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The “green agenda” combined with highway congestion has accelerated the demand for increased freight and passenger travel on the world’s railways. These increases have driven demand for more efficient and rapid investigation of trackbed ballast. Network Rail and other rail infrastructure operators spend significant financial sums on inspecting, tamping, adjusting, cleaning, and replacing trackbed ballast. Such maintenance is often to the detriment of normal network operation. Industry requires a method of ballast evaluation that is non-intrusive, cheap, can appraise long stretches of track in a short period of time, and give a fingerprinting result from which time-to-maintenance can be calculated and planned. Thus, the aim was to develop evaluation methods using non-destructive testing techniques. A 10-year old full-scale trackbed composed of variously fouled ballast was re-visited and used for experimentation. The condition of the ballast was calculated using the Ionescu Fouling Index. Earlier research at the University of Edinburgh enabled researchers worldwide to characterise ballast using ground penetrating radar (GPR). This research was repeated, validated and taken forward in a series of GPR experiments on the trackbed using a range of antennas from 500MHz to 2.6GHz. New "scatter" metrics were developed to determine ballast condition from the GPR waveforms. These metrics were then used to predict the Ionescu Fouling Index with a correlation coefficient greater than 0.9. One of the current approaches to evaluating the stiffness of railway ballast is to use a Falling Weight Deflectometer (FWD). The viability of using a Prima 100 mini-FWD on railways to measure stiffness was determined and deemed to be ineffective on ballast. The applicability of the impulse response technique on railways was determined. An instrumented hammer was used to excite the ballast, with a geophone measuring the response. The Frequency Response Function of this was successfully correlated with the Ionescu Fouling Index with a correlation coefficient also greater than 0.9. Finally, using GPR data and measured stiffness data collected by Banverket, Sweden, a numerical model to successfully relate radar responses to stiffness was developed.Content:-
Declaration
Abstract
Acknowledgments
Contents
Figures
Tables
Chapter 1. Introduction
Chapter 2. University of Edinburgh Railway
Chapter 3. Ground Penetrating Radar
Chapter 4. GPR Testing
Chapter 5. GPR Analysis
Chapter 6. Mini Falling Weight Deflectometer
Chapter 7. Impulse Response
Chapter 8. Impulse Response Analysis
Chapter 9. Dynamic Track Modulus From GPR
Chapter 10. Conclusions
References
Appendix 1. Work Plan
Appendix 2. Particle Size Distribution Charts
Appendix 3. FWD Drops on Fixed Positions on Sleepers
Appendix 4. FWD Drops on Fixed Positions on Cribs
Appendix 5. FWD Drops on Different Positions on Sleeper 6
Appendix 6. FWD Drops on Different Positions on Crib 6
Appendix 7. Full Impulse Response Results
Appendix 8. 114km to 122km Multi-Variate Regression (All Samples)
Appendix 9. 114km to 122km Multi-Variate Regression (Not All Samples)
Appendix 10. 120,889m to 121,009m Multi-Variate Regression (All Samples) 7
Appendix 11. Papers
Author Details
"Robert De Boldtails"
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