Probabilistic Life-Cycle Costing: Beyond the Great Expectation

作为我国经济的支柱，加拿大的民用基础设施长期以来一直受到影响。 原因是系统性和多方面的，从资金短缺和不协调的系统规划，到无情的极端事件和低效的工程设计和管理。 与此同时，公众对基础设施的期望已从安全、健康和流动性转向智能、弹性、可持续性和灵活性等概念。 基础设施相关决策的透明度也是赢得公众支持的一个重要因素。 为了应对这些挑战，必须建立一个风险知情的生命周期基础设施工程（RILCIE）理论，为现代基础设施问题提供一个整体的解决方案。 申请人的长期研究目标是通过开发可用于支持实际决策的理论，方法和工具来推进RILCIE。 与这一长期目标相一致，拟议的研究计划旨在回答基础设施生命周期几乎每个阶段都会出现的一个紧迫问题：建造一个基础设施并将其服务维持在令人满意的水平需要多少成本和多少应急费用？ 寻找这个问题的完整答案比简单的成本会计要深入得多。 这是一项科学奋进，涉及几个基本的，相互交织的研究问题，包括随机退化建模，时间相关的可靠性分析，寿命预测，最佳的检查和维护计划，时间偏好和折扣，以及风险知情的决策。 拟议的研究计划的重点是开发一个先进的概率生命周期成本计算系统，将解决这些问题，重点是在分析的每个关键组成部分所涉及的不确定性建模。 寿命周期成本信息的使用超出了替代比较等传统应用。 相反，建议在评价公私伙伴关系等创新项目交付模式、制定综合优化设计和资产管理计划以及指导风险知情的结构完整性管理方面发挥关键作用，每种模式在基础设施寿命的不同阶段代表基础设施问题的不同方面。所提出的不确定性建模方法的全概率量化-而不是平均值或预期只有-的生命周期成本，并使用成本信息的决策支持的方式是非常原始和创新的。 预计拟议的研究将对项目评估、工程设计和基础设施资产管理产生重大影响。该研究计划包括六名博士和三名MASc学生的全面高素质人才培养计划。

The backbone of our nation's economy, Canada's civil infrastructure has been long suffering. The reasons are systemic and multi-faceted, ranging from funding deficits and uncoordinated systems planning, to unrelenting extreme events and inefficient engineering design and management. Meanwhile, public expectations on infrastructure have moved from safety, health and mobility to the notions such as intelligence, resilience, sustainability and flexibility. Transparency in infrastructure-related decision makings is also an important factor in winning public support. To meet these challenges, a risk-informed life-cycle infrastructure engineering (RILCIE) theory that provides a holistic solution to modern infrastructure issues must be established. The applicant's long-term research goal is to advance RILCIE by developing theories, methods and tools that can be applied to support practical decision makings. Aligning with this long-term goal, the proposed research program aims to answer a burning question that arises in almost every stage of the infrastructure life cycle: How much does it cost and how much contingency is required to build a piece of infrastructure and uphold its services to a satisfactory level? Searching for a complete answer to this question goes much deeper than simple cost accounting. It turns out to be a scientific endeavor that involves several fundamental, intertwined research issues, including stochastic degradation modeling, time-dependent reliability analysis, lifetime prediction, optimal inspection and maintenance planning, time preference and discounting, and risk-informed decision making. The proposed research program focuses on the development of an advanced probabilistic life-cycle costing system that would address these issues with an emphasis on the modeling of uncertainties involved in each key component of the analysis. The use of the life-cycle cost information goes beyond conventional applications such as alternative comparisons. Rather, it is proposed to play a pivotal role in evaluating innovative project delivery models such as public-private partnerships, developing integrated optimal design and asset management plans, and guiding risk-informed structural integrity management each representing a very different aspect of infrastructure issues at distinguishing phases of infrastructure life. The proposed uncertainty modeling methodology for a full probabilistic quantification - rather than the average or expectation only - of the life-cycle cost, and the way of using the cost information for decision making support are highly original and innovative. The proposed research is expected to have a significant impact on project evaluation, engineering design, and infrastructure asset management. The research program includes a comprehensive highly-qualified personnel training plan of six PhD and three MASc students.