Structural Design of Pavements PART VI Structural ... - TU Delft

23
The following sections are discriminated.
Section
Locations
1 0.05-0.1-0.15
2 0.2-0.25-0.3
3 0.35-0.4-0.45
4 0.5-0.55-0.6
5 0.65 this is a single point clearly visible in the SCI plot
6 0.7-0.75-0.8-0.85-0.9-0.95
7 1 this is a single point clearly visible in the SCI plot
8 1.05-1.1-1.05
9 1.1-1.15-1.2-1.25-1.3-1.35-1.4-1.45
10 1.5 this is a single point clearly visible in the SCI plot
11 1.55-1.6
12 1.65-1.7-1.75-1.8-1.85-1.9-1.95-2
By means of the cumsum method we have arrived to a set of successive sub-sections, each
of them having more or less a certain flexural stiffness. Now it is interesting to determine if we
can combine a few sections. If this is possible we would reduce the work load. The question
now is how to achieve that.
If we compare the slopes of the different sections we notice that the slopes of sections 2, 4
and 12 are about the same. This means that they can be taken as one section in the further
analysis. This also holds for sections 1 and 6, so also these can be treated as one section.
The same is true for sections 3, 8 and 11.
Then we have a look to the single points that are discriminated and we try to assign them to a
particular subsection. We observe that location 0.65 is clearly an isolated peak value and
should therefore be treated as such. Location 1 however could very well be combined with
section 2. Also location 1.5 is better treated as a single point.
All in all we arrive to the subsections given below.
Section
Locations
1 0.05-0.1-0.15 and 0.7-0.75-0.8-0.85-0.9-0.95
2 0.2-0.25-0.3 and 0.5-0.55-0.6 and 1.65-1.7-1.75-1.8-1.85
-1.9-1.95-2 and 1
3 0.35-0.4-0.45 and 1.05-1.1-1.15 and 1.55-1.6
4 0.65
5 1.1-1.15-1.2-1.25-1.3-1.35-1.4-1.45
6 1.5
The statistics of the sub-sections mentioned above are tabulated below.
Section Mean Value SCI Standard Deviation SCI Var. Coeff.
1 420 111 26%
2 175 65 37%
3 494 62 13%
4 962
5 423 77 18%
6 96
As one will notice, rather high values for the coefficient of variation are still obtained for
sections 1 and 2. We have to look then in table 2, in order to find out what the possible
reasons for this could be. By doing so we observe that location 0.8 doesn’t really fit in section
1 and should better be moved to section 2. The high variation in section 2 is probably caused
by the inclusion of locations 1.7 and 1.75; also location 1.9 could contribute to the high
variation. Therefore it is suggested to move location 1.9 to section 1 and to combine locations
1.7 and 1.75 with location 1.5. We then obtain the sections and summary statistics as shown
in table 3.
As one can observe a better result in terms of lower coefficients of variation are obtained. The
division in subsections as shown in table 3 will be used for further treatment.