CN114535600A - Method for optimizing CuAlNi memory alloy 4D printing process - Google Patents
Method for optimizing CuAlNi memory alloy 4D printing process Download PDFInfo
- Publication number
- CN114535600A CN114535600A CN202210024668.4A CN202210024668A CN114535600A CN 114535600 A CN114535600 A CN 114535600A CN 202210024668 A CN202210024668 A CN 202210024668A CN 114535600 A CN114535600 A CN 114535600A
- Authority
- CN
- China
- Prior art keywords
- memory alloy
- cualni
- shape memory
- optimizing
- temperature
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 70
- 229910001285 shape-memory alloy Inorganic materials 0.000 title claims abstract description 65
- 238000007639 printing Methods 0.000 title claims abstract description 46
- 230000008569 process Effects 0.000 title claims abstract description 45
- 239000000843 powder Substances 0.000 claims abstract description 31
- 238000004458 analytical method Methods 0.000 claims abstract description 28
- 238000012360 testing method Methods 0.000 claims abstract description 23
- 238000002844 melting Methods 0.000 claims abstract description 21
- 230000008018 melting Effects 0.000 claims abstract description 21
- 238000005457 optimization Methods 0.000 claims abstract description 20
- 230000003446 memory effect Effects 0.000 claims abstract description 11
- 238000004088 simulation Methods 0.000 claims abstract description 11
- 238000002360 preparation method Methods 0.000 claims abstract description 10
- 230000008859 change Effects 0.000 claims abstract description 8
- 238000012795 verification Methods 0.000 claims abstract description 7
- 238000009826 distribution Methods 0.000 claims abstract description 4
- 238000013386 optimize process Methods 0.000 claims abstract description 4
- 238000002474 experimental method Methods 0.000 claims description 9
- 238000000889 atomisation Methods 0.000 claims description 5
- 230000003287 optical effect Effects 0.000 claims description 4
- 238000000465 moulding Methods 0.000 claims description 2
- 238000005275 alloying Methods 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 abstract description 18
- 230000007704 transition Effects 0.000 abstract description 9
- 238000013461 design Methods 0.000 abstract description 7
- 239000000654 additive Substances 0.000 abstract description 4
- 230000000996 additive effect Effects 0.000 abstract description 4
- 230000007334 memory performance Effects 0.000 abstract description 4
- 230000009466 transformation Effects 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 6
- 229910045601 alloy Inorganic materials 0.000 description 5
- 239000000956 alloy Substances 0.000 description 5
- 230000007547 defect Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 5
- 239000000463 material Substances 0.000 description 5
- XKRFYHLGVUSROY-UHFFFAOYSA-N Argon Chemical compound [Ar] XKRFYHLGVUSROY-UHFFFAOYSA-N 0.000 description 4
- 229910000734 martensite Inorganic materials 0.000 description 4
- 229910001000 nickel titanium Inorganic materials 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000003247 decreasing effect Effects 0.000 description 3
- 238000011084 recovery Methods 0.000 description 3
- 238000010146 3D printing Methods 0.000 description 2
- 229910052786 argon Inorganic materials 0.000 description 2
- 229910001566 austenite Inorganic materials 0.000 description 2
- 238000004140 cleaning Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000003825 pressing Methods 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 238000005303 weighing Methods 0.000 description 2
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 1
- HZEWFHLRYVTOIW-UHFFFAOYSA-N [Ti].[Ni] Chemical compound [Ti].[Ni] HZEWFHLRYVTOIW-UHFFFAOYSA-N 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005422 blasting Methods 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 239000013078 crystal Substances 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000002050 diffraction method Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000000227 grinding Methods 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000000608 laser ablation Methods 0.000 description 1
- 230000000670 limiting effect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 239000011812 mixed powder Substances 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000009740 moulding (composite fabrication) Methods 0.000 description 1
- 238000013021 overheating Methods 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 230000036961 partial effect Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000002829 reductive effect Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000007711 solidification Methods 0.000 description 1
- 230000008023 solidification Effects 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 238000009864 tensile test Methods 0.000 description 1
- 238000002076 thermal analysis method Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
- B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
- B22F10/20—Direct sintering or melting
- B22F10/28—Powder bed fusion, e.g. selective laser melting [SLM] or electron beam melting [EBM]
