CN-122021213-A - Soot particle size distribution calculation method based on detailed transport model and partition method

CN122021213ACN 122021213 ACN122021213 ACN 122021213ACN-122021213-A

Abstract

The invention discloses a carbon smoke particle size distribution calculation method based on a detailed transportation model and a partition method, and belongs to the technical field of carbon smoke numerical simulation in a carbon-containing fuel combustion process. The method is based on a detailed transport model of a standard gas dynamic theory, is coupled with a limited rate chemical reaction model through a partitioning method, combines a detailed chemical reaction mechanism and a differential diffusion effect, and solves the problem that the traditional numerical method cannot accurately describe components, temperature and soot particle size distribution and component-soot interaction. The method comprises the specific steps of calculating component transportation characteristics through a detailed transportation model, coupling a partition method and a particle dynamics process, establishing a control equation, performing numerical discrete and solving, and combining a reference mapping model and a dynamic load balancing method to realize parallel simulation acceleration. The invention can predict key parameters such as components, temperature, soot volume fraction, particle size distribution and the like with high precision by solving the components and soot transportation in real time, and provides theoretical support for low-carbon emission design of the new energy burner.

Inventors

WANG FEI
YANG KUN
WANG ZHIPAN
XIE DINGXUAN

Assignees

长沙理工大学

Dates

Publication Date: 20260512
Application Date: 20251224

Claims (10)

