Robust numerical approaches for simulating the buckling response of 3D fiber-metal laminates under axial impact – Validation with experimental results
Source abstract
Abstract
The reliability and efficiency of three different numerical modeling approaches for simulating the response of a newly developed 3D fiber-metal laminate (3D-FML), subject to axial impact loading, are considered in this paper. The main objective of the study is to establish the most robust numerical framework for analyzing the performance of such complexly configured hybrid materials subject to axial impact loading in a fairly accurate, yet efficient manner. LS-DYNA finite element software is used for the purpose. The models include: (i) a full 3D solid model, where all 3D-FML constituents are modeled with 3D elements; (ii) a model with intermediate complexity, in which two different element types are used to model the metallic skins and 3D-fiberglass/foam core, respectively; and (iii) a simplified scheme, consisting of a single layer of thin-shell elements, representing all constituents of the FML. An experimental investigation is also conducted in parallel to verify the accuracy of the modeling schemes. Force and axial-shortening histories, energy absorption capacity, and overall qualitative behavior obtained numerically are compared to experimental results. Both accuracy and computation cost are considered as the performance criteria, all with the aim of providing the reader with some perspective for robust modeling of such geometrically sophisticated composites, subject to a complex loading mechanism.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Mechanical Behavior of Composites · Composite Structure Analysis and Optimization · Numerical methods in engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Mechanical Engineering, Advanced Composite and Mechanics Laboratory, Dalhousie University, Halifax, Nova Scotia, Canada
Funding
Mitacs · National Research Council Canada
References (42)
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