1. Introduction
Since January 2020, the International Maritime Organization (IMO) has been applying a stricter standard for the sulfur content of ship fuel oil, finally announcing a plan to restrict the sulfur content of ship fuel oil from the current level of 3.5% to 0.5% in 2020. Around the world, each country has legislated the IMO 2020 standards, and is applying more stringent regulations to voluntarily designated emission control areas rather than other sea areas. Major domestic and international carriers are complying with IMO’s strict environmental regulations by considering the pros and cons of various alternatives such as installing a scrubber, using low-sulfur oil, or using LNG.
As eco-friendliness has become an international trend, a dramatic energy transition is taking place around the world and the demand for liquefied natural gas (LNG) is also increasing in the shipping sector. The bunkering industry (i.e., refueling LNG to LNG-powered ships), is also emerging around the world. The equipment applied to an LNG propulsion ship can be broadly divided into engines, fuel tanks, fuel supply systems, and fuel supply control systems. A shipbuilder or shipowner makes an order in a packaged type, in which a tank or supply system can be directly installed onto a ship. However, high-quality products with special materials and structural technologies for cryogenic operability are needed, since operational disruption or anchoring due to equipment failure can cause significant economic losses [
1,
2,
3,
4].
The LNG storage tank has a cryogenic structure, and 9% Ni steel (which has excellent mechanical properties and fatigue strength at room temperature as well as in low temperature environments) is most often used as the material for the inner tank. The 9% Ni steel has excellent impact toughness and fatigue strength in a cryogenic environment, and is widely used in the production of LNG storage tanks due to its low material price compared to steel density. When using 9% Ni steel, it is recommended the absorption energy specified in domestic and international regulations should be 34 J or more at −196 °C. However, there are slight differences depending on the standard actually applied. INCO (International Nickel Co., Ltd., New York, NY, USA) in the United States first developed 9% Ni steel in 1944, and more recently Japan has been at the forefront of improvements in steel quality, developing welding technology, and continuing research on safety considering the trend of larger tank sizes [
5,
6].
The welding process of 9% Ni steel is very difficult for field engineers due to the difference between the melting point of the base metal and the welding wire. This represents the hurdle for using 9% Ni steel in its many applications. Thus, this research focuses on the determination of welding performance and suggests the optimal welding condition.
Since the welding material has a lower melting point than a base material and the welding quality is different depending on the welder’s skills, A553-1 steel welding is not easy. Therefore, it is necessary to review the issues that might occur during the welding of A553-1 steel and to prevent welding defects by evaluating the characteristics of the weldment.
This study focused the specific welding method and a material, FCAW and 9% nickel steel. For analyzing the welding quality, the hardness of the upper welding part after welding (which is known to be vulnerable to cracks due to ‘weldment hardening’) was defined. Furthermore, that concept was used as an output variable for determination formula in order to evaluate the welding quality. Many parameters related to the welding process were used as input variables. By optimizing those input variables based on that determination formula and multi objective optimization algorithm, improved welding qualities were obtained.
This study was related the previous research which evaluated the weldability with solidification crack susceptibility [
7], and used similar evaluating methods such as welding test and optimization. However, it focused on weldment hardening as an evaluating method differently.
Naturally, the previous studies are similar to past research [
7]. Yun [
8] performed the optimization of fillet laser welding for 9% Ni steel, and Na [
9] compared GTAW and FCAW for 9% Ni steel. Kim [
10] designed the LNG fueled ship with 9% Ni steel and evaluated the welding performance. Watanabe [
11] performed a double tension test for a surface notch of A553-1 steel. X Liu et al. [
12] performed a study to measure and analyze the fracture toughness of metals by using machine learning models such as regression trees and neural networks. Oliveira [
13,
14] evaluated the mechanical properties that changed according to the micro-evolution occurring in the gas tungsten arc welding process, analyzed the process of material ductility by the refined grain structure in the fusion zone, and studied how low hardness can cause breakage. Kim evaluated the GMA welding performance with deep learning methods [
15], and Zhu used deep learning-based classification for checking the defects of weld surface [
16].
In previous studies, the correlation between diverse variables and mechanical characteristics applied to the welding process of cryogenic steels such as STS series or Ni alloy series has been reviewed and the process problems and quality deterioration that occurred when those were used in the LNG-related equipment were also reviewed. However, the previous research on weldment quality in cryogenic steel has not reflected the complex alternating effects, and most studies concern the application of automation, high melting, or high speeds to compensate for the disadvantages of manual welding [
17,
18]. In addition, research on the correlation between bead geometry and weldability has been performed in previous studies to improve welding quality by establishing the key factors affecting bead formation. However, similar size areas and heat-affected zones are derived intermittently even for different welding process variables, so the applicability of analysis and consideration limited to bead geometry in the actual field has been reduced.
In this way, an analysis based on various perspectives is needed to clearly identify the specific conditions that can have a similar bead geometry compared to the intermittent variables, and it is necessary to identify the phenomenon in which the structure of a weldment is hardened by matching the characteristics generated from the correlation between the partially divided bead geometry within a weldment to the dilution ratio of a weldment.
In 9% Ni steel, a higher dilution ratio of the base material leads to lower strength. For this reason, to guarantee the required strength, excessive dilution of the base material should be avoided. Although prior studies on the correlation between dilution ratio and strength have found that tensile strength does not change dramatically even when there is 10–20% change in the dilution ratio, it has been reported that strength may drop below the API standard of 363 MPa due to the hardening of the weldment if the dilution ratio is 25% or more [
19,
20].
Therefore, in this study, the dilution ratio formed in the weldment was calculated for the flux cored arc welding process applied to 9% Ni, a cryogenic steel, and the phenomenon in which a hardened weldment is created compared to the heat-affected zone was identified in a procedure based on the calculated dilution ratio. This study tried with purpose a method for quantitatively evaluating the quality of weldments. Therefore, the bead geometry, hardness, and dilution rate were analyzed for the welded part (which was tested by applying various process variables), and the correlation of the tendency of the quality of the welded part to deteriorate was derived. In addition, the raw data collected to quantify the quality deterioration characteristics of the collected welds was trained by the discriminant function. The effects contained in the process variables were predicted, and the quality deterioration characteristics were based on the process variables [
21,
22,
23]. If this as expected, we have also proposed a multipurpose algorithm that can be systematically avoided.