Hirpa G. Lemu

Study of capabilities and limitations of 3D printing technology

3D printing is one of the developments in rapid prototyping technology. The inception and development of the technology has highly assisted the product development phase of product design and manufacturing. The technology is particularly important in educating product design and 3D modeling because it helps students to visualize their design idea, to enhance their creative design process and enables them to touch and feel the result of their innovative work. The availability of many 3D printers on the market has created a certain level of challenge for the user. Among others, complexity of part geometry, material type, compatibility with 3D CAD models and other technical aspects still need in-depth study. This paper presents results of the experimental work on the capabilities and limitations of the Z510 3D printer from Z-corporation. Several parameters such as dimensional and geometrical accuracy, surface quality and strength as a function of model size, orientation and file exchange format are closely studied.

3D Printing for Rapid Manufacturing: study of dimensional and geometrical accuracy

3D printing (3DP) is one of the innovative developments in rapid prototyping (RP) technology. The goal of the initial inception and progress of the technology was to assist the product development phase of product design and manufacturing. The technology has played an important role in educating product design and 3D modeling because it helps students/designer to visualize their design idea, to enhance their creative design process and enables them to touch and feel the result of their innovative work. This paper presents the results of the study done on the in-built potentials and limitations of 3DP technology when used for rapid manufacturing purposes.

A Comparative Analysis of Nature-Inspired Optimization Approaches to 2D Geometric Modelling for Turbomachinery Applications

A vast variety of population-based optimization techniques have been formulated in recent years for use in different engineering applications, most of which are inspired by natural processes taking place in our environment. However, the mathematical and statistical analysis of these algorithms is still lacking. This paper addresses a comparative performance analysis on some of the most important nature-inspired optimization algorithms with a different basis for the complex high-dimensional curve/surface fitting problems. As a case study, the point cloud of an in-hand gas turbine compressor blade measured by touch trigger probes is optimally fitted using B-spline curves. In order to determine the optimum number/location of a set of Bezier/NURBS control points for all segments of the airfoil profiles, five dissimilar population-based evolutionary and swarm optimization techniques are employed. To comprehensively peruse and to fairly compare the obtained results, parametric and nonparametric statistical evaluations as the mathematical study are presented before designing an experiment. Results illuminate a number of advantages/disadvantages of each optimization method for such complex geometries’ parameterization from several different points of view. In terms of application, the final appropriate parametric representation of geometries is an essential, significant component of aerodynamic profile optimization processes as well as reverse engineering purposes.

A Novel Combination of Adaptive Tools for Turbomachinery Airfoil Shape Optimization Using a Real-Coded Genetic Algorithm

An automated shape optimization methodology for a typical heavy-duty gas turbine (GT) compressor rotor blade section is presented in this paper. The approach combines a Non-Uniform Rational B-Spline (NURBS) driven parametric geometry description, a two-dimensional flow analysis, and a Genetic Algorithm (GA)-based optimization route. The objective is minimizing the total pressure losses for design condition as well as maximizing the airfoils operating range which is an assessment of the off-design behavior. To achieve the goal, design optimization process is carried out by coupling an established MATLAB code for the Differential Evolution (DE)-based optimum parameterized curve fitting of the measured point cloud of the airfoils’ shape, a blade-to-blade flow analysis in COMSOL Multiphysics, and a developed real-coded GA in MATLAB script. Using the combination of these adaptive tools and methods, the first results are considerably promising in terms of computation time, ability to extend the methodology for three-dimensional and multidisciplinary approach, and last but not least airfoil shape performance enhancement from efficiency and pressure rise point of view.Copyright

Study of Frictional Properties of AMS Nickel-Chromium Alloys

The research reported in this article has considered the frictional characteristics of three kinds of AMS nickel-chromium alloys that are commonly used in aerospace industry. These are alloys with additions of titanium and aluminum AMS5542, nickel-chromium alloy AMS5596, and non-magnetic, corrosion and oxidation resistant, nickel-chromium alloy AMS5599. To determine the friction coefficient two tribological tests, a strip drawing test and a pin-on-disc tribometer have been conducted. Three different friction conditions were considered, dry friction, lubrication conditions using two grades of oils used in sheet metal forming of AMS alloys. The experimental results have ascertained several relationships showing the effect of sheet metal surface roughness, lubricant conditions and sheet orientation on the value of friction coefficient in sheet metal forming processes. Different levels of normal pressure were also used in friction tests. The results further showed that the surface topography and sample orientation in the rolling direction of the sheet are significant factors that influence the friction coefficient. It has been observed that the tested AMS alloys, selected from aerospace industry applications, exhibit anisotropic resistance to the friction corresponding to the measured orientation in relation to the rolling direction of the sheet.

