Abstract

Event Abstract Back to Event Development of a flow evolution network model for predicting the viscoplastic behavior of poly(L-lactide) Maureen Dreher1*, Srinidhi Nagaraja1*, Jorgen Bergstrom2* and Danika Hayman2* 1 FDA/CDRH, Division of Applied Mechanics/ Office of Science and Engineering Laboratories, United States 2 Veryst Engineering, United States Introduction: Absorbable polymers are increasingly being used for medical implants that perform a structural role[1]. Computational modeling is critical to device development in order to predict the stress distribution under typical loading conditions. This is especially true for absorbable cardiovascular devices, such as stents, which experience significant plastic deformation when crimped onto a delivery catheter and are cyclically loaded in vivo. However, computational modeling of absorbable devices is significantly hampered by a lack of appropriate constitutive models that capture their viscoelasticity and post-yield behavior. Here, we developed a constitutive model that incorporated viscoplasticity for a common medical absorbable polymer. Materials and Methods: Candidate constitutive models were selected based on the experimental response at 37°C observed during multiple tensile test protocols performed on microtensile bars (thickness=0.5mm, width = 1.42mm, length = 3.8mm) fabricated from poly(L-lactide), i.e., PLLA. The dimensions were chosen in order to be relevant for transcatheter cardiovascular devices. Before testing, all specimens were airbrushed to create a speckled pattern and enable local strain measurements through digital image correlation[2]. The protocols encompassed monotonic ramp (strain rate=0.5%/min, 5%/min, 10%/min), stress relaxation, and “yield point” tests consisting of load/ un-load cycles below and above the yield. Yield point tests provide information on the unloading behavior of the polymer prior to and after yield. The experimental stress-strain data were curve-fit to two candidate constitutive relationships, namely, the Three Network Model (TNM) and a Flow Evolution Network Model (FEN)[3], followed by refinement through finite element simulations of tensile experiments. Both the TNM and the FEN models are capable of capturing large strain viscoplastic behavior, but the FEN model has the advantage of capturing strong softening post-yield. Results and Discussion: Monotonic testing demonstrated that PLLA exhibits rate dependent stress-strain behavior with a significant post-yield region (Fig 1). The peak stress increased with increasing strain rate (47MPa vs 62MPa) while the strain at failure decreased (0.75 vs 0.3). PLLA exhibited significant relaxation prior to and post yield with stress decreases of ~75% and 80% over 30 min, respectively (Fig 2). Yield point tests demonstrate that little hysteresis is generated in linear region. Together, these results suggest that PLLA exhibits complex viscoplasticity that influences the stress level and should be accounted for in computational models of PLLA devices. The FEN model was able to capture these relevant behaviors more accurately than the TNM (NMAD fitness_TNM=9.4, NMAD fitness_FEN=3.5). Conclusion: The FEN constitutive model was able to accurately capture the strain rate dependent loading and unloading behavior which suggests its validity for modeling mechanics of PLLA. This study was funded by the CDRH Critical Path program; We gratefully acknowledge the insights and support David Quinn, PhD

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