Session 5D: Benefits of Live Load Testing and Finite Element Modeling in Rating Bridges Douglas R. Heath P.E., Structural Engineer Corey Richard P.E., Project Manager AECOM
Overview Bridge Testing/Rating Program implemented for RIDOT Testing: Ground penetrating radar (GPR) Material Testing Live Load Testing Rating: Development and calibration of finite element (FE) models against test data Outcome: Additional sources of bridge capacity and greater live load distribution identified Increased rating factors Lowering and/or removal or postings
Agenda Project background Overview of testing procedures FE modeling considerations Case Study: Johnsons Pond Bridge Benefits to testing and FE modeling approach Current trends and recommendations for future work
Project Background Project Objectives: Convert all bridge ratings to updated LRFR methodology Improve state s Functionally Obsolete/Structurally Deficient bridge list by improving/removing postings Strategy for improving bridge deficiency list: Many structures lacked enough information to perform accurate rating analysis à arbitrary load limits imposed Testing performed to develop analytic models for rating Live load testing results used to calibrate 3D FE models Gain confidence in models Identify additional sources of capacity and improved live load distribution Lead to increased rating factors and removal of load limits
Ground Penetrating Radar Uses reflected electromagnetic waves for evaluating subsurface conditions Requires site-specific calibration Used to determine depths of fill and rebar patterns
Material Testing Concrete cores removed from the structure and tested for compressive strength Provides insight into capacity and stiffness Typically shows higher strengths than design plans http://www.fhwa.dot.gov/publications/research/infrastructure/structures/07024/chapt3.cfm, 2012
Live Load Testing Structure instrumented with strain, tilt, and displacement sensors Truck with known weight driven across the bridge at crawl speed (~5 mph) Measurements used to calibrate FE models
Live Load Testing Estimates of Load Rating Improvement Bridge Type Influencing Factors % Improvement R/C Slabs Greatest benefit, end conditions, edge stiffening, no longitudinal joints 30 to 60% Beam Slab Bridges Culverts and arches Ratings controlled by moment, Beam lines > wheel lines, End conditions and edge stiffening Function of fill depth, endconditions, span length 20 to 40% 20 to 30% Truss Bridges Members inline with floor system 0 to 30% RC T-Beam/Shear Pre 1975 Ratings controlled by shear, # of beam lines, edge stiffening. 2 Girder bridges No improvement in distribution. End conditions may influence ratings. 0 to 15% 0 to 15%
FE Modeling Provides versatile means of modeling à calibration against test results Improved accuracy over code-specified procedures May simplify analysis
Factors Affecting Bridge Capacity/Stiffness Reference: NCHRP Research Results Digest 234 1. Unintended Composite Action 2. Effects of Deterioration 3. Load Distribution Effects 4. Material Properties Differences 5. Unintended Continuity Limits of Effective Width Interface Stress (p) Jeffrey, Breña, and Civjan (2009)
Factors Affecting Bridge Capacity/Stiffness (cont d) Reference: NCHRP Research Results Digest 234 6. Participation of Parapets, Railings, Curbs, and Utilities 7. Participation of Secondary Members 8. Portion of Load Carried by Deck 9. Effects of Skew 10. Unintended Arching (Shear Friction) P bearing P bearing Locked bearings can act as a form of pre-stress
Case Study: Johnsons Pond Bridge Reinforced Concrete (R/C) slab bridge Constructed in 1934 Single 30-0 span Heavily cracked underside
Testing Plan Instrumented with 32 sensors 23 strain gauges, 7 displacements sensors, 2 tiltmeters 3 load paths considered Test gauge malfunction
