Multi-Site Soil-Structure-Foundation Interaction Test (MISST)
The MISST concept was developed to provide a realistic test bed application with which to verify and extend all components of hybrid distributed simulation as well as all components of the sites taking part in the experiment. Concurrently, it has extended and represents the current state-of-the-art in distributed and integrated experimental-analytical earthquake structural and geotechnical engineering simulations.
The MISST structure is based on the Collector-Distributor 36 of the I-10 Santa Monica Freeway which was damaged during the 17 January 1994 Northridge Earthquake. The idealized structure and sub-structuring scheme are illustrated in Figures 1 and 2 respectively. The distributed simulation will be orchestrated by UI-SIMCOR, UIUC’s simulation coordinator software. UI-SIMCOR handles all inter-module communication and hosts the numerical integration scheme. As shown in the figure below, large-scale pier specimens at the UIUC and Lehigh sites are combined with advanced soil models at RPI.
- Input Motion: Northridge EQ, Station – Newhall Fire, PGA = 0.583g
- 1210 steps imposed
- Lehigh Pier: Total loss of load-carrying capacity
- UIUC Pier: Two stage failure
- The coordination of three sites, Lehigh, UIUC and RPI, for a five-component hybrid (testing-analysis), geographically distributed NEES simulation worked seamlessly.
- The redistribution of forces between the two sites with bridge piers as either of the two suffered partial failure shows that a full interaction was taking place between the distant sites at each time step.
- The failure modes obtained are similar to those observed in the Northridge earthquake, thus opening the door to formulating design and retrofitting approaches to avoid such failures in the future.
- Lehigh University
- University of Illinois at Urbana-Champaign (UIUC)
- Rensselaer Polytechnic Institute (RPI)
- James Ricles – Lehigh University
- Bill Spencer – UIUC
- Amr Elnashai – UIUC
- Daniel Kuchma – UIUC
- Tarek Abdoun – RPI