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

美国未来的持续经济增长与我们的民用基础设施系统（如公路和桥梁）的可靠性和可持续性有关。人们普遍认为，桥梁基础设施管理中的最佳资源利用应基于集成结构可靠性，从概率的角度进行评估，和生命周期成本。在美国，交通官员认为桥梁的寿命周期成本和可靠性分析是协助投资决策的最先进技术。在此过程中，他们试图确定并实施最佳策略，以尽可能低的生命周期成本保持足够的桥梁可靠性水平。本研究探讨如何合理分配有限的资源，主要目的是开发一个以模型为基础的模拟器，以模拟时间相关的性能和生命周期成本为基础，来优化桥梁网络的管理决策。这一创新模型将整合计算科学、桥梁网络建模和可靠性技术，用于基于寿命可靠性和寿命周期成本模拟和可视化最佳网络级桥梁维护规划和管理过程。该解决方案是基于表征突然的不连续性，包括网络中的桥的故障和桥网络的大规模性能模拟等现象。该方法还将需要表示的不确定性传播通过网络在每个桥梁的使用寿命。通过模拟网桥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，将为网络中的每个单独的桥梁、网络的整体性能以及每个维护策略的成本效益开发性能可视化技术。 位于科罗拉多公路网中的大约30多座桥梁的数据库将被用来证明该方法的适用性和效率。这项研究是在创建新一代桥梁管理系统的基础上迈出的重要一步，在网络层面上，同时明确考虑到在网络中各个桥梁的整个使用寿命期间传播的不确定性，根据生命周期成本的最佳维护决策。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梁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模拟结果将被纳入本科和研究生阶段的工程教育。

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.