Damper Optimization for Long-Span Suspension Bridges - Design Optimization of Active and Passive Structural Control Systems - page 122

CONCLUSION response control effect turns unobvious when the

damp coefficient C is greater than 15000 kN·s/m
(Figure 5), the total damper of the two towers of
the RSB is set as 30000 kN·s/m.

In this chapter, the damper optimization of the RSB
is conducted under seismic input considering the
traveling wave effect, based on the combination
of the AHP and first-order optimization method.
The following conclusions could be drawn:

Results of Damper Optimization

Table 1 shows the optimization analysis results
under 5 cases. Note that case 1 is without dampers,
and Cases 2, 3, 4 and 5 correspond to Equations
(9), (10), (11) and (12), respectively.
When compared with results of Case 1, Table
1 shows that values of M 1 and D 3 reduce signifi-
cantly and values of M 2 turn larger, indicating
effects in seismic control induced by the applica-
tion of dampers.
When only the girder displacement D 1 is re-
garded, the optimization is achieved in Cases 2
and 3 whose dampers are not evenly distributed
between the left and right towers. This phenom-
enon is mainly derived from the traveling wave
effect in this chapter. However, consider the
complication and uncertainty of traveling wave
effect, equal distribution of dampers on the two
towers is the most general choice. In addition,
values of M 2 , D 2 , F 3 and D 3 are larger in cases 2
and 3 when compared to those of cases 4 and 5,
indicating the other advantages of adopting equal
distribution approach. Therefore the spatially
equal distribution of dampers in the two towers
is recommended.

• Dampers with appropriate parameters can

reduce the seismic displacement of super-
long-span suspension bridges significantly.
The parameter sensitive analysis involved
in influence of damping coefficient C on
the structural responses will necessarily fa-
cilitate the damper optimization.

• When creating evaluation model based on

AHP method, a correct evaluation model,
adequate evaluation parameters and the de-
termination of their weighting factors are
significant for the accuracy and credibility
of the analysis results. In this chapter, the
model is established on the author's expe-
rience. More research is required to refine
the model for better damper optimization.

• Four assessment functions are proposed as

the optimization criteria, by first-order op-
timization method to deal with quantitive
assessment. Different functions can lead to
different optimization results and their op-
timization results are compared with each
other to indentify the most effective one.

• Although spatially unequal damper distri-

bution on the two towers can lead to the

Table 1. Comparison of optimization result

M 1 ×10 6
(kN· M)

M 2 ×10 3
(kN· M)

Case C 1 (kN·s/m) C 2 (kN·s/m) D 1 (m) D 2 (m) F 3 (kN) D 3 (m)

1 1.890 0.423 81.52 0.372

2 18000 12000 1.429 0.235 103.8 0.263 9160 0.216

3 18000 12000 1.429 0.235 103.8 0.263 9160 0.216

4 15000 15000 1.382 0.243 95.3 0.238 7850 0.207

5 15000 15000 1.382 0.243 95.3 0.238 7850 0.207