Method for predicting property of aluminum member

Abstract

This method for predicting a property of an aluminum member comprises: a mechanical property measuring step for measuring a mechanical property after T6 treatment for an unforged first aluminum member and a plurality of forged second aluminum members; a Z-factor calculating step for obtaining a temperature and a strain rate for each forging step by numerical analysis for the second aluminum members during forging, and calculating a Z-factor using the obtained temperature and strain rate; a regression equation deriving step for deriving a regression equation indicating a relationship between the mechanical property and the Z-factor, using a plurality of combinations of the measured value of the mechanical property and the calculated value of the Z factor that correspond through strength; and a mechanical property predicting step for predicting the mechanical property of the third aluminum member after T6 treatment after an arbitrary forging step, using the regression equation.

Description

Method for predicting properties of aluminum components

[0001] This application claims priority to Japanese Patent Application No. 2023-171242, filed on October 2, 2023, the contents of which are incorporated herein by reference.

[0002] In recent years, electric vehicles (EVs) and battery-electric vehicles (BEVs) have inevitably increased the weight of their bodies due to the batteries they carry. However, reducing the weight of the body is essential to improve fuel efficiency, and aluminum is increasingly being used in forged parts such as suspensions that make up the body. For forged parts such as suspensions, aluminum alloys such as JIS 6000 series (Al-Mg-Si series) are often used to enhance strength and corrosion resistance. In order to obtain the required mechanical properties (e.g., 0.2% yield strength, tensile strength, elongation), forged parts made of JIS 6000 series aluminum alloys require a forging process followed by heat treatment processes such as solution treatment and artificial aging.

[0003] Reducing greenhouse gas (GHG) emissions has already become a requirement in the manufacturing and development stages of automobiles and automobile components, and the same trend is emerging in the design stage. During the typical design stage, multiple forging and heat treatment processes are typically performed until a manufacturing process that achieves the desired mechanical properties is identified, which means that energy consumption in each process is also repeated. To reduce GHG emissions during the design stage, it is important to reduce the number of processes required to identify the manufacturing process. Therefore, technology to predict the mechanical properties of aluminum components manufactured through each process is essential. Patent documents 1 to 3 disclose technologies for determining the properties of aluminum alloys before the forging or heat treatment process.

[0004] In Patent Document 1, it is stated that sufficient hardness and strength can be obtained by specifying the length of low-angle grain boundaries together with the alloy composition for hot-forged products of JIS 6000 series aluminum alloys, and a Z factor (Zener-Hollomon parameter) of 1 × 10 is set as a guideline for the forging process to include a predetermined or greater length of low-angle grain boundaries. １１It is expected that processing will be more than / s.

[0005] Patent Document 2 also shows that, with regard to the properties of a hot-forged product of a JIS 6000 series aluminum alloy, when hot forging is performed, the increase in hardness due to subsequent heat treatment can be predicted, which is expressed by a certain Z factor. The Z factor used to predict the increase in hardness is calculated using an arbitrary time-average temperature and time-average strain rate.

[0006] Patent Document 3 discloses that, in order to provide an aluminum alloy forged member that has excellent mechanical properties and that fully ensures the strength and reliability of the entire member, the structure of the forged member can be controlled to subgrains or fine recrystallized grains by specifying the range of the Z factor in forging along with the composition range of the JIS 6000 series aluminum alloy.

[0007] JP 2021-066900 A JP 2021-090998 A JP 2022-161591 A

[0008] In Patent Documents 1 to 3, the Z factor that represents the forging process is calculated from the material temperature and strain rate averaged at the start and end of processing, and does not fully represent the complex temperature and strain rate changes during forging. Patent Document 2 uses time-averaged values ​​for the temperature and strain rate, as well as the Z factor. Patent Document 3 specifies a range of the Z factor for controlling the structure of the forged member to subcrystallization or fine recrystallization, but does not predict the properties of the forged member itself.

[0009] When a material and die are heated to a predetermined temperature and then forged, the temperature and strain rate of the material during the forging process constantly change from part to part and are not uniform throughout the material. This is one of the reasons why it is difficult to predict the mechanical properties of forged parts. The Z factor, calculated from the time-averaged temperature and time-averaged strain rate, may not be able to accurately represent the actual forging process, making it difficult to accurately predict the mechanical properties of forged parts.

