1742
Proceedings of the 18
th
International Conference on Soil Mechanics and Geotechnical Engineering, Paris 2013
The resulting prognosis values are only valid for projects and
TBMs that also comply with the standardized ranges for the
other influencing factors on the tool life given in tab. 3.
3.3
Prognosis of interventions and tool changes
Based on the expected value for the cutting distance
s
ce
the
maximum obtainable length
b
I,max
in m of the intervals between
interventions for tool changes can be estimated for each ge-
otechnical section using the estimated penetration rate
p
e
in mm
and the diameter of the TBM
D
TBM
in m (8).
,
=
∙
2 ∙ ∙
8
While
b
I,max
is calculated for both, disc cutters and scrapers,
only the lower value of both is considered for the determination
of the position of the interventions for tool changes
I
. Conse-
quently the positions can be determined by consecutive addition
of the intervals
b
I,max
. More detailed calculations for the deter-
mination of
b
I,max
considering the factor of utilization of the in-
dividual tools are necessary, in case
b
I,max
covers the boundary
between different geotechnical sections where different values
for
s
ce
and
p
e
are estimated. In addition the positions of the in-
terventions also need to be adapted to the boundary conditions
for hyperbaric works along the tunnel axis. Therefore the actual
length of the intervals
b
I,act
can also be selected lower than
b
I,max
(9) in order to shift the position of the interventions
I
and avoid
critical areas.
,
≤
,
9
The relation between
b
I,act
and
b
I,max
influences on the
amount of tools that need to be changed during each interven-
tion in order to allow for the intended length of the interval to
the next intervention. The lower
b
I,act
is selected compared to
b
I,max
, the less tools have to be changed during each interven-
tion, but in return the number of interventions increases.
The number of tools
n
t,I
to be changed during each interven-
tion can be calculated in detail from the factor of utilization of
each individual tool. However, this process is often not feasible
during early planning stages of a project. Therefore an estimator
for the relation of
n
t,I
and the total number of cutting tools on
the cutter head
n
tbm
shown in fig. 3 was developed from a de-
tailed simulation of several TBMs in different ground condi-
tions. In the estimator in fig. 3 disc cutters and scrapers can be
considered separately, based on the maximum obtainable length
of the intervals
b
I,max
(9).
Aside the planned interventions for tool changes also short
interventions for validation of the geological conditions and the
estimated values for the cutting distance
s
ce
have to be consid-
ered. A common strategy is to validate
s
ce
in each new geotech-
nical section once the actual cutting distance
s
c,act
of the tools
reaches a value equal to 30-50% of
s
ce
in the new geotechnical
section. Again the factor of utilization of the individual tools at
the boundary between the geotechnical sections has to be con-
sidered.
Additional interventions have to be taken into account if
risks for damages of the cutting tools due to clogging in fine
grained cohesive soils, in soils containing boulders or manmade
obstacles like steel reinforced concrete piles are indicated.
4 CONCLUSIONS
The results presented in this paper provide a new approach to
the empirical prognosis of tool wear and the related demand for
interventions for Mix-Shield TBMs in soft ground. However,
the model still needs to be validated in practical use and an even
wider data base is necessary to quantify further influencing fac-
tors. For both tasks a followup of the prognosis during advance
is mandatory. Consequently the methods for the acquisition of
geological data (W
ENDL
2012) and tool wear data in the ad-
vance phase need to be improved. The improvement of the
prognosis model and its application in a more detailed version
additionally depend on development of according software tools
in order to organize the amount of various data types and follow
up the exact condition of each individual tool on the cutter head.
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Figure 1. Estimator for the amount of cutting tools
n
t,I
to be changed
during an intervention
I
.
