In this article, a layered shell element-based, elastic finite element method for predicting welding distortion in multi-pass welding is developed. The welding distortion generated in each pass can be predicted by employing layer-by-layer equivalent plastic strains as thermal expansion coefficients and using the heat-affected zone (HAZ) width as the mesh size. The final distortion can be expressed as the sum of the distortions for each pass. This study focuses on extraction of the equivalent plastic strain and HAZ width through 3D thermal elastic plastic analysis (TEPA) for each pass. The input variables extracted from each pass can be converted and added to simulate the final distortion of the multi-pass welding. A 10 mm thick, multi-pass butt-welded joint, subjected to three passes, is simulated via the proposed method. The predicted welding distortion is compared with the 3D TEPA results and the measured experimental data. The outcome indicates that good agreement can be obtained.

This paper presents an investigation of sloshing loads acting on liquid cargo tanks based on classification rules and numerical simulations. For the design of liquid cargo tanks, sloshing load is one of the key factors that should be considered. To reduce the sloshing load and motion of the contained liquid, internal structures such as bulkheads and baffles are commonly installed in the tanks. In classification rules, methodologies to estimate the sloshing loads are proposed considering the design parameters related to these internal structure members. In this paper, we carefully investigate the limitation of classification rules through smoothed particle hydrodynamics. Our investigations focus on the impact of the design parameters on sloshing loads, the patterns of the free surface, and the characteristics of velocity distribution in the tank. Through the obtained results, it is identified that the existing classification rules lack consideration for the design parameters that affect the sloshing loads and fluid characteristics in the tank. This result provides a better understanding of the existing classification rules and their limitations. It can contribute to foundational data for the future revision of classification rules.