[0010] The present invention has been made in consideration of the above circumstances, and an object of the present invention is to provide a method for predicting the properties of an aluminum component that makes it possible to accurately predict the mechanical properties of an aluminum component that has been subjected to any forging process.

[0011] In order to solve the above problems, the present invention employs the following means.

[0012] (1) A method for predicting properties of an aluminum component according to one embodiment of the present invention includes a mechanical property measurement step of measuring the mechanical properties of an unforged first aluminum component and a plurality of second aluminum components forged at different strengths after T6 treatment, respectively; a Z-factor calculation step of determining the temperature and strain rate for each forging step for an arbitrary portion of the second aluminum component during forging by numerical analysis and calculating a Z-factor using the determined temperature and strain rate; a regression equation derivation step of deriving a regression equation showing the relationship between the mechanical properties and the Z-factor using a plurality of combinations of the measured values ​​of the mechanical properties and the calculated values ​​of the Z-factors corresponding to the strength; and a mechanical property prediction step of predicting the mechanical properties of a third aluminum component after T6 treatment using the regression equation.

[0013] (2) In the method for predicting properties of an aluminum component described in (1) above, in the Z factor calculation step, the temperature and the strain rate are measured at predetermined intervals t ｓｔｅｐ The temperature and strain rate are measured at different times i, and the Z factor Z is calculated using the measured values ​​at each of the times i. ｉ Calculate the Z factor Z ｉ It is preferable that the Z factor be Z obtained by adding up the above values ​​according to the following formula (1):

[0014]

[0015] (3) In the method for predicting properties of aluminum components described in either (1) or (2) above, it is preferable to perform an angle change rate calculation step of measuring the mechanical properties of the second aluminum component in the main axis direction and in a direction tilted from the main axis direction, and using the measurement results to calculate the rate of change of the mechanical properties with respect to the angle of tilt from the main axis direction; an angle detection step of detecting an angle formed by the tensile direction of the third aluminum component in the mechanical property prediction step with respect to the main axis direction of the second aluminum component; and predicting the mechanical properties of the third aluminum component in the main axis direction taking into account the detected angle and the rate of change of the mechanical properties.

[0016] (4) In the Z-factor calculation step of the method for predicting the properties of an aluminum component described in any one of (1) to (3) above, it is preferable to examine the relationship between the presence or absence of recrystallization in the second aluminum component after the T6 treatment and the Z-factor, and to exclude from the plurality of second aluminum components those corresponding to the cases where the recrystallization has occurred.

[0017] According to the present invention, it is possible to provide a method for predicting the properties of an aluminum member, which makes it possible to accurately predict the mechanical properties of an aluminum member that has been subjected to any forging process.

[0018] FIG. 1 is a diagram showing a process flow of a method for predicting properties of an aluminum component according to one embodiment of the present invention. FIG. 2 is a diagram showing a process flow for measuring mechanical properties. FIG. 3 is a diagram explaining the state of an aluminum component before forging. FIG. 4 is a diagram explaining the state of an aluminum component after forging. FIG. 5 is a diagram showing a process flow for calculating a Z factor. FIG. 6 is a diagram explaining a calculation method for obtaining a cumulative Z factor. FIG. 7 is a graph showing the relationship between the mechanical properties of an aluminum component and the Z factor. FIG. 8 is a diagram showing a plan view of a portion to be actually evaluated in an aluminum component after T6 treatment, viewed from a spread direction perpendicular to the upsetting direction. FIG. 9 is a diagram showing a portion to be actually evaluated in an aluminum component after T6 treatment, viewed from the upsetting direction. FIG. 10 is a graph showing the relationship between the 0.2% proof stress of an aluminum component and the Z factor.

[0019] Hereinafter, a method for predicting the properties of an aluminum component according to an embodiment of the present invention will be described in detail with reference to the drawings. Note that the drawings used in the following description may show characteristic portions enlarged for the sake of clarity, and the dimensional ratios of the components may not necessarily be the same as those in reality. Furthermore, the materials, dimensions, etc. exemplified in the following description are merely examples, and the present invention is not limited thereto. Appropriate modifications may be made within the scope of the present invention.

