RAPID: Adaptive Management of Geotechnical Construction in Urban Areas

美国和世界许多地区的城市化和交通拥堵加剧，促使人们对地下空间产生了巨大需求，以通过降低污染和能源消耗使新兴的特大城市变得宜居。 地下建筑提供了可持续发展的好处，在现有基础设施的地区创造公共交通和商业空间，有能力捕获排放物，并有机会通过将交通系统和其他结构重新安置在地下来保护绿色空间。 然而，地下空间的规划和建设是一个漫长的过程，需要大量的预算（美国每年超过1000亿美元）。 成本和进度延迟是常见的（例如，波士顿大挖掘从最初估计的20亿美元到超过130亿美元）。 大多数地下建筑是公共的，纳税人资助的项目。 因此，在地下空间的设计和建设中可以开发的效应将对美国产生巨大的经济效益。 一个这样的发展是自适应管理技术，提供了一种手段，将传感器的发展，信息技术和数值分析的最新进展，以预测，监测和控制在挖掘过程中的地面运动。 本研究的目的是采用第一次自适应管理技术的岩土工程建设，提供真实的时间更新的性能预测，在这种情况下，在50英尺深的挖掘，在芝加哥的多层建筑。 该项目将开发工具，推动地下建筑行业的最新技术和实践，以便在城市地区创造地下空间，使该过程对邻近结构和公用设施的影响最小，从而最大限度地降低建筑成本，消除昂贵的建筑索赔和诉讼。 虽然该项目侧重于深开挖的适应性管理，但其结果直接适用于任何岩土工程施工活动。 与海沃德贝克公司的工业合作，该项目的开挖支撑承包商和岩土专业施工的全球领导者将确保结果将对地下建筑行业产生直接影响。本研究建立在几个NSF支持的项目，其中开发的优化技术的结果，采用自动化监测技术，全面的现场性能进行了详细的量化，采用复杂的土壤行为模型，参数识别技术进行了量化在深开挖现场。 这项研究的试验台是辛普森·奎里生物医学研究中心大楼的挖掘工作。 这项工作将由西北大学与海沃德贝克公司合作进行，该项目的挖掘支持分包商。 首席研究员在邻近的Lurie研究中心建设期间和之后进行了广泛的研究，其中包括40英尺深的挖掘。 海沃德贝克将安装和维护一个自动监测系统，该系统将包括基于MEMS的形状阵列来测量横向移动，机器人全站仪来测量支撑系统和邻近建筑物的移动。 西北大学的研究人员将开发挖掘的二维和三维有限元模型，基于考虑土壤小应变非线性行为的本构模型，实现网站之间的接口，开发一个分析平台，允许基于有限元模型自动更新性能预测，并安排学生担任现场工作人员，记录详细的施工活动，以确保在更新现场性能时考虑到适当的条件。 该研究解决了有关天然粘土在非常小的应变水平下的应力-应变行为的基本问题，以及由于施工活动而导致的详细土壤和结构响应之间的关系。 这些工具将包括综合分析和信息平台，以促进工程师、承包商、业主和公众之间的沟通，并将允许接近真实的时间更新性能预测。

Increased dense urbanization and traffic congestion in the US and many parts of the world are prompting a significant demand for underground space to make emerging mega-cities livable by lowering pollution and energy consumption. Underground construction provides sustainable development benefits in terms of creating mass transit and commercial space in areas with existing infrastructure, with the ability to capture emissions, and the opportunity to preserve green space by relocating transportation systems and other structures underground. However, planning and construction of underground space is a lengthy process that requires large budgets (over $100 billion annually in the U.S.). Cost and schedule delays are common (e.g., Boston Big Dig from initial estimate of $2 billion to over $13 billion). Most of underground construction is public, taxpayer-funded projects. Efficiencies that can be developed in design and construction of underground space thus will have a large financial benefit to the US. One such development is an adaptive management technique that provides a means to incorporate recent advances in sensor development, information technology, and numerical analyses to predict, monitor, and control ground movements during excavation. The purpose of this research is to employ for the first time adaptive management techniques for geotechnical construction to provide real time updates of performance predictions, in this case during the 50 foot deep excavation for a multi-story building in Chicago. The project will develop tools that will advance the state-of-art and practice in the underground construction industry so that underground space can be created in urban areas in such a way that the process will have minimal impact on adjacent structures and utilities, thereby minimizing construction costs and eliminating expensive construction claims and lawsuits. While this project focuses on adaptive management of deep excavations, its results are directly applicable to any geotechnical construction activity. Industrial collaboration with Hayward Baker, Inc., the excavation support contractor for the project and a worldwide leader in geotechnical specialty construction, will ensure that results will have immediate impact in the underground construction industry. This research builds upon the results of several of NSF-supported projects in which optimization techniques were developed, automated monitoring technologies were employed, full-scale field performance was quantified in detail, sophisticated models of soil behavior were employed, and parameter identification techniques were quantified at deep excavation sites. The test bed for this research is the excavation for the Simpson Querrey Biomedical Research Center building. The work will be conducted by Northwestern University in collaboration with Hayward Baker, Inc., the excavation support subcontractor for the project. The Principal Investigator conducted extensive research during and after construction of the adjacent Lurie Research Center which included a 40 ft deep excavation. At no cost to the research, Hayward Baker will install and maintain an automated monitoring system which will include MEMS-based shape arrays to measure lateral movements, robotic total stations to measure support system and adjacent building movements. Northwestern researchers will develop 2D and 3D finite element models of the excavation, based on constitutive models that account for small strain nonlinearity behavior of soils, implement an interface between the website, develop an analyses platform to allow automatic updates of performance predictions based on the finite element model, and deploy students as field personnel to record the detailed construction activities which will assure that the proper conditions have been considered in the update of the field performance. The research addresses fundamental issues regarding stress-strain behavior of natural clays at very small strain levels, and the relationships between detailed soil and structural responses due to construction activities. The tools will include integrated analyses and information platforms to facilitate communication among engineers, contractors, owners and the public, and will permit updated predictions of performance in near real time.