A new evolutionary polynomial regression technique to assess the fundamental periods of irregular buildings

The main seismic design codes propose simplified formulations to evaluate the fundamental period of regular structures based on the total height. Indeed, the fundamental period depends on several parameters directly connected to the mass and stiffness of the structure and on its geometrical characteristics, including also irregularities. This paper proposes a set of mathematical formulations to evaluate the longitudinal and transversal fundamental period of vibration of 3D Reinforced Concrete (RC) frames, which have various vertical and plan irregularities and for different mechanical and geometrical design parameters. Several types of Reinforced Concrete Bare Moment Resisting Frame (RC-BMRF) buildings have been designed according to the different versions of the Italian codes starting from 1916 to nowadays and then used as case studies. Modal analysis is performed on the entire building dataset to assess the fundamental periods in both longitudinal and transversal directions. Then, cluster analysis is carried out to classify the buildings based on similar design characteristics and construction details. Finally, a robust Evolutionary Polynomial Regression (EPR) technique is used to find the optimal polynomial forms of the natural period. Numerical results show a better performance of the proposed formulation compared with the existing methodologies available in the literature

Quantitative Framework to Assess Resilience and Risk at the Country Level

This paper presents a quantitative method to assess the resilience and the resilience-based risk at the country level. The approach is inspired by the classical risk analysis, in which risk is a function of vulnerability, hazard, and exposure. In the proposed analysis, resilience based risk is a function of resilience, hazard, and exposure. In the new formula, the resilience parameter is evaluated using the data provided by the Hyogo Framework for Action (HFA). HFA scores and ranks countries based on a number of equally weighted indicators. To use those indicators in the resilience assessment, the contribution of each indicator toward resilience must be determined. To do that, three methods to weight and combine the different HFA indicators are proposed. The first two methods are based on the dependence tree analysis (DTA), while the third method is based on a geometrical combination of the indicators using spider plots. The proposed methodology has been applied to a case study composed of 37 countries for which both the resilience (R) and the resilience-based risk (RBR) indexes have been determined

Time-Dependent Probability of Exceeding a Target Level of Recovery

The resilience of a system is generally defined in terms of its ability to withstand external perturbations, adapt, and rapidly recover. This paper introduces a probabilistic formulation to predict the recovery process of a system given past recovery data and to estimate the probability of reaching or exceeding a target value of functionality at any time. A Bayesian inference is used to capture the changes over time of model parameters as recovery data become available during the work progress. The proposed formulation is general and can be applied to continuous recovery processes such as those of economic or natural systems, as well as to discrete recovery processes typical of engineering systems. As an illustration of the proposed formulation, two examples are provided. The paper models the recovery of a reinforced concrete bridge following seismic damage, as well as the population relocation after the occurrence of a seismic event when no data on the duration of the recovery are available a priori

Modelling cascading failures in lifelines using temporal networks

Lifelines are critical infrastructure systems with high interdependency. During a disaster, the interdependency between the lifelines can lead to cascading failures. In the literature, the approaches used to analyze infrastructure interdependencies within the social, political, and economic domains do not properly describe the infrastructures’ emergency management. During an emergency, the response phase is very condensed in time, and the failures that occur are usually amplified through cascading effects in the long-term period. Because of these peculiarities, interdependencies need to be modeled considering the time dimension. The methodology proposed in this paper is based on a modified version of the Input-output Inoperability Model. The lifelines are modeled using graph theory, and perturbations are applied to the elements of the graph, simulating natural or man-made disasters. The cascading effect among the interdependent networks has been simulated using a spatial multilayer approach. The adjancency tensor has been used to for the temporal dimension and its effects. Finally, the numerical results of the simulations with the proposed model are represented by probabilities of failure for each node of the system. As a case study, the methodology has been applied to a nuclear power plant. The model can be adopted to run analysis at different scales, from the regional to the local scales

Resilience assessment of high damping rubber bearings in beyond-design conditions

