Fail-safe optimization of beam structures

Abstract

In the current work, a fail-safe optimization of beam structures is carried out. This approach may provide an insight into the robustness of lattice structures. The use of beam elements allows a commonly used engineering approach for obtaining a fail-safe design to be applied. This consists of removing one beam element at a time and optimizing the remaining structure. At the end of the process, the maximum beam radii are used for the final design. This approach is computationally extremely expensive for lattice structures, as it requires one optimization per removed beam. In our contribution, we show that the design obtained from this approach does not actually achieve the desired fail-safe behaviour. We therefore apply a multi-model approach in which the fail-safe requirement is an optimization constraint. This is still computationally demanding and therefore, methods for reducing the number of failure cases to be considered within the optimization are discussed. Furthermore, the p-norm is applied to the stress constraints to reduce the computational effort for the gradient calculation. Reduction of failure cases and use of the p-norm have opposite effects on the conservatism of the result and therefore compensate each other to some extent. Highlights Stress constrained optimization of beam structures. Evaluation of different approaches for fail-safe design. Strategies for efficiency improvement (reducing failure cases/p-norm).

Fail‐safe optimization of viscous dampers for seismic retrofitting

“…44,45 However, reliability-based optimization approaches rely on statistics and probabilistic analyses, whereas fail-safe approaches rely on the definition of worst case locations of failure scenarios and their associated optimization constraints. 46,47 In the context of more traditional structural design applications, the fail-safe optimization for static loading has received an increasing attention by several researchers. One of the first contributions is from 1976 by Sun et al, 48 in the field of fail-safe truss structural optimization.…”

“…In general, the fail‐safe optimization subject falls into the category of design involving uncertainties, known generally as reliability‐based design optimization (RBDO) 44,45 . However, reliability‐based optimization approaches rely on statistics and probabilistic analyses, whereas fail‐safe approaches rely on the definition of worst case locations of failure scenarios and their associated optimization constraints 46,47 …”

“…Kanno 51 in 2017 proposed an approach for fail‐safe structural optimization of trusses based on the worst case scenario of structural degradation. Lüdeker and Kriegesmann 47 in 2019 discussed the fail‐safe optimization of beam structures. They define the failure scenarios as complete removal of one beam at a time.…”

On stress-constrained fail-safe structural optimization considering partial damage

“…In the literature, fail-safe structural optimization has long been developed to achieve fail-safe design by including damage scenarios or failure modes into the design optimization problem, see e.g. Sun et al (1976); Achtziger and Bendsøe (1999); Jansen et al (2014); Zhou and Fleury (2016); Peng and Sui (2018); Lüdeker and Kriegesmann (2019); Stolpe (2019); Pollini (2020); Ambrozkiewicz and Kriegesmann (2020). Previous studies have considered complete loss of one arbitrary member in frame structures (Sun et al, 1976;Lüdeker and Kriegesmann, 2019;Stolpe, 2019), or complete loss of one arbitrary element/patch of material in continuum structures (Jansen et al, 2014;Zhou and Fleury, 2016).…”

Probability-damage approach for fail-safe design optimization (PDFSO)

“…Therefore, this optimization strategy achieves a fail-safe design with the minimum penalty weight over the intact structure. Lüdeker and Kriegesmann (2019) carried out the fail-safe optimization of beam structures, providing an insight into the robustness of lattice structures. Furthermore, if random parameters are considered in the optimization process, the multi-model Reliability-Based Design Optimization (RBDO) approach was proposed by Cid et al (2018) to obtain the fail-safe optimum design under uncertainty.…”