CN111833972A - Performance simulation-based aluminum alloy composition optimization method and device for wire - Google Patents
Performance simulation-based aluminum alloy composition optimization method and device for wire Download PDFInfo
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- 229910052804 chromium Inorganic materials 0.000 claims description 3
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- 229910052712 strontium Inorganic materials 0.000 claims description 3
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Abstract
The invention relates to the technical field of aluminum alloy, in particular to a method and a device for optimizing components of aluminum alloy for a wire based on performance simulation, wherein the method comprises the following steps: collecting alloy element parameter data, wherein the element parameter data comprise alloy element types, content variation range and variation increment of each alloy element, and all aluminum alloy components; performing performance simulation on the element parameter data by using a performance simulation model, and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature; and obtaining the optimal aluminum alloy component according to the conductivity and the tensile strength. The method comprehensively considers the interaction among the alloy elements, obtains more accurate and reliable simulation data, can be quickly mastered in a short time for technicians in the field, reasonably optimizes the components of the aluminum alloy for the wire without carrying out a large amount of batching and smelting tests and mathematical calculation, greatly reduces the design period and the cost of the optimized components of the aluminum alloy for the wire, and has stronger practicability and application prospect.
Description
Technical Field
The invention relates to the technical field of aluminum alloy, in particular to a method and a device for optimizing components of aluminum alloy for a wire based on performance simulation.
Background
In recent years, the rapid development of the fields of electric power, communication, rail transit and the like in China effectively drives the rapid development of the matched industry of the wire, and the market demand of the wire is increased day by day at present. The common lead wire materials mainly comprise copper alloy and aluminum alloy, the conductivity of the copper alloy is excellent, but the price of copper is high and is about 3 times of the price of aluminum with the same quality, meanwhile, the copper is used as an important strategic reserve resource in China, the mineral reserve is far lower than the average level in the world, the aluminum mineral reserve resource in China is very rich, the production and processing technology is mature, and the production energy consumption is far lower than that of the copper, so that the vigorous development of the aluminum alloy lead wire by replacing the copper with the aluminum in various fields of lead wire application is a common strategic target and an effort direction of the current country and enterprises. The lead needs to be able to bear a certain load in addition to the electrical conductivity, so for the aluminum alloy lead, not only the better electrical conductivity but also the better mechanical properties are needed, that is, the electrical conductivity and the tensile strength of the aluminum alloy lead are needed to be well matched. There are many factors that affect the conductivity and tensile strength of the aluminum alloy wire, such as alloy composition, processing technology, heat treatment technology, etc., but the most significant and dominant factor among them is the alloy composition of the aluminum alloy wire. Therefore, in order to obtain an aluminum alloy wire having excellent electrical conductivity and tensile strength, a reasonable composition of the aluminum alloy is first designed.
At present, the main method for designing the components of the aluminum alloy is a trial and error method, namely, a series of aluminum alloy test pieces with different alloy component contents are manufactured by smelting in a small furnace, then the conductivity and mechanical property are tested, and then the best aluminum alloy component is selected by comparative analysis. However, this optimization method is not only material-consuming, but also time-consuming and labor-consuming, and is obviously not an economical and efficient method. Nowadays, with the development of computer simulation technology, simulation calculation provides possibility for the optimization of the aluminum alloy composition for the wire, however, through search, the reports on the optimization method of the aluminum alloy composition for the wire based on the simulation calculation are few at present, through search, the invention patent with publication number CN104462798A is more relevant to the optimization of the aluminum alloy composition for the wire, the patent relates to a prediction method of the resistance of the aluminum alloy wire, a calculation model between the resistance of the aluminum alloy wire and the content of alloy elements is provided, but the patent does not consider the prediction method of the tensile strength of the aluminum alloy, so that a certain deficiency still exists in the efficient optimization of the aluminum alloy composition for the wire, and therefore, it is necessary to research and develop the optimization of the aluminum alloy composition considering both the conductivity and the tensile strength of the wire.
Disclosure of Invention
Therefore, the invention provides a performance simulation-based method and device for optimizing the components of the aluminum alloy for the lead, which take the conductivity and the tensile strength of the aluminum alloy at a set temperature as core indexes of the aluminum alloy lead, can efficiently and quickly obtain the optimal component combination of the aluminum alloy through performance simulation, greatly reduces the design period and the cost of the aluminum alloy lead, and has a strong application prospect.
