Page 62 - Numerical Analysis and Modelling in Geomechanics
P. 62

COMPRESSED AIR TUNNELLING 43



















            Figure 2.8 Comparison of the predicted and measured air losses from the tunnel face.

            number of sections along the tunnel length. In Figure 2.8, the calculated values
            of the air losses at these locations have been plotted against the measured values.
             The figure shows that the results of the numerical model are in close agreement
            with the measured values. The slight differences between the calculated and the
            measured values are likely to be due to the heterogeneity of the ground.
              The air losses from the perimeter walls were calculated using the second part
            of  the  numerical  model  where  the  excavation  sequence  and  the  age  of  the
            installed shotcrete lining at each stage were considered. The tunnel length was
            divided  into  a  number  of  segments  and  the  permeability  of  the  shotcrete  was
            calculated  for  each  segment  from  equation  (2.8)  considering  the  time  of
            installation  and  age  of  shotcrete.  The  air  losses  for  each  segment  were  then
            calculated using the corresponding permeability and thickness of shotcrete and
            soil  layers.  For  every  location  of  the  tunnel  face,  the  total  air  loss  from  the
            perimeter walls was considered as the sum of the air losses from the segments
            behind the face. Delays in construction, such as those due to local collapse of the
            tunnel or holidays, were taken into consideration.
              Coefficients  A  and  B  in  equation  (2.8)  were  determined  by  minimising  the
            discrepancies  between  the  measured  and  calculated  values  of  air  losses  as
            described earlier. The final values were:





            Figure 2.9 shows the results of the GA analysis in the identification process in
            terms  of  variation  of  the  objective  function  value  against  the  number  of
            generations. The figure shows the rapid convergence of the algorithm and high
            efficiency of the method. The following parameter values were used in the GA:
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