CN117054236A - Method for predicting tensile strength of cast aluminum part body - Google Patents
Method for predicting tensile strength of cast aluminum part body Download PDFInfo
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- CN117054236A CN117054236A CN202311109026.5A CN202311109026A CN117054236A CN 117054236 A CN117054236 A CN 117054236A CN 202311109026 A CN202311109026 A CN 202311109026A CN 117054236 A CN117054236 A CN 117054236A
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- 238000000034 method Methods 0.000 title claims abstract description 26
- AZDRQVAHHNSJOQ-UHFFFAOYSA-N alumane Chemical group [AlH3] AZDRQVAHHNSJOQ-UHFFFAOYSA-N 0.000 title claims abstract description 25
- 239000000463 material Substances 0.000 claims abstract description 58
- 229910052782 aluminium Inorganic materials 0.000 claims abstract description 37
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 claims abstract description 37
- 238000007711 solidification Methods 0.000 claims abstract description 26
- 230000008023 solidification Effects 0.000 claims abstract description 26
- 238000001816 cooling Methods 0.000 claims abstract description 25
- 238000011160 research Methods 0.000 claims abstract description 21
- 238000012360 testing method Methods 0.000 claims abstract description 17
- 238000005070 sampling Methods 0.000 claims abstract description 9
- 238000011156 evaluation Methods 0.000 claims abstract description 7
- 238000012937 correction Methods 0.000 claims abstract description 4
- 238000010998 test method Methods 0.000 claims abstract description 4
- 239000013589 supplement Substances 0.000 claims abstract description 3
- 238000005266 casting Methods 0.000 claims description 12
- 230000007547 defect Effects 0.000 claims description 10
- 210000001787 dendrite Anatomy 0.000 claims description 7
- 229910000838 Al alloy Inorganic materials 0.000 claims description 6
- 238000012986 modification Methods 0.000 claims description 4
- 230000004048 modification Effects 0.000 claims description 4
- 230000008569 process Effects 0.000 claims description 4
- 239000011148 porous material Substances 0.000 claims description 3
- 238000004458 analytical method Methods 0.000 claims description 2
- 238000004088 simulation Methods 0.000 claims description 2
- 239000000126 substance Substances 0.000 claims description 2
- 238000012512 characterization method Methods 0.000 claims 2
- 238000011835 investigation Methods 0.000 claims 1
- 230000008859 change Effects 0.000 abstract description 3
- 230000001419 dependent effect Effects 0.000 abstract description 3
- 229910045601 alloy Inorganic materials 0.000 description 3
- 239000000956 alloy Substances 0.000 description 3
- 230000003068 static effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 229910018125 Al-Si Inorganic materials 0.000 description 1
- 229910018520 Al—Si Inorganic materials 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 239000007769 metal material Substances 0.000 description 1
- 238000004806 packaging method and process Methods 0.000 description 1
- 230000005476 size effect Effects 0.000 description 1
- 238000009864 tensile test Methods 0.000 description 1
- 238000004227 thermal cracking Methods 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/08—Investigating strength properties of solid materials by application of mechanical stress by applying steady tensile or compressive forces
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/02—Devices for withdrawing samples
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N1/00—Sampling; Preparing specimens for investigation
- G01N1/02—Devices for withdrawing samples
- G01N1/04—Devices for withdrawing samples in the solid state, e.g. by cutting
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N3/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N3/02—Details
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2203/00—Investigating strength properties of solid materials by application of mechanical stress
- G01N2203/0014—Type of force applied
- G01N2203/0016—Tensile or compressive
- G01N2203/0017—Tensile
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- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
Abstract
The invention relates to a method for predicting tensile strength of a cast aluminum part body, which is characterized in that material tissue characteristic information is extracted, and the tensile property of a material standard sample and the relation between the material standard sample and tissue characteristics of different positions of the part body are used as corrections to establish a cast aluminum part body tensile strength prediction model, so that the supplement of an evaluation method is provided for a traditional sampling test method; the method provided by the invention has ideal predicted results, most of the predicted results are slightly lower than the test results, and a certain safety margin is reserved. The parameter lambda and omega values in the prediction model are determined by material properties, and are related to the research position of the part body, and the model establishment takes the solidification cooling rate of cast aluminum as a dependent variable to determine parameter change conditions, so that the model has universality.
