CN114535600B - CuAlNi memory alloy 4D printing process optimization method - Google Patents
CuAlNi memory alloy 4D printing process optimization method Download PDFInfo
- Publication number
- CN114535600B CN114535600B CN202210024668.4A CN202210024668A CN114535600B CN 114535600 B CN114535600 B CN 114535600B CN 202210024668 A CN202210024668 A CN 202210024668A CN 114535600 B CN114535600 B CN 114535600B
- Authority
- CN
- China
- Prior art keywords
- memory alloy
- shape memory
- cualni
- printability
- 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.)
- Active
Links
- 229910001285 shape-memory alloy Inorganic materials 0.000 title claims abstract description 62
- 238000000034 method Methods 0.000 title claims abstract description 58
- 238000007639 printing Methods 0.000 title claims abstract description 41
- 238000005457 optimization Methods 0.000 title claims abstract description 24
- 230000008569 process Effects 0.000 claims abstract description 36
- 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 24
- 238000002844 melting Methods 0.000 claims abstract description 22
- 230000008018 melting Effects 0.000 claims abstract description 22
- 230000007704 transition Effects 0.000 claims abstract description 18
- 238000004088 simulation Methods 0.000 claims abstract description 12
- 230000003446 memory effect Effects 0.000 claims abstract description 11
- 238000002360 preparation method Methods 0.000 claims abstract description 10
- 238000000465 moulding Methods 0.000 claims abstract description 7
- 238000012795 verification Methods 0.000 claims abstract description 7
- 238000010586 diagram Methods 0.000 claims abstract description 5
- 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
- 238000004519 manufacturing process Methods 0.000 abstract description 18
- 238000013461 design Methods 0.000 abstract description 8
- 239000000654 additive Substances 0.000 abstract description 5
- 230000000996 additive effect Effects 0.000 abstract description 5
- 230000007334 memory performance Effects 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 8
- 239000000463 material Substances 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
- 238000004364 calculation method Methods 0.000 description 4
- 238000011161 development Methods 0.000 description 4
- 229910000734 martensite Inorganic materials 0.000 description 4
- 230000009466 transformation Effects 0.000 description 4
- 239000000203 mixture Substances 0.000 description 3
- 229910001000 nickel titanium Inorganic materials 0.000 description 3
- 238000011084 recovery Methods 0.000 description 3
- 238000010146 3D printing Methods 0.000 description 2
- XKRFYHLGVUSROY-UHFFFAOYSA-N Argon Chemical compound [Ar] XKRFYHLGVUSROY-UHFFFAOYSA-N 0.000 description 2
- 229910001566 austenite Inorganic materials 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004140 cleaning Methods 0.000 description 2
- 238000001816 cooling Methods 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000010438 heat treatment Methods 0.000 description 2
- 239000011148 porous material Substances 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
- 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
- 230000006978 adaptation Effects 0.000 description 1
- 229910052786 argon Inorganic materials 0.000 description 1
- 239000012300 argon atmosphere Substances 0.000 description 1
- 239000012298 atmosphere Substances 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
- 238000012512 characterization method Methods 0.000 description 1
- 238000005336 cracking Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000004927 fusion 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
- 239000012535 impurity Substances 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000011068 loading method Methods 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
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 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
- 230000035515 penetration Effects 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
- 238000005488 sandblasting Methods 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
- 238000007655 standard test method 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
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 4D printing process of a CuAlNi memory alloy. The method comprises the following steps: preparing prealloyed powder, performing selective laser melting block molding in a small parameter range, and analyzing the size and printability of a molten pool; obtaining a theoretical result of the shape and the size of the molten pool under the combination of different process parameters in a large range through finite element analysis; optimizing and calculating a finite element simulation result based on the actual bath size to obtain a theoretical printable performance distribution diagram of the high-temperature shape memory alloy with a large parameter range and an optimal technological parameter combination interval; and carrying out printability verification and phase transition temperature and shape memory effect test of the optimized process parameter interval aiming at the printability prediction result of the large parameter range. The process design optimization method realizes the rapid and efficient process optimization of the 4D printing preparation of the CuAlNi high-temperature shape memory alloy with high phase transition temperature and excellent shape memory performance.
