In-cylinder oil-gas mixing optimization method based on liquid drop phase change state in high-density environment

Abstract

The invention discloses an in-cylinder oil-gas mixing optimization method based on a liquid drop phase change state in a high-density environment, and belongs to the technical field of in-cylinder oil-gas mixing, and the specific process is as follows: step 1, selecting an alkane component of which the density monotonically changes in a gas-liquid interface in a binary mixture as a reference component; 2, calculating density distribution and influence parameters of reference components in the normal direction of the gas-liquid interface; step 3, according to the density distribution of the reference component in the normal direction of the gas-liquid interface, calculating to obtain the characteristic interface thickness and surface tension of the gas-liquid interface; 4, calculating an average molecular free path and a Knudsen number according to the interface temperature, the equilibrium pressure and the average molecular hard sphere diameter; 5, jointly predicting the evolution of a gas-liquid interface space structure through the interface thickness, the surface tension, the average molecular free path and the Knudsen number; and 6, when the predicted result in the step 5 is that supercritical phase change of the liquid drops occurs, the Reynolds number of airflow in the cylinder is increased, and oil-gas mixing in the cylinder is optimized.

Description

Technical Field

[0001] The present invention belongs to the technical field of in-cylinder oil-gas mixing, and in particular relates to an in-cylinder oil-gas mixing optimization method based on a droplet phase change state under a high-density environment. Background Art

[0002] Yang and Meng and their team have made outstanding contributions in the field of phase change and mixing characteristics of fuel droplets in supercritical environments. Yang, Meng and others studied the transport mixing and dynamic evolution of single LOX droplets in supercritical laminar flow. They focused on two environmental factors, ambient pressure and convection velocity. Their research results also confirmed that the increase in ambient pressure would enhance the tensile deformation of droplets. After that, Yang, Meng and others studied the oil-gas mixing process of two LOX droplets in a supercritical convective nitrogen environment, providing more information about the effect of the interaction between the front and rear droplets on the oil-gas mixing. Sierra-Pallares et al. studied the effects of droplet size, ambient pressure and convection velocity on the oil-gas mixing process of fuel droplets in supercritical environments. Their results showed that the droplet size had no effect on the dynamic evolution of the droplets. Chae et al. studied the effects of ambient pressure and convection velocity on the dynamic evolution and vaporization characteristics of supercritical LOX droplets. They found that increased ambient pressure would accelerate the tensile deformation of droplets. They also concluded that under supercritical conditions, increasing ambient pressure would inhibit diffusion, which would lead to a shortened droplet life. Lee et al. simulated the mixing and deformation process of supercritical n-heptane droplets in a nitrogen environment far above the critical point of the fuel. Their numerical results showed that due to the disappearance of the gas-liquid interface and surface tension, the fuel droplets that initially maintained a spherical shape deformed significantly and formed a ring-shaped vortex at the tail. However, in their thermodynamic model, the thermodynamic properties of the fuel and gas did not consider the real gas effect, and the fluid density was assumed to be constant, so their results have certain limitations. The study of optimizing the in-cylinder mixed gas based on the thickness of the gas-liquid interface helps to optimize the effect of the oil-gas mixing in the cylinder from a microscopic perspective, and can regulate the in-cylinder airflow to optimize the oil-gas mixing by predicting the supercritical phase transition of the fuel in advance. However, since the thickness scale of the gas-liquid interface is at the nanometer level, traditional optical experimental methods cannot capture the evolution of the gas-liquid interface structure, and are not enough to reveal the mechanism of the supercritical phase transition of liquid fuel jets under trans / supercritical environments. Therefore, it is crucial to analyze the timing of the transition from the traditional two-phase evaporation-dominated mixing behavior to the supercritical unidirectional diffusion-dominated mixing behavior from the perspective of the microscopic gas-liquid interface. Summary of the invention

[0003] The purpose of the present invention is to provide an in-cylinder oil-gas mixing optimization method based on the phase change state of droplets under a high-density environment, so as to solve the problems that traditional optical experimental means in the prior art cannot capture the evolution process of the gas-liquid interface structure, and the real gas effect and poor oil-gas mixing uniformity are not considered in traditional thermodynamic models.

[0004] To achieve the above object, the present invention provides an in-cylinder oil-gas mixing optimization method based on the phase change state of droplets under a high-density environment, comprising the following steps:

[0005] Step 1, selecting an alkane component whose density changes monotonically at the gas-liquid interface in the binary mixture as a reference component, wherein the gas-liquid interface is the region between the alkane / nitrogen binary mixture in a gas-liquid phase equilibrium state;

[0006] Step 2, calculating the density distribution and influencing parameters of the reference component in the normal direction of the gas-liquid interface;

[0007] Step 3, according to the density distribution of the reference component in the normal direction of the gas-liquid interface, the characteristic interface thickness and surface tension of the gas-liquid interface are calculated;

[0008] Step 4, calculating the average molecular free path and Knudsen number according to the interface temperature, equilibrium pressure and average molecular hard sphere diameter;

