Simultaneous Optimization of a Multiple-Aircraft Family

Multidisciplinary design optimization is considered in the context of designing a family of aircraft. A framework is developed in which multiple aircraft, each with different missions but sharing common parts, can be optimized simultaneously. The new framework is used to gain insight to the effect of design variable scaling on the optimization algorithm. Results are presented for a two-member family whose individual missions differ significantly. Both missions can be satisfied with common designs. Moreover, optimizing both planes simultaneously rather than following the traditional baseline plus derivative approach vastly improves the common solution. A cost modeling framework is outlined that allows the value of commonality to be quantified for design and manufacturing costs. A notional example is presented to show the cost benefit that may be achieved by designing a common family of aircraft.