Generation and dissipation of ocean surface waves

Ocean surface waves constitute one of the most important sources of external forces that act on ships and offshore structures. Most ocean waves are generated by wind, but various other effects such as currents, ground and coastal topology, breaking and wave–wave interaction have an influence on the growth and dissipation of wave energy at specific frequency ranges. These water waves are inherently random in nature and their exact shape is difficult to describe, even when confining the described area to a small range. While many different approaches exist to describe the spectral characteristics of ocean waves, some of the processes which affect the generation of waves are still poorly understood. This paper addresses some techniques which serve to describe seaway spectra with respect to the subsequent analysis of dynamic mechanical systems in the ocean such as ships, platforms and pipelines. Advantages and limits of the different approaches are discussed. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

The determination of uncertainty levels in robust clustering of subjects with longitudinal observations using the Dirichlet process mixture

In this paper we introduce a new method to the cluster analysis of longitudinal data focusing on the determination of uncertainty levels for cluster memberships. The method uses the Dirichlet-t distribution which notably utilizes the robustness feature of the student-t distribution in the framework of a Bayesian semi-parametric approach together with robust clustering of subjects evaluates the uncertainty level of subjects memberships to their clusters. We let the number of clusters and the uncertainty levels be unknown while fitting Dirichlet process mixture models. Two simulation studies are conducted to demonstrate the proposed methodology. The method is applied to cluster a real data set taken from gene expression studies.     

The influence of shelf zone topography and coastline geometry on coastal trapped waves

The results of numerical experiments with a model of coastal trapped waves are presented to identify two important features for regional modeling of the interaction of a shelf zone with open ocean. First, a wave train of this type can be formed by wind action at a considerable distance from the place of impact. The waves propagate along a coastline without significant loss of energy, provided that the coastline and shelf zone topography have no features comparable to the Rossby radius. However, the waves lose energy while passing over capes and submarine canyons and when the shelf width decreases. For regional modeling, remote generation of waves must be thoroughly investigated and taken into account. The other feature is that the propagating waves can use part of energy to form density anomalies on the shelf by raising intermediate waters from the adjacent offshore areas of the open ocean. Thus, coastal trapped waves can carry wind energy from wind action areas to other coastal areas to form density anomalies and other types of motion.     

Residual saturated porous media – from oscillating water blobs to waves in ground earth

A model for wave propagation in residual saturated porous media is presented distinguishing enclosed fluid clusters with respect to their eigenfrequency and damping properties. The additional micro-structure information of cluster specific damping is preserved during the formal upscaling process and allows a stronger coupling between micro- and macro-scale than characterisation via eigenfrequencies alone. A numerical example of sandstone filled with air and liquid clusters of different eigenfrequency and damping distributions is given. If energy dissipation due to viscous damping dominates energy storage due to cluster oscillations, the damping distribution is more influential than the eigenfrequency distribution and vice versa. Spreading the damping distribution around a constant mean value supported the effect of capillary forces and spreading the eigenfrequency distribution around a constant mean value supported the effect of viscous damping in the investigated samples. For a wide distribution of the liquid clusters' damping properties, two damping mechanisms of propagating waves occur at the same time: damping due to viscous effects (for highly damped clusters) and energy storage by cluster oscillations (for underdamped clusters). (© 2013 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Sequential clustering with radius and split criteria

Sequential clustering aims at determining homogeneous and/or well-separated clusters within a given set of entities, one at a time, until no more such clusters can be found. We consider a bi-criterion sequential clustering problem in which the radius of a cluster (or maximum dissimilarity between an entity chosen as center and any other entity of the cluster) is chosen as a homogeneity criterion and the split of a cluster (or minimum dissimilarity between an entity in the cluster and one outside of it) is chosen as a separation criterion. An O(N ³) algorithm is proposed for determining radii and splits of all efficient clusters, which leads to an O(N ⁴) algorithm for bi-criterion sequential clustering with radius and split as criteria. This algorithm is illustrated on the well known Ruspini data set.     

