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Knowledge and awareness of the risks generated by natural hazards are essential requirements for the enhancement of communities’ resilience to disasters. The Sendai Framework for Disaster Risk Reduction 2015–2030 has recently pointed out the necessity of undertaking actions aimed to anticipate, manage, and mitigate disaster risks, to reduce their economic and social impact and protect health, socioeconomic assets, cultural heritage, and ecosystems of communities and countries. While the increasing occurrence of disasters caused by meteorological events, such as floods, storms, and droughts, can be directly ascribed to the consequence of climate change, disasters induced by earthquakes and tsunamis are increasing even if the frequency of occurrence is historically unchanged. Therefore, other anthropogenic causes intervene to determine an increment of a risk exposure and community vulnerability, such as land misuse in densely populated areas and coastal zones. This Special Issue addresses concepts, methods, and predictive methodologies for assessing natural hazards risks. This Special Issue presents fifteen articles focusing on the single-risk assessment of a broad range of natural hazards, such as earthquakes, river, and see floods, meteotsunamis, tornados, hydrological and meteorological drought, liquefaction, as well as on multirisk assessment in the presence of multiple hazards. The adopted methodologies rely on: (a) quantitative, semi- quantitative, and qualitative methods for the assessment of the risks related to natural hazards ; (b) risk analysis at different scales ; (c) multi-hazard risk assessment techniques ; (d) real-time hazard monitoring and warning systems ; (e) disaster mitigation strategies ; and (f) risk management and emergency planning at multiple scales.

A comprehensive hybrid approach to large-scale seismic vulnerability and risk assessment of existing urban areas is presented in this study. The approach combines the advantages of the vulnerability index method in assessing the vulnerability of a large number of buildings with the pushover method, that allows to determine the capacity curves and detect the specific limit states of the buildings. The described methodology is used to calculate seismic vulnerability indexes, damage indexes, critical accelerations for different limit states and seismic risk indexes for the case study Kaštel Kambelovac.

The virtual element method (VEM), is a stabilized Galerkin scheme deriving from mimetic finite differences, which allows for very general polygonal meshes, and does not require the explicit knowledge of the shape functions within the problem domain. In the VEM, the discrete counterpart of the continuum formulation of the problem is defined by means of a suitable projection of the virtual shape functions onto a polynomial space, which allows the decomposition of the bilinear form into a consistent part, reproducing the polynomial space, and a correction term ensuring stability. In the present contribution, we outline an extended virtual element method (X-VEM) for two-dimensional elastic fracture problems where, drawing inspiration from the extended finite element method (X-FEM), we extend the standard virtual element space with the product of vector-valued virtual nodal shape functions and suitable enrichment fields, which reproduce the singularities of the exact solution. We define an extended projection operator that maps functions in the extended virtual element space onto a set spanned by the space of linear polynomials augmented with the enrichment fields. Numerical examples in 2D elastic fracture are worked out to assess convergence and accuracy of the proposed method for both quadrilateral and general polygonal meshes.

We have devised a crack-tracking methodology for general crack paths in elasto-damaging materials based on the regularized extended finite element method. The resulting procedure is in-between nonlocal models, where the discontinuity surface is replaced by a finite width zone, and cohesive zone models, where the discontinuous regime is governed by a traction-separation law.

In this research a flood exposure analysis for the coastal area of Kaštel Kambelovac in Croatia is performed considering sea level rise impact of extreme waves on the coastline. An analysis of different coastal flooding scenarios is performed following the EU Flood Directive requirements. Flooding scenarios are determined based on the combination of three different natural factors ; tidal effect, atmospheric pressure and extreme coastal waves. Furthermore, coastal flooding scenarios are adapted to climate change impact and sea level rise projections for the Adriatic Sea.

In the context of Performance-Based Earthquake Engineering, an intensity measure provides a link between the probabilistic seismic hazard analysis and the probabilistic structural response analysis. The purpose of this study is to develop a structural damage classifier and improve current prediction on the basis of a given intensity measure and different supervised machine learning algorithms: Support-Vector Machine, Logistic Regression and Random Forest. In particular, the efficiency of four different IMs for estimating the seismic response of three different kind of buildings is evaluated, namely peak ground acceleration, spectral acceleration evaluated at the principal period, average spectral acceleration and filtered incremental velocity. The classifier will be able to predict the post- earthquake damage state, given the geometry of the building and the intensity of the ground motion input. In particular, the purpose of this classifier is to accelerate post- earthquake damage evaluation of critical buildings. This will allow faster recovery time and decrease financial losses expected from downtime and repair. A focus is made on three different buildings typologies that can be used to represent the majority of the building stock in the city of Ferrara (Italy).