Description
Technical Field
The invention belongs to the technical field of mechanical property evaluation of a part body, in particular relates to a method for predicting the tensile strength of a cast aluminum part body, and particularly relates to a method for predicting the tensile strength of the cast aluminum part body based on a material structure and tensile property.
Background
Cast aluminum alloys are widely used for automotive parts by virtue of their low density, high specific strength and good corrosion resistance. The use of cast aluminum parts is beneficial to improving the working efficiency and the fuel economy of the vehicle engine. As one of the most important series in casting aluminum alloy, the cast Al-Si series alloy casting accounts for nearly 90% of the aluminum alloy casting, and the alloy has good mechanical property and casting performance, no thermal cracking tendency, small line shrinkage and high air tightness, and is commonly used for complex structural components such as transmission cases, cylinder covers and the like. However, with the continuous expansion of the application field of cast aluminum materials, the requirements on the mechanical properties of the cast aluminum materials are also higher and higher. In fact, the introduction of defects, shrinkage porosity, impurities and the like during the casting process will significantly reduce the mechanical properties of the cast aluminum material, thereby affecting the static strength and service life of the cast aluminum component. The key to improving the mechanical properties of cast aluminum materials is to improve the microstructure thereof, so that the establishment of the relationship between the microstructure and the macroscopic mechanical properties is of great importance.
Previous studies have accumulated many empirical formulas for evaluating mechanical properties of materials through microstructure characteristics of cast aluminum materials, but these formulas only extract a single information of the material structure and do not establish a coupling relationship between a plurality of structure information. In addition, the mechanical properties of the cast aluminum part are greatly influenced by external factors such as self structures, technological processes and the like, and compared with the mapping relation between the microstructure of the material and the mechanical properties, the mechanical properties of the cast aluminum part body are more difficult to evaluate and more interference factors are caused only by the tissue characteristics. To date, mechanical property evaluation of a cast aluminum part body is mainly to directly perform mechanical property test through body sampling, but the test task is complex and the workload is large; and for the position where the standard tensile sample cannot be obtained, the test is also required to be carried out by designing a non-standard small sample, so that the influence of the size effect of the material is inevitably required to be overlapped and considered, and the ambiguity of the evaluation model is amplified.
The traditional method for evaluating the static strength of the component is to sample and test mechanical properties at different positions of the component, and small samples are required to be tested at positions where standard tensile samples are difficult to take out, so that the workload is high and the evaluation efficiency is low.
Disclosure of Invention
The invention provides a method for predicting tensile strength of a cast aluminum part body, which aims to carry out overall evaluation on mechanical properties of the part body with a complex structure, and particularly aims at key positions where standard tensile samples are difficult to obtain, and the tissue characteristics and tensile properties of materials are packaged in a part body tensile strength prediction model, so that information distortion caused by multiple iterations of tissue information is avoided, and the problem of cooperative restriction of multiple elements on static strength of the cast aluminum part is solved.
In order to solve the technical problems, the invention provides the following components.
The beneficial effects are that: on the basis of obtaining the tensile property of the cast aluminum material, the invention provides a method for rapidly identifying and predicting the tensile strength of the cast aluminum part body by representing the microstructure of different positions of the cast aluminum material and the cast aluminum part, extracting typical tissue characteristics including porosity, secondary dendrite arm spacing and the like, establishing a cast aluminum part body tensile strength prediction model for packaging multiple elements, and providing supplements for the evaluation method of the traditional sampling test method. The method provided by the invention has ideal predicted results, most of the predicted results are slightly lower than the test results, and a certain safety margin is reserved. The parameter lambda and omega values in the prediction model are determined by material properties, and are related to the research position of the part body, and the model establishment takes the solidification cooling rate of cast aluminum as a dependent variable to determine parameter change conditions, so that the model has universality.
Drawings
FIG. 1 is a graph showing the relationship between the test and simulation results of the cooling rate test and the secondary dendrite arm spacing of the body of an aluminum cast part in a research position
FIG. 2 sigma P and θP- θM exponential function fitting chart
FIG. 3 is a graph of predicted tensile strength versus test values for different study locations of cast aluminum part bodies.
Detailed Description
To make the objects, contents and advantages of the present invention more apparent, the following detailed description of the specific embodiments of the present invention will be given.