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B22—CASTING; POWDER METALLURGY
- B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
- B22F10/00—Additive manufacturing of workpieces or articles from metallic powder
- B22F10/80—Data acquisition or data processing
- B22F10/85—Data acquisition or data processing for controlling or regulating additive manufacturing processes
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y10/00—Processes of additive manufacturing
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
- B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
-
- C—CHEMISTRY; METALLURGY
- C22—METALLURGY; FERROUS OR NON-FERROUS ALLOYS; TREATMENT OF ALLOYS OR NON-FERROUS METALS
- C22C—ALLOYS
- C22C9/00—Alloys based on copper
- C22C9/01—Alloys based on copper with aluminium as the next major constituent
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P10/00—Technologies related to metal processing
- Y02P10/25—Process efficiency
Abstract
The invention relates to the technical field of additive manufacturing, in particular to a method for optimizing a CuAlNi memory alloy 4D printing process. The method comprises the following steps: preparing prealloying powder, carrying out selective laser melting block forming in a small parameter range, and analyzing the size and the printability of a molten pool; obtaining a theoretical result of the shape and size of the molten pool under the condition of large-range different process parameter combinations through finite element analysis; optimizing and calculating a finite element simulation result based on the actual size of the molten pool to obtain a theoretical printable performance distribution map and an optimal technological parameter combination interval of the high-temperature shape memory alloy with a large parameter range; and aiming at the printable prediction result in the large parameter range, performing printability verification and phase change temperature and shape memory effect test on the optimized process parameter interval. According to the invention, through the process design optimization method, the rapid and efficient process optimization of the CuAlNi high-temperature shape memory alloy 4D printing preparation with high phase transition temperature and excellent shape memory performance is realized.
Description
Technical Field
The invention relates to the technical field of additive manufacturing, in particular to a method for optimizing a CuAlNi memory alloy 4D printing process.
Background
The additive manufacturing technology (commonly known as 3D printing technology) is a technology which is developed in the last thirty years and decomposes materials into layer-by-layer data based on digital model design software to realize the accumulative manufacturing of solid parts, has the advantages of high forming speed, short production period, high material utilization rate, good material adaptability, no need of drawings and tooling equipment, high digitization degree and the like, and is widely applied to the fields of mechanical manufacturing, aerospace, biomedical treatment and the like. With the gradual change of the center of gravity of high-end equipment in the intelligent development to the intelligent characteristic requirement, the 4D printing technology realizes the controllable change of the shape, the performance or the function along with the time by manufacturing a special component through the 3D printing technology, and is an effective means for realizing the manufacture of complex intelligent components or intelligent materials.
The shape memory alloy can automatically recover the shape before deformation after the temperature reaches the austenite transformation temperature after the phase transformation is carried out in the low-temperature martensite form through the crystallography corresponding relation between the austenite phase and the martensite phase, and is an intelligent material with wide application. The shape memory alloy which is most widely applied at present is the nickel titanium shape memory alloy with the approximate equal atomic ratio. However, the low martensitic transformation temperature (generally lower than 373K) and the poor machinability of NiTi shape memory alloys greatly limit their further applications. The Cu-based shape memory alloy has a higher transformation temperature and superior workability, compared to conventional NiTi alloys. However, the Cu-based shape memory alloy manufactured by the conventional processing method is susceptible to intergranular cracking during processing due to its inherent high brittleness. The selective laser melting technology is also called laser powder bed manufacturing, is one of the representative processes of the prior additive manufacturing, has extremely high cooling and solidification speed in the printing and manufacturing process, can effectively refine crystal grains, and is a manufacturing process which is expected to solve the problem of high brittleness of the Cu-based high-temperature shape memory alloy.
