posted on 2021-05-13, 10:15authored byF. Cavaliere, S. Zlotnik, R. Sevilla, X. Larráyoz, P. Díez
The goal of this work is to develop a computational method able to optimize the design process of a car
structure and provide a tool which can support designers during the decision-making phase. The design of
a car body-in-white (BIW) structure is the process which goes from the initial idea to the final approved
model. During this phase, which represents the most time-consuming part of the whole development
process, designers have to deal with very complex parametric problems where material and geometric
characteristics of the car components are the unknown. Any change in these parameters might significantly
affect the global behaviour of the car. A target which is very sensitive to small variations of the parameters
is the noise and vibration response of the vehicle (NVH test), which strictly depends on the global static
and dynamic stiffness. In order to find the optimal solution, a lot of configurations exploring all the
possible parametric combinations need to be tested. Standard numerical methods are computationally
very expensive when applied to this kind of multidimensional problems. An alternative is represented
by reduced order models (ROM), which are based on the idea that the essential behaviour of complex
systems can be accurately described by simplified low-order models. In this work, the encapsulated proper
generalized decomposition (Encapsulated-PGD) toolbox, based on the PGD Least-Squares approximation
[3] is proposed. As a main advantage, this ROM technique requires only one offline computation. The
latter provides a separable solution which depends explicitly on an a-priori unknown number of parametric
and mechanic modes or snapshots. Then, during an online stage, the solution can be particularized in realtime for any set of the parameters. In a previous work [4], a coupling of the PGD method with the Inertia
Relief technique was implemented in order to perform the parametric static analysis of an unconstrained
structures. A novel algebraic approach allowed to incorporate both material and complex geometric
parameters and to perform shape optimization. Here, the method is extended to the case of a parametric
generalized eigenvalue problem, in order to identify how a variation of user-defined parameters affects
the dynamic response of the structure in terms of dominant eigenmodes and related natural frequencies.
Moreover, thanks to the nonintrusive format of the toolbox, an interaction with commercial software is
possible, which makes it particularly interesting for real industrial applications.