Optimal sustainable life cycle maintenance strategies for port infrastructures
Optimal sustainable life cycle maintenance strategies for port infrastructures
复制标题
DOI：
10.1016/j.jclepro.2016.11.120
复制
发表时间：
2017-01
影响因子：
11.1
通讯作者：
Yi Zhang;Chul‐Woo Kim;K. Tee;J. Lam
中科院分区：
文献类型：
--
作者：
Yi Zhang;Chul‐Woo Kim;K. Tee;J. Lam
在严重依赖港口基础设施使用的中部经济和工业区，港口作业非常重要。一个经济和有效的维修战略对于管理港口基础设施的正常运行，从而对海运至关重要。世界各地的许多机构都设法制定了维护战略，以确保港口基础设施的适用性和安全性达到最佳水平。然而，关于如何在维修规划中实施可持续问题的信息并不多。本文提出了一种评估、比较和改进港口基础设施维护策略可持续性的方法。该方法是基于提出的随机化结构劣化模型而发展的。在全寿命周期费用估算中考虑了改造费用、运行损失和环境损失。利用效用函数的概念，从多个维修方案中寻找最优维修方案。对东京的一个码头进行了调查，以验证所提出的方法。讨论了港口基础设施中不同结构元素的维护策略。结果表明，该方法能够提供更可靠的检修时机信息。预测的成本界限允许业主/风险经理以多种方式了解结构的当前状况，其中包括安全侧预测和平均预测。
Port operations are highly important in the central economic and industrial regions which rely heavily on the use of port infrastructures. An economic and efficient maintenance strategy is essential to govern the normal running of port infrastructures and thus seaborne transportation. Many agencies worldwide have managed to develop maintenance strategies to ensure optimal levels of serviceability and safety for port infrastructures. However, there is not much information about how sustainable issues can be implemented in the maintenance planning. This paper proposes a methodology for evaluating, comparing and improving sustainability of maintenance strategies for port infrastructures. The method is developed based on a proposed randomized structural deterioration model. The costs due to retrofitting, operating loss and environmental loss are considered in the total life cycle cost estimation. The concept of utility function is utilized to serve as a criterion for finding the optimal strategy among the alternative maintenance strategies. An investigation is performed on a Tokyo wharf to demonstrate the proposed approach. The maintenance strategies for different structural elements in the port infrastructures are discussed. The results show that the proposed approach can provide more reliable information on the maintenance timing. The predicted cost bounds allow owners/risk managers to understand the current condition of the structure in several ways, which include both safe-side prediction and average prediction.