The prediction model for additively manufacturing of NiTiHf high-temperature shape memory alloy

NiTi-based alloys are one of the most well-known alloys among shape memory alloys having a wide range of applications from biomedical to aerospace areas. Adding a third element to the binary alloys of NiTi changes the thermomechanical properties of the material remarkably. Two unique features of stability and high transformation temperature have turned NiTiHf as a suitable ternary shape memory alloys in various applications. Selective laser melting (SLM) as a layer-based fabrication method addresses the difficulties and limitations of conventional methods. Process parameters of SLM play a prominent role in the properties of the final parts so that by using the different sets of process parameters, different thermomechanical responses can be achieved. In this study, different sets of process parameters (PPs) including laser power, hatch space, and scanning speed were defined to fabricate the NiTiHf samples. Changing the PPs is a powerful tool for tailoring the thermomechanical response of the fabricated parts such as transformation temperature (TTs), density, and mechanical response. In this work, an artificial neural network (ANN) was developed to achieve a prediction tool for finding the effect of the PPs on the TTs and the size deviation of the printed parts

Additive Manufacturing of Binary Ni–Ti Shape Memory Alloys Using Electron Beam Powder Bed Fusion: Functional Reversibility Through Minor Alloy Modification and Carbide Formation

Shape memory alloys (SMAs), such as Ni–Ti, are promising candidates for actuation and damping applications. Although processing of Ni–Ti bulk materials is challenging, well-established processing routes (i.e. casting, forging, wire drawing, laser cutting) enabled application in several niche applications, e.g. in the medical sector. Additive manufacturing, also referred to as 4D-printing in this case, is known to be highly interesting for the fabrication of SMAs in order to produce near-net-shaped actuators and dampers. The present study investigated the impact of electron beam powder bed fusion (PBF-EB/M) on the functional properties of C-rich Ni50.9Ti49.1 alloy. The results revealed a significant loss of Ni during PBF-EB/M processing. Process microstructure property relationships are discussed in view of the applied master alloy and powder processing route, i.e. vacuum induction-melting inert gas atomization (VIGA). Relatively high amounts of TiC, being already present in the master alloy and powder feedstock, are finely dispersed in the matrix upon PBF-EB/M. This leads to a local change in the chemical composition (depletion of Ti) and a pronounced shift of the transformation temperatures. Despite the high TiC content, superelastic testing revealed a good shape recovery and, thus, a negligible degradation in both, the as-built and the heat-treated state

Titanium based cranial reconstruction using incremental sheet forming

In this paper, we report recent work in cranial plate manufacturing using incremental sheet forming (ISF) process. With a typical cranial shape, the ISF process was used to manufacture the titanium cranial shape by using different ISF tooling solutions with and without backing plates. Detailed evaluation of the ISF process including material deformation and thinning, geometric accuracy and surface finish was conducted by using a combination of experimental testing and Finite Element (FE) simulation. The results show that satisfactory cranial shape can be achieved with sufficient accuracy and surface finish by using a feature based tool path generation method and new ISF tooling design. The results also demonstrate that the ISF based cranial reconstruction has the potential to achieve considerable lead time reduction as compared to conventional methods for cranial plate manufacturing. This outcome indicates that there is a potential for the ISF process to achieve technological advances and economic benefits as well as improvement to quality of life

The development of TiNi-based negative poisson's ratio structure using selective laser melting

AbstractThere is a growing interest in using additive manufacturing to produce smart structures, which have the capability to respond to thermal and mechanical stimuli. In this report, Selective Laser Melting (SLM) is used to build a Negative Poisson's Ratio (NPR) TiNi-based Shape Memory Alloy (SMA) structure, creating a multi-functional structure that could be used as reusable armour. The study assesses the influence of SLM process parameters (laser power, scan speed, and track spacing) on the microstructural and structural integrity development in a Ti-rich TiNi alloy, as well as the impact of the post-process homogenisation treatment on the microstructure and phase transformations. The builds generally shows stress-induced cracks and residual porosity, which could be minimised through process optimisation. Nonetheless, the homogenisation treatment is essential to reduce the fraction of Ti2Ni intermetallics, which are known to disturb the B19′-chemistry, and hence the required phase transformation temperatures. The optimum process parameters are finally used to fabricate NPR structures, which were mechanically tested to validate the Poisson's ratio predictions. A higher ductility was observed in the structures that have undergone the homogenisation treatment

Shape Memory Alloy Actuators: Design, Fabrication and Experimental Evaluation

This chapters builds on the mathematical foundation developed in previous chapters to discuss design methodologies for several SMA actuators