[0009] Step 5, predicting the evolution of the spatial structure of the gas-liquid interface by using the interface thickness, surface tension, average molecular free path and Knudsen number. Specifically, when the Knudsen number is greater than 0.1, the interface thickness increases, the surface tension decreases, and the average molecular free path shortens, but it does not reach the limit; when the Knudsen number is not greater than 0.1, the interface thickness is the thickest, the surface tension is the smallest, and the average molecular free path is the shortest. It is predicted that the mixed fluid in the gas-liquid interface changes from a discontinuous fluid to a continuous fluid, and a supercritical phase transition occurs. At this time, the gas-liquid interface disappears and turns into a supercritical fluid boundary mixing layer;

[0010] Step 6: When the result predicted in step 5 is that the droplets undergo a supercritical phase transition, increase the Reynolds number of the airflow in the cylinder, establish a subcritical evaporation mixing model of droplets in a high-density convective environment and a supercritical diffusion mixing model of droplets in a high-density convective environment to jointly optimize the oil-gas mixing in the cylinder.

[0011] Preferably, the calculation expression of the density distribution of the reference component in the normal direction of the gas-liquid interface in step 2 is as follows:

[0012]

[0013] In the formula, ρ I,L is the liquid density, ρ I,V is the gas phase density, Δρ I is the density increment, N is the number of mesh nodes for the gas-liquid interface discretization, ρi Represents the density of the liquid phase.

[0014] Preferably, the influencing parameter κ in step 2 i,j The calculation expression is as follows:

[0015]

[0016] c 0,i =-2.985+4.332Z c,i +10.859Z c,i 2 -1.990ω i +1.798ω i 2 -5.436×10 -6 (θ r,i ) 2

[0017] c 1,i =-0.965+1.405Z c,i +2.746Z c,i 2 -0.963ω i +1.346ω i 2 -1.110×10 -6 (θ r,i ) 2

[0018] c 2,i =-0.121+0.156Z c,i +0.540Z c,i 2 -0.123ω i +0.090ω i 2 -0.219×10 -6 (θ r,i ) 2

[0019] In the formula, β i,j represents the binary interaction parameter, κ i represents the influence parameter of pure component i, κ j represents the influence parameter of pure component j, a i and b i are constants, N A represents Avogadro's constant, c 0,i 、c 1,i and c 2,i are the correlation coefficients of pure substances, T' r represents the characteristic temperature, Z c,i represents the critical compression factor, ωi represents the eccentricity factor, θ r,i Represents the contrast dipole moment.

[0020] Preferably, the specific calculation process of the surface tension of the gas-liquid interface in step 3 is as follows:

[0021] S31. The expression of surface tension σ1 in spatial coordinate form in the normal direction of the gas-liquid interface is as follows:

[0022]

[0023] S32. The spatial coordinate form in the normal direction of the gas-liquid interface is converted into the density distribution form in the normal direction of the gas-liquid interface by using the coordinate conversion rule. The specific calculation expression is as follows:

[0024]

[0025] In the formula, ρ M,i and ρ M,j are the densities of the liquid and gas components in the mixture, respectively. Subscript I represents the reference component, subscripts V and L represent the gas and liquid phases in phase equilibrium, respectively. i and ρ j are the densities of the liquid and gas phases, respectively, and σ represents the surface tension in the form of density distribution in the normal direction of the gas-liquid interface.

[0026] Preferably, the characteristic interface thickness l of the gas-liquid interface in step 3 is VLE The calculation expression is as follows:

[0027]

[0028] In the formula, ρ I,0 is the gas phase density of the reference component I at the initial integration point, z0 represents ρ I,0 The position where z represents ρ I Location, represents the giant thermodynamic potential energy density of the mixture, Indicates a negative value of the equilibrium pressure, is the huge thermodynamic potential energy density difference, the huge thermodynamic potential energy density difference The calculation expression is as follows:

[0029]

[0030] In the formula, ρ M,i represents the density of the liquid phase in the mixture, ρ M,j Represents the density of the gas phase in the mixture.

[0031] Preferably, the calculation expression for calculating the average molecular free path in step 4 according to the interface temperature, equilibrium pressure and average molecular hard sphere diameter is as follows:

[0032]

[0033] Where, d i is the diameter of the chain hard sphere, m i is the hard sphere number, is the hard sphere diameter, d is the average molecular hard sphere diameter, x i is, Λ is the average molecular free path, k B is the Boltzmann constant, T is the interface temperature, and P is the equilibrium pressure;

[0034] The ratio of the average molecular free path to the characteristic interface thickness is the Knudsen number, which is calculated as follows:

[0035]

[0036] Where Kn is the Knudsen number.