The invention provides a method for predicting tensile strength of a cast aluminum part body, which takes ZL702A aluminum alloy castings as examples of research materials, and comprises the following chemical components in percentage by weight: 6.8Si,1.5Cu,0.25Mg,0.1Fe,0.15Mn,0.1Ti, the sum of other elements is less than 0.35, and the balance is Al. The method comprises the following specific steps:
(1) Tensile property test for cast aluminum material standard sample
By controlling different solidification cooling rates under the casting process, the cast aluminum material with different structural characteristics is obtained. Reference is made to GB/T228.1-2010 section 1 of the metallic material tensile test: room temperature test method, standard test sample is taken for the cast aluminum materials with different cooling rates to carry out tensile mechanical property test, and yield strength sigma is obtained 0.2 And tensile strength sigma M And the like.
(2) Cast aluminum material and cast aluminum part tissue characteristic information extraction analysis
1) Characterizing different solidification cooling rates by referring to GB/T13298-2015 metal microstructure inspection method to obtain microstructure of cast aluminum material, and obtaining porosity theta of the material M And secondary dendrite arm spacing SDAS (M) And iso-tissue characteristic information, wherein the porosity is obtained according to the ratio of the defect volume calculated by the equivalent diameter of the defect to the total volume of the sampling area.
2) The actual solidification cooling rate of the research position of the part body is measured by utilizing a thermocouple temperature measuring device, and the solidification process is simulated by combining casting process simulation software (such as ProCAST), so that the solidification cooling rate of the research position of the part body is verified.
3) Sampling the research position of the part body calibrated by the solidification cooling rate in the step 2), and measuring the corresponding porosity theta P Secondary dendrite arm spacing SDAS (P) And the like.
4) The solidification cooling rate of cast aluminum has an important effect on the formation of solidification structure, as shown in fig. 1, the higher the solidification cooling rate, the smaller the secondary dendrite arm spacing of the alloy. Therefore, in predicting the tensile strength of a site of study on the body of a cast aluminum part, the texture characteristics and tensile strength of the cast aluminum material obtained at a solidification cooling rate similar to that site should be selected as the input of the prediction model.
(3) Component body tensile strength prediction model establishment based on material structure and tensile property
The microstructure features mainly considered in the patent are pore defect features including defects, shrinkage porosity, and the like, and SDAS structural features of the cast aluminum alloy.
1) According to the influence relationship of the density on the tensile strength of the material during the forming of the material:
σ L ＝σ C e -λθ (1)
wherein sigma L Sum sigma C Lambda is the material pore modification coefficient, which is a constant when the type of material is determined, and is only related to the material properties, corresponding to the tensile strength of the material in which the defect is actually present and the tensile strength of the ideal dense material, respectively. From the point of view of defect magnification, the cast aluminum material can be used as a relatively dense material, and the cast aluminum part can be used as a material in which defects exist in practice.
2) Based on a Hall-Peltier formula of the grain size and the yield strength of the material, the following relationship exists between the yield strength of the material and SDAS:
wherein sigma 0.2 Indicating the yield strength of the cast aluminum material, which did not show significant due to the tensile behavior of the cast aluminum materialThe yield point, the tensile strength corresponding to 0.2% strain was taken as the yield strength. Description sigma 0.2 Presence with SDASThus, in->The microstructure feature is used as an inverse proportion factor to correct the relation (1); due to->The relation is established with the yield strength, so that the relation formula (1) is corrected by making a positive scale factor between the yield strength and the tensile strength through a correction coefficient omega, and the physical meaning of omega is the ratio of the tensile strength to the yield strength; in summary, the prediction model of the tensile strength of the component body is obtained as follows:
(4) Determination of unknown parameters of predictive model
1) The tensile property of the cast aluminum part is tested by sampling the research position of the cast aluminum part, which is convenient for taking a standard tensile sample, and the tensile strength sigma of the part body is obtained P . Using sigma P 、σ M 、θ M 、SDAS (M) 、θ P And SDAS (P) These 6 known parameter fits determine the values of the unknown parameters λ and ω, as shown in fig. 2.
2) The lambda and omega values of the cast aluminum material at different research positions of the part body corresponding to different solidification cooling rates are obtained, as shown in Table 1. And constructing a prediction model by using the determined lambda and omega values, and predicting the tensile strength of a part research position with a complex structure and a standard tensile sample which cannot be obtained.