Changes in Length during Free End Torsion of Nitinol Rods

In this experiment, the axial deformation caused during pure torsion in investigated. It was found that axial strains approaching 0.5% are generated when maximum torsional shear strain at the outer radius is 16%. The axial and torsional strains are fully recovered upon unloading. Further study of the micromechanical mechanisms at play is needed to advance the understanding of Nitinol behavior and allow for greater accuracy in modeling and actuator development. Clearly, “pure” torsion (and, conversely, “pure” tension) modes of deformation are impossible to achieve as the two modes are deeply coupled

Vibration Isolation for Parallel Hydraulic Hybrid Vehicles

In recent decades, several types of hybrid vehicles have been developed in order to improve the fuel economy and to reduce the pollution. Hybrid electric vehicles (HEV) have shown a significant improvement in fuel efficiency for small and medium-sized passenger vehicles and SUVs. HEV has several limitations when applied to heavy vehicles; one is that larger vehicles demand more power, which requires significantly larger battery capacities. As an alternative solution, hydraulic hybrid technology has been found effective for heavy duty vehicle because of its high power density. The mechanical batteries used in hydraulic hybrid vehicles (HHV) can be charged and discharged remarkably faster than chemical batteries. This feature is essential for heavy vehicle hybridization. One of the main problems that should be solved for the successful commercialization of HHV is the excessive noise and vibration involving with the hydraulic systems. This study focuses on using magnetorheological (MR) technology to reduce the noise and vibration transmissibility from the hydraulic system to the vehicle body. In order to study the noise and vibration of HHV, a hydraulic hybrid subsystem in parallel design is analyzed. This research shows that the MR elements play an important role in reducing the transmitted noise and vibration to the vehicle body. Additionally, locations and orientations of the isolation system also affect the efficiency of the noise and vibration mitigation. In simulations, a skyhook control algorithm is used to achieve the highest possible effectiveness of the MR isolation system

Development and testing of a hybrid SMA/MR passive clutch

The reduction of consumption and emissions is a key fac- tor in modern vehicle design. The overall vehicle efficiency is pursued in several ways, including the reduction of consumption of the auxiliary devices (e.g. water pumps, oil pumps, vacuum pumps etc.). In this paper, using two different smart materials (i.e. magnetorheological fluids and shape memory alloys) a de- vice aimed at disengaging the vacuum pump was developed. The conceived device is composed of a magnetorheological (MR) clutch excited by permanent magnets coaxially manufac- tured with a sliding spline sleeve moved by shape memory alloys (SMA) springs. In the MR clutch, the magnet can move under the effect of a passive pneumatic system. The magnetic field in the fluid varies with the magnets displacement and as a result two steady positions are possible: the engaged clutch (ON) and the disengaged clutch (OFF). The torque in the ON configuration is high enough to drive the vacuum pump during normal operating conditions, whereas the low torque value in the OFF condition guarantees power saving up to 150 W. In particular operating conditions (i.e. at low environmen- tal temperatures) the torque necessary to start the vacuum pump may exceed the maximum transmissible torque of the MR clutch. For this reason a sliding spline sleeve, actuated by two SMA springs which counteract the force of two traditional springs was developed. A dummy plain sliding sleeve with SMA and con- ventional springs was numerically developed and tested. The fairly good agreement of the results confirmed the feasibility of the combined SMA/MR device

Numerical study for prediction of optimum operational parameters in laser welding of NiTi alloy

Laser welding of NiTi alloy is a challenging process since it strongly affects the functionality of the material in the heat affected and fusion zones. In fact, the inherent thermal process can remarkably change the transformation temperature of NiTi alloy in the welding zone because of variation in the material composition. Accordingly, the laser parameters such as laser power and velocity effectively determine the quality of the welded component. The functional and mechanical behavior of the resulting welded NiTi parts can also be effectively improved by controlling laser parameters, and consequently, improve the weldability quality. The purpose of the present study was to establish a reliable finite element model to predict the thermal behavior induced by the laser welding process. To this end, a numerical model was employed to estimate the optimum laser parameters, which can reduce the heat affected and the fusion regions and thus result in a better weld. The results of the finite element model show good accuracy compared to the experimental results including the transient temperature and the dimension of the heat affected and fusion zones. In addition, an Artificial Neural Network (ANN)approach was applied, as a predictable tool, to perform a nonlinear mapping between inputs and outputs of the welding process in order to find the optimum laser parameters