scholarly journals A State-of-the-Art Review on Robots and Medical Devices Using Smart Fluids and Shape Memory Alloys

2018 ◽  
Vol 8 (10) ◽  
pp. 1928 ◽  
Author(s):  
Jung Sohn ◽  
Gi-Woo Kim ◽  
Seung-Bok Choi
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Medical Devices ◽  
Smart Materials ◽  
State Of The Art ◽  
Specific Mechanism ◽  
Smart Fluids ◽  
Different Types ◽  
Magneto Rheological ◽  
Significant Attention

Over the last two decades, smart materials have received significant attention over a broad range of engineering applications because of their unique and inherent characteristics for actuating and sensing aspects. In this review article, recent research works on various robots, medical devices and rehabilitation mechanisms whose main functions are activated by smart materials are introduced and discussed. Among many smart materials, electro-rheological fluids, magneto-rheological fluids, and shape memory alloys are considered since there are mostly appropriate application candidates for the robot and medical devices. Many different types of robots proposed to date, such as parallel planar robots, are investigated focusing on design configuration and operating principles. In addition, specific mechanism and operating principles of medical devices and rehabilitation systems are introduced and commented in terms of practical realization.

Smart Materials, Characteristics, Applications and Modeling

2009 ◽  
Author(s):  
Abbas Amini ◽  
Hamid Mehdigholi ◽  
Mohammad Elahinia
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Advanced Materials ◽  
New Era ◽  
Research Results ◽  
Smart Composites ◽  
Smart Fluids ◽  
Material Behaviors ◽  
Recent Developments

This paper reviews the research results, characteristics, modeling and recent developments of smart materials specially shape memory alloys and smart composites. This field even involves smart fluids and it opens a new era to find new smart materials for eliminating their flaws by combination with other advanced materials. The purpose of this paper is showing the current research coordinate. These issues help to have a technological reference for these materials. At the end, there is specific attention to Nitinols and by experiments is shown that Oliver-Pharr formulation does not cover these material behaviors. These experiments cover some important aspects of Nitinols which have not been considered by current researches.

The Development and Application of Smart Material Pumps

2013 ◽  
Vol 681 ◽  
pp. 260-265
Author(s):  
Ya Peng Zhao ◽  
Ding Fang Chen ◽  
Quan Guo Lu
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Smart Material ◽  
Different Types ◽  
Application Fields ◽  
Free Strain

This paper reviews the characteristics of smart materials, such as Piezoelectrics (PZT), shape memory alloys (SMA) and mganetostrictive materials (Terfenol-D). Since the properties of these smart materials vary greatly in terms of free strain and actuation stress, there is a need to identify the optimum smart materials for a particular application. From the review and comparison of different types of pumps (based on PZT, SMA and Terfenol-D), we recognize that these pumps have their unique advantages in specific application fields.

Intelligent Material Systems: Application of Functional Materials

1998 ◽  
Vol 51 (8) ◽  
pp. 505-521 ◽  
Author(s):  
Junji Tani ◽  
Toshiyuki Takagi ◽  
Jinhao Qiu
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Piezoelectric Materials ◽  
Functional Materials ◽  
Sensors And Actuators ◽  
Magnetostrictive Materials ◽  
Material Systems ◽  
Intelligent Material ◽  
Magneto Rheological

This article presents a review of recent important developments in the field of intelligent material systems. Intelligent material systems, sometimes referred to as smart materials, can adjust their behavior to changes of external or internal parameters analogously to biological systems. In these systems, sensors, actuators and controllers are seamlessly integrated with structural materials at the macroscopic or mesoscopic level. In general, sensors and actuators are made of functional materials and fluids such as piezoelectric materials, magnetostrictive materials, shape memory alloys, polymer hydrogels, electro- and magneto-rheological fluids and so on. This article is specifically focused on the application of piezoelectric materials, magnetostrictive materials and shape memory alloys to intelligent material systems used to control the deformation, vibration and fracture of composite materials and structures. This review article contains 188 references.

