Влияние температуры окружающей среды на коррозионную стойкость различных алюминиевых сплавов: экспериментальное исследование

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Одной из самых серьезных проблем, с которой сталкиваются инженеры в различных отраслях промышленности, является коррозия. В настоящее время основное внимание уделяется коррозионным свойствам различных типов алюминиевых сплавов, широко используемых в промышленности. В связи с этим были протестированы алюминиевые сплавы Al 2024, Al 6061 и Al 7075. Кроме того, было исследовано влияние температуры окружающей среды на скорость коррозии каждой группы материалов. В качестве индикаторов коррозии образцов были измерены три статистических параметра, включая общую площадь коррозии, скорость коррозии (отношение общей площади коррозии к общей площади образца) и максимальный размер точки коррозии. Кроме того, с помощью метода Бринелля была измерена и представлена поверхностная твердость образцов. Наконец, был представлен алюминиевый сплав, наиболее устойчивый к коррозии при различных температурных режимах. Испытание на коррозию, проведенное в присутствии холодного воздуха, показало максимальную твердость среди всех исследованных алюминиевых сплавов (2024, 6061 и 7075). Алюминий 7075 имеет самую низкую коррозионную стойкость, тогда как алюминий 6061 имеет самую высокую коррозионную стойкость, если принять во внимание различные условия испытаний.

