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?