CN114611298A

CN114611298A - Method and equipment for optimizing technological parameters through modeling and simulation in sand laying process of ink-jet 3D printing sand mould

Info

Publication number: CN114611298A
Application number: CN202210247337.7A
Authority: CN
Inventors: 石德全; 史栋良; 高桂丽; 姜爱龙; 孙明; 陈泽中; 江鸿; 康凯娇
Original assignee: Harbin University of Science and Technology; University of Shanghai for Science and Technology
Current assignee: Harbin University of Science and Technology; University of Shanghai for Science and Technology
Priority date: 2022-03-14
Filing date: 2022-03-14
Publication date: 2022-06-10

Abstract

The invention provides a method and equipment for modeling and simulating optimization of process parameters in a sand-paving process of a sand mold through ink-jet 3D printing. The method accelerates the process of optimizing the technological parameters of the sand mold, feeds back the sanding effect and the sanding performance of the ink-jet 3D printing sand mold under different technological parameters more quickly and intuitively, and provides a basis for optimizing the technological parameters and measuring the performance of the sand mold.

Description

Method and equipment for optimizing technological parameters through modeling and simulation in sand laying process of ink-jet 3D printing sand mould

Technical Field

The invention belongs to the technical field of simulation, and particularly relates to a method and equipment for modeling and simulating optimization of process parameters in a sand laying process of a sand mold through ink-jet 3D printing.

Background

The 3DP printing is a rapid molding technology which selectively sprays a binder onto a sand bed through a spray head, reacts with a curing agent which is mixed into sand in advance, cures and molds a set area, prints layer by layer and piles up layer by layer to finally obtain a casting mold. The method has the advantages of high forming speed, editable printing model, no need of a mold, capability of realizing color three-dimensional printing and the like, and has extremely wide application in the field of sand mold manufacturing. Different printing technological parameters of the sand mold can affect the sand laying performance and the sand laying effect, and further affect the performance of the sand mold in the casting process. Therefore, it is very necessary to select the optimal process parameters for inkjet 3D printing.

Under the common conditions, the sand mold printing process parameters need to be tested by adopting a very professional instrument, the operation method is complex, the cost is high, and in order to meet and match the characteristics of high efficiency and high speed of ink-jet 3D printing, the method for selecting the optimal process parameters of the 3D printing sand mold through the simulation method is very important. Therefore, it is necessary to provide a simulation method for optimizing the optimal process parameters of the inkjet 3D printing sand mold.

Disclosure of Invention

The invention provides a method and equipment for optimizing process parameters through modeling and simulation in a sand laying process of an inkjet 3D printing sand mould, aiming at solving the problems that the existing method for selecting the optimal process parameters for 3DP printing is complex in operation and slow in selection speed.

The invention is realized by the following technical scheme, and provides a method for optimizing process parameters through modeling and simulation in a sand laying process of an inkjet 3D printing sand mold, which comprises the following steps of:

step 1, designing 3DP printing equipment and an irregular particle model by adopting three-dimensional software UG and ProE;

step 2, conducting assembly processing on the 3DP printing equipment model and then importing the 3DP printing equipment model into simulation software EDEM;

step 3, filling the irregular particle model at the EDEM pretreatment interface, and setting round particles;

step 4, setting a particle factory in simulation software EDEM, calibrating various parameters of the particles, the contact model and parameters influencing the sanding effect, and setting Bond keys so as to observe bonding bridges among the particles and derive critical shearing force among the particles during post-processing; the particles include irregular particles and round particles;

step 5, calculating a time step length, setting the time step length on an EDEM solver interface, and simultaneously setting the number of grids and simulation time;

step 6, setting different sanding speeds to perform simulation in an EDEM solver, obtaining different sanding plane diagrams as sanding effect diagrams on a post-processing interface, and then rendering the particles to change the particles into red and green;

step 7, cutting the image processed in the step 6, rendering the particles to change the image into color, and keeping the micro-topography parts of the bonding bridges among different molding sand particles;

step 8, setting a fixed range calculation domain on a post-processing interface, wherein the percentage of the area of a white part area in an image is the porosity of the inkjet 3D printing sand mold;

and 9, obtaining the optimized optimal process parameters in the simulation by comparing the porosity, the critical shearing force and the sanding plan.

Further, in step 1, the modeling ratio of the 3DP printing device is 1:10, the width of the lower sand opening is set to be 12mm, the angle of the sand scraping plate is set to be 3 degrees, and the average distance of the centers of the irregular particle models is set to be 0.18 mm.

