Concrete Tie Degradation Study Tie Condition and Crack Growth Rate - PowerPoint PPT Presentation

Concrete Tie Degradation Study Tie Condition and Crack Growth Rate Assessment Final Results Funded By Federal Railroad Administration Office of Research and Development Under Broad Agency Announcement BAA-2010-1 June 5, 2014 Presented by: Jeff Henderson ENSCO, Inc. Federal Railroad Administration Office of Research and Development

Study Overview • Main Objective Using machine vision technology, develop a better understanding of concrete tie degradation • Project Team – FRA Office of Research and Development – AMTRAK – ENSCO Sponsored by the Federal Railroad Administration under BAA-2010-1 Federal Railroad Administration Office of Research and Development

Technical Approach Overview 1) Image 100 miles of track 3 times over ~1-year 2) Use software to manually align track bed images 3) Grade ties and determine crack growth rates 4) Assess concrete tie degradation over time Federal Railroad Administration Office of Research and Development

Technology Used Hi-rail-based Machine Vision Imaging System • High Data Rate Line Scan Machine Vision Cameras • High Data Rate Solid State Hard Drives • High-intensity LED Lighting Federal Railroad Administration Office of Research and Development

Test Zone Location (Amtrak’s AB Line, Northeast Corridor) Track Mile Post Mile Post Total Miles Number Start End 1 187 158 29 1 218 189 29 2 143 158 15 2 187 159 28 2 189 218 29 Total Number of Miles 130 Federal Railroad Administration Office of Research and Development

Summary of Test Schedule • Survey 1 – August 16 to 19, 2012 • Survey 2 – April 15 to 19, 2013 • Survey 3 –September 23 to 25, 2013 Federal Railroad Administration Office of Research and Development

Concrete Tie Degradation Study Summary of Analysis Approaches Subjective Analysis Assess general tie conditions • Evaluate tie degradation based on tie grades • Grading scale: 1-good to 5-ineffective • Assess a large population of ties ~26,000 • Objective Analysis Use machine vision images to measure crack area • Derive growth rate from measured crack area • Conduct parametric analysis of crack growth rates • From track charts: Speed, Grade, Curvature, • From other sources: Manufacturer, Crack Size, and • Crack Location Federal Railroad Administration Office of Research and Development

Tie Condition Analysis Types of Conditions Observed Cracking Chipping Crumbling Erosion Missing Fastener Federal Railroad Administration Office of Research and Development

Tie Grading Approach Use software to visually review and grade tie images Grade 1 – Good Tie Grade 2 Grade 3 Grade 4 Grade 5 – Ineffective Tie Federal Railroad Administration Office of Research and Development

Crack Growth Rate Determination Use Software to Measure Crack Growth Rate Unannotated Survey 1 Survey 3 Crack Annotation Annotation Area 1 = 928 mm 2 Area 2 = 935 mm 2 Δ Area = 7 mm 2 Annualize the result: Growth Rate = 6.5 mm 2 /yr Federal Railroad Administration Office of Research and Development

Parametric Analysis Approach Use Statistics to Assess Growth Rates Across Multiple Crack Populations 120% 0.15 Normalized Frequency 100% Cumulative Frequency 0.13 80% 0.10 Frequency distributioin 60% 0.08 Cumulative percent curve 40% 0.05 20% 0.03 0% 0.00 3 6 9 12 15 18 21 24 27 30 33 36 39 42 45 48 51 54 57 60 63 66 69 72 75 78 81 84 87 90 93 96 99 More Annualized Growth Rate (mm^2/yr) • Cumulative percentage is the integral (running total) of normalized frequency • Combines crack growth rate within a population of cracks into a single curve • Provides a means of quantifying crack growth rate over a population of cracks Federal Railroad Administration Office of Research and Development

Tie Condition Results Distribution of Tie Grades Grade 5 – 0.2% Grade 4 – 0.2% Grade 3 – 0.8% Grade 2 – 2% Grade 1 – 97% Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 • Distribution based on ~26,000 ties • Typical tie age 33 years Federal Railroad Administration Office of Research and Development 12

Tie Condition Results Distribution of Condition Types 4% 6% Crack Chip 46% Missing Fastener Crumbling 44% Federal Railroad Administration Office of Research and Development 13

