This study presents a traceable global–local finite element (FE) framework for assessing stern-boss structural integrity under operationally derived loading. Two production-scale MSC Nastran models—a shell-dominant model and an otherwise equivalent global model with a locally solid stern-boss region—were compared under five vessel-specific states generated from trim-and-stability weight, buoyancy, hydrostatic, ballast, and machinery-load distributions. Baseline-to-fine mesh changes were limited to 0.68% for the shell model and 1.07% for the solid model. Both models reproduced the same global deformation mode, while the solid model predicted 5.9–6.3% greater maximum vertical deflection. Within a common stern-boss assessment region, the shell and solid peak von Mises stresses were 42.1–70.9 MPa and 41.5–72.4 MPa, respectively, with differences confined to −1.4% to +2.3%. By contrast, stresses extracted at the stern-tube interface were 17.2–26.8 MPa in the shell model and 29.7–46.6 MPa in the solid model, demonstrating the importance of three-dimensional constraint, transverse shear, and through-thickness response at the local interface. The governing design-draught/APT-full condition produced a solid-model deflection of 46.8 mm and a regional stress of 72.4 MPa. Its nominal SS400 yield-utilization ratio was 0.308, whereas the LR rule-based inverse safety-factor index ranged from 1.3 to 2.1 and identified surrounding panel buckling as the more restrictive limit state. The shell model reduced wall-clock time by 38.6% and is therefore appropriate for global screening, while the solid representation is required for interface-level assessment. The framework constitutes a numerically verified, digital-twin-compatible baseline; independent validation against measured structural or shaft-line data remains necessary.
Abstract This study presents an Advanced Actor-Critic (AAC) reinforcement-learning framework for automating linear support-type selection in piping stress analysis for shipbuilding and offshore systems. In practice, improper support configurations often result in excessive stress, displacement, or nozzle loads, leading to repeated manual redesign cycles. The proposed framework aims to reduce these iterations by learning consistent and code-compliant support-type decisions directly from analysis feedback. The AAC framework enhances a Vanilla Actor-Critic (VAC) structure through domain-driven improvements that stabilize learning and improve adaptability across thermal and mechanical load cases. These include adaptive advantage control, stabilized long-horizon reward evaluation, retention of effective behaviors under changing operating conditions, and modeling of interactions among distributed supports within the piping configuration. Applications to cryogenic and high-temperature piping systems show that the trained policy reduces redesign iterations and improves first-pass structural code compliance compared with a VAC baseline. The framework provides stable, interpretable, and practically deployable support-type decisions for automated piping stress design.
Abstract This study presents a time domain hydroelastic analysis framework developed for the SnapWind floating offshore wind turbine (FOWT), a system engineered for reliable and safe long-term operation. The SnapWind substructure is represented using a detailed shell and beam finite element model that captures the local structural configuration. To enable efficient time-domain simulation, this high-fidelity model is dynamically condensed into a reduced order representation that preserves the rigid body modes and the dominant elastic modes whose eigenfrequencies align with the key wind, wave, and turbine induced load spectra. The resulting reduced order model is implemented within a commercial Integrated Load Analysis (ILA) tool and fully coupled with the wind turbine, mooring system, and inter array power cables. Hydrodynamic coefficients associated with both rigid body and elastic modes are incorporated to ensure that hydroelastic effects are consistently represented in the time domain. These responses are then used to reconstruct detailed structural quantities—such as nodal displacements and element stresses—required for fatigue assessment over the design life. A comparative fatigue study is conducted with and without the inclusion of substructure structural dynamics, demonstrating the significant influence of hydroelastic behavior on fatigue damage and underscoring the importance of accounting for structural dynamics in the design of next generation FOWTs.
In the shipbuilding and offshore industries, dimensional errors are managed based on quality management points to ensure seamless block assembly. Terrestrial laser scanners are widely used to measure these points in the field. However, owing to the massive size of ship blocks, operators often rely on empirical judgment to determine scanning positions, resulting in an excessive number of viewpoints. This inefficiency prolongs both data acquisition and computational processing times. In this study, we propose a two-stage viewpoint optimization method that combines a genetic algorithm with a greedy algorithm. In the proposed method, initial viewpoints are randomly determined according to the number of quality management points, and a genetic algorithm is then used to determine the viewpoints that maximize coverage. Subsequently, a greedy algorithm is applied to select the minimum number of viewpoints while maintaining coverage. We conducted experiments on actual ship blocks by implementing the proposed method. The results show that selecting initial viewpoints using the genetic algorithm provided only a slight improvement in coverage compared to random selection. In contrast, the greedy algorithm reduced the number of viewpoints by approximately 48.65
_ This study presents a comprehensive comparative investigation of the buckling and ultimate strength behavior of flat and curved plates subjected to longitudinal compression, utilizing nonlinear finite element analysis (FEA) with NASTRAN, ABAQUS, and ANSYS and benchmarking the results against the established rules of major classification societies including American Bureau of Shipping (ABS), Bureau Veritas (BV), Det Norske Veritas (DNV), and Germanischer Lloyd (GL). The parametric analysis was conducted on plates with an aspect ratio of 3.0, thicknesses ranging from 10 to 25 mm, widths from 800 to 1000 mm, and curvature radii from 3000 to 10;000 mm (corresponding to flank angles of 5°–45°), encompassing the typical geometric configurations found in large LNG carrier hull structures. The findings reveal that for flat plates, FEA predictions demonstrate excellent correlation with classification society rules, with mean ratios of FEA to rule-based strengths between .988 and 1.036, coefficients of variation below 5%, and coefficients of determination R2 exceeding .985, confirming the adequacy of existing empirical methods for flat plate assessment. Keywords ship structure; buckling; regulations and standards; longitudinal strength; structural analysis