Effects of Annealing on Microstructure and Martensitic Transition of Ni-Mn-Co-In Ferromagnetic Shape Memory Alloys

2011 ◽  
Vol 674 ◽  
pp. 171-175
Author(s):  
Katarzyna Bałdys ◽  
Grzegorz Dercz ◽  
Łukasz Madej
Keyword(s):  
Electron Microscopy ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Martensitic Transition ◽  
Magnetic Shape Memory ◽  
Ferromagnetic Shape Memory Alloys ◽  
Initial State ◽  
X Ray ◽  
Ferromagnetic Shape Memory

The ferromagnetic shape memory alloys (FSMA) are relatively the brand new smart materials group. The most interesting issue connected with FSMA is magnetic shape memory, which gives a possibility to achieve relatively high strain (over 8%) caused by magnetic field. In this paper the effect of annealing on the microstructure and martensitic transition on Ni-Mn-Co-In ferromagnetic shape memory alloy has been studied. The alloy was prepared by melting of 99,98% pure Ni, 99,98% pure Mn, 99,98% pure Co, 99,99% pure In. The chemical composition, its homogeneity and the alloy microstructure were characterized using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The phase composition was also studied by X-ray analysis. The transformation course and characteristic temperatures were determined by the use of differential scanning calorimetry (DSC) and magnetic balance techniques. The results show that Tc of the annealed sample was found to decrease with increasing the annealing temperature. The Ms and Af increases with increasing annealing temperatures and showed best results in 1173K. The studied alloy exhibits a martensitic transformation from a L21 austenite to a martensite phase with a 7-layer (14M) and 5-layer (10M) modulated structure. The lattice constants of the L21 (a0) structure determined by TEM and X-ray analysis in this alloy were a0=0,4866. The TEM observation exhibit that the studied alloy in initial state has bigger accumulations of 10M and 14M structures as opposed from the annealed state.

Adaptive Elastic SMA Elements for Damping Applications

2013 ◽  
Author(s):  
Alexander Czechowicz ◽  
Peter Dültgen ◽  
Sven Langbein
Keyword(s):  
Boundary Conditions ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Electrical Resistance ◽  
Thermal Activation ◽  
Hysteretic Behavior ◽  
Damping Function ◽  
Actual Shape ◽  
Elastic Elements

Shape memory alloys (SMA) are smart materials, which have two technical usable effects: While pseudoplastic SMA have the ability to change into a previously imprinted actual shape through the means of thermal activation, pseudoelastic SMA show a reversible mechanical elongation up to 8% at constant temperature. The transformation between the two possible material phases (austenite and martensite) shows a hysteretic behavior. As a result of these properties, SMA can be used as elastic elements with intrinsic damping function. Additionally the electrical resistance changes remarkably during the material deformation. These effects are presented in the publication in combination with potential for applications in different branches at varying boundary conditions. The focus of the presented research is concentrated on the application of elastic elements with adaptive damping function. As a proof for the potential considerations, an application example sums up this presentation.

Modeling Smart Materials Using Hysteretic Recurrent Neural Networks

2009 ◽  
Author(s):  
Arun Veeramani ◽  
John Crews ◽  
Gregory D. Buckner
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Real Time Control ◽  
Ferromagnetic Shape Memory Alloys ◽  
Two Phase ◽  
Time Control ◽  
Novel Approach ◽  
Three Phase ◽  
Ferromagnetic Shape Memory

This paper describes a novel approach to modeling hysteresis using a Hysteretic Recurrent Neural Network (HRNN). The HRNN utilizes weighted recurrent neurons, each composed of conjoined sigmoid activation functions to capture the directional dependencies typical of hysteretic smart materials (piezoelectrics, ferromagnetic, shape memory alloys, etc.) Network weights are included on the output layer to facilitate training and provide statistical model information such as phase fraction probabilities. This paper demonstrates HRNN-based modeling of two- and three-phase transformations in hysteretic materials (shape memory alloys) with experimental validation. A two-phase network is constructed to model the displacement characteristics of a shape memory alloy (SMA) wire under constant stress. To capture the more general thermo-mechanical behavior of SMAs, a three-phase HRNN model (which accounts for detwinned Martensite, twinned Martensite, and Austensite phases) is developed and experimentally validated. The HRNN modeling approach described in this paper readily lends itself to other hysteretic materials and may be used for developing real-time control algorithms.

Shape memory alloy–actuated prestressed composites with application to morphing automotive fender skirts

2018 ◽  
Vol 30 (3) ◽  
pp. 479-494 ◽  
Author(s):  
Venkata Siva C Chillara ◽  
Leon M Headings ◽  
Ryohei Tsuruta ◽  
Eiji Itakura ◽  
Umesh Gandhi ◽  
...  
Keyword(s):  
Shape Memory Alloy ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Design Procedure ◽  
Building Blocks ◽  
Smart Composite ◽  
Thermally Induced ◽  
One Dimensional ◽  
Flat Shape

This work presents smart laminated composites that enable morphing vehicle structures. Morphing panels can be effective for drag reduction, for example, adaptive fender skirts. Mechanical prestress provides tailored curvature in composites without the drawbacks of thermally induced residual stress. When driven by smart materials such as shape memory alloys, mechanically-prestressed composites can serve as building blocks for morphing structures. An analytical energy-based model is presented to calculate the curved shape of a composite as a function of force applied by an embedded actuator. Shape transition is modeled by providing the actuation force as an input to a one-dimensional thermomechanical constitutive model of a shape memory alloy wire. A design procedure, based on the analytical model, is presented for morphing fender skirts comprising radially configured smart composite elements. A half-scale fender skirt for a compact passenger car is designed, fabricated, and tested. The demonstrator has a domed unactuated shape and morphs to a flat shape when actuated using shape memory alloys. Rapid actuation is demonstrated by coupling shape memory alloys with integrated quick-release latches; the latches reduce actuation time by 95%. The demonstrator is 62% lighter than an equivalent dome-shaped steel fender skirt.

