pressure drop coupling model, and thereby performing optimization for minimizing cold energy loss within the pipeline design parameter space to obtain an optimized pipeline design layout scheme; performing cold energy loss control analysis on a multi-stage throttling device based on the fire extinguishing area situation information to determine the throttling device control parameters; and performing closed-loop control of the cold energy loss on the target liquid nitrogen transport pipeline based on the pipeline design layout optimization scheme and the throttling device control parameters. The technical effect of realizing intelligent targeted control of the cold energy loss of the liquid nitrogen transport pipeline, improving the cold energy loss control effect, and further ensuring the safety of liquid nitrogen explosion suppression and fire extinguishing is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of fire pipelines, and particularly to a method for controlling the cold loss of pipelines during the liquid nitrogen explosion suppression and fire extinguishing process. Background Art

[0002] Lithium-ion battery energy storage power stations are widely used in the energy storage field due to their high energy density and long life. However, when the battery undergoes thermal runaway, it will rapidly heat up and may cause fires or explosions, posing a great threat to personnel safety and equipment. Liquid nitrogen, as an efficient and environmentally friendly fire extinguishing medium, has a dual fire extinguishing mechanism of rapid cooling and oxygen isolation and suffocation. However, liquid nitrogen is easily affected by the external environment during pipeline transportation, resulting in cold loss and premature vaporization, thereby affecting its fire extinguishing effect. Therefore, how to effectively control the cold loss of liquid nitrogen during pipeline transportation has become an urgent technical problem to be solved.

[0003] However, the existing control effect of cold loss in liquid nitrogen transportation pipelines is poor, which affects the stability of liquid nitrogen transportation, and further leads to the technical problem of low safety in liquid nitrogen explosion suppression and fire extinguishing. Summary of the Invention

[0004] By providing a method for controlling the cold loss of pipelines during the liquid nitrogen explosion suppression and fire extinguishing process, the present invention solves the technical problem that the existing control effect of cold loss in liquid nitrogen transportation pipelines is poor, which affects the stability of liquid nitrogen transportation, and further leads to low safety in liquid nitrogen explosion suppression and fire extinguishing. The technical effect is achieved of intelligent targeted control of the cold loss of liquid nitrogen transportation pipelines through the optimization of pipeline design layout and the control of throttling devices, improving the control effect of cold loss, and further ensuring the safety of liquid nitrogen explosion suppression and fire extinguishing.

[0005] In view of the above problems, the present invention provides a method for controlling the cold loss of pipelines during the liquid nitrogen explosion suppression and fire extinguishing process.

[0006] In a first aspect, the present invention provides a method for controlling the cold energy loss in a pipeline during the liquid nitrogen explosion suppression and fire extinguishing process. The method includes: collecting and obtaining the pipeline transportation structure data set and the pipeline application environment data set of the target liquid nitrogen transportation pipeline, performing throttling effect analysis and heat and mass transfer characteristic analysis on the pipeline transportation structure data set and the pipeline application environment data set, and generating a throttling effect model and a heat and mass transfer characteristic model; coupling, solving, validating and optimizing the throttling effect model and the heat and mass transfer characteristic model to establish a pipeline temperature gradient - pressure drop coupling model; excavating and constructing a pipeline design parameter space, and performing optimization for minimizing cold energy loss in the pipeline design parameter space based on the pipeline temperature gradient - pressure drop coupling model to obtain an optimized pipeline design layout plan; selecting and setting a multi-stage throttling device at the end of the target liquid nitrogen transportation pipeline, performing cold energy loss control analysis on the multi-stage throttling device based on the fire extinguishing area situation information to determine the throttling device control parameters; and performing closed-loop control of cold energy loss on the target liquid nitrogen transportation pipeline based on the pipeline design layout optimization plan and the throttling device control parameters.

[0007] Further, the establishment of the pipeline temperature gradient - pressure drop coupling model includes: defining the data interfaces of the throttling effect model and the heat and mass transfer characteristic model, and determining the throttling model transfer variables and the heat and mass transfer model transfer variables; selecting a coupling solution algorithm according to the model coupling target and the target solution complexity, and using the coupling solution algorithm to perform iterative solution on the throttling effect model and the heat and mass transfer characteristic model in sequence based on the throttling model transfer variables and the heat and mass transfer model transfer variables to obtain a pipeline coupling solution model; setting a convergence criterion, and performing convergence judgment on the pipeline coupling solution model based on the convergence criterion until the convergence criterion is satisfied to obtain a basic pipeline coupling model; performing verification and evaluation on the basic pipeline coupling model to obtain coupling model performance information, and performing parameter optimization on the basic pipeline coupling model based on the coupling model performance information to establish a pipeline temperature gradient - pressure drop coupling model.

[0008] Further, the establishment of the pipeline temperature gradient - pressure drop coupling model includes: extracting parameters of the basic pipeline coupling model to obtain key coupling model parameters, and determining a model optimization target according to the coupling model performance information; initializing particle swarm parameters based on the value ranges of the key coupling model parameters, where the particle swarm parameters include particle positions and particle velocities; defining a parameter fitness function according to the model optimization target, and using the parameter fitness function to evaluate and iteratively update the particle swarm parameters until a preset convergence condition is satisfied, and determining the particle with the maximum fitness as the model parameter combination solution; and performing tuning and configuration on the basic pipeline coupling model based on the model parameter combination solution to establish the pipeline temperature gradient - pressure drop coupling model.

