A hybrid ant colony–particle swarm optimization method (ACOPSO) for aerospace propulsion systems

Abstract

Purpose The purpose of this paper is to introduce a hybrid, metaheuristic, multimodal and multi-objective optimization tool that is needed for aerospace propulsion engineering problems. Design/methodology/approach Multi-objective hybrid optimization code is integrated with various benchmark and test functions that are selected suitable to the difficulty level of the aero propulsion performance problems. Findings Ant colony and particle swarm optimization (ACOPSO) has performed satisfactorily with benchmark problems. Research limitations/implications ACOPSO is able to solve multi-objective and multimodal problems. Because every optimization problem has specific features, it is necessary to search their general behavior using other algorithms. Practical implications In addition to the optimization solving, ACOPSO enables an alternative methodology for turbine engine performance calculations by using generic components maps. The user is flexible for searching various effects of component designs along with the compressor and turbine maps. Originality/value A hybrid optimization code that has not been used before is introduced. It is targeted use is propulsion systems optimization and design such as Turboshaft or turbofan by preparing the necessary engine functions. A number of input parameters and objective functions can be modified accordingly.

Characterization modeling of wake vortex circulation decay under reasonable worst case conditions with cuckoo search algorithm

“…For this reason, as in other fields, the methods specified in aviation are often preferred. [20][21][22][23][24][25][26][27][28][29][30] In this study, the modeling of dimensionless decay curves, which were developed using three experimental LIDAR datasets in the RECAT-EU project and is a useful tool to characterize the wake vortex circulation decay under RWC conditions, was carried out using cuckoo search algorithm (CSA). The decay curves used in the modeling are the median (P50), 10th (P10), and 90th (P90) percentile decay curves of the RWC tracks, which constitute the top 2% longest lasting wakes.…”