A 3D SMA constitutive model in the framework of finite strain

The aim of the present paper is to propose a phenomenological thermodynamically consistent 3D model for shape memory alloys (SMA) in the finite strain range. In particular, a model able to predict the main features of SMA materials, such as the superelastic and the shape‐memory effects, is proposed. The model is based on the assumption of the local multiplicative split of the deformation gradient into an elastic and a phase transformation part. The governing state and evolutive equations are written in the undeformed configuration. The material parameters of the model are characterized by a clear physical meaning so that they can be determined by simple experimental tests. The finite deformation SMA model is also reformulated in the framework of small strain, linearizing the strain and stress measures in order to obtain a consistent constitutive model preserving the nonlinear material response. A robust algorithm is adopted in order to integrate the nonlinear evolutive equations; 2D and 3D finite elements are implemented in a numerical code considering finite and small deformations. Some numerical applications are carried out showing the performances of the proposed model and the developed numerical procedure to describe the superelastic and the shape‐memory effects of SMA devices. Comparisons of different results obtained by the small and finite strain formulations are reported. Copyright © 2009 John Wiley & Sons, Ltd.     

On the robustness and efficiency of integration algorithms for a 3D finite strain phenomenological SMA constitutive model

Most devices based on shape memory alloys experience large rotations and moderate or finite strains. This motivates the development of finite‐strain constitutive models together with the appropriate computational counterparts. To this end, in the present paper a three‐dimensional finite‐strain phenomenological constitutive model is investigated and a robust and efficient integration algorithm is proposed. Properly defining the variables, extensively used regularization schemes are avoided and a nucleation–completion criterion is defined. Moreover, introducing a logarithmic mapping, a new form of time‐discrete equations is proposed. The solution algorithm as well as a suitable initial guess for the resultant nonlinear equations are also deeply discussed. Extensive numerical tests are performed to show robustness as well as efficiency of the proposed integration algorithm. Implementation of the integration algorithm within a user‐defined subroutine UMAT in the commercial nonlinear finite element software ABAQUS/Standard makes also possible the solution of a variety of boundary value problems. The obtained results show the efficiency and robustness of the proposed approach and confirm the improved efficiency (in terms of solution CPU time) when a nucleation–completion criterion is used instead of regularization schemes, as well as when a logarithmic mapping is used for the time‐discrete evolution equation instead of an exponential mapping. Copyright © 2010 John Wiley & Sons, Ltd.     

形状记忆合金纤维混杂正交对称铺层板的固有频率

形状记忆合金（SMA）混杂复合材料板是将有预应变的SMA纤维与普通纤维混杂单层内构成的。基于主动应变能调节（ASET）的概念,可实现对板的固有频率的调整。本文采用Galerkin法导出形状记忆合金（SAM）纤维混杂对称正交智能复合材料铺层板自由振动的频率的分析表达式。数值结果表明,SMA纤维的相变激发温度、体积含量、分布方式及其预应变对固有频率均有的影响,尤其是温度、SAM含量及其分布的作用更为显著,是结构振动控制的重要设计参数。     

An incremental energy minimization state update algorithm for 3D phenomenological internal‐variable SMA constitutive models based on isotropic flow potentials

An incremental energy minimization approach for the solution of the constitutive equations of 3D phenomenological models for shape memory alloys (SMA) is presented. A robust algorithm for the solution of the resulting nonsmooth constrained minimization problem is devised, without introducing any regularization in the dissipation or chemical terms. The proposed algorithm is based on a thorough detection of the singularities relevant to the incremental energy formulation, in conjunction with a Newton–Raphson method equipped with a Wolfe line search dealing with regular solutions. The saturation constraint on the transformation strain is treated by means of an active set strategy, thus avoiding any need for a two‐stage return‐mapping algorithm. A parametrization of the saturation constraint manifold is introduced, thus reducing the problem dimensionality, with improved computational performance. Finally, an efficient algorithm for the computation of the dissipation function in terms of Haigh–Westergaard invariants is presented, allowing for a quite general choice of deviatoric transformation functions. Numerical results confirm the robustness and consistency of the proposed state update algorithm. Copyright © 2015 John Wiley & Sons, Ltd.     

