PECASE: Revolutionizing Surface Wave Methods for Engineering Analyses - from Deterministic and Incoherent to Probabilistic and Standardized (DIPS)

PECASE：彻底改变工程分析的表面波方法 - 从确定性和非相干性到概率性和标准化 (DIPS)

• 批准号: 1055611
• 负责人: Brady Cox
• 金额: $ 42.16万
• 依托单位: University of Arkansas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2012-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1055611&HistoricalAwards=false
• 关键词: PECASE; Revolutionizing; Surface; Wave; Methods

This Faculty Early Career Development (CAREER) Program award is jointly funded by the Civil, Mechanical and Manufacturing Innovation Division and the Office of International Science and Education. Surface wave methods (SWMs) have become fully entrenched as powerful tools in geotechnical site investigation over the past decade, and their end result - a subsurface profile of small-strain shear modulus/shear wave velocity (Vs) - is used as a key input parameter in many engineering analyses. The expanding use of SWMs is driven by the desire to "reach" within the earth and retrieve accurate and meaningful engineering parameters without the need for borings. Traditionally, SWMs have been used to provide a single, deterministic Vs profile for each site tested, without consideration given to measurement/dispersion uncertainty and how it propagates forward through the inversion process used to estimate Vs. However, as the profession moves toward probabilistic design and performance-based engineering, the inability to quantify uncertainty in Vs from SWMs has been exposed as a major impediment to future progress. An ever increasing number of researchers and practitioners are using SWMs without understanding how acquisition parameters such as spatial sampling interval, array aperture, source proximity, and signal-to-noise ratio influence the uncertainty of their results. Furthermore, only anecdotal recommendations exist (often conflicting) to guide the selection of these parameters relative to a desired depth of exploration. It is likely that no other non-standardized test is used in geotechnical engineering more widely than SWMs. The PI will address these issues in his career by revolutionizing SWMs from Deterministic and Incoherent to Probabilistic and Standardized (DIPS). The DIPS plan (aimed at "smoothing-out the dips" in SWMs) involves: (1) quantifying measurement/dispersion uncertainty in SWMs so that Monte Carlo-based inversions can be used to propagate this uncertainty forward into a suite of acceptable Vs profiles with confidence intervals on layer thickness and velocity (i.e., advancing from deterministic to probabilistic), and (2) developing standards for SWMs applied to solving engineering problems (i.e., advancing from incoherent recommendations to coherent standards). The DIPS plan is guided by the vision to collect and analyze a unique, large and freely-shared set of experimental data at key benchmark sites across the country using the four main types of SWMs with systematically varied acquisition parameters. Meaningful dispersion uncertainty will be evaluated for each set of acquisition parameters using newly-proposed methods. Intra-method variability in dispersion estimates will then be examined and the set of parameters with the lowest uncertainty selected to anchor the development of standards. With meaningful estimates of dispersion uncertainty, Monte Carlo inversions will be used to establish confidence intervals for Vs layer thickness and velocity, resulting in fully probabilistic results that can be incorporated into subsequent performance-based analyses. Following this step, inter-method variability will be examined in order to evaluate bias between various SWMs and borehole Vs measurements.The University of Arkansas (UA) has placed the PI in a unique position to carry out the DIPS plan and integrate it with existing educational programs aimed at increasing undergraduate research experiences, diversifying the student body, and developing international collaborations. The PI is committed to integrating research and education in SWMs, having been involved in this field since his own undergraduate research project. The DIPS plan will not only allow for students to become involved in undergraduate research, but will also provide an opportunity to spend a semester abroad through a preexisting foreign exchange agreement between UA and the Politecnico di Torino (PDT) in Italy. The PI's colleagues at PDT are experts in surface wave testing, and this project opens up a unique chance for our institutions, professors and students to participate in international exchange of education, ideas and culture through undergraduate researchers. Recruitment of students to participate in the PDT exchange will occur through the Engineering Career Awareness Program (ECAP), a UA College of Engineering program that combines several piloted and proven strategies to recruit, retain and graduate minority undergraduate students. UA tracks the progress of ECAP students to assess the impact of the program, providing a pre-existing mechanism to track the retention and success of ECAP students with international PDT research experiences. The PI believes that this experience will lead to 100 percent retention and a high likelihood that these underrepresented students will continue their education via graduate studies.

