Abstract
This study presents KIC data obtained from KIC-CVN correlations from Charpy CVN values. For this study, T-welded connections were manufactured from ASTM A36 and E6013 electrodes in dry conditions. Then, a rectangular grinding at the weld toe was carried out and filled with wet welding. Charpy specimens were extracted to obtain CVN values. An exhaustive search through the literature of several authors was performed to collect experimental CVN data about wet welding being applied to A36 steel for comparison with CVN data obtained in this study. By using Charpy impact energy (CVN), KIC values could be predicted by KIC-CVN correlations. In addition, correlations were presented to obtain KIC values in the lower shelf, transition temperature zones and different zones for the energy-temperature curve of A36 steel. Of these correlations, Barsom’s equation was adopted, because he applied the stress yield (σYS) of the material and it can be applied in all zones for the energy-temperature curve. The results revealed that CVN values are proportionate to KIC, this data decreases as water depth increases. This took place because several discontinuities, such as, porosity, slag inclusion, non-metallic inclusion, cracking and microstructures are present in the wet welding.
Keywords: Fracture Toughness (KIC); Charpy impact energy (CVN); Wet welding; A36 Steel; Porosity
1. Introduction
It´s widely recognized that Charpy CVN impact energy values can be converted to KIC using KIC-CVN correlations [1-7]. In this context, plane-strain fracture toughness (KIC) is an important material property in the prediction and prevention of fracture, and for damage tolerance assessment of brittle materials [8]. The KIC in the linear elastic fracture mechanics (LEFM) is the size of the stress intensity factor at the tip of the crack if the strain in the body is elastic. The ASTM E-399 standard [9] is used to obtain KIC values in plane-strain for the displacement mode of the opening cracking. However, it is not always possible to prepare such specimens when the analyzed material does not have the proper dimensions [10], even at room temperature, standard tests for KIC are difficult, time-consuming and costly [8].
Charpy impact energy CVN is utilized to indirectly estimate CVN data for KIC values. Then, to obtain the KIC values from the CVN data, it is necessary to select the behavior from CVN impact results, according to the interest zone, σYS of the material and the CVN energy values. Although this CVN impact test data does not represent the real fracture toughness data, this data can be used as a series of points to estimate toughness in an evaluation of fracture mechanics. Nevertheless, there are studies in the literature about estimating KIC values from correlations of CVN impact data [11-17]. KIC-CVN correlations available in published literature are applied to lower-shelf, transition zone and upper-shelf temperatures and are not applicable to wet welding. However, many of these correlations are based on the yield stress (σYS) of the material, Young´s Module (E), and correlations applied to different zones in a Charpy transition temperature curve. Thus, these correlations could be applied to different metals and wet welding.
The purpose of this study was to estimate the fracture toughness (KIC) of CVN data from different authors who employed wet welding in A36 steel and compared with CVN values obtained in this study. A36 steel and E6013 electrodes were utilized to construct T-welded connections. Then, a rectangular grinding was carried out at the weld toe with two depths, 6 mm and 10 mm. The rectangular grinding was filled with wet welding simulating seawater at depths of 50, 70 and 100 m. Standard Charpy specimens were extracted to obtain energy values. In addition, a search of Charpy CVN values using A36 steel and E6013 electrodes was performed with wet welding. Finally, KIC -CVN correlations were presented to measure the fracture toughness.
