Fault Displacement Mapping of the 2023 Türkiye Earthquake Ruptures for Seismic Risk Reduction in the U.S.
The intellectual merit of this work lies in setting a new paradigm in fault rupture field mapping for engineering applications. While there is field, laboratory and numerical evidence that shallow geological conditions affect fault displacements, the evidence is at best qualitative, and thus the documented data cannot be integrated in engineering models for risk reduction. If we want to capture these effects in predictive empirical models for engineering applications, we need a new kind of dataset that associates each fault displacement measurement site with geotechnical site characterization measurements. Our primary field objectives include characterization of the 2023 ruptures by means of: (1) mapping the main fault rupture with high-resolution (cm-scale) GNSS surveys, photographs, ground-based lidar, and UAV-based terrain models, (2) documenting discrete and perishable offsets of cultural and geomorphic features, (3) characterizing the width and style of the deformation zone, (4) accompanying the measurements of the transient deformation zones with dynamic site characterization measurements on a sub-km scale using active source and ambient wavefield surface wave methods, along with horizontal to vertical spectral ratio (HVSR) measurements, (5) providing geological context (e.g., dominant geological processes and depositional units) for site characterization efforts, and (6) identifying secondary effects such as gravitational failures and liquefaction. Insights and scaling behaviors stemming directly from our field data will provide the first of what we envision will constitute the next-generation fault displacement datasets that will allow future PFDHA models to capture repeatable effects associated with local geologic conditions and fault geometry among other parameters.
Seepage Investigation of Hindsville and Elmdale Lake Dams
Updating ARDOT Liquefaction Evaluation Procedures
Advancing the Development of Realistic and Probabilistic Shear Wave Velocity Profiles Using Advanced Inversion Strategies
The intellectual merit of this research lies in the development of state-of-the-art surface wave inversion algorithms. These algorithms will incorporate a Bayesian statistical framework into high-level inversion algorithms using machine learning and trans-dimensional Monte Carlo methodologies. The algorithms will incorporate expert knowledge into the inverse problem and characterize the uncertainty of the developed Vs profiles based on the experimental data. The use of Bayesian and machine learning methods will allow uncertainty in the solution to be considered and presented in a more robust way than current approaches. In addition, further understanding of the petrophysical link between multiple data types advances our knowledge of how different data types work together within joint inversion frameworks to constrain the inversion problem. Advances in the inversion framework will produce broader impacts for multiple applications including site response, liquefaction analysis, and infrastructure evaluation. Moreover, the development of more accurate, realistic, and probabilistic Vs profiles allows for the inclusion of resulting shear wave velocity profiles into performance-based designs. Lastly, advancements in inversion algorithms and knowledge of petrophysical links are transferable to other non-invasive geophysical methods, which all suffer from non-uniqueness issues.
Rapid Assessment of Internal Erosion Damage and Erodibility in Levees
Applying UAS LiDAR for Developing Small Project Terrain Models
The overarching objective of this research effort is to assess the accuracy and benefits of using UAS LiDAR to collect high quality survey data for small area projects such as bridge replacements. This study will adhere to federal regulations 14 CFR Part 107, the FAA’s regulations for small unmanned aerial systems.
Ohio River Valley Supply Chain Scenario Analysis
RAPID/Collaborative: Dynamic site characterization following the Mw 7.1 Puebla Earthquake for the development of a refined 3D shallow crust velocity model of the Mexico City Basin
Mapping Subsurface Conditions for Transportation Applications
Development of Deep Shear Wave Velocity Profiles at Seismic Stations in the Mississippi Embayment
Rapid and Continuous Assessment of Soil Condition Along Highway Alignments
Rapid and non-destructive assessment of levees for strength and liquefaction resistance
Deep Shear Wave Velocity Profiling in North-Eastern Arkansas
Development of the MASW Method for Pavement Evaluation
Evaluating the Condition of Asbestos-Cement Pipe within the Bella Vista Village Water Distribution System
Dynamic site characterisation of Canterbury strong motion stations using surface wave testing to resolve shallow and deep stratigraphy