Description
Technical Field
The invention relates to the technical field of additive manufacturing, in particular to a method for optimizing a 4D printing process of a CuAlNi memory alloy.
Background
The additive manufacturing technology (commonly called as the 3D printing technology) is a technology developed in the last thirty years based on digital model design software to decompose materials into layer-by-layer data so as to realize additive manufacturing of solid parts, has the advantages of high forming speed, short production period, high material utilization rate, good material adaptability, no need of drawing 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. Along with the gradual change of the gravity center in the intelligent development of high-end equipment into intelligent characteristic requirements, the 4D printing technology realizes the controllable change of the shape, performance or function along with time by manufacturing special components through a 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 through the crystallographic correspondence relationship between the austenite phase and the martensite phase after the transformation under the low-temperature martensite form, and is an intelligent material with wide application. The most widely used shape memory alloy at present is near-equiatomic ratio nickel titanium shape memory alloy. However, niTi shape memory alloys have low martensitic transformation temperatures (typically below 373K) and poor workability, which greatly limits their further use. Compared with the traditional NiTi alloy, the Cu-based shape memory alloy has higher phase transition temperature and excellent machinability. However, cu-based shape memory alloys manufactured by conventional processing methods are susceptible to intergranular cracking during processing due to their inherent high brittleness. The selective laser melting technology is also called laser powder bed manufacturing, is one of the representative technologies of the prior additive manufacturing, has extremely high cooling solidification speed in the printing manufacturing process, can effectively refine grains, and is a manufacturing technology hopeful to solve the problem of high brittleness of the Cu-based high-temperature shape memory alloy.
The transformation temperature and shape memory effect of the Cu-based shape memory alloy are controlled by the composition of the alloy. While this provides an effective means of regulating the phase transition temperature and shape memory effect of Cu-based shape memory alloys, the particular powder composition needs to be individually tailored during the powdering process, with extremely high costs of regulating the phase transition temperature and shape memory effect by varying the composition. How to reduce the cost, and realizing the rapid and efficient process optimization of the Cu-based high-temperature shape memory alloy by using a small amount of powder are important problems to be solved in the development of 4D printing of the current high-temperature shape memory alloy.
Disclosure of Invention
The invention aims to provide a method for optimizing a 4D printing process of a CuAlNi memory alloy, and by the method for optimizing process design, the rapid and efficient process optimization of the 4D printing preparation of the CuAlNi high-temperature shape memory alloy with high phase transition temperature and excellent shape memory performance is realized.
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:
(1) Preparing prealloyed powder of the CuAlNi high-temperature shape memory alloy;
(2) Performing selective laser melting block molding of a small parameter range on the prealloyed powder obtained in the step (1), and analyzing the size and printability of a molten pool;
(3) Obtaining a theoretical result of the shape and the size of the molten pool under the combination of different process parameters in a large range through finite element analysis;
(4) Optimizing and calculating a finite element simulation result based on the actual bath size to obtain a theoretical printable performance distribution diagram of the high-temperature shape memory alloy with a large parameter range and an optimal technological parameter combination interval;
(5) And aiming at the printability prediction result in a large parameter range, performing printability verification and phase transition temperature and shape memory effect test in an optimized process parameter interval, and realizing process optimization of 4D printing preparation based on the CuAlNi high-temperature shape memory alloy.
Preferably, the prealloyed powder of the CuAlNi high-temperature shape memory alloy in the step (1) comprises the following components in percentage by mass: al: ni=80 to 90:10 to 14:2 to 4.
Preferably, step (1) prepares prealloyed powder of the CuAlNi high temperature shape memory alloy by rotary electrode atomization.
Preferably, the step (2) uses a ZEISS AX10 optical microscope and a ST-100E fully automated electron densitometer for printability analysis.