2. Experimental Procedure
2.1. Wet welding
T-welded connections of A36 steel were manufactured in dry conditions. The T-welded connections were welded employing E6013 electrodes following the procedure detailed by Terán et al. [17,18] and conforming to the welding procedure specification (WPS) AWS D.1.1/D1.1M code [19]. In Figure 1a, T-welded connections and Charpy specimens are graphically presented. The rectangular grinding was carried out with a manual grinder machine employing 4 mm of width. Two different grinding depths of 6 mm and 10 mm, corresponding to 30% and 50% of the plate thickness, respectively, were carried out at the weld toe of the T-welded connections. Then, underwater wet welding was employed with three different water depths of 50 m, 70 m and 100 m. The wet welding method was done according to [18,20]. A hyperbaric chamber was employed to simulate the water depths, see Figure 1b. Inside of the chamber, a gravity welding system (GWS) was used to fill the rectangular grinding with wet welding, as illustrated in Figure 1c. The E6013 electrodes were used with diameters of 2.4 mm and 3.2 mm and the length of each electrode was 350 mm. The electrodes were coated with vinylic varnish. Variables used in wet welding are presented in Table 1. The polarity was from a direct current. A T-welded connection, after applying wet welding, is presented in Figure 1d.
a) Charpy specimen extraction in T-welded connection, units in mm; b) Hyperbaric chamber; c) Gravity welding system (GWS) inside the chamber; and d) grinding filled with wet welding in T-welded connections.
To obtain CVN values, standard specimens for Charpy V-noth (CVN) were extracted at the weld toe. Charpy tests were performed at a test temperature of 20 °C. A Charpy model 74 machine with a capacity of 0.0-274 ft-lb conforming to the recommendation of ASTM E23 [21] was employed. Charpy specimen’s dimensions were 10 mm × 10 mm × 55 mm. For each grinding and water depth, three Charpy test were conducted.
2.2. KIC-CVN correlations
A review has been conducted to obtain KIC-CVN correlations. These were taken into the studying zone in the energy-temperature curve. Lower shelf and transition zones were considered because different authors conducted their impact test from -1 °C to 0 °C [22-29]. Also, there are studies for temperatures in the transition zone and upper zone [30]. In this study, Charpy values were conducted at room temperature, 20 °C. The equations from a literature review where the lower shelf region and transition temperature region were considered can be seen in Table 2. Then, KIC-CVN correlations must be considered in the lower shelf, since different authors tested their Charpy tests at 0 °C. Robert-Newton [31], and INSTA [32] applied their correlations to the lower shelf region. While in the transition zone, the equations from Barsom-Rolfe [33], Marandet-Sanz [34], and Sailor-Corten [7] can be used. In the search of CVN by different authors, it has been necessary to employ the stress yield (σYS) of the material. Then, in order to make a Charpy energy values comparison and to obtain KIC values, the Barsom-Rolfe´s equation [33] was used. It is because it can be applied to all areas of the energy-temperature curve, lower shelf, transition temperature region and upper shelf for several steels. Another important consideration is that this equation considers the σYS of the material to convert KIC-CVN values. Although those KIC-CVN correlations are for base materials, they can be used in wet welding, since it is considered the brittle-ductile transition zone for steels.
KIC-CVN correlations for lower shelf regions and different zones found in published literature.
3. Results and Discussion
3.1. CVN data
Table 3 presents the Charpy CVN values and σYS of the material gathered by different authors who employed wet welding in ASTM A36 steel. It can be observed that Di Lorenzo [30] did not report the σYS values of the material. The overview of absorbed energy versus water depth is displayed in Figure 2. One objective in observing the absorbed energy and temperature data is to know the ductile-brittle behavior from the Charpy transition temperature curve of the wet welding.
Absorbed Charpy energy and yield stress (σYS) values by different authors, (units in Joules and MPa) who employed wet welding on ASTM A36 steel.
Di Lorenzo et al. [30] applied wet welding for A36 plates steel and E6013 electrodes to different meters of water columns (wcm) at 0 wcm, 20 wcm, 40 wcm and 60 wcm, which are 0 m, 19.36 m, 38.72 m and 58.08 m, of water depth, respectively. Figure 3 depicts Lorenzo’s results where he used the tangent-hyperbolic method. It is noted that CVN values decrease as water depth increases. Although in this study only Charpy specimens were assessed at 20 °C, with the CVN data of other authors and Lorenzo’s values, it is reasonable to predict the Charpy transition temperature curves for underwater wet welding at several depths.