该学院早期职业发展（CAREER）计划奖由土木，机械和制造创新部门以及国际科学和教育办公室共同资助。 在过去的十年中，表面波法（SWM）已经成为岩土工程现场勘察中的强大工具，其最终结果-小应变剪切模量/剪切波速度（Vs）的地下剖面-被用作许多工程分析中的关键输入参数。 SWM的扩展使用是由“到达”地球内部并在不需要钻孔的情况下检索准确和有意义的工程参数的愿望驱动的。 传统上，SWM已被用来提供一个单一的，确定性的Vs配置文件为每个网站测试，不考虑测量/分散的不确定性，以及它如何传播通过反演过程中用于估计Vs，但是，随着专业走向概率设计和性能为基础的工程，无法量化的不确定性，在Vs从SWM已被暴露为一个主要障碍，未来的进展。 越来越多的研究人员和从业人员使用SWM，而不了解采集参数，如空间采样间隔，阵列孔径，源接近度和信噪比如何影响其结果的不确定性。 此外，只有轶事建议存在（往往相互矛盾），以指导选择这些参数相对于所需的勘探深度。 很可能没有其他非标准化测试在岩土工程中比SWM更广泛地使用。 PI将通过将SWM从确定性和不一致性革命到概率和标准化（DIPS）来解决这些问题。 DIPS计划（旨在“平滑SWM中的倾角”）涉及：（1）量化SWM中的测量/分散不确定性，使得基于蒙特卡罗的反演可以用于将该不确定性向前传播到一套可接受的Vs剖面中，该剖面具有关于层厚度和速度的置信区间（即，从确定性发展到概率性），以及（2）开发应用于解决工程问题的SWM的标准（即，从不连贯的建议到连贯的标准）。 DIPS计划的指导思想是，使用四种主要类型的SWM，系统地改变采集参数，在全国各地的关键基准点收集和分析一组独特的、大型的和自由共享的实验数据。 将使用新提出的方法对每组采集参数进行有意义的色散不确定性评估。 然后将检查分散估计值的方法内变异性，并选择不确定性最低的一组参数来锚标准的制定。 通过对分散不确定性进行有意义的估计，将使用蒙特卡罗反演来建立Vs层厚度和速度的置信区间，从而产生完全概率性的结果，这些结果可以纳入后续的基于性能的分析中。 在此步骤之后，将检查方法间的变异性，以评估各种SWM和钻孔Vs测量值之间的偏差。阿肯色州大学（UA）将PI置于一个独特的位置，以执行DIPS计划，并将其与现有的教育计划相结合，旨在增加本科生的研究经验，使学生多样化，并发展国际合作。 PI致力于整合SWMs的研究和教育，自他自己的本科研究项目以来一直参与这一领域。 DIPS计划不仅允许学生参与本科研究，还将提供一个机会，通过UA和意大利的Politecnico di都灵（PDT）之间预先存在的外汇协议在国外度过一个学期。 PDT的PI同事是表面波测试方面的专家，该项目为我们的机构，教授和学生提供了一个独特的机会，通过本科研究人员参与国际教育，思想和文化交流。 招募学生参加PDT交流将通过工程职业意识计划（ECAP）进行，这是一个工程计划的UA学院，结合了几个试点和成熟的策略来招募，保留和毕业少数民族本科生。 UA跟踪ECAP学生的进展，以评估该计划的影响，提供了一个预先存在的机制，以跟踪具有国际PDT研究经验的ECAP学生的保留和成功。 PI认为，这种经验将导致100%的保留和这些代表性不足的学生将通过研究生学习继续他们的教育的可能性很高。