The phase transition temperature and shape memory effect of Cu-based shape memory alloys are controlled by the composition of the alloy. Although this provides an effective means for regulating the transformation temperature and shape memory effect of Cu-based shape memory alloys, the specific powder components need to be individually customized during the powdering process, and regulating the transformation temperature and shape memory effect by changing the components has a very high cost. How to reduce the cost and realize the rapid and efficient process optimization of the Cu-based high-temperature shape memory alloy by using a small amount of powder is an important problem to be solved urgently in the 4D printing development of the current high-temperature shape memory alloy.
Disclosure of Invention
The invention aims to provide a method for optimizing a CuAlNi memory alloy 4D printing process, and the method for optimizing the process design realizes the quick and efficient process optimization of CuAlNi high-temperature shape memory alloy 4D printing preparation with high phase transition temperature and excellent shape memory performance.
In order to achieve the above object, the present invention provides the following technical solutions:
the invention provides a method for optimizing a 4D printing process of a CuAlNi memory alloy, which comprises the following steps of:
(1) preparing prealloying powder of CuAlNi high-temperature shape memory alloy;
(2) carrying out selective laser melting block forming in a small parameter range on the pre-alloyed powder obtained in the step (1), and analyzing the size and the printability of a molten pool;
(3) obtaining a theoretical result of the shape and size of the molten pool under the condition of large-range different process parameter combinations through finite element analysis;
(4) optimizing and calculating a finite element simulation result based on the actual size of the molten pool to obtain a theoretical printable performance distribution map and an optimal technological parameter combination interval of the high-temperature shape memory alloy with a large parameter range;
(5) and aiming at the printability prediction result in the large parameter range, performing printability verification and phase change temperature and shape memory effect test on an optimized process parameter interval, and realizing 4D printing preparation process optimization based on the CuAlNi high-temperature shape memory alloy.
Preferably, the pre-alloyed powder of the CuAlNi high-temperature shape memory alloy in the step (1) comprises the following components in percentage by mass: al: ni 80-90: 10-14: 2 to 4.
Preferably, step (1) is carried out by rotary electrode atomization to prepare the pre-alloyed powder of the CuAlNi high-temperature shape memory alloy.
Preferably, the step (2) is carried out with a ZEISS AX10 optical microscope and an ST-100E full-automatic electron densitometer for printability analysis.
Preferably, in the step (2), RENISHAW-AM400 laser selective melting rapid prototyping equipment is adopted for selective laser melting, three variable parameters of line spacing, exposure time and laser power are selected as small-parameter-range printing test parameters, and a sample is prepared through an experiment.
Preferably, in step (3), finite element analysis is performed using Abaqus 6.14.
Compared with the prior art, the invention has the following beneficial effects:
1. the invention discloses a process optimization design method for 4D printing preparation of CuAlNi high-temperature shape memory alloy based on selective laser melting, which comprises the steps of preparing pre-alloyed powder of CuAlNi high-temperature shape memory alloy with expected components by rotary electrode atomization; performing a small-range parameter pre-experiment on the powder of the high-temperature shape memory alloy by selective laser melting to obtain the printability of the high-temperature shape memory alloy in a small parameter range;
carrying out finite element analysis on different process parameters in a large parameter range to obtain a simulation result of the size of the molten pool; correcting the simulation result and calculating the printable boundary condition according to the actual size of the molten pool to obtain the printable simulation calculation result of the high-temperature shape memory alloy with a large parameter range; and selecting part of process parameters to perform a verification experiment for simulating printability, and determining the optimal process of the high-temperature shape memory alloy by the aid of phase change temperature and shape memory effect tests.
According to the invention, through the process design optimization method, the rapid and efficient process optimization of the CuAlNi high-temperature shape memory alloy 4D printing preparation with high phase transition temperature and excellent shape memory performance is realized.