A time integration algorithm for a 3D constitutive model for SMAs including permanent inelasticity and degradation effects

Components based on shape‐memory alloys are often subjected to several loading cycles that result in substantial alteration of material behavior. In such a framework, accurate models, as well as robust and efficient numerical approaches, become essential to allow for the simulation of complex devices. The present paper focuses on the numerical simulation of quasi‐static problems involving shape‐memory alloy structures or components subjected to multiple loading‐unloading cycles. A novel state‐update procedure for a three‐dimensional phenomenological model able to describe the saturation of permanent inelasticity, including degradation effects, is proposed here. The algorithm, being of the predictor‐corrector type and relying on an incremental energy minimization approach, is based on elastic checks, closed‐form solutions of polynomial equations, and nonlinear scalar equations solved through a combination of Newton‐Raphson and bisection methods. This allows for an easy implementation of model equations and to avoid the use of regularization parameters for the treatment of nonsmooth functions. Numerical results assess the good performances of the proposed approach in predicting both pseudoelastic and shape‐memory material behavior under cyclic loading as well as algorithm robustness.     

On instabilities and autocatalytic effects associated with the nucleation of martensite bands in polycrystalline SMA flat tensile specimens

The mechanical response in the pseudoelastic range of polycrystalline NiTi SMA specimens in displacement controlled tensile tests exhibits a load drop associated with the nucleation of martensitic bands, a phenomenon which is similar to the formation of Lüders bands in mild steel. A continuum mechanical energy approach allows to calculate the nominal stress–strain curve incorporating the characteristic load drop. The influence of the geometrical aspect ratio, i.e., thickness-to-width ratio of the flat tensile test specimens on the load drop is discussed and compared to the experimental data.     

Dynamic multiaxial behaviors of 3D shape memory alloy nanowires: A phase-field study

This article focuses on the dynamic multiaxial behaviors of shape memory alloy (SMA) rectangular prismatic nanowires. A strain-based order parameter 3D phase-field model is used to study microstructure evolution and consequent thermo-mechanical behaviors in the cubic-to-tetragonal transformations in SMA nanowires. The FePd nanowire is subjected to axial-transverse and axial-torsion loadings paths. The numerical results demonstrate the strong influence of multiaxial loadings on microstructures and thermo-mechanical response. The variation of thermo-mechanical response stems from the nucleation of energetically favorable martensitic variants to the applied loading. The understanding of multiaxial thermo-mechanical response of nanowires is essential in developing better SMA-based devices.     

3D analytical mathematical models of random star-shape particles via a combination of X-ray computed microtomography and spherical harmonic analysis

To compute any physical quantity for a random particle, one needs to know the mathematical shape of the particle. For regular particles like spheres and ellipsoids, the mathematics are straightforward. For random particles, with realistic shapes, mathematically characterizing the shape had not been generally done. But since about the year 2002, a method has been developed that combines X-ray computed tomography and spherical harmonic analysis to give analytical, differentiable mathematical functions for the three-dimensional shape of star-shape particles, which are a wide class of particles covering most industrial particles of interest, ranging from micrometer scale to millimeter scale particles. This review article describes how this is done, in some detail, and then gives examples of applications of this method, including a contact function that is suitable for these random shape particles. The purpose of this article is to make these ideas widely available for the general powder researcher who knows that particle shape is important to his/her applications, and especially for those researchers who are just starting out in their particle science and technology careers.     

3D Printable and Reconfigurable Liquid Crystal Elastomers with Light-Induced Shape Memory via Dynamic Bond Exchange

3D printable and reconfigurable liquid crystal elastomers (LCEs) that reversibly shape-morph when cycled above and below their nematic-to-isotropic transition temperature (T_NI) are created, whose actuated shape can be locked-in via high-temperature UV exposure. By synthesizing LCE-based inks with light-triggerable dynamic bonds, printing can be harnessed to locally program their director alignment and UV light can be used to enable controlled network reconfiguration without requiring an imposed mechanical field. Using this integrated approach, 3D LCEs are constructed in both monolithic and heterogenous layouts that exhibit complex shape changes, and whose transformed shapes could be locked-in on demand.     

Generation of realistic 3D concrete aggregate microstructures using multiscale multifractal evolutionary stochastic manifold and operator-split-genetic algorithm

Concrete aggregates have a random and complex microstructure. This study presents a computational framework and methodology for realistic representation, simulation, and optimization of stochastic 3D aggregate microstructures. Central to the proposed methodology is the representation of aggregate microstructures as multiscale multifractal evolutionary stochastic manifolds that evolve over time in the topological space. In addition to the manifold representation scheme, a coupled-operator-split-genetic algorithm is also developed for the simulation and optimization of aggregate microstructures. The proposed scheme is particularly attractive due to its simplicity and ability to capture the complex morphological, topographical, and evolutionary characteristics of aggregate microstructures. More than a new method, this study introduces a novel concept of multiscale multifractal evolutionary hypersurface for the simulation and optimization of aggregate microstructures. The applicability and capability of the proposed approach may open up new ways to better understand, characterize, simulate, and capture many complex micromechanical behaviors of cementitious materials.     

