Pedro Poseiro

Port of Ponta Delgada, S. Miguel, Azores: assessment of the consequences of overtopping using AHP methodology

This work describes the application of a methodology for assessment of overtopping consequences at the port of Ponta Delgada, S. Miguel, Azores, by using a multi-criteria analysis (Analytic Hierarchy Process, AHP) on the impact of extreme overtopping exceeding the admissible values. Such approach allows obtaining results based on spatial analysis of the indicators that characterize the studied port area with respect to their relative importance.

Performance of a Fuzzy ARTMAP Artificial Neural Network in Characterizing the Wave Regime at the Port of Sines (Portugal)

ABSTRACT Santos, F.L.; Reis, M.T.; Fortes, C.J.E.M.; Lotufo, A.D.; Neves, D.R.C.B.; Poseiro, P., and Maciel, G.F., 2016. Performance of a fuzzy ARTMAP artificial neural network in characterizing the wave regime at the Port of Sines (Portugal). Techniques based on artificial neural networks (ANNs) have been increasingly applied to predict emergency situations, such as extreme wave conditions, wave overtopping or flooding, and damage to maritime structures, in coastal and port areas. In this work, a fuzzy adaptive resonance theory with mapping (FAM) ANN was trained to predict the wave regime both inside and at the entrance to the Port of Sines, one of the major trade and economic gateways of the Iberian Peninsula, located on the Portuguese west coast. In situ measurements using pressure sensors, wave buoy data, and results from two numerical wave propagation models—simulating waves nearshore (SWAN) and diffraction refraction elliptic approximation mild slope (DREAMS)—were used to train and validate the ANN. The wave regime was calculated for different points outside and inside the port. In general, the FAM predictions outside the port showed a satisfactory fit to the wave parameters (significant wave height, peak wave period, and mean wave direction) from the numerical model SWAN. Inside the port, differences from the DREAMS model were greater, because the optimized FAM parameters were obtained only for outside the port and the FAM network showed some difficulties in accounting for the complex phenomena of wave refraction, diffraction, and reflection within the port. Consequently, it is of paramount importance to obtain the FAM results based on fully optimized parameters to use the FAM output in place of the numerical models of wave propagation. Nevertheless, this methodology proved capable of providing a fast and satisfactory response that is especially useful in the scope of risk management, particularly in wave forecasting and warning systems.

Coastal risk forecast system

Runnup and overtopping are the two main sea wave originated events that threat coastal structures. These events may cause destruction of property and the environment, and endanger people. To build early warning forecast systems, we must take into account the consequence and risk characterization of the events in the affected area, and understand how these two types of spatial information integrate with sensor data sources and the risk determination methodology. In this paper we present the description and relationship between consequence and risk maps, their role on the risk calculation, and how the HIDRALERTA project integrates both aspects into its risk methodology. We present a case study for Praia da Vitoria port, in Azores Portugal.

Risk Management in Maritime Structures

Maritime structures (breakwaters, groynes, ocean wave/wind energy converters, etc.) are exposed to wave attack, which generates common emergency situations with serious environmental and economic consequences. This paper presents a methodology developed at LNEC for forecasting and early warning of wave overtopping in ports/coastal areas to prevent emergency situations and support their management and the long-term planning of interventions in the study area. It is implemented in a risk management tool. The methodology uses numerical models to propagate waves from offshore to port/coastal areas to obtain the required input for overtopping assessment methods, such as empirical formulas and artificial neural networks. The calculated overtopping values are compared with pre-established admissible values in order to define the warning levels. These admissible values are derived from general international recommendations and information from local authorities. They depend on the characteristics of the overtopped structure and of the protected area, and on the activities developed there. The warning methodology is applied to Praia da Vitoria Port (Azores-Portugal) as an illustrative example. Future developments include the use of complex numerical models (e.g. Navier-Stokes equations solvers; particle methods) to calculate wave overtopping and to extend the methodology to warn of risks associated with wave energy production failure.