[0020] 1 is a diagram showing a flow of main steps S included in a method for predicting properties of an aluminum component according to one embodiment of the present invention. The method for predicting properties of an aluminum component mainly includes a mechanical property measurement step S1, a Z-factor calculation step S2, a regression equation deriving step S3, and a mechanical property prediction step S4. In this embodiment, a component containing aluminum or an aluminum alloy (such as a JIS 6000 series (Al-Mg-Si series)) is referred to as an aluminum component.

[0021] 2 is a diagram showing the flow of steps included in the mechanical property measuring step S1. The mechanical property measuring step S1 is further divided into two smaller steps S11 and S12.

[0022] In step S11, the mechanical properties (0.2% yield strength, tensile strength, etc.) of a predetermined portion of a first aluminum member (aluminum forged material) that has not been subjected to forging such as upsetting are measured after T6 treatment (artificial aging treatment).

[0023] In step S12, predetermined portions of a plurality of second aluminum members (forged aluminum members) forged at different strengths (compression ratios) are subjected to T6 treatment, and then mechanical properties are measured. In the following, an example is shown in which upsetting is performed as forging.

[0024] The T6 treatment is a treatment in which aluminum members (first aluminum member, second aluminum member) are solution-treated, cooled (quenched), and then age-hardened. The conditions of the T6 treatment may be newly determined at the time of treatment, or may be determined after obtaining data on the relationship with the resulting mechanical properties and taking the data into consideration.

[0025] 3A and 3B are diagrams showing the state of the second aluminum member 100 before and after forging (upsetting) in step S12. As shown in FIG. 3A, an unprocessed aluminum forged material 100A is placed on a die (lower die) 101, and a punch (upper die) 102 is placed on the opposite side (here, the upper side) of the die 101. The punch 102 is moved toward the die 101 (here, the lower side) to press the aluminum forged material 100A, thereby obtaining an aluminum forged member 100B compressed in the pressing direction L, as shown in FIG. 3B. The compression rate due to upsetting is calculated by the ratio of the length h of the aluminum forged material 100A in the pressing direction L to the length h of the aluminum forged material 100A. ０ , the length h of the aluminum forged member 100B １ Using (h ０ -h １ ) / h ０ It is expressed as:

[0026] (Z-factor calculation step) Fig. 4 is a diagram showing the flow of steps included in the Z-factor calculation step S2. The Z-factor calculation step S2 is further divided into steps S21, S22, S23, S24, and S25.

[0027] In step S21, a model of the forging process (the relationship between temperature, strain rate, and compression ratio) is reproduced by numerical simulation. For example, DEFORM manufactured by SFTC can be used as the analysis software for the numerical simulation. The friction coefficient μ and heat transfer coefficient h of the contact surfaces are set for the aluminum workpiece, punch (upper die), and die (lower die). The aluminum workpiece is treated as a rigid plastic body, and the punch and die are treated as rigid bodies. Material data for the aluminum workpiece may be obtained from the software's built-in aluminum database, or material data acquired specifically for the aluminum workpiece may be used. Material data for die steel (SKD61) built into the software may be used for the punch and die. Next, a mesh is created for each aluminum workpiece model.

[0028] In step S22, the boundary conditions for the numerical simulation are set. Each member is aligned, the speed of the die and aluminum member is set to 0, and processing speed information is input for the punch. A motion curve may be set to match the actual forging process.

[0029] In step S23, a thermal coupled analysis is performed to model the heat transfer inside the aluminum part, that is, a numerical analysis is performed of the plastic deformation of the aluminum part, the internal heat transfer (or conduction), and the heat transfer between the aluminum part and the mold.

[0030] In step S24, after upset forging at a predetermined compression ratio (for example, 0.3 to 0.7), the temperature history and strain rate history of the evaluation portion corresponding to the portion where the tensile test was performed are extracted.

[0031] In step S25, the Z factor is calculated from the temperature history and strain rate history extracted in step S24. When calculating the Z factor, the following formula (1) is generally used. Z, ε (epsilon dot), Q, and R in formula (1) are defined as follows: Z: Z factor (s －１ ) ε: strain rate Q: self-diffusion activation energy of aluminum (144 kJ / mol) R: gas constant (8.314 J / mol / K) T: temperature (K)

[0032]

[0033] In the above formula (1), the temperature T and the strain rate ε are constant. However, in a normal forging process, the temperature T and the strain rate ε are not strictly constant. Therefore, from the viewpoint of accurately calculating the Z factor Z, it is preferable to reflect the influence of changes in the temperature T and the strain rate ε during the forging process in formula (1).