Resonant triad model for studying evolution of the energy spectrum among a large number of internal waves

Internal waves are generally accepted to be responsible for a large fraction of mixing in the deep ocean. Internal waves interact nonlinearly with one another, exchanging energy among themselves to create the background internal wave spectrum. The most important mechanism resulting in the transfer of energy from one wave to another is believed to be resonant triad interactions. In this paper we consider a large number of resonantly interacting triads in order to investigate the evolution of the energy spectrum due to solely resonant triad interactions. To this end we solve the evolution equations for a large number of resonant triads to determine the temporal evolution of the energy distribution among the various possible wave numbers and frequencies. Our model involves internal waves with frequencies spanning the range of possible frequencies, i.e., between a maximum of the buoyancy frequency N for horizontal wave vectors (vertical motion) to a minimum of the inertial frequency f for vertical wave vectors (horizontal motion) [two limiting cases]. Because of the inclusion of high-frequency waves we cannot make the hydrostatic approximation. We investigate the evolution of the wave’s amplitudes to predict the evolution of the internal wave energy spectrum.     

Clustering Motion

Given a set of moving points in ^d, we show how to cluster them in advance, using a small number of clusters, so that at any time this static clustering is competitive with the optimal k-center clustering at that time. The advantage of this approach is that it avoids updating the clustering as time passes. We also show how to maintain this static clustering efficiently under insertions and deletions. To implement this static clustering efficiently, we describe a simple technique for speeding up clustering algorithms and apply it to achieve faster clustering algorithms for several problems. In particular, we present a linear time algorithm for computing a 2-approximation to the k-center clustering of a set of n points in ^d. This slightly improves the algorithm of Feder and Greene, that runs in (n log k) time (which is optimal in the algebraic decision tree model).     

A new cluster-expansion approach to the calculation of the energy structure of crystals

We propose a new approach to the calculation of energy spectra for strongly compressed or imperfect crystals in the case where the localized orbitals (LO) of atoms with different space positions overlap considerably. This approach is based on the exact orthogonalization of the LO for all atoms according to Lövdin's method and on the cluster expansion (CE). In all nth orders of the CE, we take into account the overlapping integrals (OI) of the LO for atoms belonging to the same n-particle cluster. For every n, such clusters comprise the whole crystal. For n ; , the CE converges exponentially to the OI. The two-particle cluster expansion is discussed in detail.Translated from Teoreticheskaya i Matematicheskaya Fizika, Vol. 106, No. 3, pp. 498–512, March, 1996.Translated by M. V. Chekhova.     

土壤分类的模糊集成算法与应用

土壤是一个多性状的连续体,其分类的首选方法是模糊聚类分析.但是模糊聚类分析中现有的基于模糊等价关系的动态聚类法和模糊c-均值法各有利弊,采用其中一种方法聚类肯定存在不足.为此集成两种聚类方法的优点,避其缺点,提出了用基于模糊等价关系的动态聚类方法和方差分析方法确定聚类数目和初始聚类中心,再用模糊c-均值法决定最终分类结果的集成算法,并将其应用到松花江流域土壤分类中,得到了较为切合实际的分类结果.     

Simultaneous Distributions of Space-Time Wave Characteristics in a Gaussian Sea

A simultaneous pair (L, T) is defined, representing crest length and crest period of the same random wave, i.e. the length and duration of the half of the wave that contains the crest. The simultaneous density in the ergodic sense of (L, T) is derived and evaluated for a homogeneous Gaussian spatio-temporal random sea model. Other names of this type of distribution are Palm, intensity, and long-run distribution. The density is compared to the deterministic relation given by the dispersion relation for deep water: L=T ² g/. A two-dimensional sea model parametrized by time and a single space coordinate is used, based on a directional spectrum. Only the case of deep water is considered. Furthermore, the crest height associated with the (L, T)-pair is studied. The ergodic distribution of (L, T) for significant waves is compared to that for all waves. All results are verified through comparison to simulated observations, but no real data are considered.     

Existence and Stability of Traveling Waves for Degenerate Reaction–Diffusion Equation with Time Delay

This paper deals with the existence and stability of traveling wave solutions for a degenerate reaction–diffusion equation with time delay. The degeneracy of spatial diffusion together with the effect of time delay causes us the essential difficulty for the existence of the traveling waves and their stabilities. In order to treat this case, we first show the existence of smooth- and sharp-type traveling wave solutions in the case of \(c\ge c^*\) for the degenerate reaction–diffusion equation without delay, where \(c^*>0\) is the critical wave speed of smooth traveling waves. Then, as a small perturbation, we obtain the existence of the smooth non-critical traveling waves for the degenerate diffusion equation with small time delay \(\tau >0\). Furthermore, we prove the global existence and uniqueness of \(C^{\alpha ,\beta }\)-solution to the time-delayed degenerate reaction–diffusion equation via compactness analysis. Finally, by the weighted energy method, we prove that the smooth non-critical traveling wave is globally stable in the weighted \(L^1\)-space. The exponential convergence rate is also derived.     

