REGIONAL RISK ASSESSMENT OFCOASTAL BRIDGES DURING HURRICANE             EVENTS Candase Arnold- Graduate Research Assistant...
OVERVIEW AND OBJECTIVES   Motivation for Research     Empirical evidence from past hurricanes     Typical failure mecha...
MOTIVATION FOR RESEARCH                     Bridges are among the                   most critical and vulnerable          ...
TYPICAL FAILURE MECHANISMS
VULNERABILITY METHODOLOGIES   Inundation of Bridge            Static Bridge Deck    Deck                             Upl...
DECK UPLIFT ILLUSTRATION
BRIDGE DECK UPLIFT- VULNERABILITY   MODELING Adapted from Ataei and Padgett, 2010¹                                        ...
SCOUR VULNERABILITY MODELING                              Pier        Hydraulic           Soil New probabilistic        P...
REGIONAL CASE STUDY- HOUSTON/GALVESTON BAY AREA                  Galveston
REGIONAL CASE STUDY- GALVESTON BAYAREA   Number of Bridges:              Bay Area Bridges by Soil                        ...
REGIONAL CASE STUDY- GALVESTON BAY  AREA                  Bay Area Bridges by                                         Heig...
RESULTS FROM CASE STUDY   Inundation and Bridge    Deck Uplift Only   3 Hurricane Scenarios       Simulation       Failu...
Hurricane Ike Scenario    Storm surge data courtesy of Dawson and Proft, UT Austin
30% Stronger Ike Scenario    Storm surge data courtesy of Dawson and Proft, UT Austin
“Mighty Ike” Scenario    Storm surge data courtesy of Dawson and Proft, UT Austin
“Mighty Ike” Inundation    Storm surge data courtesy of Dawson and Proft, UT Austin
“Mighty Ike” Comparison    Storm surge data courtesy of Dawson and Proft, UT Austin
IMPLICATIONS FOR SUSTAINABILITY   Predictive Failure Probabilities       Can be utilized to predict damage as a hurrican...
CLOSING REMARKS   Future Work:                       Conclusions:     Complete pier and                  Coastal bridg...
Acknowledgments:NSF: Graduate Research Fellowship ProgramHouston EndowmentNavid Ataei: Graduate Research Assistant
IC WES15 - Towards a More Sustainable, Resilient Infrastructure System:  Regional Risk Assessment of Coastal Bridges durin...
IC WES15 - Towards a More Sustainable, Resilient Infrastructure System:  Regional Risk Assessment of Coastal Bridges durin...
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IC WES15 - Towards a More Sustainable, Resilient Infrastructure System: Regional Risk Assessment of Coastal Bridges during Hurricane Events. Presented by Candase D Arnold, USA

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IC WES15 - Towards a More Sustainable, Resilient Infrastructure System: Regional Risk Assessment of Coastal Bridges during Hurricane Events. Presented by Candase D Arnold, USA

