Purpose -The purpose of this paper is to study the consideration of uncertainty from analysis modules for aircraft conceptual design by implementing uncertainty-based design optimization methods. Reliability-Based Design Optimization (RBDO), Possibility-Based Design Optimization (PBDO) and Robust Design Optimization (RDO) methods were developed to handle uncertainties of design optimization. The RBDO method is found suitable for uncertain parameters when sufficient information is available. On the other hand, the PBDO method is proposed when uncertain parameters have insufficient information. The RDO method can apply to both cases. The RBDO, PBDO and RDO methods were considered with the Multidisciplinary Design Optimization (MDO) method to generate conservative design results when low fidelity analysis tools are used. Design/methodology/approach -Methods combining MDO with RBDO, PBDO and RDO were developed and have been applied to a numerical analysis and an aircraft conceptual design. This research evaluates and compares the characteristics of each method in both cases. Findings -The RBDO result can be improved when the amount of data concerning uncertain parameters is increased. Conversely, increasing information regarding uncertain parameters does not improve the PBDO result. The PBDO provides a conservative result when less information about uncertain parameters is available.Research limitations/implications -The formulation of RDO is more complex than other methods. If the uncertainty information is increased in aircraft conceptual design case, the accuracy of RBDO will be enhanced. Practical implications -This research increases the probability of a feasible design when it considers the uncertainty. This result gives more practical optimization results on a conceptual design level for fabrication. Originality/value -It is RBDO, PBDO and RDO methods combined with MDO that satisfy the target probability when the uncertainties of low fidelity analysis models are considered.

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Herein, the design optimization of multi-objective controllers for the lateral–directional motion using proportional–integral–derivative controllers for a twin-engine, propeller-driven airplane is presented. The design optimization has been accomplished using the genetic algorithm and the main goal was to enhance the handling quality of the aircraft. The proportional–integral–derivative controllers have been designed such that not only the stability of the lateral–directional motion was satisfied but also the optimum result in longitudinal trim condition was achieved through genetic algorithm. Using genetic algorithm optimization, the handling quality was improved and placed in level 1 from level 2 for the proposed aircraft. A comprehensive sensitivity analysis to different velocities, altitudes and centre of mass positions is presented. Also, the performance of the genetic algorithm has been compared to the case where the particle swarm optimization tool is implemented. In this work, the aerodynamic coefficients as well as the stability and control derivatives were predicted using analytical and semi-empirical methods validated for this type of aircraft.

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.

Aircraft manufacturers often consider producing multiple derivatives of aircraft to satisfy various market demands and technical changes while keeping development costs and time to a minimum. Many approaches have been proposed for carrying out derivative design. However, these approaches consider both the baseline design and derivatives together at the conceptual design stage using the entire set of design variables with an assumed set of expected requirements. These frozen requirements on derivative design cannot consider new demands from market changes. In this paper, a method is proposed that uses design optimisation for conceptual design of derivatives for existing aircraft that consider requirement changes. Furthermore, the Possibility-Based Design Optimisation (PBDO) method was implemented to consider uncertainty in the aircraft operation phase. The altitude range of aircraft operation was defined as an uncertain parameter to prevent violation of constraints in the entire operating envelope of the aircraft. The PBDO method yields a more conservative design than those obtained with deterministic design optimisation.In this paper, the proposed derivative design process was applied to the Expedition 350, a small piston engine powered aircraft produced by Found Aircraft, Canada. A derivative that changes the normally aspirated engine to a turbocharged engine for high-altitude operation was considered. An optimum configuration with the new engine was obtained while enhancing performance and stability characteristics. The proposed derivative design process can be implemented on the derivative design of other aircraft.