Vol. 27 No. 2 2025 3 EDITORIAL COUNCIL EDITORIAL BOARD EDITOR-IN-CHIEF: Anatoliy A. Bataev, D.Sc. (Engineering), Professor, Rector, Novosibirsk State Technical University, Novosibirsk, Russian Federation DEPUTIES EDITOR-IN-CHIEF: Vladimir V. Ivancivsky, D.Sc. (Engineering), Associate Professor, Department of Industrial Machinery Design, Novosibirsk State Technical University, Novosibirsk, Russian Federation Vadim Y. Skeeba, Ph.D. (Engineering), Associate Professor, Department of Industrial Machinery Design, Novosibirsk State Technical University, Novosibirsk, Russian Federation Editor of the English translation: Elena A. Lozhkina, Ph.D. (Engineering), Department of Material Science in Mechanical Engineering, Novosibirsk State Technical University, Novosibirsk, Russian Federation The journal is issued since 1999 Publication frequency – 4 numbers a year Data on the journal are published in «Ulrich's Periodical Directory» Journal “Obrabotka Metallov” (“Metal Working and Material Science”) has been Indexed in Clarivate Analytics Services. Novosibirsk State Technical University, Prospekt K. Marksa, 20, Novosibirsk, 630073, Russia Tel.: +7 (383) 346-17-75 http://journals.nstu.ru/obrabotka_metallov E-mail: metal_working@mail.ru; metal_working@corp.nstu.ru Journal “Obrabotka Metallov – Metal Working and Material Science” is indexed in the world's largest abstracting bibliographic and scientometric databases Web of Science and Scopus. Journal “Obrabotka Metallov” (“Metal Working & Material Science”) has entered into an electronic licensing relationship with EBSCO Publishing, the world's leading aggregator of full text journals, magazines and eBooks. The full text of JOURNAL can be found in the EBSCOhost™ databases.
OBRABOTKAMETALLOV Vol. 27 No. 2 2025 4 EDITORIAL COUNCIL EDITORIAL COUNCIL CHAIRMAN: Nikolai V. Pustovoy, D.Sc. (Engineering), Professor, President, Novosibirsk State Technical University, Novosibirsk, Russian Federation MEMBERS: The Federative Republic of Brazil: Alberto Moreira Jorge Junior, Dr.-Ing., Full Professor; Federal University of São Carlos, São Carlos The Federal Republic of Germany: Moniko Greif, Dr.-Ing., Professor, Hochschule RheinMain University of Applied Sciences, Russelsheim Florian Nürnberger, Dr.-Ing., Chief Engineer and Head of the Department “Technology of Materials”, Leibniz Universität Hannover, Garbsen; Thomas Hassel, Dr.-Ing., Head of Underwater Technology Center Hanover, Leibniz Universität Hannover, Garbsen The Spain: Andrey L. Chuvilin, Ph.D. (Physics and Mathematics), Ikerbasque Research Professor, Head of Electron Microscopy Laboratory “CIC nanoGUNE”, San Sebastian The Republic of Belarus: Fyodor I. Panteleenko, D.Sc. (Engineering), Professor, First Vice-Rector, Corresponding Member of National Academy of Sciences of Belarus, Belarusian National Technical University, Minsk The Ukraine: Sergiy V. Kovalevskyy, D.Sc. (Engineering), Professor, Vice Rector for Research and Academic Aff airs, Donbass State Engineering Academy, Kramatorsk The Russian Federation: Vladimir G. Atapin, D.Sc. (Engineering), Professor, Novosibirsk State Technical University, Novosibirsk; Victor P. Balkov, Deputy general director, Research and Development Tooling Institute “VNIIINSTRUMENT”, Moscow; Vladimir A. Bataev, D.Sc. (Engineering), Professor, Novosibirsk State Technical University, Novosibirsk; Vladimir G. Burov, D.Sc. (Engineering), Professor, Novosibirsk State Technical University, Novosibirsk; Aleksandr N. Korotkov, D.Sc. (Engineering), Professor, Kuzbass State Technical University, Kemerovo; Dmitry V. Lobanov, D.Sc. (Engineering), Associate Professor, I.N. Ulianov Chuvash State University, Cheboksary; Aleksey V. Makarov, D.Sc. (Engineering), Corresponding Member of RAS, Head of division, Head of laboratory (Laboratory of Mechanical Properties) M.N. Miheev Institute of Metal Physics, Russian Academy of Sciences (Ural Branch), Yekaterinburg; Aleksandr G. Ovcharenko, D.Sc. (Engineering), Professor, Biysk Technological Institute, Biysk; Yuriy N. Saraev, D.Sc. (Engineering), Professor, V.P. Larionov Institute of the Physical-Technical Problems of the North of the Siberian Branch of the RAS, Yakutsk; Alexander S. Yanyushkin, D.Sc. (Engineering), Professor, I.N. Ulianov Chuvash State University, Cheboksary
