30 results about "Chemical reaction model" patented technology

The invention discloses a pulverized coal gasifier modeling method and device based on a CFD reduced-order model. Constructing a flow network model of the gasification furnace based on the functional partitions of the gasification furnace, and constructing a chemical reaction model of each functional partition; cFD simulation is carried out based on the flow network model and the chemical reaction model; constructing an order reduction model based on the CFD simulation result and the field experiment data of the gasification furnace; and carrying out hybrid modeling on the reduced-order model and the mechanism model of the gasification furnace to obtain a gasification furnace hybrid model. According to the technical scheme provided by the embodiment of the invention, a multi-disciplinary and multi-dimensional coupling technology is adopted for analogue simulation of the industrial pulverized coal gasifier, so that a high-precision model is realized in a manner of combining mechanism modeling with CFD reduced-order model data correction; and the defects of poor epitaxy and the like caused by structural data missing, mechanism data insufficiency and the like of a traditional pure mechanism model or data model device are overcome, and high-precision simulation of the process is realized.

The invention belongs to the technical field of computer aided design, and provides a C / C composite material thermochemical response and pore scale structure evolution prediction method, which comprises the following steps: constructing a geometric model of the pore scale of a rocket engine jet pipe; establishing a fluid flow model in a D2Q9 form; establishing a multi-component mass transport model in a D2Q5 form; establishing a heat transfer model in a D2Q5 form; establishing a heterogeneous chemical reaction model of the fluid-solid boundary; establishing an updating model of the composite material based on a volume pixel method; and based on a geometric model, a fluid flow model, a multi-component mass transport model, a heat transfer model, a heterogeneous chemical reaction model and an update model, predicting the thermochemical response and pore scale structure evolution of the C / C composite material in the rocket engine nozzle. The method is provided for studying the ablation process of the C / C composite material, and theoretical basis and guidance direction are provided for thermal performance study and fine design of the spray pipe.

The invention discloses a fractured reservoir acidification method based on a three-dimensional embedded discrete fracture model. The method comprises the following steps: S1, constructing a three-dimensional fractured reservoir physical model containing natural fractures; s2, carrying out structured grid division on the matrix, carrying out unstructured grid division on the crack by utilizing a matrix grid boundary, endowing physical parameters to the physical model, and setting acidification construction time; s3, fluid channeling coefficients between the matrix and the fractures and between the fractures are calculated; s4, based on the characteristics of the three-dimensional embedded discrete fracture model, constructing an acid liquor seepage model and an acid liquor chemical reaction model in the matrix and the fracture, and constructing a pore permeability evolution auxiliary equation of the matrix and the fracture; s5, coupling and solving the model and the equation in the S4; and S6, if the current time step reaches the construction time, obtaining a three-dimensional fractured reservoir acidification numerical simulation result. According to the method, high-precision dynamic coupling simulation of the three-dimensional complex fracture network and the acidification process is realized, and the method has a wide market application prospect.

The invention relates to a reaction process model construction method and a reaction safety prediction method. The method comprises the following steps: acquiring catalyst particle parameters and reactor reaction section parameters in the current reaction process; simulating the filling process of the catalyst particles in the fixed bed reactor based on the catalyst particle parameters and the reactor reaction section parameters to obtain a catalyst particle accumulation model; constructing a reaction process model of the current reaction process according to the particle position of the catalyst particle accumulation model; the reaction process model comprises a multiphase flow field model and a chemical reaction model which are coupled with each other. By adopting the method, the comprehensiveness and accuracy of a prediction result can be improved.

The invention discloses a rotary kiln multi-physical phenomenon numerical simulation method based on artificial intelligence reasoning, and relates to the technical field of rotary kiln multi-physical phenomenon simulation. On the basis of an Euler multiphase flow equation, a heat transfer model, a chemical kinetic reaction model, a particle growth model, a chemical reaction model and the like are added; establishing a three-dimensional numerical model capable of accurately simulating multiple physical and chemical phenomena such as gas-solid two-phase flow movement, combustion, NOx generation, clinker calcination and particle growth in the rotary kiln; a long-short-term memory neural network is introduced to build an AI model, the AI model is used for predicting the working condition of the second half section of the model, the simulation speed is increased, and long-time simulation of the rotary kiln is achieved.