  1. 1. REGIONAL RISK ASSESSMENT OFCOASTAL BRIDGES DURING HURRICANE EVENTS Candase Arnold- Graduate Research Assistant Dr. Jamie Padgett- Assistant Professor ICWES15-July 21, 2011
  2. 2. OVERVIEW AND OBJECTIVES Motivation for Research  Empirical evidence from past hurricanes  Typical failure mechanisms Methodologies for Estimating Failure Probability  Bride Deck Uplift  Pier and Abutment Scour Galveston Bay Area Case Study Results from Hurricane Simulations Implications for Sustainability Conclusions and Future Work
  3. 3. MOTIVATION FOR RESEARCH Bridges are among the most critical and vulnerable components of the transportation system during an extreme event  Emergency Response  “Lifeline” routes for goods and supplies  Long term sustainability of the bridge network
  4. 4. TYPICAL FAILURE MECHANISMS
  5. 5. VULNERABILITY METHODOLOGIES Inundation of Bridge  Static Bridge Deck Deck Uplift  Conveys short-term  Conveys long-term damage or structural functionality impassability  Compares capacity of  Compares elevation of bridge deck with bridge with surge height demand of hurricane  Previous method of forces determining bridge  New method of vulnerability assessing bridge vulnerability
  6. 6. DECK UPLIFT ILLUSTRATION
  7. 7. BRIDGE DECK UPLIFT- VULNERABILITY MODELING Adapted from Ataei and Padgett, 2010¹ Static Reliability Assessment for Span Unseating Probabilistic Demand Probabilistic Capacity Estimate Estimate Wave and surge parameter estimation Weight Anchorage and associated uncertainties Joint pdf of wave period Uncertainties in materials and wave height densities and superstructure geometry Uniform distribution for surge elevation Uncertainties in materials strengths Maximum Demand pdf Capacity pdf P[Demand > Capacity | Hazard Intensity] = Probability of Failure (Pf)ATAEI, N. & PADGETT, J. E. 2010. Probabilistic Modeling of Bridge Deck Unseating duringHurricane Events. ASCE Journal of Bridge Engineering. In Review. November 2010
  8. 8. SCOUR VULNERABILITY MODELING Pier Hydraulic Soil New probabilistic Parameters Parameters Parameters approach Uses existing Account for uncertainties deterministic HEC-18 in input data clay method Applicable to pier and Pier scour depth using SRICOS abutment scour method Account for uncertainty in predictive model Obtain PDF of Scour Depth
  9. 9. REGIONAL CASE STUDY- HOUSTON/GALVESTON BAY AREA Galveston
  10. 10. REGIONAL CASE STUDY- GALVESTON BAYAREA Number of Bridges: Bay Area Bridges by Soil Type  155 total (excluding culverts) 5%  136 used in Uplift Modeling 9% 3% Sand  123 used in Pier Scour Sandy Clay  107 used in Abutment Scour Silty-Sand 25% Sources of Data 58% Clay-Silt  National Bridge Inventory Clay Database  TxDOT inspection files  SoilMart
  11. 11. REGIONAL CASE STUDY- GALVESTON BAY AREA Bay Area Bridges by Height Above Water  Parameters Collected: 4%  Bridge Type 18% 0-5 ft 28% 5-15 ft  Year Built 15-30 ft  Connection Details 50% 30-65 ft  Number of Spans  Bridge Dimensions Bay Area Bridges by  Height above Water Structure Type  Water Depth 3% MSC Steel  Soil Type 29% MSSS  Surge/ Wave Height Concrete 1% MSSS Steel 67%MSSS- Multi-Span Simply SupportedMSC- Multi-Span Continuous SS ConcreteSS- Single Span
  12. 12. RESULTS FROM CASE STUDY Inundation and Bridge Deck Uplift Only 3 Hurricane Scenarios Simulation Failure Probability (%)  Hurricane Ike 0-5 5-25 25-75 75-100  Hurricane Ike with 30% Ike 127 5 1 3 stronger wind speeds  “Mighty Ike”- Hurricane Ike 30% 106 4 7 19 Ike with 30% stronger Stronger wind speeds and a “Mighty Ike” 69 7 8 52 southern landing position- worst case Failure Probability of Bridge Deck Uplift for scenario hurricane scenarios
  13. 13. Hurricane Ike Scenario Storm surge data courtesy of Dawson and Proft, UT Austin
  14. 14. 30% Stronger Ike Scenario Storm surge data courtesy of Dawson and Proft, UT Austin
  15. 15. “Mighty Ike” Scenario Storm surge data courtesy of Dawson and Proft, UT Austin
  16. 16. “Mighty Ike” Inundation Storm surge data courtesy of Dawson and Proft, UT Austin
  17. 17. “Mighty Ike” Comparison Storm surge data courtesy of Dawson and Proft, UT Austin
  18. 18. IMPLICATIONS FOR SUSTAINABILITY Predictive Failure Probabilities  Can be utilized to predict damage as a hurricane moves through the Gulf of Mexico Mitigation and Retrofit Efforts  Testing various retrofit measures like increased connection between sub and super-structure  Prioritize bridges for retrofit or rebuilding Post Event Re-Entry and Recovery Efforts  Assess “life-line” routes onto Galveston Island  Prioritize supply and emergency services locations based on spatial distribution of damage
  19. 19. CLOSING REMARKS Future Work:  Conclusions:  Complete pier and  Coastal bridges are vulnerable to abutment scour models both deck displacement and  Assess soil erosion scour during hurricanes potential at roadways  New probabilistic models in deck  Full automation of all risk displacement and scour assessment models determination are developed and together for predictive applied to a regional risk modeling assessment  Case study shows that a future worst case scenario storm could devastate the bridge network.  Results can be used to prioritize bridge retrofits, emergency services locations and post-event re-entry routes
  20. 20. Acknowledgments:NSF: Graduate Research Fellowship ProgramHouston EndowmentNavid Ataei: Graduate Research Assistant

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