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

Abstract

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.

Trends, Problems, and Solutions from Point Cloud via Non-Uniform Rational Basis Spline to Building Information Modelling: Bibliometric and Systematic Study

“…Twenty-six authors are gathered on reverse engineering with three leading articles' authors, Sansoni and Docchio (2004), Besl (1990), and [35][36][37]. Clusters #4-#6 have the same number of authors-twenty-five-as a critical literature review, geometry parametrisation, and heritage place-data-driven conservation action with major citing articles by Barazzetti (2016), Safari et al (2013), and Bolognesi and Fiorillo (2023) [38][39][40]. The other groups, #7-#13, are working on the rectangular domain, 3D surface, a repair method of a point cloud with a big hole, direct boolean intersection, as-built modelling, nature-inspired optimisation approaches, and improvement in the 3D digitisation processa reverse engineering process again [37,[39][40][41][42][43][44].…”

Aerodynamic Design Optimization of a Morphing Leading Edge and Trailing Edge Airfoil–Application on the UAS-S45

“…These algorithms are discussed in the following sections. Many optimization techniques based on bioinspired processes and Surrogate-Assisted natural methods have been formulated, and mathematical and statistical analysis of these algorithms has been performed [49][50][51][52]. The comparative performance study based on convergence trends was performed with different geometry parameterization techniques.…”

Advanced modeling and control of 5 MW wind turbine using global optimization algorithms

“…The Imperialist Competitive Algorithm (ICA) as a newly established GO algorithm (Atashpaz-Gargari and Lucas, 2007) and the Differential Evolution (DE) (Storn and Price, 1997) are used in order to cope with the controller design of wind turbines. These algorithms are widely used in system structure design (Safari et al, 2013), controller structure design (Behera et al, 2013), controller gain tuning and performance optimization (Saad et al, 2012), advanced controller (Shuai and Wei, 2014) and technology design (Goudos et al, 2010), and in many other applications and their ability to deal with nonlinear real-world complex problems with huge number of parameters are confirmed.…”