Microstructure and Aging Influence on the Mechanical Properties of High-Voltage Poles

Introduction High-voltage poles made in 1956 had to satisfy the cross-sectional geometry related standard (GOST 850957 confirmed later). However, the stricter requirements weren’t applied for the microstructure. In this paper a strength analysis of the pillars’ material is provided. The technological specificities of profile manufacturing were mostly determined by differences in mechanical properties influenced by differences in microstructures of pillars’ material investigated. Although the confirmed standard of steel CT3 (GOST 380-71) had new requirements and clear criteria of microstructure acceptance but made pillars with the non-homogeneous microstructure remained standing. The differences in microstructural components create conditions for appreciable differences in mechanical properties such like yield stress and ultimate stress, fracture strain. In this paper, the limits of elastic and plastic strains are identified in order to quantify the changes in elastic and plastic properties with the differences in their intensity for selected step-like stress range. Corrosion depth and width play the large role and ones often determine the fracture location of samples. The end of this work is dedicated to conclusion based on the relation of experimental part and analytical calculations presented.


Introduction
High-voltage poles made in 1956 had to satisfy the cross-sectional geometry related standard (GOST 8509-57 confirmed later).However, the stricter requirements weren't applied for the microstructure.In this paper a strength analysis of the pillars' material is provided.The technological specificities of profile manufacturing were mostly determined by differences in mechanical properties influenced by differences in microstructures of pillars' material investigated.Although the confirmed standard of steel CT3 (GOST 380-71) had new requirements and clear criteria of microstructure acceptance but made pillars with the non-homogeneous microstructure remained standing.The differences in microstructural components create conditions for appreciable differences in mechanical properties such like yield stress and ultimate stress, fracture strain.In this paper, the limits of elastic and plastic strains are identified in order to quantify the changes in elastic and plastic properties with the differences in their intensity for selected step-like stress range.Corrosion depth and width play the large role and ones often determine the fracture location of samples.The end of this work is dedicated to conclusion based on the relation of experimental part and analytical calculations presented.KEYWORDS: ageing, corrosion, microstructure, mechanical properties.
The tensile properties of the alloys have been measured at room temperature as an expected function of corrosion level.Investigation indicates that the very fine stable microstructure of the specimens' material influences on mechanical properties combined with adequate corrosion impact.Corrosion evolution on the cold-rolled low carbon steels is one of many examples of dynamics in corrosion that may occur under atmospheric/oxidizing conditions.Cold forming operations and cold rolling generally do not decrease the corrosion resistance (Barbier et al. 2009).It is important that such kind of steels do not demonstrate sufficient resistance to the corrosive effects of the most commonly encountered environment like atmosphere.
In this article, authors present their study how level of corrosion may influence on mechanical properties after some period of maintenance time of high voltage piles.In electric industry, the structures mentioned retain wide appearance of corrosion not only for long but also for short periods of time.Data of this investigation was analyzed statistically, and a set of equations was derived that allows comparison of corrosion level as a function of the mechanical properties presented below (Flower and Lindley 2000).
The height and roughness of exposed corrosion samples have been measured by mechanical profilometer for comparison with the results of fracture area gotten after tensile experiment.In some experimental studies, the averaged magnitude of corroded area has been used to image and map the corrosion under specimen surface and some authors showed that corrosion level may be described by the power function which is also suitable for demonstrating the development of long-term corrosion.(Garcia et al. 2003).
The mechanical properties and microstructures of low-carbon steel were investigated by tensile testing machine and optical microscopy, respectively.The results showed that significant differences existed in the yield strength, ultimate strength and fracture strength (Arafin and Szpunar 2009).
The aim of the present work is to show the difference in mechanical properties for cold-rolled specimen made of law carbon steel and used in old design of high-voltage poles.The differences in microstructure and corrosion related damages influence on the dissipation of mechanical properties.Used statistical method shows how experimental results are close to their mean values and what reasons of microstructural quality lead to those differences (Serenelli et al. 2011, Hughes et al. 2003).
The present work is important for the development of statistical method that tries to overcome details of the differences in microstructure and level of corrosion on the specimen surface as a result of deformational state of material.The microstructural observations show that the difference of material quality naming it as a non-homogeneous specimen has a significant effect on different stages of deformation.The description of mechanical behaviour of crystalline material is a complex multiscale problem.While the underlying deformation processes such as the intergranural slip lead atomic plane inclinations and like-screw dislocations are microscopic problems, the measured results exhibit usually macroscopic stages.As it is presented in this work, provided tensile tests show a deformational behaviour of individual specimens.They also may exhibit that some level of corrosion over the area of the specimen is the reason of fracture.
Tensile test were provided using the standard LST EN ISO 6892-1:2009.The standard exhibits basic requirements for the methodology of test procedure like specimen geometry and speed of straining.During the test authors use deformation speed 1 mm/min.The result of the tests especially is important for an assessment of differences in deformational behaviour and it is one of the principal criteria of material quality of specimen.
The principal mechanical properties were fixed using experimental curve "force vs. displacement" and calculated for individual specimens separately to find means presented in Table 1.For the statistical analysis, authors try to choose some alternative method on approximation of results and it is necessary to determine the values of the probability distribution over the variable experimental values changing their interval.It also influences on determination of the type of data distribution.In most cases the data are distributed according to the normal (Gaussian) law.