The invention discloses a pollutant diffusion simulation and evaluation method for marine environmental protection, which belongs to the technical field of marine pollutants, and comprises the following steps: configuring a pollutant model based on obtained multi-source data, and performing dynamic factor initialization, initial data such as ocean current velocity and direction, tide height and period, wind field intensity and direction, temperature, salinity and pH value are obtained, and a chemical reaction model is defined based on the initial data in combination with a pollutant characteristic matrix. Through fusion and dynamic modeling of multi-source data, simulation precision of a pollutant diffusion path is remarkably improved, dynamic change characteristics of a diffusion process are accurately captured, and comprehensive analysis of pollutant diffusion behaviors is realized by combining efficient initialization of dynamic factors and multi-dimensional analysis of physical and chemical conditions. And reliable technical support is provided for marine pollution monitoring and evaluation.

The application discloses a rotary kiln multi-physical phenomenon numerical simulation method based on artificial intelligence reasoning, relates to the technical field of rotary kiln multi-physical phenomenon simulation, and is based on the Euler multiphase flow equation, adds a heat transfer model, a chemical dynamics reaction model, a particle growth model, a chemical reaction model and the like, establishes a three-dimensional numerical model capable of accurately simulating the multi-physical and chemical phenomena such as the gas-solid two-phase flow movement, combustion, NOx generation, clinker calcination and particle growth in the rotary kiln, introduces a long short-term memory neural network to build an AI model, uses the AI model to predict the latter half of the working condition, accelerates the simulation speed, and realizes long-time simulation of the rotary kiln.

The invention discloses a method and system for estimating the concentration of radioactive iodine species in a containment after an accident, and the method comprises the steps: inputting the content of gaseous iodine in the atmosphere of the containment, and calculating the acid content in the wall surface of the containment and the liquid phase of a pit; on the basis of the content of acid in the pit liquid phase and the content of a medicine added into the pit in advance, the pH value in the pit liquid phase is calculated through a pH model; determining the content of iodine which enters the liquid phase of the pit and does not participate in the chemical reaction of the liquid phase; on the basis of the content and the pH value of iodine which can be subjected to chemical reaction in the pool, combining an iodine water chemical equation, and calculating through a liquid phase chemical reaction model to obtain the concentrations of different iodine species in a liquid phase; calculating the mass transfer amount of gaseous iodine in the gas phase between the containment atmosphere and the pit water based on a pool mass transfer model; the content of gaseous iodine in the containment atmosphere is calculated through a gaseous iodine radiolysis and ionization model; determining the content of iodine deposited on the dry wall surface of the containment based on a gaseous iodine deposition model; and finally outputting the concentration of each iodine species in the gas liquid.

The invention relates to the technical field of water treatment disinfection monitoring, and discloses a chlorine dioxide intelligent monitoring system design method, system and medium, and the method comprises the steps: building a turbulence numerical model used for simulating the water flow movement of a disinfection tank and a chlorine attenuation model used for simulating the change of chlorine dioxide in the disinfection tank based on a CFD method; solving the turbulence numerical model and the chlorine attenuation model to obtain the attenuation change speed of chlorine dioxide in each area of the disinfection tank in the water flow flowing process; according to the distribution characteristics of the attenuation change speed, an area with the attenuation change speed larger than a set threshold value is set as a monitoring key area, a chlorine dioxide monitoring sensor is arranged in the monitoring key area, and the set threshold value is determined based on the allowable fluctuation range of the standard value of the residual chlorine at the outlet of the disinfection tank. The Realizable k-epsilon model and the limited rate chemical reaction model are utilized to accurately simulate attenuation of water flow and chlorine dioxide in the disinfection tank, concentration abnormity can be captured in time, and the regulation and control timeliness of the disinfection effect is improved.

The invention relates to a multi-target intelligent optimization method of a biomass supercritical water fluidized bed reactor. A two-fluid model is coupled with a chemical reaction model to carry out analog simulation on a reaction process of supercritical water and biomass under different operation parameters and reactor structure parameters, and the gas yield of gases such as hydrogen and the like is obtained; dividing data obtained by simulation into a training set, a test set and a verification set; constructing a neural network prediction model by adopting the training set, and evaluating the generalization ability of the ANN-GA neural network prediction model by adopting cross validation; and testing the precision of the neural network prediction model by using the test set and performing index evaluation. According to the method, the predicted value of the gas yield of the biomass supercritical water fluidized bed can be obtained according to industrial requirements, the process parameters and the structure combination under the expected target can be reversely obtained, the optimization time can be greatly saved, and the optimization cost of the biomass supercritical water fluidized bed reactor can be reduced.