Further, when the 3DP printing device model is imported into the EDEM software in STEP 2, it is stored in STEP or IGS format, and the unit parameter is set to millimeter.

Further, in step 3, the distribution of different particle types is normal distribution, and the Physical Radius of the round particles is set to be 0.14 mm.

Further, in the step 4, a Hertz-Mindline nonlinear mold bonding contact model is selected as a contact model between the particles, under the contact model, the normal contact force between the particles is calculated according to the Hertz theory, and the tangential contact force is calculated according to the Mindline-Deresiewicz theory.

Further, parameters influencing the sanding effect are kept constant.

Further, the time step calculation formula in step 5 is:

wherein, Deltat is the time step, G is the shear modulus of the particles, rho is the density of the particles, upsilon is the Poisson ratio, and R is the radius of the particles.

Further, in the step 6, red represents silica sand, green represents ceramsite sand, and the ratio of the red particles to the green particles is the molding sand ratio of the silica sand to the ceramsite sand.

Further, in step 7, the Color By function of Bond keys is adopted to set the bonding bridges among the particles to be three different colors, wherein the blue bonding bridge represents that the shearing force which can be borne among the particles is the largest, the green bonding bridge represents that the shearing force which can be borne among the particles is between the largest and the smallest, and the red bonding bridge represents that the shearing force which can be borne among the particles is the smallest.

The invention further provides electronic equipment which comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the method for modeling and simulating optimization of process parameters in the sand paving process of the sand mold through ink-jet 3D printing when executing the computer program.

The invention has the following beneficial effects:

according to the invention, the 3DP printing process parameters are obtained by continuously changing the influence factor parameters in a test, and the process parameters and the sanding effect can be set and simulated in the EDEM, so that the sanding process of the 3DP printing sand mold is optimized by using a simulation technology.

The method provided by the invention accelerates the process of optimizing the technological parameters of the sand mold, more quickly and intuitively feeds back the sanding effect and the sanding performance of the ink-jet 3D printing sand mold under different technological parameters, and provides a basis for optimizing the technological parameters and measuring the performance of the sand mold.

Drawings

FIG. 1 is a photograph of a sand paver in example 1;

FIG. 2 is a photograph of the stage in example 1;

FIG. 3 is a photograph of irregular particles in example 1;

FIG. 4 is an overall effect diagram of the sand-laying structure after assembly in example 1;

FIG. 5 is a graph showing the effect of the irregular particles after filling in example 1;

FIG. 6 is a photograph of a circular pellet having a radius of 0.14mm in example 1;

FIG. 7 is an effect diagram of the sanding structure adjusted by EDEM software in example 1;

FIG. 8 is a sand-laying effect diagram in example 1, in which the sand-laying speed is 120mm/s after the brightness adjustment;

FIG. 9 is a sand-laying effect diagram in example 1 at a sand-laying speed of 160mm/s after brightness adjustment;

FIG. 10 is a sand-laying effect diagram in example 1, in which the sand-laying speed is 180mm/s after the brightness adjustment;

FIG. 11 is a sand-laying effect diagram in example 1 at a sand-laying speed of 200mm/s after brightness adjustment;

FIG. 12 is a sand laying effect graph in example 1 at a sand laying speed of 220mm/s after brightness adjustment;

FIG. 13 is a sand-laying effect diagram in example 1, in which the sand-laying speed is 120mm/s after color adjustment;

FIG. 14 is a sand-laying effect graph showing that the sand-laying speed is 160mm/s after color adjustment in example 1;

FIG. 15 is a sand laying effect graph at a sand laying speed of 180mm/s after color adjustment in example 1;

FIG. 16 is a sand-laying effect diagram in example 1, in which the sand-laying speed is 200mm/s after color adjustment;

FIG. 17 is a sand-laying effect diagram in example 1, in which the sand-laying speed is 220mm/s after color adjustment;

FIG. 18 is a graph showing the effect of the bond bridge at a sanding speed of 120mm/s after cutting and color adjustment in example 1;

FIG. 19 is a graph showing the effect of the bond bridge at a sanding speed of 160mm/s after cutting and color adjustment in example 1;

FIG. 20 is a graph showing the effect of a bond bridge at a sanding speed of 180mm/s after cutting and color adjustment in example 1;

FIG. 21 is a graph showing the effect of the bond bridge at a sanding speed of 200mm/s after cutting and color adjustment in example 1;

FIG. 22 is a graph showing the effect of the bond bridge at a sanding speed of 220mm/s after cutting and color adjustment in example 1;