Vol. 27 No. 2 2025 5 CONTENTS OBRABOTKAMETALLOV TECHNOLOGY Sundukov S.K., Nigmetzyanov R.I., Prikhodko V.M., Fatyukhin D.S., Koldyushov V.K. Comparison of ultrasonic surface treatment methods applied to additively manufactured Ti-6Al-4V alloy................................................................ 6 Kate N., Kulkarni A.P., Dama Y.B. A comparative evaluation of friction and wear in alternative materials for brake friction composites............................................................................................................................................................... 29 Naumov S.V., Panov D.O., Sokolovsky V.S., Chernichenko R.S., Salishchev G.A., Belinin D.S., Lukianov V.V. Microstructure and mechanical properties of Ti2AlNb-based alloy weld joints as a function of gas tungsten arc welding parameters............................................................................................................................................................................. 43 Jatti V.S., Singarajan V., SaiyathibrahimA., Jatti V.S., KrishnanM.R., Jatti S.V. Enhancement of EDM performance for NiTi, NiCu, and BeCu alloys using a multi-criteria approach based on utility function................................................ 57 Stelmakov V.A., Gimadeev M.R., Nikitenko A.V. Ensuring hole shape accuracy in fi nish machining using boring...... 89 EQUIPMENT. INSTRUMENTS Patil N., Agarwal S., Kulkarni A.P., Saraf A., Rane M., Dama Y.B. Experimental investigation of graphene oxide-based nano cutting fl uid in drilling of aluminum matrix composite reinforced with SiC particles under nano-MQL conditions............................................................................................................................................................................. 103 Gimadeev M.R., Stelmakov V.A., Nikitenko A.V., Uliskov M.V. Prediction of surface roughness in milling with a ball end tool using an artifi cial neural network................................................................................................................. 126 Osipovich K.O., Sidorov E.A., Chumaevskii A.V., Nikonov S.N., Kolubaev E.A. Manufacturing conditions of bimetallic samples based on iron and copper alloys by wire-feed electron beam additive manufacturing......................... 142 Babaev A.S., Savchenko N.L., Kozlov V.N., Semenov A.R., Grigoriev M.V. Performance of Y-TZP-Al2O3 composite ceramics in dry high-speed turning of thermally hardened steel 0.4 C-Cr (AISI 5135)...................................................... 159 MATERIAL SCIENCE Sokolov R.A., Muratov K.R., Mamadaliev R.A. Morphological changes of deformed structural steel surface in corrosive environment......................................................................................................................................................... 174 Chernichenko R.S., Panov D.O., Naumov S.V., Kudryavtsev E.A., Salishchev G.A., Pertsev A.S. Eff ect of heterogeneous structure on mechanical behavior of austenitic stainless steel subjected to novel thermomechanical processing............................................................................................................................................................................. 189 Panov D.O., Chernichenko R.S., Naumov S.V., Kudryavtsev E.A., Salishchev G.A., Pertsev A.S. Eff ect of cold radial forging on structure, texture and mechanical properties of lightweight austenitic steel................................................ 206 Deshpande A., Kulkarni A.P., Anerao P., Deshpande L., Somatkar A. Integrated numerical and experimental investigation of tribological performance of PTFE based composite material.................................................................... 219 Vorontsov A.V., Panfi lov A.O., Nikolaeva A.V., Cheremnov A.V., Knyazhev E.O. Eff ect of impact processing on the structure and properties of nickel alloy ZhS6U produced by casting and electron beam additive manufacturing........ 238 Misochenko A.A. Martensitic transformations in TiNi-based alloys during rolling with pulsed current........................... 255 EDITORIALMATERIALS 270 FOUNDERS MATERIALS 279 CONTENTS
