Application of Aluminium Flakes in Fabrication of Open-Cell Aluminium Foams by Space Holder Method

In the current study, a first attempt at using aluminum flakes for the manufacture of open-cell aluminum foams with the space holder method is presented. The method involves powder mixing, compaction, leaching, and sintering processes. Saccharose particles were used as space holders, and multiple parameters were investigated to optimize the manufacturing processing route in order to produce high-quality open-cell aluminum foams with a simple, economic, and environmentally friendly method. The implementation of aluminum flakes leads to foams with 80 vol.% porosity, an excellent internal open-cell porous structure, low green compaction pressures, and does not require the use of binding additives

The Design Process of an Optimized Road Racing Bicycle Frame

This paper recommends an alternative designing process for a superior road racing bicycle frame manufactured from composite materials that is much faster than typically used design processes. The main design goal is for the rider to be faster under the same riding conditions and with the same effort made. This performance gain is the result of a combined structural and aerodynamic optimization process used during the design process along with the selection of the materials. As the needs of the rider are the focus of this design proposal, the optimization can be carried out only after they are understood. The main difference in this approach compared to the typically used methodology is that, instead of analyzing the frame as a whole from the beginning of the design process and the CFD and CAE iterations, we examine each candidate part of the frame separately. After evaluating the parts’ performances, we select those that performed better to create a single frame. This final frame design is used to choose the appropriate layup that would meet the performance needs of the riders and the necessary safety regulations. The benefit of this approach is that the design time is reduced, allowing the product to reach the market faster. Furthermore, it is more convenient and easier to make any modifications required by marketing or regulations

Modeling of Ti6Al4V Alloy Orthogonal Cutting with Smooth Particle Hydrodynamics: A Parametric Analysis on Formulation and Particle Density

Computational modeling is a widely used method for simulation and analysis of machining processes. Smooth particle hydrodynamics (SPH) is a comparatively recently developed method that is used for the simulation of processes where high strains and fragmentation occur. The purpose of this work is the application of the SPH method for the prediction of cutting forces and chip formation mechanism in orthogonal cutting of Ti6Al4V alloy. In addition, it is examined how the final results of the simulation are influenced by the choice of the particular formulation of the SPH method, as well as by the density of the particles

The Design Process of an Optimized Road Racing Bicycle Frame

This paper recommends an alternative designing process for a superior road racing bicycle frame manufactured from composite materials that is much faster than typically used design processes. The main design goal is for the rider to be faster under the same riding conditions and with the same effort made. This performance gain is the result of a combined structural and aerodynamic optimization process used during the design process along with the selection of the materials. As the needs of the rider are the focus of this design proposal, the optimization can be carried out only after they are understood. The main difference in this approach compared to the typically used methodology is that, instead of analyzing the frame as a whole from the beginning of the design process and the CFD and CAE iterations, we examine each candidate part of the frame separately. After evaluating the parts’ performances, we select those that performed better to create a single frame. This final frame design is used to choose the appropriate layup that would meet the performance needs of the riders and the necessary safety regulations. The benefit of this approach is that the design time is reduced, allowing the product to reach the market faster. Furthermore, it is more convenient and easier to make any modifications required by marketing or regulations

Precision CNC Machining of Femoral Component of Knee Implant: A Case Study

The design and manufacturing of medical implants constitutes an active and highly important field of research, both from a medical and an engineering point of view. From an engineering aspect, the machining of implants is undoubtedly challenging due to the complex shape of the implants and the associated restrictive geometrical and dimensional requirements. Furthermore, it is crucial to ensure that the surface integrity of the implant is not severely affected, in order for the implant to be durable and wear resistant. In the present work, the methodology of designing and machining the femoral component of total knee replacement using a 3-axis Computer Numerical Control (CNC) machine is presented, and then, the results of the machining process, as well as the evaluation of implant surface quality are discussed in detail. At first, a preliminary design of the components of the knee implant is performed and the planning for the production of the femoral component is implemented in Computed Aided Manufacturing (CAM) software. Then, three femoral components are machined under different process conditions and the surface quality is evaluated in terms of surface roughness. Analysis of the results indicated the appropriate process conditions for each part of the implant surface and led to the determination of optimum machining strategy for the finishing stage

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM FOR END MILLING

Soft computing is commonly used as a modelling method in various technological areas. Methods such as Artificial Neural Networks and Fuzzy Logic have found application in manufacturing technology as well. NeuroFuzzy systems, aimed to combine the benefits of both the aforementioned Artificial Intelligence methods, are a subject of research lately as have proven to be superior compared to other methods. In this paper an adaptive neuro-fuzzy inference system for the prediction of surface roughness in end milling is presented. Spindle speed, feed rate, depth of cut and vibrations were used as independent input variables, while roughness parameter Ra as dependent output variable. Several variations are tested and the results of the optimum system are presented. Final results indicate that the proposed model can accurately predict surface roughness, even for input that was not used in training

Crashworthiness Performance of Aluminium, GFRP and Hybrid Aluminium/GFRP Circular Tubes under Quasi-Static and Dynamic Axial Loading Conditions: A Comparative Experimental Study

Offshore structures are exposed to risks of vessel collisions and impacts from dropped objects. Tubular members are extensively used in offshore construction, and thus, there is scope to investigate their crashworthiness behaviour. Aluminium, glass fibre reinforced polymer (GFRP) and hybrid aluminium/GFRP circular tube specimens were fabricated and then tested under quasi-static and dynamic axial loading conditions. Two hybrid configurations were examined: external and internal layers from respectively aluminium and GFRP, and vice versa. The material impregnated with epoxy resin woven glass fabric was allowed to cure attached to the aluminium layer to ensure interlayer bonding. The quasi-static and dynamic tests were conducted using respectively a universal testing machine at a prescribed crosshead speed of 10 mm/min, and a 78 kg drop hammer released from 2.5 m. The non-hybrid configurations (aluminium and GFRP specimens) outperformed their hybrid counterparts in terms of crashworthiness characteristics

Engineering Solid Mechanics The influence of cutting conditions and cutting tool geometry on the atomistic modeling of precision cutting

In this paper a molecular dynamics simulation of nano-metric cutting of copper with a diamond tool is presented. MD simulations require the determination of the interaction of the involved atoms through a function of potential for the materials involved in the analysis and the accurate topography of the studied area, leading to high demand of computational time. The models presented are taking into account the cubic lattice of copper, test two different potential functions and at the same time control the computational cost by introducing small models at realistic cutting conditions. This is realized by a novel code developed and allows focusing on the influence of several processes and modeling parameters on the outcome of the simulations. Models with and without thermostat atoms are investigated and the influence of cutting conditions and cutting tool geometry on chip morphology, cutting forces and cutting temperatures are studied