A comparative approach to the economic modelling of a large-scale wave power scheme

Conversion of marine energy sources, including ocean waves and tidal currents, into electricity is a rapidly developing industry. Although many technologies have been proposed and some have generated electricity at full scale, it is difficult to predict which technology will be economic at large scales of installation. Several studies have been conducted which estimate the cost of electricity on the basis of schematic designs. However, each study represents a best estimate of the future cost based on current design details and direct comparison between the results of these studies is not straightforward. A methodology for directly comparing different wave energy concepts and potential locations would be beneficial to aid investment decisions. In this study we describe how the established data envelopment analysis technique could be employed for this purpose. The developed model is employed to rank the efficacy with which several types of conceptual and prototype wave energy conversion technologies generate electricity from the wave energy resource available at UK and US sites.     

On camel-like traveling wave solutions in cellular neural networks

This paper is concerned with the existence of camel-like traveling wave solutions of cellular neural networks distributed in the one-dimensional integer lattice . The dynamics of each given cell depends on itself and its nearest m left neighbor cells with instantaneous feedback. The profile equation of the infinite system of ordinary differential equations can be written as a functional differential equation in delayed type. Under appropriate assumptions, we can directly figure out the solution formula with many parameters. When the wave speed is negative and close to zero, we prove the existence of camel-like traveling waves for certain parameters. In addition, we also provide some numerical results for more general output functions and find out oscillating traveling waves numerically.     

The geometric generalized minimum spanning tree problem with grid clustering

This paper is concerned with a special case of the generalized minimum spanning tree problem. The problem is defined on an undirected graph, where the vertex set is partitioned into clusters, and non-negative costs are associated with the edges. The problem is to find a tree of minimum cost containing at least one vertex in each cluster. We consider a geometric case of the problem where the graph is complete, all vertices are situated in the plane, and Euclidean distance defines the edge cost. We prove that the problem is strongly -hard even in the case of a special structure of the clustering called grid clustering. We construct an exact exponential time dynamic programming algorithm and, based on this dynamic programming algorithm, we develop a polynomial time approximation scheme for the problem with grid clustering.     

Double-Scan Statistics

Researchers frequently scan sequences for unusual clustering of events. Glaz et al. (2001) survey scan statistic tools developed for these analyses. Many of these tools deal with clustering of one type of event. In other applications the researcher scans for clusters of two types of events, A and B. Consider a sequence of D independent and identically distributed trials where each trial has one of four possible outcomes: A ^c B ^c , A B ^c , A ^c B, A B. When the events A and B occur within d consecutive trials, we say that a two-type d-cluster has occurred (a directional cluster is also defined that requires that the A event comes at least as early as the B event). Naus and Wartenberg (1997) develop a double scan statistic that counts the number of declumped (a type of non-overlapping) clusters that contain at least one of each of two different types of events. They derived the expectation and variance and Poisson approximation for the distribution of the double scan statistic. The approximation and declumping methods used work well when the events are relatively rare but not as well for the case where the two types of events occur with high frequency. This paper develops an alternative family of double scan statistics to count the number of non-overlapping two-type d-clusters. These new double scan statistics behave similarly to the Naus-Wartenberg statistic for rare events, but capture other information for the more dense event case. Exact and approximate results are derived for the distribution of the new double scan statistics, allowing its use for a wider range of density of events. The double scan statistics are compared for the epidemiologic application in Naus and Wartenberg, and for a molecular biology application involving genome versus genome protein hits.     