[0037] Preferably, in step 6, a subcritical evaporation mixing model of droplets in a high-density convection environment is established based on the VOF method, including a continuity equation, a momentum equation, an energy equation, and a component equation, as follows:

[0038] The VOF method is used to capture the interface between the gas and liquid phases, and the piecewise linear interface algorithm is used to reconstruct the high-resolution gas-liquid interface. In the VOF method, the sum of the volume fractions of the liquid and gas phases in any control volume is always 1. The specific expression is as follows:

[0039]

[0040] In the formula, α l is the liquid phase volume fraction;

[0041] The calculation expression of the continuity equation is as follows:

[0042]

[0043] Where ρ is the density, is the velocity, α is the volume fraction, subscript q is the phase q, S m,q represents the mass source term, which is used to describe the mass transfer process between gas and liquid phases. Specifically, the mass transfer rate at the gas-liquid interface is calculated by a mass transfer model with a physical basis. Based on this mass transfer model, the mass transfer rate It is calculated by the following equation:

[0044]

[0045] Where δ is the evaporation coefficient, R is the universal gas constant, and T ν represents the saturation temperature, P ν is the saturation pressure, Pi is the vapor partial pressure at the gas-liquid interface. Finally, combined with the Clausius-Clapeyron relationship, the mass transfer rate in the above equation is Converted to the following form:

[0046]

[0047] Where ΔH represents the enthalpy difference, T i represents the temperature at the gas-liquid interface, ρ v Represents density. The above formula is the mass source term S used in this model. m,q final form;

[0048] The calculation expression of the momentum equation is as follows:

[0049]

[0050] In the formula, P represents pressure, μ represents viscosity, represents the gradient, It represents the surface tension existing in the gas-liquid interface. The surface tension is calculated by the following formula:

[0051]

[0052] Where κ represents the curvature, ρ l represents the liquid side density, ρ g represents the gas phase density, σ is the surface tension coefficient, and the surface tension coefficient σ under subcritical conditions is calculated by the following relationship:

[0053]

[0054] Where P c represents the critical pressure, T c represents the critical temperature, ω represents the eccentricity factor, and T represents the interface temperature;

[0055] The calculation expression of the energy equation is as follows:

[0056]

[0057] Where E represents the energy of the binary mixture, calculated using the mass average method, and λ represents the thermal conductivity. is the stress tensor, T is the temperature, h i,q is the enthalpy of component i in phase q, is the diffusion flux, S h represents the energy source term, and the calculation expression is as follows:

[0058]

[0059] The calculation expression of the component equation is as follows:

[0060]

[0061] Where Y i.q is the mass fraction of component i in phase q, S s,q represents the component source term, α q represents the volume fraction, ρ q represents density, represents the diffusion flux of component i in phase q. In all the above equations, the density ρ, thermal conductivity λ and viscosity μ of the binary mixture are calculated by the volume fraction averaging method, and the constant pressure specific heat cp of the binary mixture is calculated by the mass averaging method.

[0062] Preferably, the high-density convective environment droplet supercritical diffusion mixing model established in step 6 includes four control equations, specifically the continuity control equation, the momentum control equation, the energy control equation and the component control equation. The calculation expression of each control equation is as follows:

[0063] Continuity equation:

[0064]

[0065] Momentum equation:

[0066]

[0067] Where, I represents impulse;

[0068] Energy equation:

[0069]

[0070] In the formula, h j represents the enthalpy of component j; the second term on the right side of the above formula represents the temperature gradient due to component diffusion, i.e., the Dufour effect;

[0071] Component equation:

[0072]

[0073] In the formula, is the diffusion flux of component i, and the calculation expression is as follows:

[0074]

[0075] Where D i,m represents the mass diffusion coefficient of component i, D T,i represents the thermal diffusion coefficient of component i, represents the mass fraction gradient of component i, the second term on the right side of the above formula It represents the component transport caused by the additional concentration gradient caused by the temperature gradient, namely the Soret effect.

[0076] Therefore, the present invention adopts the above-mentioned in-cylinder oil-gas mixing optimization method based on the phase change state of droplets under high-density environment. By establishing a gas-liquid interface model, it can quickly and accurately determine whether the droplets enter the supercritical state, and by establishing a subcritical evaporation mixing model and a supercritical diffusion mixing model under a high-density convection environment, it is obtained that when the droplets enter the supercritical state, the Reynolds number of the airflow in the cylinder is increased, thereby promoting oil-gas mixing.

[0077] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is an overall flow chart of the in-cylinder oil-gas mixing optimization method based on the phase change state of droplets under high-density environment of the present invention;

[0079] Figure 2 It is a curve diagram showing the change of giant thermodynamic potential energy density difference with the density distribution in the gas-liquid interface;

[0080] Figure 3 It is a graph showing the variation of the average molecular free path with the composition of the saturated gas phase mixture under different ambient pressures;

[0081] Figure 4 is a graph showing the variation of Knudsen number with interface temperature at different equilibrium pressures;

[0082] Figure 5 It is a graph showing the change of gas-liquid interface thickness with interface temperature under different pressures;

[0083] Figure 6 It is a graph showing the change of surface tension of gas-liquid interface with interface temperature under different pressures;

