Integrated Maintenance-Monitoring-Management Framework for Optimal Decision Making in Bridge Life-Cycle Performance

CMS-0509772 -桥梁寿命周期性能优化决策的抽象集成维护-监测-管理框架 在这项拟议的研究中，一个分析和计算的框架，集成的公路桥梁的维修监测管理系统将开发。该框架将以一种新颖的方式结合联合收割机新兴的健康监测技术，时间相关的结构可靠性理论，生命周期成本，贝叶斯更新方法，公路运输网络分析和优化。将开发有无监测数据的公路桥梁寿命安全性和性能预测方法。将特别强调适当处理与荷载、环境压力源、结构抗力、退化过程以及监测和维护活动相关的各种不确定性。将系统地讨论不同技术在提高桥梁安全性和性能预测以及提高后续管理决策质量方面的成本效益。建议的综合维修监测管理框架将制定为一个非线性，离散，组合优化问题，多个和相互冲突的目标将被考虑。这些目标将解决桥梁的安全和性能以及长期的经济后果。演化计算将被执行，以产生一组帕累托最优的权衡解决方案的决策过程。这种新的综合框架将在项目级应用于单个桥梁，在网络级应用于地理上分布的一组桥梁，形成公路网。国家未来的持续经济增长和社会发展与其民用基础设施系统（如公路桥梁）的可靠性和耐久性密切相关。公路桥梁基础设施正经历着严重的安全和条件恶化，由于逐渐老化，侵略性的环境压力，并增加交通负荷。然而，日益恶化的公路桥梁的维修需求远远超过了美国联邦和州公路机构所能提供的稀缺资金。因此，桥梁管理系统是至关重要的成本效益分配有限的维修资源，以实现令人满意的寿命安全和性能的桥梁。为此，先进的技术，包括新兴的健康监测技术，创新的保护策略，改进的不确定性分析，生命周期成本计算方法和计算优化都变得非常重要。然而，在现有的桥梁管理系统中，目视检查是最广泛采用的量化和评估桥梁状况的方法，无法反映结构能力的退化。由于例如腐蚀、损坏、疲劳和不能忠实地评估真实的桥梁健康状态而不能检测到结构缺陷可能导致不可靠的桥梁管理决策，甚至造成巨大的安全和经济后果。此外，民用基础设施健康监测的研究和实践大多集中在传感技术、原型设备和数据处理算法的开发上。很少有研究已经做了系统集成的健康监测和维护管理的民用基础设施，更可靠的性能预测。提出的研究工作将产生重大影响的公路桥梁基础设施管理的演变，创新性地弥合了目前的公路基础设施管理和监测研究与实践之间的明显差距。使用建议的综合框架，整个桥梁工程界将意识到竞争目标之间存在的权衡，既有直接的和长期的安全和经济的影响。因此，这项研究将是形成下一代桥梁管理系统的必要基础的重要一步，该系统应通过整合更新的桥梁信息并考虑多个相互冲突的标准来产生最佳的维护解决方案。此外，拟议的研究有可能通过影响国家民用基础设施的安全、维护和管理，显着降低生命周期成本，并延长建筑环境的寿命。

CMS-0509772 --- Abstract Integrated Maintenance-Monitoring-Management Framework for Optimal Decision Making in Bridge Life-Cycle Performance In this proposed research, an analytical and computational framework for integrated maintenance-monitoring-management systems of highway bridges will be developed. This framework will combine in a novel manner emerging health monitoring techniques, time-dependent structural reliability theory, life-cycle costing, Bayesian updating approaches, highway transportation network analysis, and optimization. Methodologies for predicting lifetime safety and performance of highway bridges with and without monitored data will be developed. Particular emphases will be placed on proper treatment of various uncertainties associated with loading, environmental stressors, structural resistances, deterioration processes, and monitoring and maintenance activities. Cost-effectiveness of different techniques in improving the prediction of bridge safety and performance and in improving the quality of subsequent management decisions will be systematically addressed. The proposed integrated maintenance-monitoring-management framework will be formulated as a nonlinear, discrete, combinatorial optimization problem for which multiple and conflicting objectives will be considered. These objectives will address bridge safety and performance as well as long-term economic consequences. Evolutionary computation will be performed to produce a group of Pareto-optimal tradeoff solutions for the decision-making process. The novel integrated framework will be applied at project-level for individual bridges and at network-level for a group of bridges geographically distributed to form highway networks.Future sustained economic growth and social development of the Nation is very much linked to the reliability and durability of its civil infrastructure systems such as highway bridges. The highway bridge infrastructure has been undergoing severe safety and condition deterioration due to gradual aging, aggressive environmental stressors, and increasing traffic loads. Maintenance needs for deteriorating highway bridges, however, have far outpaced available scarce funds that the U.S. federal and state highway agencies can provide. Bridge management systems are thus critical to cost-effectively allocate limited maintenance resources to bridges for achieving satisfactory lifetime safety and performance. To this end, advanced technologies including emerging health monitoring techniques, innovative preservation strategies, improved uncertainty analysis, life-cycle costing methods, and computational optimization all become very important. In existing bridge management systems, however, visual inspections are the most widely adopted practice to quantify and assess bridge conditions, which are unable to reflect the structural capacity deterioration. Failure to detect structural deficiency due to, for example, corrosion, damage, fatigue and inability to faithfully assess real bridge health states may lead to unreliable bridge management decisions and even enormous safety and economic consequences. In addition, most research and practice in civil infrastructure health monitoring have been centered on development of sensing technologies, prototype devises, and data processing algorithms. Little research has been done on systematical integration of health monitoring and maintenance into management of civil infrastructure for more reliable performance prediction. The research efforts proposed will have a significant impact on the evolution of highway bridge infrastructure management by innovatively bridging the apparent gap between the current highway infrastructure management and monitoring research and practice. Using the proposed integrated framework, the entire bridge engineering community will become aware of the tradeoffs existing between competing objectives that have both immediate and long-term safety and economic implications. Therefore, this research will be an important step in forming the necessary basis for the next-generation of bridge management systems, which should produce optimum maintenance solutions by integrating updated bridge information and by considering multiple and conflicting criteria. In addition, the proposed research has the potential to significantly reduce life-cycle costs and to increase the longevity for the built environment by impacting the safety, maintenance, and management of the Nation's civil infrastructure.