[0009] Further, obtaining the optimized pipeline design layout scheme includes: performing cold loss evaluation conversion based on the pipeline temperature gradient-pressure drop coupling model to generate a cold loss evaluation objective function; performing parameter encoding and initializing the population within the pipeline design parameter space to obtain a pipeline design parameter population, using the cold loss evaluation objective function to evaluate the individual loss degrees of the pipeline design parameter population, and obtaining a set of parameter solution loss degrees; performing loss degree ranking and parent solution selection on the pipeline design parameter population based on the set of parameter solution loss degrees to determine a parent parameter solution set; performing crossover and mutation operations and population iterative update on the pipeline design parameter population based on the parent parameter solution set to obtain an updated pipeline design parameter population, and optimizing the updated pipeline design parameter population to obtain the optimized pipeline design layout scheme.

[0010] Further, optimizing the updated pipeline design parameter population to obtain the optimized pipeline design layout scheme includes: dividing the updated pipeline design parameter population into multiple parameter solution intervals, uniformly selecting N interval parameter solutions within the multiple parameter solution intervals respectively; using the cold loss evaluation objective function to evaluate the N interval parameter solutions in sequence to obtain a set of N interval parameter loss degrees; performing minimum loss degree screening on the multiple parameter solution intervals based on the set of N interval parameter loss degrees to determine the first parameter solution interval; performing iterative segmentation optimization within the first parameter solution interval through the cold loss evaluation objective function, and comparing to obtain the optimized pipeline design layout scheme.

[0011] Further, comparing to obtain the optimized pipeline design layout scheme includes: dividing the first parameter solution interval into multiple parameter sub-intervals, and performing parameter solution selection evaluation and minimum loss degree screening on the multiple parameter sub-intervals through the cold loss evaluation objective function to obtain the second parameter solution interval; performing iterative evaluation and screening within the second parameter solution interval until the preset number of iterations to determine the target parameter solution interval; performing global optimization within the target parameter solution interval through the cold loss evaluation objective function to obtain the optimized pipeline design layout scheme.

[0012] Further, determining the control parameters of the throttling device includes: analyzing the liquid nitrogen explosion suppression and fire extinguishing requirements for the fire area situation information to obtain the liquid nitrogen fire extinguishing demand flow parameter and the liquid nitrogen fire extinguishing demand pressure parameter; performing control analysis on the multi-stage throttling device based on the liquid nitrogen fire extinguishing demand flow parameter and the liquid nitrogen fire extinguishing demand pressure parameter to determine the selection threshold of the throttling control parameter; performing comparison and optimization within the selection threshold of the throttling control parameter through the cold loss evaluation objective function to determine the control parameters of the throttling device.

[0013] Further, the method further includes: obtaining dynamic change information of the fire extinguishing area in real-time monitoring, extracting influencing factors from the dynamic change information of the fire extinguishing area to obtain a set of fire trend influencing factor parameters; analyzing the influence of cold loss on the target liquid nitrogen transport pipeline based on the set of fire trend influencing factor parameters to determine a cold loss influence factor of the pipeline; and optimizing and correcting the control parameters of the throttling device based on the cold loss influence factor of the pipeline.

[0014] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0015] By analyzing the throttling effect and heat and mass transfer characteristics of the delivery structure data set and pipeline application environment data set of the target liquid nitrogen transport pipeline, generating a throttling effect model and a heat and mass transfer characteristics model, coupling and solving and verifying and optimizing the throttling effect model and the heat and mass transfer characteristics model, establishing a pipeline temperature gradient-pressure drop coupling model, and performing optimization for minimizing cold loss within the pipeline design parameter space based on this to obtain an optimized pipeline design layout plan. At the same time, analyzing the cold loss control of a multi-stage throttling device based on the fire extinguishing area situation information to determine the control parameters of the throttling device, and performing closed-loop control of the cold loss of the target liquid nitrogen transport pipeline based on the optimized pipeline design layout plan and the control parameters of the throttling device. Furthermore, it achieves the technical effect of intelligent targeted control of the cold loss of the liquid nitrogen transport pipeline through pipeline design layout optimization and throttling device control, improves the cold loss control effect, and further ensures the safety of liquid nitrogen explosion suppression and fire extinguishing.

[0016] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the following specifically illustrates the embodiments of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic flow chart of the pipeline cold loss control method in the liquid nitrogen explosion suppression and fire extinguishing process of the present invention.

[0018] Figure 2 It is a schematic flow chart of establishing a pipeline temperature gradient-pressure drop coupling model in the pipeline cold loss control method in the liquid nitrogen explosion suppression and fire extinguishing process of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The present invention provides a method for controlling the cold energy loss of pipelines during liquid nitrogen explosion suppression and fire extinguishing, which solves the technical problems in the prior art that the control effect of cold energy loss in liquid nitrogen transportation pipelines is poor, affecting the stability of liquid nitrogen transportation, and further resulting in low safety of liquid nitrogen explosion suppression and fire extinguishing. The technical effect is achieved by optimizing the pipeline design layout and controlling the throttling device to achieve intelligent targeted control of the cold energy loss of the liquid nitrogen transportation pipeline, improving the control effect of cold energy loss, and further ensuring the safety of liquid nitrogen explosion suppression and fire extinguishing.

[0020] In order to make the objectives, technical solutions and advantages of the present invention more clear and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0021] The present invention will be described below with reference to the accompanying drawings in the present invention.

