PEER Research Project Highlight: “Geometrically Exact Nonlinear Modeling of Multi-stage Friction Pendulum Systems”

The impact of a PEER funded research project “Geometrically Exact Nonlinear Modeling of Multi-stage Friction Pendulum Systems” is highlighted below. The project Principal Investigator is Sanjay Govindjee, Professor of Civil Engineering, UC Berkeley. The research team includes Paul Drazin, Graduate Student Researcher, UC Berkeley.

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

Research Impact:

California is at a constant risk of a major earthquake, and the proper usage of seismic isolators, such as MSFPs, can drastically reduce the damage sustained to buildings, bridges, etc. due to a seismic event. For this reason, well-functioning models of MSFPs are of importance to make sure that structures are properly isolated in the event of an earthquake. However, current models lack the ability to properly predict isolator response under seismic excitation, which can potentially lead to more physical damage to a structure than was predicted by the model. The proposed developments are designed to directly replace and enhance currently available models for performing design computations on MSFP isolated structural systems. Enhancements are envisaged with respect to both modeling fidelity as well as the robustness of the models within the context of time history analysis systems. These enhanced models are foreseen to help reduce the damage and downtime of structures during post-earthquake recovery. The proposed model will also lead to cost and time savings, since there will be less need to physically test either full-scale or scaled-down MSFPs in a laboratory setting to get accurate results. There is also potential impact for isolating systems other than standard civil structures. Certain machine tools and instruments need to be seismically isolated for proper use, and a more effective and efficient model will make it easier for MSFPs to be developed for these non-structural situations.