2. Compared with NiTi alloy, the Cu-based shape memory alloy has higher phase transition temperature and machinability, and the problem of high brittleness is hopeful to be solved by realizing 4D printing manufacturing of the Cu-based shape memory alloy through selective laser melting. The traditional process optimization mode of selective laser melting has a series of problems of high cost, low efficiency and the like in the process of modifying components in 4D printing and manufacturing. The prealloying manufacturing powder has high cost, only can produce alloy powder with single component in a single furnace, and simultaneously, the powder output is not high, thus the development of 4D printing manufacturing is severely limited.
Meanwhile, the traditional process optimization method based on density and laser energy density is low in efficiency, low density is lack of persuasion due to combination of extreme process parameters with the same energy density, and scientific and reasonable analysis of process optimization can be realized only by evaluating necessary indexes, namely shape memory performance, required by use of the shape memory alloy. According to the invention, through a process design method based on the combination of finite element analysis and practice, an optimal process optimization parameter interval is determined scientifically, quickly and efficiently, and then phase transition temperature and shape memory effect tests are assisted, so that the process optimization of 4D printing preparation of the CuAlNi high-temperature shape memory alloy with a large parameter range is successfully realized, and the method has important significance for solving the development limitation problems of high process optimization cost and low efficiency in the 4D printing field.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 shows 4D printing of molded raw powders (a and b) and molded samples (c);
FIG. 2 is a printability of a small parameter range CuAlNi alloy;
FIG. 3 is a relationship between the compactness of Cu-13.2Al-3.5Ni manufactured by 4D printing in a small parameter interval and laser energy density and defect analysis.
Detailed Description
The invention provides a method for optimizing a 4D printing process of a CuAlNi memory alloy, which comprises the following steps of:
(1) preparing prealloying powder of CuAlNi high-temperature shape memory alloy;
(2) carrying out selective laser melting block forming in a small parameter range on the pre-alloyed powder obtained in the step (1), and analyzing the size and the printability of a molten pool;
(3) obtaining a theoretical result of the shape and size of the molten pool under the condition of large-range different process parameter combinations through finite element analysis;
(4) optimizing and calculating a finite element simulation result based on the actual size of the molten pool to obtain a theoretical printable performance distribution map and an optimal technological parameter combination interval of the high-temperature shape memory alloy with a large parameter range;
(5) and aiming at the printability prediction result in the large parameter range, performing printability verification and phase change temperature and shape memory effect test on an optimized process parameter interval, and realizing 4D printing preparation process optimization based on the CuAlNi high-temperature shape memory alloy.
In the invention, the pre-alloyed powder of the CuAlNi high-temperature shape memory alloy in the step (1) comprises the following components in percentage by mass: al: ni 80-90: 10-14: 2-4; preferably 82-88: 11-13.2: 3.5; further preferably 83.3: 12: 3.5; more preferably 83.3: 13.2: 3.5.
in the invention, step (1) is to prepare the pre-alloyed powder of the CuAlNi high-temperature shape memory alloy through rotary electrode atomization.
In the present invention, the step (2) is performed with printability analysis using ZEISS AX10 optical microscope and ST-100E full automatic electron densitometer.
In the invention, the step (2) adopts a RENISHAW-AM400 laser selective melting rapid molding device to perform selective laser melting, three variable parameters of line spacing, exposure time and laser power are selected as small parameter range printing test parameters, and a sample is prepared through an experiment.
In the present invention, finite element analysis is performed in the step (3) using Abaqus 6.14.
The technical solutions provided by the present invention are described in detail below with reference to examples, but they should not be construed as limiting the scope of the present invention.
Example 1
Atomizing by a rotating electrode to obtain 83.3Cu-13.2Al-3.5Ni high-temperature shape memory alloy prealloying powder; then, performing selective laser melting block forming on the original powder, and performing selective laser melting small-range parameter pre-experiment on the powder of the high-temperature shape memory alloy to obtain the printability of the high-temperature shape memory alloy in a small parameter range; carrying out finite element analysis on different process parameters in a large parameter range to obtain a simulation result of the size of the molten pool; correcting the simulation result and calculating the printable boundary condition according to the actual size of the molten pool to obtain the printable simulation calculation result of the high-temperature shape memory alloy with a large parameter range; and selecting part of process parameters to perform a verification experiment for simulating printability, and determining the optimal process of the high-temperature shape memory alloy by testing the phase transition temperature and the shape memory effect.