The present invention discloses a pollutant diffusion simulation and assessment method for marine environmental protection, which belongs to the field of marine pollutant technology and includes the following steps: configuring a pollutant model based on obtained multi-source data, initializing dynamic factors, obtaining initialization data such as ocean current speed and direction, tidal height and period, wind field intensity and direction, temperature, salinity, and pH value, and defining a chemical reaction model based on the initialization data combined with the pollutant characteristic matrix. Through the fusion and dynamic modeling of multi-source data, the simulation accuracy of the pollutant diffusion path is significantly improved, and the dynamic change characteristics of the diffusion process can be accurately captured. Combined with the efficient initialization of dynamic factors and the multi-dimensional analysis of physical and chemical conditions, a comprehensive analysis of pollutant diffusion behavior is achieved, providing reliable technical support for marine pollution monitoring and assessment.

The invention discloses a rotary kiln temperature field real-time numerical simulation method based on deep learning, and the method comprises the following steps: S1), building a numerical simulation model of a rotary kiln based on an Euler-Lagrange discrete phase model, a coupled radiation model and a chemical reaction model through a computational fluid dynamics method; s2) determining boundary conditions and working condition parameters of the rotary kiln; s3) processing the temperature field sample data set obtained in the step 1) by using an intrinsic orthogonal decomposition method; s4) constructing a deep neural network of the gating circulation unit; s5) in a deployment application stage, obtaining a corresponding intrinsic orthogonal decomposition modal coefficient; s6, the internal temperature field of the rotary kiln is reconstructed, and real-time prediction.The prediction efficiency is greatly improved, computing resource consumption is remarkably reduced, the bottleneck of an existing numerical simulation technology in the aspect of real-time performance is broken through, and rapid and continuous thermal state evaluation and operation optimization decision support can be provided for an industrial site.

The present application relates to a kind of evaluation methods of lowest fuel ratio of blast furnace iron-making process, the three-dimensional model of blast furnace body is constructed in the present application;The three-dimensional model of blast furnace body is gridded;According to the principle of computational fluid dynamics, the three-dimensional model of blast furnace body is used as input model, and blast furnace submodel is established, and blast furnace submodel includes: furnace top cloth model, heat transfer model, mass transfer model, chemical reaction model, injection model, gas-solid two-phase model and soft melting zone model;The simulation model is integrated into blast furnace submodel;Production data and simulation model are used to simulate blast furnace production process;Adjust and optimize simulation model, when iron-making process parameters meet one of the following three states: the dew point temperature of furnace top gas temperature, the position of soft melting zone reaches blast furnace dead coke zone, and the temperature of molten iron is lower than the freezing point, the fuel ratio of blast furnace at this time is the lowest fuel ratio of blast furnace iron-making process;During the process, by changing parameters to observe its influence on fuel ratio, to more accurately determine the evaluation of lowest fuel ratio.

The present invention provides a method for determining the fire kinetic parameters of a lithium-ion battery electrolyte and a method for evaluating its fire hazard. The method for determining the fire kinetic parameters of a lithium-ion battery electrolyte includes the following steps: S1: Construct an electrolyte group model and obtain electrolyte environment parameters; S2: Obtain the evaporation free energy and the standard reaction Gibbs free energy of each elementary reaction; S3: Construct a combustion elementary reaction model; S4: Construct a chain chemical reaction model for each component of the electrolyte and calculate the reaction Gibbs free energy of each elementary reaction at different temperatures; S5: Determine the fire chemical kinetic parameters. Compared with the traditional experimental method, the present invention is faster and more accurate, can effectively reduce the model construction time, significantly improve the calculation accuracy, obtain more accurate fire kinetic parameters of the electrolyte, and thus accurately and quickly evaluate the fire hazard of lithium-ion batteries.

The invention relates to the technical field of waste gas emission control, and discloses an optimal control method and system for waste gas emission of a cement kiln and a storage medium. The method comprises the steps that multi-point oxygen concentration data and combustion temperature data are collected in real time, and an oxygen concentration change trend is generated in combination with a prediction model; based on the oxygen concentration change trend and the combustion temperature data, a filtering algorithm is adopted to predict the temperature distribution trend in the kiln in a future period of time, whether a local high-temperature area exists or not is judged, if yes, a key airflow path in the kiln is determined according to the temperature distribution trend, an airflow retention area is recognized, and an airflow organization state analysis result is obtained; a combustion chemical reaction model is established, the sulfide generation trend is judged, and combustion atmosphere regulation and control parameters are determined; and processing regulation and control parameters by adopting a control algorithm, determining an optimal oxygen supply quantity and an optimal air distribution proportion regulation strategy, monitoring emission concentrations of nitrogen oxides and sulfides, and dynamically correcting oxygen supply and air distribution parameters. The combustion efficiency of the kiln is improved.

