1. FDOT project: BDV 31-977-21 Project manager: Will Potter University of Florida Principal investigator: Gary Consolazio Graduate research assistant: George Kantrales Determination of Barge Impact Probabilities for Bridge Design 5th Annual FDOT Structures Research Update (Aug. 4-5, 2015) Source: Oklahoma Department of Transportation (ODOT)

2. (2 of 33) Background

3. (3 of 33) More accurate structural analysis procedures Coupled dynamic(barge and bridge together) Simplified dynamic(impact force-time history) Equivalent static(load cases) Barge impact load-prediction model Revised probability of collapse expression (based on reliability analysis) Past UF/FDOT research

4. (4 of 33) No previous research on predicting the frequency of barge-bridge impacts Current AASHTO impact probability expressions developed in late 1980's Changes in vessel technology and operator training Advances in GPS accuracy (within 300 ft to within 40 ft) Lack of available barge-bridge accident data (other vessel casualties also used) Current Work

5. (5 of 33) Propose revisions to AASHTO specifications which predict the frequency of barge-bridge collisions Recent barge traffic and accident data for Florida waterways (approach applicable nationwide) Concentrate solely on barge-bridge collision events Operate within existing AASHTO framework (re- calibrate specific values based on collected data) Objective

6. (6 of 33) Project Tasks Task 1 (completed): Literature review AASHTO, Eurocode, related research Task 2 (completed): Methodology Selection of data sources and analysis procedures Task 3 (nearly complete): Data collection Collection of all data required to perform statistical analyses Task 4 (underway): Data analysis Analysis of collected data, formulation of revised probabilities, and preparation of risk assessment examples Task 5 (outstanding): Final report

7. Task 1: Literature review (completed)

8. (8 of 33) Literature Review 1.AASHTO specifications 2.Eurocode provisions 3.Related research Source: Oklahoma Department of Transportation (ODOT)

9. (9 of 33) AASHTO Bridge Design Spec. (2014) Default design methodology for vessel impact: comprehensive risk assessment Compute the Annual Frequency of Collapse ( AF ) for each bridge element : - Number of vessel transits per year - Probability of vessel aberrancy - Geometric probability of collision - Probability of collapse - Protection factor AF values compared against permissible limits (0.001 for typical bridges, 0.0001 for critical/essential bridges) Probability of Impact (PI)

10. (10 of 33) AASHTO Bridge Design Spec. (2014) Probability of Aberrancy ( PA ): - Base aberrancy rate (0.00006 [ships], 0.00012 [barges]) - Bridge location modification factor - Current (water velocity) modification factor - Cross-current (water velocity) modification factor - Vessel traffic density modification factor

11. (11 of 33) AASHTO Bridge Design Spec. (2014) Geometric Probability ( PG ): Mean corresponds to centerline of vessel transit path Standard deviation is the overall vessel length (LOA) Any bridge elements outside of 3 x LOA from the centerline need not be considered in the risk analysis (AASHTO 2014)

12. (12 of 33) AASHTO Bridge Design Spec. (2014) source: https://www.flickr.com

13. (13 of 33) Eurocode 1: Actions on Structures

14. (14 of 33) Related Research and Findings Relevant research reviewed: Friis-Hansen and Simonsen (2003); Gucma (2003); Hutchinson et al. (2003); Kunz (1998); Larsen (1993); Wang and Wang (2014); Zhang (2013); Zhou (2011) Findings No study focused specifically on quantifying barge-bridge collision probabilities Many variables not readily characterized probabilistically (e.g., human error, current conditions) Most prominent existing empirical method (AASHTO) was developed with limited data Remains a need for a revised empirical approach focused specifically on barge-bridge collisions

15. Task 2: Methodology (completed)

16. (16 of 33) Interviews What factors may have caused a change in BR since the early 1990s? Interview with lead author of existing AASHTO provisions Reviewed basis for existing BR expression Barge-bridge accident data not readily available Different types of vessel casualties used (e.g., strandings) Interviews with tug operators Global positioning systems (GPS) Automatic identification systems (AIS) Electronic chart and display systems (ECDIS) Advances in mechanical technology Changes in operator training

