Theory, Method and Engineering Application of Computational Mechanics in Offshore Structures II

A cryogenic hose is used to transport liquefied natural gas at sea, where flexible fittings are sealed by corrugated lining and end flange welding. However, the extreme cryogenic temperatures of the conveyed fluid introduce substantial challenges to the integrity of the fitting seals’ structure during the LNG transfer process. In order to study the sealing performance of the fitting under LNG conveying conditions, this paper was based on the general finite element software ABAQUS 6.11 to carry out a thermo-mechanical coupling analysis of the end sealing stress. This paper also established a sealing performance analysis model of the corrugated fitting welding area under the fitting action of LNG load and internal pressure load. A sensitivity analysis was conducted on the influence of weld clearance, blunt edge size, and weld residual height on the weld stress of a fitting ring. The results show that, under the combined action of the medium internal pressure and cryogenic load, the size design of the weld area significantly affects the sealing performance of the fitting, among which the equivalent force of the weld clearance butt sealing area has the greatest impact. Moreover, it was found that a pressure of 5 MPa was 2 mm when the weld clearance was 2 mm, and the average stress at the weld was 53.68 MPa. Further, considering the synergistic influence of the blunt edge size, the weld clearance was 3 mm, the stress was minimal when the blunt side size was 4 mm, and the average stress was 17.42 MPa. These research results can serve as a reference for the design and analysis of the sealing structure of non-adhesive inner corrugated cryogenic hose fittings. Full article

The reliability of liquefied natural gas (LNG) storage tanks is an important factor that must be considered in their structural design. Concrete is a core component of LNG storage tanks, and the geometric uncertainty of concrete aggregate material has a significant impact on their reliability. However, owing to the significant size difference between the concrete aggregate compared to the LNG storage tank, structural analysis using an accurate finite element model that includes all the geometric characteristics of the aggregate incurs significant analytical costs. In particular, for reliability analysis requiring a large number of samples, the computational costs incurred by finite element models are infeasible. Therefore, a dual acceleration strategy based on the asymptotic homogenization method and surrogate model technology is proposed to improve the efficiency of LNG storage tank reliability analysis. In the cross-scale analysis of a LNG storage tank based on asymptotic homogenization, order reduction of the LNG storage tank analysis model was realized. Based on this, a surrogate model construction method with the aggregate fraction and mass moment as inputs was proposed to further accelerate the reliability analysis of LNG storage tanks. Subsequently, a Monte Carlo method was used to perform a reliability analysis of the LNG storage tank considering the uncertainty of the concrete aggregate geometry and distribution under the action of liquid weight and wind load. The analysis showed that the wind load has a significant influence on the safety of the design of the roof of a LNG storage tank. The directionality of the wind load has a significant impact on the distribution of the sample point response for reliability analysis and the failure mode of the LNG storage tank. Owing to the directionality of the wind load, the response distributions of the maximum displacement and maximum stress of LNG were more concentrated, and the reliability of the LNG storage tank decreased after considering the wind load. In particular, the stress reliability of the tank decreased by 5.86%. When only the liquid load was considered, the maximum displacement and stress exhibited asynchronous failure, and the two almost never occurred simultaneously. When the wind load was considered, the failure mode of the LNG storage tank was dominated by the maximum stress. Moreover, the numerical example also demonstrated that the degree of freedom involved in structural analysis, as well as the time of structural analysis can be significantly reduced. So, the proposed cross-scale analysis framework can significantly improve the efficiency of reliability analysis. The conclusions established in this study provide theoretical and methodological guidance for the reliable design of LNG storage tanks. Full article

Due to inherent nonlinearities within floating systems and the second-order wave forces affecting them, the dynamic responses of floating systems manifest as bimodal Gaussian processes. Consequently, the classical spectral fatigue assessment method grounded in the Rayleigh distribution cannot be applied. This paper introduces the double frequency coupled (DFC) method as a spectral fatigue assessment approach, providing an accurate estimation of fatigue damage originating from bimodal Gaussian processes. Within the DFC method, the bimodal Gaussian process is partitioned into two components: low-frequency (LF) and high-frequency (HF) processes. A Gaussian distribution is employed to describe the probability distribution function (PDF) of the amplitude reduction induced by the interaction between LF and HF processes. The PDF of small-cycle fatigue can be computed by convoluting the PDF of HF amplitudes and the reduction amplitude between LF and HF. Similarly, the PDF of large-cycle fatigue can be determined through convolution, which involves the PDF of LF amplitudes and small-cycle fatigue. The overall fatigue damage arising from the bimodal Gaussian process is obtained by directly summing the contributions of small-cycle and large-cycle fatigue. Numerical investigations of the DFC method’s effectiveness are presented through a series of parametric studies, demonstrating its robustness, efficiency, and accuracy within engineering expectations. Furthermore, the DFC method is found to be applicable to both single-slope and two-slope S-N curves. Full article

Deep-water flexible composite pipes have been widely employed in the domain of deep-water oil and gas transportation, and high-density polyethylene (HDPE) is used to seal the inner sheath of internal oil and gas media containing H₂S and CH₄, due to its favorable barrier properties and mechanical properties. The morphological evolution of HDPE during the extrusion process exerts a direct impact on the material’s barrier properties. The grand canonical Monte Carlo (GCMC) approach and the molecular dynamics (MD) method were coupled in this study to examine the morphological evolution of HDPE under various shear rates as well as the penetration of methane (CH₄) in HDPE under various shear rates. The results indicate that with an increase in shear rate, the HDPE undergoes decoupling, leading to the formation of a densely arranged, rigidly oriented structure. Gas solubility and diffusion coefficients exhibit an initial increase followed by a subsequent reduction as the shear rate increases, which corresponds to the evolution of microscopic morphology. The current simulation can effectively forecast the microscopic morphology and material permeability coefficient and provide valuable insights for enhancing the barrier effectiveness of the inner sheath. Full article

Three-dimensional path planning is instrumental in path decision making and obstacle avoidance for deep-sea mining vehicles (DSMV). However, conventional particle swarm algorithms have been prone to trapping in local optima and have slow convergence rates when applied to underwater robot path planning. In order to secure a safe and economical three-dimensional path for the DSMV from the mining area to the storage base in connection with innovative mining system, this paper proposes a multi-objective optimization algorithm based on improved particle swarm optimization (IPSO) path planning. Firstly, we construct an unstructured seabed mining area terrain model with hazardous obstacles. Consequently, by considering optimization objectives such as the path length, terrain undulation, comprehensive energy consumption, and crawler slippage rate, we convert the path planning problem into a multi-objective optimization problem, constructing a multi-objective optimization mathematical model. Following that, we propose an IPSO algorithm to tackle the multi-objective non-linear optimization problem, which enables global optimization for DSMV path planning. Finally, we conduct a comprehensive set of experiments using the MATLAB simulation platform and compare the proposed method with existing advanced methods. Experimental results indicate that the path planned by the IPSO exhibits superior performance in terms of path length, terrain undulation, energy consumption, and safety. Full article