Umbilicals, which link top floaters and subsea devices, provide control functions through electrical cables and hydraulic remote transmission. These cables are considered the “lifeline” of subsea production systems for offshore oil and gas exploitation. Umbilicals should undertake self-weight and periodic loading during operation because of the severe conditions of the ocean environment. Heat is released to the umbilical body during power transmission in electric cables, which influences the mechanical properties and optical transmission in the cable. However, several sectional arrangements can be applied to a number of umbilical components. Thus, sectional layout design with multiple components should be treated as a multidisciplinary optimization problem. From the mechanical point of view, the umbilical structure should be designed with compact and symmetric layout to obtain an even probability of resistance to loads and reduce structural stress, thereby improving fatigue performance. In terms of thermal effect, these electric cables should be arranged to dissipate heat easily and avoid influence on functional and structural components. This study quantifies compactness, symmetry, and temperature distribution by introducing corresponding indices. A multidisciplinary optimization framework is then established. Particle swarm optimization (PSO) intelligent algorithm is adopted to perform optimization and obtain the optimal solution, which is superior to the initial design. The optimization design strategy is proven effective and efficient by a case study, which provides a reference for umbilical design.

The aim of this paper is to study the optimization design of a steep wave configuration based on a surrogate model for an extremely shallow water application of a flexible riser. As the traditional technique of riser configuration design is rather time-consuming and exhaustive due to the nonlinear time domain analysis and large quantities of load cases, it will be challenging when engineers address an extreme design, such as the configuration design in the case of extremely shallow water. To avoid expensive simulations, surrogate models are constructed in this paper with the Kriging model and radial basis function (RBF) networks by using the samples obtained by optimal Latin hypercubic sampling (LHS) and time domain analysis in a specified design space. The RBF model is found to be easier to construct and to show better accuracy compared with the Kriging model according to the numerical simulations in this work. On the basis of the RBF model, a hybrid optimization is performed to find the minimum curvature design with corresponding engineering constraints. In addition, an optimized design is found to meet all of the design criteria with high accuracy and efficiency, even though all of the samples associated with construction of the surrogate model fail to meet the curvature criterion. Thus, the technique developed in this paper provides a novel method for riser configuration design under extreme conditions.

A design method is presented, which aims at the optimal cross-sectional layout of the multilayer steel tube umbilical. The merit of the method is to improve the tension stiffness and the fatigue life of umbilical. An optimization model is developed for arranging each component layer of the layout by considering the symmetry of mechanical performances of components. Finite element analysis (FEA) is carried out to check the contact force and the radial deformation of different layout types and to confirm the optimal layout design.

The dynamic ice load of conical offshore wind turbines (OWTs) in cold regions is unclear. The ice force period is the key parameter used to establish an ice force model for conical structures. To obtain ice load data, a field monitoring system was installed on an OWT in a cold region in China. Based on the monitoring data, a new formula for calculating the ice force period of conical structures was established. By comparing the period calculated with this formula and the measured ice force period, it was found that the calculated data generally agreed with the measured data. Then, a random dynamic ice force model for conical OWTs can be established. Based on this ice force model, the ice-induced vibration of an OWT was analyzed with the ANSYS finite element software. The results are in good agreement with the measured data obtained from the OWT in the time and frequency domains. Therefore, the random dynamic ice force model established in this paper can be used to evaluate the ice resistance performance of conical OWTs in cold regions.

Umbilical is an important equipment in the subsea production to supply a connection between the floater and the subsea well. Analyzing strength and fatigue behaviors under bending is a key requirement to assure safety. An analytical model is proposed for predicting the bending behavior of a steel tube wounded helically around a frictionless cylinder. A full three-dimensional (3D) finite element (FE) model of an umbilical is developed by considering the frictions and contacts among its components. The numerical results of the bending stress of a steel tube were validated against that of the analytical model. The impacts of friction coefficients on the bending stress, contact pressure, and friction stress have been further investigated by the established FE model.

Recently, the flexible cryogenic hose has been preferred as an alternative to exploit offshore liquefied natural gas (LNG), in which helical corrugated steel pipe is the crucial component with C-shaped corrugation. Parametric finite element models of the LNG cryogenic helical corrugated pipe are established using a three-dimensional shell element in this paper. Considering the nonlinearity of cryogenic material and large geometric structural deformation, mechanical behaviors are simulated under axial tension, bending, and internal pressure loads. In addition, design parameters are determined to optimize the shape of flexible cryogenic hose structures through sectional dimension analysis, and sensitivity analysis is performed with changing geometric parameters. A multi-objective optimization to minimize stiffness and stress is formulated under operation conditions. Full factorial experiment and radial basis function (RBF) neural network are applied to establish the approximated model for structure analysis. The set of Pareto optimal solutions and value range of parameters are obtained through nondominated sorting genetic algorithm II (NSGA-II) under manufacturing and stiffness constraints, thereby providing a feasible optimal approach for the structural design of LNG cryogenic corrugated hose.