The durability project

1. The durability project To see if test sites (road trial or wear simulator) produce similar results 1. do different trial sites give roughly equal relative marks to the materials ? 2. do different trial sites cause roughly equal relative marks to the different characteristics ? 3. what factors determine the loads so that the loads at different trial sites can be predicted and compared

2. Materials, trial sites and applications of materials

3. Materials made available for application

4. Materials and patterns applied

5. Number of values

6. Materials and patterns applied

7. Number of values *) *) only average values

8. Materials and patterns applied

9. Number of values

10. Roads used in road trials Data regarding application/road/traffic/wheel passages is still missing.

12. Spanish roads

13. Presentation, use and quality of the final data

14. Table of Qd values (mcdm-2lx-1) from the Danish longitudinal road trial Each value is the average of three measured values

15. Table of Qd values (mcdm-2lx-1) from the German wear simulator The initial values are not included

20. All points are inside the box Chromaticity is not cnsidered further

21. RL and Qd of repetitions of materials Large variation, percentage scatter Smaller variation, constant scatter

22. Beta and SRT of repetitions of materials Smaller variation, constant scatter Smaller variation, constant scatter

23. These trial sites are treated as independent These are very similar in models These are not similar in models

24. b. good correlation between final values and model values. The data seems OK: a. good correlation between values for materials and repetitions

25. Model analysis

26. Principle of the models Model: predicted = initial – loadsensitivity Choose reasonable initial values for the different materials Allow: - distributions of load(s) for transverse locations (or wheel passages at wear simulators) - distribution(s) of sensitivities for the materials Determine load and sensitivity values by the RMS method (so that Root(Mean(Square(measured-predicted))) is minimum) The RMS method minimizes the standard deviation of the predicted values relative to the measured values

27. Some details Sensitivity values are scaled so that the average is 1 Values in positions where RL is below 40 mcd/m2/lx are ignored It is necessary to make a choice of scale of either sensitivity or load To exclude heavily eroded markings from the analysis

28. For the characteristics Qd,  and SRT, the loads are directly in the scale of the characteristics. EXAMPLE: If the load to Qd is 80 mcdm-2lx-1 at a particular position at a road trial, then the Qd of the materials is on the average reduced by this amount at that position of the road trial. However, if the sensitivity of a material is 0,75 then the actual reduction for that material is only by 0,7580 = 60 mcdm-2lx-1.

29. For the characteristic RL, on the other hand, the loads are factors of reduction. The models are based on ln(RL) instead of RL directly in order to: - avoid that large values (for the tape) dominate the analysis - obtain factor result (for instance standard deviation as percentage) EXAMPLE: If the load to RL is 4 at a particular position at a road trial, then the RL of the materials is on the average reduced by this factor at that position of the road trial. However, if the sensitivity of a material is 0,5 then the actual reduction for that material is only by a factor of 4 to the power of 0,5 equal to a factor of 2.

30. Initial or potential values used for the models Why not also determine initial values by the RMS method ?

31. Some observations It is reasonable that the models for RL, Qd and  are depreciation models with a high initial or potential value and gradual loss. This is not the case for SRT – will be considered separately. Models for Qd and  give quite similar results.

32. 1. do different trial sites give roughly equal relative marks to the materials ? Two models: I: the sensitivity values of the materials are the same at all test sites II: the sensitivity values of the materials are individual at each test site Can we reply yes in general to question 1 ? Average standard deviations for two models:

33. Model I: Match between model and measured RL values The match is not good

34. Model II: Match between model and measured RL values This is probably the least scatter we can hope to get

35. The diagrams for Qd and beta look similar to those for RL

36. We cannot reply yes to question 1 in general !

37. 1. do different trial sites give roughly equal relative marks to the materials ? Additional model: III: the sensitivity values of the materials are the same at test sites within groups, but individual between groups and at test sites not belonging to a group Average standard deviations for three models:

38. We can reply yes to question 1 in a limited sense (within groups of road trials) !

39. Sensitivities of RL

40. Sensitivities of Qd (or beta)

41. 2. do different trial sites cause roughly equal relative marks to the different characteristics ? We can reply yes if the loads are in approximately the same proportions for the three characteristics of RL, Qd and beta

49. We can reply yes to question 2 in a limited sense (within groups of road trials) !

50. 3. what factors determine the loads so that the loads at different trial sites can be predicted and compared