The impact of a PEER funded research project “Performance Based Tsunami Engineering II” is highlighted below. The project Principal Investigator is Harry Yeh, Professor of Civil & Construction Engineering, Oregon State University. The research team includes Dylan Keon, Associate Director of NACSE, Oregon State University and Juan Restrepo, Professor of Mathematics, Oregon State University

Download the Research Project Highlight which includes the abstract. (PDF)

Research Impact:

The development of Performance Based Tsunami Engineering (PBTE) together with the effective IT tool – the Data Explorer – drastically improves the engineering design (or retrofit) practice for critical coastal facilities and structures. The Data Explorer represents an effective tool for the analysis of critical structures that require probabilistic considerations with regard to uncertainty quantification. Significant advances in information technology – in particular, computational speed, data handling, and the ability to store massive datasets and quickly index through them – have facilitated the development of this tool. The Data Explorer can be used to evaluate quantifiable uncertainty supported by the data for a given critical structure. In spite of the presence of substantial uncertainty in tsunami hazard estimates, this tool enables users to comprehensively analyze a structure using the best available engineering models and
knowledge, minimizing potentially unreliable expert judgment and guesswork. The present methodology is necessary for critical facilities that require analysis beyond the justification made via the forthcoming ASCE 7 guidelines. Further development of the Data Explorer is being pursued, including the ability to automate the calculation of additional parameters and the production of additional charts and graphs, as well as the ability to define multiple points of interest in the interface itself and download a spreadsheet containing all simulated and calculated data for all points. The technique called the polynomial chaos method is used for part of the analysis of uncertainty quantification. The development of the Data Explorer was reported in Computer (Keon et al. 2015), the Journal of Disaster Research (Keon et al. 2016), and at the ASCE Coastal Structures & Solutions to Coastal Disasters Joint Conference (Yeh et al. 2015).