First, selective laser ablation
And collecting the mixed powder in a powder cylinder, cleaning the substrate, blasting sand, removing a surface oxide layer, and then installing, and finally finishing the replacement and installation of the scraper. And opening an air extractor, introducing argon for protection, ensuring that the oxygen content in the equipment is below 100ppm, and preheating the Cu substrate to 170 ℃. Completion of 5 x 5mm using QuantAM software3Building a cube model and setting process parameters, importing model data into equipment, and automatically starting sample manufacturing by the equipment system after preparation conditions are ready. Three variable parameters of laser line spacing, exposure time and laser power are selected as orthogonal test factors in the experiment, and the experiment is carried out to prepare the sample.
Second, density analysis
Putting the sample after wire cutting into absolute ethyl alcohol, cleaning and removing impurities adhered to the surface, drying, putting the sample on a measuring table, weighing, recording data by pressing a key after the number is stable, then weighing the sample in a hanging basket in a water tank, and directly obtaining a result and recording data by pressing the key after the number is stable. At least three measurements are guaranteed for each sample and averaged to reduce error.
Third, printability analysis
Printable testing is divided into three areas: forming quality analysis, defect analysis and single melt channel analysis;
the forming quality is directly carried out in the printing process, and the problems of the forming quality such as warping, overheating and the like in the layer-by-layer manufacturing process of the samples with different process parameters are analyzed;
analyzing the surface porosity and the pore morphology of the polished sample by using a ZEISS AX10 optical microscope for defect analysis, and classifying and judging the printing defects;
in the single-channel analysis, if the molten pool is clear and visible after the sample is corroded, information collection such as the penetration and the fusion width of the single-channel molten pool can be directly carried out through the last printing layer formed by the block; if the shape of the molten pool can not be judged, extra single-channel printing tests are required to be directly carried out, and melting depth and melting width of different process parameters are counted.
Four, finite element analysis
Finite element analysis the single-channel molten pool size parameters of different process parameters during printing were simulated and characterized using the Abaqus 6.14 software. And (3) comprehensively considering simulation precision and efficiency, dividing uneven model grids, using a two-dimensional thermal analysis unit DC2D4/DC2D3, calculating and selecting a Gauss surface heat source model by using a temperature field, and considering radiation heat transfer and convection heat transfer.
Fifth, simulating printability calculation
Based on the size information of the molten pool with a large parameter range, the printability of the CuAlNi shape memory alloy is predicted, and the defect boundary conditions are as follows:
non-fusion:
keyhole:
spheroidizing:
wherein D is the depth of the molten pool, W is the width of the molten pool, t is the thickness of the layer, and L is the length of the molten pool.
Sixth, verification of process design optimization
The method comprises the following two aspects: phase transition temperature test and shape memory recovery test
Phase transition temperature testing the heat absorption and heat release behaviors of the samples during slow temperature rise and fall were characterized using a STA449f3 comprehensive thermal analyzer. Taking the size of 1.5 x 1.5mm3The test sample is placed in a special crucible for an instrument to be tested, the test atmosphere is an argon environment, the temperature of the sample is slowly increased from 100 ℃ to 700 ℃ and then is decreased to 100 ℃, and the temperature increasing rate and the temperature decreasing rate are both 10 ℃/min.
Shape memory recovery rate test A force test microcomputer controlled electronic universal tester LD26.105 was used to perform a load/unload test on a tensile sample, and then the recoverable strain after high temperature recovery was measured. The tensile test was carried out according to ASTM E8/E8M-13 Standard methods for Testing of Metallic Materials, with both tensile and unload rates of 0.375 mm/min; the heating temperature is 50 ℃ above the martensite reverse phase transformation final temperature.
