This study investigated the effect of laser shock peening (LSP) treatment on the fatigue performance of Q355D steel butt-welded joints. The results demonstrate that LSP sig-nificantly enhances joint fatigue resistance through gradient hardening in surface lay-ers, introduction of high-magnitude residual compressive stress fields, and micro-structural refinement. Specifically, microhardness increased across all joint zones with gradient attenuation of strengthening effects within an approximately 700 μm depth. LSP effectively suppressed residual tensile stress concentration in regions beyond 4 mm on both sides of the weld. Fatigue tests confirmed that LSP substantially extended joint fatigue life: by 113–165% in the high-stress region (250–270 MPa) and 46–63% in the medium-low-stress region (230–240 MPa). Fractographic analysis further revealed reduced fatigue striation spacing and lower microcrack density in LSP-treated speci-mens, reflecting the synergistic effect of residual compressive stress fields and micro-structural refinement in retarding crack propagation. This work substantiates LSP as an effective method for enhancing fatigue resistance in Q355D steel welded joints.

DH36 high-strength steel is widely used in shipbuilding and other fields due to its excellent strength, low-temperature toughness, wear resistance, and corrosion resistance. However, the harsh deep-sea environment seriously reduces the service life of welds. In this study we subjected DH36 welded joints to laser shock peening at three different energy levels (5 J, 7 J, 9 J) to investigate its effects on microhardness, microstructure, high-cycle fatigue, and residual stress of the DH36 welded joints. Results indicate that LSP can significantly enhance the surface microhardness of welded joints. Notably, the 7 J energy treatment increased the weld zone microhardness from 195 HV_0.2 to 231 HV_0.2 (18.5% improvement) and the heat-affected zone microhardness from 194 HV_0.2 to 234 HV_0.2 (20.6% improvement). Residual tensile stress on the specimen surface was offset and replaced by residual compressive stress after LSP. Concurrently, the high-cycle fatigue limit of the specimens was significantly improved, with the most pronounced improvement observed in specimens subjected to 5 J energy—increasing from 258 MPa to 295 MPa, representing an increase of 14.34%.

The construction cost of offshore wind farms (OWFs) is heavily influenced by vessel scheduling and meteorological uncertainties. To address these challenges, this paper proposes a constraint-driven hierarchical optimization framework for the coordinated scheduling of installation vessels (IVs) and transport vessels (TVs). First, a Mixed-Integer Linear Programming (MILP) model is established to describe the operational constraints, which is then decomposed into two interrelated sub-problems: vessel path planning and scheduling optimization. For path planning, the problem is modeled as a Multiple Traveling Salesman Problem (MTSP) to ensure balanced fleet workloads. This stage is solved via a tailored three-stage heuristic combining balanced sweep clustering and penalized local search. For scheduling optimization, a hybrid Earliest Deadline First (EDF)-Simulated Annealing (SA) strategy is employed, where EDF generates a strictly feasible baseline to warm-start the SA optimization. Furthermore, a stochastic optimization approach integrates historical meteorological data to ensure schedule robustness against weather uncertainty. The validity of the framework is supported by two real-world OWF cases, which demonstrate total cost reductions of 15.44% and 13.20%, respectively, under stochastic weather conditions. These results demonstrate its effectiveness in solving high-constraint offshore engineering problems.