Preliminary Review of Test Data Initial review of data to inform modeling process Determine: Participation of parapets Usefulness of strain data Effective width Rotational end restraint
Model Development Consists of solid and link elements Curbs and parapets explicitly modeled End restraint at abutments provided 14,560 nodes & 10,240 elements
Model Calibration Calibrate by varying selected parameters: Abutment rotational support Concrete elastic modulus Upper and lower bound values established à used to infer calibrated value Revise as necessary
Parapet Participation FE model consistently over-predicted strains Calibration attempts: Vary elastic modulus of slab and parapet Flexible connection between slab and parapet Test data showed small strains Conclusion: Parapet was not participating in resisting loads
Model Validation Qualitative: Visual comparison of force effect plots Quantitative: Comparison of 3 statistical metrics Correlation Coefficient Absolute Error Percent Error Line 1 Deflection 0.916-60.48% 23.26% Line 2 Deflection 0.963-33.97% 28.70% Line 3 Deflection 0.975-14.22% 14.72% Line 4 Deflection 0.983-19.81% 12.68% Path Y1 Line 5 Deflection 0.984-3.21% 3.90% Line 6 Deflection 0.975 9.12% 3.31% Line 7 Deflection 0.978 20.70% 0.52% West Rotation 0.842 4.56% 1.60% East Rotation 0.976 34.12% 26.68% Average 0.955-7.02% 12.82% Line 1 Deflection 0.959-7.10% 5.56% Line 2 Deflection 0.970-3.44% 8.26% Line 3 Deflection 0.980-4.02% 5.25% Line 4 Deflection 0.981-19.14% 10.18% Path Y2 Line 5 Deflection 0.980-11.02% 7.58% Line 6 Deflection 0.972-4.80% 9.40% Line 7 Deflection 0.961-27.11% 20.42% West Rotation 0.877 8.96% 0.00% East Rotation 0.983 4.58% 0.04% Average 0.963-7.01% 7.41% Line 1 Deflection 0.966 16.18% 2.51% Line 2 Deflection 0.969-2.64% 7.03% Line 3 Deflection 0.978-11.28% 8.87% Line 4 Deflection 0.978-12.94% 9.96% Path Y3 Line 5 Deflection 0.968-19.89% 14.52% Line 6 Deflection 0.924-7.03% 0.73% Line 7 Deflection 0.917-54.50% 48.73% West Rotation 0.854 15.56% 1.37% East Rotation 0.959-7.48% 1.58% Average 0.946-9.34% 10.59% Average of All Tests 0.954-7.79% 10.27% Parameter Value E slab West k θ East k θ 3,200 ksi 3,000 k/in 11,000 k/in
Rating Modifications to model: Apply external dead loads Apply rating vehicle loads Post-Processing: Factor load output Calculate section capacity Compute rating factors VEHICLE TYPE Adjust rating based on comparison of FE output to test results RF INV 1.78 HL-93 OPER 2.30 H20 3.59 TYPE 3 3.58 TYPE 3S2 3.69 TYPE 3-3 4.41 SU 4 3.59 SU 5 3.36 SU 6 3.06 SU 7 2.93 RI-BP 1 2.11 RI-BP2 2.19 RI-BP 3 2.39 RI-BP 4 1.82 RI-OP1 2.69 RI-OP2 2.91 RI-OP3 3.49
Comparison to Previous Rating Structure rated 1 year prior using traditional methods Previous rating assumed simply supported slab Resulted in higher midspan moments and decreased RF DL DW LL Calibrated FEM Moment (ft*k) 23.58 5.47 23.04 Traditional Rating Moment (ft*k) 54.30 14.51 48.40 VEHICLE TYPE CALIBRATED FEM TRADITIONAL RATING HL-93 INV 1.78 0.52 OPER 2.30 0.67 H20 3.59 0.93 TYPE 3 3.58 1.03 TYPE 3S2 3.69 1.06 TYPE 3-3 4.41 1.26 SU 4 3.59 1.04 SU 5 3.36 0.98 SU 6 3.06 0.90 SU 7 2.93 0.84 RI-BP 1 2.11 0.60 RI-BP2 2.19 0.63 RI-BP 3 2.39 0.72 RI-BP 4 1.82 0.62 RI-OP1 2.69 0.64 RI-OP2 2.91 0.75 RI-OP3 3.49 0.86
Summary of Testing Program Bridges were tested to: Verify structural configurations (arches, frames, slabs) Identify additional sources of capacity (frames, slabs, girders) Number of Bridges Tested 8 7 6 5 4 3 2 1 0 Types of Bridges Tested Total: 29
Overall Benefits of the Program Testing program has led to:» Total removal of load restrictions from 8 Bridges» Previously posted for 7T-19T» Increases in allowable load postings» Better understanding of real world vs code guided ratings RIDOT now has electronic models of all bridge Posting Increased from 10T to 19T structures.» Ease of assessing structures for special permit vehicle crossings» Ease of updating ratings/postings for future condition changes found during inspections
