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.
