AbstractAircraft manufacturers are facing several challenges in the pre-design of aircraft structures. This early stage of the aircraft design has a very multi-disciplinary character. Different competence centres need input data, which is at this point in time to a large extent undefined. Therefore, a large variety of specialised tools is used in order to estimate and predict the required data. If these tools are not compatible, interface problems are the consequence. A permanent improvement of the applied processes with regard to the informal value as well as the applicability remains a continuous challenge.The objective of a collaboration project between Airbus Germany GmbH, the DLR Braunschweig, and the ETH Zurich is to find new methods and approaches to improve accuracy, efficiency, and flexibility of data prediction for primary aircraft structures. The use of modern CAE systems together with the integration of finite element methods into the early pre-design process is a very promising approach [F. Bianconi, P. Conti, N. Senin, D.R. Wallace, CAE systems and distributed design environments, in: XII ADM International Conference, Italy, 5–7 September, 2001 [2]; M. Pellicciari, G. Barbanti, A.O. Andrisano, Functional requirements for a modern CAD system, in: XII ADM International Conference, Italy, 5–7 September, 2001 [9]; T. Richter, H. Mechler, D. Schmitt, Integrated parametric aircraft design, in: ICAS 2002 Congress, Institute of Aeronautical Engineering, TU Munich].The modular and knowledge-based architecture of modern CAE systems allows to represent complex assemblies like aircraft structures by parametric associative and very dynamic models. Design knowledge can be integrated into the modelling [M. Mäntylä, S. Finger, T. Tomiyama, Knowledge Intensive CAD, vol. 2, Chapman & Hall, 1997 [8]] and different characteristics or individuals of the same structure can be mapped through parameters.This document presents concepts, which allow to design comprehensive digital models of novel aircraft structures whereas the level of the modelling detail shall be variegated flexibly [D.E. Whitney, R. Mantripragada, J.D. Adams, S.J. Rhee, Designing assemblies, Res. Engrg. Design 11 (1999) 229–253 [11]; P. Aspettati, S. Barone, A. Curcio, M. Picone, Parametric and feature-based assembly in motorcycle design: from preliminary development to detail definition, in: XII ADM International Conference, Italy, 5–7 September, 2001].The strongly parameterised structures allow calculating and assessing different individuals of a given structure in a very efficient and automated way. This makes parametric associative structures very suitable for optimisation.After structural optimisation tasks have successfully been performed with parametric models [U.M. Fasel, O. König, M. Wintermantel, N. Zehnder, P. Ermanni, DynOPS – an approach to parameter optimization with arbitrary simulation software, Centre of Structure Technologies, ETH Zurich; O. König, R. Puisa, M. Wintermantel, P. Ermanni, CAD-entity based evolutionary design optimization, Centre of Structure Technologies, ETH Zurich, and VGTU, Faculty of Mechanics, Vilnius, Lithuania; U.M. Fasel, O. König, M. Wintermantel, P. Ermanni, Using evolutionary methods with a heterogeneous genotype representation for design optimization of a tubular steel trellis motorbike-frame, Centre of Structure Technologies, ETH Zurich], multi-disciplinary optimisations are gaining importance, since they have the potential to find global optima instead of the discipline-dependent optimal configurations and solutions.