Current Trend: FE Calibration Through Optimization Techniques Use a computer to determine appropriate model input values Research at Tufts and UNH PARIS open source software MUSTANG program Other proprietary examples http://engineering.tufts.edu/cee/people/sanayei/paris/home.html Accessed 02/25/15
Future Work: How to Determine Effective Width? Procedure for finding b eff : (Reference: Jones, 2011) 1. Find A1 & A2 from Actual Strain Distribution 2. Transform A1 & A2 into rectangles with height = Max. Strain 3. b eff = (Min Width from A1 or A2) + ½ Axle Width Idealized Strain Distribution Actual Strain Distribution A1 A1 Axle Width =7 Axle Width =7 A2 A2 Max. Strain Max. Strain Max. Micro-Strain - Midspan 12.00 10.00 8.00 6.00 4.00 2.00 0.00 A1 Axle Width 7 Max. Strain 0 5 10 15 20 25 30 35 40 45 A2 Transverse Location (ft)
Future Work: How to Determine Material Properties from Testing? How to find compressive strength (f c )? Core C- 1 C- 2 C- 3 C- 4 C- 5 C- 6 Dia. (in) 2.75 2.75 2.75 2.75 2.75 2.75 Length (in) 3.88 N/A 5.63 5.13 5.50 5.25 Area (in^2) 5.94 5.94 5.94 5.94 5.94 5.94 Max. Load (lb) 44,520 N/A 19,840 37,570 36,010 37,110 Strength (psi) 7,490 N/A 3,340 6,320 6,060 6,250 L/D 1.35 <1.0 1.96 1.78 1.91 1.83 Adj. Factor 0.94 N/A 1.00 1.00 1.00 1.00 Adj. Strength (psi) 7,060 N/A 3,340 6,320 6,060 6,250 ACI 318 & ACI 214 provide guidance based on: f cr = Average Compressive Strength = 5806 psi s= Standard Deviation of Compressive Strength = 1430 psi n = Number of Samples = 5 For n<15, use ACI 318 T.5.3.2.2 Design Strength (f'c) (psi) Average Strength (f'cr) (psi) If more cores are sampled, different f'c<3000 f'cr=f'c+1000 methods can be used: 3000<f'c<5000 f'cr=f'c+1200 f'c>5000 f'cr=1.10f'c+700 1. Standard Deviation Method 2. Coefficient of Variation Method
Additional Recommendations for Future Work FE calibration acceptance criteria Work by Mongiardini, 2010 How closely does the model result need to match the test result? Which test results are most important to compare and what can be neglected? Reliability of factors affecting bridge capacity Can we rely on the strength provided by parapets? What if they are damaged in a collision? Support fixity? etc.
Conclusion Program resulted in removal of posting loads Role of testing: Provide geometry, material properties, reinforcement patters using survey data, material testing, and GPR to develop analytical models Gain insight into structural behavior and possible additional sources of structural capacity Role of FE modeling: Allows for flexible modeling approach Able to identify sources of capacity and assess their reliability Current Trends and Future Work: FE calibration through optimization techniques Guidelines for determining acceptance criteria for FE calibration, effective width, concrete strength, and reliability of factors affecting bridge capacity
Acknowledgements Bridge Diagnostics Incorporated: Live Load Testing and GPR Aries Support Services: Traffic Management and Material Testing AECOM Bridge Rating/Inspection Team
References (1) Jones, Brian P. "Reevaluation of the AASHTO Effective Width Equation in Concrete Slab Bridges in Delaware." Thesis. Newark Delaware, University of Delaware, 2011. (2) AASHTO LRFD Bridge Design Specifications. Washington D.C.: American Association of State Highway and Transportation Officials, 2010. Print. (3) The Manual for Bridge Evaluation. Washington D.C.: American Association of State Highway and Transportation Officials, 2010. Print. (4) CSI Analysis Reference Manual. Berkley, California: Computers & Structures Incorporated, 2011. (5) Manual for Bridge Rating Through Load Testing. Washington D.C.: National Cooperative Highway Research Program, 1998. Print. (6) Jeffrey, Andrew, Sergio Brena, and Scott Civjan. Evaluation of Bridge Performance and Rating through Non-Destructive Load Testing. 2009.
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