[0034] As a method for reflecting the time changes of the temperature T and strain rate ε during the forging process, for example, there is a calculation method in which the Z factor is calculated as a cumulative Z factor by adding up the Z factors that change over time. Figure 5 is a graph explaining this calculation method. The horizontal axis of the graph represents the time of the forging process divided into multiple calculation steps (unit time) t ｓｔｅｐ The number of calculation steps S when divided by ｉ The vertical axis of the graph represents the number of calculation steps S ｉ The magnitude of the Z factor corresponding to

[0035] In this calculation method, the number of calculation steps S ｉ Z factor Z for each ｉCalculate the Z factor Z of all steps calculated as in the following formula (2). ｉ At calculation step t ｓｔｅｐ The cumulative Z factor thus obtained reflects the influence of changes in temperature T and strain rate ε during the forging process, so the Z factor Z can be calculated accurately. Note that if the Z factor Z can be expressed as a function of time Z(t), it may be calculated by integrating the function over the range of the processing time.

[0036]

[0037] (Regression Equation Deriving Step) In the regression equation deriving step S3, the relationship between the mechanical properties measured in the mechanical property measuring step S1 and the Z factor calculated in the Z factor calculating step S2 is determined. That is, a plurality of combinations (A, B) of corresponding measured values ​​A of mechanical properties and calculated values ​​B of Z factors are determined via forging strength such as compression ratio, and plotted in the A-B plane. FIG. 6 is a graph showing an example of the plot. The horizontal axis of the graph represents the Z factor, and the vertical axis of the graph represents the 0.2% yield strength F of the first aluminum member (forged material) after T6 treatment. ０ The increment of 0.2% yield strength F of the second aluminum member (forged member) after T6 treatment, i.e., F - F ０ The plot of (A, B) is distributed along a specific curve (e.g., a parabola). Therefore, a regression equation showing the relationship between mechanical properties and Z-factor can be derived from the distribution of the plot of (A, B).

[0038] The regression equation derived in the regression equation deriving step has a specific shape for each material configuration of the second aluminum component to be forged, and therefore, the regression equation can be used to predict the mechanical properties of the third aluminum component after T6 treatment following any forging step.

[0039] <Determination of recrystallization range> When hot forging is performed to increase the Z factor, the crystal grains associated with the processed structure become finer and a large number of small-angle grain boundaries are introduced. For example, in the case of a 6000 series alloy, the Mg ２ High strength is obtained by promoting the precipitation of Si.

[0040] On the other hand, if a certain amount or more of low-angle grain boundaries are introduced, recrystallization occurs during the subsequent solution treatment, and the disappearance of the introduced low-angle grain boundaries and the coarsening of crystal grains result in a decrease in mechanical properties or a large fluctuation in the property values, which becomes a factor in deteriorating the accuracy of the mechanical properties. Therefore, in order to accurately predict the mechanical properties, it is preferable to examine the relationship between the presence or absence of recrystallization in the second aluminum member after the T6 treatment and the Z factor.

[0041] The relationship between the occurrence of recrystallization and the Z factor can be confirmed using the same method as that for obtaining the relationship between mechanical properties and the Z factor. Specifically, the magnitude of the Z factor at which recrystallization occurs can be determined from the results of hot working under a plurality of different Z factor conditions and a certain solution treatment followed by structural observation. Based on these results, it is possible to determine at least the Z factor at which recrystallization occurs. By selecting and performing hot working with a Z factor smaller than this Z factor, it is possible to exclude from the plurality of second aluminum components those that correspond to cases in which recrystallization occurs, and it is possible to predict the mechanical properties of a second aluminum component in which the occurrence of recrystallization is suppressed.

[0042] <Understanding the relationship of anisotropy> Generally, aluminum forged members have anisotropy due to metal flow during forging. When conducting a tensile test, the mechanical properties of the aluminum forged member change depending on the direction of the metal flow in which the tensile test specimen is taken and the tensile test is conducted. This anisotropy affects the accuracy of predicting mechanical properties, so it is preferable to consider the effects of anisotropy based on the results of numerical simulations.