Tie Condition Results Percent Change in Number of Tie Grades Over One Year Grade 1 Grade 2 Grade 3 Grade 4 Grade 5 • Most ties did not Grade 1 0.22% 0.01% 0.00% 0.00% advance in grade -0.23% 55 Ties 3 Ties 58 Ties • Most ties that did advance in grade did Grade 2 6.2% 0.0% 0.3% 0.0% so by 1 grade level -6.5% 32 Ties 2 Ties 34 Ties • Relatively few ties advanced by 2 grade 3.0% 0.0% 0.0% 0.8% Grade 3 levels -3.8% 6 Ties 2 Ties 8 Ties • No ties advanced by more than 2 grade Grade 4 5.8% 0.0% 0.0% 0.0% levels -5.8% 3 Ties Federal Railroad Administration Office of Research and Development

Crack Growth Rates for Total Assessed Crack Population 1386 110 100 100% 90 Cumulative Percentage 80 90% Measured Growth Rate Frequency 70 Half Normal Distribution 60 80% Cauchy Distribution 50 40 70% Cumulative Percentage 30 20 60% 10 0 50% 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 More Annualized Crack Growth Rate ( mm^2/year ) • Number of cracks assessed: 2139 • Number that did not grow: 1386 • Number that grew: 748 • Median growth rate: 6.5 mm 2 /year Federal Railroad Administration Office of Research and Development

Parametric Analysis Results Parameters that Influenced Crack Growth Rate Growth Rate of a Growth Rate 2-Sigma Uncertainty Residual Parameter Typical Crack (mm 2 /Yr) Spread (mm 2 /Yr) (mm 2 /Yr) (mm 2 /Yr) Combined Factors Worst case 13 9.2 2.4 6.8 Best case 3.8 Crack Size Small crack 4 Medium crack 8.3 4.3 2.0 2.3 Large crack 7.9 Field VS Gauge Gauge side 8.9 3.9 2.1 1.8 Field side 5 Curvature Non-tangent track 8.9 3.6 2.1 1.5 Tangent track 5.3 Tie Manufacturer Manufacturer “B” 8.1 2.2 2.1 0.1 Manufacturer “A” 5.9 Federal Railroad Administration Office of Research and Development

Parametric Analysis Results Parameters that did not Influence Crack Growth Rate Parameter Growth Rate of a Growth Rate 2-Sigma Residual (mm 2 /Yr) Typical Crack Spread Uncertainty (mm 2 /Yr) (mm 2 /Yr) (mm 2 /Yr) Posted Speed High range (130 - 150 mph) 6.5 0.5 2.0 -1.5 Low range (30 - 125 mph) 6 Grade Neutral Grade (|Grade|≤ .116) 6.4 0.2 1.9 -1.7 Non-neutral Grade (|Grade|> .116) 6.2 Federal Railroad Administration Office of Research and Development

Impact of Measurement Uncertainty 1.20 Standard Deviation of Median 1.00 0.80 0.60 0.40 0.20 0.00 0 1 2 3 4 5 6 RSS Measurement Uncertainty Federal Railroad Administration Office of Research and Development

Tie Manufacturer Comparison 2.2% 2.0% Percentage of Cracked Ties 1.8% Manufacturer "A" 1.6% Manufacturer "B" 1.4% 1.2% 1.0% 0.8% 0.6% 0.4% 0.2% 0.0% -52 -48 -44 -40 -36 -32 -28 -24 -20 -16 -12 -8 -4 0 4 8 12 16 20 24 28 32 36 40 44 48 52 Approximate Distance from Tie Ceter (inches) Federal Railroad Administration Office of Research and Development

Conclusions • The observed crack growth rates were not alarming (median growth rate = 6.5 mm 2 /year • Tie grades progressed at a non-alarming rate • Curvature, crack size, crack location (field or gauge side of the tie), and tie manufacturer had a statistically significant impact on crack growth rates • Posted speed (track class) and track grade (the degree of incline) did not have a statistically significant impact on crack growth rates • Tie manufacturer and/or manufacturing lot appears to play an important role in crack prevalence Federal Railroad Administration Office of Research and Development

Remaining Unknowns • The progression rate of failure modes other than cracks (e.g., crumbling and chipping) • The impact of tonnage on crack growth rates • The impact of seasonal variations on crack growth rates • The impact of different geographical regions on tie degradation • Potential variations among additional tie manufacturers Federal Railroad Administration Office of Research and Development

Acknowledgements Federal Railroad Administration Office of Research and Development • Mr. Hugh Thompson – FRA Project Manager • Mr. Cameron Stuart – BAA Program Manager National Railroad Passenger Corporation (Amtrak) • Mr. Mike Trosino • Mr. Steven Sawadasavi • Mr. Joe Mascara Computer Vision Laboratory at the University of Maryland, College Park • Professor Rama Chellapa • Mr. Xavier Gibert-Serra Federal Railroad Administration Office of Research and Development