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CN-120877985-B - Numerical simulation method for microstructure of laser surface remelting particle reinforced magnesium-based composite material

CN120877985BCN 120877985 BCN120877985 BCN 120877985BCN-120877985-B

Abstract

A numerical simulation method for microstructure of laser surface remelting particle reinforced magnesium-based composite material belongs to the technical field of numerical simulation of microstructure of composite material. The invention solves the problem that the existing numerical simulation method does not fully consider the interaction between dendrite growth and particle movement. According to the invention, based on an electron probe experimental characterization result, an as-cast real solid phase component field is used as an initial condition of calculation, an actual solidification process is more truly reproduced, and simultaneously microstructure evolution and particle movement are coupled and calculated, a cellular automaton technology is adopted to simulate magnesium alloy with reinforced particles, the influence of dendrite growth on particle movement is considered, the numerical prediction of microstructure of a laser surface remelting particle reinforced magnesium-based composite material can be realized, and microstructure formation and particle movement in a molten pool in a laser metal melting process can be more accurately predicted. The method can be applied to numerical simulation of the microstructure of the particle reinforced magnesium-based composite material.

Inventors

  • LIU DONGRONG
  • XIE HUAZHEN
  • ZHAO SICONG
  • FENG YICHENG
  • GUO ERJUN

Assignees

  • 哈尔滨理工大学

Dates

Publication Date
20260508
Application Date
20250715

Claims (10)