Preferably, the step (2) adopts RENISHAW-AM400 laser selective melting rapid forming equipment to perform selective laser melting, and three variable parameters of line spacing, exposure time and laser power are selected as small parameter range printing test parameters to perform experiments to prepare samples.
Preferably, in the step (3), the 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 prealloyed powder of CuAlNi high-temperature shape memory alloy with expected components through rotary electrode atomization; performing a small-range parameter pre-experiment of selective laser melting on powder of the high-temperature shape memory alloy to obtain the printability of the high-temperature shape memory alloy with a small parameter range;
Finite element analysis is carried out on different technological parameters in a large parameter range, and a simulation result of the size of a molten pool is obtained; correcting the simulation result and calculating the printability boundary conditions according to the actual size of the molten pool to obtain a printability 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 assisting in testing the phase transition temperature and the shape memory effect.
The process design optimization method realizes the rapid and efficient process optimization of the 4D printing preparation of the CuAlNi high-temperature shape memory alloy with high phase transition temperature and excellent shape memory performance.
2. Compared with NiTi alloy, the Cu-based shape memory alloy has higher phase transition temperature and machinability, and 4D printing manufacture of the Cu-based shape memory alloy by selective laser melting is expected to solve the problem of high brittleness. The traditional process optimization mode of selective laser melting has a series of problems of high cost, low efficiency and the like because the traditional process optimization mode is changed into component optimization in 4D printing manufacturing. The prealloying powder manufacturing cost is high, only alloy powder with a single component can be produced by a single furnace, and meanwhile, the powder yield is not high, so that 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 in density caused by extreme process parameter combination of the same energy density is not convinced, and scientific and reasonable analysis of process optimization can be realized only by evaluating shape memory performance, which is a necessary index required by the use of the shape memory alloy. According to the invention, through a process design method based on combination of finite element analysis and reality, an optimal process optimization parameter interval is scientifically, rapidly and efficiently determined, and then phase transition temperature and shape memory effect test are assisted, so that process optimization of 4D printing preparation of CuAlNi high-temperature shape memory alloy with a large parameter range is successfully realized, and the method has important significance in solving the problems of high process optimization cost and low efficiency development limit 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 that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 shows 4D printing of shaped raw powders (a and b) with shaped sample (c);
FIG. 2 is the printability of a small parameter range CuAlNi alloy;
FIG. 3 shows the relationship between the density and the laser energy density of Cu-13.2Al-3.5Ni manufactured by 4D printing in a small parameter area and the 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:
(1) Preparing prealloyed powder of the CuAlNi high-temperature shape memory alloy;
(2) Performing selective laser melting block molding of a small parameter range on the prealloyed powder obtained in the step (1), and analyzing the size and printability of a molten pool;
(3) Obtaining a theoretical result of the shape and the size of the molten pool under the combination of different process parameters in a large range through finite element analysis;
(4) Optimizing and calculating a finite element simulation result based on the actual bath size to obtain a theoretical printable performance distribution diagram of the high-temperature shape memory alloy with a large parameter range and an optimal technological parameter combination interval;
(5) And aiming at the printability prediction result in a large parameter range, performing printability verification and phase transition temperature and shape memory effect test in an optimized process parameter interval, and realizing process optimization of 4D printing preparation based on the CuAlNi high-temperature shape memory alloy.
In the invention, the prealloyed powder of the CuAlNi high-temperature shape memory alloy in the step (1) comprises the following components in percentage by mass: al: ni=80 to 90:10 to 14:2 to 4; preferably 82 to 88:11 to 13.2:3.5; further preferably 83.3:12:3.5; more preferably 83.3:13.2:3.5.
In the present invention, step (1) prepares prealloyed powder of the CuAlNi high temperature shape memory alloy by rotary electrode atomization.
In the invention, the step (2) adopts a ZEISS AX10 optical microscope and an ST-100E fully-automatic electron densitometer for printability analysis.
