IC WES15 - Towards a More Sustainable, Resilient Infrastructure System: Regional Risk Assessment of Coastal Bridges during Hurricane Events. Presented by Candase D Arnold, USA
This document summarizes a regional risk assessment of coastal bridges in the Galveston Bay area during hurricane events. It presents new probabilistic models for estimating bridge deck uplift and pier/abutment scour failure probabilities. A case study of over 100 bridges found failure probabilities increased for stronger hurricane scenarios. Implications include using results to prioritize bridge retrofits and post-hurricane recovery routes. Future work includes completing scour models and fully automating the risk assessment.
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The market for mobile banking and other mobile financial services is growing at an ever increasing rate, with customer adoption in the US set to grow to 56 million users in the next few years. Institutions that have led the way are already seeing customer loyalty, return per customer and customer acquisition benefits.
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Luxury brands market their product in a way that creates great brand awareness, like Chanel N5 or RR Phantom. This prsentation talks about how these brands sell without selling, Have a look at a common framework, analyse 8Ps abstractions and Examples
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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. REGIONAL RISK ASSESSMENT OF
COASTAL BRIDGES DURING HURRICANE
EVENTS
Candase Arnold- Graduate Research Assistant
Dr. Jamie Padgett- Assistant Professor
ICWES15-July 21, 2011
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. 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
8. 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 during
Hurricane Events. ASCE Journal of Bridge Engineering. In Review. November 2010
9. 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
11. REGIONAL CASE STUDY- GALVESTON BAY
AREA
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
12. 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 Supported
MSC- Multi-Span Continuous SS Concrete
SS- Single Span
13. 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
19. 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
20.
21. 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