  1. 1. The numerical simulation method for the microstructure of the laser surface remelting particle reinforced magnesium-based composite material is characterized by specifically comprising the following steps of: Step one, taking the prepared as-cast sample as a substrate, carrying out sand blasting treatment on the surface of the substrate, carrying out laser surface remelting on the treated substrate, and measuring the depth L molten-pool of a molten pool and the primary dendrite spacing lambda PDAS ; Calculating liquidus temperature T ' l in the unbalanced solidification process, and then calculating eutectic reaction temperature T ' e in the unbalanced solidification process according to T ' l , molten pool depth L molten-pool and primary dendrite spacing lambda PDAS ; step two, determining the corresponding relation between the melt viscosity and the temperature of the particle reinforced magnesium-based composite material; Dividing cube grids of the molten pool area and the air layer, wherein the size of each cube grid obtained by division is delta x; Square grid division is carried out on the substrate layer, and the size of each square grid obtained through division is Deltax o ×Δx o ×Δx o ,Δx＜Δx o ; heat and momentum transfer in the molten pool in the LSR process can be calculated through grid division, so that temperature field and flow field change in the molten pool forming process are described; Step four, calculating flow fields of an air layer and a molten pool area according to the corresponding relation between liquidus temperature T ' l , eutectic reaction temperature T' e and melt viscosity and temperature in the unbalanced solidification process, and solving the average density and the flowing speed of molten metal; step five, calculating a temperature field for the air layer, the molten pool area and the substrate area according to the average density and the metal liquid flowing speed obtained in the step four; Step six, for a molten pool area, calculating the resultant force born by the particles according to the molten metal flow speed solved in the step four, and solving the motion equation of the particles according to the resultant force born by the particles and the molten metal flow speed solved in the step four to obtain a particle motion speed field; step seven, judging whether the laser scanning process is finished; If the laser scanning process is finished, stopping calculation, outputting a temperature field, a liquid flow speed field and a particle movement speed field of a local area of the lower molten pool at different moments, and continuing to execute the step eight; If the laser scanning process is not finished, adding 1 to the time step, and returning to execute the fourth step by utilizing the resultant force of the particles calculated in the sixth step; Step eight, selecting a sub-area from the molten pool area as a calculation area of the organization simulation, and carrying out grid division on the selected calculation area, wherein the size of each grid obtained by division is delta x sub-cell ·Δx sub-cell , delta x > delta x sub-cell , the number of grid lines obtained by division is N X-cell , and the number of grid columns is N Y-cell ; Obtaining a cooling curve of a tissue simulation calculation domain according to the temperature field of the local area of the molten pool output in the step seven, and marking the maximum value of the temperature on the cooling curve as T max-cell ; step nine, forming a microstructure according to T max-cell , wherein the specific process is as follows: Step nine, reading an experimental result data file obtained by electronic probe characterization, wherein the experimental result data file is a matrix of N X-cell rows and N Y-cell columns; step nine, endowing the grid of the ith row and the jth column in the calculation domain with temperatures T cell,k (i, j) at different moments according to a cooling curve, wherein the number of Time points included in the cooling curve is NK, and the Time step is Deltat cell ＝Time cell,2 -Time cell,1 ＝Time cell,3 -Time cell,2 ＝…＝Time cell,NK -Time cell,NK-1 , and Time cell,1 is the Time corresponding to the 1 st moment; and at the same time, the temperature of each grid in the calculation domain is the same; according to the experimental result data file obtained by the electronic probe characterization, imparting a solid phase component Cs cell,1 (i, j) at the initial moment to each grid in the calculation domain, wherein the value of i is [1, N X-cell ], and the value of j is [1, N Y-cell ]; step nine three, at the initial time, initializing a liquid phase component initial value of the grid (i, j) to be C l,1 (i,j)＝Cs cell,1 (i,j)/k v ,k v to represent a non-equilibrium solute distribution coefficient, wherein a solid phase fraction initial value of the grid (i, j) is f s-r,1 (i, j) =1, and an initial value of a component at a solid-liquid interface is The initial value of the solid phase fraction in the resolidification stage is f s-s,k (i, j) =0; Initializing time k=1; Step nine four, calculating the melting factor q m of the grid (i, j) according to f s-r,k (i, j): Wherein q m is the melting factor of grid (i, j), m is the first neighbor grid of grid (i, j), m' is the second neighbor grid of grid (i, j), d 2 is a constant, if at time k, the solid phase fraction f s-r,k (m) >0 of the m-th grid in the first neighbor of grid (i, j) Otherwise the first set of parameters is selected, If at time k, the solid phase fraction f s-r,k (m ') >0 of the m' th grid in the second neighbor of grid (i, j) then Otherwise the first set of parameters is selected, The composition at the solid-liquid interface The solid fraction change amount Δf s-r and the remelting stage solid fraction f s-r are: Wherein T m is the melting point, Δf s-r,k (i, j) represents the solid phase fraction change amount at time k, f s-r,k+1 (i, j) represents the solid phase fraction of the grid (i, j) at time k+1, Representing the composition at the solid-liquid interface of grid (i, j) at time k+1; solving a partial differential equation by adopting a display differential algorithm, wherein the solute diffusion partial differential equation in the remelting process is as follows: Wherein C l,k+1 (i, j) represents the liquid phase component of the grid (i, j) at time k+1; Step nine five, let k=k+1, judge whether all grids meet f s-r,k (i, j) =0; If all grids meet f s-r,k (i, j) =0, then the complete melting is indicated, cs cell,k (i, j) =0 is detected, and the step nine six is continuously executed; If not all grids meet f s-r,k (i, j) =0, returning to the step nine four; step nine, six, calculating the solidification