Charpy transition temperature curves for underwater wet welding at several depths, adapted from Di Lorenzo [30].
It is well-recognized that energy absorption decreases as the water depth increases. During the wet welding process, different discontinuities can be present, such as, porosity, slag inclusion, non-metallic inclusion, or cracking. An image of a fracture surface for a Charpy specimen, as shown in Figure 4a, exhibits pores at the notch. This fracture surface was photographed after wet welding was employed. A great number of pores was observed in the weld beads (WB) on the fracture surfaces of the Charpy specimens. Figure 4b presents pores at the WB. This is due to the fast cooling of the weld, and it is difficult to eliminate these discontinuities [30]. The discontinuities reduce the energy absorbed, and, consequently, low CVN values can be anticipated as the water depth increases. Welding discontinuities, such as slag inclusions, lack of penetration, lack of fusion, cracking, undercutting and porosity, can be enlarged with the increase of depth of welding [35].
a) Charpy specimen tested with 10 mm of grinding depth and 50 m of water depth, and b) pores in the welding bead (WB).
3.2. KIC data of KIC-CVN correlations
KIC values estimated for this study are listed in Table 4 and Figure 5. In this table, KIC values are not reported by Di Lorenzo [30] because he did not report stress yield data and the Barsom-Rolfe equation [33] could not be used. This table proves that KIC values decreased as the depth increased. As presented above, this trend is because CVN values are proportionate to the KIC values and CVN decreases due to the porosity percentage, microstructure and slag produced in the wet weld beads. It is well-known that porosity is caused by gases (H2, CO and CO2) trapped during weld melting. In these gases, the pores contain 96% of H2 in volume, 0.4% of CO and 0.06% of CO2 [36]. For example, Pessoa et al. [37] found porosity values of 1% and 8% for 50 and 100 m water depths because the slag reaches the top of the weld seams by itself, due to its low density. However, due to the hydrostatic pressure, it could not reach the top of the weld seam and was retained to develop porosity. Another explanation is that, when cracking is in the welding, these cracks connect the pores in the fracture planes, resulting in low KIC values [38,39]. The toughness and ductility are more affected than yield and strength limits [40]. The following microstructure phases were identified [17,18]: ferrite with aligned second phase (FSA), sideplate ferrite (FS) and grain-boundary ferrite (GBF). These microstructures are typical of low mechanical properties according to Charpy impact test values. Therefore, in order to have high Charpy impact data and KIC values, acicular ferrite in wet weld beads must be obtained. This can be achieved if specific elements are added to the electrodes, such as titanium and boron together with an adequate concentration of oxygen and manganese [36].
It can be seen, as expected, that KIC values reported by Barsom [13] are close to the real KIC measured values. It is necessary, however, to compare this data testing with the ASTM E399 [9]. Barsom uses the σYS of the material to estimate KIC values. Using the yield stress of the material and Charpy values, it is possible to achieve more reliable results which are close to the ASTM E399 standard. In this sense, to estimate KIC-CVN values, more KIC-CVN correlations are required. Other parameters of the material in the KIC-CVN correlations, such as, σYS, ultimate tensile stress (σUTS), and hardness (HRC), as well as the microstructures could be considered. For example, Salemi et al. [41] determined that it is necessary to establish the microstructures and to better determine their mechanical behavior. If the microstructure used in the KIC-CVN correlations is not indicated, erroneous values could be obtained. Qamar [8] developed models for KIC data based on hardness (HRC) and impact energy (CVN) data. Dexter [42] measured the J value for underwater wet welds for several types of steels, electrodes and water depths using JIC compact tension specimens. In these conditions, A36 steel, E6013 electrodes and water depths of 10, 35 and 60 m are chosen. Using the conversion of J values to KIC results for water depths of 10 m, 35 m and 60 m, KIC values are 7.2 , 39.12 , and 44.50 , respectively. KIC data decreases as water depths increase, which agrees with the values presented above. On the other hand, it can be seen that there is no single fracture toughness value for steel even at a fixed temperature and loading rate as pointed out by several authors [43-45]. Thus, at room temperature, the fracture toughness values measured at high loading rates are lower than those measured at lower loading rates. Therefore, KIC can vary for the same material tested under similar laboratory conditions. As expected, the KIC values obtained in the present study can be considered effective and used in research to estimate the real fracture toughness. Therefore, this data can be taken as a starting point to estimate KIC values.
