Automated and Integrated Decision Support System for Tunnel Construction**

为了满足城市化的要求，隧道工程正在进行，以扩大地下基础设施系统。隧道工程的成功不仅取决于隧道设备的性能，还取决于经验丰富的人员所采取的主观行动和决策，以及与隧道施工相关的无数不可预见的因素和事件。这些因素的数量和不可预测性导致相当大的项目不确定性，使得从业者很难在偏离项目基线或发生意外事件后确定最有效的行动方针。捕获项目信息的尝试导致了数据收集系统在整个隧道行业的广泛实施。然而，尽管收集了大量数据，从业者仍在努力将这些数据转换为有用的信息，以提高隧道工程的绩效。事实上，如果没有能够自动组合、分析数据并将其转换为易于解释的格式的系统，决策将继续主要依赖从业者的主观决策。*拟议的工作将把我们的研究团队在基于模拟的分析和岩土工程方面的学术实力与我们的行业合作伙伴的实践知识和经验结合起来，开发一种新的、能够实时集成项目、设备、地面和行为数据的决策支持框架，以有效和快速地重新定向隧道施工，以应对项目违规或偏差。除了加强隧道运营外，这项工作还有望为建筑决策支持领域的运营行为建模提供新的见解。

To meet the requirements of urbanization, tunneling projects are being undertaken to enlarge underground infrastructure systems. The success of a tunneling project not only depends on the performance of tunneling equipment, but also on the subjective actions and decisions taken by experienced personnel as well as a myriad of unforeseen factors and events associated with tunneling operations. The number and unpredictability of these factors results in considerable project uncertainty, making it difficult for practitioners to determine the most effective course of action following deviations from project baselines or an unanticipated event. Attempts to capture project information have resulted in the widespread implementation of data collection systems throughout the tunneling industry. Despite collecting vast amounts of data, however, practitioners continue to struggle with the transformation of these data into usable information for improved tunneling project performance. Indeed, without systems capable of automatically combining, analyzing, and transforming data into a format that is easily interpretable, decision-making will continue to rely primarily on the subjective decisions of practitioners.****The proposed work will combine our research team's academic strength in simulation-based analytics and geotechnical engineering with the practical knowledge and experience of our industrial collaborator to develop a new, decision-support framework for tunnel construction that is capable of integrating project, equipment, ground, and behavioral data, in real-time, to effectively and rapidly redirect tunneling operations in response to project irregularities or deviations. In addition to enhancing tunneling operations, this work is expected to provide new insights into the modeling of operational behavior in the construction decision-support domain.****