Testing and Analysis to Optimize Transit System Maintenance:

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1 Transportation Technology Center, Inc., a subsidiary of the Association of American Railroads Testing and Analysis to Optimize Transit System Maintenance: Charity Ketchum Russell Walker Nicholas Wilson Performance Based Track Geometry and Mathematical Modeling of Slab Track June 5, 2012 Transportation Technology Center, Inc. Marco Pontieri Augusto Metro São Paulo TTCI/AAR, 6/5/2012. filename, p1

2 Optimizing Maintenance with PBTG Poor vehicle dynamics and poor passenger ride quality frequently occur at track locations that do not exceed any track geometry or safety standards. Curve entry or exit Special trackwork Track misalignments that promote yaw instability or hunting Welds, joints Poor ride quality may not be an indicator of unsafe operation, but may point to an area of track or vehicle that needs maintenance to prevent further degradation. Performance Based Track Geometry (PBTG ) was developed by TTCI to improve and advance current track geometry inspection practices. Trained neural networks relate complex dynamic relationships between vehicles and track geometry to vehicle performance TTCI/AAR, 6/5/2012, Filename p2

3 Optimizing Transit System Maintenance PBTG benefits for the transit agency Help identify maintenance priorities Problem locations that do not exceed normal track geometry standards Problems as they arise rather than waiting for scheduled maintenance Car designs and car component wear issues that can contribute to poor vehicle performance and poor passenger ride quality An indirect benefit of implementing a PBTG system is making a vehicle model available to the transit agency Models can be used for Investigating dynamic performance problems Evaluating vehicle modifications Optimizing wheel/rail profiles TTCI/AAR, 6/5/2012, Filename p3

4 Optimizing Transit System Maintenance Possible Applications Onboard accelerometers on the fleet and a PBTG neural network can be used to identify track locations that need work without direct measurements of track geometry. PBTG can also be used to identify cars whose performance is beginning to deteriorate. Measured track geometry and the PBTG neural network can be used to identify track locations likely to cause poor passenger ride quality. TTCI/AAR, 6/5/2012, Filename p4

5 Transit Cooperative Research Program In support of TCRP, TTCI is conducting research to develop methods for relating track geometry to system vehicle performance and passenger ride quality. Combination of PBTG and NUCARS modeling techniques used These studies will form the basis for determining improvement in track geometry and track maintenance practices to improve passenger ride quality. This work consists of several phases: Proof of concept: Determine if PBTG will work to predict passenger ride quality for transit Industry Train PBTG neural net algorithms for DART and one other transit system Methodology and recommendations for implementing PBTG on other transit systems TTCI/AAR, 6/5/2012, Filename p5

6 TCRP Project Phase I - Complete Passenger ride quality literature review Vehicle characterization and on-track testing NUCARS vehicle dynamics modeling Comparison of NUCARS simulation predictions to on-track test results Relate passenger ride quality to track geometry Phase II In Progress Determine best input into neural network for predicting passenger ride quality Train PBTG neural network Use neural network to predict passenger ride quality Repeat Phase I testing on different system TTCI/AAR, 6/5/2012, Filename p6

7 Partner Transit Authority DART All testing was performed on DART property located in Dallas, Texas The following is a summary of the variety of conditions that were tested on the DART system: Tunnel 3.5 miles long with direct fixation track Ballasted track with concrete ties Direct fixation track Embedded track Curvature range from 2 to 20 degrees Overhead catenary system Operating speed 25 to 60 mph Rail profile 115 pound/yard rail TTCI/AAR, 6/5/2012, Filename p7

8 Partner Transit Authority DART Vehicle Characterization Tests Measured vehicle characteristics for input to NUCARS model Primary and secondary suspension stiffness, vehicle resonant responses, inertial parameters, CG heights Passenger Ride Quality Test: DART Red Line Measured passenger ride quality and vehicle dynamic responses Used normal operational conditions and speeds to obtain representative responses Track geometry measurements: DART Red Line TTCI/AAR, 6/5/2012, Filename p8

9 Red Line Passenger Ride Quality Tests Passenger ride quality tests were performed over the Red Line. TTCI/AAR, 6/5/2012, Filename p9

10 Passenger Ride Quality Test Data Lateral Accelerations TTCI/AAR, 6/5/2012, Filename p10

11 Lateral Ride Quality Index (MTVV) Lateral Ride Quality (Northbound) ISO 2631 Running RMS Method Lateral MTVV Not Uncomfortable Little Uncomfortable Fairly Uncomfortable Uncomfortable Extremely Uncomfortable TTCI/AAR, 6/5/2012, Filename p11

12 Lateral Ride Quality Index (MTVV) Lateral 2.00 Ride Quality (Southbound) ISO 2631 Running RMS Method Lateral MTVV Not Uncomfortable Little Uncomfortable Fairly Uncomfortable Uncomfortable Extremely Uncomfortable TTCI/AAR, 6/5/2012, Filename p12

13 Track Geometry Measurements Required Geometry Profile Cross-level Alignment Gage Deviations Curvature TTCI/AAR, 6/5/2012, Filename p13

