A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Risk-Cost Optimization of Buried Pipelines Using Subset Simulation
On the basis of time-dependent reliability analysis, a computational framework called subset simulation (SS) has been applied for risk-cost optimization of flexible underground pipeline networks. SS can provide better resolution for rare failure events that are commonly encountered in pipeline engineering applications. Attention in this work is devoted to scrutinize the robustness of SS in risk-cost optimization of pipelines. SS is first employed to estimate the reliability of flexible underground pipes subjected to externally applied loading and material corrosion. Then SS is extended to determine the intervention year for maintenance and to identify the most appropriate renewal solution and renewal priority by minimizing the risk of failure and whole life-cycle cost. The efficiency of SS compared to genetic algorithm has been demonstrated by numerical studies with a view to prevent unexpected failure of flexible pipes at minimal cost by prioritizing maintenance based on failure severity and system reliability. This paper shows that SS is a more robust method in the decision-making process of reliability-based management for underground pipeline networks.
Risk-Cost Optimization of Buried Pipelines Using Subset Simulation
On the basis of time-dependent reliability analysis, a computational framework called subset simulation (SS) has been applied for risk-cost optimization of flexible underground pipeline networks. SS can provide better resolution for rare failure events that are commonly encountered in pipeline engineering applications. Attention in this work is devoted to scrutinize the robustness of SS in risk-cost optimization of pipelines. SS is first employed to estimate the reliability of flexible underground pipes subjected to externally applied loading and material corrosion. Then SS is extended to determine the intervention year for maintenance and to identify the most appropriate renewal solution and renewal priority by minimizing the risk of failure and whole life-cycle cost. The efficiency of SS compared to genetic algorithm has been demonstrated by numerical studies with a view to prevent unexpected failure of flexible pipes at minimal cost by prioritizing maintenance based on failure severity and system reliability. This paper shows that SS is a more robust method in the decision-making process of reliability-based management for underground pipeline networks.
Risk-Cost Optimization of Buried Pipelines Using Subset Simulation
Khan, Lutfor Rahman (author) / Tee, Kong Fah (author)
2016-01-06
Article (Journal)
Electronic Resource
Unknown
Risk-Cost Optimization of Buried Pipelines Using Subset Simulation
| Online Contents | 2016
Risk-Cost Optimization of Buried Pipelines Using Subset Simulation
| Online Contents | 2016
| Elsevier | 1985
Design optimization using Subset Simulation algorithm
| Elsevier | 2010