factor q s of the grid (i, j) according to f s-s,k (i, j): the composition at the solid-liquid interface The solid phase fraction change amount Δf s-s and the solid phase fraction f s-s in the resolidification stage are: Wherein Γ is a Gibbs coefficient, wmc is a solid-liquid interface curvature, Δf s-s,k (i, j) represents a solid phase fraction change amount at time k, and f s-s,k+1 represents a solid phase fraction at the resolidification stage at time k+1; the calculation formula of the curvature of the solid-liquid interface is as follows: Wherein, the As a function of the anisotropy of the material, Representing the divergence of the vector; Where n z = 0 is a two-dimensional tissue simulation, epsilon 1 、ε 2 and epsilon 3 are coefficients; solving a partial differential equation by adopting a display differential algorithm, wherein a solute diffusion equation in the resolidification process is as follows: Wherein, the Seventhly, let k=k+1, judge whether all grids in the calculation domain meet f s-s,k (i, j) =1; if all grids meet f s-s,k (i, j) =1, then complete coagulation is indicated, C l,k (i, j) =0; if not all grids meet f s-s,k (i, j) =1, returning to the step nine to six; and simulating the processes represented by the calculation results of the step nine four and the step nine six by adopting a cellular automaton technology, namely realizing the remelting of a solid phase and the simulation of the formation of dendrite structures in a liquid phase, and outputting microstructures at different moments.
  2. 2. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium matrix composite material according to claim 1, wherein the calculating liquidus temperature T ' l in the unbalanced solidification process, and calculating eutectic reaction temperature T ' e in the unbalanced solidification process according to T ' l , molten pool depth L molten-pool and primary dendrite spacing λ PDAS comprises: T′ l ＝(T l -ΔT R ) (6) ΔT ls ＝(T l -ΔT R )-T′ e (7) Wherein R tip is dendrite tip radius, V scan is laser scanning speed, D L is diffusion coefficient of solute in liquid phase, m lv is liquidus slope in unbalanced solidification process, k v is liquid solute distribution coefficient in unbalanced solidification process, C o is alloy initial component, Γ is gibbs coefficient, m le is liquidus slope in balanced solidification process, k e is solute distribution coefficient in balanced solidification process, Δt R is curvature supercooling, Δt ls is crystallization temperature range in unbalanced solidification process, G T is temperature gradient between bath surface and substrate, T l is liquidus temperature corresponding to equilibrium phase diagram, T ' e is eutectic reaction temperature in unbalanced solidification process, T' l is liquidus temperature in unbalanced solidification process, l is atomic spacing at solid-liquid interface.
  3. 3. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium matrix composite according to claim 2, wherein the temperature gradient G T between the molten pool surface and the substrate is: G T ＝(T surface -T substrate )/(0.827·L molten-pool ) (8) Where T substrate represents the initial temperature of the substrate (taken to room temperature), T surface represents the maximum bath surface temperature, and L molten-pool represents the bath depth.
  4. 4. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium-based composite material according to claim 3, wherein the specific process of the second step is as follows: Step two, under the condition of known particle content, carrying out a mold filling experiment of a composite material melt thin-wall part by adopting a sand mold gravity casting process, obtaining a stepped thin-wall casting after the casting is completely solidified, and measuring the mold filling length of the melt; Step two, under the experimental parameters of the sand mould gravity casting process of step two, based on the change curve of the viscosity of the magnesium alloy melt along with the temperature Performing ProCAST numerical simulation calculation to obtain the melt filling length obtained through simulation; Wherein μ represents the melt viscosity of the magnesium alloy, T represents the temperature, and a o and b o are coefficients of the curve; step two, the melt filling length measured in the step two is subjected to difference with the melt filling length obtained through simulation, and a difference result is obtained; If the absolute value of the difference result is not more than 1mm, obtaining a curve of the viscosity changing along with the temperature, and marking the obtained curve of the viscosity changing along with the temperature as mu=aT -b , wherein a and b are coefficients of the curve; If the absolute value of the difference result exceeds 1mm, the melt viscosity value is adjusted up by 0.1 Pa.s, and then the second step is continuously executed; Step two, performing ProCAST numerical simulation calculation by using the adjusted melt viscosity value to obtain a melt filling length obtained through simulation; and returning to the second step and executing the third step.
  5. 5. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium matrix composite material of claim 4, wherein the specific process of the fourth step is as follows: for grids with temperature T less than T ' e in the air layer and molten pool area, i.e. for grids with T ' e > T, no flow field calculation is required; For grids with temperature T greater than or equal to T ' e in the air layer and molten pool area, namely for grids with T ' e less than or equal to T, the flow field needs to be calculated, and the calculation equation is as follows: Wherein, the In order to achieve an average density of the particles, Is the flowing speed of the molten metal, t is the time, The gradient is calculated, p is the pressure, eta is the dynamic viscosity calculated according to the corresponding relation between the viscosity and the temperature, The acceleration of the gravity is that, Is the volumetric force caused by the solid phase particles, For the buoyancy force, the water is pumped, In order to provide a recoil pressure, In the form of a surface tension force, For Ma Rige Ni shear force, alpha 1 is the volume fraction of metal phase, 1-alpha 1 is the volume fraction of gas, ρ Mg-9Al is metal density, ρ gas is gas density, β T is thermal expansion coefficient, P 0 is standard atmospheric pressure, L v is metal latent heat of evaporation, M is molar mass, T v is metal evaporation temperature, R is gas constant, T is molten bath metal temperature, The gradient of alpha 1 is that of alpha 1 , Equal to K 1 is the surface curvature of the molten pool, sigma 0 is the surface tension coefficient corresponding to liquidus temperature T' l , dsigma/dT is the slope of the curve of the surface tension coefficient with temperature T, V c is the volume of the split grid, and I represent absolute values and temperature gradients for the resultant force of particle motion Gradient of normal vector of bath surface