[0022] Embodiment, as Figure 1 shown, the present invention provides a method for controlling the cold energy loss of pipelines during liquid nitrogen explosion suppression and fire extinguishing, and the method includes:

[0023] Step S100: Collect and obtain the conveying structure data set and pipeline application environment data set of the target liquid nitrogen transportation pipeline, perform throttling effect analysis and heat and mass transfer characteristic analysis on the conveying structure data set and pipeline application environment data set, and generate a throttling effect model and a heat and mass transfer characteristic model.

[0024] Specifically, to ensure the control effect of the cold energy loss of the liquid nitrogen transportation pipeline, first collect and obtain the conveying structure data set and pipeline application environment data set of the target liquid nitrogen transportation pipeline through the liquid nitrogen transportation pipeline system. Among them, the target liquid nitrogen transportation pipeline is the liquid nitrogen transportation pipeline to be used for explosion suppression and fire extinguishing. The collected conveying structure data set includes pipeline materials: recording the materials of the pipeline, such as stainless steel, copper, aluminum, etc. Pipeline dimensions: including inner diameter, outer diameter, wall thickness, etc. Pipeline layout: the direction, bending radius, branching situation, etc. of the pipeline. Thermal insulation measures: the type, thickness, etc. of the thermal insulation material. Valves and joints: valve types, quantities, positions, joint types and connection methods; the pipeline application environment data set includes ambient temperature: recording the temperature range of the environment where the pipeline is located. Pressure conditions: the pressure change range inside the pipeline. Fluid characteristics: physical properties such as the density, viscosity, and thermal conductivity of liquid nitrogen. External interference: factors such as vibration and electromagnetic interference that may affect the pipeline performance.

[0025] Clean the pipeline application environment dataset for the transportation structure dataset, remove outliers and missing values, and standardize the cleaned datasets to ensure data consistency and comparability. Then, perform throttling effect analysis on the preprocessed transportation structure dataset and pipeline application environment dataset. First, use the principles of fluid mechanics to calculate the throttling effect in the pipeline, such as Bernoulli's equation and flow rate equation. Then, consider the influence of local resistance components such as valves, elbows, and diameter changes in the pipeline on the throttling effect. Use CFD (Computational Fluid Dynamics) software to perform numerical simulation on the pipeline, analyze the throttling effect, and adjust the simulation parameters to compare and verify with the experimental results. Based on the theoretical calculation and numerical simulation results, establish a throttling effect model that can predict the throttling effect of the pipeline under different working conditions.

[0026] Perform heat transfer and mass transfer characteristic analysis on the preprocessed transportation structure dataset and pipeline application environment dataset. First, conduct heat conduction analysis on the datasets, considering the thermal conductivity of the pipeline material, the thickness of the pipe wall, and the insulation measures on heat conduction, and use the heat conduction equation to calculate the heat transfer inside and outside the pipeline. Then, perform convective heat transfer analysis to analyze the convective heat transfer characteristics of liquid nitrogen in the pipeline, considering factors such as flow velocity and temperature gradient, and use the convective heat transfer coefficient formula for calculation. Furthermore, conduct mass transfer analysis, considering mass transfer processes such as evaporation and condensation of liquid nitrogen in the pipeline, and use the mass conservation equation and mass transfer coefficient for analysis. Use heat transfer and mass transfer simulation software to perform numerical simulation on the pipeline and design experiments to verify the accuracy of the simulation results. Finally, based on the heat conduction, convective heat transfer, and mass transfer analysis results, establish a heat transfer and mass transfer characteristic model that can predict the heat transfer and mass transfer performance of the pipeline under different working conditions. Through the above steps, the transportation structure and application environment data of the liquid nitrogen transportation pipeline can be systematically collected and analyzed, and then accurate throttling effect models and heat transfer and mass transfer characteristic models can be established, providing a scientific basis for the optimal design and operation management of the pipeline.

[0027] Step S200: Couple, solve, verify, and optimize the throttling effect model and the heat transfer and mass transfer characteristic model to establish a pipeline temperature gradient-pressure drop coupling model.

[0028] As Figure 2 shown, furthermore, for the establishment of the pipeline temperature gradient-pressure drop coupling model, the steps of the present invention further include:

[0029] Define the data interfaces of the throttling effect model and the heat and mass transfer characteristic model, and determine the transfer variables of the throttling model and the transfer variables of the heat and mass transfer model; according to the model coupling objective and the complexity of the objective solution, select a coupling solution algorithm, and based on the transfer variables of the throttling model and the transfer variables of the heat and mass transfer model, use the coupling solution algorithm to iteratively solve the throttling effect model and the heat and mass transfer characteristic model in sequence to obtain a pipeline coupling solution model; set a convergence criterion, and based on the convergence criterion, judge the convergence of the pipeline coupling solution model until the convergence criterion is met to obtain a basic pipeline coupling model; verify and evaluate the basic pipeline coupling model to obtain coupling model performance information, and based on the coupling model performance information, optimize the parameters of the basic pipeline coupling model to establish a pipeline temperature gradient-pressure drop coupling model.

[0030] Furthermore, for the establishment of the pipeline temperature gradient-pressure drop coupling model, the steps of the present invention further include:

[0031] Extract the parameters of the basic pipeline coupling model to obtain the key parameters of the coupling model, and determine the model optimization objective according to the coupling model performance information; initialize the particle swarm parameters based on the value range of the key parameters of the coupling model, where the particle swarm parameters include particle positions and particle velocities; define a parameter fitness function according to the model optimization objective, and use the parameter fitness function to evaluate and iteratively update the particle swarm parameters until the preset convergence condition is met, and determine the particle with the maximum fitness as the solution of the model parameter combination; optimize and configure the basic pipeline coupling model based on the model parameter combination solution to establish the pipeline temperature gradient-pressure drop coupling model.

