Panagiotis Prinos

Extremes from scarce data: The role of Bayesian and scaling techniques in reducing uncertainty

This paper deals with the analysis of extreme wave heights and their uncertainties. The main purpose is to assess confidence intervals using a conventional extreme value, and a Bayesian approach. It is shown how the introduction of an a priori information helps to bound the upper confidence limit. The analysis is performed with wave-height data recorded off the Spanish Catalan coast (NW Mediterranean) and wave-height data from the Dutch coast (North Sea). An analysis with natural-scale and log-transformed wave-height time series has been performed. This scale selection is proven to be advantageous for naturally bounded variables and also better captures some distribution features. The paper ends with a discussion on how the different techniques can be used to select a statistically robust threshold for an extreme event definition. This affects the evaluation of risk in low-lying coastal areas, associated to variables controlling flooding and erosion risks.

Estimation of Extremes: Conventional versus Bayesian techniques

The Bayesian and Maximum Likelihood (ML) estimators of surges at two stations of the Dutch coast on the North Sea are compared herein. The ML approach is commonly used, while the Bayesian approach allows both for a parameter uncertainty and a randomness inclusion in future observations. In the Bayesian framework, two different ways of constructing prior distributions are examined, namely the near flat distributions for model parameters and the incorporation of information from neighborhood sites of that under consideration through the distribution of quantile differences. The Bayesian framework offers substantial advantages to analyze the extreme values in both cases. The analysis is also performed using log-transformed surge data. This selection is proven to be advantageous for naturally bounded variables and to better capture the “relative” character of extremes.

Uniform flow in open channels with steep slopes

The characteristics of turbulent flow in open channels with steep slopes are studied experimentally and numerically. Velocity measurements indicate that the von Karman constant K of the log law of the wall remains constant in both the subcritical and supercritical regimes while the constant A decreases with increasing Fr number. A modified Preston tube method is developed for estimating the boundary shear stress in flows with unknown constant of the log law of the wall and gives satisfactory results. Two low-Re turbulence models of the k-∊ type are used in the computational study and are found to reproduce satisfactorily the velocity distribution except in the case of very steep slopes (high Fr number). They also predict the reduction of the viscous sub-layer in supercritical flows but they fail to predict the reduction of the turbulence kinetic energy and turbulence intensities for such conditions due to their isotropic nature.

Statistical models for bivariate extremal analysis of a spatial process

In the present paper different dependence measures are examined to investigate the structure of a spatial process of storm surges in the Dutch part of the North Sea. Four different dependence measures are implemented to the data: (1) the correlation coefficient as well as the Spearman (rank) correlation of the sample, (2) the transformation of the variables to determine the marginal distributions, (3) the dependence measures (χ, ) and (4) the coefficient of tail dependence η. Two different approaches for modelling the threshold exceedances are examined, namely the implementation of bivariate extreme value models and the use of more general point process characterizations of extremal dependence. The strength of dependence appears to vary with the location as well as with the separation distance. It is also observed that the point process approach estimates are in general lower than those using the bivariate threshold exceedance models.

Low-Crested Structures: Boussinesq Modeling of Waves Propagation

In the last few decades, low-crested structures have been extensively used in costal zones for shoreline protection and to prevent beach erosion. Their presence results primarily in wave energy dissipation through the physical mechanisms of wave breaking and friction. In most of the cases these structures are rubble mound permeable breakwaters whose design is based on empirical rules.

Bivariate Analysis of Extreme Wave and Storm Surge Events. Determining the Failure Area of Structures

In the present paper a bivariate process of extreme waves and storm surges at a Dutch station on the North Sea is considered. A bivariate logistic model and a sequential estimation procedure are used to extract joint exceedance probabilities of the two variables. The parameters of the margins of the bivariate distribution are defined by three different methods of estimation: a) the Maximum Likelihood Estimation (MLE) approach, b) a Bayesian procedure with flat prior distributions and c) the L-Moments (LM) estimation procedure. Comparison of the results of the three methods is performed and general conclusions are extracted. An approach to estimate the failure area of a particular structure under extreme sea conditions is presented, using the margins resulting from the three different estimation methods.

Flow Characteristics Behind A Butterfly Valve

The characteristics of mean flow and turbulence behind a butterfly valve are studied experimentally using a Laser-Doppler anemometry. Velocity and turbulence intensity are measured at donstream locations 0.086D, 0.5D, ID and 2D (D = pipe diameter) for three valve angular positions corresponding to fully open, partly open and relatively closed positions. Comparison of the isovels for the three positions indicates flow patterns with quite distinct features. Levels of turbulence intensity may increase up to 150% of the mean velocity for relatively closed valve, indicating the complex structure of such a flow.