1. The soot particle size distribution calculating method based on the detailed transportation model and the partition method is characterized by comprising the following calculating steps of: Step one, calculating the transportation characteristics of the mixture; for any component Based on standard gas dynamic theory, the depth of Lanna-Jones potential energy well is calculated according to the molecular geometry (single atom, linear molecule, nonlinear polyatomic molecule) and Lanna-Jones potential energy well depth ) Diameter of collision ) Dipole moment [ ] ) Polarity% ) And the number of rotation and relaxation collisions ) Calculating the composition Dynamic viscosity of [ (] ) Thermal conductivity [ ] ) Diffusion coefficient [ ] ); Component (A) Dynamic viscosity of [ (] ) Calculated from the following formula: Wherein, the Is the molecular mass of the polymer, Is the boltzmann constant, Is the temperature of the liquid at which the liquid is to be cooled, , ; Component (A) Heat conductivity of [ (] ) Calculated from the following formula: Wherein, the Is a component Is used for the preparation of a polymer, Is a general-purpose gas constant and is, Is the density and for a single atom molecule, For linear molecules, the linear molecules are, for example, In the case of non-linear polyatomic molecules, ; ; ; , , ; Component (A) Diffusion coefficient of [ ] ) Calculated from the following formula: Wherein, the Is the pressure at which the pressure is applied, ; In the calculated dynamic viscosity of each component ) Thermal conductivity [ ] ) Diffusion coefficient [ ] ) Based on the above, a proper detailed transportation model such as multicomponent, mixture average or very Liuz number is selected to calculate the dynamic viscosity of the mixture ) Thermal conductivity [ ] ) Diffusion coefficient [ ] ) Equal transport characteristics; Step two, establishing a soot partition; Log-discretizing the soot aggregates into particle sizes A plurality of partitions, each partition representing a specific particle size, whereby each soot aggregate is allocated to a respective partition according to the particle size; Step three, coupling particle dynamics process; For each zone, a series of dynamic processes of the soot particles are processed into source items to realize coupling, the dynamic processes of the soot particles comprise nucleation, agglomeration, condensation, surface growth, oxidation, fragmentation, deposition and the like, the nucleation is realized through dimerization of precursors, gas phase components and primary soot are connected, chemical components serving as precursors comprise acetylene molecules, polycyclic aromatic hydrocarbon molecules and the like, only soot of the lowest zone is influenced, when the agglomeration, condensation and surface growth occur, soot of the low zone moves to the high zone, soot of the high zone moves to the low zone through oxidation and fragmentation, the deposition is realized to remove the soot, and all mass exchange between the gas phase components and the soot is realized through exchanging carbon atom numbers, and hydrogen atoms in the gas phase components are combined to form hydrogen molecules, so that the complete coupling of the components-the soot is realized; establishing a mathematical model; Establishing a continuity equation, a momentum equation, a component equation and an energy equation based on a detailed chemical reaction mechanism, and establishing a soot aggregate number density and an initial particle number density equation based on a partition method under the consideration of thermophoresis and differential diffusion conditions, wherein parameters such as density, speed, temperature, pressure, component concentration and the like obtained by solving the continuity equation, the momentum equation, the component equation and the energy equation are used as input parameters of the soot aggregate number density transport equation and the initial particle number density transport equation, and the component reaction rate, the heat release rate and the like in a combustion solver are updated when the soot aggregate number density transport equation and the initial particle number density transport equation are solved, and are realized in a source item of a control equation; the form of the continuity equation, momentum equation, component equation, and energy equation is: Wherein, the And The pressure and the time, respectively, And The gas phase density and velocity respectively, Is that The coordinates of the direction are used to determine, Is the tensor of the reynolds stress, Is the specific heat capacity of constant pressure, And Respectively is a component of Mass fraction and component comprising soot reactions Is used for the reaction of the catalyst, And The sensible heat and the radiant heat comprising the soot reaction respectively, Is the rate of heat release caused by the combustion of the gas phase components and the soot reaction, Is a turbulent viscosity which is a function of the viscosity, And The turbulent schmitt and turbulent planter numbers respectively, 、、 And The change in the control equation source term for the fuel particles, 、 And Respectively dynamic viscosity, thermal conductivity and composition The diffusion coefficient in the mixture is calculated by the first step; For the one established in the second step The individual partitions respectively construct a soot aggregate number density and an initial particle number density control equation in the form of: Wherein, the And Respectively the first Zoned soot aggregate number density and initial particle number density, And Respectively the first The partitioned carbon smoke aggregate number density source item and the initial particle number density source item are obtained by adding the source items of the dynamic processes calculated in the step three; Is the first The thermophoresis speed of the subarea, Is the first The partitioned soot diffusion coefficient is solved by: Wherein, the , Is the first Average diameter of primary particles in the zoned soot aggregates; Fifthly, dispersing and solving numerical values; Dividing a computational domain grid, setting boundary conditions, and dispersing control equations by numerical values, wherein coupling of pressure and speed is realized through an operator splitting pressure implicit algorithm or a semi-implicit algorithm of an operator splitting pressure implicit and pressure correlation equation, constructing a corresponding algebraic equation set, and carrying out iterative solution; And step six, parallel acceleration is realized by combining a reference mapping model and a dynamic load balancing method.
2. The method for calculating the soot particle size distribution based on the detailed transportation model and the partition method according to claim 1, wherein in the first step, the transportation characteristics such as the dynamic viscosity, the thermal conductivity and the diffusion coefficient of the mixture are calculated by adopting the detailed transportation model such as multicomponent, mixture average or non-unit one-Lius number.
3. The method for calculating the soot particle size distribution based on the detailed transportation model and the partition method according to claim 1, wherein in the second step, the soot aggregates in the same partition are identical and consist of initial particles having the same spherical size.
4. The method according to claim 1, wherein in the third step, two or more soot particles collide and form a large particle, and the agglomeration means that two or more soot particles collide and adhere together, the condensation is modeled by collision of precursor molecules with the soot particles, the surface growth is realized by dehydrogenation and acetylene addition of the soot particles, and the oxidation is a process of oxidizing the soot particles with oxygen and hydroxyl groups, and the large soot particles are broken up into two or more small particles, and the structure of the soot particles has fractal dimension.
5. The method of claim 1, wherein in the third step, the source term of the soot transport equation describing the particle dynamics is calculated in real time by using the local concentrations of the relevant gas phase components and the thermochemical parameters.
6. The method for calculating the soot particle size distribution based on the detailed transportation model and the partition method according to claim 1, wherein in the fourth step, the component source term is solved by using the Euler implicit integration method based on the jacobian matrix of the reaction rate.
7. The method for calculating the particle size distribution of soot based on the detailed transportation model and the partition method according to claim 1, wherein in the fourth step, for turbulent combustion, the local concentration and the thermochemical parameter of the real-time gas phase component are obtained by using a finite rate combustion model, and for laminar combustion, the local concentration and the thermochemical parameter of the real-time gas phase component are obtained by using a uniform stirring reactor combustion model, and the reynolds stress tensor and the turbulent viscosity are both 0, 、、 And All 0.
8. The method for calculating the soot particle size distribution based on the detailed transportation model and the partition method according to claim 1, wherein in the fifth step, numerical dispersion is performed based on a finite volume method or a finite element method, and the iterative solution of each algebraic equation set is required to satisfy convergence conditions such as a given error range or a maximum iteration number.
9. The method for calculating the soot particle size distribution based on the detailed transportation model and the partition method according to claim 1, wherein in the sixth step, the component source term is obtained by reference demapping and is sent from the high-load processor to the low-load processor in parallel calculation.
10. The method according to claim 1, wherein in the sixth step, the calculated soot characteristics include soot volume fraction, particle size distribution, particle diameter, soot aggregate number density, initial particle number density, and the like.