[0084] Figure 7 The figure shows the influence of air flow rate on the dynamic evolution of droplets and the oil-gas mixing process in different modes; (a) shows the influence of the dynamic evolution of droplets and the oil-gas mixing process in the subcritical evaporation mixing mode, and (b) shows the influence of the dynamic evolution of droplets and the oil-gas mixing process in the supercritical diffusion mixing mode;

[0085] Figure 8 It is a curve diagram of the change of the average mass fraction of n-heptane of n-heptane droplets at different air flow rates;

[0086] Fig. 9 The figure shows the influence of different Reynolds numbers on the droplets; (a) is the distribution diagram of the mass fraction of n-heptane, and (b) is the distribution diagram of the vorticity;

[0087] Fig.10The graphs are the influence of different Reynolds numbers on the properties of n-heptane droplets; (a) is the influence of the stratification coefficient, and (b) is the influence of the droplet phase change rate;

[0088] Fig.11 This is a graph showing the effect of Reynolds number on the thermodynamic state evolution of a binary mixture of n-heptane / nitrogen. DETAILED DESCRIPTION

[0089] The following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0090] See also Figure 1-11 , an in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment, comprising the following steps:

[0091] Step 1, selecting an alkane component whose density changes monotonically at the gas-liquid interface in the binary mixture as a reference component, wherein the gas-liquid interface is the region between the alkane / nitrogen binary mixture in a gas-liquid phase equilibrium state;

[0092] Step 2, calculating the density distribution and influencing parameters of the reference component in the normal direction of the gas-liquid interface;

[0093] Among them, the calculation expression of the density distribution of the reference component in the normal direction of the gas-liquid interface is as follows:

[0094]

[0095] In the formula, ρ I,L is the liquid density, ρ I,V is the gas phase density, Δρ I is the density increment, N is the number of grid nodes for the gas-liquid interface discretization, ρ i Represents the density of the liquid phase.

[0096] Influencing parameter κ i,j The calculation expression is as follows:

[0097]

[0098] c 0,i =-2.985+4.332Z c,i +10.859Z c,i 2 -1.990ω i +1.798ω i 2 -5.436×10 -6(θ r,i ) 2

[0099] c 1,i =-0.965+1.405Z c,i +2.746Z c,i 2 -0.963ω i +1.346ω i 2 -1.110×10 -6 (θ r,i ) 2

[0100] c 2,i =-0.121+0.156Z c,i +0.540Z c,i 2 -0.123ω i +0.090ω i 2 -0.219×10 -6 (θ r,i ) 2

[0101] In the formula, β i,j represents the binary interaction parameter, κ i represents the influence parameter of pure component i, κ j represents the influence parameter of pure component j, a i and b i are constants, N A represents Avogadro's constant, c 0,i 、c 1,i and c 2,i are the correlation coefficients of pure substances, T' r represents the characteristic temperature, Z c,i represents the critical compression factor, ω i represents the eccentricity factor, θ r,i Represents the contrast dipole moment.

[0102] Step 3, according to the density distribution of the reference component in the normal direction of the gas-liquid interface, the characteristic interface thickness and surface tension of the gas-liquid interface are calculated;

[0103] Among them, the specific calculation process of the surface tension of the gas-liquid interface is as follows:

[0104] S31. According to the linear density gradient theory, the surface tension κ1 in the space coordinate form in the normal direction of the gas-liquid interface is expressed as follows:

[0105]

[0106] S32. The spatial coordinate form in the normal direction of the gas-liquid interface is converted into the density distribution form in the normal direction of the gas-liquid interface by using the coordinate conversion rule. The specific calculation expression is as follows:

[0107]

[0108] In the formula, ρ M,i and ρ M,j are the densities of the liquid and gas components in the mixture, respectively. Subscript I represents the reference component, subscripts V and L represent the gas and liquid phases in phase equilibrium, respectively. i and ρ j are the densities of the liquid and gas phases, respectively, and σ represents the surface tension in the form of density distribution in the normal direction of the gas-liquid interface.

[0109] Characteristic interface thickness l of the gas-liquid interface VLE The calculation expression is as follows:

[0110]

[0111] In the formula, ρ I,0 is the gas phase density of the reference component I at the initial integration point, z0 represents ρ I,0 The position where z represents ρ I Location, represents the giant thermodynamic potential energy density of the mixture, Indicates a negative value of the equilibrium pressure, is the huge thermodynamic potential energy density difference, the huge thermodynamic potential energy density difference The calculation expression is as follows:

[0112]

[0113] In the formula, ρ M,i represents the density of the liquid phase in the mixture, ρ M,j Represents the density of the gas phase in the mixture.

[0114] Step 4: Calculate the average molecular free path and Knudsen number based on the interface temperature, equilibrium pressure and average molecular hard sphere diameter; the specific calculation expression is as follows:

[0115]

[0116]

[0117] Where, d i is the diameter of the chain hard sphere, m i is the hard sphere number, is the hard sphere diameter, d is the average molecular hard sphere diameter, x i is, Λ is the average molecular free path, k Bis the Boltzmann constant, whose value is k B =1.380649×10 -23 J / K, T is the interface temperature, P is the equilibrium pressure;

[0118] The ratio of the average molecular free path to the characteristic interface thickness is the Knudsen number, which is calculated as follows:

[0119]

[0120] Where Kn is the Knudsen number.

