Analysis of the Effects of 3DP Parameters on Part Feature Dimensional Accuracy

3D printing (3DP) is a widely investigated scaffold manufacturing process for Tissue Engineering (TE). Useful scaffold geometries should have high porosity (60-80%) with small (100-500 μm) interconnected pores. Therefore dimensional accuracy on the micron level is one of the crucial parameters of the bone scaffolds. Previously it was shown that the behavior of scaffold geometries can be well simulated with Finite Element Modeling (FEM) however the prediction of actual strength and stiffness values are dependent on dimensional accuracy. This accuracy is in turn dependent on several parameters including particle size and shape, powderbinder interaction, and machine setup. In this work different scaffold strut sizes (0.3 - 0.5 mm) have been fabricated using two different plaster powders (zp102 and zp130) with variations in shell saturation levels, part print position, and part print orientation. The parameters for each powder were analyzed using a full 35 factorial experimental design. It was found that the part size and orientation had a significant effect on the dimensional accuracy while the influence of the shell saturation and position was relatively small. The results allow for better dimensional specification for scaffold geometry fabrication by defining the process parameters in 3DP that may be used further in scaffold accuracy optimization.Mechanical Engineerin

Injection tests and effect on microstructure and properties of aluminium 7075 direct thermal method feedstock billets

The success of semi-solid metal forming is dependent on a globular solid grain formation within a liquid phase. This paper presents experimental works concerning semi-solid metal processing of aluminium 7075 feedstock billets which were produced by direct thermal method. The flowability of feedstock billets was evaluated by an injection test processing unit. The feedstock billets were heated to a temperature of 620 °C by using a box furnace before transferred into a forming die. The formed feedstock billet was removed from the forming die after it was cooled to ambient temperature. Several analyses were conducted on the formed feedstock billets including dimensional measurement and microstructure analysis. The results show that the feedstock billets which contained the highest amount of free secondary phase were most successfully formed. Microstructure analysis results also revealed the formation of more globular and larger α–Al solid grains in the same feedstock billets. In this experimental work, the feedstock billets with higher amount of secondary (liquid) phase had a significant effect on formability. It is concluded that in order to achieve successful formability of the direct thermal method feedstock billets, the billets need to a have higher secondary phase content. Thus, important preparation methods of feedstock billets were characterised in order to allow for SSM processing

Atomic diffusion in laser surface modified AISI H13 steel

This paper presents a laser surface modification process of AISI H13 steel using 0.09 and 0.4 mm of laser spot sizes with an aim to increase surface hardness and investigate elements diffusion in laser modified surface. A Rofin DC-015 diffusion-cooled CO2 slab laser was used to process AISI H13 steel samples. Samples of 10 mm diameter were sectioned to 100 mm length in order to process a predefined circumferential area. The parameters selected for examination were laser peak power, pulse repetition frequency (PRF), and overlap percentage. The hardness properties were tested at 981 mN force. Metallographic study and energy dispersive X-ray spectroscopy (EDXS) were performed to observe presence of elements and their distribution in the sample surface. Maximum hardness achieved in the modified surface was 1017 HV0.1. Change of elements composition in the modified layer region was detected in the laser modified samples. Diffusion possibly occurred for C, Cr, Cu, Ni, and S elements. The potential found for increase in surface hardness represents an important method to sustain tooling life. The EDXS findings signify understanding of processing parameters effect on the modified surface composition

Prediction of Mechanical Properties of Graphene Oxide Reinforced Aluminum Composites

Estimating the effect of graphene oxide (GO) reinforcement on overall properties of aluminum (Al) matrix composites experimentally is time-consuming and involves high manufacturing costs and sophisticated characterizations. An attempt was made in this paper to predict the mechanical properties of GO/Al composites by using a micromechanical finite element approach. The materials used for prediction included monolayer and multilayer GO layers distributed uniformly on the spherical Al matrix particles. The estimation was done by assuming that a representative volumetric element (RVE) represents the composite structure, and reinforcement and matrix were modeled as continuum. The load transfer between the GO reinforcement and Al was modeled using joint elements that connect the two materials. The numerical results from the finite element model were compared with Voigt model and experimental results from the GO/Al composites produced at optimized process parameters. A good agreement of numerical results with the theoretical models was noted. The load-bearing capacity of the Al matrix increased with the addition of GO layers, however, Young’s modulus of the GO/Al composites decreased with an increase in the number of layers from monolayer to 5 layers. The numerical results presented in this paper have demonstrated the applicability of the current approach for predicting the overall properties of composites

An Evolutionary Optimization Approach to Risk Parity Portfolio Selection

In this paper we present an evolutionary optimization approach to solve the risk parity portfolio selection problem. While there exist convex optimization approaches to solve this problem when long-only portfolios are considered, the optimization problem becomes non-trivial in the long-short case. To solve this problem, we propose a genetic algorithm as well as a local search heuristic. This algorithmic framework is able to compute solutions successfully. Numerical results using real-world data substantiate the practicability of the approach presented in this paper