According to the design scheme provided by the invention, the performance simulation-based method for optimizing the components of the aluminum alloy for the lead comprises the following steps:
collecting alloy element parameter data, wherein the element parameter data comprise alloy element types, content variation range and variation increment of each alloy element, and all aluminum alloy components;
performing performance simulation on the element parameter data by using a performance simulation model, and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature;
and obtaining the optimal aluminum alloy component according to the conductivity and the tensile strength.
Furthermore, in the invention, the alloy element is one or more of Mg, Si, Zn, Li, Zr, B, Fe, Cu, Sr, La, Ce, Ca, V, Mo, Cr, Ni, Co, Ti, Pb, Bi, Sc, Mn and Sn.
Further, in the present invention, the content of the alloying element is expressed by mass%.
Further, in the invention, the set temperature is set according to the practical application environment of the lead.
Further, in the invention, the conductivity and tensile strength of each group of aluminum alloy are optimized into characteristic index values by adopting weighting calculation, and the optimal aluminum alloy component is obtained by obtaining the maximum value of the characteristic index values.
Further, in the present invention, the weighting calculation formula is expressed as: zb ═ X1×Ec×10-6+X2×bWherein Zb is a weighted characteristic index value, Ec is the electrical conductivity of the aluminum alloy at a set temperature,bis the tensile strength, X, of an aluminum alloy at a set temperature1Is a conductivity weighting coefficient, X, of an aluminum alloy2Is the weighting coefficient of the tensile strength of the aluminum alloy.
Further, in the present invention, the weighting coefficient X1And X2The method is set according to the requirements of the application on the weight bias degree of the conductivity and the tensile strength of the aluminum alloy.
Further, the invention also provides a performance simulation-based aluminum alloy composition optimization device for a lead, which comprises: an element collection module, a performance simulation module and an optimal output module, wherein,
the element collection module is used for collecting alloy element parameter data, and the element parameter data comprises alloy element types, the content variation range and the variation increment of each alloy element and all aluminum alloy components;
the performance simulation module is used for performing performance simulation on the element parameter data by using the performance simulation model and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature;
and the optimal output module is used for acquiring the optimal aluminum alloy component according to the conductivity and the tensile strength.
The invention has the beneficial effects that:
by the aid of composition combination and performance simulation, all alloy elements possibly related to the aluminum alloy for the lead can be optimally designed; meanwhile, important indexes of the conductivity and the tensile strength of the aluminum alloy for the lead are considered, and the weight bias degree of the indexes can be set according to the actual needs of the aluminum alloy to be researched, so that the most reasonable optimization design is carried out; in addition, the interaction among all alloy elements is comprehensively considered by the aluminum alloy performance calculation model for carrying out simulation calculation on the conductivity and the tensile strength of the aluminum alloy, so that the obtained simulation data is more accurate and reliable; in addition, the method is simple and easy to implement, and can be quickly mastered in a short time for technicians in the field, so that the technicians can reasonably optimize the components of the aluminum alloy for the lead without performing a large amount of batching and smelting tests and mathematical calculations, the period and the cost of the optimal design of the components of the aluminum alloy for the lead are greatly reduced, and the method has strong practicability and application prospects.
Description of the drawings:
FIG. 1 is a flow chart of optimization in the example;
FIG. 2 is a schematic diagram of the apparatus in the example.
The specific implementation mode is as follows:
in order to make the objects, technical solutions and advantages of the present invention clearer and more obvious, the present invention is further described in detail below with reference to the accompanying drawings and technical solutions.
In order to overcome the defects and shortcomings of time consuming, labor consuming, material consuming, low efficiency and the like of aluminum alloy component design in the prior art, and enable a person skilled in the art to reasonably optimize the components of the aluminum alloy for the lead in an efficient, rapid and relatively economic manner, in the embodiment of the invention, referring to fig. 1, a method for optimizing the components of the aluminum alloy for the lead based on performance simulation is provided, and comprises the following steps:
s101, collecting alloy element parameter data, wherein the element parameter data comprise alloy element types, the content variation range and the variation increment of each alloy element and all aluminum alloy components;
s102, performing performance simulation on the element parameter data by using a performance simulation model, and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature;
and S103, obtaining the optimal aluminum alloy component according to the electric conductivity and the tensile strength.