This invention provides a soft measurement method and a readable storage medium for measuring the titanium dioxide grain size in a rotary kiln during the sulfuric acid process. The soft measurement method combines the flow model of the rotary kiln, the mass conservation equation, the energy conservation equation, the chemical reaction model of the rotary kiln, and the titanium dioxide grain size growth kinetic model. This allows for the calculation of the axial distribution of titanium dioxide grain size within the rotary kiln under different operating conditions. This method is of great significance for optimizing and controlling operating conditions such as fuel flow rate, air flow rate, material flow rate, and kiln speed in the rotary kiln reactor, thereby obtaining high-quality titanium dioxide products.

The invention discloses a DSMC method for coupling a surface catalytic reaction, which is characterized in that on the architecture of a basic DSMC method, a limited reaction rate model of the surface catalytic reaction is constructed by coupling physical adsorption, chemical adsorption, E-R composite reaction and L-H composite reaction; the method is used for considering heat flow contribution brought by surface reaction in prediction of the strength of an aircraft surface thermal protection system and characterization of a thermochemical unbalanced surface effect under a hypersonic flight condition. According to the DSMC method coupled with the surface catalytic reaction, compared with a traditional surface reflection and diffuse reflection gas-surface action model, a limited reaction rate model provides a gas-solid chemical reaction model based on multidisciplinary intersection of chemical kinetics, statistical mechanics and the like, heat flow contribution brought by the surface reaction can be further considered, and the method has the advantages that the method is simple and convenient to operate. The problem of inaccurate prediction of the heat flow intensity of the aircraft surface thermal protection system is effectively improved.

The invention discloses a soot particle size distribution calculation method based on a detailed transport model and a zoning method, and belongs to the technical field of soot numerical simulation in a carbon-containing fuel combustion process. According to the method, on the basis of a detailed transport model of a standard gas kinetic theory, a partitioning method is coupled with a limited rate chemical reaction model, and a detailed chemical reaction mechanism and a difference diffusion effect are combined, so that the problem that components, temperature, soot particle size distribution and component-soot interaction cannot be accurately described by a traditional numerical method is solved. The method comprises the following specific steps: calculating component transport characteristics through a detailed transport model, coupling a partition method and a particle dynamics process, establishing a control equation, discretizing and solving numerical values, and realizing parallel simulation acceleration in combination with a reference mapping model and a dynamic load balancing method. According to the method, key parameters such as components, temperature, soot volume fraction and particle size distribution can be predicted with high precision by solving the components and soot transportation in real time, and theoretical support is provided for low-carbon emission design of a new energy burner.

The invention relates to a quantitative calculation method for reservoir dissolution and permeation enhancement in the carbon dioxide oil displacement and storage process. The method comprises the following steps that an initial reservoir rock model composed of grid units is established; wherein the initial type of each grid unit comprises a pore space for a carbon dioxide-fluid to flow and a solid space occupied by rock particles; taking the grid units of which the attributes are solid nodes and the surrounding grid units are not completely occupied by the solid nodes as reaction grid units, and adapting to different chemical reaction models according to the attributes of the reaction grid units; and the attributes of all the reaction grid units are updated in parallel, a final reservoir rock model is formed when the corrosion rate reaches a preset target, and the corrosion permeation increasing phenomenon is quantitatively represented through the difference between the corrosion rate and the oil-phase and gas-phase relative permeability curve of the final reservoir rock model and the initial reservoir rock model. According to the method, the corrosion permeation increasing phenomenon of the carbon dioxide-fluid in the reservoir rock under different mineral compositions and temperature and pressure environments is quantitatively represented.

The invention discloses a data-driven CVD-SiC deposition rate prediction model and method, and belongs to the technical field of ceramic matrix composites and semiconductor materials.The data-driven CVD-SiC deposition rate prediction model comprises a reactor, graphite flakes and a deposition sample, the reactor and the deposition sample are both arranged in the reactor, the reactor is tightly attached to the inner wall of the reactor, and the graphite flakes are arranged in the reactor; according to the data-driven CVD-SiC deposition rate prediction model and the prediction method, the data-driven CVD-SiC deposition rate prediction model of the structure is adopted, the prediction method is combined, a more concise chemical reaction model and multi-field coupling of heat and mass transfer are established, and the deposition rate of the CVD-SiC is predicted. The deposition rate of the deposition surface under different process conditions can be accurately predicted, meanwhile, an accurate correlation function of the process conditions and the deposition rate is established through a machine learning method, the efficient and accurate relation between experimental parameters and the deposition rate is constructed, and combination of numerical simulation and machine learning is achieved.

