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.

该小型企业技术转移（STTR）I阶段项目的更广泛的影响/商业潜力是通过开发基于计算软件的工具来实时使用数据驱动的高级分析，通过开发基于计算软件的工具来实时创建和更新地面模型，从而降低地下民用基础设施构建的成本。民事基础设施越来越多地在地下移动，包括道路，过境，公用事业和设施。但是，地下建筑中的风险仍然是吸引投资的关键障碍。建造潜在的重大风险是地面条件和影响设计和施工的物理特性的高度不确定性，从而导致成本增加，因为过度设计和/或施工过程中的延迟和失败。该项目通过提供解决方案来以常规和自主的方式更新地面模型来提高对地面条件的理解，从而充分利用施工过程中收集的大量数据。这个小型企业技术转移（STTR）I阶段项目旨在开发一种技术解决方案，该解决方案可自动化回分析地面属性并实时更新地面模型的过程。将解决一些技术挑战。当前的Backanalyses实践在管理和整合基础基础设施项目的数据方面非常昂贵，并且昂贵。施工过程中的动态环境需要对可能数百种独特的隧道结构相互作用进行4D反转分析。此外，反转在估计岩土参数中的效率，这仅在技术的基本开发过程中仅在有限的情况下证明。拟议的研究的目标是（1）开发算法，以自动整合岩土技术仪器和监视，施工过程监控，现有基础架构，Apriori地理模型等的数据在各种地面条件和隧道结构相互作用之间以及（4）学习灵敏度布局和优化敏感性对反转功效的影响。这项I阶段的工作将奠定开发“现场”地面建模工具的基础。该奖项反映了NSF的法定任务，并通过使用基金会的知识分子优点和更广泛的影响审查标准来评估，被认为是珍贵的支持。