[0121] Step 5, predicting the evolution of the spatial structure of the gas-liquid interface by using the interface thickness, surface tension, average molecular free path and Knudsen number. Specifically, when the Knudsen number is greater than 0.1, the interface thickness increases, the surface tension decreases, and the average molecular free path shortens, but it does not reach the limit; when the Knudsen number is not greater than 0.1, the interface thickness is the thickest, the surface tension is the smallest, and the average molecular free path is the shortest. It is predicted that the mixed fluid in the gas-liquid interface changes from a discontinuous fluid to a continuous fluid, and a supercritical phase transition occurs. At this time, the gas-liquid interface disappears and turns into a supercritical fluid boundary mixing layer;

[0122] Step 6: When the result predicted in step 5 is that the droplets undergo a supercritical phase transition, the Reynolds number of the airflow in the cylinder is increased, and a subcritical evaporation mixing model of droplets in a high-density convection environment and a supercritical diffusion mixing model of droplets in a high-density convection environment are established to jointly optimize the oil-gas mixing in the cylinder. Among them, the subcritical evaporation mixing model of droplets in a high-density convection environment is established based on the VOF method, including the continuity equation, momentum equation, energy equation and component equation, as follows:

[0123] The VOF method is used to capture the interface between the gas and liquid phases, and the piecewise linear interface algorithm is used to reconstruct the high-resolution gas-liquid interface. In the VOF method, the sum of the volume fractions of the liquid and gas phases in any control volume is always 1. In other words, in any given control volume, the variables therein either represent one of the gas and liquid phases, or represent a two-phase mixture (i.e., the gas-liquid interface). The specific expression is as follows:

[0124]

[0125] In the formula, α l is the liquid phase volume fraction;

[0126] The continuity equation, for one phase q in the gas-liquid two-phase system, supports the high-resolution reconstruction of the gas-liquid interface as follows:

[0127]

[0128] Where ρ is the density, is the velocity, α is the volume fraction, subscript q is the phase q, S m,q represents the mass source term, which is used to describe the mass transfer process between gas and liquid phases. Specifically, the mass transfer rate at the gas-liquid interface is calculated by a mass transfer model with a physical basis. Based on this mass transfer model, the mass transfer rate It is calculated by the following equation:

[0129]

[0130] Where δ is the evaporation coefficient, R is the universal gas constant, and T ν represents the saturation temperature, P ν is the saturation pressure, P i is the vapor partial pressure at the gas-liquid interface. Finally, combined with the Clausius-Clapeyron relationship, the mass transfer rate in the above equation is Converted to the following form:

[0131]

[0132] Where ΔH represents the enthalpy difference, T i represents the temperature at the gas-liquid interface, ρ v Represents density. The above formula is the mass source term S used in this model. m,q final form;

[0133] Momentum equation. In this model, it is assumed that the momentum equations of the gas and liquid phases in the computational domain are the same, and the calculated velocity field is shared by the gas and liquid phases. In high velocity and turbulent environments, the simplified treatment method of gas and liquid phases sharing the same velocity field is inappropriate, but it is still applicable to the laminar flow environment studied in this paper, and the momentum equation can be obtained as follows:

[0134]

[0135] In the formula, P represents pressure, μ represents viscosity, represents the gradient, It represents the surface tension existing in the gas-liquid interface. The surface tension is calculated by the following formula:

[0136]

[0137] Where κ represents the curvature, ρ l represents the liquid side density, ρ g represents the gas phase density, σ is the surface tension coefficient, and the surface tension coefficient σ under subcritical conditions is calculated by the following relationship:

[0138]

[0139] Where P c represents the critical pressure, Tc represents the critical temperature, ω represents the eccentricity factor, and T represents the interface temperature;

[0140] Energy equation. In this model, the energy equation of the gas and liquid phases in the computational domain has the same form. The calculated velocity field is shared by the gas and liquid phases, and its expression is as follows:

[0141]

[0142] Where E represents the energy of the binary mixture, calculated using the mass average method, and λ represents the thermal conductivity. is the stress tensor, T is the temperature, h i,q is the enthalpy of component i in phase q, is the diffusion flux, S h represents the energy source term, and the calculation expression is as follows:

[0143]

[0144] The calculation expression of the component equation is as follows:

[0145]

[0146] Where Y i.q is the mass fraction of component i in phase q, S s,q represents the component source term, α q represents the volume fraction, ρ q represents density, represents the diffusion flux of component i in phase q. In all the above equations, the density ρ, thermal conductivity λ and viscosity μ of the binary mixture are calculated by the volume fraction averaging method, and the constant pressure specific heat cp of the binary mixture is calculated by the mass averaging method.