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Introduction Corrosion is one of the biggest challenges faced by engineers in various industries [1-3]. This destructive phenomenon is a physical and chemical interaction between a metal material and the environment, which leads to a change in the properties of the metal and can cause a significant disruption in the performance of the metal, the environment, or the technical system of which they are a part of [4; 5]. Owing to the presence of an oxide layer on its surface, aluminum alloys show good corrosion resistance in corrosive environments with pH values in the range of 3 to 9. However, in environments with pH values lower than 3 or higher than 9, the outer porous layer is dissolved, and the aluminum surface is severely corroded. In other words, aluminum products are quickly destroyed as a result of long-term exposure to aggressive environments, especially those containing chlorine [6; 7]. Therefore, it is very important to understand the corrosion properties of aluminum alloys in special environments and under harsh working conditions. Failures caused by corrosion in metals have caused irreparable economic losses in large industries such as petrochemical, automotive, and aerospace, etc. [8; 9]. National Association of Corrosion Engineers (NACE), as a world leader in corrosion control, has estimated the total costs associated with global corrosion losses at 2.5 trillion dollars per year, which is equivalent to 3.4% of the world’s Gross Domestic Product (GDP) [10]. According to the NACE international report, corrosion losses in the world’s largest economies include 5% of GDP for Arab countries, 4.2% for China and India, 4% for Russia, 3.8% for the European Union (Norway and Switzerland), 2.7% for the United States, and 1% in the case of Japan. These statistics emphasize the importance of understanding corrosion phenomenon, as well as the development of plans that prioritize the long-term stability of materials and the use of optimal corrosion protection methods. As mentioned previously, aluminum alloys have many uses in industry. Therefore, considerable research has been conducted to investigate the destructive phenomena on aluminum. As schematically illustrated in Figure 1, a wide variety of corrosion types exist [11]. Figure 1. Schematics of different types of corrosion in aluminum alloys S o u r c e: made by A.S. Averyanov, S. Ghorbani, K. Reza Kashyzadeh [11] Among the corrosion mechanisms, pitting, intergranular, and exfoliation corrosion are the most prominent [12]. Moreover, exfoliation corrosion and stress corrosion are also the main types of corrosion in aircraft materials [13]. Paglia and Buchheit investigated the sensitivity of aluminum alloy friction stir welds to corrosion [14]. Because the microstructure of the material changes drastically in the Heat-Affected Zone (HAZ), intergranular corrosion occurs in this area. This corrosion becomes more severe as the grain boundary sediments become coarser. They reported that by using a short-term heat treatment after welding at a temperature similar to the welding temperature, the microstructure can be modified, and the corrosion rate can be reduced. Xu X. et al. utilized an amorphous CrAlN coat-ing to improve the corrosion resistance of aluminum alloy in a 3.5% NaCl solution [15]. They reported that material properties (i.e., microstructure and corrosion resistance) of the amorphous CrAlN coating depends on the nitrogen content of the coating. Sánchez-Amaya et al. studied the influence of heat treatment on the susceptibility of AA2024 and AA7075 alloys to intergranular corrosion [16]. They showed that slow quench step resulted in samples with high susceptibility to intergranular corrosion in both alloys. Li X. et al. simulated a mechanical test in line with the corrosion behavior of 7005 aluminum alloys in atmospheric environments [17]. In other words, they believed that the stress concentration of the pits led to the destruction of the mechanical properties. Therefore, the effects of pit size and location parameters on stress concentration were analyzed using Finite Element (FE) method. Finally, they presented a Back Propagation Neural Network (BPNN) model to predict stress concentration. As is clear from the above literature review, much research has been carried out in the field of aluminum corrosion and different methods to prevent or reduce the corrosion rate. Most research has been experimental. However, a limited number of simulation studies have been conducted. In addition, in recent years, machine-learning techniques have been used in this field. In simulation studies, laboratory data are required to validate the model. Furthermore, using machine learning techniques, experimental data is collected, and the machine is trained. Therefore, it can be concluded that laboratory data and tests are required in any case. In addition to the above-mentioned issues, not all the details of the corrosion phenomenon can be simulated in the software, and the main reason is the simplification of the software to solve various problems. Therefore, to achieve a system response with a higher accuracy, it is necessary to perform a series of tests. Therefore, this study was performed in a laboratory. In this study, different groups of aluminum alloys were prepared and immersed in a corrosive solution with a pH of approximately 12. Finally, the solution containing the sample was placed in three different environments at different temperatures. After a specified period of time, the samples were removed from the solution and the corrosion parameters were investigated. The subsequent parts of the article are organized in such a way that the second section is dedicated to materials and methods. The third section describes the experiment, and the obtained results are discussed in the fourth section. Finally, the achievements of the current study are presented in the last section. 