[0032] Specifically, the pressure change caused by throttling may affect the heat and mass transfer process, and vice versa. Therefore, when coupling and solving the throttling effect model and the heat and mass transfer characteristic model, first define the data interfaces of the throttling effect model and the heat and mass transfer characteristic model, and determine the interfaces for data exchange between the models, including the variables transferred by the throttling model (such as pressure, flow rate) and the variables transferred by the heat and mass transfer model (such as temperature, heat flux). These variables are the basis for coupling and solving. According to the model coupling objective, such as predicting the overall performance of the pipeline system, and the complexity of the objective solution, select a suitable coupling solution algorithm, such as the finite difference method, the parallel iteration method, or the relaxation iteration method, etc. Based on the transfer variables of the throttling model and the transfer variables of the heat and mass transfer model, use the coupling solution algorithm to iteratively solve the throttling effect model and the heat and mass transfer characteristic model in sequence. In each iteration, solve the throttling effect model and the heat and mass transfer characteristic model in sequence. After solving one model, transfer the updated variable values to the other model as inputs to obtain the initial pipeline coupling solution model for each iteration.

[0033] Set convergence criteria, such as the relative change in the variable value is less than a certain threshold, or the iteration error is less than a certain threshold, or the number of iterations reaches the upper limit. Based on the convergence criteria, judge the convergence of the pipeline coupling solution model. Check the convergence after each iteration. If the convergence criteria are not met, continue the iteration until the convergence criteria are satisfied, and obtain a basic pipeline coupling model that can simultaneously predict the temperature gradient and pressure drop in the pipeline. Conduct a verification and evaluation of the basic pipeline coupling model, design experiments, collect data such as temperature gradients and pressure drops of the pipeline under different working conditions, compare the experimental data with the prediction results of the coupling model, evaluate the accuracy of the model, and obtain corresponding coupling model performance information, such as prediction accuracy, calculation efficiency, etc.

[0034] Based on the coupling model performance information, perform parameter tuning on the basic pipeline coupling model. First, extract the parameters of the basic pipeline coupling model to obtain the key parameters of the coupling model that have a significant impact on the model performance, such as hyperparameters, weight parameters, etc. And according to the coupling model performance information, determine the model optimization goal, such as improving the model accuracy, etc. Fit and transform the model optimization goal into a mathematical expression, define a parameter fitness function, such as a mean square error fitness function. The fitness function should be able to reflect the performance of the coupling model and guide the particles to move in a better direction for calculation during the optimization process. Initialize the particle swarm parameters based on the value range of the key parameters of the coupling model, that is, randomly generate a set of initial particles within the value range. The particle swarm parameters include particle positions, that is, the model parameter combination scheme, and particle velocities, that is, the moving update step size for each update of the model parameter combination. Each particle represents a model parameter combination and has a corresponding fitness value.

[0035] Use the parameter fitness function to evaluate and iteratively update the particle swarm parameters. In each iteration, calculate the fitness value of each particle. Update the individual optimal position and global optimal position of each particle according to the fitness value and particle velocity, ensuring that the updated positions of the particles are within the defined value range. After each iteration, check whether the convergence condition is met (such as reaching the maximum number of iterations or the change in the fitness value is less than a certain threshold). If the convergence condition is met, stop the iteration; otherwise, continue the next iteration until the preset convergence condition is satisfied, and determine the particle with the maximum fitness as the model parameter combination solution, that is, the global optimal position. Based on the model parameter combination solution, perform parameter tuning and configuration on the basic pipeline coupling model, that is, use the optimal parameter combination to re - establish the pipeline temperature gradient - pressure drop coupling model to guide the pipeline design and operation management. Use the particle swarm optimization algorithm to perform parameter tuning on the basic pipeline coupling model, establish a more accurate pipeline temperature gradient - pressure drop coupling model, and provide more powerful support for the optimal design and operation management of the pipeline.

[0036] Step S300: Mine and construct the pipeline design parameter space, and perform optimization for minimizing the cooling loss within the pipeline design parameter space based on the pipeline temperature gradient - pressure drop coupling model to obtain an optimized pipeline design layout scheme.

[0037] Furthermore, for obtaining the optimized pipeline design layout scheme, the steps of the present invention further include:

[0038] Perform evaluation conversion of the cooling loss based on the pipeline temperature gradient - pressure drop coupling model to generate an objective function for evaluating the cooling loss; perform parameter coding and initialize the population within the pipeline design parameter space to obtain a pipeline design parameter population, and use the objective function for evaluating the cooling loss to evaluate the individual loss degrees of the pipeline design parameter population to obtain a set of parameter solution loss degrees; perform loss degree ranking and selection of the parent solution for the pipeline design parameter population based on the set of parameter solution loss degrees to determine a set of parent parameter solutions; perform crossover and mutation operations and population iterative update on the pipeline design parameter population based on the set of parent parameter solutions to obtain an updated pipeline design parameter population, and perform optimization on the updated pipeline design parameter population to obtain an optimized pipeline design layout scheme.

