Life-Cycle Cost Model Simulator for Decision Making in Bridge Network Management

美国未来持续的经济增长与我们民用基础设施系统的可靠性和可持续性有关，例如高速公路和桥梁。人们普遍认为，桥梁基础设施管理中的资源优化利用应基于综合结构可靠性，从概率角度进行评估，并考虑寿命周期成本。在美国，交通官员认为桥梁的生命周期成本和可靠性分析是协助投资决策的最先进技术。在这样做的过程中，他们试图确定并实施以尽可能低的生命周期成本维持适当水平的桥梁可靠性的最佳策略。研究的是如何合理分配有限的可用资源。该研究的主要目的是开发一个基于模型的模拟器，以基于模拟的时间依赖性能和生命周期成本来优化桥梁网络的管理决策。这个创新的模型将集成计算科学、桥梁网络建模和可靠性技术，以模拟和可视化基于生命周期可靠性和生命周期成本的最佳网络级桥梁维护计划和管理过程。该解决方案是基于突发性不连续的特征，包括网络中桥梁破坏等现象和桥梁网络的大规模性能模拟。该方法还需要表示在每个桥梁的使用寿命期间通过网络传播的不确定性。通过模拟桥梁网络的时间相关性能，将利用新的数据来更新网络性能以及自动适应。最后，为了促进桥梁管理过程中的实时成本效益决策，将为网络中的每座桥梁、网络的整体性能和每种维护策略的成本效益开发性能可视化技术。一个位于科罗拉多州公路网的大约36座桥梁的数据库将被用来证明该方法的适用性和效率。该研究是建立新一代桥梁管理系统基础的重要一步，该系统在网络层面上根据生命周期成本做出最佳维护决策，同时明确考虑到网络中单个桥梁在整个使用寿命期间的不确定性传播。通过这种方式，美国数十亿美元的桥梁基础设施维护投资将得到优化。优化对提高国家公路桥的质量和功能的影响可能是巨大的。最后，生命周期成本建模和仿真结果将整合到本科和研究生阶段的工程教育中。

Future continued economic growth of the United States is linked to the reliability and sustainability of our civil infrastructure systems, such as highways and bridges. It is widely recognized that optimal resource use in bridge infrastructure management should be based on integrating structural reliability, evaluated from a probabilistic perspective, and life-cycle cost. In the United States, transportation officials consider life-cycle cost and reliability analysis for bridges to be the most advanced techniques for assisting with investment decisions. In so doing, they attempt to determine and implement the best possible strategy for maintaining an adequate level of bridge reliability at the lowest possible life-cycle cost. The research delves into to rationally distribute limited available resources.The main objective of the research is to develop a model-based simulator to optimize management decisions for bridge networks based on simulated time-dependent performance and life-cycle cost. This innovative model will integrate computational sciences, bridge network modeling, and reliability technologies for simulating and visualizing optimal network-level bridge maintenance planning and management processes based on lifetime reliability and life-cycle cost. The solution is based on characterizing abrupt discontinuities, including phenomena such as failure of a bridge in the network and large-scale performance simulations of bridge networks. The approach will also entail representation of uncertainties propagating through the network during the service life of each bridge. By simulating the time-dependent performance of the bridge network, new data will be exploited to update the network performance as well as to auto-adapt. Finally, to facilitate real-time cost-effective decision-making in the bridge management process performance visualization techniques will be developed for each individual bridge in the network, the overall performance of the network, and the cost-benefit of each maintenance strategy. A database of about three dozen bridges located in highway networks in Colorado will be used to demonstrate the applicability and efficiency of the methodology. The research represents an important step in creating the basis of a new generation of bridge management systems where optimal maintenance decisions based on life-cycle cost are made at the network-level while explicitly taking into account the propagation of uncertainties during the entire service life of individual bridges in network. In this manner, the multi-billion dollar investment in the maintenance of bridge infrastructure in the US will be optimized. The impact of the optimization on improving the quality and functionality of the nation's highway bridges could be enormous. Finally, life-cycle cost modeling and simulation results will be integrated into engineering education at both undergraduate and graduate levels.