17. (17 of 33) Approach Re-calibrate design base aberrancy rate ( BR ) for barges Collect barge-bridge accident data for Florida bridges Collect supporting information for each bridge site (e.g., barge traffic, water current data) Back-calculate BR values for each bridge location Determine re-calibrated design BR value(s) for barges

18. (18 of 33) Re-calibration of Base Aberrancy Rate ( BR ) Revised BR values will be derived using current AASHTO expressions Probability of Impact ( PI ): the probability that a given vessel will strike the bridge Expanding: Rearranging terms:

19. Task 3: Data collection (nearly complete)

20. (20 of 33) Data Collection – Collision Data (completed) Barge-bridge collision data obtained from United States Coast Guard (USCG) Data collected every year from 2002-2014 Some data available for earlier incidents (as early as 1992) (map adapted from: the United States Geological Survey [USGS])

21. (21 of 33) Data Collection – Collision Data (completed) Collision data sets Contain incident date, location of incident, vessel information, narratives Screened to remove events other than barge-bridge impacts In some cases, relevant data fields were blank (e.g., vessel dimensions were omitted) Collision incident reports (CG-2692 and CG-2692A) Original incident reports for each collision Obtained from the USCG through the Freedom of Information Act (FOIA) Used to obtain information left out of previously collected data and to determine the cause of each collision

22. (22 of 33) Data Collection – Barge Traffic Data (underway) Barge traffic data requested from the United States Army Corps of Engineers (USACE) Data requested every other year from 2002-2014 40% of requested data sets have been obtained Data associated with mile marker locations near bridges Traffic (trips) data organized by year, vessel characteristics (e.g., length, width) and direction of travel

23. (23 of 33) Data Collection – Barge Traffic Data (underway) Processing methodology

24. (24 of 33) Data Collection – Other (completed) Bridge plans Needed for: PG ; PF FDOT district offices Water current data Needed for: R C ; R XC National Oceanic and Atmospheric Administration (NOAA) Hydraulic reports Accident reports

25. Task 3: Data analysis (underway)

26. (26 of 33) Data Analysis – Probability of Impact ( PI Data Analysis – Probability of Impact ( PI ) - Probability of impact (per vessel passage) - Number of vessel casualties that occurred in year t - Number of barge transits from year t i to 2014

27. (27 of 33) Data Analysis – Geometric Probability ( PG ) AASHTO (2014) Flotilla with fewest number of rows and columns will be used Results in a lower calculated PG Conservative re- calibration of BR

28. (28 of 33) Data Analysis – Protection Factor ( PF Data Analysis – Protection Factor ( PF ) source: https://www.flickr.com AASHTO (2014)

29. (29 of 33) Data Analysis – Modification Factors ( R B Data Analysis – Modification Factors ( R B ) AASHTO (2014) Within turn or bend Within transition region 3,000 ft from the end of the turn or bend Smallest R B value will be selected (conservative)

30. (30 of 33) Data Analysis – Modification Factors ( R C,R XC,R D Data Analysis – Modification Factors ( R C,R XC,R D ) AASHTO (2014) Current and cross-current ( R C, R XC ) Calculated directly from velocity data Vessel traffic density ( R D ) Low density ( R D = 1.0) Average density ( R D = 1.3) High density ( R D = 1.6)

31. (31 of 33) - Vessel density factor - Average annual barge traffic - Width of the waterway near the bridge location Data Analysis – Modification Factors ( R D Data Analysis – Modification Factors ( R D ) Selection of R D value for each bridge location Based on calculated VDF values and possible consultation with industry professionals (e.g., tug operators, bridge designers, port captains)

32. (32 of 33) Data Analysis – Re-calibration of BR

33. (33 of 33) Thank you for your attention Questions?