[0039] Furthermore, for performing optimization on the updated pipeline design parameter population to obtain an optimized pipeline design layout scheme, the steps of the present invention further include:

[0040] Divide the updated pipeline design parameter population into multiple parameter solution intervals, and uniformly select N interval parameter solutions within each of the multiple parameter solution intervals; use the objective function for evaluating the cooling loss to evaluate the N interval parameter solutions in sequence to obtain N sets of interval parameter loss degrees; perform screening for the minimum loss degree on the multiple parameter solution intervals based on the N sets of interval parameter loss degrees to determine the first parameter solution interval; perform iterative segmentation and optimization within the first parameter solution interval through the objective function for evaluating the cooling loss, and compare to obtain an optimized pipeline design layout scheme.

[0041] Furthermore, for comparing to obtain an optimized pipeline design layout scheme, the steps of the present invention further include:

[0042] Divide the first parameter solution interval into multiple parameter sub - intervals, and perform parameter solution selection evaluation and minimum loss degree screening on the multiple parameter sub - intervals through the objective function for evaluating the cooling loss to obtain a second parameter solution interval; perform iterative evaluation and screening within the second parameter solution interval until a preset number of iterations to determine the target parameter solution interval; perform global optimization within the target parameter solution interval through the objective function for evaluating the cooling loss to obtain the optimized pipeline design layout scheme.

[0043] Specifically, to minimize the thermal interference of the external environment on the liquid nitrogen in the pipeline, it is necessary to optimize the layout design of the liquid nitrogen transportation pipeline. First, identify the key factors affecting the temperature gradient, pressure drop, and cold loss of the pipeline, such as pipeline length, insulation material, insulation layer thickness, type and location of throttling devices, etc. Then, based on engineering experience and actual requirements, conduct data mining on historical pipeline layout data, set reasonable value ranges for each key design parameter, and combine all key design parameters and their value ranges to form a multi-dimensional parameter space, constructing a pipeline design parameter space, which contains all possible pipeline layout schemes.

[0044] Based on the pipeline temperature gradient-pressure drop coupling model, conduct cold loss evaluation conversion. Cold loss refers to the part of the fluid's cold quantity reduction caused by factors such as temperature difference, heat conduction, and heat convection. In the pipeline system, cold loss may occur between the pipe wall and the fluid, within the fluid, and between the pipeline and the environment. Based on the first and second laws of thermodynamics, combined with the pipeline temperature gradient-pressure drop coupling model, fit and derive a calculation function for generating cold loss to calculate cold loss, which should include all factors affecting cold loss, such as flow rate, pipe diameter, material thermal conductivity, ambient temperature, etc. Embed the derived cold loss calculation function into the pipeline temperature gradient-pressure drop coupling model to achieve cold loss evaluation conversion. Define the optimization goal of pipeline design, that is, to minimize cold loss. Taking the pipeline design parameters as independent variables and the output result of the cold loss calculation function as the dependent variable, fit and construct a cold loss evaluation objective function to reflect the variation law of cold loss under different combinations of design parameters.

[0045] Encode the pipeline design parameters within the pipeline design parameter space, such as binary encoding or real number encoding, encode the pipeline design parameters into gene code chains, and initialize the population. Randomly generate a certain number of initial populations within the pipeline design parameter space, where each individual represents a pipeline design scheme, to obtain the pipeline design parameter population. Use the cold loss evaluation objective function to evaluate the individual loss degrees of the pipeline design parameter population, obtaining the corresponding parameter solution loss degree set, which reflects the cold loss situation of each scheme. Based on the parameter solution loss degree set, sort the pipeline design parameter population according to the loss degree. The lower the loss degree of an individual, the smaller its cold loss. Select the parent solutions in ascending order according to the loss degree set to determine a preset number of parent parameter solution sets for generating the next generation population. Based on the parent parameter solution sets, perform crossover and mutation operations on the pipeline design parameter population, that is, perform crossover and mutation operations on the selected parent individuals to generate new offspring individuals. The crossover operation can adopt methods such as single-point crossover, two-point crossover, or uniform crossover to increase the diversity of the population. Combine the newly generated offspring individuals with the parent individuals to form a new population, and use this to perform population iteration and update. Repeat the fitness evaluation, selection, crossover, and mutation operations until the preset number of iterations is reached or the fitness value converges, obtaining the updated pipeline design parameter population after expansion and update, ensuring the global diversity of the optimization of the pipeline design layout scheme.

[0046] Update the population optimization for the obtained pipeline design parameters. First, divide the updated population of pipeline design parameters into multiple parameter solution intervals, which represent different value ranges of pipeline parameters. Uniformly select N interval parameter solutions within the multiple parameter solution intervals, and these candidate solutions will be used for subsequent evaluation. Use the cold loss evaluation objective function to evaluate the loss degrees of the N interval parameter solutions in sequence, obtaining the corresponding N interval parameter loss degree sets. Based on the N interval parameter loss degree sets, perform a minimum loss degree screening on the multiple parameter solution intervals, and select the interval where the parameter solution with the minimum loss degree is located as the first parameter solution interval. Perform iterative segmentation optimization within the first parameter solution interval through the cold loss evaluation objective function. Specifically: divide the first parameter solution interval into multiple parameter sub-intervals, and repeat the above steps. Uniformly select parameter solutions and evaluate the loss degrees for the multiple parameter sub-intervals through the cold loss evaluation objective function, and then perform a minimum loss degree screening on them as the second parameter solution interval. Perform iterative evaluation and screening within the second parameter solution interval, repeating the above process of iterative segmentation and evaluation screening until the preset number of iterations. This will gradually narrow the range of parameter solutions until the target parameter solution interval is determined as the final parameter optimization range. Use the cold loss evaluation objective function to perform global evaluation and optimization within the target parameter solution interval, and obtain the one with the minimum loss degree as the optimized pipeline design layout scheme. Realize the targeted optimization analysis of the pipeline design layout scheme, effectively optimize the pipeline design layout, reduce the cold loss of the pipeline, and thereby improve the overall performance of the fire extinguishing system.