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 Morphological changes of deformed structural steel surface in corrosive environment Roman Sokolov a, *, Kamil muratov b, Rasul Mamadaliev c Tyumen Industrial University, 38 Volodarskogo str., Tyumen, 625000, Russian Federation a https://orcid.org/0000-0001-5867-8170, falcon.rs@mail.ru; b https://orcid.org/0000-0002-8079-2022, muratows@mail.ru; c https://orcid.org/0000-0003-0813-0961, mamadalievra@tyuiu.ru Obrabotka metallov - Metal Working and Material Science Journal homepage: http://journals.nstu.ru/obrabotka_metallov Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science. 2025 vol. 27 no. 2 pp. 174–188 ISSN: 1994-6309 (print) / 2541-819X (online) DOI: 10.17212/1994-6309-2025-27.2-174-188 ART I CLE I NFO Article history: Received: 17 January 2025 Revised: 14 February 2025 Accepted: 17 March 2025 Available online: 15 June 2025 Keywords: Residual stresses Median depth Degree of grain anisotropy Structural steel Residual strain Corrosion rate ABSTRACT Introduction. Internal factors, including phase heterogeneity, crystallographic texture, residual stress amplitude and the concentration of non-metallic inclusions, exert a nonlinear, multi-parametric effect on the corrosion resistance of metallic systems in aggressive environments. This complex interaction significantly complicates the prediction of corrosion degradation kinetics and the assessment of the operational life of metal structures. These parameters modulate the spatial distribution of corrosion defects, their morphology and penetration depth, necessitating a systematic approach to establish quantitative correlations. To gain a more accurate understanding and account for the influence of internal factors on the corrosion process, comprehensive research and analysis are required. The use of mathematical processing methods in the analysis of influence will reveal stronger regularities applicable to the process of corrosion damage. This will enable the development of methods and approaches for optimizing the design, production and operation of metal structures and products, as well as improving their reliability and durability. Purpose of work is to develop a multi-criteria model linking the depth of corrosion damage (an integral indicator of environmental aggressiveness) with microstructural, mechanical, and topographic characteristics of low-carbon steel St3. The objects of the study are samples from rolled sheet metal with varying degrees of residual plastic deformation (ε = 0–7%). Methods of investigation. Grain size, texture, and dislocation density were assessed through microstructural analysis using optical microscopy (Olympus GX53) and scanning electron microscopy (JEOL 6008A). Quantitative morphometry of corrosion damage was performed using digital image analysis (AXALIT software), with median depth determined as a key parameter. X-ray diffraction analysis of residual stresses was implemented to construct tensor stress fields. Results and discussion. Experimental data demonstrates a non-linear increase of the median depth of corrosion damage with the degree of deformation: at ε = 6.6%, a twofold increase in the median depth is observed compared to the undeformed state. Multivariate regression analysis revealed the dominant influence of internal residual stresses on the kinetics of the corrosion damage process (R² = 0.89). The scatter of the determined values for internal stresses is ±5 μm. The observed regularities are associated with the behavior of the material structure during plastic deformation, which occurs most significantly in the {111} <110> directions, leading to the generation of reverse residual stresses. The median depth of corrosion damage reflects the rate of corrosion. The group method of data handling (GMDH) allowed for the synthesis a complex parameter combining various parameters of steel structure. Polynomial approximation of the dependence of the median depth of corrosion damage in 5% HCl on the complex parameter shows high convergence (R² = 0.99) with a determination error of ±1 μm. The developed model confirms that residual stresses are one of the key factors modulating the corrosion activity of deformed St3 steel. The results obtained allow for the optimization of cold treatment of steel to increase the corrosion resistance of metal structures. Further studies are planned to focus on the influence of dynamic loads and temperature gradients on the evolution of dislocation substructures. For citation: Sokolov R.A., Muratov K.R., Mamadaliev R.A. Morphological changes of deformed structural steel surface in corrosive environment. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2025, vol. 27, no. 2, pp. 174–188. DOI: 10.17212/1994-6309-2025-27.2-174-188. (In Russian). ______ * Corresponding author Sokolov Roman A., Ph.D. (Engineering) Tyumen Industrial University, 38 Volodarskogo str., 625000, Tyumen, Russian Federation Tel.: +7 919 925-88-47, e-mail: falcon.rs@mail.ru Introduction The corrosion failure of steel is a complex process influenced by both external and internal factors. For example, the material structure determines the susceptibility of steel to the corrosion process [1–3]. Thus, it is shown in [4] that ferrite and austenite are more electronegative than cementite. The close location of phases with different electric potentials in the material structure leads to the appearance of microgalvanic couples and an intensive destruction process in an aggressive environment. The presence of defects in the phases accelerates the corrosion damage of the material. In the steel structure, one of the phases with a high degree of defectivity is martensite [5–7]. The process of corrosion fracture is also affected by the homogeneity of the material surface [7–11]. It is especially important for steels with a low content of alloying elements [7, 12].
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 Studies have shown that grain size also affects corrosion [1, 13–14]. This is usually due to the fact that grain boundaries attract crystal structure defects and inclusion atoms [6–7, 15–16]. Pitting corrosion of steel can be observed when impurity elements are present in the structure [7, 17– 19]. The impurities can form chemical compounds that increase the activity of the material in the corrosive environment [7, 20–21] due to their electrochemical heterogeneity [6]. It has been demonstrated in studies [22, 25–26] that there is a direct correlation between the magnitude of internal residual stresses and the corrosion rate of structural steel. Internal stresses can reach values that exceed the yield strength of the material. This leads to plastic deformation and an increase in the number of linear defects in the form of dislocations [22, 25–29]. Residual deformation of the material under the influence of external loads increases the anisotropy of grains, which affects the rate of the corrosion process [3, 22]. The presented data from scientific studies confirm the existence of a multiparametric dependence of corrosion processes on exogenous and endogenous factors, including the crystal structure of the material, the degree of phase homogeneity, the morphology of the surface layer, the presence of foreign chemical elements in the alloy matrix, as well as dislocation and boundary-defect formations. Numerous experimental works [23–24] have contributed to the systematization of key aspects of the kinetics and thermodynamics of corrosion phenomena, which creates a theoretical basis for identifying factors determining material degradation under conditions of a specific operating environment. The purpose of this work is to develop a multi-criteria model linking the depth of corrosion damage (integral index of aggressiveness of the environment) with microstructural, mechanical and topographic characteristics of low-carbon steel St3. The subject of the study are samples cut from rolled steel sheets with varying degrees of residual plastic deformation (ε = 0–7 %). It is possible to use such an approach by relying on mathematical methods that allow taking into account the influence of various factors, for example, by using a group method of data handling (GMDH). The objectives of the study are: – to study quantitative relationships between the depth of corrosion damage to steel, the magnitude of residual internal stresses, grain size anisotropy, and their number in an aggressive environment; – to investigate the influence of plastic deformation (not exceeding 7 %) on the kinetics of corrosion processes, with emphasis on the change in the depth of damage and the role of residual stresses; – to analyze possible crystallographic mechanisms determining the correlation between corrosion depth and residual stresses; – to develop a physical and mathematical model describing the dependence of corrosion kinetics on structural and morphological parameters, taking into account strain anisotropy and dislocation dynamics using a group method of data handling (GMDH). Methods In this study, samples were taken from St3 steel sheet stock, which was used in its initial state. The samples (4.0 × 70.0 × 25.0 mm) were prepared with their longitudinal axis perpendicular to the rolling direction of the steel. The paper [22] presents data on the magnitude of internal stresses, degree of grain anisotropy, corrosion rate of the studied samples in a 5 % hydrochloric acid solution, and also reflects the methodology for determining these parameters. The investigated samples had different values of residual strain (Table). The microstructure of the investigated samples obtained on an optical microscope is shown in Fig. 1. Sample number and corresponding residual strain value Sample No. 1 2 3 4 5 ε, % 0 1.5 3.0 4.5 6.6