Description

Soot particle size distribution calculation method based on detailed transport model and partition method Technical Field The invention relates to the technical field of combustion pollutant control, in particular to a method for calculating particle size distribution of soot particles in a combustion process based on coupling of a detailed transport model and a partition method. Background With the transformation of the global energy system to clean and low-carbonization, the ratio of renewable energy sources such as wind energy, solar energy and the like is remarkably improved, but the application of the traditional carbon-containing fuel in the fields of industry, traffic and the like still exists widely, and carbon smoke generated by incomplete combustion becomes an important source of pollution of atmospheric particulate matters. Soot is the main product of incomplete combustion of carbonaceous fuels, and its formation and evolution processes have a decisive influence on combustion efficiency, environmental emissions and equipment life. In the research of combustion process simulation and pollutant generation mechanism, traditional soot simulation methods are mostly based on simplified models, such as empirical relation, semi-empirical correlation or simplified dynamics models, and although the methods have high calculation efficiency, microscopic characteristics (such as particle size distribution and aggregate structure) of soot particles and dynamic interaction of the soot particles with gas phase components are difficult to capture accurately. Especially in complex combustion environments (such as internal combustion engines, gas turbines, aeroengines), the spatial distribution, number density and component-soot coupling effect of soot directly affect the accuracy of pollutant emission prediction, and conventional methods often introduce significant errors due to model simplification. Along with the expansion of the application of new energy technologies such as hydrogen-doped fuel, ammonia-doped fuel, biomass energy, synthetic fuel and the like in the fields of industrial combustion, traffic power and the like, the complexity and the variability of a carbon smoke generation path are obviously increased, and the requirements on the simulation precision of combustion pollutants are higher. In the prior art, some studies have attempted to combine detailed chemical reaction mechanisms with soot transport models, but have often faced computational efficiency bottlenecks. When a finite rate model based on a detailed chemical reaction mechanism is adopted, a large number of components and reactions are required to be processed, the calculation cost grows exponentially along with the reaction complexity, and the prediction accuracy of soot generation and evolution is influenced because the local concentration and thermochemical parameters of gas phase components cannot be accurately calculated by a traditional saland formula and a highly simplified unit-normal lewis number transport model. The traditional method for solving the soot is difficult to accurately describe the dynamic process and fractal structure of the soot particles, so that the particle size distribution of the soot cannot be accurately obtained in real time. In the combustion process of novel low-carbon fuels such as hydrogen-doped fuel, ammonia-doped fuel, biomass energy and synthetic fuel, the soot generation path is obviously different from that of the traditional fuel, and the traditional method is difficult to adapt to the change. In addition, the traditional parallel simulation method has defects in dynamic load distribution and data mapping, so that the utilization rate of computational resources is low in large-scale simulation, and high-efficiency component distribution and soot distribution solving are difficult to realize, so that quick iteration of a pollutant control strategy in the research and development of a new energy combustion technology is restricted. Aiming at the problems, the method creatively integrates a detailed transport model and a detailed chemical reaction mechanism of a standard gas dynamic theory, and realizes real-time accurate calculation of the spatial distribution of the carbon smoke aggregate number density and the initial particle number density through a coupling partition method and a limited rate chemical reaction model. Meanwhile, a reference mapping model and a dynamic load balancing technology are introduced, so that the parallel simulation efficiency is remarkably improved. Compared with the traditional method, the method improves the calculation precision of the components and the soot, realizes the prediction of the soot particle size distribution, greatly shortens the parallel simulation time, and provides a new technical path for solving the component distribution, the soot particle size distribution and the component-soot interaction in real time, accurately and efficiently. The breakthro