No abstract

This paper describes a multidisciplinary robust optimisation framework for UAV conceptual design. An in-house configuration designer system is implemented to generate the full sets of configuration data for a well-developed advanced UAV analysis tool. A fully integrated configuration designer along with the UAV analysis tool ensures that full sets of configuration data are provided simultaneously while the UAV configuration changes during optimisation. The computational strategy for probabilistic analysis is proposed by implementing a central difference method and fitting distribution for a reduced number of Monte Carlo Simulation sampling points. The minimisation of a new robust design objective function helps to enhance the reliability while other UAV performance criteria are satisfied. In addition, the fully integrated process and a probabilistic analysis strategy method demonstrate a reduction in the probability of failure under noise factors without any noticeable increase in design turnaround time. The proposed robust optimisation framework for UAV conceptual design case study yields a more trustworthy prediction of the optimal configuration and is preferable to the traditional deterministic design approach. The high fidelity analysis ANSYS Fluent 13 is performed to demonstrate the accuracy of proposed framework on baseline, deterministic and RDO configuration.