# Long Term Effects of Reduced Track Tamping Works
## 2 Methodology
### Pre-Work and Applied Algorithms
#### 2.1.2 Defining the Interaction between Track Quality and Tamping Measures  
Track tamping, more precisely levelling, lining, lifting, and tamping, improves the geometrical position of the track grid (rails and sleepers). However, the improvement and the sustainability of the established track geometry depends on some preconditions. For through-going tamping actions, we look at the standard deviation of the longitudinal level (SDLL or oLL). We learn that there is a trade-off between intervention level and reachable quality level after tamping. Track quality behavior between two tamping tasks can be described by the initial quality (Qn = SDLL) the deterioration rate (b), and the end quality after tamping is executed (Qult). Generally, the absolute level of SDLL (Qn) after tamping is lower than the starting quality in the deterioration period earlier (Qn-1). This is not due to poor working quality, as the track geometry delivered by the tamping machine is very precise. On includes the initial settlements directly after tamping and due to train operation. It is an artificial quality that is not calculated from a measurement signal, but the result of the calculated regression function at the point in time of tamping. The deterioration rate (bn), the loss of quality over time, generally increases compared to bn-1. Evaluations of thousands of track sections show that the stricter the intervention level (the higher the quality at the time of intervention), the higher the quality level after tamping. In more detail, the interaction of tamping and track geometry level depends on existing track quality (Qn and bn), the intervention level (Qult), and, of course, on the working quality. The 4 tamping-algorithm [8] aims at a long-term optimization of line tamping actions, taking into account those parameters and seeking for the optimal intervention level for the giventrack quality. This algorithm is applied when evaluating the long-term effects of different damping strategies within this study. However, beside the prediction of the next tamping task, it is important to know about the track quality behavior after the upcoming tamping work in order to develop tamping strategies for future periods. In general, track quality improves significantly after tamping and a new initial quality (Qn2) is achieved. The deterioration process starts again described by the new degradation rate (b2). If we know these two parameters, we can also describe track quality behavior after tamping and the next intervention. Hence, it is possible to calculate the point in time when quality improvement should be executed to reach the highest effectiveness. Forecasting the next intervention underlies the same procedure. Figure 2 summarizes the notation and processes. Within a comprehensive network-wide investigation [10], special attention is paid to the evolution of the track quality parameters after tamping. Results show that b2 and Qn2 are mainly triggered by the intervention level Qult1 and b1. Qn1, cumulated tonnage, and type of superstructure (sleepers) are also influences. Sophisticated analyses enable the clustering of results and determination of the relevant track quality parameters after tamping as functions of the influencing parameters. Figure 1: Applying the CoMPAcT-algorithm for reliable time-rows and robust forecasting of Longitudinal Level. (**a**) raw longitudinal level measurements (**b**) Euclidean distance function (**c**) post-positioned longitudinal level measurements. Using this knowledge, we can derive the optimal intervention level for any specific situation in the network and the sustainable tamping strategy for specific boundary conditions. We underline that track quality itself is not the criterion for optimization but much more a fundamental input parameter. The 4 tamping-algorithm [10] aims for a long-term optimization of line tamping actions considering the entire service life of track. The optimized intervention levels deliver the longest possible time (service life) with ten tamping actions.