[0043] For example, data on the direction of the maximum principal strain and the changes in mechanical properties when the angle relative to that direction is changed can be obtained by numerical simulation, and based on that data, corrections can be considered for the mechanical properties predicted through the mechanical property prediction process. Specifically, an angle change rate calculation process and an angle detection process can be added to the above-mentioned process.

[0044] In the angle change rate calculation process, the mechanical properties of the second aluminum component in the main axis direction and in a direction tilted from the main axis direction are measured, and the measurement results are used to calculate the rate of change of the mechanical properties with respect to the angle of tilt from the main axis direction.

[0045] In the angle detection step, the angle formed by the tensile direction of the second aluminum member in the mechanical property prediction step with respect to the principal axis direction of the second aluminum member is detected. The mechanical properties of the third aluminum member in the principal axis direction are predicted in consideration of the detected angle and the rate of change of the mechanical properties calculated in the angle change rate calculation step, and the predicted value is corrected as necessary.

[0046] As described above, the aluminum component property prediction method of this embodiment utilizes the material-specific relationship between the mechanical properties of a forged second aluminum component and the Z factor determined by numerical simulation. Based on this relationship, the aluminum component property prediction method of this embodiment can predict the mechanical properties of any portion of a forged second aluminum component after T6 treatment without performing T6 treatment. Therefore, there is no need to repeatedly produce prototypes to determine the conditions under which predetermined mechanical properties can be obtained, thereby reducing the amount of energy consumed during prototyping. For example, by applying this embodiment to a hot-forged aluminum alloy component used in an automobile suspension arm to predict its mechanical properties in advance, it is possible to reduce the number of prototypes and molds required and reduce GHG emissions during the development stage.

[0047] The effects of the present invention will be more clearly understood from the following examples. The present invention is not limited to the following examples, and can be practiced with appropriate modifications within the scope of the present invention.

[0048] The properties of aluminum members were predicted in accordance with the above embodiment. Three types of JIS 6000 series aluminum alloy members with the compositions shown in Table 1 were used as samples (test pieces) of the aluminum members before forging. The (average) crystal grain sizes of the three types of members were 56 μm, 70 μm, and 96 μm, respectively. The only difference between the three types of members was the crystal grain size.

[0049]

[0050] In order to obtain the relationship between mechanical properties and Z factor, the following tests were carried out. Upset forging was carried out on a 6000 series aluminum alloy cast bar (diameter φ57 × height h ０ The initial temperature of the upsetting process was 480°C. The temperature of the die and punch was 180°C. ０ and the height after upset forging h １ The upsetting rate (h ０ -h １ ) / h ０ Using a knuckle press with a pressurizing capacity of 630 t that was driven at 25 SPM with a stroke distance of 180 mm, and by adjusting the position of the bottom dead center, a 6000 series aluminum alloy cast bar was worked at each upsetting ratio.

[0051] The samples after upset forging (forged aluminum members) and samples with an upset ratio of 0 (as-continuously cast aluminum materials) (forged aluminum materials) were subjected to a predetermined T6 treatment. Here, the solution treatment was performed at a holding temperature of 530°C for 3 hours, and the subsequent artificial aging treatment was performed at a holding temperature of 180°C for 6 hours.

[0052] The 0.2% yield strength of the aluminum forged material samples and the aluminum forged member samples upset at each upsetting rate was measured, and the increase in 0.2% yield strength of each aluminum forged member sample relative to the aluminum forged material sample was determined.

[0053] 7A and 7B are plan views of a forged aluminum member after T6 treatment, viewed from the spreading direction perpendicular to the upsetting direction. The forged aluminum member samples were measured at a position midway between the center and the outermost periphery, i.e., at a thickness h １ Thickness h from the center C １ / 2 and at the maximum radius r １ For radius r １The sample of the forged aluminum material was taken from the position of the maximum radius r from the center in the state shown in FIG. ０ For radius r ０ The sample was taken at the position / 2 from the area extending in the height direction L.

[0054] For the numerical simulation to calculate the Z factor, a model mesh of the material and die for the above upset forging process was created. A ring compression test was separately conducted to determine the friction coefficient from the deformation state of the ring, and the friction coefficient was set as the boundary condition in the numerical simulation. The deformation resistance value obtained from the high-temperature compression test was used as the material property value, and added to the material database of the numerical simulation software.

