Variable-complexity Multidisciplinary Design Optimization Using Parallel Computers

The use of multidisciplinary optimization techniques in aerospace vehicle design often is limited because of the signi cant computational expense incurred in the analysis of the vehicle and its many systems In response to this di culty a variable complexity modeling approach involving the use of re ned and computationally expensive models together with simple and computationally inexpensive models has been developed This variable complexity technique has been previously applied to the combined aerodynamic structural optimization of subsonic transport aircraft wings and the aerodynamic structural optimization of the High Speed Civil Transport HSCT In related research conducted by members of the MAD Center at Virginia Tech convergence di culties were encountered in the aerodynamic structural optimization of the HSCT The convergence problems were traced to numerical noise in the computation of aerodynamic drag components which inhibited the use of gradient based optimization techniques An example problem which involved two design variables was used to determine the feasibility of using a response surface methodology in conjunction with our existing multidisciplinary analysis tools The long term goal of this research e ort is to apply the response surface methods to the full HSCT design optimization problem Such applications of response surface methods to vehicle design have proven successful in previous studies e g To e ciently use non derivative based optimization involving response surface approximation we have developed a coarse grained parallel implementation of our HSCT analysis codes In addi tion we have produced parallel versions of existing nite element analysis codes The aerodynamic and structural analysis codes have been implemented on Virginia Tech s twenty eight node Intel Paragon parallel computer a distributed memory architecture with MB of memory at each node