[0147] The above four equations are solved by the commercial software ANSYS Fluent 2021R1, and the simulation is carried out using the Pressure-based transient solver based on the SIMPLEPressure-velocity coupling method. The spatial discretization of the momentum equation, energy equation and component equation uses the second-order upwind format, while the spatial discretization of the pressure equation uses the PRESTO format. The spatial discretization of the volume fraction equation is achieved through the Geo-Reconstruct scheme, and the time discretization method is a first-order implicit format.

[0148] The established supercritical diffusion mixing model of droplets in a high-density convection environment includes four control equations, namely, continuity control equation, momentum control equation, energy control equation and component control equation. Different from the phase change mixing of fuel droplets in a subcritical convection environment, in a supercritical convection environment, when the initial temperature of the introduced fuel droplets is close to the critical mixing temperature of the mixture, the rapid heat transfer between the droplets and the environment causes the gas-liquid interface of the droplets to reach the critical mixing state instantly. It can be assumed that the effect of the supercritical phase change on the behavior of the droplets is negligible. At this time, there is no longer a gas-liquid interface with significant surface tension between the gas and liquid phases, and the latent heat of evaporation is reduced to zero, but the temperature inside the droplets is still lower than the critical mixing temperature, which indicates that the fluid inside the droplets still maintains a liquid phase thermodynamic state. Then, in a supercritical convection environment, it can be assumed that the fuel droplets are dense fluids enclosed by the critical mixing state isosurface, and the fluid in the entire flow field can be regarded as a single-phase continuous medium, and its phase state is distinguished by the thermodynamic state of the fluid. Based on this, the supercritical diffusion mixing model is used to describe the droplet dynamics behavior and oil-gas mixing process of the fuel droplets in the convective environment after the supercritical transition occurs; the calculation expression of each control equation is as follows:

[0149] Continuity governing equation:

[0150]

[0151] Momentum governing equation:

[0152]

[0153] Where, I represents impulse;

[0154] Energy governing equation:

[0155]

[0156] In the formula, h j represents the enthalpy of component j; the second term on the right side of the above formula represents the temperature gradient due to component diffusion, i.e., the Dufour effect;

[0157] Component governing equation:

[0158]

[0159] In the formula, is the diffusion flux of component i, and the calculation expression is as follows:

[0160]

[0161] Where D i,m represents the mass diffusion coefficient of component i, D T,i represents the thermal diffusion coefficient of component i, represents the mass fraction gradient of component i, the second term on the right side of the above formula It represents the component transport caused by the additional concentration gradient caused by the temperature gradient, namely the Soret effect.

[0162] Based on the finite volume method, the above basic control equations are solved by the commercial software ANSYS FLUENT 2021R1. The simulation is carried out using the Pressure-based transient solver based on the SIMPLE Pressure-velocity coupling method. The spatial discretization of the gradient and pressure equations adopts the second-order upwind scheme. The spatial discretization method of the momentum control equation, component control equation and energy control equation also adopts the second-order upwind scheme. The time discretization method is a first-order implicit format.

[0163] Under high-density environmental conditions, the droplets first undergo a subcritical evaporation phase transition. As the temperature of the gas-liquid interface continues to increase, the droplets will enter a supercritical phase transition mode. When the droplets undergo a supercritical phase transition, the gas-liquid interface between the droplets and the gas disappears and transforms into a supercritical fluid boundary mixing layer. Figure 5 As shown in , the thickness of the gas-liquid interface increases exponentially with increasing temperature. Figure 6 As shown in Figure 2, the surface tension of the gas-liquid interface decreases exponentially with increasing temperature. Figure 3 As shown in Figure 1, the average molecular free path shortens with the increase of interface temperature. Based on the increase of gas-liquid interface thickness, the decrease of surface tension and the shortening of average molecular free path, it is predicted that the droplet has a supercritical phase transition trend. Figure 4 As shown in , the Knudsen number of the gas-liquid interface decreases with the increase of the interface temperature. When it is less than 0.1, the mixture in the gas-liquid interface changes from a discontinuous fluid to a continuous fluid, that is, a supercritical transition occurs. At this time, the gas-liquid interface disappears and is transformed into a supercritical fluid boundary mixing layer. Figure 7 As shown in Figure 2, increasing the air flow rate can accelerate the phase transition of droplets under subcritical and supercritical conditions, but when the droplets are in the supercritical state, increasing the air flow rate has a more significant effect on the phase transition of the droplets. Figure 8 As shown in the figure, under all air flow rate conditions, the movement distance of droplets in the supercritical diffusion mixing mode is always greater than that in the subcritical evaporation mixing mode at the same time, and the greater the air flow rate, the more obvious the advantage of the supercritical diffusion mixing mode. When the droplets are in the supercritical state: Fig. 9 As shown in the figure, when the droplet Reynolds number is Red = 1271, due to the increase in air velocity, a larger area of ​​vorticity distribution is formed on both sides of the droplet, and the vorticity at this time is significantly greater than that when Red = 85, which ultimately causes the vortex on the weak side of the droplet to curl and expand continuously and cause the droplet to stretch and deform. Fig.10As shown in (a), at all Reynolds numbers, the stratification coefficient of the fuel droplets decreases with time, which is determined by the supercritical diffusion mixing mode, and the stratification coefficient of the fuel droplets decreases with the increase of Reynolds number. The reason is that the vortex structure on the weak side of the droplet expands with the increase of Reynolds number, and the enhanced component diffusion leads to the generation of more uniform oil-gas mixtures, which indicates that the oil-gas mixing uniformity is higher at higher Reynolds numbers. Fig.10 As shown in (b), the droplet phase change rate increases with the increase of Reynolds number. The reasons are: on the one hand, the high Reynolds number leads to more significant tensile deformation of the droplet, thereby strengthening the heat and mass transfer process between the fuel droplet and the ambient gas; on the other hand, increasing the gas flow rate is conducive to "blowing away" the n-heptane vapor generated near the droplet surface, increasing the n-heptane concentration gradient on the droplet surface, thereby accelerating the droplet phase change process dominated by diffusion. Fig.11 As shown, at high Reynolds numbers, the thermodynamic state of the binary mixture in the gas phase region is more widely distributed, resulting in faster and more uniform mixing with air.