[0055] 8 is a graph showing the relationship between the 0.2% yield strength of the aluminum forged member samples and the Z factor. The horizontal axis of the graph represents the Z factor, and the vertical axis of the graph represents the 0.2% yield strength F of the aluminum forged material after the T6 treatment. ０ The increment of 0.2% yield strength F of the aluminum forged member after T6 treatment, i.e., F-F ０ Plots are made for multiple combinations (A, B) of the measured 0.2% proof stress A and the calculated Z-factor B corresponding to the upsetting rate.

[0056] The plots are distributed so that they line up along a common curve. The same tendency is observed for samples of any grain size. These results show that there is a material-specific relationship between mechanical properties and Z factor that can be expressed by a single regression equation. If this regression equation is understood in advance, it is possible to predict the mechanical properties of any part of any forged aluminum component based on the regression equation without performing T6 treatment.

[0057] For multiple samples that were upset with different Z factors, the relationship between the magnitude of the Z factor, whether or not recrystallization occurred, and the prediction accuracy of 0.2% proof stress was investigated. The results are shown in Table 2.

[0058]

[0059] Z factor is 3.0 x 10 １１In the above cases, recrystallization occurs in the internal structure of the aluminum forged member, and the error in the predicted value of 0.2% proof stress becomes large. １１ When the Z factor is smaller than this, no recrystallization occurs, and the error in the predicted value of 0.2% proof stress is kept to 10% or less. These results show that the presence or absence of recrystallization changes depending on the Z factor's size. Furthermore, it is clear that the occurrence of recrystallization in the internal structure of an aluminum forged component significantly reduces the accuracy of mechanical property prediction. Therefore, it is believed that by investigating the relationship between the Z factor and recrystallization in advance and then limiting the Z factor during forging to a range in which recrystallization does not occur, it is possible to predict the mechanical properties of an aluminum component with high accuracy.

[0060] 100: Second aluminum member 100A: Forging material 100B: Forging member 101: Die 102: Punch

Claims

1. A method for predicting properties of an aluminum component, comprising: a mechanical property measurement step of measuring the mechanical properties of an unforged first aluminum component and a plurality of second aluminum components forged to different strengths after T6 treatment; a Z-factor calculation step of determining the temperature and strain rate for each forging step for an arbitrary portion of the second aluminum component during forging by numerical analysis, and calculating a Z-factor using the determined temperature and strain rate; a regression equation derivation step of deriving a regression equation showing the relationship between the mechanical properties and the Z-factor using a plurality of combinations of measured values ​​of the mechanical properties and calculated values ​​of the Z-factor corresponding via the strength; and a mechanical property prediction step of predicting the mechanical properties of a third aluminum component after a desired forging step after T6 treatment using the regression equation.

2. In the Z factor calculation step, the temperature and strain rate are measured at a predetermined interval t ｓｔｅｐ The temperature and strain rate are measured at different times i, and the Z factor Z ｉ Calculate the Z factor Z ｉ The method for predicting characteristics of an aluminum component according to claim 1, characterized in that the Z factor is calculated by adding up the above values ​​according to the following formula (1):

3. A method for predicting properties of aluminum components as described in either one of claims 1 or 2, characterized in that it comprises: an angle change rate calculation process for measuring mechanical properties in the main axis direction and mechanical properties in a direction tilted from the main axis direction of the second aluminum component, and using the results of the measurements to calculate a rate of change of the mechanical properties with respect to the angle of tilt from the main axis direction; an angle detection process for detecting an angle made by the tensile direction of the third aluminum component in the mechanical property prediction process with respect to the main axis direction of the second aluminum component; and predicting the mechanical properties of the third aluminum component in the main axis direction taking into account the detected angle and the rate of change of the mechanical properties.

4. A method for predicting the properties of an aluminum component as described in either one of claims 1 or 2, characterized in that in the Z factor calculation step, the relationship between the presence or absence of recrystallization in the second aluminum component after the T6 treatment and the Z factor is examined, and those corresponding to the cases where the recrystallization has occurred are excluded from the plurality of second aluminum components.

5. A method for predicting the characteristics of an aluminum component as described in claim 3, characterized in that in the Z factor calculation step, the relationship between the presence or absence of recrystallization in the second aluminum component after the T6 treatment and the Z factor is examined, and those corresponding to the cases where the recrystallization has occurred are excluded from the multiple second aluminum components.

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