Methods
Using hypothetical assumptions in statistical calculations, it is important to have some sufficient number of specimens.In the case of small number of specimens, there are some problems related usually with data normality.Then, description or approximation of results is difficult.In determining the distribution type, authors assume that the data may be distributed by the normal distribution.Normal distribution was defined by the arithmetic mean ave X of mechanical properties and statistical analysis of their distributed values i X for some specimens' set.Therefore, in further analysis authors try to use that assumption of normal law and used criteria will provide some quality of analysis.The literature indicates that a rough estimation of the distribution determination is sufficient if number of experiments is at least 20.In our study there were 9 specimens tested.
The individual statistical values i X are dissipated around the arithmetic mean value ave X or around relative mean value 1 = X with some probabilistic value ∆ and ones represent some density of points influencing on data normality.Authors use simplified method how to visualize such kind of distribution by the equation Fig. 1 Family of tensile curves in terms of engineering (i/iii) and true (ii/ iv) stresses/strains, respectively.Explanation of stress/strain state related letters: A is yielding, B is ultimate, C is fracture For the approximation of expected statistical distribution of experimental results, following equation was used: The parameter ∆ ( ) was adopted to determine some expectation related probability of mechanical property that reaches maximal value at point 1 = X .The final equation was chosen according to the maximal value of squared root deviation 2 R for stresses and for strains, respectively, presented in the Tables 2 and 3.
In terms of stresses and strains, Eq. 1 may by written as follows and Eq.(2) adopted for stress looks like In Table 2 there are constants i C presented according to relative mechanical property σ X with the use of third order polynomial equations Eq. ( 4). ( 4) Table 2 Relative mechanical properties σ X and constants i C (×10 3 ) used in Eq. 4 In terms of stresses and strains, Eq. 1 may by written as follows *-Eq.4 is transformed to second order equation ( 5) and Eq. ( 2) applied for strains is similar with Eq. ( 4) used for stresses: In Table 3, there are constants i C presented according to relative mechanical property ε X with the use of same structure polynomial equations Eq. ( 6). ( 6) Using equations 3 and 5 the values σ ∆ and ε ∆ were obtained and ones represent dots in the plotted graph of Fig. 2. For those dots distributed around the relative mean 1 = X in the left and right sides the equations of approximation Eq. 5 and Eq. 6 were applied.In Fig. 2, i(a) the mostly dissipated engineering stress is stress B with its value ∆ in comparison with engineering stress mentioned above but dots are dissipated widely along to axis σ X .This fact is related to the differences in methods for stresses used non-/reducing area of cross-section.
In Fig. 2. graphs iii and iv exhibit families of engineering and true strains, respectively.The largest difference was gotten for curve A representing engineering yield strain at the highest pick of yield stress Y σ (Fig. 2, iii(a)).The dissipation was high enough 6 . 1 = ε X and its probability was very low % 3 6 = ∆ ε 36 %.In the shorter enlarged range (Fig. 2, iii(b)), the picks reach following values: for True strain curves show similar distribution of mechanical characteristics A, B and C but the points in the curves B and C are dissipated widely along to axis ε X (Fig. 2, iv(a)).In the case of true strains, the contraction of cross-section area changes pick of characteristic B with value ( ) % 5 .9 5 max = ∆ ε 95.5 % while it was higher for engineering strain ( ) % 5 .9 8 max = ∆ ε 98.5 %.

