Decision-making on economic maintenance of earthquake-resistant reinforced concrete structures
It is necessary to repair or reinforce earthquake-resistant reinforced concrete structures during their service time since their safety performance may gradually deteriorate due to environmental factors such as concrete carbonation, steel erosion, natural aging, or earthquake damage. This paper adopts a benefit-cost analysis and puts forward an economic decision-making method on preventive maintenance, pre-earthquake reinforcement, and post-earthquake repair and dismantling of structures, with consideration to earthquake damage accumulation, natural aging, and durability damage. It is of crucial theoretical significance and application value to the decision-making on the maintenance of structures.
Lifetime Bridge Maintenance Strategies Based on System Reliability
This study proposes a methodology for a system reliability-based condition evaluation of existing highway bridges. The approach is illustrated for an existing steel bridge located in Colorado, USA....
Using Fuzzy-Delphi technique to determine the concession period in BOT projects
BOT projects are affected by several risks and uncertainties. One of the most important issues in this type of contract is to determine the length of concession period considering these uncertainties. The previous studies have developed several models to determine the concession period. However, the uncertainties are not taking into account in most of the previous works. Moreover, none of the previous researches has the capability to aggregate the opinions of different experts being involved in a project regarding the values of the uncertain input parameters. In this research, a Fuzzy-Delphi technique is implemented to determine the length of concession period considering uncertainties. Using the proposed Fuzzy-Delphi technique, the values of different uncertain factors affecting a BOT project is determined considering opinions of a group of experts. The NPV value is calculated considering the resulted aggregated values of uncertain input parameters. Finally, the concession period is determined using fuzzy approach. A case study is conducted to evaluate the performance of the proposed methodology. It is shown that the concession period is determined more effectively using the proposed approach.