Hence, with traditional equations of KIC, it was possible to estimate KIC values and to assess traditional components. The treatment of fracture toughness data is used in the analysis of fracture mechanics and depends on the available data. This dependence makes the structural integrity evaluation difficult when only applying a simplified procedure. Data of fracture toughness cannot be available in all situations or cannot be obtained due to the lack of material or the impossibility of removing material from an actual structure. CVN testing is less demanding than KIC testing in terms of experimental complexity, speed, and cost [8]. We know that the correlation equations are based on base materials without welding. However, there are no other equations proposed to obtain KIC data, thus, these equations will serve to estimate KIC data and could be applied for several metals and wet welding. In these circumstances, the Charpy impact data can be all the available and reliable correlation between the Charpy impact energy and the fracture toughness that should be found [30].
The Charpy impact test will be used to indirectly estimate the fracture toughness of metals. It is necessary to make a KIC direct measurement and compare the KIC correlations values with standard specimens. However, because of the relative difficulty and expense of these tests, the Charpy test will probably continue to be used. The correlation between the Charpy CVN and KIC fracture toughness will be topics for future study due to the importance of KIC in the LEFM. In addition, this standard characterizes the critical value of the crack driving force at the initiation of crack extension, and this allegedly represents a material property that is transferable from a test specimen to a structure [45].
For the sake of illustration, Figure 6 shows normalized boxplot graphs of the distribution of the variables involved in the experiment of this study. In the Equation 1 [46], it was used to normalize the variables [46]:
In the equation above, is the normalized value of the variable, is the actual value, is the minimum value and is the maximum value. The boxplot graph is divided by minimum value, first quartile, median, third quartile and maximum. The central rectangle extends from the first to second quartile, representing the interquartile range (IQR). The rectangle and horizontal line inside the IQR display the mean and the median respectively. The summary of the experimental results is shown in Table 5 for each studied variable; this summary is useful for plotting Figure 6.
4. Conclusions
KIC values were estimated from KIC-CVN correlations from CVN impact data by authors who employed A36 steel, wet welding and E6013 electrodes. CVN impact energy and KIC values decrease as the sea depth increases. It is attributed to various discontinuities in wet welding, such as porosity, slag-inclusion, non-metallic inclusion and cracking. Although the equations of KIC-CVN correlations did not specify that they can apply to wet welding, the KIC values obtained by Barsom could be considered the closest values in order to compare them with the ASTM E369 standard specimens. This is because they use values from Charpy (CVN) in all zones of the absorbed energy curve, and the yield stress of the material. It is necessary to conduct or develop further correlation equations to introduce different mechanical properties, such as, σYS, σUTS, hardness (HRC) and define microstructure. It is noted that there is no singles fracture toughness value for steels, nor a fixed temperature, Charpy CVN data and water depths. A relatively accurate KIC -CVN correlation can be a useful tool in the MFLE. CVN testing is less demanding than KIC testing in terms of experimental complexity, speed, and cost. Then, traditional equations to estimate KIC data will be used. It is due to KIC representing a mechanical material property that it could be transferable from a test specimen to a structure.
Acknowledgements
The authors would thank to the ESIQIE-IPN, CONACYT-México and IMP for financial and material support.
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Publication Dates
-
Publication in this collection
Sept 2017
History
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Received
01 June 2017 -
Accepted
12 Sept 2017