FIG. 23 is a graph comparing the total volume of particles at different sanding speeds in the set calculation field in example 1;

FIG. 24 is a graph comparing the porosity of particles at different sanding speeds in the set calculated field in example 1;

FIG. 25 is a graph comparing the critical shear force of bond bridges at different sanding speeds in example 1;

FIG. 26 is a graph comparing the flexural strength of samples from example 1 at different sanding rates;

FIG. 27 is a graph comparing the tensile strength of samples from example 1 at different sanding rates;

FIG. 28 is a graph comparing the gas evolution of samples from example 1 at different sanding speeds;

FIG. 29 is a graph showing a comparison of the amount of burn of the samples obtained in example 1 at different sanding rates.

Detailed Description

The technical solutions in the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

With reference to fig. 1-29, the present invention provides a method for optimizing process parameters by modeling and simulation of a sand-laying process of an inkjet 3D printing sand mold, the method comprising:

in the step 1, the modeling proportion of the 3DP printing equipment is 1:10, the width of a lower sand opening is set to be 12mm, the angle of a sand scraping plate is set to be 3 degrees, and the average distance of the centers of irregular particle models is set to be 0.18 mm.

and (3) when the 3DP printing equipment model is imported into the EDEM software in the STEP 2, storing the model in a STEP or IGS format, and setting unit parameters to be millimeters.

in the step 3, the distribution of different particle types adopts normal distribution, and the parameter of the circular particle Physical Radius is set to be 0.14 mm.

and 4, selecting a Hertz-Mindline nonlinear mold bonding contact model as a contact model between the particles in the step 4, calculating the normal contact force between the particles according to the Hertz theory under the contact model, and calculating the tangential contact force according to the Mindline-Derestiewicz theory. The particle and contact model parameter calibration is shown in tables 1 to 4 below:

TABLE 1 silica Sand Material Properties

TABLE 2 silica Sand and contact model interaction parameters

TABLE 3 ceramsite sand material Properties

TABLE 4 interaction parameters of ceramsite sand with contact model

The parameters influencing the sand laying effect are all kept constant. As shown in table 5 below:

TABLE 53 DP print variable parameter values

the time step calculation formula in step 5 is:

in the step 6, red represents silica sand, green represents ceramsite sand, and the ratio of the red particles to the green particles is the molding sand ratio of the silica sand to the ceramsite sand.

and 7, setting bonding bridges among the particles into three different colors By adopting the Color By function of the Bond key, wherein the blue bonding bridge represents that the shearing force which can be born among the particles is the largest, the green bonding bridge represents that the shearing force which can be born among the particles is between the largest and the smallest, and the red bonding bridge represents that the shearing force which can be born among the particles is the smallest.

Example 1:

(1) modeling is carried out by utilizing UG and Proe three-dimensional modeling software according to the proportion of 1:10 by referring to a real 3DP sand spreader and a workbench, the width of a lower sand opening is set to be 12mm, the angle of a sand scraping plate is set to be 3 degrees, and an irregular particle model is designed, as shown in figures 1, 2 and 3;

(2) assembling the sand spreader and the workbench in UG, and exporting the assembled sand spreader and the workbench into an IGS format, as shown in FIG. 4;

(3) filling the irregular particle model by utilizing a pretreatment function in EDEM software, and setting spherical particles with the radius of 0.14mm as shown in figures 5 and 6;

(4) the overall sanding structure after various parameter calibrations and treatments are carried out on different grain types of particles, a 3DP sanding model and a contact model by utilizing the functions in the pretreatment interface of the EDEM software is shown in FIG. 7;

(5) setting different sanding speed parameters by utilizing the EDEM pretreatment function, performing simulation in an EDEM solver to obtain five groups of different sanding effect graphs, and intercepting and adjusting the brightness by using screenshot software, wherein the screenshot software is shown in figures 8, 9, 10, 11 and 12;

(6) rendering different grain type particles by using a rendering function in EDEM software post-processing, performing color adjustment, converting the color of the circular particles in the picture into green, and adjusting the color of the irregular particles into red, as shown in FIGS. 13, 14, 15, 16 and 17;

(7) cutting a sand paving finished photo by using a picture cutting function in MATLAB software, only keeping a micro-morphology part of a bonding bridge between different molding sands, adjusting brightness by using the picture adjusting function in MATLAB, and rendering particles and the bonding bridge by using an EDEM post-processing function, wherein light blue is ceramsite sand particles, brown is silica sand particles, and the bonding bridge is red, green and blue in color, as shown in FIGS. 18, 19, 20, 21 and 22;

