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Candase Arnold- Graduate Research Assistant
Dr. Jamie Padgett- Assistant Professor
ICWES15-July 21, 2011
REGIONAL RISK ASSESSMENT OF COASTAL BRIDGES
DURING HURRICANE EVENTS
Towards a More Sustainable, Resilient Infrastructure System
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
MOTIVATION FOR RESEARCH
Emergency Response “Lifeline” routes for goods
and supplies Long term sustainability of
the bridge network
Bridges are among the most critical and
vulnerable components of the transportation
system during an extreme event
TYPICAL FAILURE MECHANISMS
Deck Displacement(Uplift)
Scour Damage
Scour DamageImpact Damage
VULNERABILITY METHODOLOGIES
Inundation of Bridge Deck Conveys short-term
damage or impassability
Compares elevation of bridge with surge height
Previous method of determining bridge vulnerability
Static Bridge Deck Uplift Conveys long-term
structural functionality
Compares capacity of bridge deck with demand of hurricane forces
New method of assessing bridge vulnerability
DECK UPLIFT ILLUSTRATION
BRIDGE DECK UPLIFT- VULNERABILITY MODELING
Static Reliability Assessment for Span Unseating
Probabilistic Demand Estimate
Probabilistic Capacity Estimate
Weight
Uncertainties in materials densities and
superstructure geometry
Uncertainties in materials strengths
Wave and surge parameter estimation and associated
uncertaintiesJoint pdf of wave period and wave
heightUniform distribution for surge elevation
Maximum Demand pdf Capacity pdf
P[Demand > Capacity | Hazard Intensity] =
Probability of Failure (Pf)
Anchorage
ATAEI, N. & PADGETT, J. E. 2010. Probabilistic Modeling of Bridge Deck Unseating during Hurricane Events. ASCE Journal of Bridge Engineering. In Review. November 2010
Adapted from Ataei and Padgett, 2010¹
SCOUR VULNERABILITY MODELING
New probabilistic approach
Uses existing deterministic HEC-18 clay method
Applicable to pier and abutment scour
Pier Parameters
Account for uncertainties in input data
Hydraulic Parameters
Soil Parameters
Pier scour depth using SRICOS
method
Account for uncertainty in predictive model
Obtain PDF of Scour Depth
REGIONAL CASE STUDY- HOUSTON/ GALVESTON BAY AREA
Galveston
REGIONAL CASE STUDY- GALVESTON BAY AREA
Number of Bridges: 155 total (excluding
culverts) 136 used in Uplift
Modeling 123 used in Pier Scour 107 used in Abutment
Scour Sources of Data
National Bridge Inventory Database
TxDOT inspection files SoilMart
9%
5%
3%
25%58%
Bay Area Bridges by Soil Type
SandSandy ClaySilty-SandClay-SiltClay
REGIONAL CASE STUDY- GALVESTON BAY AREA
Parameters Collected: Bridge Type Year Built Connection Details Number of Spans Bridge Dimensions Height above Water Water Depth Soil Type Surge/ Wave Height
18%
50%
28%
4%
Bay Area Bridges by Height Above
Water 0-5 ft5-15 ft15-30 ft30-65 ft
3%
67%1%
29%
Bay Area Bridges by Structure Type
MSC Steel
MSSS Concrete
MSSS Steel
SS ConcreteMSSS- Multi-Span Simply SupportedMSC- Multi-Span ContinuousSS- Single Span
RESULTS FROM CASE STUDY Inundation and Bridge
Deck Uplift Only 3 Hurricane Scenarios
Hurricane Ike Hurricane Ike with
30% stronger wind speeds
“Mighty Ike”- Hurricane Ike with 30% stronger wind speeds and a southern landing position- worst case scenario
Simulation
Failure Probability (%)
0-5 5-25 25-75 75-100
Ike 127 5 1 3
Ike 30% Stronger
106 4 7 19
“Mighty Ike”
69 7 8 52
Failure Probability of Bridge Deck Uplift for hurricane scenarios
Hurricane Ike ScenarioStorm surge data courtesy of Dawson and Proft, UT Austin
30% Stronger Ike ScenarioStorm surge data courtesy of Dawson and Proft, UT Austin
“Mighty Ike” ScenarioStorm surge data courtesy of Dawson and Proft, UT Austin
“Mighty Ike” InundationStorm surge data courtesy of Dawson and Proft, UT Austin
“Mighty Ike” ComparisonStorm surge data courtesy of Dawson and Proft, UT Austin
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
CLOSING REMARKS
Future Work: Complete pier and
abutment scour models
Assess soil erosion potential at roadways
Full automation of all risk assessment models together for predictive modeling
Conclusions: Coastal bridges are vulnerable
to both deck displacement and scour during hurricanes
New probabilistic models in deck displacement and scour determination are developed and applied to a regional risk 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
Acknowledgments:
NSF: Graduate Research Fellowship Program
Houston Endowment
Navid Ataei: Graduate Research Assistant
QUESTIONS?