STTR Phase I: Underground Live - an innovative, advanced analytical tool for characterizing the subsurface and reducing underground construction risk

STTR 第一阶段：Underground Live - 一种创新、先进的分析工具，用于表征地下特征并降低地下施工风险

• 批准号: 2304544
• 负责人: Jacob Grasmick
• 金额: $ 27.5万
• 依托单位: EMPRISE CONCEPTS LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2304544&HistoricalAwards=false
• 关键词: STTR; Phase; Underground; Live; innovative

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project is to reduce the cost of underground civil infrastructure construction and make new infrastructure more sustainable by developing a computational software-based tool to create and update ground models in real time using data-driven advanced analytics. Civil infrastructure is increasingly moving underground, including roadways, transit, utilities, and facilities. However, risk in underground construction remains a critical barrier to attracting investment. A significant risk in building underground is the high uncertainty in ground conditions and physical properties influencing design and construction, resulting in increased costs due to over-design and/or delays and failures during construction. This project strives to improve the understanding of ground conditions by providing a solution to update the ground models during construction in a routine and autonomous manner, making full use of the wealth of data collected during construction. This Small Business Technology Transfer (STTR) Phase I project aims to develop a technical solution that automates the process of back-analyzing ground properties and updating ground models in real time. Several technical challenges will be addressed. Current backanalyses practice is extraordinarily labor-intensive and expensive in managing and integrating data from underground infrastructure projects. The dynamic environment during construction requires 4D inversion analysis on potentially hundreds of unique tunnel-structure interactions. Furthermore, the efficacy of the inversion in estimating geotechnical parameters, which has been demonstrated for only limited situations during the fundamental development of the techniques, needs to be validated. The goals of the proposed research are to (1) develop algorithms to automatically integrate data from geotechnical instrumentation and monitoring, construction process monitoring, existing infrastructure, apriori geostatistical model, etc., (2) develop algorithms to dynamically update the geotechnical parameter inversion in spatial proximity of tunnel construction to adjacent structures, sensors, and ground conditions, (3) characterize the geotechnical parameter inversion efficacy across a broad variety of ground conditions and tunneling-structure interactions, and (4) learn the influence of sensing layout and optimized sensing on inversion efficacy. This Phase I work will lay the foundation for the development of a ‘live’ ground modelling tool.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这个小企业技术转让（STTR）第一阶段项目的更广泛影响/商业潜力是通过开发基于计算软件的工具，使用数据驱动的高级分析来真实的实时创建和更新地面模型，从而降低地下民用基础设施建设的成本，并使新基础设施更具可持续性。民用基础设施越来越多地转移到地下，包括道路、交通、公用事业和设施。然而，地下建筑的风险仍然是吸引投资的一个关键障碍。地下建筑的一个重大风险是影响设计和施工的地面条件和物理特性的高度不确定性，导致由于过度设计和/或施工期间的延误和故障而增加成本。本项目充分利用施工过程中收集的大量数据，提供施工过程中以常规和自主方式更新地面模型的解决方案，努力提高对地面状况的理解。该小企业技术转让（STTR）第一阶段项目旨在开发一种技术解决方案，该解决方案可自动执行地面属性的反向分析和真实的更新地面模型的过程。一些技术挑战将得到解决。目前的反分析实践是非常劳动密集型和昂贵的管理和集成数据从地下基础设施项目。施工期间的动态环境需要对潜在的数百个独特的隧道-结构相互作用进行4D反演分析。此外，反演在估计岩土参数，这已被证明是有限的情况下，在技术的基本发展，需要验证的功效。所提出的研究的目标是（1）开发算法，以自动集成来自岩土仪器和监测、施工过程监测、现有基础设施、先验地质统计模型等的数据，(2)开发算法，以动态更新隧道施工与相邻结构、传感器和地面条件的空间接近度中的岩土参数反演，（3）表征各种地面条件和隧道-结构相互作用下的岩土参数反演功效，以及（4）了解传感布局和优化传感对反演功效的影响。第一阶段的工作将为开发“实时”地面建模工具奠定基础。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。