In the invention, the step (2) adopts RENISHAW-AM400 laser selective melting rapid forming equipment to carry out selective laser melting, and three variable parameters of line spacing, exposure time and laser power are selected as small parameter range printing test parameters to carry out experiments to prepare samples.
In the present invention, the step (3) uses Abaqus 6.14 for finite element analysis.
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 rotary electrode to obtain 83.3Cu-13.2Al-3.5Ni high-temperature shape memory alloy prealloyed powder; then carrying out selective laser melting block molding on the original powder, and carrying out a 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; finite element analysis is carried out on different technological parameters in a large parameter range, and a simulation result of the size of a molten pool is obtained; correcting the simulation result and calculating the printability boundary conditions according to the actual size of the molten pool to obtain a printability 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 assisting in testing the phase transition temperature and the shape memory effect.
1. Selective laser melting
And collecting the mixed powder in a powder cylinder, cleaning, sand blasting, removing a surface oxide layer, and then installing the substrate, and finally completing replacement and installation of the scraper. The air extractor is opened, argon is filled for protection, so that the oxygen content in the equipment is ensured to be below 100ppm, and the Cu substrate is preheated to 170 ℃. The method comprises the steps of using QuantAM software to complete the establishment of 5 x 5mm 3 cube models and the setting of process parameters, importing model data into equipment, and automatically starting sample manufacture by the equipment system after the equipment system is ready for preparation. In the experiment, three variable parameters of laser line spacing, exposure time and laser power are selected as orthogonal test factors, and an experiment is performed to prepare a sample.
2. Density analysis
And (3) placing the sample subjected to linear cutting into absolute ethyl alcohol, cleaning to remove impurities adhered to the surface, drying, placing the sample on a measuring table, weighing, pressing a key to record data after the indication is stable, placing the sample into a hanging basket in a water tank, weighing, pressing a key to directly obtain a result after the indication is stable, and recording the data. At least three measurements are guaranteed per sample, and an average is taken to reduce errors.
3. Printability analysis
Printable testing is divided into three aspects: forming quality analysis, defect analysis and single melt channel analysis;
The forming quality is directly carried out in the printing process, and the forming quality problems such as warping, overheating and the like in the layer-by-layer manufacturing process of the samples with different process parameters are analyzed;
The defect analysis uses a ZEISS AX10 optical microscope to analyze the surface porosity and the pore morphology of the polished sample, and classifies and judges the printing defects;
in single-channel analysis, if the appearance of a molten pool is clearly visible after the sample is corroded, information collection such as the penetration width of the single-channel molten pool can be directly carried out through a final printing layer formed by the block; if the appearance of the molten pool cannot be judged, additional single-melt-channel printing tests are required to be directly carried out, and the melting depths and the melting widths of different process parameters are counted.
4. Finite element analysis
Finite element analysis simulation characterization of single melt channel melt pool size parameters during printing of different process parameters was performed using Abaqus 6.14 software. The simulation precision and efficiency are comprehensively considered, the non-uniform model grids are divided, a two-dimensional thermal analysis unit DC2D4/DC2D3 is used, a Gauss surface heat source model is selected through temperature field calculation, and radiation heat exchange and convection heat exchange are considered.
5. Simulated printability calculation
Based on the size information of the molten pool in a large parameter range, the printability prediction of the CuAlNi shape memory alloy is carried out, and the defect boundary conditions are as follows:
Unfused:
A key hole:
spheroidizing:
wherein D is the depth of the molten pool, W is the width of the molten pool, t is the layer thickness, and L is the length of the molten pool.
Sixth, verification of process design optimization
Comprising two aspects: phase transition temperature test and shape memory recovery test
The phase transition temperature test uses an STA449f3 comprehensive thermal analyzer to characterize the endothermic and exothermic behavior of a sample during slow temperature rise and drop. And (3) placing a test sample with the size of 1.5 x 1.5mm 3 into a special crucible of an instrument for testing, wherein the test atmosphere is an argon atmosphere, and the temperature of the sample is slowly increased from 100 ℃ to 700 ℃ and then reduced to 100 ℃, and the heating rate and the cooling rate are 10 ℃/min.