Stress and Displacement Analysis of a HAWT Under Time-Variable Wind

The article presents a study conducted to analyze the vulnerable zones of horizontal axis wind turbine (HAWT) wings, the nacelle, and the tower during the rotor revolution. The objective of the study is to establish relations between the extreme values of the investigated variables (wind velocity and pressure, von Mises stresses, displacements, etc. vs. angle of rotation or position of the rotor) in order to explore the vulnerable zone. The numerical model, as a computer-aided design (CAD) model geometry of the turbine assembly, was developed using freeform outline of the blade profile according to a previously designed twisted and tapered blade shape and a simplified outline of the nacelle. The tower was assumed to be made of a pipe and unites pipes of increasing diameter; hence its outline is a conic form. All solid bodies, i.e., blades of fiber glass composite and the tower and nacelle of alloy steel, are meshed using parabolic tetrahedral finite elements. The article demonstrates the used simulation technique and the results that are visualized using diverse graphical tools. Though it is hard to precisely point out the location of the vulnerable zone, the results indicate that the highest stresses appear along the trailing edge when the blade is in vertical direction.Copyright

Study of Horizontal Axis Wind Turbine Blade in Virtual Wind Tunnel Simulator

The article presents a 3D model analysis of a single blade for a horizontal axis wind turbine (HAWT). The analysis focuses on calculation of the wind pressure on the blade under different wind velocities and directions within the range of −45 deg. to +45 deg. using virtual wind tunnel simulators based on the Computational Fluid Dynamics (CFD) approach. Furthermore, the study deals with a linear modal analysis of the loaded blade subjected to aerodynamic loads, dead weight and angular velocity of the rotor. By modeling the blade as a thick shell, composite shell and through solid spatial finite elements (FE), a comparison of the final results regarding the modal characteristics of the blade is discussed. The objective of this comparison is to develop better understanding of the blade performance and find the best ways for computer analysis regarding the complexity of the model, computer resources and accuracy of the results. The authors consider this analysis and the corresponding conclusions as a crucial perquisite for further geometrical optimization of the flap-wise rigidity of the blade aiming reduction of the strain energy and the noise. The results of the study indicate that different solutions are possible to implement in achieving almost equal flap-wise rigidity along the blade.Copyright

A case study on topology optimized design for additive manufacturing

Topology optimization is an optimization method that employs mathematical tools to optimize material distribution in a part to be designed. Earlier developments of topology optimization considered conventional manufacturing techniques that have limitations in producing complex geometries. This has hindered the topology optimization efforts not to fully be realized. With the emergence of additive manufacturing (AM) technologies, the technology that builds a part layer upon a layer directly from three dimensional (3D) model data of the part, however, producing complex shape geometry is no longer an issue. Realization of topology optimization through AM provides full design freedom for the design engineers. The article focuses on topologically optimized design approach for additive manufacturing with a case study on lightweight design of jet engine bracket. The study result shows that topology optimization is a powerful design technique to reduce the weight of a product while maintaining the design requirements if additive manufacturing is considered.

Effect of Activation Function and Post Synaptic Potential on Response of Artificial Neural Network to Predict Frictional Resistance of Aluminium Alloy Sheets

Many technological factors affect the friction phenomenon in sheet metal forming process. As a result, the determination of the analytical model describing the frictional resistance is very difficult. In this paper, a friction model was built based on the experimental results of strip drawing tests. Friction tests were carried out in order to determine the effect of surface and tool roughness parameters, the pressure force and mechanical parameters of the sheets on the value of coefficient of friction. The strip drawing friction tests were conducted on aluminium alloy sheets: AA5251-H14, AA5754-H14, AA5754-H18, AA5754-H24. The surface topography of the sheets was measured using Taylor Hobson Surtronic 3+ instrument. In order to describe complex relations between friction and factors influencing tribological conditions of sheet metal forming, the multilayer artificial network was built in Statistica Neural Network program. The effect of activation function and post synaptic potential function on the sensitivity of multilayer neural network to predict the friction coefficient value is presented. It has been found that the difference in the prediction of error of neural network for different approaches can reach 400%. So, the proper selection of activation and post synaptic potential functions is crucial in neural network modelling.

Surrogate-assisted Self-accelerated Particle Swarm Optimization

Surrogate-assisted self-accelerated particle swarm optimization (SASA-PSO) is a major modification of an original PSO which uses all previously evaluated particles aiming to increase the computational efficiency. A newly in-house developed metamodeling approach named high dimensional model representation with principal component analysis (PCAHDMR), which was specifically established for so called high-dimensional, expensive, blackbox (HEB) problems, is used to approximate a function using all particles calculated during the optimization process. Then, based on the minimum of the constructed metamodel, a term called “metamodeling acceleration” is added to the velocity update formula in the original PSO algorithm. The proposed optimization algorithm performance is investigated using several benchmark problems with different number of variables and the results are also compared with original PSO results. Preliminary results show a considerable performance improvement in terms of number of function evaluations as well as achieved global optimum specifically for high-dimensional problems.