1. Materials and methods 1.1. Materials The studied materials are widely used aluminum alloys in industry, including 2000, 6000, and 7000 series sheets with a thickness of 4 mm. These sheets were prepared using a casting process. Then, using a wire cutter, they were cut into pieces with a square cross-section and side size of 10 mm. Quantometric test was performed to extract the percentage of the constituent elements in the raw materials. Table 1 illustrates the chemical compo-sition of Al 2024, Al 6061, and Al 7075. Moreover, for each group, a specific heat treatment was defined according to what is most commonly used in the industry. For example, to perform T6 heat treatment, Al 7075 samples were fully tempered by heating at 480 °C for 5 h and then quenched in water below 120°C (slow cooling of approximately 28 °C per hour). Finally, they were kept at this temperature for 24 h [18]. Moreover, to determine the effect of heat treatment on the mechanical properties of each group of aluminum alloys, nine laboratory samples were prepared according to the ASTM E8/E8M standard. Tensile tests were performed at room temperature under controlled environmental conditions according to ISO 17025. The obtained results, including the key parameters, are listed in Table 2. Table 1 Chemical composition of different aluminum alloys used in the current research, wt% Material Al Si Fe Cu Mn Mg Ni Ti Cr Al 7075 96.68 1.15 0.32 0.01 0.73 0.99 0.01 0.01 0.10 Al 6061 97.72 0.58 0.36 0.21 0.03 0.93 0.00 0.01 0.16 Al 2024 97.57 0.64 0.14 0.27 0.12 1.00 0.01 0.03 0.22 S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov Table 2 The results obtained from tensile tests Material Yield strength Ultimate tensile strength Al 2024 98 MPa 186 MPa Al 7075-T6 483 MPa 560 MPa S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov 1.2. Methods This section describes the general idea behind conducting this research. The working algorithm is illustrated step by step in Figure 2. This research includes two preparation steps, that is, aluminum samples and a corrosive solution with a minimum pH of 12. The tests were divided into three groups: primary, main, and secondary. Rectangular cubes Figure 2. The working algorithm used in the current research S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov In fact, primary tests are related to the tests performed before the main test, that is, corrosion, and the goal is to better understand the properties of the material. Subsequently, the main test is corrosion, which is done by immersing the samples in the corrosive solution for a certain period of time. Finally, there is a secondary test that is performed on the corroded samples to determine their corrosion rate through microscopic observations and measurement of statistical parameters. Furthermore, to determine the effect of corrosion on the properties of the raw material, hardness measurement is also done. 2. Experiments Before performing the main test, the surfaces of the samples were polished with P800 grit sandpaper so that they had the same surface roughness. To create a corrosive solution, 20 g calcium hydroxide was added to 250 ml of distilled water (pH~6.5). In this time, the pH of the solution was measured and showed a value of 10.2. Subsequently, 20 g of sodium hydroxide was added; as a result, the pH value reached approximately 12.12. The solutions were poured into nine glass containers at the same height level and each sample was immersed in a solution container. The glass containers were placed in three different environments in terms of temperature, including 2-4 degrees called cold air, 10-12 degrees called fresh air, and 22-24 degrees called room temperature. The immersion time for all samples was considered one hour. Subsequently, the samples were removed from the solution, washed with distilled water, and their surface was dried with a heater, and finally they were not exposed to air. The corrosion process in aluminum is based on the following reaction equations: ; (1) . (2) The surface analysis of the samples was performed using an Olympus GX53 optical microscope and the Olympus Stream program. In fact, Optical Microscope (OM) observations were conducted to monitor surface damage characteristics such as the maximum, minimum, and average diameters of pits, pit shapes, and corrosion rate. Thus, the area of the visible sample in the observation range of the microscope was measured in square micrometers. Moreover, the area of each corrosion damage was measured and dis played as,where represents the number of damages caused on the surface of the sample owing to the corrosion. Eventually, the corrosion rate was obtained as the ratio of the total area of corrosion damage on the surface to the total area. In addition, the largest corrosion damage was identified on the surface, and assuming the shape of the damage to be circular or several circles connected together, the largest diameter of the damage was measured as. Finally, the hardness values of the samples were measured. For this purpose, a universal hardness tester METOLAB 703 was used with the ability to measure hardness based on Brinell, Rockwell, and Vickers methods. Three points were measured for each sample to verify the reproducibility of the results. The hardness test was performed based on the Brinell method with a ball (diameter of 10 mm), applying a load of 187.5 kg and a settling time of 30 s. 3. Results and Discussion For ease of understanding, each sample was assigned a unique numeric and letter code that indicated the raw material and corrosion conditions. The four-digit number indicates the series of aluminum alloys, and the letter indicates the test conditions. In this regard, X, K, and Y represent cold air, room temperature, and fresh air, respectively. The samples after the corrosion test along with their identification codes are shown in Figure 3. It is clear that the images of the samples exposed to fresh air have a darker surface than the other samples. On the other hand, the images related to samples that are in the vicinity of cold air have a brighter surface, such as snow salt. Identification code K X Y 2024 6061 A close up of a grey and white speckled surface Description automatically generated 7075 A close up of a stone Description automatically generated A close up of a rock Description automatically generated A close up of a stone Description automatically generated Figure 3. Samples after performing corrosion tests under different conditions S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov In addition, Figure 4 illustrates the corroded surfaces of different samples under an optical microscope at 10 × magnification. These images were obtained after cleaning (washing with distilled water, drying with a heater, and not being in close proximity to air). Therefore, the corroded parts can be recognized as dark holes with prominent depths [19]. OM observations showed that aluminum 7075 suffered more corrosion damage under all temperature conditions than the other two aluminum series (6xxx and 2xxx) did. Moreover, among