[0047] Step S400: Select and set a multi-stage throttling device at the end of the target liquid nitrogen transport pipeline, and perform cold loss control analysis on the multi-stage throttling device based on the fire extinguishing area situation information to determine the throttling device control parameters.

[0048] Furthermore, the step of determining the throttling device control parameters in the present invention further includes:

[0049] Perform an analysis of the liquid nitrogen explosion suppression and fire extinguishing requirements for the fire extinguishing area situation information to obtain the liquid nitrogen fire extinguishing required flow rate parameter and the liquid nitrogen fire extinguishing required pressure parameter; perform control analysis on the multi-stage throttling device based on the liquid nitrogen fire extinguishing required flow rate parameter and the liquid nitrogen fire extinguishing required pressure parameter to determine the selection threshold of the throttling control parameters; use the cold loss evaluation objective function to perform comparison and optimization within the selection threshold of the throttling control parameters to determine the throttling device control parameters.

[0050] Furthermore, the steps of the present invention further include:

[0051] Obtain the dynamic change information of the fire extinguishing area through real-time monitoring, extract the influencing factors of the dynamic change information of the fire extinguishing area to obtain the parameter set of the fire influencing factors; based on the parameter set of the fire influencing factors, analyze the influence of the cold loss of the target liquid nitrogen transportation pipeline, and determine the influencing factor of the pipeline cold loss; based on the influencing factor of the pipeline cold loss, optimize and correct the control parameters of the throttling device.

[0052] Specifically, according to the pipeline design layout optimization plan, select and set multi-stage throttling devices at the end of the target liquid nitrogen transportation pipeline, such as throttle valves, expansion valves, etc., to control the flow rate and pressure of liquid nitrogen and reduce the cold loss during the throttling process. At the end of the liquid nitrogen transportation pipeline, according to the specific requirements of the fire extinguishing area and the pipeline layout, reasonably set the positions of the multi-stage throttling devices. Clearly define the area range where liquid nitrogen fire extinguishing is required, including the space size, structural characteristics, potential fire source locations, etc., and then collect the situation information of the fire extinguishing area: including but not limited to key parameters such as fire type, fire size, combustible distribution, oxygen concentration, environmental temperature, etc. These information can be obtained through on-site monitoring equipment, sensor networks or remote monitoring systems. Conduct a cold loss control analysis on the multi-stage throttling device based on the situation information of the fire extinguishing area. Specifically: conduct an analysis on the liquid nitrogen explosion suppression and fire extinguishing requirements for the situation information of the fire extinguishing area. According to the collected situation information of the fire extinguishing area, evaluate the intensity, diffusion speed and possible development trend of the fire source. Based on the fire source intensity and the characteristics of the fire extinguishing area, calculate the required liquid nitrogen flow rate and pressure parameters, which usually involves a comprehensive consideration of the cooling effect, asphyxiation effect and diffusion ability of liquid nitrogen, and according to the calculation results, determine the range of liquid nitrogen flow rate and pressure parameters that meet the fire extinguishing requirements.

[0053] Conduct a control analysis on the multi-stage throttling device based on the liquid nitrogen fire extinguishing demand flow rate parameter and the liquid nitrogen fire extinguishing demand pressure parameter. The multi-stage throttling device controls the flow rate and pressure by reducing the aperture, and obtains the characteristics such as the aperture distribution, throttling efficiency, and pressure loss of the multi-stage throttling device. Based on the liquid nitrogen fire extinguishing demand flow rate parameter and pressure parameter, combined with the characteristics of the multi-stage throttling device, empirically analyze and determine the selection threshold of the throttling control parameters of the multi-stage throttling device, including the selection range of control parameters such as the opening degree and pressure of the throttling device under the condition of meeting the explosion suppression and fire extinguishing requirements. Use the cold loss evaluation objective function to compare and optimize within the selection threshold of the throttling control parameters. The loss degree evaluation and parameter comparison and optimization can be carried out within the selection threshold of the throttling control parameters through algorithms such as simulated annealing algorithm to determine the throttling device control parameters with the minimum cold loss degree. Realize the fire extinguishing adaptability control of the multi-stage throttling device to ensure that the liquid nitrogen transportation pipeline can minimize the cold loss while meeting the fire extinguishing requirements.

[0054] In addition, deploy a variety of sensors in the fire extinguishing area, such as temperature sensors, smoke sensors, infrared thermal imagers, etc., to monitor and obtain the dynamic change information of the fire extinguishing area in real time, including key information such as fire intensity, smoke concentration, temperature change, etc. Use machine learning or data mining techniques to extract influencing factors from the dynamic change information of the fire extinguishing area, identify the key factors affecting the fire intensity, and organize these key factors to obtain a set of fire intensity influencing factor parameters, including the position of the fire source, the size of the fire, wind speed, wind direction, humidity, etc. Based on the set of fire intensity influencing factor parameters, conduct an analysis of the influence of cold loss on the target liquid nitrogen transportation pipeline, and use mathematical models or simulation software to quantitatively analyze the specific influence of each factor on cold loss. These models require input parameters such as pipeline material, length, diameter, ambient temperature, wind speed, etc. According to the results of the quantitative analysis, determine the main influencing factors of pipeline cold loss, such as pipeline material, length, ambient temperature or wind speed, etc., and the degree of influence quantification of these factors, providing a basis for optimization and correction.