  6. 6. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium matrix composite material of claim 5, wherein the specific process of the fifth step is as follows: H=c pMg-9Al T+(1-f s-mico )L latent (20) Wherein H is enthalpy change, lambda is the heat conductivity coefficient of the magnesium-based composite material, Q laser is heat input from laser, Q v is heat loss caused by evaporation, Q rad is heat loss caused by radiation, c pMg-9Al is specific heat of magnesium alloy, f s-mico is solid phase fraction, L latent is latent heat of magnesium alloy, Q 0 is coefficient required for calculation of laser heat input, x is energy density ratio, Z e is the position of the upper surface of the conical laser heat source along the Z axis, Z i is the position of the lower surface of the conical laser heat source along the Z axis, r 0 (Z) is the radius of the conical laser heat source at the Z axis of the device, c pgas is specific heat of gas, eta l is laser absorptivity, Q l is laser power, r is the radius of the upper surface of the conical laser heat source, r i is the radius of the lower surface of the conical laser heat source, gamma is Stefan-Boltzmann constant, tau is radiation heat dissipation, T 0 is room temperature, (x, y, Z) is coordinate value of the center in three-dimensional space, E is the base of natural logarithm, which is the mixed specific heat of magnesium alloy and gas.
  7. 7. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium matrix composite material of claim 6, wherein the specific process of the step six is as follows: Step six, for the grids with T' e being more than or equal to T in the molten pool area, the particle stress does not need to be calculated; For a grid of T' e < T in the region of the bath, the forces to which the particles are subjected include gravity, buoyancy, pressure, drag and mass forces, then classical discrete particle models are used to calculate the resultant forces to which the particles are subjected The method comprises the following steps: Wherein, the For the buoyancy force, the water is pumped, In the case of a pressure force, the pressure, In order for the drag force to be a drag force, For mass force, d is particle diameter, ρ SiC is particle density, R e is Reynolds number, The movement speed of the particles in the molten metal is represented by m add , and the mass coefficient is represented by m add ; And step six, predicting particle movement based on the resultant force of the particles and the instantaneous flow field of the particles obtained in the step four, and if at least A particles move to the same position in the current time step, forming agglomerates by the particles moving to the same position.
  8. 8. The numerical simulation method of microstructure of laser surface remelting particle-reinforced magnesium-based composite material according to claim 7, wherein the method is characterized in that the particle motion is predicted based on resultant force of particles and the instantaneous flow field of the particles obtained in the step four, and a lagrangian method is adopted.
  9. 9. The numerical simulation method of microstructure of laser surface remelting grain reinforced magnesium matrix composite of claim 8 wherein the value of a is 5.
  10. 10. The numerical simulation method of microstructure of laser surface remelting grain-reinforced magnesium-based composite material according to claim 1, further comprising grain movement coupling simulation, wherein grain brownian motion calculation is performed at each moment, N par grains are randomly distributed into grids in a calculation domain at an initial moment, each grid can be distributed to one grain at most, if grids in an ith row and a jth column in the calculation domain are distributed to the grains, pii cell,1 (i, j) is 1, otherwise Pii cell,1 (i, j) is 0; Taking any grid with particles at the moment Time cell,k as a research object, if a grid (i, j) with 0<f s-s,k (i, j) less than or equal to 1 exists in the first neighbor grid and the second neighbor grid of the grid, the pushing or capturing effect of a solid-liquid interface on the particles is required to be considered, namely, the step 1 is executed, otherwise, the step 2 is directly executed; step 1, calculating a critical speed V pcr of solid-liquid interface to particle capture: wherein A is Hamaker constant, h cr is critical distance between particles and solid-liquid interface, eta is viscosity of melt, d is diameter of particles, and a 0 is atomic distance of magnesium; Calculating the moving speed V sl of the solid-liquid interface in the solidification process: V sl ＝(Δf s-s,k (i,j)·Δx sub-cell )/(6·Δt cell ) Wherein, deltaf s-s,k (i, j) is the solid phase fraction variation corresponding to the remelting and resolidification stage; If V sl >V pcr shows that the growth speed of the solid-liquid interface is greater than the critical speed of capturing, the particles are captured by the solid-liquid interface, and the movement calculation of the particles in the grid is not needed; If V sl ≤V pcr shows that the growth speed of the solid-liquid interface does not exceed the critical speed of capturing, at Time Time cell,k , particles are not captured by the solid-liquid interface, and then the step 2 is continuously executed; step 2, judging whether grids (i, j) meeting the condition (1) or (2) exist in all the first neighbor grids and the second neighbor grids of the grid; T' l <T cell,k (i, j); Condition (2) T' e <T cell,k (i,j)<T' l and T cell,k (i, j) have reached T max-cell ; If there is a grid (i, j) satisfying the condition (1) or (2), the particles in the grid of the subject move to any one of the grids satisfying the condition (1) or (2); The movement velocity v pr of the particles and the migration distance l pr in a time step are respectively: l pr ＝v pr ·β·Δt cell Wherein T cell,k is the time corresponding to the kth moment, gamma is Stefan-Boltzmann constant, m pr is the mass of the particles, and beta is the calculated times; If it is The particle moves from the current grid to the first neighbor grid if And after the particles in the current grid are transferred, the value Pii cell,k+1 of the current grid at the moment k+1 is 0, and the value Pii cell,k+1 of the grid with the particles transferred to at the moment k+1 is recorded as 1.

