Characterizing impulsive wave-in-deck loads on coastal bridges by probabilistic models of impact maxima and rise times

Abstract

When waves impact a seawall, a vertical breakwater, an exposed jetty, a pier or a coastal bridge, they abruptly transfer their momentum into the structure. This energy transfer can be very violent and its duration exceptionally short. In the case of coastal bridges, whose spans are designed to have very short vibration period, wave impacts might have duration comparable to the natural period of oscillation of the structure, which therefore becomes prone to damage and failure. Previous forensic studies have documented the relative importance of impulsive loads on deck suspended structure, demonstrating the need to assess the effect of wave impacts on both the stability and the integrity of structural members since the early stages of the design. This requires the estimation of the dynamic characteristics of the loading pattern, and in particular the wave impulse and corresponding impact maxima and rise times. Based on the conservation of momentum, functional relationships between these parameters have been identified since pioneering work dating back to the late '30s of the 20th century. The complexity of the loading process, however, results in a significantly large variability of wave impact maxima and rise times even under similar conditions, suggesting the need for a probabilistic approach to the definition of the relationship between these two variables, to be applied when estimating the dynamic properties of wave for use in structural analysis of coastal structures. In the recent past, some effort has been made to identify functional relationships between such quantities; these require the assessment of the conditional quantiles (or similarly the conditional distribution) of wave impact maxima given the rise times. In this paper, we compare three different statistical methods proposed in the literature to accomplish this task, in order to assess the reliability of the approach and suggest guidelines for practical applications. A copula-based method, Generalized Additive Models for Location, Scale and Shape (GAMLSS), and quantile regression are applied to measurements from large-scale 3-dimensional physical model tests. The investigation suggests that quantile regression gives the simplest results to be used in practice; copula approach and GAMLSS are possible alternative when semi-parametric or fully parametric modeling is needed.