Water main breaks disrupt water services and impact traffic flow along congested city roads. Dispatching water pipe repair crews needs to consider several factors that include: 1) the priority of repair site; 2) the suitability and efficiency of the construction crew in repairing a particular break type; and 3) the time required for crews to travel between break sites. This paper presents a simulation-based multi-objective optimization model to schedule repair crews across water network break sites in an urban setting. Discrete-event simulation models for the water pipe repair process are developed to account for various repair methods. These models are subsequently integrated within a GA-based multi-objective optimization model that considers the following objectives: 1) minimizing the total repair time required to complete all breaks; 2) minimizing the total cost to complete the breaks; and 3) minimizing the cumulative impact of all breaks incident on road users and water customers. A case study for the water network on the City of Damietta, Egypt is used to demonstrate the capabilities of the model. Results show a 21% reduction in repair time and 50% reduction in user impact compared to heuristic crew allocation methods used by the water utility.
Fault tree (FT) is a standardized notation for representing relationships between a system's reliability and the faults and/or the events associated with it. However, the existing FT fault models are only capable of portraying permanent events in the system. This is a major hindrance since these models fail to reflect accurately the other classes of faults, such as soft-faults, which are often temporary events that usually disappear after the source of the interference is no longer present. This paper proposes a new fault tree modeling paradigm, to capture the impact of temporal events in systems, called temporal dynamic fault trees (TDFTs). TDFTs are utilized to model the characteristics and dependencies between different temporal events, soft-faults, and permanent faults. These features are integrated into the proposed probabilistic models of the temporal gates, which are modeled as priced-timed automata. This paper also proposes a new FT analysis methodology, based on statistical model checking, designed to circumvent the state-explosion problem that is inherent to other model-checking approaches. The proposed analysis is able to evaluate the impact of temporal faults in systems, as well as to estimate the reliability and availability of the system over extended periods of time. The experiments reported in this paper demonstrate the versatility and scalability of the proposed approach. For instance, the results display the impact that temporal events may have in a digital system. Our observations indicate that while regular soft-fault analyses tend to underestimate metrics such as system reliability, TDFT analysis shows remarkable consistency with radiation testing, with differences of under 2%, in the conducted analysis.
Fault Tree Analysis (FTA) is a widespread technique used to assess the reliability of safety-critical systems. The traditional way of conducting FTA is either through paper and pencil proof or through computer simulation techniques, which are inefficient and prone to inaccuracy. In this paper, we propose the use of probabilistic model checking to automatically analyze fault trees of safety-critical systems. Our methodology consists in the probabilistic formalization of the gates used in a fault tree to a Discrete-Time Markov Chain (DTMC) and a Markov Decision Process (MDP), and the subsequent probabilistic verification using PRISM tool to quantitatively analyze the system. To illustrate the proposed approach we perform the fault tree analysis of a solar array system, used as power source for the DFH-3 satellite. The results show that harsh thermal environment is the main cause of system failures.
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