Abstract

The number of procedures focused on dam safety is very large, mainly due to the rules established by different regulatory bodies, the guidelines that are part of the recommended best practices for engineering works, and the common sense and conservatism present in dam operation and maintenance because of the large socioeconomic and environmental impacts that any incident with a dam can cause. In practice, the vulnerability of a dam is inversely proportional to the improvement of safety procedures, such as monitoring and sensing, and the staff’s capacity to interpret the information in timely fashion. Therefore, establishing priorities for these procedures is essential for the plant management to define the scheduling and detailing of inspections and monitoring, as well as training needs. The MCDA model described here was specified based on regulations and practical public domain guidelines. The subjective estimation of preferences was done by the staff of a hydroelectric plant located in central Brazil. It employed the Simos method combined with a procedure adopted to convert the scores to the format of paired comparisons. The weights for dam safety procedures were obtained using the fuzzy AHP method. The method allowed obtaining the classification of safety procedures according to their priorities, and thus provided the plant management with elements to better schedule monitoring and staff training.

Highlights

  • IntroductionA dam fails due to a severe event that can result from heavy rainfall, earthquakes, strong winds, snow and ice, volcanic action, landslides, tsunamis, and wildfires

  • The subdivision of the subcriteria depends on the documents, processes, practices, or instruments as they were classified in the criteria

  • We interviewed each member of the plant's staff separately, we were unable to control whether there was any communication between them outside the interview room, so we cannot guarantee there was no suggestion between them regarding the ordering of preferences, possibly introducing bias

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Summary

Introduction

A dam fails due to a severe event that can result from heavy rainfall, earthquakes, strong winds, snow and ice, volcanic action, landslides, tsunamis, and wildfires All of these events can cause some degree of risk to dams and related infrastructure. To these natural hazards, one can add terrorist acts, design defects, excessively long service lives, aging materials, and unsatisfactory maintenance (Little, 2002). With respect to the last item, a significant probability of failure is due to human factors, including maintenance, inattention to regular testing, faulty communication during an emergency, or incorrect action at the moment before the occurrence This involves both cognitive and physical responses that, depending on the event sequence, can have results ranging from minor loss to catastrophic failure (Baecher, 2016). The purpose of this article is to propose a multicriteria model to order the criteria adopted for the assessment of dam vulnerability in relation to operation, inspection, sensing and maintenance procedures

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