14 Processed Track Geometry Data High and low pass filters were applied to: Remove long wavelength effects of curvature and entry spirals from the short wavelength alignment data Separate long wavelength superelevation in curves from the short wavelength cross-level deviations Drop-outs in the data were present because of the speed of the measurement vehicle dropping below a critical threshold. In these drop-out locations, the curvature channel was filtered and a correction factor was determined. TTCI/AAR, 6/5/2012, Filename p14

15 Passenger Ride Quality and Track Geometry Comparison Cedars and 8 th & Corinth stations in the southbound direction Passenger ride quality index Uncomfortable The 2-second peak to peak value is approximately 0.35 g s Deviation in the lateral alignment TTCI/AAR, 6/5/2012, Filename p15

16 Passenger Ride Quality and Track Geometry Vehicle Response 1 Hz and 1.65 Hz Track Geometry 1-Hz peak corresponding to a wavelength of 93 ft TTCI/AAR, 6/5/2012, Filename p16

17 PBTG Conclusions Southbound section of track between Cedars and 8 th & Corinth stations was uncomfortable with a passenger ride quality index of Section of track contained lateral alignment deviations with a wavelength of 93 ft corresponding to a frequency of 1 Hz at the speed the train was running Vehicle yaw response of 1 Hz Correlation between track geometry and vehicle response exists Track geometry deviations did not exceed any safety criteria, but affected passenger ride quality Track geometry must be measured at same time as passenger ride quality Other factors may influence vehicle response. It is important to determine the effects of wheel / rail interface, including profile shapes and contact geometry, and speed in order to understand and accurately predict rigid body vibration modes of the vehicle TTCI/AAR, 6/5/2012, Filename p17

18 Mathematical Modeling of Track Structure: Metro Sao Paulo Slab Track Testing and modeling of slab track with NUCARS What is the NUCARS track model and how does it work? There are several ways to represent the track when simulating vehicle-track interaction: Rigid Track Model Elastic Support Track Model Common method for most rail vehicle dynamics software. Flexible Track Model This is what a NUCARS user normally means when they say Track Model, although the other types are available in NUCARS TTCI/AAR, 6/5/2012, Filename p18

19 Rigid Track Model Rigid rail, fixed to ground with infinite stiffness TTCI/AAR, 6/5/2012, Filename p19

20 Elastic Support Track Model Rigid rails, move in only vertical and lateral directions TTCI/AAR, 6/5/2012, Filename p20

21 One Layer Flexible Track Model Flexible rails, Euler-Bernoulli beams, move in vertical, lateral and roll directions TTCI/AAR, 6/5/2012, Filename p21

22 NUCARS Track Model Two Layer Model TTCI/AAR, 6/5/2012, Filename p22

23 Metro Sao Paulo Slab Track Modeling Metro Sao Paulo interested in the effect of suspended slabs on vehicle dynamic forces Three locations identified: Line 2 60-meter slab supported on discrete foam pads Line meter slab supported on coil springs Line 5 2-meter slabs supported on continuous foam pads Investigate using vehicle dynamics models that include description of the flexible track structure Performed tests to tune model performance Hammer test Rail-slab fasteners Operational test Slab flexibility and slab to ground connection stiffness TTCI/AAR, 6/5/2012, Filename p23

24 Model of Long Suspended Slab Model includes two cars to capture the behavior of the track as affected by two closely spaced trucks of coupled cars. Flexible rails Springs and dampers representing rail fasteners Flexible slab Springs and dampers representing the slab suspension TTCI/AAR, 6/5/2012, Filename p24

25 Acceleration (g) Hammer Testing to Identify Fastener Stiffness Hammer testing is used to identify fastener stiffness. 25 Line 2 Coil Springs - Over Fastener Model Test Time TTCI/AAR, 6/5/2012, Filename p25

26 Deflection (m)/load (N) Deflection (m)/load (N) Hammer Testing to Identify Fastener Stiffness Models are tuned to match the test data by changing stiffness and damping parameters Top right - change in results with damping Bottom overall view of final match 1.2E E E E E E E Frequency (Hz) 8.0E E E E E E E E E+00 Test m/n Model - Zdamp=2e3 Model - Zdamp=2e2 Model - Zdamp=4e2 Model Test m/n Model Frequency (hz) TTCI/AAR, 6/5/2012, Filename p26

27 Displacement (mm) Displacement (mm) Displacement (mm) Slab Displacements Two long slabs have similar performance. Short slab performance is different. Can see effect of individual trucks Line 5 - Short Slab Time (s) Line 2 Pad Site - Long Slab Line 2 Coil Spring Site - Long Slab Time (s) Time (s) TTCI/AAR, 6/5/2012, Filename p27

28 Displacement (m) Load Distribution in the Track Structure Matching measured slab displacements (6 cars) with model slab displacements (2 cars) 124-m slab in curve suspended on coil springs DZ07 DZ08 DY Line 2 Coil Springs Adjacent slab, not suspended on coil springs DZ03 DZ04 DY02 DZ05 DZ01 31 m DZ06 62 m DZ02 DY DZ07 model Time (s) TTCI/AAR, 6/5/2012, Filename p28

29 Slab Track Model Conclusions Able to produce reasonable correlation between model and test Rail fastener stiffness hammer tests Slab flexibility and suspension stiffness operational test Next steps Determine how the suspended slabs affect vehicle dynamic response, including body and suspension motions, and W/R forces TTCI/AAR, 6/5/2012, Filename p29

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