Thermal fatigue properties of laser treated steels

This paper presents the thermal fatigue resistance of laser treated steels. The C40 and AISI H13 steels were machined into a geometry which allowed thermal gradients on the inner and outer surface during testing. A CO2 laser system was used with a focused spot size of 0.09 mm on the sample surface. The laser peak power and pulse repetition frequency (PRF) range were set to 760 and 1515 W, and 2900 to 3500 Hz respectively. The thermal fatigue machine used consists of Nabertherm model cylindrical high temperature furnace with digital control panel, controlled temperature quenching system, and pneumatics control sample movement mechanism. The thermal fatigue test involved immersion of samples into molten aluminium, and quenched in ionised water emulsion at 17°C temperature. The quenching system equipped with thermocouple to control the water temperature. Testing was done at a total of 1,750 number of cycles. Internal surface cooling was controlled by water inlet and outlet tubes. Samples were cleaned using NaOH solution after thermal fatigue testing to remove oxides on the surface. The solution temperature and magnetic stirrer speed were set to 100°C and 4.5 rpm respectively. Samples were characterised using scanning electron microscope (SEM), energy discharge x-ray spectroscopy (EDXS) and 2D stylus profilometer. Presence of different phases on the sample surface were analysed from back-scattered detector micrographs. Heat checks were observed on laser glazed surface at several regions. Carbides and oxides elements were detected on the sample surface after the thermal fatigue test. The relationship between surface roughness of laser treated surface and thermal fatigue behaviour was investigated

Effect of micro-channel geometry on fluid flow and mixing

Understanding the flow fields at the micro-scale is key to developing methods of successfully mixing fluids for micro-scale applications. This paper investigates flow characteristics and mixing efficiency of three different geometries in micro-channels. The geometries of these channels were rectangular with a dimension of; 300 lm wide, 100 lm deep and 50 mm long. In first channel there was no obstacle and in the second channel there were rectangular blocks of dimension 300 lm long and 150 lmwide are placed in the flow fields with every 300 lm distance attaching along the channel wall. In the third geometry, there were 100 lm wide fins with 150_ angle which were placed at a distance of 500 lm apart from each other attached with the wall along the 50 mm channel. Fluent software of Computational Fluid Dynamics (CFD) was used to investigate the flow characteristics within these microfluidic model for three different geometries. A species 2D model was created for three geometries and simulations were run in order to investigate the mixing behavior of two different fluid with viscosity of water (1 mPa s). Models were only built to investigate the effect of geometry, therefore only one fluid with similar viscosity was used in these models. Velocity vector plots were used in the CFD analysis to visualise the fluid flow path. Mass fractions of fluid were used to analyse the mixing efficiency. Two different colours for water were used to simulate the effect of two different fluids. The results showed that the mixing behaviour strongly depended on the channel geometry when other parameters such as fluid inlet velocity, viscosity and pressure of fluids were kept constant. In two geometries lateral pressure and swirling vortexes were developed which provided better mixing results. Creation of swirling vortexes increased diffusion gradients which enhanced diffusive mixing

Evolutionary Behavior Tree Approaches for Navigating Platform Games

Computer games are highly dynamic environments, where players are faced with a multitude of potentially unseen scenarios. In this article, AI controllers are applied to the Mario AI Benchmark platform, by using the Grammatical Evolution system to evolve Behavior Tree structures. These controllers are either evolved to both deal with navigation and reactiveness to elements of the game, or used in conjunction with a dynamic A* approach. The results obtained highlight the applicability of Behavior Trees as representations for evolutionary computation, and their flexibility for incorporation of diverse algorithms to deal with specific aspects of bot control in game environments

Parametric study for graphene reinforced aluminum matrix composites production using Box Behnken design

The production of graphene reinforced aluminum matrix composite through powder metallurgical route requires optimization of process parameters to obtain better performance characteristics. One of the advanced method available for statistical analysis of parameters is Response Surface Methodology (RSM). The statistical analysis was carried out with three parameters, weight percentage of graphene reinforcement Wg (0.05%, 0.1% and 0.2%), stirring time ST(1h, 2h and 3h) and compaction pressure Pc(16T, 17T and 19T) while sintering temperature T kept constant. The performance of the Box Behnken design was analyzed and optimized using Design Expert software for the effective production of composites. From the results obtained from the analysis, the best set of parameters were considered for the future production of composites

Graphene and derivatives – Synthesis techniques, properties and their energy applications

2D nanomaterials with exceptional electrical, mechanical and thermal properties are promising reinforcing materials for fabricating high-performance composite materials. Rapid developments in nanotechnology in recent years have facilitated the development of advanced materials for functional devices. In particular, this review is focussed on the application of graphene nanoparticle-based composites (GNP's) and graphene derivatives in the fields of energy storage and conversion devices. This review focuses on these recent developments including the synthesis of graphene-based materials and its derivative, as well as the related achieved electrical, mechanical and thermal properties