Showing papers by "Solomon Tesfamariam published in 2011"

Risk analysis in a linguistic environment: A fuzzy evidential reasoning-based approach

Abstract: Performing risk analysis can be a challenging task for complex systems due to lack of data and insufficient understanding of the failure mechanisms. A semi quantitative approach that can utilize imprecise information, uncertain data and domain experts' knowledge can be an effective way to perform risk analysis for complex systems. Though the definition of risk varies considerably across disciplines, it is a well accepted notion to use a composition of likelihood of system failure and the associated consequences (severity of loss). A complex system consists of various components, where these two elements of risk for each component can be linguistically described by the domain experts. The proposed linguistic approach is based on fuzzy set theory and Dempster-Shafer theory of evidence, where the later has been used to combine the risk of components to determine the system risk. The proposed risk analysis approach is demonstrated through a numerical example.

Developing a road performance index using a Bayesian belief network model

Abstract: There is a high demand to develop and incorporate decision support tools, by the transportation sectors and other concerned agencies, to improve their infrastructure assets management under shrinking budgets and increasing demands. This paper develops a proof-of-concept Bayesian belief network (BBN) model to rank roads in a network system based on several key performance indicators (KPI) using a probabilistic framework. For a given road network, the proposed tool is capable of ranking or prioritizing the segment of roads for high level management objectives. To demonstrate the application of the proposed model, various scenarios are elaborated and discussed in detail. Finally, the sensitivity analysis is carried out to evaluate the effects of different KPIs.

A model for earthquake risk management based on the life-cycle performance of structures

Abstract: Over 50 years of design life, buildings are exposed to different magnitudes and frequencies of earthquakes that require consideration of life-cycle cost (LCC). The LCC entails quantifying the building performance under seismic hazard and investments throughout the life of the structures. Traditional LCC utilises probabilities of being in different damage states. However, for buildings with inherent irregularities (e.g. vertical irregularity and plan irregularity), these probabilities are not readily available. In this paper, a system-based approach, utilising fuzzy set theory, is used to quantify the possibility of being in different damage states. The analysis is limited to study the effect of seismic exposure on the building LCC. The proposed method is illustrated with two case studies, a six-storey reinforced concrete (RC) building located in Vancouver, Canada, and vulnerability of an urban centre with 1000 RC buildings. Furthermore, sensitivity analysis is carried out to highlight the impact of differ...

Multi Criteria Decision Making Tool for the Selection of Seismic Retrofitting Techniques

Abstract: Upgrading existing buildings to meet current seismi c design codes is important in high seismic hazard regions. Decision makers must choose from many possible retrofitting options, each with inherent advantages and disadvantages. The two main decision drivers that are commonly used are: increasing engineering performance (ductility, stre ngth, etc.) and reducing cost. There is currently little information that incorporates socio-economic factors (e.g., aesthetics, sustainability) into th e decision making process. The aim of this paper is to develop a multi criteria decision making tool that takes both the engineering and socio-economic factors into consideration for retrofit selection. Since the importance of each factor varies based on building type, location, and attitude of the decision makers, OWA operators will be utilized. As well, for multiple decision makers, credibility factors will be introduced. This model can be expan ded in the future to incorporate new retrofitting techniques and selection criteria.

Effect of construction quality variability on seismic fragility of reinforced concrete building

Abstract: This paper discusses effect of construction defects on probabilistic seismic demand model (PSDM) of reinforced concrete (RC) frames. A six-storey three-bay moment resisting RC frame is designed to a 1984 Canadian Concrete Design Code. The RC frame is further modified to investigate variability of construction quality (CQ) on the PSDM. Three levels of CQ are considered, poor, average, and good. Forty five ground motion records were used to study the ground motion variability. The numerical model of the frame was developed in OpenSees and nonlinear dynamic analyses were performed, and the maximum interstorey drift is obtained as a response parameter for all simulations. The PSDM parameters are calculated using "cloud analysis" for all combinations of construction quality. The variation in the PSDM parameters is studied. Finally, the effects of CQ on the seismic fragilities are discussed.

An aggregative fuzzy risk analysis for flood incident management

Abstract: Mitigation of loss or damage is the prime focus in flood incident management (FIM). Emergency response program, a key element in flood incident management can fail in multiple ways; however it can be mainly attributed to failure of infrastructure and/or failure of human institutions. Characterization and quantification of various risk factors in emergency response is a difficult task because responses to floods are complex and dynamic in nature. For these reasons, high level of uncertainties are inherent in the estimation of risk associated with the emergency response and may warrant the usage of a quantitative–qualitative risk assessment framework. In this paper, a multi-stage hierarchical model is developed to estimate the aggregative risk associated with the failure of emergency response system in case of flood. Each risk item is defined by the product of the likelihood of a failure event and associated consequences. Both likelihood and the consequences of a failure event are defined using fuzzy numbers to capture vagueness in the concept of relevant risk factors. An analytic hierarchy process is used for estimating the priority matrix (weights) for grouping risk attributes. Utility of a proposed model is demonstrated through a simplified risk hierarchy representing emergency response system failure of a FIM.