TABLE 1 lambda and omega values for cast aluminum materials at different solidification cooling rates
The invention provides a method for predicting the tensile strength of a cast aluminum part body based on material structure and tensile property, which is shown in a comparison chart of tensile strength predicted values and test values of different research positions of the cast aluminum part body by using the method, and can be seen from the comparison result, the predicted result is ideal by using the method provided by the invention, and most of the predicted results are slightly lower than the test result, so that a certain safety margin is reserved. The parameter lambda and omega values in the prediction model are determined by material properties, and are related to the research position of the part body, and the model establishment takes the solidification cooling rate of cast aluminum as a dependent variable to determine parameter change conditions, so that the model has universality.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (5)
1. A method of predicting the tensile strength of a cast aluminum component body, comprising: by extracting material tissue characteristic information, the tensile strength prediction model of the cast aluminum part body is established by taking the tensile property of a material standard sample and the relation between the material standard sample and the tissue characteristics of different positions of the part body as corrections, and the supplement of an evaluation method is provided for a traditional sampling test method; the method specifically comprises the following steps:
s1, obtaining cast aluminum materials with different structural characteristics by controlling different solidification and cooling rates in a casting process; standard samples of cast aluminum materials obtained by different solidification and cooling rates are taken to carry out yield strength sigma 0.2 And tensile strength sigma M Tensile mechanical property test of (2);
s2, carrying out microstructure characterization analysis on cast aluminum materials obtained by different solidification and cooling rates, and extracting the porosity theta of the materials M Secondary dendrite arm spacing SDAS (M) Wherein the porosity is obtained as a ratio of the defect volume calculated as the defect equivalent diameter to the total volume of the sampling region;
s3, simulating a solidification process by using casting process simulation software, and determining the solidification cooling rate of the research position of the part body;
s4, determining the actual solidification cooling rate of the research position of the component body by using a thermocouple temperature measuring device, wherein the actual solidification cooling rate of the research position of the component body is verified with the solidification cooling rate of the research position of the component body obtained by the simulation process in the claim S3;
s5, sampling the research positions of the part body of the solidification cooling rate marked in S3 and S4, and measuring the corresponding porosity theta P Secondary dendrite arm spacing SDAS (P) ；
S6, based on the test result of S1 and the characterization results of S2 and S5, establishing tensile strength sigma 'of the research position of the component body' p The prediction model of (2) is:
wherein ω is a ratio correction factor between the yield strength and the tensile strength of the cast aluminum material, and λ is a material pore modification coefficient related to material properties only;
s7, testing tensile strength sigma of research position of part body P And fitting and determining the lambda value and the omega value in the S6 prediction model, and predicting the tensile strength of a research position which has a complex structure and cannot acquire a standard tensile sample by using the prediction model with the lambda value and the omega value.
2. A method of predicting the tensile strength of a cast aluminum component body as set forth in claim 1, wherein in predicting the tensile strength of a cast aluminum component body at a site of investigation, the texture characteristics and tensile strength of the cast aluminum material obtained at a solidification cooling rate similar to the site should be selected as the input to the S6 prediction model.
3. A method of predicting the tensile strength of a cast aluminum component body as recited in claim 1, wherein the values of λ and ω in the prediction model are determined by material properties, wherein the value of ω is related to the study location of the component body, and wherein the value of ω of the cast aluminum material corresponding to the solidification cooling rate is selected to be substituted into the prediction model in predicting the tensile strength of the cast aluminum component body at different study locations.
4. A method of predicting the tensile strength of a cast aluminum component body as recited in claim 1 in which the casting process simulation software employs ProCAST.
5. The method for predicting the tensile strength of a cast aluminum component body according to claim 1, wherein the research material is a ZL702A aluminum alloy casting, and the mass percentages of the chemical components are as follows: 6.8Si,1.5Cu,0.25Mg,0.1Fe,0.15Mn,0.1Ti, the sum of other elements is less than 0.35, and the balance is Al.
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| CN202311109026.5A CN117054236A (en) | 2023-08-31 | 2023-08-31 | Method for predicting tensile strength of cast aluminum part body |
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| CN202311109026.5A CN117054236A (en) | 2023-08-31 | 2023-08-31 | Method for predicting tensile strength of cast aluminum part body |
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