Table 3
Mechanical properties ε X and constants i C (×10 3 ) used in Eq. 6 To describe the effects during deformation within the microstructure caused by heterogeneity is difficult because of disorientation of atomic planes in the crystals.Such analyses have difficulty accounting for the evolution of yield surfaces in the crystals that are first sources of plastic deformation.These effects were not taken into account but they were assumed naturally occurring as inevitable process.
The microstructural heterogeneity is usually inherited from the crystallization if the carbon amount in the edge and in the centre of steel ingot is different.Iron oxides influence on the mechanical properties much stronger because of the joining fireplaces of those oxides inside the material.In the case of large amount of oxides, those fireplaces can easily connect by themselves and give a star to an earlier material degradation.The oxides especially are dangerous if their amounts are distributed stochastically inside the microstructure.

Results
After examination of the fracture photos the irregular damage of material along the tested samples which surface affected by long-term corrosion was revealed.As a result the characteristic parameters of corrosion defects were determined: such as the corrosion level, the approximate area of the damage, the intensity of corrosion and so on.On the surface of observed samples corrosion damage area and volume increase was examined according to the regulations of Europe standard for metal and alloy corrosion and so on (LST EN ISO 8403:2000).Data of this investigation presented in Fig. 3.The study found the dispersion of corrosion spots and the differences of intensity damage (cracks) on the sample surface or the surface layer.By using the Photoshop program the rust area of ten samples was calculated.In calculating area, the program self-identified rusty color intensity of its surface area.Then this program calculated the area of pixels, and later pixels was converted into area units (cm 2 ) according the known area.
The area of rust was calculated on ten samples by choosing the rustiest spots of investigated samples.The study found that the rusty area of individual samples varied in the range of 0.26 cm 2 to 3.06 cm 2 (Fig. 3).The area of average rusty was 1.24 cm 2 , or 31% calculating from the measured area.By identifying rust damage spot the cleaning of sample surface could be affected on the size of dispersion.
All samples have similar microstructure like steel CT 3 (GOST).Many of the studied samples are microstructuraly inhomogeneous, that is, in the microstructure there were found areas with a lower carbon amount of about 0.1% C, and areas with a higher carbon amount reaching 0.3% C.Those inaccuracies were the primary sources of material fracture presenting in Fig. 4. Samples containing more homogeneous microstructure had quantity of carbon equal to 0.14−0.22%.It is obvious looking at microstructures presented in Fig. 5.
Correlation between depth of corrosion and area of fracture is weak enough as it is shown in Fig. 5.In the microstructures, there is some amount of other kind of defects like non−metallic inclusions (iron oxides and sulphides, decarbonizes surface layer, bandwidth and "Widmanstatten" pattern).
%. Also, for same enlarged distribution presented in Fig.2, i(b) the picks of engineering stress on the dashed mean line1 = Xrepresents maximal values of that distribution related characteristics A, B and C. Obviously, for Aof true stress (see Fig.2, ii(a)), the characteristics A and C are dissipating mostly with %, respectively.Enlarged view (Fig.2, ii(b)) shows approximately same values for σ Fig. 2 Parameters representing statistical distribution of relative stresses σ X and strains ε X versus related probabilistic values σ ∆ and ε ∆ , respectively.Explanation of letters used: i and ii are engineering and true stresses; iii and iv are engineering and true strains; (a) is full set of results and (b) is enlarged view for chosen bi-axial range of figure (a) Fig. 3The diagram of corrosion area (A, cm 2 ) influencing on indicator of corrosion affects R. Notes: 1-9 are numbers of specimens