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

这项教师早期职业发展(CALEAR)计划奖由土木工程、机械和制造创新部门和国际科学和教育办公室联合资助。近十年来，面波法已成为岩土场地勘察的有力工具，其最终结果--小应变剪切模数/剪切波速的地下剖面--被用作许多工程分析的关键输入参数。SWMS的广泛使用是因为人们希望“接触”到地球内部，并在不需要钻探的情况下获取准确和有意义的工程参数。传统上，SWMS被用来为每个测试站点提供单一的、确定性的VS分布，而没有考虑测量/弥散的不确定性以及它如何通过用于估计VS的反演过程向前传播。然而，随着该专业走向概率设计和基于性能的工程，无法量化来自SWMS的V的不确定性已被暴露为未来发展的主要障碍。越来越多的研究人员和实践者正在使用SWMS，而不了解空间采样间隔、阵列孔径、源邻近程度和信噪比等采集参数如何影响其结果的不确定性。此外，只有传闻中的建议(往往相互矛盾)来指导相对于所需勘探深度选择这些参数。很可能没有其他非标准化测试在岩土工程中的应用比SWMS更广泛。PI将在他的职业生涯中通过将SWMS从确定性和不连贯转变为概率和标准化(DIPS)来解决这些问题。DIPS计划(旨在消除SWMS中的DIP)包括：(1)量化SWMS中的测量/分散不确定性，以便基于蒙特卡洛的反演可以将这种不确定性向前传播到一套可接受的、具有关于层厚和速度的置信度区间的VS剖面(即，从确定性推进到概率)，以及(2)制定用于解决工程问题的SWMS标准(即，从不连贯的建议推进到连贯的标准)。DIPS计划以VISION为指导，使用四种主要类型的SWMS和系统不同的采集参数，在全国各地的关键基准地点收集和分析一组独特的、大量的和免费共享的实验数据。将使用新提出的方法评估每组采集参数的有意义的色散不确定度。然后将审查离散估计的方法内可变性，并选择不确定度最低的一组参数来支撑标准的制定。通过对弥散不确定度的有意义的估计，蒙特卡罗反演将用于建立V层厚度和速度的可信区间，从而产生完全概率的结果，可纳入后续的基于性能的分析中。在这一步之后，将检查方法间的可变性，以评估各种SWMS和钻孔VS测量之间的偏差。阿肯色大学(UA)已将PI置于独特的地位，以执行DIPS计划，并将其与旨在增加本科生研究经验、多样化学生群体和发展国际合作的现有教育项目相结合。PI致力于将SWMS的研究与教育相结合，从他自己的本科研究项目开始就参与了这一领域。DIPS计划不仅允许学生参与本科生的研究，还将通过UA和意大利都灵理工大学(PDT)之间预先存在的外汇协议，提供在国外度过一个学期的机会。PI在PDT的同事都是面波测试方面的专家，这个项目为我们的机构、教授和学生提供了一个独特的机会，通过本科生研究人员参与国际教育、思想和文化交流。招募学生参加PDT交换将通过工程职业意识计划(ECAP)进行，该计划是UA工程学院的一个计划，结合了几个试点和经过验证的战略，以招募、留住和毕业少数族裔本科生。UA跟踪ECAP学生的进度以评估该计划的影响，提供一个预先存在的机制来跟踪具有国际PDT研究经验的ECAP学生的留住和成功情况。国际学生联合会认为，这一经历将导致100%的留校率，这些代表性不足的学生很有可能通过研究生学习继续他们的教育。

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.