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.

该教师早期职业发展（CAREER）计划奖由土木、机械和制造创新部门以及国际科学与教育办公室共同资助。 过去十年来，表面波方法 (SWM) 已成为岩土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 (Vs) 的地下剖面 - 被用作关键输入许多工程分析中的参数。 SWM 的使用不断扩大，是因为人们希望“到达”地球内部并在无需钻孔的情况下检索准确且有意义的工程参数。 传统上，SWM 用于为每个测试站点提供单一的、确定性的 Vs 剖面，而不考虑测量/色散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，随着该行业转向概率设计和基于性能的工程，无法量化 SWM 的 V 的不确定性已成为未来进步的主要障碍。 越来越多的研究人员和从业者在使用 SWM 时，并不了解空间采样间隔、阵列孔径、源接近度和信噪比等采集参数如何影响其结果的不确定性。 此外，仅存在轶事建议（通常是相互冲突的）来指导相对于所需勘探深度选择这些参数。 岩土工程中可能没有其他非标准化测试比 SWM 更广泛地使用。 PI 将通过将 SWM 从确定性和不连贯性转变为概率性和标准化 (DIPS) 来解决其职业生涯中的这些问题。 DIPS 计划（旨在“平滑 SWM 中的下降”）涉及：(1) 量化 SWM 中的测量/色散不确定性，以便可以使用基于蒙特卡罗的反演将这种不确定性向前传播到一组可接受的 Vs 剖面中层厚度和速度的置信区间（即从确定性进展到概率性），以及（2）制定用于解决工程问题的 SWM 标准（即从确定性进展到概率性）不一致的建议与一致的标准）。 DIPS 计划的愿景是使用四种主要类型的 SWM 以及系统地变化的采集参数，在全国各地的关键基准站点收集和分析一组独特的、大量的、自由共享的实验数据。 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性。 然后将检查分散估计的方法内变异性，并选择不确定性最低的参数集来锚定标准的制定。 通过对色散不确定性进行有意义的估计，蒙特卡罗反演将用于建立 Vs 层厚度和速度的置信区间，从而产生完全概率的结果，可以将其纳入后续基于性能的分析中。 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 测量之间的偏差。阿肯色大学 (UA) 已将 PI 置于独特的位置来执行 DIPS 计划并将其与现有的集成教育计划旨在增加本科生研究经验、使学生群体多样化并发展国际合作。 PI 致力于将 SWM 的研究和教育结合起来，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研究，还将通过 UA 与意大利都灵理工大学 (PDT) 之间现有的外汇协议提供在国外度过一个学期的机会。 PDT 的 PI 同事都是表面波测试方面的专家，该项目为我们的机构、教授和学生通过本科研究人员参与国际教育、思想和文化交流提供了独特的机会。 参与 PDT 交流的学生将通过工程职业意识计划 (ECAP) 进行招募，该计划是 UA 工程学院的一项计划，结合了几种经过试点和行之有效的策略来招募、保留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，提供现有机制来跟踪具有国际 PDT 研究经验的 ECAP 学生的保留和成功。 PI 认为，这种经历将带来 100% 的保留率，并且这些代表性不足的学生很有可能通过研究生学习继续接受教育。