Optimization of Performance and Failure Predictability in Composite Laminates Undergoing Progressive Failure

Abstract

Increasing robustness of structures with non-linear history dependent behavior requires that their response to be very predictable. Predictability is made difficult by lack of good physical models (e.g. material failure), inaccurate analysis models, and insufficient resolution used in the discretized solutions. In complex structures the problem is compounded because numerous bifurcation events in non-linear response lead to competing failure paths. Introducing small changes to designs parameters or loading in designs having competing failure modes significantly alters the failure paths, reducing predictability. Progressive failure of a composite laminate is a system with many failing components (plies) and multiple failure modes (plies can fail by shear, matrix and/or fiber failure) that exhibits this behavior. This paper demonstrates that deterministic optimization makes predictability poor due the coalescence in failure modes. A deterministic approach is developed to overcome this problem and simultaneously optimize the laminate to maximize energy absorption (performance) and improve failure predictability. The approach is contrasted with traditional reliability-based optimization. The approach developed for eliminating competing failure modes is effective in increasing predictability and robustness, requiring very small computational effort compared to traditional non-deterministic methods used for such problems.