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 The study of the microstructure performed in [22] revealed that it consists of a ferrite-perlite mixture. It contains 81.7 % ferrite and 18.3 % pearlite. According to GOST 8233, the structure rating is 8. The minimum grain size rating is 8, the maximum grain size rating is 13, and the most frequently observed grain size rating on the micrographs is 11. The study of corrosion damage of the investigated samples was carried out on a JEOL 6008A scanning electron microscope (Fig. 2). The corrosion products of the material were removed from the surface before the study. Fig. 2. Structure of sample No. 1 of St3 steel Fig. 1. Microstructure of undeformed St3 steel sample Determination of the geometric parameters of the polished microsection surface was performed on images acquired using a scanning electron microscope (within the scanning area) with AXALIT software [30]. The values of the damage depth distribution were set in the software. Using the color gamut of the image, the depth of the observed damage was determined. Image scaling was performed in AXALIT to allow more accurate measurement results. Themeasurement was performed by delineating the defect contour, after which the software automatically calculated the area in μm². Depth variation was performed along a straight line, with the software counting darker areas of the image as deeper. The graph obtained in this way represents a profilogram of the surface along the selected direction. The constructed graphs determine the dependence of the depth in µm (determined by brightness) on the coordinate of the line position on the sample (µm). The methodology for calculating the depth of corrosion damage is as follows. The values of the corrosion damage depth obtained by measurements along a straight line (profilogram) on the base image surface were used to find the median value. Results and discussion Fig. 3 shows an example of the surface image of the investigated sample No. 2, obtained on a scanning electron microscope and analyzed in AXALIT software. An example of a profilogram is shown in Fig. 4. According to the obtained depth values from several measurements, the median corrosion damage depth values were determined for each sample. Determination of the median corrosion damage depth of the material under study was based on the following considerations: – the sample surface exhibits significant variations in height, even in areas without apparent corrosion damage (variations can reach 45 μm). this is attributed to the fact that the material under investigation is a multiphase system, in which different components react differently to the aggressive environment. furthermore, the grain boundaries are highly heterogeneous due to the high concentration of crystalline defects;
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 – material destruction occurs non-uniformly, even within a localized corrosion site. this is attributed to the varying rates of the corrosion process and the slower diffusion processes in the material-electrolyte system; – the median value represents the average value within the considered sample set, rather than averaging the obtained measurement results. The dependence of the median value of the corrosion damage depth on the value of residual strain is presented in Fig. 5. a b Fig. 3. Microstructure of Sample No. 2: a – profile line location; b – highlighted area of corrosion damage) Fig. 4. Profilogram obtained from the micrograph of Sample No. 1 using AXALIT software
