National Academies Press: OpenBook

Performance-Based Track Geometry, Phase 1 (2012)

Chapter: 5.0 Ride Quality and Track Geometry Data Analysis

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Page 36
Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
×
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
×
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
×
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
×
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
×
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
×
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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Suggested Citation:"5.0 Ride Quality and Track Geometry Data Analysis ." National Academies of Sciences, Engineering, and Medicine. 2012. Performance-Based Track Geometry, Phase 1. Washington, DC: The National Academies Press. doi: 10.17226/22785.
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34 5.0 RIDE QUALITY AND TRACK GEOMETRY DATA ANALYSIS The data collected during the ride quality and track geometry tests were compared to determine if a correlation between the two was possible. 5.1 Ride Quality Test Ride quality measurements were taken on DART’s Red Line in both directions. The train was operated with typical operating conditions. Accelerations were measured on the floor at the following locations: • A-end under operator’s seat (lateral, vertical, and longitudinal) • B-end under operator’s seat (lateral, vertical, and longitudinal) • A-end over bogie (lateral, vertical, and longitudinal) • A-end center of car (lateral, vertical, and longitudinal) • Lateral accelerometer between the A and C cars • Lateral accelerometer between the C and B cars • Lateral accelerometers at each axle Gyrometers were also placed under the A-end and B-end operator’s seats to measure the carbody roll angle as the vehicle traveled through the curves. Figure 33 shows an example of ride quality data. It shows Westmoreland to Pearl Street Station and the accelerations measured under the operator’s seat in the A-end of the SLRV. The data was analyzed between each station. Ride quality was determined according to ISO 2631-1997. Longitudinal, lateral, and vertical ride quality was determined between each station. The identified ride quality issues will be compared to track geometry to determine if there is a correlation.

35 Figure 33. Example Ride Quality Data Lateral Accelerations A cc el er at io n (G s)

36 Table 11 describes ISO 2631 ride quality index boundaries. Figure 34 (a, b) shows the crest factors calculated for each segment. The appendix contains the definitions of the parameters related to ride quality. There are some areas that have crest factors above 9; therefore, as required by ISO 2631, the running root-mean-square (RMS) Method was used to evaluate the ride quality. The vibration magnitude is defined as the maximum transient vibration value (MTVV). Figure 35 (a, b, c) shows the MTVV for vertical, lateral, and longitudinal accelerations. Table 11. ISO 2631 Ride Quality Index Boundaries Vibration Magnitude (meters/second Comfort Level 2) aw Not uncomfortable <0.315 0.315 <aw A little uncomfortable <0.63 0.5 <aw Fairly uncomfortable <1 0.8<aw Uncomfortable <1.6 1.25<aw Very uncomfortable <2.5 aw Extremely uncomfortable >2

37 Figure 34a. Crest Factors for Vertical Accelerations Figure 34b. Crest Factors for Lateral Accelerations

38 Figure 34c. Crest Factors for Longitudinal Accelerations

39 Figure 35a. MTVV Values for Vertical Accelerations

40 Figure 35b. MTVV Values for Lateral Accelerations

41 Figure 35c. MTVV Values for Longitudinal Accelerations

42 The ride quality for the longitudinal and vertical directions was in the “comfortable” to “not uncomfortable” range for both directions of travel. However, the lateral direction had areas with ride quality in the “little uncomfortable” to “fairly uncomfortable” range. Table 12 summarizes the areas with ride quality exceptions. Table 12. Segments of Track with Ride Quality Exceptions Direction Stations Lateral Ride Quality Index Description Northbound Dallas Zoo to 8th 0.661 & Corinth Fairly uncomfortable Northbound Walnut Hill to Forest Lane 0.763 Fairly uncomfortable Northbound LBJ/Central to Spring Valley 0.651 Fairly uncomfortable Northbound Galatyn Park to Bush Turnpike 0.681 Fairly uncomfortable Southbound Plano Center to Bush Turnpike 0.845 Uncomfortable Southbound Spring Valley to LBJ/Central 0.640 Fairly uncomfortable Southbound Cedars to 8th 1.056 & Corinth Uncomfortable The measured track geometry in these areas is evaluated in section 5.3 to determine if there is a correlation to the ride quality issues. 5.2 Track Geometry Track geometry measurements were taken by Holland August 13-14, 2010, on DART Red Line in both directions. No measurements were taken in the tunnel because of a size restriction in the tunnel. Data from a previous track geometry run was used for the tunnel. The tunnel has direct fixation track, and therefore, it was assumed that track geometry changes in the time since the previous run were negligible. Figure 36 shows an example of the measured track geometry. The tight gauge in the embedded track is evident. The data was processed for use in the NUCARS simulations. High and low pass filters were applied to the data to ensure the long wavelength effects of curvature and entry spirals were removed from the short wavelength alignment data, and to ensure that long wavelength superelevation in curves was clearly separated from the short wavelength crosslevel deviations. In some areas, dropouts in the data were present due to the speed of the measurement vehicle dropping below a critical threshold. In these dropout locations, the curvature channel was filtered and a correction factor was determined. Figure 37 shows an example of the data processed for use in NUCARS.