Smart materials: Properties, design and mechatronic applications

2016 ◽  
Vol 233 (4) ◽  
pp. 734-762 ◽  
Author(s):  
A Spaggiari ◽  
D Castagnetti ◽  
N Golinelli ◽  
E Dragoni ◽  
G Scirè Mammano
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Piezoelectric Materials ◽  
Magnetorheological Fluids ◽  
Research Perspective ◽  
Active Devices ◽  
Complete Survey ◽  
Basic Equations ◽  
Commercial Applications

This paper describes the properties and the engineering applications of the smart materials, especially in the mechatronics field. Even though there are several smart materials which all are very interesting from the research perspective, we decide to focus the work on just three of them. The adopted criterion privileges the most promising technologies in terms of commercial applications available on the market, namely: magnetorheological fluids, shape memory alloys and piezoelectric materials. Many semi-active devices such as dampers or brakes or clutches, based on magnetorheological fluids are commercially available; in addition, we can trace several applications of piezo actuators and shape memory-based devices, especially in the field of micro actuations. The work describes the physics behind these three materials and it gives some basic equations to dimension a system based on one of these technologies. The work helps the designer in a first feasibility study for the applications of one of these smart materials inside an industrial context. Moreover, the paper shows a complete survey of the applications of magnetorheological fluids, piezoelectric devices and shape memory alloys that have hit the market, considering industrial, biomedical, civil and automotive field.

Phenomenological Models of Solid State Actuators for Network Based System Modelling

2014 ◽  
Author(s):  
Johannes Ziske ◽  
Fabian Ehle ◽  
Holger Neubert
Keyword(s):  
Solid State ◽  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Magnetic Flux Density ◽  
System Modelling ◽  
Magnetic Shape Memory ◽  
Magnetic Shape Memory Alloys ◽  
Design And Optimization ◽  
Highly Nonlinear

Smart materials, such as thermal or magnetic shape memory alloys, provide interesting characteristics for new solid state actuators. However, their behavior is highly nonlinear and determined by strong hysteresis effects. This complex behavior must be adequately considered in simulation models which can be applied for efficient actuator design and optimization. We present a new phenomenological lumped element model for magnetic shape memory alloys (MSM). The model takes into account the two-dimensional hysteresis of the magnetic field induced strain as a function of both the compressive stress and the magnetic flux density. It is implemented in Modelica. The model bases on measured limiting hysteresis surfaces which are material specific. An extended Tellinen hysteresis modeling approach is used to calculate inner hysteresis trajectories in between the limiting surfaces. The developed model provides sufficient accuracy with low computational effort compared to finite element models. Thus, it is well suited for system design and optimization based on network models. This is demonstrated with exemplary models of MSM based actuators. System models and simulation results are shown and evaluated for different topologies.

scholarly journals Development of Smart Textile Materials with Shape Memory Alloys for Application in Protective Clothing

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 689 ◽  
Author(s):  
Grażyna Bartkowiak ◽  
Anna Dąbrowska ◽  
Agnieszka Greszta
Keyword(s):  
Shape Memory Alloys ◽  
Shape Memory ◽  
Smart Materials ◽  
Protective Clothing ◽  
Radiant Heat ◽  
Textile Material ◽  
Material System ◽  
Molten Metals ◽  
Textile Materials ◽  
Smart Textile

The latest directions of research on the design of protective clothing concern the implementation of smart materials, in order to increase its protective performance. This paper presents results on the resistance to thermal factors such as flames, radiant heat, and molten metals, which were obtained for the developed smart textile material with shape memory alloys (SMAs). The laboratory tests performed indicated that the application of the designed SMA elements in the selected textile material system caused more than a twofold increase in the resistance to radiant heat (RHTI24 = 224 s) with an increase of thickness of 13 mm (sample located vertically with a load), while in the case of tests on the resistance to flames, it was equal to 41 mm (sample located vertically without a load) and in the case of tests on the resistance to molten metal, it was 17 mm (sample located horizontally).

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