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 Fig. 5. Median depth of corrosion damage as a function of residual strain in the material From the samples after corrosion tests, cross sections were additionally made. Microphotographs were taken, and the distance from the surface of the sample to the upper forming surface at the points of corrosion damage registration was measured. These measurements are presented in Fig. 6, where there is a direct measurement of the corrosion damage depth. The distance from the surface of the sample to the upper Fig. 6. Micrograph of a cross-section prepared from Sample No. 3 after corrosion testing, showing the locations where corrosion damage depth was measured
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 Fig. 7. Median depth of corrosion damage at varying levels of residual strain: hp – results obtained using AXALIT software; hm – results obtained from cross-sectional analysis forming surface at the points of corrosion damage registration is shown in Fig. 6 in the form of blue lines. According to the measurements obtained, the median depth of corrosion damage was determined. A comparison of the results of the median depth measurement from the cross-section micrograph and from the surface photograph in the AXALIT software is shown in Fig. 7. As can be seen from Fig. 7, the results of determining the median depth of corrosion damage using AXALIT software are satisfactory. The obtained dependences of the change in median corrosion damage depth on the residual strain of the material exhibit a similar trend in both cases, indicating a consistency between the results. The results from direct measurement and those obtained using the software differ by a factor of 1.45, as shown in Fig. 8. However, the median corrosion damage depths obtained by the two methods are directly correlated, as evidenced by the linear dependence presented in Fig. 8. The coefficient of determination (R²) for the obtained relationship is 0.91, further indicating a strong agreement between the results. The data observed in Figs. 5, 7, and 8 indicate that during plastic deformation, there is an increase in the penetration depth of corrosion damage into the material. This is because the material fracture process initiates at surface micro-inhomogeneities, which can be considered as dislocations and atoms of chemical elements. Plastic deformation of the material leads to an increase in dislocation density [22, 25-27]. During material deformation, dislocations move due to the slip process. During movement, dislocations collide with grain boundaries, which act as obstacles. Accumulation of dislocations occurs in the grain boundary regions. Plastic deformation leads to the generation of new dislocations and an increase in dislocation collisions. This results in the formation of dislocation clusters that are unable to move through the crystal lattice. Together with impurity atoms diffusing into the grain boundaries, this intensifies the corrosion fracture process. In this case, the grain boundaries are the initiation sites for this process (Fig. 9). Restriction of dislocation movement and formation of a more extensive cluster leads to hardening of the material [20], which affects the grain shape and its average size. The average size is in direct relation to the number of grains in the microstructure, and it affects the extent of grain boundaries. The greater the number of grains, the greater the probability of accumulation of crystal structure defects in these areas and the higher the corrosion susceptibility of the material. However, other parameters of the system under consideration also change during deformation.
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 Fig. 8. Relationship between median corrosion damage depth hm and hp a b Fig. 9. Microstructure of Sample No. 4 (a) and Sample No. 5 (b), showing the highlighted area of corrosion initiation The grain shape can be evaluated by its degree of anisotropy, which increases with plastic deformation of the material [22]. Plastic deformation in a phase with a body-centered cubic (BCC) lattice most commonly leads to slip along crystallographic planes and directions {110} <111> [31]. This accounts for the described process. Due to the change in grain shape, there is a decrease in internal residual stresses as a consequence of the appearance of stresses of opposite sign [28]. The resulting anisotropy of texture and material properties affects the corrosion fracture process (Fig. 10). The correlation between corrosion processes and internal stresses, arising during plastic deformation, is due to the modification of the defect