43 Figure 36. Raw Track Geometry Data (from top graph down—Cross level (in); Curvature (degree); Profile, Alignment, Profile, Alignment, Gauge (in) Embedded track. gauge was 56 inches in this area.

44 Figure 37. Processed Track Geometry Data for Use in NUCARS [from top graph down—Curvature (degree); superelevation, left lateral, left vertical, right lateral, right vertical (in.)]

45 5.3 Ride Quality and Track Geometry Comparison A major objective was to determine if there is a correlation between ride quality and track geometry. Places on the Red Line that had ride quality issues were identified from the ride quality test performed (section 5.1). The section of track that was fairly uncomfortable was located between Cedars and 8th & Corinth stations in the southbound direction. Figure 38 (top) shows the accelerations measured under the operator’s seat in the leading end of the SLRV in this area. Figure 38 (bottom) shows the track geometry measured in the same area. The two-second peak-to-peak value is approximately 0.35 Gs. In the area where this occurs, there is a deviation in the lateral alignment. Figure 38. Measured Acceleration Data between Cedars and 8th & Corinth Stations (top), and Measured Track Geometry Data between Cedars and 8th & Corinth Stations (bottom)

46 Figure 39 shows the frequency content of the acceleration data and lateral alignment of the track geometry. There are peaks at approximately 1 Hz and 1.65 Hz in the lateral vehicle response. In the lateral alignment of the track geometry in this area there is also a 1 Hz peak corresponding to a wavelength of 94 feet. Figure 40 shows the acceleration data for the A-carbody and the B-carbody. The two carbodies are moving approximately 90 degrees out-of-phase. Its frequency content is approximately 1.63 Hz. There is also a 1 Hz response of the vehicle that correlates to the 1 Hz frequency content of the lateral alignment of the track in this area. Figure 39. Frequency Content of Track Geometry (top), and Vehicle Response (bottom)

47 Figure 40. Yaw Acceleration Data for the A- and B-carbodies. Description of the U-shaped Yaw Vibration Mode (top) It is possible to identify track geometry that can cause ride quality issues, such as the lateral deviations with the 94-foot wavelength between Cedars & 8th Hunting may be triggered by a combination of lateral deviation, speed, and wheel/rail interaction. It will be important in the next phase of this project to investigate the potential triggers in more detail. & Corinth Stations. These track misalignments cause a response in the vehicle. It is important to note that although these track geometry deviations do not exceed any safety criteria, they can affect passenger ride quality. In order to identify the track geometry issues that affect ride quality, it is imperative to take track geometry measurements at the same time as ride quality measurements. Figure 41 shows a sun kink that developed on the DART Red Line as a result of the extreme heat. Figure 42 shows the track geometry in the area. The sun kink is not evident in the measured track geometry, but it was present during the ride quality tests. The track geometry was taken at night a week after the ride quality test, and DART had already repaired it. The ride quality test does show some lateral acceleration in this area. DART was actively working to correct sun kinks as soon as possible after they occurred. This illustrates the importance of taking track geometry measurements at the same time as ride quality measurements, which will enhance the ability to correlate ride quality to track geometry.

48 Figure 41. Sun Kink Observed During Track Inspection Sun Kink

49 Figure 42. Measured Track Geometry in area of Observed Sun Kinks [from top graph down—Curvature (degree); superelevation, left lateral, left vertical, right lateral, right vertical (in.)]

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TRB’s Transit Cooperative Research Program (TCRP) Web-Only Document 52: Performance-Based Track Geometry explores ride quality literature, vehicle characterization and on-track ride quality testing, track geometry measures, and NUCARS' (a railway multi-body dynamics computer program) modeling and simulation capabilities.

The research highlighted in TCRP Web-Only Document 52 is the first phase of a two-phase project. Phase II of the project will apply the NUCARS simulations and data collected on transit systems during Phase I to train performance-based track geometry (PBTG) neural networks and will explore the PBTG model’s ability to predict ride quality.

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