all the samples, the sample made of the 6061 alloy showed the least corrosion effects at room temperature, which is consistent with the results presented in the laboratory study of Kharitonov et al. [20] on the corrosion observations of the sixth series aluminum alloy. Next, to measure the statistical parameters and compare the samples from the viewpoint of corrosion resistance, microscopic observations were performed at 100 × magnification. These images (Figures 5-7) are shown in detail, including the corroded areas with red lines and the largest corrosion damage in yellow. Also, the blue number indicates the largest size corresponding to the largest corrosion damage, which was extracted in micrometers using the software. In addition, the area of the corroded zones was extracted using the software and is reported in Tables 3-5. All corroded zones are indicated by numbers. Moreover, the zero number represents the total area of the examined surface. Identification code K X Y 2024 6061 7075 Figure 4. OM observations at 10 × magnification S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov a b с Figure 5. OM observations with 100 times magnification for Al 2024 samples at different temperature conditions including: a - in the vicinity of cold air; b - at room temperature; c - in the vicinity of fresh air S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov Table 3 Statistical characteristics (area in ) corresponding to Figure 5 Zone No. 0 1 2 3 4 5 6 7 Part (a) 73913 81.4 180.5 190.8 386 - - - Part (b) 74404 54 32 11 5 6 104 7 Part (c) 74695 108 47 333 113 248 265 - S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov a b c Figure 6. OM observations with 100 times magnification for Al 6061 samples at different temperature conditions including: a - in the vicinity of cold air; b - at room temperature; c - in the vicinity of fresh air S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov Table 4 Statistical characteristics (area in ) corresponding to Figure 6 Zone No. 0 1 2 3 4 5 6 7 8 9 Part (a) 72766 234 106 121 119 114 102 - - - Part (b) 74131 67 63 50 43 - - - - - Part (c) 74237 86 104 306 71 106 145 232 52 54 S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov a b c Figure 7. OM observations with 100 times magnification for Al 7075 samples at different temperature conditions including: a - in the vicinity of cold air; b - at room temperature; c - in the vicinity of fresh air S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov Table 5 Statistical characteristics(area in ) corresponding to Figure 7 Part (a) Zone No. 0 1 2 3 4 5 6 7 8 Area 74208 20 24 33 17 15 27 10 17 Zone No. 9 10 11 12 13 14 15 16 17 Area 14 191 21 20 20 8 19 10 10 Zone No. 18 19 20 21 22 23 24 25 26 Area 17 20 25 26 166 17 8 9 23 Zone No. 27 28 29 30 31 32 33 34 35 Area 23 23 54 151 10 116 36 91 20 Zone No. 36 37 38 39 40 41 42 43 44 Area 16 22 24 22 90 103 18 - - Ending of the Table 5 Part (b) Zone No. 0 1 2 3 4 5 6 7 8 Area 74419 232 41 157 42 32 28 55 30 Zone No. 9 10 11 12 13 14 15 16 17 Area 34 45 54 41 43 51 34 47 25 Zone No. 18 19 20 21 22 23 24 25 26 Area 24 43 47 51 44 - - - - Part (c) Zone No. 0 1 2 3 4 5 6 7 8 Area 74028 42 15 49 112 19 63 40 58 Zone No. 9 10 11 12 13 14 15 16 17 Area 77 26 52 33 27 45 29 39 47 Zone No. 18 19 20 21 22 23 24 25 26 Area 48 48 24 46 70 20 30 - - S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov Table 6 Corrosion rate and hardness in different aluminum alloys corroded under different environmental temperatures Identification code 2024 X 907.5 0.011307 13.2 12.1 12.8 12.7 2024 K 525.0 0.002953 11.3 10.6 10.3 10.7 2024 Y 827.0 0.015224 11.7 13.0 12.2 12.3 6061 X 644.5 0.009767 16.2 15.6 14.6 15.5 6061 K 369.3 0.003008 13.3 13.2 13.1 13.2 6061 Y 749.0 0.015612 12.5 11.0 11.8 11.7 7075 X 513.5 0.021644 21.7 23.5 20.3 21.8 7075 K 570.0 0.016127 19.2 18.2 20.2 19.1 7075 Y 639.3 0.014305 21.2 21.5 21.8 21.5 S o u r c e: made by K. Reza Kashyzadeh, S. Ghorbani, A.S. Averyanov As is clear from the microscopic images, the number of corrosion damages on the surface of 7075 aluminum samples is much higher than the others, with the difference that the size of the pits is smaller. The corrosion rate in each of the samples, along with the hardness measurements including three different points and their average, are given in Table 6. In this table, and represent the maximum size of the maximum corrosion damage on the surface and corrosion ratio, respectively. Also, is the Brinell hardness at th measurement, and the average value is indicated by Conclusion In this study, the authors investigated the corrosion rates of various series of aluminum alloys in the vicinity of a corrosive solution with a pH of 12 and different environmental temperatures in the laboratory. The most important achievements of this study are as follows: - The largest corrosion damage occurred in aluminum alloy 2024 and in the vicinity of cold air. - The highest corrosion rate was observed for aluminum alloy 7075 in the vicinity of cold air. - Among all the studied aluminum alloys (2024, 6061, and 7075), the highest hardness was observed when the corrosion test was performed in the vicinity of cold air. - The lowest corrosion rate was observed for aluminum samples 2024 and 6061 when the corrosive solution was at room temperature. - Considering the different experimental conditions, it can be concluded that aluminum 6061 has the highest corrosion resistance, and aluminum 7075 has the lowest corrosion resistance. References
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Об авторах

Казем Реза Каши Заде

Российский университет дружбы народов

Автор, ответственный за переписку.
Email: reza-kashi-zade-ka@rudn.ru
ORCID iD: 0000-0003-0552-9950

кандидат технических наук, профессор кафедры техники и технологий транспорта, инженерная академия

Российская Федерация, 117198, г. Москва, ул. Миклухо-Маклая, д. 6

Сиамак Горбани

Российский университет дружбы народов

Email: gorbani-s@rudn.ru
ORCID iD: 0000-0003-0251-3144
SPIN-код: 8272-2337

кандидат технических наук, доцент кафедры машиностроительных технологий, инженерная академия

Российская Федерация, 117198, г. Москва, ул. Миклухо-Маклая, д. 6

Андрей Сергеевич Аверьянов

Российский университет дружбы народов

Email: 1142220720@rudn.ru
ORCID iD: 0009-0007-0985-3869
SPIN-код: 9650-9795

аспирант кафедры машиностроительных технологий, инженерная академия

Российская Федерация, 117198, г. Москва, ул. Миклухо-Маклая, д. 6

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