NEES @ UC San Diego
Performance-Based Seismic Design for Reinforced Masonry Shear-Wall Structures Large-Scale Validation of Seismic Performance of Bridge Columns Collapse Vulnerability and Seismic Design of Metal Building Systems Seismic Study of Wind Turbines for Renewable EnergySeismic Design of Retaining Walls with/without Sound Wall Seismic Response of a 7-Story RC Building

NEES @ UC San Diego Large High Performance Outdoor Shake Table

The world's first outdoor shake table is also the largest in the U.S. learn more

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Project Description: The objective of the research project is to develop improved and validated rational guidelines for seismic design of cut-and-cover tunnels to overcome the drawbacks in the existing Caltrans design specification and tools. The research work involves intensive dynamic tests for the 1/9 scale steel tunnel specimen (4 ft height, 6 ft width, and 9 ft long in model scale), that is adopted from the Doyle Drive Battery Tunnel (reinforced concrete structure, San Francisco, CA). The tunnel model is fully buried at shallow depth (2 ft) in dry soil using a large scale laminar soil shear container, funded by the California Department of Transportation. The container consists of 31 steel laminar frames, each separated by a steel roller system to allow for uni-directional displacement. Dimensions of the container are a length of 22 ft, a width of 9.6 ft, and a height of 15.2 ft. The tunnel and soil will be extensively instrumented to acquire measurements of accelerations, displacements, strains, earth/soil pressures, etc, during the shaking. Each soil-foundation system will be tested under a series of earthquakes starting with slow motions with low amplitude and culminating with severe earthquake motions (e.g., Northridge record, M=6.7). The outcome of this research will ensure that future cut-and-cover tunnels are designed to a higher performance standard and existing systems are upgraded to offer satisfactory performance.

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The Large High-Performance Outdoor Shake Table is supported in part by the George E. Brown, Jr. Network for Engineering Simulation (NEES) program of the National Science Foundation under Award Number CMMI-0927178.

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