Passive isolation systems are an established solution for the design of civil engineering structures that are required to provide superior performances in the case of a seismic event. Although their application to the seismic protection of bridges is currently limited, isolation systems are likely to become more widespread in the design of strategic infrastructures and facilities. In this work numerical investigations on the ultimate limit state conditions of filled high damping rubber bearings under cyclic shear loading are presented, focusing on the influence of the axial load with respect to the device

Disaster Resilience Assessment of Building and Transportation System

The paper presents a new methodology to assist decision-makers in the management of critical events such as earthquakes evaluating the recovery time, and the resilience index of a building system that is a component of the physical infrastructure dimension of the PEOPLES Resilience framework. The interdependencies between building system and transportation network in term of accessibility are modeled. Finally, the methodology has been implemented in a software and has been applied in two case studies: (a) the old medieval center of L’Aquila town and (b) the Treasure Island in the San Francisco Bay area

Factor Analysis to Evaluate Hospital Resilience

Health care facilities should be able to quickly adapt to catastrophic events such as natural and human-made disasters. One way to reduce the impacts of extreme events is to enhance a hospital's resilience. Resilience is defined as the ability to absorb and recover from hazardous events, containing the effects of disasters when they occur. The goal of this paper is to propose a fast methodology for quantifying disaster resilience of health care facilities. An evaluation of disaster resilience was conducted on empirical data from tertiary hospitals in the San Francisco Bay area. A survey was conducted during a 4-month period using an ad hoc questionnaire, and the collected data were analyzed using factor analysis. A combination of variables was used to describe the characteristics of the hidden factors. Three factors were identified as most representative of hospital disaster resilience: (1)cooperation and training management; (2)resources and equipment capability; and (3)structural and organizational operating procedures. Together they cover 83% of the total variance. The overall level of hospital disaster resilience (R) was calculated by linearly combining the three extracted factors. This methodology provides a relatively simple way to evaluate a hospital's ability to manage extreme events

Nondestructive monitoring techniques for crack detection and localization in RC elements

This paper presents the structural and damage assessment of a reinforced concrete (RC) beam subjected to a four-point bending test until yielding of reinforcing steel. The deterioration progress was monitored using different nondestructive testing (NDT) techniques. The strain was measured by distributed fiber optic sensors (FOSs), embedded prior to concrete pouring. The initiation and propagation of cracks were monitored by acoustic emission (AE) sensors attached to the surface of the material. The recorded AE activity results in good agreement with FOS strain measurements. The results of the integrated monitoring system are confirmed by visual observation of the actual crack pattern. At different loading steps, digital image correlation (DIC) analysis was also conducted

Resilience framework for seaport infrastructure: theory and application

The efficient movement of goods is crucial to the economic growth of communities. This makes the existence of seaports essential for the marine transportation system. Due to their natural location, ports are continuously threatened by natural hazards such as wind action, which necessitates a continuous monitoring and assessment for their performance. The work presented here aims at assessing the resilience of ports against natural disasters. This is done by identifying the performance and the recovery rate of such infrastructure during the period following the event. The research commenced with gathering information about the port’s main components that are influenced by natural hazards. The collected data has been compiled in the form of indicators, which have been filtered and grouped under four dimensions in the proposed “PORT framework”. Each of the indicator has been allocated a measure to enable its quantitative evaluation. The aggregation of the indicators’ values allows identifying the port resilience

Seismic Resilience of Electric Power Networks in Urban Areas

Recent natural disasters have raised the question of how communities can recover from extreme events. In the last decade the research has been focusing on analyzing interdependencies between different networks. In this paper the focus is on the distribution power network, developing a method to estimate a realistic grid of a vir-tual city called “Ideal City” freely inspired to the city of Turin in Italy. A software called Matpower devel-oped by the Joint Research Center has been used for the load flow analysis of the power network. Fragility curves, repair costs and downtime are evaluated using FEMA’s database. Finally, a strategy to improve the network resilience is proposed considering the complexity of the environmen