Generation and quality improvement of 3D models from silhouettes of 2D images

The shape-from-silhouette (SFS) method has been widely used in 3D shape reconstruction. It uses silhouettes of a series of 2D images captured from multiple viewpoints of an object to generate a 3D model that describes the visual hull of the object. The SFS method faces an inherent problem that virtual features appear all over the model. In addition, concavities on the object may wrongly be modeled as convex shapes because they are invisible on image silhouettes. The purpose of this study is to propose a method to generate a 3D model from silhouettes of multiple images and propose a quality improvement method to overcome the above-mentioned problems. The 3D modeling method focuses on accurate evaluation of 3D points intersected by all polyhedra from different views and the removal of poor meshes on triangulation. The quality improvement method is essentially an iterative procedure, which for smoothing the model and eliminating virtual features and artifacts, while preserving the consistency of all silhouettes. The proposed method is to be used for product presentations in e-commerce, in which the 3D model must be covered with color texture of an object. Several examples are presented to illustrate the capability of the proposed method.     

Direct Fused Deposition Modeling 4D Printing and Programming of Thermoresponsive Shape Memory Polymers with Autonomous 2D-to-3D Shape Transformations

Herein, direct 4D printing of thermoresponsive shape memory polymers (SMPs) by the fused deposition modeling (FDM) method that enables programing of 2D objects during printing for autonomous 2D-to-3D shape transformations via simply heating is focused on. The programming process during printing is investigated through designs and experiments. The capability of programming SMPs during printing is illustrated by prestrain and bending capabilities, which are highly related to printing settings, such as nozzle temperature, print speed, layer height, infill patterns, and ratio of active parts in a bilayer structure. A nearly linear relationship for prestrain and bending parameters is experimentally revealed for different printing factors. Quantitative results are presented to be used as a guidance for designing complex 3D structures via 4D printing of 2D structures. Helix structure, twisting structure, DNA-like structures, and functional gripper are designed to demonstrate the potential of direct FDM 4D printing for creating complex 3D structures from simple 2D structures with advantages over traditional manufacturing methods. It is shown that, by removing the need for a layer-by-layer stacking process to achieve a complex 3D shape, FDM can promote sustainability via 4D printing of autonomous 2D-to-3D shape transformer structures with lower materials, time, energy, and longer service life.     

Curing characteristics of shape memory polymers in 3D projection and laser stereolithography

The radical shift in 3D printing to fabricate soft active materials such as shape memory polymers (SMPs) has brought along other techniques in realising 4D printing. Stereolithography (SL) process has recently been one of the popular systems for printing SMPs. In this paper, the curing characteristics and behaviour of the SMPs fabricated via projection-type and laser-scanning-type SL process were analysed. Factors such as the UV exposure of the projection type and variation in resin compositions have significant differences in terms of energy density and curing depths when compared to the laser scanning type. Hence, theoretical calculations were made to determine the critical energy density and threshold penetration depth attainable, which enables newly developed SMP materials to be successfully printable using different types of UV-based 3D printing systems.     

Rapid Open‐Air Digital Light 3D Printing of Thermoplastic Polymer

3D printing has witnessed a new era in which highly complexed customized products become reality. Realizing its ultimate potential requires simultaneous attainment of both printing speed and product versatility. Among various printing techniques, digital light processing (DLP) stands out in its high speed but is limited to intractable light curable thermosets. Thermoplastic polymers, despite their reprocessibility that allows more options for further manipulation, are restricted to intrinsically slow printing methods such as fused deposition modeling. Extending DLP to thermoplastics is highly desirable, but is challenging due to the need to reach rapid liquid–solid separation during the printing process. Here, a successful attempt at DLP printing of thermoplastic polymers is reported, realized by controlling two competing kinetic processes (polymerization and polymer dissolution) simultaneously occurring during printing. With a selected monomer, 4‐acryloylmorpholine (ACMO), printing of thermoplastic 3D scaffolds is demonstrated, which can be further converted into various materials/devices utilizing its unique water‐soluble characteristic. The ultralow viscosity of ACMO, along with surface oxygen inhibition, allows rapid liquid flow toward high‐speed open‐air printing. The process simplicity, enabling mechanism, and material versatility broaden the scope of 3D printing in constructing functional 3D devices including reconfigurable antenna, shape‐shifting structures, and microfluidics.     