Traveling wavefronts for time-delayed reaction-diffusion equation: (II) Nonlocal nonlinearity

This is the second part of a series of study on the stability of traveling wavefronts of reaction-diffusion equations with time delays. In this paper we will consider a nonlocal time-delayed reaction-diffusion equation. When the initial perturbation around the traveling wave decays exponentially as x→−∞ (but the initial perturbation can be arbitrarily large in other locations), we prove the asymptotic stability of all traveling waves for the reaction-diffusion equation, including even the slower waves whose speed are close to the critical speed. This essentially improves the previous stability results by Mei and So [M. Mei, J.W.-H. So, Stability of strong traveling waves for a nonlocal time-delayed reaction-diffusion equation, Proc. Roy. Soc. Edinburgh Sect. A 138 (2008) 551-568] for the speed with a small initial perturbation. The approach we use here is the weighted energy method, but the weight function is more tricky to construct due to the property of the critical wavefront, and the difficulty arising from the nonlocal nonlinearity is also overcome. Finally, by using the Crank-Nicholson scheme, we present some numerical results which confirm our theoretical study.     

Guided construction search metaheuristics for the capacitated p-median problem with single source constraint

In the capacitated p-median problem with single source constraint, also known as the capacitated clustering problem, a given set of n weighted points is to be partitioned into p clusters such that the total weight of the points in each cluster does not exceed a given cluster capacity. The objective is to find a set of p centres that minimizes the total scatter of points allocated to these clusters. In this paper, a (λ, μ)-interchange neighbourhood based on the concept of λ-interchange of points restricted to μ-adjacent clusters is proposed. Structural properties of centres are identified and exploited to derive special data structures for their efficient evaluations. Different search and selection strategies including the variable neighbourhood search descent with respect to μ-nearest points are investigated. The most efficient strategies are then embedded in a guided construction search metaheuristic framework based either on a periodic local search procedure or a greedy random adaptive search procedure to solve the problem. Computational experience is reported on a standard set of benchmarks. The computational experience demonstrates the competitive performance of the proposed algorithms when compared to the best-known procedures in the literature in terms of solution quality and computational requirement.     

An application of the minimal spanning tree approach to the cluster stability problem

Among the areas of data and text mining which are employed today in OR, science, economy and technology, clustering theory serves as a preprocessing step in the data analyzing. An important component of clustering theory is determination of the true number of clusters. This problem has not been satisfactorily solved. In our paper, this problem is addressed by the cluster stability approach. For several possible numbers of clusters, we estimate the stability of the partitions obtained from clustering of samples. Partitions are considered consistent if their clusters are stable. Clusters validity is measured by the total number of edges, in the clusters’ minimal spanning trees, connecting points from different samples. Actually, we use the Friedman and Rafsky two sample test statistic. The homogeneity hypothesis of well mingled samples, within the clusters, leads to an asymptotic normal distribution of the considered statistic. Resting upon this fact, the standard score of the mentioned edges quantity is set, and the partition quality is represented by the worst cluster, corresponding to the minimal standard score value. It is natural to expect that the true number of clusters can be characterized by the empirical distribution having the shortest left tail. The proposed methodology sequentially creates the described distribution and estimates its left-asymmetry. Several presented numerical experiments demonstrate the ability of the approach to detect the true number of clusters.     

Modeling aspects and numerical analysis of offshore systems

There is a strong effort to improve the efficiency of renewable energy systems in order to reduce the CO₂ emissions. This paper addresses an approach to increase the efficiency of an ocean wave energy plant with a model based predictive controller. For this controller it is necessary to have a prediction of the ocean waves and a model of the whole system. The future development of the ocean waves is predicted by an AR-model. A system identification yields the model of the energy plant. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

One-dimensional center-based l 1-clustering method

Motivated by the method for solving center-based Least Squares—clustering problem (Kogan in Introduction to clustering large and high-dimensional data, Cambridge University Press, 2007; Teboulle in J Mach Learn Res 8:65–102, 2007) we construct a very efficient iterative process for solving a one-dimensional center-based l ₁—clustering problem, on the basis of which it is possible to determine the optimal partition. We analyze the basic properties and convergence of our iterative process, which converges to a stationary point of the corresponding objective function for each choice of the initial approximation. Given is also a corresponding algorithm, which in only few steps gives a stationary point and the corresponding partition. The method is illustrated and visualized on the example of looking for an optimal partition with two clusters, where we check all stationary points of the corresponding minimizing functional. Also, the method is tested on the basis of large numbers of data points and clusters and compared with the method for solving the center-based Least Squares—clustering problem described in Kogan (2007) and Teboulle (2007).