The aim of this study is to investigate the effect of porosity on the tensile properties of cast discontinuous reinforced metal matrix composite (DRMMC) at room temperature. Aluminum silicon alloy reinforced with silicon carbide particles of %20 mm size are fabricated via conventional and modified stir casting methods. Specimens are cast at varied content of silicon carbide particles for porosity measurement and tensile test. The porosity content is measured using an image analyzer while the tensile test is conducted according to the ASTM B557 test method. A finite element method (FEM) based simulation is produced using Solidworks 2003 software to identify the effect of porosity formation at the strain areas caused by axial loading. From the evaluated findings, the porosity content increased with an increase in reinforcing silicon carbide particles. The deviation between conventional stir cast DRMMC and modified stir cast DRMMC is an average of 68%, which indicates a significant porosity reduction using the modified stir casting method. Porosity formation in conventional stir cast DRMMC is revealed to constrain the specimen to lower the tensile strength and yield stress. Based on the FEM analysis, the effect of this constraint is indicated by a high von Mises stress distribution at porosity-affected areas. The highest von Mises stress of 40.2 MPa is revealed in porosity-affected conventional stir cast DRMMC, whereas, with the minimal content of porosity, the highest von Mises stress produced in the modified stir cast DRMMC is 12.6 MPa.KEY WORDS: DRMMC, aluminum silicon alloy, silicon carbide particle, tensile properties, porosity content, finite element method analysis.

Selection of the most suitable sustainable material to fulfill the requirements of a product in a specific application is a complex task. Material selection problems are basically multi-criteria decision making problems as selection of the optimal material is based on the evaluation of conflicting criteria. Considering the limitations such as ranking reversal problem of the various multi-criteria decision making methods available in the literature, a combination of two recently developed techniques, i.e. the Goal Programming Model for Best Worst Method and Proximity Indexed Value method, is employed in the present study. This hybrid method was used for selection of the best possible material for manufacturing of a complex automobile part for which F1 race car as advanced automotive and its gearbox casing as sensitive part was used. Available alternative materials considered in the present study are alloys of aluminum, magnesium, titanium, and carbon fiber/epoxy laminate. Whereas, criteria affecting gearbox casing’s performance are tensile strength/density, cost, stiffness, damping capacity, thermal conductivity, and sustainable criteria, such as CO2 emission and recycling energy. Goal Programming Model for Best Worst Method is used to determine weights of the criteria and Proximity Indexed Value method is employed for final selection of material. Furthermore, ranking of alternatives was also supported by other multi-criteria decision making methods namely, range of value, weighted product model, simple additive weighting, the technique for order of preference by similarity to ideal solution, a combined compromise solution, and the multi-attributive border approximation area comparison. Membership degree method was also employed to obtain the final optimal ranking of alternative materials from individual results of applied multi-criteria decision making methods. Besides, sensitivity analysis is done to validate reliability of the results and to determine the most critical evaluation criterion. The result of this study revealed that carbon fiber/epoxy laminate is the best alternative material.

Provided it is applied with proper understanding of biomechanics, LCP is one of the best available options for management of challenging peri- and intra-articular fractures.

Efforts are continuously being made by researchers to improve fuel efficiency and to reduce CO2 emissions from the passenger cars. To achieve these goal, recent trend is to make the cars components light in weight for which manufacturing car roofs using natural fiber reinforced composites (NFCs) is one of the method. Several natural fibers (NFs)are available as alternative reinforcements for the fabrication of NFCs. Different NFs possess different properties and therefore, it is necessary to select the most appropriate natural fiber for fabrication of the composites which in turn will lead to the desired performance of the vehicle. Selection of the optimal natural fiber, amongst the several alternatives, is basically a multi criteria decision making (MCDM) problem as selection is based on the evaluation of several conflicting criteria. In this study, twelve alternative natural fibers (Flax,