CAREER: Advanced and Uncertainty-Informed Site Investigation

由该学院早期职业发展（Career）奖资助的研究计划通过探索基本土壤关系和与地下数据解释相关的不确定性来提高岩土工程现场调查的能力。岩土工程现场调查对安全、经济、有弹性的民用基础设施至关重要。然而，这仍然是土木工程实践中的一个挑战。现场调查不充分是造成工程预算和工期超支或建筑工程保险索赔的主要原因。锥贯入测试收集地下数据，并在整个岩土工程和环境工程实践中使用。当土壤和条件与开发和验证数据解释方法的标准土壤不同时，工程师会谨慎使用锥突测试数据。本研究的结果旨在通过以下方式为工程师提供一个更有能力的现场调查框架：(1)从标准和非标准土壤类型的锥贯试验数据中估计先进的工程参数，从而允许工程师对数据做更多的工作；(2)量化与标准和非标准土壤的现场调查数据相关的不确定性。因此，使工程师能够将不确定性传播到基础设施的预测性能，并评估附加数据的价值。该项目将研究与社区大学转校生的教育和推广计划相结合，旨在增加成功转学并从四年制土木工程专业毕业的学生人数。该项目将支持当地社区学院的外展活动，组织年度转学生研讨会，包括研究实验室参观和外展演示，并接待社区学院本科转学生从事研究实习工作。该研究将通过检查锥体穿透试验过程中基本的土壤载荷相互作用和表征土壤参数估计产生的不确定性来推进现场调查方法。本研究的目的是：(i)研究土壤类型、土壤性质、初始条件、临界状态线位置和形状与锥贯试验数据之间的关系；（ii）研究在标准和非标准土壤中基于锥贯试验的土壤参数解释的不确定性量化；（iii）在更广泛的现场调查背景下探索不确定性量化和数据同化。先进的实验室测试、系统级计算锥体穿透模型和物理锥体穿透测试的综合计划将表征土壤临界状态线和初始状态对锥体穿透测试数据的基本作用。这项研究的预期结果是一种关键的基于状态线的锥体穿透测试数据解释方法，该方法将在一系列标准和非标准土壤中开发和验证。一个大型的土壤性质数据集和现场调查信息将用于调查与现场调查数据中土壤参数估计相关的不确定性。这种评估将为不确定性知情的现场调查提供一个框架，将不确定性从现场测试传播到设计和预测性能，使工程师能够使用可量化的度量来进行现场调查决策以及他们的工程判断。该奖项反映了美国国家科学基金会的法定使命，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。

Research funded by this Faculty Early Career Development (CAREER) award plans to advance the capability of geotechnical site investigation by exploring fundamental soil relationships and the uncertainty associated with subsurface data interpretation. Geotechnical site investigation is critical to safe, cost-efficient, and resilient civil infrastructure. However, it remains a challenge for civil engineering practice. Insufficient site investigation is a primary reason for project budget and timeline overruns or insurance claims on construction projects. The cone penetration test collects subsurface data and is used throughout geotechnical and environmental engineering practice. Engineers use cone penetration test data cautiously when soils and conditions vary from the standard soils that data interpretation methods were developed and validated with. Findings from this research are intended to provide engineers with a more capable framework for site investigation by (1) estimating advanced engineering parameters from cone penetration test data for standard and non-standard soil types, therefore allowing engineers to do more with the data, and (2) quantifying uncertainties associated with site investigation data for both standard and non-standard soils, therefore enabling engineers to propagate uncertainties to predicted performance of infrastructure, and evaluate the value of additional data. This project integrates research with an education and outreach program for community college transfer students that aims to increase the number of students who successfully transfer to and graduate from four-year Civil Engineering programs. The project will support outreach events at local community colleges, organization of an annual transfer student workshop, including research lab tours and outreach demonstrations, and hosting undergraduate community college transfer students in research intern positions.This research will advance site investigation methods by examining fundamental soil-load interactions during cone penetration testing and characterizing uncertainties stemming from soil parameter estimation. The objectives of this research are to (i) investigate relationships between soil type, soil properties, initial conditions, critical state line position and shape, and cone penetration test data, (ii) investigate uncertainty quantification for cone penetration test-based soil parameter interpretation in standard and non-standard soils, and (iii) explore uncertainty quantification and data assimilation in the broader context of site investigation. An integrated program of advanced laboratory testing, a system-level computational cone penetration model, and physical cone penetration tests will characterize the fundamental role of the soil critical state line and initial state on cone penetration test data. The anticipated outcome of this investigation is a critical state line-based interpretation approach for cone penetration test data that will be developed and validated across a range of standard and non-standard soils. A large dataset of soil properties and site investigation information will be used to investigate uncertainty associated with soil parameter estimation from site investigation data. This assessment will enable a framework for uncertainty-informed site investigation that will propagate uncertainties from site tests to design and predicted performance, enabling engineers to use quantifiable metrics for site investigation decisions alongside their engineering judgment.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.