[0055] Optimize and correct the control parameters of the throttling device based on the influencing factors of pipeline cold loss. According to the influencing factors of cold loss and the specific influence degree of each influencing factor on cold loss, formulate an optimization and correction strategy for the control parameters of the throttling device. For example, when the ambient temperature rises, according to the associated control parameters of the throttling device, it may be necessary to increase the opening degree of the throttling device to reduce cold loss. According to the optimization and correction strategy, adjust the control parameters of the throttling device and monitor the effect after adjustment in real time. According to the real-time monitoring results, feedback and adjust the optimization and correction strategy to ensure that the control parameters of the throttling device reach the optimal state. Realize the real-time monitoring and analysis of the dynamic change information of the fire extinguishing area, optimize the control parameters of the throttling device of the liquid nitrogen transportation pipeline, and thus ensure the fire extinguishing efficiency and safety.

[0056] Step S500: Perform closed-loop control of cold loss on the target liquid nitrogen transportation pipeline based on the pipeline design layout optimization plan and the control parameters of the throttling device.

[0057] Specifically, a closed-loop control of the cold loss of the target liquid nitrogen transport pipeline is performed based on the pipeline design layout optimization scheme and the throttle device control parameters, specifically as follows: Install sensors and monitoring equipment at key positions of the pipeline to real-time monitor parameters such as the temperature, pressure, and flow rate of the pipeline. According to the collected data and analysis results, set reasonable control strategies, which may include setting the control parameter range of the throttle device, setting the threshold of cold loss, etc. When the monitoring system detects that the cold loss of the pipeline exceeds the set threshold, automatically adjust the control parameters of the throttle device to reduce the cold loss. At the same time, continuously optimize the control strategy according to the real-time data feedback to achieve closed-loop control. During the closed-loop control process, continuously monitor the cold loss situation of the pipeline to ensure the control effect. Through the pipeline design layout optimization and throttle device control, realize the intelligent targeted control of the cold loss of the liquid nitrogen transport pipeline, improve the control effect of the cold loss, and further ensure the safety of liquid nitrogen explosion suppression and fire extinguishing.

[0058] In summary, the pipeline cold loss control method provided by the present invention during the liquid nitrogen explosion suppression and fire extinguishing process has the following technical effects:

[0059] Due to the adoption of the technical solution of performing throttling effect analysis and heat transfer and mass transfer characteristic analysis on the transport structure data set and pipeline application environment data set of the target liquid nitrogen transport pipeline, generating a throttling effect model and a heat transfer and mass transfer characteristic model, then coupling and solving and verifying and optimizing the throttling effect model and the heat transfer and mass transfer characteristic model, establishing a pipeline temperature gradient-pressure drop coupling model, based on which minimizing the cold loss is optimized within the pipeline design parameter space to obtain a pipeline design layout optimization scheme, and at the same time performing cold loss control analysis on the multi-stage throttle device based on the fire extinguishing area situation information to determine the throttle device control parameters, and performing closed-loop control of the cold loss of the target liquid nitrogen transport pipeline based on the pipeline design layout optimization scheme and the throttle device control parameters. Furthermore, the technical effect of realizing the intelligent targeted control of the cold loss of the liquid nitrogen transport pipeline through the pipeline design layout optimization and throttle device control, improving the control effect of the cold loss, and further ensuring the safety of liquid nitrogen explosion suppression and fire extinguishing is achieved.

[0060] This specification and the drawings are only exemplary descriptions of the present invention, but the protection scope of the present invention is not limited thereto. It should be noted that any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should be covered by the protection scope of the present invention. In some cases, the actions or steps recorded in the present invention can be executed in a different order from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A method for controlling the cold quantity loss of pipelines during the liquid nitrogen explosion suppression and fire extinguishing process, characterized in that, The method includes: Collecting and obtaining the conveying structure data set and the pipeline application environment data set of the target liquid nitrogen transportation pipeline, performing throttling effect analysis and heat and mass transfer characteristic analysis on the conveying structure data set and the pipeline application environment data set, and generating a throttling effect model and a heat and mass transfer characteristic model; Coupling, solving, validating and optimizing the throttling effect model and the heat and mass transfer characteristic model to establish a pipeline temperature gradient-pressure drop coupling model; Mining and constructing a pipeline design parameter space, and performing optimization for minimizing cold loss in the pipeline design parameter space based on the pipeline temperature gradient-pressure drop coupling model to obtain an optimized pipeline design layout scheme; Selecting and setting a multi-stage throttling device at the end of the target liquid nitrogen transportation pipeline, performing cold loss control analysis on the multi-stage throttling device based on the fire extinguishing area situation information, and determining the throttling device control parameters; Performing closed-loop control of cold loss on the target liquid nitrogen transportation pipeline based on the pipeline design layout optimization scheme and the throttling device control parameters.