Description

Numerical simulation method for microstructure of laser surface remelting particle reinforced magnesium-based composite material Technical Field The invention belongs to the technical field of numerical simulation of composite microstructure, and particularly relates to a numerical simulation method for particle dispersion in a molten pool of a laser surface remelting particle reinforced magnesium-based composite material. Background The magnesium alloy has the advantages of low density, high specific strength, high specific stiffness, good electromagnetic shielding property, good machining property and the like, and is the lightest weight engineering material applicable at present. However, the magnesium alloy has lower strength and hardness, and poorer wear resistance and corrosion resistance, and limits the development of the magnesium alloy to a certain extent. The ceramic particles are introduced into the magnesium alloy to obtain extraordinary physical, chemical and mechanical properties. The particle reinforced magnesium-based composite material not only inherits the advantages of magnesium alloy, but also obviously enhances the absolute strength, high-temperature mechanical property and friction property, and is one of the most advantageous ways for improving the mechanical property of magnesium alloy and realizing industrial application at present. However, an important factor limiting the rapid development of as-cast grain-reinforced magnesium-based composites is that the resulting grain size is relatively coarse due to the low cooling rate during casting. Coarse grains form triangular grain boundaries, reducing the continuity of eutectic phase distribution at the grain boundaries. When exposed to corrosive media, the eutectic phase may protect the magnesium matrix as a passivating phase if it is continuously distributed at the grain boundaries, thereby slowing the corrosion rate, and may not protect the magnesium matrix as a passivating phase if it is discontinuously distributed at the grain boundaries. Since the corrosion behavior begins at the surface of the component, surface modification studies of particle-reinforced magnesium-based composites are particularly important. Laser Surface Remelting (LSR) irradiates a metal surface with a laser beam having a relatively high energy density to cause instantaneous melting of a surface layer of a certain thickness, and then rapidly solidifies a molten pool by means of heat transfer and cooling of the base member itself, thereby improving the surface texture of the material, and improving the toughness and corrosion resistance of the material surface. However, the different LSR processes have different effects on the surface structure of the component, so that the effects on the mechanical properties are different, and finally the use of the product is affected. The quantitative relation between the LSR technology and the microstructure is blindly discovered by experimental means, and a large number of experiments mean a large number of trial and error, which consumes a large amount of manpower, material resources and financial resources. With the development of computer technology, numerical simulation is becoming important as an effective means for researching the solidification process of metals. Through numerical simulation, a series of physical phenomena such as heat/mass/momentum transmission, particle transmission, grain nucleation and growth and the like in the nonlinear unsteady state solidification process can be quantitatively or qualitatively analyzed, and the obtained simulation result has a key guiding effect on process development and optimization. The quantitative relation between the technological parameters and the microstructure can be established in a short time through numerical simulation, so that the research and development period is shortened. However, a great deal of numerical simulation research is focused on the evolution process of a molten pool in the LSR process, and the numerical simulation research on the microstructure evolution of the solidification process has less work. The main reason is that the first is that the LSR process involves melting and the composition of the object being melted is not uniform, which means that the assumption of uniform composition in the initial state in the previous calculations is no longer applicable. The second is that the system contains two substances, namely magnesium dendrites and ceramic particles, wherein during the solidification process of LSR, the magnesium dendrites grow and the ceramic particles move, so that the collision between the dendrites and the particles can induce the movement of the particles, and the particles can do Brownian movement under the high-temperature condition, but the interaction between the growth of the dendrites and the movement of the particles is not fully considered at present. Therefore, the numerical simulation method of the microstructure o