Amir Safari

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

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.

Role of Gas-Fuelled Solutions in Support of Future Sustainable Energy World; Part I: Stimuluses, Enablers, and Barriers

Tackling the challenges of energy poverty and changing living conditions in line with the growing population, and doing so in a sustainable manner, is recognised as being of utmost importance for the world today. The main goal of this study is to illuminate the fact that providing energy to an ever-growing population of the globe during a period of transition, and so doing in a responsible manner, requires a sustainable energy mix of fossils and renewables. Given the fact that the energy solution of tomorrow has to combine various fuels and technologies, different solutions will be needed for different regions, as determined in line with various factors, including the availability of resources and specific needs. Consequently, the role of gas-fuelled solutions as part of the transition towards future sustainable energy world needs to be illuminated from a technical, economic, social, political and geographical point of view. The discussions and conclusions presented in the chapter support the expectation of the increased use of natural gas as a part of the global transition towards a low-carbon energy society. From a carbon-neutral energy perspective, however, the use of biogas and renewable-based hydrogen as replacement for natural gas, in the long-term perspective, could be expected. In this way, natural gas will be an important complement to renewable energy during the transition period. Infrastructure and energy conversion technologies developed for natural gas need to be designed in such a way so as to be able to cope with the transition towards biogas and renewable supported hydrogen. Moreover, small-scale combined heat- and electricity-production and distributed generation could be a potential gas-fuelled solution, providing an improved fuel utilisation factor and, as a result, reduced emissions of greenhouse gases. Taking into account the challenges of the increasing demand for reliable and affordable energy, as well as global climate change, it is concluded that common understanding needs to be established amongst all the players, including society, industries, strategists, decision-makers, politicians and environmentalists, so as to reach a new level of commitment and partnership.

Role of Gas-Fuelled Solutions in Support of Future Sustainable Energy World: Part II: Case Studies

Following Part I of this study, this chapter highlights each region in the world as having its own solution and approach to considering natural gas as a fuel of choice for smooth transition towards a sustainable energy world. Although energy sustainability is recognised as a global challenge, many of the issues inherent in this domain are site-specific. Therefore, it is necessary to identify suitable local solutions whilst taking into account resources, infrastructure, economic aspects, as well as the local/national energy policies. This means that there is not one solution that fits all cases; therefore, tailor-made solutions devised in mind of different circumstances need to be considered. The case study presented in this chapter compares different countries, i.e. industrial vs developing and those with national resources vs import dependent countries, with the aim of illuminating the fact that final choices and approaches that are seen to have a major impact on global warming due to CO2 emissions from fossil fuels might look very different. In this part of the study, focus is centred on the utilisation of natural gas as the ideal partner complementary to renewables in a future sustainable energy mix, in support of different regions’ policies. In this way, security of supply as a foundation for industrial development and the continued functioning of a modern society have to be maintained independent of the energy mix applied in each country. Different scenarios are presented and analysed in the case study, with attention paid towards discussing and illuminating the possible ways in which natural gas may be seen as a transition fuel from a global perspective so as to pave the way for the realisation of carbon-neutral or carbon-free energy solutions for the future. Since the examples presented cover four different categories of country (India, Iran, Norway and UK), combined characteristics may be recognised as representative for a large number of countries, thus making the generality of the conclusions rather strong.

Decomposition of High-Dimensional Shape Optimization Problems Through Quantifying Design Variable Correlation

This paper proposes a novel strategy for the shape optimization procedures using a recently developed metamodel-based decomposition algorithm for High-dimensional, Expensive and Black-box (HEB) design problems. A metamodel named High Dimensional Model Representation (HDMR) is used for decomposition of design variables in a complex aerodynamic profile optimization process as a HEB design problem. The approach uncovers and quantifies design variable correlations. Weak correlations are neglected and strong ones are kept for grouping. In this way, the vast search space is decomposed to small ones, and the large-scale CFD simulation based optimization is replaced by smaller-scale sub-problems. Though a typical gas turbine compressor airfoil shape has been selected as the case study in this paper, the methodology is introduced as a general procedure for shape optimization problems. The obtained results from the decomposition also show good agreement with the aerodynamics of such turbomachinery airfoils and found promising.Copyright

Optimum NURBS Curve Fitting for Geometry Parameterization of Gas Turbine Blades’ Sections: Part I — Evolutionary Optimization Techniques

This paper presents two evolutionary optimization methods: Genetic Algorithm and Differential Evolution, aimed at optimizing the location of a set of NURBS control points that are used to calculate the NURBS points for leading edge, trailing edge, suction side and pressure side of an airfoil shape. The approach is illustrated on point cloud of several 2D sections of a typical gas turbine compressor blade, so that the results can be used for both reverse engineering purposes and geometry parameterization in airfoil aerodynamic shape optimization process. The optimization algorithms in this research are based on minimization of an analytical error function related to the distance between the fitted curve and original data points. Finally, the obtained results from these two techniques are compared with each other to distinguish the advantages and disadvantages of each method for such curve fitting problems.Copyright

Optimum NURBS Curve Fitting for Geometry Parameterization of Gas Turbine Blades’ Sections: Part II — Swarm Intelligence Techniques

In part I of this study an optimum NURBS curve fitting by two evolutionary optimization techniques was successfully designed. These methods were implemented to optimize the location of a set of NURBS control points for the measured point cloud of four segments of a gas turbine compressor airfoil shape. The purpose of the optimization was to demonstrate the good ability of evolutionary techniques, in particular Genetic Algorithms, in optimizing such curve fitting problems. The objective of part II is to examine two alternative solutions for NURBS curve fitting of the same airfoil point cloud with swarm intelligence optimization technique. Indeed, the same work has been done by applying two basically different optimization approaches that is Particle Swarm Optimization and Invasive Weed Optimization. Results allow seeing a number of advantages as well as some disadvantages in this optimum curve fitting approach in comparison to the previous techniques applied by authors.Copyright