To mitigate against scour hole formation, scour protection can be placed around offshore wind turbine monopiles. Few studies have considered the beneficial effect of this geotechnical reinforcement measure on the foundation lateral resistance. The contribution of scour protection to lateral resistance of monopiles in sand is investigated in this paper using centrifuge tests and finite element analyses. Multiple scour protection widths and thicknesses are modelled around a monopile, to identify the most effective scour protection properties at mitigating lateral displacements. Two methods for modelling scour protection effects (one using material, the other using direct overburden pressure) are compared. The lateral response of monopiles with different slenderness ratios under various scour protection widths and overburden pressures are simulated. Results suggest that pile lateral displacements reduce by up to 41% when scour protection with width 2D (D, pile diameter) and applied overburden pressure of 30 kPa is used, compared to no scour protection, for a given test case. A method to modify design approaches to consider the beneficial contribution of scour protection on pile lateral behaviour using an envelope diagram is proposed, which provides relationships for scour protection properties and various monopile slenderness ratios.

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Ghost is unavoidable in marine seismic data acquisition, limiting the bandwidth of useful information and reducing the resolution of imaging results. In the deghosting method, the 3D algorithms can better eliminate the 3D effect compared with the conventional 2D algorithm. However, the 3D algorithm requires dense sampling in the crossline direction, which means greater storage space and computational cost. In this paper, we propose a pseudo-3D deghosting method to get rid of the limitation of dense spatial sampling. We arrange the conventional 2D multi-shot gathers in the form of 3D data cube by time, offset and shot number to achieve simultaneous deghosting for multi-shot gathers; We also introduce a sparse transform based L1 constraint to avoid local minimum. The basic idea of our method is including the information of the common offset gathers (COGs) into the deghosting to improve the inversion accuracy. The proposed method is easy to implemented without any pre-processing, and field example demonstrates the effectiveness of the proposed method.

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Three-dimensional topological insulators (3D TIs) represent states of quantum matters in which surface states are protected by timereversal symmetry and an inversion occurs between bulk conduction and valence bands. However, the bulk-band inversion, which is intimately tied to the topologically nontrivial nature of 3D Tis, has rarely been investigated by experiments. Besides, 3D massive Dirac fermions with nearly linear band dispersions were seldom observed in TIs. Recently, a van der Waals crystal, ZrTe₅, was theoretically predicted to be a TI. Here, we report an infrared transmission study of a high-mobility [∼33,000 cm²/(V · s)] multilayer ZrTe₅ flake at magnetic fields (B) up to 35 T. Our observation of a linear relationship between the zero-magnetic-field optical absorption and the photon energy, a bandgap of ∼10 meV and a √B dependence of the Landau level (LL) transition energies at low magnetic fields demonstrates 3D massive Dirac fermions with nearly linear band dispersions in this system. More importantly, the reemergence of the intra-LL transitions at magnetic fields higher than 17 T reveals the energy cross between the two zeroth LLs, which reflects the inversion between the bulk conduction and valence bands. Our results not only provide spectroscopic evidence for the TI state in ZrTe₅ but also open up a new avenue for fundamental studies of Dirac fermions in van der Waals materials.

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In recent decades, a number of centrality metrics describing network properties of nodes have been proposed to rank the importance of nodes. In order to understand the correlations between centrality metrics and to approximate a high-complexity centrality metric by a strongly correlated low-complexity metric, we first study the correlation between centrality metrics in terms of their Pearson correlation coefficient and their similarity in ranking of nodes. In addition to considering the widely used centrality metrics, we introduce a new centrality measure, the degree mass. The mth-order degree mass of a node is the sum of the weighted degree of the node and its neighbors no further than m hops away. We find that the betweenness, the closeness, and the components of the principal eigenvector of the adjacency matrix are strongly correlated with the degree, the 1st-order degree mass and the 2nd-order degree mass, respectively, in both network models and real-world networks. We then theoretically prove that the Pearson correlation coefficient between the principal eigenvector and the 2nd-order degree mass is larger than that between the principal eigenvector and a lower order degree mass. Finally, we investigate the effect of the inflexible contrarians selected based on different centrality metrics in helping one opinion to compete with another in the inflexible contrarian opinion (ICO) model. Interestingly, we find that selecting the inflexible contrarians based on the leverage, the betweenness, or the degree is more effective in opinion-competition than using other centrality metrics in all types of networks. This observation is supported by our previous observations, i.e., that there is a strong linear correlation between the degree and the betweenness, as well as a high centrality similarity between the leverage and the degree.@en