Aircraft Derivative Design Optimization Considering Global Sensitivity and Uncertainty of Analysis Models
Hyeong-Uk Park, Joon Chung and Jae-Woo Lee
International Journal of Aeronautical and Space Sicences, vol. 17, no. 2, pp.268-283, 2016
Abstract : Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify
or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many
researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs
together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft
derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from
local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove
unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort
and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis
tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design
Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty
in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and
PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that
increases cruise range and the number of passengers. The proposed process provided deterministic design optimization,
RBDO, and PBDO results for given requirements.
Keyword : Reliability Based Design Optimization, Possibility Based Design Optimization, Aircraft Conceptual Design, Derivative Design |