The invention belongs to the field of numerical simulation of combustion discipline, and relates to a novel method for identifying a component coupling relation in a chemical reaction model. The method is based on a data mining theory, takes a reliable simplified reaction model library as a basis, can accurately recognize the coupling relationship between different components, and remarkably reduces the scale of a final simplified reaction model. Meanwhile, based on the method, the influence of pressure and equivalence ratio conditions and simplified targets (the ignition delay period and the component concentration) on the simplified reaction model structure is explored, simplified working conditions and simplified targets are defined, and the calculation cost of large-scale reaction model simplification can be remarkably reduced.

The invention provides a soft measurement method for the grain size of titanium dioxide in a rotary kiln in the process of preparing titanium dioxide through a sulfuric acid method and a readable storage medium, and the soft measurement method combines a flow model, a mass conservation equation, an energy conservation equation, a rotary kiln chemical reaction model and a titanium dioxide grain size growth kinetic model of the rotary kiln. According to the method, the axial distribution of the titanium dioxide grain size in the rotary kiln can be calculated according to different operation conditions, and the method has important significance in obtaining high-quality titanium dioxide products by optimizing and regulating the operation conditions such as fuel flow, air flow, material flow and kiln rotating speed in a rotary kiln reactor.

The invention relates to a composite material ablation pyrolysis evaluation method based on a lattice Boltzmann method, belongs to the technical field of solid rocket engines, solves the problem that an ablation pyrolysis mechanism of a composite material in the prior art is difficult to simulate and evaluate, and comprises the following steps: S1, taking a calculation area from a spray pipe and constructing the calculation area into a geometric model; s2, establishing an LBGK model in a D2Q9 form of fluid flow of the gas mixture flowing through the spray pipe; s3, establishing an LBGK model in a D2Q5 form for multi-component mass transportation of the gas mixture flowing through the spray pipe; s4, establishing a D2Q5-form LBGK model of heat transfer of the geometric model; s5, establishing a heterogeneous chemical reaction model of a fluid-solid interface; s6, establishing a pyrolytic reaction model of the resin matrix; s7, establishing an updating model of the carbon fiber solid and the resin matrix; and S8, based on the established model, carrying out transient simulation on the ablation pyrolysis behavior of the composite material of the spray pipe to obtain a simulation result and an evaluation scheme.

The invention relates to a method for evaluating a minimum fuel ratio in a blast furnace ironmaking process. The method comprises the following steps: constructing a three-dimensional model of a blast furnace body; gridding the three-dimensional model of the blast furnace body; according to the principle of computational fluid mechanics, the blast furnace body three-dimensional model serves as an input model, and blast furnace sub-models are established and comprise a furnace top material distribution model, a heat transfer model, a mass transfer model, a chemical reaction model, a blowing model, a gas-solid two-phase model and a soft melting zone model; integrating the blast furnace sub-models into a simulation model; performing blast furnace production process simulation by using the production data and the simulation model; the simulation model is adjusted and optimized, and when the ironmaking process parameters meet one of the three states that the furnace top gas temperature is at the dew point temperature, the soft melting zone position reaches the blast furnace dead coke zone and the molten iron temperature is lower than the freezing point, the blast furnace fuel ratio at the moment is the lowest fuel ratio in the blast furnace ironmaking process; in the process, the influence of parameters on the fuel ratio is observed by changing the parameters, so that the minimum fuel ratio is determined and evaluated more accurately.

The present invention discloses a method for constructing a microscopic reaction model of a polysilicon efficient deposition process, wherein the steps include: a. constructing the microscopic distribution state of gas and the microscopic distribution state of atoms on the surface of silicon rods; b. constructing a simulation box, introducing gas into the simulation box, and obtaining a preliminary chemical reaction model; c. optimizing the chemical reaction model; d. fixing all atoms in the cell layer at the bottom of the Si substrate in the chemical reaction model to complete the construction of the chemical reaction model. The present invention effectively solves the problem that the Si substrate cannot maintain a stable configuration at high temperature and is prone to agglomeration by fixing the Si cell layer; constructing a Si substrate (Si supercell) by periodically repeating the Si cell, and realizing the simulation of the continuous and uninterrupted Si rod surface. The chemical reaction model construction method of the present invention is applicable to the chemical vapor deposition process of polysilicon, and is also applicable to the gas-solid two-phase modeling process of other chemical vapor deposition processes.