The shape memory recovery rate test uses a force test microcomputer to control an electronic universal tester LD26.105 to carry out loading and unloading test on a tensile sample, and then the recoverable strain after high-temperature recovery is measured. The tensile test is according to ASTM E8/E8M-13 StandardTestMethods for Tension Testing of METALLIC MATERIALS, the tensile and unloading rates are all 0.375mm/min; the heating temperature is 50 ℃ above the martensite reverse phase transition finishing temperature.
7. Analysis of experimental results
FIG. 1 shows the effect of forming a 83.3Cu-13.2Al-3.5Ni high temperature shape memory alloy powder with selective laser melting; the powder manufactured by the rotary electrode atomization has good sphericity, and the surface scanning result shows that the elements of the powder are uniformly distributed and accord with the powder standard 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 warpage is serious in the printing process, and the sample forming is seriously affected; the sample with high energy density is wholly overheated in the printing process, and the forming deviation from the design shape is caused by the collapse of a molten pool, so that the forming precision is seriously influenced; of the 45 samples, only 5 samples with good apparent molding were obtained.
FIG. 2 is a graph of printability of a small parameter range of an established 83.3Cu-13.2Al-3.5Ni high temperature shape memory alloy. It can be seen that the sample is severely warped at a high scanning speed, and is difficult to mold; under the conditions of low scanning speed and high power, a keyhole phenomenon appears, and the printing quality is difficult to ensure; the molding is good only in a combination interval of a certain power and a scanning speed. Further analysis of the combined density energy density curve shows that it is difficult to fully react the printability of the sample only by energy density, and the optimal process parameters are partial intervals of different process parameter combinations, and the forming has higher quality in the intervals.
As can be seen from fig. 3, the density of the sample tends to increase and decrease after the energy density increases, and the sample can be printed at a high density in a certain energy density range. However, in this interval, the density is reduced even when the extreme parameter combination is used, and it is not enough to use the energy density as an index for optimizing the process parameters. At low energy densities, the main reason for the decrease in density is lack of fusion; the decrease in sample density at high energy density is due to the keyhole phenomenon, and the gas in the molten pool is difficult to discharge due to the excessively high energy density, so that pores are generated.
The traditional process optimization method based on density and laser energy density is low in efficiency and is not convincing for low density caused by extreme process parameter combination of the same energy density. The method is based on the combination of finite element analysis and actual process design, the printing result of the shape memory alloy in a small parameter range is used for guiding the finite element analysis, the printability prediction of the shape memory alloy in a large parameter range is realized, and the optimal process parameter interval is determined. And the phase transition temperature and shape memory effect test are used as auxiliary materials, 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 in solving the problems of high process optimization cost and low efficiency in the 4D printing field.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (3)
1. The method for optimizing the 4D printing process of the CuAlNi memory alloy is characterized by comprising the following steps of:
(1) Preparing prealloyed powder of the CuAlNi high-temperature shape memory alloy; the prealloyed powder of the CuAlNi high-temperature shape memory alloy comprises the following components in parts by mass: al: ni=80 to 90:10 to 14:2 to 4;
(2) Performing selective laser melting block molding of a small parameter range on the prealloyed powder obtained in the step (1), and analyzing the size and printability of a molten pool; carrying out printability analysis by adopting ZEISSAX optical microscope and ST-100E full-automatic electron densitometer; performing selective laser melting by adopting RENISHAW-AM400 laser selective melting rapid forming equipment, selecting three variable parameters of line spacing, exposure time and laser power as small parameter range printing test parameters, and performing experiments to prepare samples;
(3) Obtaining a theoretical result of the shape and the size of the molten pool under the combination of different process parameters in a large range through finite element analysis;
(4) Optimizing and calculating a finite element simulation result based on the actual bath size to obtain a theoretical printable performance distribution diagram of the high-temperature shape memory alloy with a large parameter range and an optimal technological parameter combination interval;
(5) And aiming at the printability prediction result in a large parameter range, performing printability verification and phase transition temperature and shape memory effect test in an optimized process parameter interval, and realizing process optimization of 4D printing preparation based on the CuAlNi high-temperature shape memory alloy.
