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Energy Absorption of Metal-FRP Hybrid Square Tubes

Lower-cost manufacturing methods have increased the anticipation for economical mass production of vehicles manufactured from composite materials. One of the potential applications of composite materials in vehicles is in energy-absorbing components such as hollow shells and struts (these components may be in the form of circular cylindrical shells, square and rectangular tubes, conical shells, and frusta). However, constructions which result in brittle fracture of the composite tubes in the form of circumferential or longitudinal corner crack propagation may lead to unstable collapse failure mode and concomitant very low energy absorption. As a result, metal-composite hollow tubes have been developed that combine the benefits of stable ductile collapse of the metal (which can absorb crushing energy in a controlled manner) and the high strength-to-weight ratio of the composites. The relative and absolute thicknesses of metal or FRP section has a substantial effect on energy absorption of the hybrid tubes. In particular, likelihood of delamination occurrence raises with increase in FRP thickness. This can reduce the energy absorption capability of the metal-FRP hybrid tubes. Additionally, adding a very thick FRP section may result in a global buckling failure mode (rather than local folding). Until now, there are no studies specifically addressing the effect of FRP thickness on energy absorption of hybrid tubes. In this study, the effects of fiber orientation and FRP thickness (the number of layers) on the energy absorption of S2-glass/epoxy-304 stainless steel square tubes were experimentally investigated. In addition, a new geometrical trigger was demonstrated which has positive effects on the collapse modes, delamination in the FRP, and the crush load efficiency of the hybrid tube.

To complete this study, a new methodology including the combination of experimental results, numerical modeling, and a multi-objective optimization process was introduced to obtain the best combination of design variables for hybrid metal-composite tubes for crashworthiness applications. The experimental results for the S2 glass/epoxy-304 stainless steel square tubes with different configurations tested under quasi-static compression loading were used to validate numerical models implemented in LS-DYNA software. The models were able to capture progressive failure mechanisms of the hybrid tubes. In addition, the effects of the design variables on the energy absorption and failure modes of the hybrid tubes were explained. Subsequently, the results from the numerical models were used to obtain optimum crashworthiness functions. The load efficiency factor (the ratio of mean crushing load to maximum load) and ratio between the difference of mean crushing load of hybrid and metal tube and thickness of the FRP section were introduced as objective functions. To connect the variables and the functions, back-propagation artificial neural networks (ANN) were used. The Non-dominated Sorting Genetic Algorithm–II (NSGAII) was applied to the constructed ANNs to obtain optimal results. The results were presented in the form of Pareto frontiers to help designers choose optimized configurations based on their manufacturing limitations. Such restrictions may include, but are not limited to, cost (related to the number of layers), laminate architecture (fiber orientation and stacking sequence) which can be constrained by the manufacturing techniques (i.e. filament winding) and thickness (as an example of physical constraints). / Ph. D. / In a car accident, the incident energy must be absorbed by elements of the vehicles to prevent it from being transferred to the occupants. (Indeed, a vehicle that is not damaged in a crash may lead to significant injury to occupants.) Typical energy absorbing elements in a vehicle include hollow shells and struts in the crumple zone, bumpers, and airbags. The focus of this study is on hollow thin-walled tubes in the form of hybrid metal-composite square tubes which have the potential to provide cost-effective structures for energy absorption applications. The behavior of these elements is complicated, requiring computationally intensive and time-consuming computer simulations to analyze their failure and to improve their design. The time required for these simulations may lead to long times before new elements are introduced into the marketplace. Consequently, the objective of this study is to provide an efficient and fast methodology to obtain the best hybrid structures for crashworthiness applications. To support the computational modeling, experimental results obtained from the samples with different configurations tested under quasi-static compression loading were used to validate the models. The effect of fiber orientation, stacking sequence, and thickness of the composite on energy absorption and failure modes were predicted using the models. To reduce the time associated with computational modeling, artificial neural networks (ANNs) were employed to fit the response at selected training points and to generate a pool of responses at other points. These responses may then be used by a designer to choose the best solution for a set of competing design constraints.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/74960
Date07 February 2017
CreatorsKalhor, Roozbeh
ContributorsEngineering Science and Mechanics, Case, Scott W., Al-Haik, Marwan, Ross, Shane D., Seidel, Gary D.
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeDissertation
FormatETD, application/pdf, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

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