substructure of crystalline material, realized through the activation of dislocation dynamics. This mechanism involves the coordinated slip of linear defects in the crystal lattice along preferred slip systems, determined by the crystallographic configuration with maximum atomic packing density, which minimizes the activation energy for shear processes [21, 32-33]. Plastic deformation induces directed migration of dislocations, accompanied by their interaction within the bulk of the material, including annihilation upon encountering dislocations of opposite sign, as well as the formation of stabilized configurations (dislocation walls, networks) [21, 32-33]. These structural transformations modulate local electrochemical potentials, creating regions of enhanced reactivity, which catalyzes corrosion processes, as seen in Fig. 11. This occurs due to the following factors: – formation of microgalvanic couples between deformed and undeformed regions;
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 a b c Fig. 10. Dependence of median corrosion damage depth on: a – degree of grain anisotropy; b – value of residual stresses; c – grain count in the material structure Fig. 11. Dependence of median corrosion damage depth on corrosion rate of St3 steel samples at varying residual strain values
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 – intensification of reagent diffusion through dislocation channels; – accumulation of residual stresses, which lowers the energy barrier for oxidation reactions. The above data show that the depth of corrosion damage depends on many internal factors. Estimating it using a single characteristic can yield both positive and negative results. However, when estimating multi-dependent parameters, it is possible to use methods that allow for a comprehensive determination of the influence of the considered values on the desired outcome. One such method is the group method of data handling (GMDH) [34-36]. The GMDH method does not perform an exhaustive search of all possible models. However, with a sufficient amount of initial data, it allows us to find the optimal solution, represented as a complex parameter that exhibits the best correlation with the considered value. Using the GMDH method, a complex parameter closely related to the corrosion damage depth of the studied material after plastic deformation was determined. This parameter is expressed by the following equation: 2 1 2 3 Ð k N k k σ ∆ (1) where N is the number of grains; σ is the internal residual stresses; Δ is the degree of grain anisotropy; k is the coefficient of mutual influence of the considered characteristics and the depth of corrosion damage. The obtained complex criterion reflects the influence of internal material parameters on the corrosion damage depth during plastic deformation (Fig. 12). When considering individual parameters, a significant scatter is observed, which, even with a coefficient of determination greater than 0.9, makes it difficult to estimate the value of interest accurately. When the complex parameter is applied, the scatter of median depth values determined from the image is reduced to a range of ±1 μm, and the coefficient of determination approaches 1. Fig. 12. Dependence of median corrosion damage depth on the complex parameter Conclusion – The study of the results obtained for St3 steel after aging in a 5 % hydrochloric acid solution demonstrates a direct correlation between the depth of corrosion damage and internal residual stresses, as well as between the depth of corrosion damage and grain size anisotropy and the total number of grains. – It was found that at a deformation of 6.6 % in the investigated material, the median depth of corrosion damage increases twofold. This is consistent with the data on the increased rate of corrosion of the material with increasing plastic deformation due to the increase in internal residual stresses.
