WIT Press


Uncertainty And Reliability In Aircraft Design And Optimization

Price

Free (open access)

Paper DOI

10.2495/OP120191

Volume

125

Pages

12

Page Range

219 - 230

Published

2012

Size

2,541 kb

Author(s)

S. Hern´andez, J. D´ıaz, M. Cid, A. Baldomir & L. Romera

Abstract

Aircraft engineering is subjected to many classes of uncertainties due to the lack of proper definition of loads, behaviour of new materials or even due to the inaccuracies produced during manufacturing. Because of that, the most advanced methods of analysis and optimization need to be used during the dimensioning of aircraft structures. One way to increase the safety level of a design could be to increase the safety coefficients for load values or material strength, but this approach would lead to an unacceptable amount of material for the aircraft. More proper approaches can be applied using probabilistic analysis during the design phase. In that case, some of the parameters, such as loads, material properties of manufacturing tolerances are defined as random variables and a probabilistic analysis is carried out to identify the safety of the design. This approach can be also enhanced by introducing the concept of design optimization. In that case the optimum solution for an aircraft structure is obtained even considering the random nature of some of the design variables. In this paper these methodologies will be described and some examples of aircraft structures will be presented to show the potential in real problems. Keywords: uncertainty quantification, reliability based design optimization. 1 Introduction Reliability is related with the probability of verifying a certain condition. This is known as the probability of failure. In a probabilistic analysis, the uncertainties in the basic magnitudes of the structure are considered directly in the analysis, changing from fixed quantities to random variables (RV). The limit state function defines if a design belongs to the failure domain, where the limit state is not

Keywords

uncertainty quantification, reliability based design optimization.