Effect of small γ-precipitates on the two-way shape memory effect in Cu–Zn–Al alloys

The γ-precipitates in Cu–Zn–Al alloys, trained by the stabilization of the stress induced martensite (SSIM) method, have been studied. After the SSIM treatment, it was found that small γ-precipitates in the β-austenite are ellipsoidal, with a large strain field oriented in the same direction; while in the martensite the γ-precipitates changed their shape from ellipsoid to spheroid, and relaxed their strain fields. In order to check whether the strain field of the γ-precipitates is capable of producing a thermoelastic martensitic transformation, an in-situ observation, by heating a sample holder in TEM, was performed. It was found that during heating over a temperature A_s, the γ-precipitates with a spherical shape in the martensite recovered their strain field and elliptical shape. During cooling, the strain field of the γ-precipitates disappeared again. It was proposed that the strain field of the γ-precipitates, trained by the SSIM method, plays an important part in the thermoelastic martensitic transformation, and presents two-way shape memory effects.     

Remotely Triggered Assembly of 3D Mesostructures Through Shape‐Memory Effects

3D structures that incorporate high‐performance electronic materials and allow for remote, on‐demand 3D shape reconfiguration are of interest for applications that range from ingestible medical devices and microrobotics to tunable optoelectronics. Here, materials and design approaches are introduced for assembly of such systems via controlled mechanical buckling of 2D precursors built on shape‐memory polymer (SMP) substrates. The temporary shape fixing and recovery of SMPs, governed by thermomechanical loading, provide deterministic control over the assembly and reconfiguration processes, including a range of mechanical manipulations facilitated by the elastic and highly stretchable properties of the materials. Experimental demonstrations include 3D mesostructures of various geometries and length scales, as well as 3D aquatic platforms that can change trajectories and release small objects on demand. The results create many opportunities for advanced, programmable 3D microsystem technologies.     

Mesoporous Metal–Metalloid Amorphous Alloys: The First Synthesis of Open 3D Mesoporous Ni‐B Amorphous Alloy Spheres via a Dual Chemical Reduction Method

Selective hydrogenation of nitriles is an industrially relevant synthetic route for the preparation of primary amines. Amorphous metal–boron alloys have a tunable, glass‐like structure that generates a high concentration of unsaturated metal surface atoms that serve as active sites in hydrogenation reactions. Here, a method to create nanoparticles composed of mesoporous 3D networks of amorphous nickel–boron (Ni‐B) alloy is reported. The hydrogenation of benzyl cyanide to β‐phenylethylamine is used as a model reaction to assess catalytic performance. The mesoporous Ni‐B alloy spheres have a turnover frequency value of 11.6 h^?1, which outperforms non‐porous Ni‐B spheres with the same composition. The bottom‐up synthesis of mesoporous transition metal–metalloid alloys expands the possible reactions that these metal architectures can perform while simultaneously incorporating more Earth‐abundant catalysts.     

Accurate evaluation of 3D stress fields in adhesive bonded joints via higher-order FE models

Abstract

The accurate representation of the 3D stress fields at the bonded areas of adhesive joints is essential for their design and strength evaluation. In the present study, higher-order beam models developed in the framework of the Carrera Unified Formulation are employed to reduce the complexity and computational cost of numerical simulations on adhesive joints. The different components of the adhesive joint, i.e. adherends and adhesive, are modeled as beams with independent kinematics based on the Hierarchical Legendre Expansion (HLE). HLE models make use of a hierarchical polynomial expansion over the cross-section of the beam, thus allowing for the control of the accuracy of the stress solutions via the polynomial expansion. Recalling the Finite Element method, the beam axis is discretized by means of 1D elements. In this manner, generic geometries of the adhesive bonded joints can be studied. The proposed model is assessed through comparison against numerical and analytical references from the literature for single lap and double lap joints. Finally, a detailed 3D analysis is performed on the single lap joint problem, showing that the stress gradients along the adhesive are correctly and efficiently described if the proposed methodology is employed.     

Three-dimensional (3D) interconnected networks fabricated via <Emphasis Type="Italic">in-situ</Emphasis> growth of N-doped graphene/carbon nanotubes on Co-containing carbon nanofibers for enhanced oxygen reduction

The strategy of combining highly conductive frameworks with abundant active sites is desirable in the preparation of alternative catalysts to commercial Pt/C for the oxygen reduction reaction (ORR). In this study, N-doped graphene (NG) and carbon nanotubes (CNT) were grown in-situ on Co-containing carbon nanofibers (CNF) to form three-dimensional (3D) interconnected networks. The NG and CNT bound the interlaced CNF together, facilitating electron transfer and providing additional active sites. The 3D interconnected fiber networks exhibited excellent ORR catalytic behavior with an onset potential of 0.924 V (vs. reversible hydrogen electrode) and a higher current density than Pt/C beyond 0.720 V. In addition, the hybrid system exhibited superior stability and methanol tolerance to Pt/C in alkaline media. This method can be extended to the design of other 3D interconnected network architectures for energy storage and conversion applications.

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