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BRIDGE PERFORMANCE: Benchmarking the Performance of California Bridges

BRIDGE PERFORMANCE: Benchmarking the Performance of California Bridges. Bozidar Stojadinovic Kevin Mackie John-Michael Wong Ady Aviram Vesna Terzic University of California, Berkeley. Focus on: Monolithic reinforced concrete construction New rather than older construction detailing

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BRIDGE PERFORMANCE: Benchmarking the Performance of California Bridges

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  1. BRIDGE PERFORMANCE:Benchmarking the Performance of California Bridges Bozidar Stojadinovic Kevin Mackie John-Michael Wong Ady Aviram Vesna Terzic University of California, Berkeley

  2. Focus on: Monolithic reinforced concrete construction New rather than older construction detailing Representative of typical: Over-crossings Viaducts Interchanges Also… Ground motions and their use in analysis and design Soil-foundation interaction Simulation of complex bridge systems Transportation networks PEER Bridge Performance Program

  3. Outline • Performance benchmarking for a baseline testbed bridge suite is done • Practicing bridge engineers can use our work: • Hazard modeling • Non-linear bridge models • Fragility curves • PEER framework • Rational uses of new technologies for bridges are devised and evaluated

  4. PEER Testbed Bridges 5-span RC overpasses (Ketchum, 2004) Type 11 Type 1

  5. Intensity Measure (IM) Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Decision Variable (DV) PEER Framework for Bridge Evaluation Hazard Model Select and scale ground motions Demand Model Damage Model Decision Model

  6. Intensity Measure (IM) Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Decision Variable (DV) C L PEER Framework for Bridge Evaluation Do non-linear time-history analyses Hazard Model Demand Model Damage Model Decision Model

  7. Intensity Measure (IM) Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Decision Variable (DV) PEER Framework for Bridge Evaluation Performance (damage) states Hazard Model Demand Model Damage Model Decision Model

  8. Intensity Measure (IM) Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Engineering Demand Parameter (EDP) discrete Damage Measure (DM) continuous Decision Variable (DV) PEER Framework for Bridge Evaluation Deaths Dollars Down-time Hazard Model Demand Model Damage Model Decision Model

  9. PEER Framework for Bridge Evaluation Outcome: Repair cost ratio fragility curves Demand Model Sa(T1)=1g

  10. 175 worldwide earthquakes >10,000 corrected records with detailed descriptors Estimate ground motion intensity and uncertainty of the estimate Ground motion scaling rules Next-Generation Attenuation Relations http://peer.berkeley.edu/nga Old Data New Data The Practice of Hazard Modeling

  11. Core The Practice of Bridge Modeling Deck Modular OpenSees model Column Foundation Abutment

  12. The Practice of Bridge Modeling Using SAP 2000

  13. Type 1 Type 11 The Practice of Damage Evaluation PEER Structural Performance Database http://nisee.berkeley.edu/spd/index.html

  14. The Practice of Decision Support Performance Groups Damage States Repair Quantities Repair Costs

  15. A Practical Implementation Matlab tool: • Given: • Demand, damage, loss models (with uncertainties) • Numerous assumptions integrate the PEER integral • Easy visualization of results • Decision fragility • Decision hazard

  16. Advances: Non-linear SFS Models • Coupled Soil-Foundation-Structure model Effects of liquefaction and lateral spreading UCB+UW team

  17. Rational use of new technologies: Re-centering columns Tendons Isolators New high-performance materials: HPFRCC Modular construction Precast, prestressed elements 2.5 2.0 HPFRCC Tensile Stress (MPa) 1.5 FRC 1.0 Mortar 0.5 0.0 0.04 0.00 0.01 0.02 0.03 Tensile Strain Advances: Enhancing Performance

  18. Advances: Regional Traffic Networks Regional Shake Map Regional Traffic Network Assessment Bridge Fragility Curves

  19. Conclusion • Performance benchmarking for a baseline testbed bridge suite is done • Practicing bridgeengineers can use our work: • Hazard modeling • Non-linear bridge models • Fragility curves • PEER framework • Rational uses of new technologies for bridges are devised and evaluated Attend Bridge breakout sessions to learn more!

  20. Thank You! Demand Hazard Loss For more information:boza@ce.berkeley.edukmackie@mail.ucf.edu Damage This research was sponsored in part by NSF EERC program grant EEC-9701568 as PEER Project 209/213

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