Seventh, analysis of experimental results
FIG. 1 shows the effect of laser melting, printing and forming 83.3Cu-13.2Al-3.5Ni high-temperature shape memory alloy powder and selected regions; the sphericity of the powder manufactured by rotary electrode atomization is good, and the surface scanning result shows that the elements of the powder are uniformly distributed and meet the powder standard used for selective laser melting. The forming effect diagram shows that the printability of the Cu-13.2Al-3.5Ni high-temperature shape memory alloy powder is poor, the sample is seriously warped in the printing process, and the sample forming is seriously influenced; in the printing process of a sample with high energy density, due to the fact that the sample is overheated integrally, a molten pool collapses to cause that the forming deviates from a designed shape, and the forming precision is seriously influenced; of the 45 samples, only 5 samples with good surface appearance were obtained.
FIG. 2 is a small parameter range printability of the established 83.3Cu-13.2Al-3.5Ni high temperature shape memory alloy. The sample can be seen to be seriously warped at a high scanning speed and is difficult to form; under the conditions of low scanning speed and high power, a keyhole phenomenon occurs, and the printing quality is difficult to ensure; can be well formed only in a certain combined interval of power and scanning speed. Further analysis is carried out by combining with a density energy density curve, so that the printability of the sample is difficult to completely react only through energy density, the optimal process parameters are partial intervals of different process parameter combinations, and the forming in the intervals has higher quality.
As shown in fig. 3, the density of the sample tends to increase first and then decrease with the increase of the energy density, and the sample can realize high-density printing in a certain energy density interval. However, in this interval, the density is also decreased due to extreme parameter combinations, and there is insufficient persuasion to use only the energy density as an index for optimizing the process parameters. At low energy densities, the main cause of the decrease in density is unfused; the density of the sample is reduced under high energy density because of a keyhole phenomenon, and gas in the molten pool is difficult to discharge due to overhigh energy density, so that air holes are generated.
The traditional process optimization method based on density and laser energy density is low in efficiency, and low density is lack of persuasion caused by combination of extreme process parameters with the same energy density. A process design method based on combination of finite element analysis and practice is used, finite element analysis is guided through a shape memory alloy printing result in a small parameter range, printability prediction of the shape memory alloy in a large parameter range is achieved, and an optimal process parameter interval is determined. And then, the phase change temperature and shape memory effect test is assisted, so that the 4D printing preparation process optimization of the CuAlNi high-temperature shape memory alloy with a large parameter range is successfully realized, and the method has important significance for solving the development limitation problems of high process optimization cost and low efficiency in the 4D printing field.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (6)
1. A method for optimizing a 4D printing process of a CuAlNi memory alloy is characterized by comprising the following steps:
(1) preparing prealloying powder of CuAlNi high-temperature shape memory alloy;
(2) carrying out selective laser melting block forming in a small parameter range on the pre-alloyed powder obtained in the step (1), and analyzing the size and the printability of a molten pool;
(3) obtaining a theoretical result of the shape and the size of the molten pool under different process parameter combinations in a large range through finite element analysis;
(4) optimizing and calculating a finite element simulation result based on the actual size of the molten pool to obtain a theoretical printable performance distribution map and an optimal technological parameter combination interval of the high-temperature shape memory alloy with a large parameter range;
(5) and aiming at the printability prediction result in the large parameter range, performing printability verification and phase change temperature and shape memory effect test on an optimized process parameter interval, and realizing 4D printing preparation process optimization based on the CuAlNi high-temperature shape memory alloy.
2. A method for optimizing a 4D printing process of a CuAlNi memory alloy is characterized by comprising the following steps: the pre-alloying powder of the CuAlNi high-temperature shape memory alloy in the step (1) comprises the following components in percentage by mass: al: ni 80-90: 10-14: 2 to 4.
3. A method for optimizing a 4D printing process of a CuAlNi memory alloy is characterized by comprising the following steps: and (1) preparing the pre-alloyed powder of the CuAlNi high-temperature shape memory alloy by rotary electrode atomization.
4. A method for optimizing a 4D printing process of a CuAlNi memory alloy is characterized by comprising the following steps: and (3) performing printability analysis by adopting a ZEISS AX10 optical microscope and an ST-100E full-automatic electron densitometer in the step (2).
