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The aim of this work is to develop a model to continuously predict inhomogeneous and homogeneous swelling behavior of temperature-sensitive poly-(N-isopropylacrylamide) hydrogels. Employing this model, some benchmark homogeneous problems such as free, unidirectional constrained and biaxial constrained swelling as well as swelling of core-shell structures are investigated. The main advantage of the model is its ability to solve inhomogeneous deformations due to a stable behavior in the vicinity of the phase transition temperature. Therefore, inhomogeneous swelling of a spherical shell on a hard core with application to microfluidics is analytically and numerically investigated for various thicknesses of the shell. Based on the solved examples, it is shown that the model possesses continuity and stability in the vicinity of the phase transition temperature.

In this article, satisfying the second law of thermodynamics, we present a 3D constitutive model for shape memory polymers. The model is based on an additive decomposition of the strain into four parts. Also, evolution laws for internal variables during both cooling and heating processes are proposed. Since temperature has considerable effect on the shape memory polymer behavior, for simulation of a shape memory polymer–based structure, it is required to perform a heat-transfer analysis. Commonly, an experimentally observed temperature rate–dependent behavior of shape memory polymers is justified by a rate-dependent glassy temperature, but using the heat-transfer analysis, it is shown that the glassy temperature could be considered as a constant material parameter. To this end, implementing the constitutive model within a nonlinear finite element code, we simulate torsion of a shape memory polymer rectangular bar and a circular tube. Moreover, we compare the predicted results with experimental data recently reported in the literature, which shows a good agreement.

This paper presents an experimental investigation on the effect of structural (geometrical) design on the thermomechanical behavior of shape memory polymers. Three beams with identical dimensions (length, width, and thickness), material, and mass, but with different geometrical cells (honeycomb, diamond, and rounded rectangle) are designed by solving a set of nonlinear equations and produced using additive manufacturing method. Then, thermomechanical tests under bending and tensile loading at different temperatures are conducted. As a result, shape recovery and force recovery of the beams, due to the shape memory behavior of the material, are measured. In bending and tensile tests, shape and force recovery results of each beam are compared with their own pre-force and other beams. According to the results, the beam with rounded rectangle cells has the most shape recovery and force recovery ratios (compared to its applied pre-force). Shape recovery for this beam type in bending and tensile tests is 93.03% and 87.86%, respectively. The beam with honeycomb cells requires more pre-force in bending and tensile modes for programming, which leads to a higher maximum force recovery, due to its higher strength.

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The deterioration of the musculoskeletal system is a serious health concern for long term space missions. The accumulated information over the past decades of space flights showed that microgravity impacts significantly the musculoskeletal system with muscle atrophy and bone loss. Until now, it has been difficult to make reasonable predictions of the bone loss for prolonged space missions due to the lack of in-space experimental data and weak understanding of the mechanobiological bone mechanisms. On earth, the healthy musculoskeletal degradation is mainly age related with osteoporosis and delayed fracture healing. A better understanding of the bone mechanobiological functions could help us improve our model predictions of the musculoskeletal health system during long term space missions.We develop a numerical model able to predict the bone loss at the mesoscopic scale (bone trabecula) in microgravity. The model is able to correlate the calculated bone degradation mechanism with data available in the literature showing the effective bone density loss measured experimentally. An optimization algorithm is used for an average bone microstructure distribution and long-term prediction. Extrapolation is made to link the local bone loss at the structural scale with the corresponding effective bone strength. The first part of the paper details the extraction of the bone microstructure using micro-CT images and numerical model development. Next, the degradation and optimization schemes are detailed. Finally, some results are presented for long term degradation.

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