On finite bending of visco-hyperelastic materials: a novel analytical solution and FEM

Shojaeifard, Mohammad; Sheikhi, Sara; Baniassadi, Majid; Baghani, Mostafa

doi:10.1007/s00707-020-02733-4

Cited by 22 publications

(4 citation statements)

References 46 publications

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“…Now to define the mechanical field, following Holzapfel (Holzapfel, 2002; Shojaeifard et al, 2020a), a Generalized Maxwell Visco-hyperelastic model is applied to capture the transient finite deformation of the hydrogel. Thus, decomposing the total energy density to isochoric, volumetric parts, and the contribution of the viscoelastic branch, the second Piola–Kirchhoff stress tensor is computed as:…”

Section: Theory and Methodologymentioning

confidence: 99%

“…In another work, Sun et al (2013) introduced polyampholytes polymers that can undergo large reversible deformation and possess high toughness. Finite deformation of the soft materials is usually described by considering hyperelastic and visco-hyperelastic constitutive models based on the time dependency of the materials’ behavior (Sheikhi et al, 2019; Shojaeifard et al, 2020a; Valiollahi et al, 2019). Possessing viscoelastic properties, polyampholytes polymers form both weak and strong bonds when the cationic and anionic groups opened out in the hydrogel structure.…”

Section: Introductionmentioning

confidence: 99%

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Programmable self-folding of trilayer and bilayer-hinge structures by time-dependent swelling of tough hydrogels

Shojaeifard

Niroumandi

Baghani

2022

Journal of Intelligent Material Systems and Structures

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Inspired by nature, active materials are used to developed complex 3D configurations considering their specific characteristics. One of the shape-shifting methods in smart structures is utilizing programmable materials in self-folding structures. Hydrogels due to their biocompatibility, controllable functionalities, large reversible deformations, and their sensitivity to environmental stimuli are vital candidates to be used in self-folding structures. To avoid the mechanical weakness of conventional hydrogels, in this paper polyampholyte tough hydrogel is inspected considering a transient electro-chemo-mechanical constitutive model combining a visco-hyperelastic model with Nernst-Planck and Poisson’s equations. After calibrating the material parameters and verifying the accuracy of the model and its implementation, we present two approaches in order to generate self-folding hydrogel-based structures: polymer structure with bilayer hinges and trilayer structure composed of a hydrogel film sandwiched between two elastomer layers. Next, diverse factors are examined in the self-folding of smart structures which conforms with experimental test data, including hydrogel swelling, structure thickness and stiffness, bilayer configuration and composition, the width of the bilayer as well as opening width in trilayer and layers thickness. Finally, several transient self-folding of 2D flat patterns which turn into 3D complex configurations are scrutinized such as the closure of box, pyramids, and flower-shaper gripper.

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Section: Theory and Methodologymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Programmable self-folding of trilayer and bilayer-hinge structures by time-dependent swelling of tough hydrogels

Shojaeifard

Niroumandi

Baghani

2022

Journal of Intelligent Material Systems and Structures

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“…Kanner and Horgan [ 26 ] introduced an analytical model to express the plane strain bending of an incompressible isotropic elastic material subjected to an end moment. Later, Shojaeifard, Sheikhi, Baniassadi, and Baghani [ 27 ] suggested a constitutive framework to represent the time-dependent behavior of visco-hyperelastic rectangular materials under finite bending. In our previous work, a new model was proposed for the stress-softening of an incompressible hyperelastic rectangular bar under cyclic bending and unbending deformation [ 28 ].…”

Section: Introductionmentioning

confidence: 99%

Finite Bending of Fiber-Reinforced Visco-Hyperelastic Material: Analytical Approach and FEM

Pashazadeh,

Ostadrahimi,

Baghani

et al. 2023

Materials

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This paper presents a new anisotropic visco-hyperelastic constitutive model for finite bending of an incompressible rectangular elastomeric material. The proposed approach is based on the Mooney–Rivlin anisotropic strain energy function and non-linear visco-hyperelastic method. In this study, we aim to examine the mechanical response of a reinforced viscoelastic rectangular bar with a group of fibers under bending. Anisotropic materials are typically composed of one (or more) family of reinforcing fibers embedded within a soft matrix material. This operation may lead to an enhancement in the strength and stiffness of soft materials. In addition, a finite element simulation is carried out to validate the accuracy of the analytical solution. In this research, the well-known stress relaxation test, as well as the multi-step relaxation test, are examined both analytically and numerically. The results obtained from the analytical solution are found to be in good agreement with those from the finite element method. Therefore, it can be deduced that the proposed model is competent in describing the mechanical behavior of fiber-reinforced materials when subjected to finite bending deformations.

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“…Accordingly, several studies have investigated this hyper-elastic behavior based on phenomenological or micromechanical approaches which use statistics of molecular chains networks (see reviews [6,7]). Shojaeifar et al [8,9] developed a model for modeling of visco-hyperelasticity of materials. Phenomenological approaches are empirical, simple, and less interpretable; however, micromechanical approaches are highly interpretable but complex because they consider the readjustment of kinks, the rearrangement of convolutions, reorientation, and uncoiling of molecular chains.…”

Section: Introductionmentioning

confidence: 99%

A Physics-Informed Assembly of Feed-Forward Neural Network Engines to Predict Inelasticity in Cross-Linked Polymers

2020

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In solid mechanics, data-driven approaches are widely considered as the new paradigm that can overcome the classic problems of constitutive models such as limiting hypothesis, complexity, and accuracy. However, the implementation of machine-learned approaches in material modeling has been modest due to the high-dimensionality of the data space, the significant size of missing data, and limited convergence. This work proposes a framework to hire concepts from polymer science, statistical physics, and continuum mechanics to provide super-constrained machine-learning techniques of reduced-order to partly overcome the existing difficulties. Using a sequential order-reduction, we have simplified the 3D stress–strain tensor mapping problem into a limited number of super-constrained 1D mapping problems. Next, we introduce an assembly of multiple replicated neural network learning agents (L-agents) to systematically classify those mapping problems into a few categories, each of which were described by a distinct agent type. By capturing all loading modes through a simplified set of dispersed experimental data, the proposed hybrid assembly of L-agents provides a new generation of machine-learned approaches that simply outperform most constitutive laws in training speed, and accuracy even in complicated loading scenarios. Interestingly, the physics-based nature of the proposed model avoids the low interpretability of conventional machine-learned models.

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On finite bending of visco-hyperelastic materials: a novel analytical solution and FEM

Cited by 22 publications

References 46 publications

Programmable self-folding of trilayer and bilayer-hinge structures by time-dependent swelling of tough hydrogels

Programmable self-folding of trilayer and bilayer-hinge structures by time-dependent swelling of tough hydrogels

Finite Bending of Fiber-Reinforced Visco-Hyperelastic Material: Analytical Approach and FEM

A Physics-Informed Assembly of Feed-Forward Neural Network Engines to Predict Inelasticity in Cross-Linked Polymers

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