5. A method for optimizing a 4D printing process of a CuAlNi memory alloy is characterized by comprising the following steps: and (2) carrying out selective laser melting by adopting a RENISHAW-AM400 laser selective melting rapid molding device, selecting three variable parameters of line spacing, exposure time and laser power as small-parameter-range printing test parameters, and carrying out experiments to prepare the sample.
6. A method for optimizing a 4D printing process of a CuAlNi memory alloy is characterized by comprising the following steps: in step (3), finite element analysis was performed using Abaqus 6.14.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210024668.4A CN114535600B (en) | 2022-01-11 | 2022-01-11 | CuAlNi memory alloy 4D printing process optimization method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210024668.4A CN114535600B (en) | 2022-01-11 | 2022-01-11 | CuAlNi memory alloy 4D printing process optimization method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114535600A true CN114535600A (en) | 2022-05-27 |
| CN114535600B CN114535600B (en) | 2024-04-19 |
Family
ID=81669657
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210024668.4A Active CN114535600B (en) | 2022-01-11 | 2022-01-11 | CuAlNi memory alloy 4D printing process optimization method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114535600B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105033255A (en) * | 2015-07-31 | 2015-11-11 | 南京航空航天大学 | Method for directly obtaining martensite die steel through laser 3D printing technology |
| CN107330137A (en) * | 2017-05-17 | 2017-11-07 | 武汉工程大学 | A kind of metal material cuts the discrimination method of Parameters of constitutive model |
| CN108197384A (en) * | 2017-12-30 | 2018-06-22 | 大族激光科技产业集团股份有限公司 | The parameter optimization method of powder laser 3D printing moulding process |
| CN108788154A (en) * | 2018-06-26 | 2018-11-13 | 华中科技大学 | A kind of 4D Method of printings of intelligence structure and products thereof with large deformation function |
| CN110788340A (en) * | 2019-11-13 | 2020-02-14 | 中南大学 | Preparation method of 4D printing copper-based shape memory alloy and 4D printing copper-based shape memory alloy |
| CN111299584A (en) * | 2019-12-17 | 2020-06-19 | 吉林大学 | Preparation method of bionic impact-resistant multilayer composite gradient material based on amorphous alloy |
| CN111842888A (en) * | 2020-06-18 | 2020-10-30 | 华中科技大学 | 4D printing method of nickel titanium based ternary shape memory alloy |
| US20210146630A1 (en) * | 2019-11-18 | 2021-05-20 | 3D Medlab | Process for the production of a 4d medical device and 4d medical device |
| CN113102754A (en) * | 2019-12-24 | 2021-07-13 | 天津大学 | High-entropy alloy selective laser melting process parameter optimization method |
| CN113139314A (en) * | 2021-04-29 | 2021-07-20 | 四川大学 | Heat source numerical simulation method for laser additive manufacturing process |
| CN113145864A (en) * | 2020-12-23 | 2021-07-23 | 华南理工大学 | 4D printing device of titanium-nickel shape memory alloy and component regulation and control method thereof |
-
2022
- 2022-01-11 CN CN202210024668.4A patent/CN114535600B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105033255A (en) * | 2015-07-31 | 2015-11-11 | 南京航空航天大学 | Method for directly obtaining martensite die steel through laser 3D printing technology |
| CN107330137A (en) * | 2017-05-17 | 2017-11-07 | 武汉工程大学 | A kind of metal material cuts the discrimination method of Parameters of constitutive model |
| CN108197384A (en) * | 2017-12-30 | 2018-06-22 | 大族激光科技产业集团股份有限公司 | The parameter optimization method of powder laser 3D printing moulding process |
| CN108788154A (en) * | 2018-06-26 | 2018-11-13 | 华中科技大学 | A kind of 4D Method of printings of intelligence structure and products thereof with large deformation function |
| CN110788340A (en) * | 2019-11-13 | 2020-02-14 | 中南大学 | Preparation method of 4D printing copper-based shape memory alloy and 4D printing copper-based shape memory alloy |
