Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT
Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT
Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT
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does not change <strong>with</strong> the design parameters, so it is generated a priori and then<br />
loaded into the workspace at each iteration. The model components are integrated<br />
<strong>with</strong> DOCS to form the fully-integrated system model and evaluate the performance.<br />
It is important to keep in mind that the process outlined in Figure 6-10 is exe-<br />
cuted once for each iteration, or random guess, in the SA algorithm. Therefore, the<br />
NASTRAN model must be built and a finite element analysis run thousands of times.<br />
This operation is computationally expensive and becomes more so as the model fi-<br />
delity and number of degrees of freedom are increased. In addition, as the design<br />
space grows, a greater number of SA iterations are required. It is clear that a brute<br />
force method such as the one outlined here may not be appropriate for a model of<br />
this fidelity and further investigation into the optimization implementation is war-<br />
ranted. There are known methods for reducing the computational effort required for<br />
these types of optimizations [28, 39] that are appropriate for this application, such as<br />
reduced-order modeling [37] and response surface approximation [22, 11].<br />
6.4 Results<br />
The TPF SCI structure is designed through a SA stochastic search using the PT, RPT<br />
and RPTT cost functions (Equations 2.1, 3.5, and 5.5, respectively). In the RPT and<br />
RPTT optimizations the uncertainty space is searched <strong>with</strong> the vertex method. Since<br />
there are three uncertainty parameters, there are eight vertices at which performance<br />
must be evaluated during each iteration. The RPTT cost is considered <strong>with</strong> α =0<br />
to obtain the most tunable design. In the PT and RPT optimizations both the<br />
tailoring, �x and tuning, �y parameters are used as tailoring parameters to provide for<br />
a fair comparison <strong>with</strong> the RPTT design. In this way all three optimizations have<br />
the same design variables available to them and the only difference lies in the manner<br />
in which the tuning parameters are incorporated.<br />
The tailoring parameters for the nominal and optimized designs are listed in Ta-<br />
ble 6.13 along <strong>with</strong> the mass of the structures. The three designs are distinct from<br />
each other and very different from the nominal design. In each case the truss bays<br />
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