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

CMS-0509772-桥梁全寿命性能优化决策的综合养护-监测-管理框架在这项拟议的研究中，将开发公路桥梁养护-监测-管理一体化系统的分析和计算框架。该框架将以一种新颖的方式将新兴的健康监测技术、时变结构可靠性理论、生命周期成本计算、贝叶斯更新方法、公路交通网络分析和优化结合在一起。将开发在有和没有监测数据的情况下预测公路桥梁寿命安全和性能的方法。将特别强调妥善处理与装载、环境应激源、结构阻力、劣化过程以及监测和维护活动有关的各种不确定因素。将系统地讨论不同技术在改进桥梁安全和性能预测以及提高后续管理决策质量方面的成本效益。拟议的综合维护-监测-管理框架将被描述为一个非线性、离散、组合优化问题，其中将考虑多个相互冲突的目标。这些目标将涉及桥梁的安全和性能以及长期的经济后果。进化计算将为决策过程产生一组帕累托最优权衡解。这一新的综合框架将应用于单个桥梁的项目层面和地理上分布的一组桥梁的网络层面，以形成高速公路网。国家未来的持续经济增长和社会发展与其公路桥梁等民用基础设施系统的可靠性和耐久性密切相关。由于逐渐老化、激进的环境压力和不断增加的交通负荷，公路桥基础设施一直在经历严重的安全和状况恶化。然而，对日益恶化的公路桥的维护需求已经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，桥梁管理系统对于以经济高效的方式将有限的维护资源分配给桥梁以实现令人满意的寿命安全和性能至关重要。为此，新兴的健康监测技术、创新的保存策略、改进的不确定性分析、生命周期成本计算方法和计算优化等先进技术都变得非常重要。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做法，无法反映结构能力的恶化。由于腐蚀、损伤、疲劳等原因而未能发现结构缺陷，以及不能真实地评估桥梁的健康状况，可能会导致不可靠的桥梁管理决策，甚至会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大部分研究和实践都集中在传感技术、原型设备和数据处理算法的开发上。将健康监测和维护系统地整合到民用基础设施的管理中，以便更可靠地进行性能预测，这方面的研究很少。本文提出的研究工作将对公路桥梁基础设施管理的演变产生重大影响，创新性地弥合了当前公路基础设施管理与监测研究和实践之间的明显差距。使用拟议的综合框架，整个桥梁工程界将意识到在具有短期和长期安全和经济影响的相互竞争的目标之间存在的权衡。因此，这项研究将是为下一代桥梁管理系统奠定必要基础的重要一步，下一代桥梁管理系统将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维护解决方案。此外，拟议的研究有可能显著降低生命周期成本，并通过影响国家民用基础设施的安全、维护和管理来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.