| US20210146630A1 (en) * | 2019-11-18 | 2021-05-20 | 3D Medlab | Process for the production of a 4d medical device and 4d medical device |
| CN111299584A (en) * | 2019-12-17 | 2020-06-19 | 吉林大学 | Preparation method of bionic impact-resistant multilayer composite gradient material based on amorphous alloy |
| CN113102754A (en) * | 2019-12-24 | 2021-07-13 | 天津大学 | High-entropy alloy selective laser melting process parameter optimization method |
| CN111842888A (en) * | 2020-06-18 | 2020-10-30 | 华中科技大学 | 4D printing method of nickel titanium based ternary shape memory alloy |
| CN113145864A (en) * | 2020-12-23 | 2021-07-23 | 华南理工大学 | 4D printing device of titanium-nickel shape memory alloy and component regulation and control method thereof |
| CN113139314A (en) * | 2021-04-29 | 2021-07-20 | 四川大学 | Heat source numerical simulation method for laser additive manufacturing process |
Non-Patent Citations (1)
| Title |
|---|
| 周馨我: "《3D打印技术及应用》", 北京理工大学出版社, pages: 364 - 367 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114535600B (en) | 2024-04-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Promoppatum et al. | Numerical modeling and experimental validation of thermal history and microstructure for additive manufacturing of an Inconel 718 product | |
| CN105033255A (en) | Method for directly obtaining martensite die steel through laser 3D printing technology | |
| CN108555296A (en) | A kind of increasing material manufacturing method of K465 alloy powders | |
| CN110976830B (en) | Control method for casting defects of aluminum alloy gear shifting hub | |
| CN105973664A (en) | Solidified sample high-flux preparation method | |
| He et al. | 3D thermal finite element analysis of the SLM 316L parts with microstructural correlations | |
| CN107586942B (en) | A kind of design method of the steel-casting heat treatment process based on multiple regression analysis | |
| CN110263418A (en) | A kind of body centred cubic alloy microsegregation Numerical Predicting Method | |
| Li et al. | Multi-principal element alloys by additive manufacturing | |
| CN114535600B (en) | CuAlNi memory alloy 4D printing process optimization method | |
| CN113136551A (en) | High-throughput method for rapidly screening antioxidant components of Nb-Si-based alloy | |
| Tan et al. | Solidification Effect on the Microstructure and Mechanism of Laser‐Solid‐Forming‐Produced Flame‐Resistant Ti–35V–15Cr Alloy | |
| CN114990411B (en) | High-copper-content 3D printing nickel-titanium-copper alloy and preparation method thereof | |
| CN114101703A (en) | 4D printing optimization method of TiZrNb high-temperature shape memory alloy based on selective laser melting | |
| Guo et al. | Mo-Si-B Alloy Formed by Optional Laser Melting Process | |
| CN116348876A (en) | Optimization of alloy properties | |
| CN112964745B (en) | Calibration method for preparing amorphous alloy internal temperature field by spark plasma sintering | |
| Dezfoli et al. | Investigation into microstructure and element segregation of Inconel 713LC during SLM processing using modified cellular automaton model | |
| US20230234132A1 (en) | Simulation system for selecting an alloy, and a production process for a workpiece to be produced having amorphous properties | |
| CN113466322B (en) | Method for detecting pollution degree of contact material for high-purity aluminum smelting on aluminum liquid | |
| CN116008148A (en) | Prediction method for solution treatment porosity of nickel-based powder superalloy | |
| CN115808511A (en) | Method for determining additive manufacturing forming parameters of metal material | |
| Polkowska et al. | Characteristics of the Evolution of Carbide Morphology in the Haynes® 230® Alloy as a Result of High Temperature Annealing | |
| CN117236189A (en) | Quick design L1 based on machine learning 2 Method and device for phase strengthening single crystal high entropy alloy | |
| CN112304844B (en) | Method for rapidly measuring initial melting temperature of single crystal high-temperature alloy |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |