A response surface approach to noise optimization of engine structures

The work presented within this thesis concerns the optimization of finite element models of engine structures to reduce radiated noise. For many engineering problems, current methods of structural optimization provide an efficient means by which to identify an optimum design, subject to a set of imposed bounds and constraints. They do not, however, have the flexibility to carry out efficient investigation of a range of different constraint criteria, and this is often a requirement of a noise optimization study. In order to address this restriction, an alternative method of noise optimization is developed, which is based on the techniques of experimental design theory and response, surface methodology. The main feature of this approach is that values of the response functions of interest are calculated at a number of selected points Within the design variable space, from which an approximating mathematical model is generated. It is this analytical model of the original responses which is used as the basis of the optimization procedure. Experimental design theory is employed in order to ensure that a sufficiently accurate model can be generated With the minimum number of function evaluations. A number of competing experimental designs and mathematical models are considered, and numerical trials are carried out to evaluate their performance in representing the noise function. A quadratic model is found to perform well throughout the design region, and can be estimated efficiently using a particular class of economic second-order designs. A number of detailed noise optimization studies are presented, involving up to seven design variables, which illustrate the ways in which the requirements of the noise optimization problem can be met using the response surface approach.