OBRABOTKAMETALLOV MATERIAL SCIENCE Vol. 27 No. 2 2025 – The highest statistically significant correlation (R² > 0.85) was found in the system “median depth of corrosion damage - magnitude of residual stresses”, where the standard deviation for the latter parameter does not exceed ±5 μm at a 95 % confidence interval. This relationship is determined by the crystallographic anisotropy of plastic deformation, manifested by the preferential activation of {111}⟨110⟩ slip systems in materials with a HCC lattice. Selective dislocation mobility along these crystallographic planes is associated with the formation of gradient fields of residual compressive stresses and localized relaxation processes occurring through the formation of dislocation substructures such as walls and cells. – The group method of data handling (GMDH) allows us to determine a complex parameter that reflects the median depth of corrosion damage of St3 structural steel in a 5 % hydrochloric acid solution. This parameter takes into account the magnitude of residual internal stresses, grain anisotropy, and their number. It exhibits a high degree of correlation with the median depth of corrosion damage. The obtained dependence is described by a second-order polynomial equation, with a coefficient of determination R² ≈ 0.99 and a scatter in the determination of the median depth of ± 1 μm. References 1. Li Y., Wang F.G., Liu G. Grain size effect on the electrochemical corrosion behavior of surface nanocrystallized low-carbon steel. Corrosion, 2004, vol. 60 (10), pp. 891–896. DOI: 10.5006/1.3287822. 2. Sokolov R.A., Novikov V.F., Muratov K.R., Venediktov A.N. Otsenka vliyaniya dispersnosti struktury stali na magnitnye i mekhanicheskie svoistva [Assessment of the effect of the steels structure dispersion on its magnetic and mechanical properties]. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2021, vol. 23, no. 4, pp. 93–110. DOI: 10.17212/1994-6309-2021-23.4-93-110. 3. PomazovaA.V., Panova T.V., Gering G.I. Rol’ faktorov formy zerennoi struktury v elektrokhimicheskoi korrozii kotel’nykh trub, izgotovlennykh iz uglerodistoi stali 20 [Role of grain structure form factors in electrochemical corrosion of boiler tubes made of carbon steel 20]. Praktika protivokorrozionnoi zashchity = Theory and Practice of Corrosion Protection, 2013, no. 3 (69), pp. 68–71. 4. Shur Ya.S., Zaikova V.A. O vliyanii napryazhenii na magnitnuyu strukturu kristallov kremnistogo zhelez [On the influence of stresses on the magnetic structure of siliceous iron crystals]. Fizika metallov i metallovedenie = Physics of Metals and Metallurgy, 1958, vol. 6, no. 3, pp. 545–555. (In Russian). 5. Smirnov M.A., Schastlivtsev V.M., Zhuravlev L.G. Osnovy termicheskoi obrabotki stali [Fundamentals of heat treatment of steel]. Yekaterinburg, Ural Branch of the Russian Academy of Sciences Publ., 1999. 495 p. 6. Ueji R., Tsuchida N., Terada D., Tsuji N., Tanaka Yu., Takemura A., Kunishige K. Tensile properties and twinning of high-manganese austenitic steel with fine-grained structure. Scripta Materialia, 2008, vol. 59 (9), pp. 963–966. DOI: 10.1016/j.scriptamat.2008.06.050. 7. Sokolov R.A., Novikov V.F., Kovenskij I.M., Muratov K.R., Venediktov A.N., Chaugarova L.Z. Vliyanie termicheskoi obrabotki na obrazovanie soedineniya MnS v nizkouglerodistoi konstruktsionnoi stali 09G2S [The effect of heat treatment on the formation of MnS compound in low-carbon structural steel 09Mn2Si]. Obrabotka metallov (tekhnologiya, oborudovanie, instrumenty) = Metal Working and Material Science, 2022, vol. 24, no. 4, pp. 113–126. DOI: 10.17212/1994-6309-2022-24.4-113-126. 8. Sokolov R.A., Novikov V.F., Venediktov A.N., Muratov K.R. Influence of surface treatment of construction steels on determination of internal stresses and grain sizes using X-ray diffractometry method. Materials Today: Proceedings, 2019, vol. 19 (5), pp. 2584–2585. DOI: 10.1016/j.matpr.2019.09.015. 9. Introduction to Corrosion Monitoring. Metal Samples: Corrosion Monitoring Systems. Website. Available at: https://www.alspi.com/introduction.htm (accessed 25.03.2025). 10. Zhuk N.P. Kurs teorii korrozii i zashchity metallov [The rate of corrosion and protection of metals]. Moscow, Metallurgiya Publ., 1976. 472 p. 11. Tiwari A., Hihara L., Rawlins J., eds. Intelligent coatings for corrosion control. Butterworth-Heinemann, 2014. 746 p. ISBN 9780124114678. 12. Nalli K. Corrosion and its mitigation in the oil and gas industry. An overview. PetroMin Pipeliner Report, 2010, January – March, pp. 10–16. 13. Sokolov R.A., Novikov V.F., Muratov K.R., Venediktov A.N. Opredelenie vzaimosvyazi faktora raznozernistosti i skorosti korrozii konstruktsionnoi stali [Determination of the relationship between the factor of grain size factor and the corrosion rate of structural steel]. Obrabotka metallov (tekhnologiya, oborudovanie,
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