(8) set the center position X using the EDEM post-processing function: 85mm, Y: 80mm, and 90 × 20 × 100, calculating the white part and the colored part in the calculation domains at different sanding speeds to obtain a comparison graph of the total volume and the porosity of the 3DP printed particles at different sanding speeds, as shown in FIGS. 23 and 24;

(9) calculating the critical shearing force of the bonding bridge at different sanding speeds by using the EDEM post-processing function to obtain a shearing force comparison diagram at different sanding speeds, as shown in FIG. 25;

(10) the EDEM software is combined with the MATLAB software to obtain a sanding plane contrast diagram and a bond bridge contrast diagram, the Origin software is combined with data derived from the EDEM to obtain a critical shearing force contrast diagram and a porosity and particle total volume contrast diagram in a certain calculation area, and the critical shearing force contrast diagram and the porosity and particle total volume contrast diagram can be used as bases for evaluating sanding performance and optimizing process parameters.

An experimental method is adopted to test the sanding performance under different sanding speeds, the X resolution is kept to be 0.1mm, the curing agent content is 0.14%, the layer thickness is kept to be 0.28mm, and the sanding speed range is changed to be 120-sand 200 mm/s. Fig. 26 shows the change of the bending strength of the sample at different sanding speeds, fig. 27 shows the change of the tensile strength of the sample at different sanding speeds, fig. 28 shows the change of the gas evolution of the sample at different sanding speeds, and fig. 29 shows the change of the ignition loss of the sample at different sanding speeds.

Sample comparison results:

when the sand spreading speed is 120mm/s, the porosity is minimum, but when the speed is too low, the particles are densely stacked, and the penetration of the binder among the particles is insufficient, so that the strength of a sample is poor, the mechanical property among molding sand is reduced, and the sand spreading performance is poor; the sand paving performance is best when the sand paving speed is 160mm/s, and the sand paving speed is the best process parameter. The sand paving performance is also optimal when the sand paving speed is 160mm/s by adopting an experimental method.

The method and the equipment for modeling and simulating optimization of process parameters in the sand-paving process of the sand mold through ink-jet 3D printing are described in detail, specific examples are applied to explain the principle and the implementation mode of the method, and the description of the examples is only used for helping to understand the method and the core idea of the method; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.

Claims

1. A method for optimizing process parameters through modeling and simulation in a sand-laying process of an inkjet 3D printing sand mold, the method comprising:

step 6, setting different sanding speeds to perform simulation in an EDEM solver, obtaining different sanding plane diagrams as sanding effect diagrams on a post-processing interface, and then rendering the particles to change the particles into red and green colors;

2. The method of claim 1, wherein: in the step 1, the modeling proportion of the 3DP printing equipment is 1:10, the width of a lower sand opening is set to be 12mm, the angle of a sand scraping plate is set to be 3 degrees, and the average distance of the centers of irregular particle models is set to be 0.18 mm.

3. The method of claim 1, wherein: and (3) when the 3DP printing equipment model is imported into the EDEM software in the STEP 2, storing the model in a STEP or IGS format, and setting unit parameters to be millimeters.

4. The method of claim 1, wherein: in the step 3, the distribution of different particle types adopts normal distribution, and the parameter of the circular particle Physical Radius is set to be 0.14 mm.

5. The method of claim 1, wherein: and 4, selecting a Hertz-Mindline nonlinear mold bonding contact model as a contact model between the particles in the step 4, calculating the normal contact force between the particles according to the Hertz theory under the contact model, and calculating the tangential contact force according to the Mindline-Derestiewicz theory.

6. The method of claim 1, wherein: the parameters influencing the sand laying effect are all kept constant.

7. The method of claim 1, wherein: the time step calculation formula in step 5 is:

8. The method of claim 1, wherein: in the step 6, red represents silica sand, green represents ceramsite sand, and the ratio of the red particles to the green particles is the molding sand ratio of the silica sand to the ceramsite sand.

9. The method of claim 1, wherein: and 7, setting bonding bridges among the particles into three different colors By adopting the Color By function of the Bond key, wherein the blue bonding bridge represents that the shearing force which can be born among the particles is the largest, the green bonding bridge represents that the shearing force which can be born among the particles is between the largest and the smallest, and the red bonding bridge represents that the shearing force which can be born among the particles is the smallest.

10. An electronic device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 9 when executing the computer program.