Journal of Ocean Engineering and Science最新文献

Deep-sea submersibles are significant mobile platforms requiring multi-functional capabilities that are strongly determined by the constituent materials. Their cylindrical protective cover can be advanced by designing their sandwiched cellular materials whose physical properties can be readily parameterized and flexibly tuned. Porous honeycomb materials are capable of possessing tuned positive, negative, or zero Poisson's ratios (PPR, NPR, and ZPR), which is expected to produce distinct physical performance when utilized as a cellular core of cylindrical shells for the deep-sea submersibles. A novel cylindrical meta-structure sandwiched with the semi-re-entrant ZPR metamaterial has been designed as well as its similarly-shaped sandwich cylindrical shell structures with PPR and NPR honeycombs. The mechanical and vibroacoustic performance of sandwich cylindrical shells with cellular materials featuring a full characteristic range of Poisson's ratios are then compared systematically to explore their potential for engineering applications on submerged pressure-resistant structures. The respective unit cells are designed to feature an equivalent load-bearing capability. Physical properties of pressure resistance, buckling, and sound insulation are simulated, respectively, and the orders of each property are then generalized by systematic comparison. The results indicate that the PPR honeycomb core takes advantage of higher structural strength and stability while the ZPR one yields better energy absorption and sound insulation behavior. The NPR one yields moderate properties and has the potential for lower circumferential deformation. The work explores the application of cellular materials with varied Poisson's ratios and provides guidance for the multi-functional design of sandwich cylindrical meta-structures.

In the field of maritime transport, motion and energy, the dynamics of deep-sea waves is one of the major problems in ocean science. A mathematical modeling of dynamics of solitary waves in deep sea under the two-layer stratification leads to NLS equation, and consequently, the interaction two of them can be formulated by coupled NLS equation. In this work, extended auxiliary equation and the $exp(-\varpi \left(\chi \right))$-expansion methods are employed to make the optical solutions of the Manakov model of coupled NLS equation. The methods used in this paper, in addition to providing the analysis of individual wave solutions, also provide general optical solutions. Some previously known solutions can be obtained by some special selections of parameters obtained by solving systems of algebraic equations. At this stage, it is more practical and convenient to apply methods with a symbolic calculation system.

Ensuring accurate parameter identification and diving motion prediction of marine crafts is essential for safe navigation, optimized operational efficiency, and the advancement of marine exploration. Addressing this, this paper proposes an instrumental variable-based least squares (IVLS) algorithm. Firstly, aiming to balance complexity with accuracy, a decoupled diving model is constructed, incorporating nonlinear actuator characteristics, inertia coefficients, and damping coefficients. Secondly, a discrete parameter identification matrix is designed based on this dedicated model, and then a IVLS algorithm is innovatively derived to reject measurement noise. Furthermore, the stability of the proposed algorithm is validated from a probabilistic point of view, providing a solid theoretical foundation. Finally, performance evaluation is conducted using four depth control datasets obtained from a piston-driven profiling float in Qiandao Lake, with desired depths of 30 m, 40 m, 50 m, and 60 m. Based on the diving dynamics identification results, the IVLS algorithm consistently shows superior performance when compared to recursive weighted least squares algorithm and least squares support vector machine algorithm across all depths, as evidenced by lower average absolute error (AVGAE), root mean square error (RMSE), and maximum absolute error values and higher determination coefficient ($R^2$). Specifically, for desired depth of 60 m, the IVLS algorithm achieved an AVGAE of 0.553 m and RMSE of 0.655 m, significantly outperforming LS-SVM with AVGAE and RMSE values of 8.782 m and 11.117 m, respectively. Moreover, the IVLS algorithm demonstrates a remarkable generalization capability with $R^2$ values consistently above 0.95, indicating its robustness in handling varied diving dynamics.

Turbulence is strongly associated with the vast majority of fluid flows in nature and industry. Traditionally, results given by the direct numerical simulation (DNS) of Navier-Stokes (NS) equations that relate to a famous millennium problem are widely regarded as ‘reliable’ benchmark solutions of turbulence, as long as grid spacing is fine enough (i.e. less than the minimum Kolmogorov scale) and time-step is small enough, say, satisfying the Courant-Friedrichs-Lewy condition (Courant number $<$ 1). Is this really true? In this paper a two-dimensional sustained turbulent Kolmogorov flow driven by an external body force governed by the NS equations under an initial condition with a spatial symmetry is investigated numerically by the two numerical methods with detailed comparisons: one is the traditional DNS, the other is the ‘clean numerical simulation’ (CNS). In theory, the exact solution must have a kind of spatial symmetry since its initial condition is spatially symmetric. However, it is found that numerical noises of the DNS are quickly enlarged to the same level as the ‘true’ physical solution, which finally destroy the spatial symmetry of the flow field. In other words, the DNS results of the turbulent Kolmogorov flow governed by the NS equations are badly polluted mostly. On the contrary, the numerical noise of the CNS is much smaller than the ‘true’ physical solution of turbulence in a long enough interval of time so that the CNS result is very close to the ‘true’ physical solution and thus can remain symmetric, which can be used as a benchmark solution for comparison. Besides, it is found that numerical noise as a kind of artificial tiny disturbances can lead to huge deviations at large scale on the two-dimensional Kolmogorov turbulence governed by the NS equations, not only quantitatively (even in statistics) but also qualitatively (such as spatial symmetry of flow). This highly suggests that fine enough spatial grid spacing with small enough time-step alone could not guarantee the validity of the DNS of the NS equations: it is only a necessary condition but not sufficient. All of these findings might challenge some of our general beliefs in turbulence: for example, it might be wrong in physics to neglect the influences of small disturbances to NS equations. Our results suggest that, from physical point of view, it should be better to use the Landau-Lifshitz-Navier-Stokes (LLNS) equations, which consider the influence of unavoidable thermal fluctuations, instead of the NS equations, to model turbulent flows.