2. The method for controlling the cold quantity loss of the pipeline during the liquid nitrogen explosion suppression and fire extinguishing process according to claim 1, wherein, The establishment of the pipeline temperature gradient-pressure drop coupling model includes: Defining the data interfaces of the throttling effect model and the heat and mass transfer characteristic model, and determining the throttling model transfer variables and the heat and mass transfer model transfer variables; Selecting a coupling solution algorithm according to the model coupling objective and the target solution complexity, and using the coupling solution algorithm to perform iterative solution on the throttling effect model and the heat and mass transfer characteristic model in sequence based on the throttling model transfer variables and the heat and mass transfer model transfer variables to obtain a pipeline coupling solution model; Setting a convergence criterion, and performing convergence judgment on the pipeline coupling solution model based on the convergence criterion until the convergence criterion is met to obtain a basic pipeline coupling model; Verifying and evaluating the basic pipeline coupling model to obtain coupling model performance information, and performing parameter optimization on the basic pipeline coupling model based on the coupling model performance information to establish a pipeline temperature gradient-pressure drop coupling model.

3. The method for controlling the cold quantity loss of pipelines during the liquid nitrogen explosion suppression and fire extinguishing process according to claim 2, wherein, The establishment of the pipeline temperature gradient-pressure drop coupling model includes: Extracting parameters of the basic pipeline coupling model to obtain key parameters of the coupling model, and determining a model optimization objective according to the coupling model performance information; Initializing particle swarm parameters based on the value range of the key parameters of the coupling model, where the particle swarm parameters include particle positions and particle velocities; Defining a parameter fitness function according to the model optimization objective, and using the parameter fitness function to evaluate, iterate and update the particle swarm parameters until a preset convergence condition is met, and determining the particle with the maximum fitness as the model parameter combination solution; Performing tuning and configuration on the basic pipeline coupling model based on the model parameter combination solution to establish the pipeline temperature gradient-pressure drop coupling model.

4. The method for controlling the cold quantity loss of the pipeline during the liquid nitrogen explosion suppression and fire extinguishing process according to claim 1, wherein, The obtaining of the optimized pipeline design layout scheme includes: Performing cold loss evaluation conversion based on the pipeline temperature gradient-pressure drop coupling model to generate a cold loss evaluation objective function; Perform parameter coding and initialize the population within the pipeline design parameter space to obtain a pipeline design parameter population. Use the cold loss evaluation objective function to evaluate the individual loss degrees of the pipeline design parameter population and obtain a parameter solution loss degree set. Based on the parameter solution loss degree set, perform loss degree ranking and parent solution selection on the pipeline design parameter population to determine a parent parameter solution set. Based on the parent parameter solution set, perform crossover and mutation operations and population iteration update on the pipeline design parameter population to obtain an updated pipeline design parameter population, and optimize the updated pipeline design parameter population to obtain an optimized pipeline design layout scheme.

5. The method for controlling the cold quantity loss of the pipeline during the liquid nitrogen explosion suppression and fire extinguishing process according to claim 4, wherein The optimization of the updated pipeline design parameter population to obtain an optimized pipeline design layout scheme includes: Divide the updated pipeline design parameter population into multiple parameter solution intervals, and uniformly select N interval parameter solutions within the multiple parameter solution intervals. Use the cold loss evaluation objective function to evaluate the N interval parameter solutions in sequence to obtain an N interval parameter loss degree set. Based on the N interval parameter loss degree set, perform minimum loss degree screening on the multiple parameter solution intervals to determine the first parameter solution interval. Perform iterative segmentation optimization within the first parameter solution interval through the cold loss evaluation objective function, and compare to obtain an optimized pipeline design layout scheme.

6. The method for controlling the cold quantity loss of the pipeline in the liquid nitrogen explosion suppression and fire extinguishing process according to claim 5, wherein The comparison to obtain an optimized pipeline design layout scheme includes: Divide the first parameter solution interval into multiple parameter sub-intervals, and use the cold loss evaluation objective function to perform parameter solution selection evaluation and minimum loss degree screening on the multiple parameter sub-intervals to obtain a second parameter solution interval. Perform iterative evaluation and screening within the second parameter solution interval until a preset number of iterations to determine the target parameter solution interval. Use the cold loss evaluation objective function to perform global optimization within the target parameter solution interval to obtain the optimized pipeline design layout scheme.

7. The method for controlling the cold energy loss of the pipeline during the liquid nitrogen explosion suppression and fire extinguishing process according to claim 4, wherein The determination of the throttle device control parameters includes: Analyze the liquid nitrogen explosion suppression and fire extinguishing requirements for the fire extinguishing area situation information to obtain the liquid nitrogen fire extinguishing demand flow parameter and the liquid nitrogen fire extinguishing demand pressure parameter. Based on the liquid nitrogen fire extinguishing demand flow parameter and the liquid nitrogen fire extinguishing demand pressure parameter, perform control analysis on the multi-stage throttle device to determine the throttle control parameter selection threshold. Use the cold loss evaluation objective function to perform comparison and optimization within the throttle control parameter selection threshold to determine the throttle device control parameters.

8. The method for controlling the cold quantity loss of the pipeline during the liquid nitrogen explosion suppression and fire extinguishing process according to claim 7, characterized in that The method includes: Real-time monitor and obtain the dynamic change information of the fire extinguishing area, extract the influencing factors from the dynamic change information of the fire extinguishing area to obtain a fire influence factor parameter set. Based on the fire influence factor parameter set, perform cold loss influence analysis on the target liquid nitrogen transport pipeline to determine the pipeline cold loss influence factor. Based on the pipeline cold loss influence factor, optimize and correct the throttle device control parameters.

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