An Integrated Quantitative and Qualitative Life Cycle Cost Assessment Technology for Cost Benefit Evaluation of Bridge Deterioration, Renewal, and Rehabilitation

这个桥梁评估数据库对于确定哪些结构对于有限的资金来说是最关键的至关重要。 然而，目前还没有评估与各种修理程序有关的各种费用的评估报告。 这种评估是非常需要的，以帮助在选择经济智能维修/加强这些结构缺陷的桥梁可用的选项的艰巨任务。 这项研究将有助于开展这种评价。 用于桥梁基础设施修复/加固或更新的成本效益评估的生命周期成本评估技术是基于桥梁设计和维修方案的技术获取和评估。 这项研究是格鲁吉亚理工学院和亚利桑那大学之间的联合综合努力。 对于建筑业而言，生命周期成本效益评估将为处理基础设施更新中的复杂决策和评估提供全面和一致的评估技术。 生命周期成本效益评估将使建筑和政策制定者有可能节省数百万纳税人和工业资本美元。 寿命周期成本效益评估的影响将首次提供一种评估技术，以评估基础设施更新和桥梁建设行业的各种维修替代方案和新兴技术。 对学术界和科学界来说，生命周期研究将推动基于知识的系统的发展。

This database of bridge assessment is essential in determining which structures are most critical for limited monies. However, an evaluation which would assess the various costs associated with the various repair procedures is unavailable. Such an evaluation is highly needed to assist in the immense task of selecting economically smart repair/strengthen options available for these structurally deficient bridges. This research will assist in the development of such an evaluation. The life cycle cost assessment technology for cost benefit evaluation of bridge infrastructure rehabilitation/strengthening or renewal is based on technical acquisition and assessment of bridge design and repair options. This research is a joint, integrated effort between Georgia Institute of Technology and University of Arizona. For the construction industry, the life cycle cost benefit evaluation will provide a thorough and consistent assessment technology for handling the complex decisions and estimating in infrastructure renewal. The life cycle cost benefit evaluation will allow construction and policy makers to potentially save millions of taxpayers' and industrial capital dollars. The impact of the life cycle cost benefit evaluation will provide, for the first time, an assessment technology to evaluate various repair alternatives and emerging technologies on infrastructure renewal and the bridge construction industry. To the academic and scientific community, the life cycle research will push the bounds of knowledge-based systems.