The present application provides a method and device for simulating the cavity evolution of underground coal gasification. The method includes: generating a multi-field coupling constitutive model for underground coal gasification according to a pre-constructed stress-strain model, gas migration model, chemical reaction model, and energy balance model; establishing a finite element initial model for underground coal gasification based on the multi-field coupling constitutive model; and simulating the cavity evolution process of underground coal gasification according to the actual occurrence conditions of the coal seam and the finite element initial model. The method and device for simulating the cavity evolution of underground coal gasification provided by the present application achieve a full-dimensional prediction of the cavity modeling and development process of deep underground coal gasification, can simulate the boundary characteristics of the coal seam gasification cavity under different injection conditions, determine the influence of different underground coal gasification characteristic fields on the cavity evolution law, and provide technical support for optimizing the gasification process parameters under in-situ temperature and pressure conditions.

A mesoscale modeling method for a complex reaction transport process of a photocatalytic reaction system adopts a lattice Boltzmann multi-component flow model, and constructs a complex transmission process numerical model coupling light, heat, mass, flow and reaction based on a photocatalytic microreactor system; compared with the prior art, the method has the advantages that the component transformation process is simulated by introducing a source item into a density distribution function, and dynamic coupling of multi-component flow, diffusion and reaction heat absorption processes under the micro-mesoscale can be accurately simulated by combining an SC pseudo-potential model, a coupling dynamic chemical reaction model and a heat transfer model; the model can analyze coupling behaviors of illumination intensity, heat transfer, material transport and interface reaction at the same time, and is suitable for micromechanism research and enhanced regulation and control of multiple physical processes in a photocatalytic microreactor; the method effectively captures the production, aggregation, desorption and discharge processes of gas-phase products in the process of producing hydrogen through photocatalytic decomposition of water with porous structure characteristics.

The present invention discloses an adaptive step-size method for calculating zero-dimensional hydrogen-air combustion reactions, which can continuously adjust the time step as the reaction proceeds, saving calculation time. Based on the classic adaptive step-size strategy, adjustments are made according to the hydrogen-oxygen chemical reaction model, and the time step is continuously adjusted as the reaction proceeds, saving calculation time. Compared with the Runge-Kutta method, the method of the present invention can save a large amount of computational effort and easily implement the calculation of adaptive step-size. The method of the present invention is based on the Gear method, an implicit multi-step method for solving a system of ordinary differential equations. According to the characteristics of hydrogen-oxygen combustion, some improvements are made, making the calculation of hydrogen-oxygen combustion more stable and efficient.

The present invention belongs to the field of high voltage and insulation technology, and in particular relates to a numerical simulation method for the decomposition mechanism of partial discharge of environmentally friendly insulating gases. First, the electron transport parameters and energy transfer coefficient parameters are solved; secondly, the plasma chemical reaction model is used to ionize and decompose the environmentally friendly insulating gas to obtain the electron source term, heavy ion source term, and ion energy term; finally, the fluid dynamics model is used to obtain the convective motion distribution of the particles based on the obtained electron source term, heavy ion source term, and ion energy term control terms. The technical solution proposed by the present invention can be used to study the decomposition mechanism of PD of various environmentally friendly insulating gases without the need for a large number of experiments. It can evaluate the microscopic change mechanism of the discharge components of PD of environmentally friendly insulating gases and has broad application prospects in this field.

The application provides a condensed-phase explosive fuel volume explosion process calculation model and a construction method, and the construction method comprises the following steps: step 201, overall setting; step 202, VOF multiphase flow model setting; step 203, turbulent flow model setting; step 204, discrete particle combustion model setting; step 205, component chemical reaction model setting; and step 206, local initialization setting. The model construction method of the application uses Fluent fluid mechanics simulation software, stimulates the chemical reaction of a composite liquid-solid explosive fuel component, realizes numerical simulation of the volume explosion process of the condensed-phase explosive fuel, describes the volume explosion process through local initialization and the component chemical reaction model, has clear ideas and clear levels, can obtain accurate calculation results, and satisfies the calculation model meeting the actual engineering application requirements. The calculation model of the application can stimulate the chemical reaction of the composite liquid-solid explosive fuel under the precondition of obtaining the condensed-phase explosive fuel scattering distribution form, can clearly describe the change law of the volume explosion process of the condensed-phase explosive fuel.