[0164] Therefore, the present invention adopts the above-mentioned in-cylinder oil-gas mixing optimization method based on the phase change state of droplets under high-density environment. By establishing a gas-liquid interface model, it can quickly and accurately determine whether the droplets enter the supercritical state, and by establishing a subcritical evaporation mixing model and a supercritical diffusion mixing model under a high-density convection environment, it is obtained that when the droplets enter the supercritical state, the Reynolds number of the airflow in the cylinder is increased, thereby promoting oil-gas mixing.

[0165] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. An optimization method for in-cylinder oil-gas mixing based on droplet phase change state under high-density environment, characterized in that: The following steps are involved: Step 1, selecting an alkane component whose density changes monotonically at the gas-liquid interface in the binary mixture as a reference component, wherein the gas-liquid interface is the region between the alkane / nitrogen binary mixture in a gas-liquid phase equilibrium state; Step 2, calculating the density distribution and influencing parameters of the reference component in the normal direction of the gas-liquid interface; Step 3, according to the density distribution of the reference component in the normal direction of the gas-liquid interface, the characteristic interface thickness and surface tension of the gas-liquid interface are calculated; Step 4, calculating the average molecular free path and Knudsen number according to the interface temperature, equilibrium pressure and average molecular hard sphere diameter; Step 5, predicting the evolution of the spatial structure of the gas-liquid interface by using the interface thickness, surface tension, average molecular free path and Knudsen number. Specifically, when the Knudsen number is greater than 0.1, the interface thickness increases, the surface tension decreases, and the average molecular free path shortens, but it does not reach the limit; when the Knudsen number is not greater than 0.1, the interface thickness is the thickest, the surface tension is the smallest, and the average molecular free path is the shortest. It is predicted that the mixed fluid in the gas-liquid interface changes from a discontinuous fluid to a continuous fluid, and a supercritical phase transition occurs. At this time, the gas-liquid interface disappears and turns into a supercritical fluid boundary mixing layer; Step 6: When the result predicted in step 5 is that the droplets undergo a supercritical phase transition, increase the Reynolds number of the airflow in the cylinder, establish a subcritical evaporation mixing model of droplets in a high-density convective environment and a supercritical diffusion mixing model of droplets in a high-density convective environment to jointly optimize the oil-gas mixing in the cylinder.

2. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 1 is characterized in that: The calculation expression for the density distribution of the reference component in the normal direction of the gas-liquid interface in step 2 is as follows: In the formula, ρ I , L is the liquid density, ρ I , V is the gas phase density, Δ PI is the density increment, N is the number of mesh nodes for the gas-liquid interface discretization, ρ i Represents the density of the liquid phase.

3. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 2 is characterized in that: In step 2, the influencing parameter κ i，j The calculation expression is as follows: c 0，i =-2.985+4.332Z c，i +10.859Z c，i 2 -1,990h i +1.798h i 2 -5.436×10 -6 (i r，i ) 2 c 1，i =-0.965+1.405Z c，i +2.746Z c，i 2 -0.963h i +1.346h i 2 -1.110×10 -6 (i r，i ) 2 c 2，i =-0.121+0.156Z c，i +0.540Z c，i 2 -0.123h i +0.090h i 2 -0.219×10 -6 (i r，i ) 2 In the formula, β i，j represents the binary interaction parameter, κ i represents the influence parameter of pure component i, κ j represents the influence parameter of pure component j, a i and b i are constants, N A represents Avogadro's constant, c 0,i 、c 1，i and c 2，i are the correlation coefficients of pure substances, T′ r represents the characteristic temperature, Z c，i represents the critical compression factor, ω i represents the eccentricity factor, θ ri Represents the contrast dipole moment.

4. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 3 is characterized in that: The specific calculation process of the surface tension of the gas-liquid interface in step 3 is as follows: S31. The expression of surface tension σ1 in spatial coordinate form in the normal direction of the gas-liquid interface is as follows: S32. The spatial coordinate form in the normal direction of the gas-liquid interface is converted into the density distribution form in the normal direction of the gas-liquid interface by using the coordinate conversion rule. The specific calculation expression is as follows: In the formula, ρ M,i and ρ M，j are the densities of the liquid and gas components in the mixture, respectively. Subscript I represents the reference component, subscripts V and L represent the gas and liquid phases in phase equilibrium, respectively. i and ρ j are the densities of the liquid and gas phases, respectively, and σ represents the surface tension in the form of density distribution in the normal direction of the gas-liquid interface.

5. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 4 is characterized in that: The characteristic interface thickness l of the gas-liquid interface in step 3 VLE The calculation expression is as follows: In the formula, ρ I，0 is the gas phase density of the reference component I at the initial integration point, z0 represents ρ I,0 The position where z represents ρ I Location, represents the giant thermodynamic potential energy density of the mixture, Indicates a negative value of the equilibrium pressure, is the huge thermodynamic potential energy density difference, the huge thermodynamic potential energy density difference The calculation expression is as follows: Where ρM,i represents the density of the liquid phase in the mixture, and PM,j represents the density of the gas phase in the mixture.

6. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 5 is characterized in that: In step 4, the calculation expression for the average molecular free path is calculated based on the interface temperature, equilibrium pressure and average molecular hard sphere diameter as follows: Where, d i is the diameter of the chain hard sphere, m i is the hard sphere number, is the hard sphere diameter, d is the average molecular hard sphere diameter, x i is, Λ is the average molecular free path, k B is the Boltzmann constant, T is the interface temperature, and P is the equilibrium pressure; The ratio of the average molecular free path to the characteristic interface thickness is the Knudsen number, which is calculated as follows: Where Kn is the Knudsen number.

7. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 6 is characterized by: In step 6, a subcritical evaporation mixing model of droplets in a high-density convection environment is established based on the VOF method, including the continuity equation, momentum equation, energy equation, and component equation, as follows: The VOF method is used to capture the interface between the gas and liquid phases, and the piecewise linear interface algorithm is used to reconstruct the high-resolution gas-liquid interface. In the VOF method, the sum of the volume fractions of the liquid and gas phases in any control volume is always 1. The specific expression is as follows: In the formula, α l is the liquid volume fraction; The calculation expression of the continuity equation is as follows: Where ρ is the density, is the velocity, α is the volume fraction, subscript q is the phase q, S m,q represents the mass source term, which is used to describe the mass transfer process between gas and liquid phases. Specifically, the mass transfer rate at the gas-liquid interface is calculated by a mass transfer model with a physical basis. Based on this mass transfer model, the mass transfer rate It is calculated by the following equation: Where δ is the evaporation coefficient, R is the universal gas constant, Tν is the saturation temperature, Pν is the saturation pressure, and P i is the vapor partial pressure at the gas-liquid interface. Finally, combined with the Clausius-Clapeyron relationship, the mass transfer rate in the above equation is Converted to the following form: Where ΔH represents the enthalpy difference, T i represents the temperature at the gas-liquid interface, ρ ν Indicates density; The calculation expression of the momentum equation is as follows: In the formula, P represents pressure, μ represents viscosity, represents the gradient, It represents the surface tension existing in the gas-liquid interface. The surface tension is calculated by the following formula: Where K represents the curvature, ρ l represents the liquid side density, ρ g represents the gas phase density, σ is the surface tension coefficient, and the surface tension coefficient σ under subcritical conditions is calculated by the following relationship: Where P c represents the critical pressure, T c represents the critical temperature, ω represents the eccentricity factor, and T represents the interface temperature; The calculation expression of the energy equation is as follows: Where E represents the energy of the binary mixture, calculated using the mass average method, and λ represents the thermal conductivity. is the stress tensor, T is the temperature, h i，q is the enthalpy of component i in phase q, is the diffusion flux, S h represents the energy source term, and the calculation expression is as follows: The calculation expression of the component equation is as follows: Where Y i.q is the mass fraction of component i in phase q, S s，q represents the component source term, α q represents the volume fraction, ρ q represents density, represents the diffusion flux of component i in phase q.

8. The in-cylinder oil-gas mixing optimization method based on droplet phase change state under high-density environment according to claim 7 is characterized in that: The supercritical diffusion mixing model of droplets in a high-density convective environment established in step 6 includes four control equations, namely, the continuity control equation, the momentum control equation, the energy control equation, and the component control equation. The calculation expression of each control equation is as follows: Continuity equation: Momentum equation: Where, I represents impulse; Energy equation: In the formula, h j represents the enthalpy of component j; Component equation: In the formula, is the diffusion flux of component i, and the calculation expression is as follows: Where D i，m represents the mass diffusion coefficient of component i, D T，i represents the thermal diffusion coefficient of component i, represents the mass fraction gradient of component i.

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