A Dynamic Bayesian Network-based approach to Resilience Assessment of Engineered Systems

Traditional risk assessment approaches mainly focus on the pre-failure scenarios with certain information. For complex systems, the scope of risk assessment needs to be extended to include the post-failure phase; because the emerging hazards of these systems cannot be wholly identified and are usually highly uncertain. Thus, resilience assessment needs to be investigated. Most of the existing literature quantify resilience based on a system's performance loss caused by disruptions. These studies fail to assess the probability of a system to sustain or restore to a normal operational state after disruptions occur, how this probability changes with time, and how fast the system can be restored. The dynamic and probabilistic characteristics of resilience must be considered in systemic resilience assessment, in which the engineered system, human and organizational factors, and external disruptions are considered. This paper aims to develop a dynamic Bayesian network (DBN)-based approach to the probabilistic assessment of the system resilience by incorporating temporal processes of adaption and recovery into the analysis of system functionality. The proposed method also provides a new way to define resilience in terms of the probability of system functionality change during and after a disruption. A case study on the Chevron refinery accident is used to demonstrate the applicability of the proposed methodology.     

Comments on selecting a geographic information system for environmental management

Many organizations in environmental fields stand to benefit from the use of a geographic information system (GIS). Selecting a GIS to implement within an organization can be a difficult task that is often required of people with little experience using a GIS. A framework for evaluating competing GIS considers cost, functionality, ease of use, future stability, development potential, support availability, and maintenance costs. Initial cost involves more than the actual purchase price of hardware and software; it includes the cost of building the data base and training users within the organization. Functionality refers to the depth and breadth of capabilities of a GIS. Issues involved in evaluating functionality include the appropriateness of raster vs vector processing and the ability to add your own software. Ease of use is important, but there is generally a trade-off with functionality. The degree of centralization of use of the GIS within the organization affects requirements for ease of use. GIS are rapidly evolving, and as a result it is important to select a system with high potential for future development. With the proliferation of companies offering GIS it is important to select one that is likely to survive and prosper. Similarly, the ability to find support in the forms of technical help, advice, and possibly even skilled employees can be significant.     

Sudden-onset disaster resilience considering functionality improvement planning: An upstream oil and gas company

The present paper presents a quantitative approach to evaluate organizational resilience in sudden-onset disasters considering preparedness actions (PAs). The resilience triangle concept is extended and gradual improvement of the level of functionality (LF) strategy is examined as PAs. Robustness and rapidity measures are considered as loss of LF and recovery time to indicate the overall disaster resilience. Besides, the resourcefulness and redundancy measures are considered pre-determined response plans and PAs aimed to improve disaster resilience. Two mathematical models are developed by applying these measures. Thereafter, graphical analytics are conducted to demonstrate the effectiveness of PAs and provide a better outlook for decision-makers. Then, mathematical analyses are conducted to show how the PAs affect resilience measures. It is mathematically proved that PAs exert considerable impacts on recovery time, loss of LF, and robustness. To illustrate the application of the proposed approach, it is applied to an upstream oil and gas company in the field of exploration and production. The results suggest that the approach is significantly effective in disaster response, planning, and mitigation.