2. The method for optimizing the 4D printing process of the CuAlNi memory alloy, according to claim 1, is characterized in that: and (1) preparing prealloyed powder of the CuAlNi high-temperature shape memory alloy through rotary electrode atomization.
3. The method for optimizing the 4D printing process of the CuAlNi memory alloy, according to claim 1, is characterized in that: the finite element analysis was performed using abaqus6.14 in step (3).
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 CN114535600A (en) | 2022-05-27 |
| CN114535600B true 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 (10)
| 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 |
| 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 |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR3103102B1 (en) * | 2019-11-18 | 2024-03-29 | 3D Medlab | Process for producing a 4D medical device and 4D medical device |
-
2022
- 2022-01-11 CN CN202210024668.4A patent/CN114535600B/en active Active
Patent Citations (10)
| 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 |
| 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 (2)
| Title |
|---|
| 周馨我.《功能材料学》.北京理工大学出版社,2002,第364-367页. * |
| 谢佩军.《3D打印技术及应用》.东华大学出版社,2020,第139-142页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114535600A (en) | 2022-05-27 |
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 | |
| CN108555296A (en) | A kind of increasing material manufacturing method of K465 alloy powders | |
| CN105033255A (en) | Method for directly obtaining martensite die steel through laser 3D printing technology | |
| CN105973664B (en) | Solidify sample high throughput preparation method | |
| He et al. | 3D thermal finite element analysis of the SLM 316L parts with microstructural correlations | |
| Hofmeister et al. | Single crystal casting with fluidized carbon bed cooling: a process innovation for quality improvement and cost reduction | |
| CN107586942B (en) | A kind of design method of the steel-casting heat treatment process based on multiple regression analysis | |
| CN114535600B (en) | CuAlNi memory alloy 4D printing process optimization method | |
| Malik et al. | Parametric appraisal of collapsibility and core shrinkage of phenol binded unbaked casting moulds using Taguchi-Sunflower optimization algorithm | |
| Yang et al. | Microstructure evolution and mechanical properties of H13 steel produced by Selective Electron Beam Melting | |
| Jia et al. | Effect of process parameters on mechanical properties of Inconel718 superalloy fabricated by directional energy deposition | |
| 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 | |
| Elliott | Directional solidification of large cross-section nickel-base superalloy castings via liquid-metal cooling | |
| CN116422900A (en) | Laser selective melting process optimization method based on molten pool lap joint model | |
| Guo et al. | Mo-Si-B Alloy Formed by Optional Laser Melting Process | |
| Peng et al. | Data-driven investigation of microstructure and surface integrity in additively manufactured multi-principal-element alloys | |
| Chen et al. | Effect of forming angle on the microstructure and properties of GH3536 nickel-based superalloy formed by SLM | |
| Abbasi et al. | On the substructure development and continuous recrystallization in the course of selective laser melting of 316L stainless steel | |
| Petrus et al. | The Importance of TDA Thermal Analysis in an Automated Metallurgical Process | |
| CN117230336B (en) | Method for preparing high-entropy alloy | |
| US20230234132A1 (en) | Simulation system for selecting an alloy, and a production process for a workpiece to be produced having amorphous properties | |
| Dezfoli et al. | Investigation into microstructure and element segregation of Inconel 713LC during SLM processing using modified cellular automaton model | |
| Liu et al. | Effect of Substitutional Solid Solution Plus Double Ageing Treatment on the Microstructure of the XY Surface of Inconel 718 Alloy Fabricated with Selective Laser Melting (SLM). | |
| Castillo et al. | Effect of Long-Term Elevated Temperatures on Mechanical Properties of AlSi10Mg |
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 |