Through composition combination and performance simulation, all alloy elements possibly related to the aluminum alloy for the lead can be optimally designed; meanwhile, important indexes of the conductivity and the tensile strength of the aluminum alloy for the lead are considered, the weight bias degree of the indexes can be set according to the actual needs of the aluminum alloy to be researched, the most reasonable optimization design is further carried out, the efficiency of the aluminum alloy composition design is greatly improved, and the generation period and the cost of the aluminum alloy lead are reduced.
Further, in the embodiment of the present invention, the alloy element is one or more of Mg, Si, Zn, Li, Zr, B, Fe, Cu, Sr, La, Ce, Ca, V, Mo, Cr, Ni, Co, Ti, Pb, Bi, Sc, Mn, and Sn. According to the practical application situation, several kinds of the alloy elements to be added are selected. Determining a suitable range of variation in the amount of each selected alloying element, determining the incremental change in the amount of each alloying element, and listing all aluminum alloy compositions.
The mass fraction refers to the percentage of the mass of a certain component in a certain substance to the total mass of the sample, and further, in the embodiment of the invention, the content of the alloy elements is expressed by mass percentage so as to obtain more accurate and reasonable aluminum alloy component data.
The performance simulation model in the embodiment of the invention can be realized by commercial simulation software, for example, the software name Jmatpro/version number of the imitation science and technology agency in guangzhou is 7.0 to realize performance simulation, and the software realization principle is introduced as follows: firstly, calculating the phase composition condition of the material at different temperatures; the calculation expression is as follows:
wherein G is the Gibbs free energy of the material system; x is the number ofiIs the content of i phase in the material system;
gibbs free energy for i single phase; r is an ideal gaseous constant; t is the temperature; x is the number ofjIs the content of phase j; omegaij vIs the interaction parameter of the i and j phases; v is the number of system phases; the first term on the right of the equal sign is the sum of free energy of each pure phase in the system, the second term is Gibbs free energy caused by ideal mixed entropy of the system, and the third term is free energy caused by interaction of each phase in the system. Then, calculating the related performance P of each phase at different temperatures according to the alloy components of the phase at the temperature; the calculation expression is as follows:
wherein P is the relevant property of a single phase; x is the number ofiIs the content of i element in a single phase; pi 0The correlation property when the element is a pure i element; x is the number ofjIs the content of the j element in a single phase; omegaij vIs the interaction parameter of elements i and j; v is the number of elements of a single phase; the first term on the right of the equal sign is the sum of the correlation performance of each single element in the system, and the second term is the performance variation caused by the interaction of every two elements in the system. Finally, calculating the overall performance of the material by using a mixing law according to the phase composition and the performance of each phase of the material at different temperatures; the calculation expression can be expressed as follows:
in the formula, PtIs a relevant property of the material system; x is the number ofiIs the content of phase i; pi 0Is the correlation property of i single phase; pΩProperty changes due to phase mixing; the first term on the right of the equal sign is the sum of the relevant performances of each pure phase in the system, and the second term is the performance variation caused by the mixing action of each phase.
Furthermore, in the embodiment of the invention, the set temperature is set according to the practical application environment of the lead. The specific temperature of the aluminum alloy in a specific environment such as an as-cast condition can be set based on empirical values or experimental data.
The weights, i.e. the weights taken in the adjustment calculation by the difference in the accuracy of the measured values, are different. The higher the precision, the larger the weight. The "weighting" means "multiplying by a weight" and "multiplying by a coefficient", and the influence of each factor on the precision or the result is analyzed by the weight or the coefficient. Further, in the embodiment of the invention, the conductivity and tensile strength of each group of aluminum alloy are optimized into the characteristic index value by adopting weighting calculation, and the optimal aluminum alloy component is obtained by obtaining the maximum value of the characteristic index value. The aluminum alloy component corresponding to the maximum value is the optimal aluminum alloy component.
Further, in the embodiment of the present invention, the weighted calculation formula is expressed as: zb ═ X1×Ec×10-6+X2×bWherein Zb is a weighted characteristic index value, Ec is the electrical conductivity of the aluminum alloy at a set temperature,bis the tensile strength, X, of an aluminum alloy at a set temperature1Is a conductivity weighting coefficient, X, of an aluminum alloy2Is the weighting coefficient of the tensile strength of the aluminum alloy.
Further, in the embodiment of the present invention, the weighting factor X1And X2The method is set according to the requirements of the application on the weight bias degree of the conductivity and the tensile strength of the aluminum alloy.
