Time-dependent damage evolution in multidirectional polymer matrix composite laminates

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Date
2008-05-07T17:20:06Z
Authors
Birur, Anand
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Abstract
Multi-directional polymer matrix composite materials are increasingly used in load-bearing structural applications ranging from primary aircraft structures and automotive parts to rehabilitation of bridges. Long-term durability, characterized by time-dependent degradation in strength (known as creep-rupture) and modulus (known as creep), is an important concern in these applications. Despite the experimental evidence on the influence of time-dependent damage on creep and creep rupture of multi-directional composites, current level of understanding of this is very limited. Hence, the focus of this thesis is to develop a clear understanding of the time dependent evolution of various damage modes and their influence on creep rupture of polymer matrix composite laminates.Three laminates [0/90/0], [±45/902]s, and [0/902]s were subjected to a wide range of constant stresses at various test temperatures and creep rupture time was recorded.The various damage modes that developed, with stress during tensile testing, and with time during constant stress creep rupture testing were transverse cracking, vertical cracking, delamination, vertical splitting and fiber fracture.The appearance of these damages were time dependent confirming that the FPF stress is time-dependent, while the conventional wisdom is to consider it to be time-independent in design. Beyond FPF, the damage continued to evolve for a certain period of time beyond which additional damage modes started to evolve influencing the evolution rate of one-another.The percentage of creep rupture time during which a single mode of damage was evolving decreased with increase in applied stress and test temperature.Based on these results it is concluded that creep rupture of multidirectional laminates is influenced by contributions from a complex interaction of various damage modes that evolve with time, suggesting that creep rupture predictions could be good approximations only.
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PMC, Time-dependent
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