Based on the above method, further, an embodiment of the present invention further provides an apparatus for optimizing composition of an aluminum alloy for a wire based on performance simulation, as shown in fig. 2, including: an element collection module 101, a performance simulation module 102, and an optimal output module 103, wherein,
an element collection module 101 for collecting alloy element parameter data including alloy element types, variation ranges and variation increments of each alloy element content, and all aluminum alloy components;
the performance simulation module 102 is used for performing performance simulation on the element parameter data by using a performance simulation model, and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature;
and the optimal output module 103 is used for acquiring the optimal aluminum alloy component according to the electrical conductivity and the tensile strength.
As described above, the optimal output module 103 includes a weight calculation sub-module and a data output sub-module, wherein,
the weighting calculation submodule is used for optimizing the conductivity and the tensile strength of each group of aluminum alloy into characteristic index values through weighting calculation;
and the data output submodule is used for acquiring the optimal aluminum alloy component by acquiring the maximum value of the characteristic index value.
In order to verify the effectiveness of the technical scheme in the embodiment of the invention, the following aluminum alloy elements involved in a certain practical application are exemplified:
according to the practical application situation, selecting several types of alloy elements to be added: two alloying elements, Mg and Si, are selected. A suitable range of variation in the content is determined for each selected alloying element: determining the content variation ranges of Mg and Si to be 0.2-0.3% and 0.3-0.4% respectively.
Determining the change increment of each alloy element content, listing all aluminum alloy components and naming each group of aluminum alloy to edit into a table file: determining that the content change increment of the Alloy elements Mg and Si is 0.1%, and sequentially naming the aluminum alloys in each group as Alloy 01-Alloy 04, wherein the aluminum alloys in each group are shown in Table 1.
TABLE 1 determination of the composition of the aluminum alloys
| Aluminum alloy composition | Mg | Si | Al |
| Alloy01 | 0.2 | 0.3 | Balance of |
| Alloy02 | 0.2 | 0.4 | Balance of |
| Alloy03 | 0.3 | 0.3 | Balance of |
| Alloy04 | 0.3 | 0.4 | Balance of |
Solving and calculating: the aluminum Alloy components in the table 1 are led into an integrated aluminum Alloy performance simulation calculation model, and the electric conductivity and the tensile strength of the aluminum alloys Alloy 01-Alloy 04 are solved and calculated. The electrical conductivity and tensile strength at a specific temperature (here, room temperature 20 ℃) for each group of aluminum alloys were extracted: the calculated electrical conductivity and tensile strength of the aluminum alloys of Alloy groups 01-04 are shown in table 2.
TABLE 2 conductivity and tensile Strength of the aluminum alloys of the respective groups
| Aluminum alloy composition | Conductivity/omega-1·m-1 | Tensile strength/MPa |
| Alloy01 | 30.031 | 117.53 |
| Alloy02 | 30.011 | 116.24 |
| Alloy03 | 29.715 | 120.66 |
| Alloy04 | 29.699 | 119.23 |
And (3) according to a weighting calculation rule shown by a weighting calculation formula, converting the conductivity and the tensile strength of each group of aluminum alloy into an index value: in the present example, only the conductivity of the aluminum Alloy is considered, the weighting coefficients X1 and X2 are selected to be 1 and 0, respectively, and the characteristic index values of the aluminum alloys 01 to 04 are shown in table 3.
TABLE 3 characteristic index values for the respective groups of aluminum alloys
| Aluminum alloy composition | Index value |
| Alloy01 | 30.031 |
| Alloy02 | 30.011 |
| Alloy03 | 29.715 |
| Alloy04 | 29.699 |
Determining the optimal aluminum alloy component: and comparing the characteristic index values of the aluminum alloys 01-04, and determining the aluminum Alloy group Alloy01 corresponding to the characteristic index value as the maximum value as the optimal aluminum Alloy component.
Based on the above contents, the interaction among all alloy elements is comprehensively considered in relation to the aluminum alloy performance calculation model for carrying out simulation calculation on the conductivity and tensile strength of the aluminum alloy, so that the method has strong theoretical support, and the calculation result is accurate, reliable, convenient, fast and efficient. For technicians in the field, the method can be quickly mastered in a short time, so that the technicians can reasonably optimize the components of the aluminum alloy for the lead without performing a large amount of batch smelting tests and mathematical calculations, and the period and the cost of the optimal design of the components of the aluminum alloy for the lead are greatly reduced.
Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present invention. It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the system and the apparatus described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. In all examples shown and described herein, any particular value should be construed as merely exemplary, and not as a limitation, and thus other examples of example embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. The term "substantially" as used herein should be understood to be within the normal tolerances in the art, e.g., within two standard deviations of the mean, unless the context specifically states or clearly indicates otherwise. "substantially" can be understood to be within a set point of 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01%. All numbers provided herein are to be modified by the term "substantially" unless an otherwise clear context.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A performance simulation-based method for optimizing the components of an aluminum alloy for a wire is characterized by comprising the following steps:
A) collecting alloy element parameter data, wherein the element parameter data comprise alloy element types, content variation range and variation increment of each alloy element, and all aluminum alloy components;
B) performing performance simulation on the element parameter data by using a performance simulation model, and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature;
C) and obtaining the optimal aluminum alloy component according to the conductivity and the tensile strength.
2. The method for optimizing the composition of the aluminum alloy for the lead based on the performance simulation as recited in claim 1, wherein the alloying elements in A) are one or more of Mg, Si, Zn, Li, Zr, B, Fe, Cu, Sr, La, Ce, Ca, V, Mo, Cr, Ni, Co, Ti, Pb, Bi, Sc, Mn and Sn.
3. The method for optimizing the composition of the aluminum alloy for the conductor based on the performance simulation as claimed in claim 1 or 2, wherein the content of the alloying element in A) is expressed by mass percent.
4. The method for optimizing composition of aluminum alloy for lead wire based on performance simulation as claimed in claim 1, wherein in B), the set temperature is set according to the actual application environment of the lead wire.
5. The performance simulation-based method for optimizing the composition of aluminum alloy for leads according to claim 1, wherein in C), the conductivity and tensile strength of each group of aluminum alloy are optimized to characteristic index values by weighting calculation, and the optimal aluminum alloy component is obtained by obtaining the maximum value of the characteristic index values.
6. The method for optimizing the composition of the aluminum alloy for the lead based on the performance simulation as recited in claim 5, wherein the weighted calculation formula is expressed as: zb ═ X1×Ec×10-6+X2×bWherein Zb is a weighted characteristic index value, Ec is the electrical conductivity of the aluminum alloy at a set temperature,bis the tensile strength, X, of an aluminum alloy at a set temperature1Is a conductivity weighting coefficient, X, of an aluminum alloy2Is the weighting coefficient of the tensile strength of the aluminum alloy.
7. The method of claim 6, wherein the weighting factor X is a weight factor of the aluminum alloy composition for conductive wire1And X2The method is set according to the requirements of the application on the weight bias degree of the conductivity and the tensile strength of the aluminum alloy.
8. An aluminum alloy composition optimizing device for a wire based on performance simulation, comprising: an element collection module, a performance simulation module and an optimal output module, wherein,
the element collection module is used for collecting alloy element parameter data, and the element parameter data comprises alloy element types, the content variation range and the variation increment of each alloy element and all aluminum alloy components;
the performance simulation module is used for performing performance simulation on the element parameter data by using the performance simulation model and extracting the conductivity and tensile strength of each group of aluminum alloy at a set temperature;
and the optimal output module is used for acquiring the optimal aluminum alloy component according to the conductivity and the tensile strength.
9. The apparatus for optimizing composition of aluminum alloy for lead wire based on performance simulation of claim 8, wherein the optimal output module comprises a weight calculation sub-module and a data output sub-module, wherein,
the weighting calculation submodule is used for optimizing the conductivity and the tensile strength of each group of aluminum alloy into characteristic index values through weighting calculation;
and the data output submodule is used for acquiring the optimal aluminum alloy component by acquiring the maximum value of the characteristic index value.
10. The performance simulation-based aluminum alloy composition optimization device for the lead according to claim 9, wherein in the weight calculation submodule, the weight calculation formula is represented as: zb ═ X1×Ec×10-6+X2×bWherein Zb is a weighted characteristic index value, Ec is the electrical conductivity of the aluminum alloy at a set temperature,bis the tensile strength, X, of an aluminum alloy at a set temperature1Is a conductivity weighting coefficient, X, of an aluminum alloy2Is the weighting coefficient of the tensile strength of the aluminum alloy.
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| CN114121185A (en) * | 2021-11-16 | 2022-03-01 | 湖南航天天麓新材料检测有限责任公司 | Novel method for improving performance of aluminum alloy |
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| CN111833972B (en) | 2024-01-26 |
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