Sedelnikov, A.; Kurkin, E.; Quijada-Pioquinto, J.G.; Lukyanov, O.; Nazarov, D.; Chertykovtseva, V.; Kurkina, E.; Hoang, V.H. Algorithm for Propeller Optimization Based on Differential Evolution. Computation2024, 12, 52.
Sedelnikov, A.; Kurkin, E.; Quijada-Pioquinto, J.G.; Lukyanov, O.; Nazarov, D.; Chertykovtseva, V.; Kurkina, E.; Hoang, V.H. Algorithm for Propeller Optimization Based on Differential Evolution. Computation 2024, 12, 52.
Sedelnikov, A.; Kurkin, E.; Quijada-Pioquinto, J.G.; Lukyanov, O.; Nazarov, D.; Chertykovtseva, V.; Kurkina, E.; Hoang, V.H. Algorithm for Propeller Optimization Based on Differential Evolution. Computation2024, 12, 52.
Sedelnikov, A.; Kurkin, E.; Quijada-Pioquinto, J.G.; Lukyanov, O.; Nazarov, D.; Chertykovtseva, V.; Kurkina, E.; Hoang, V.H. Algorithm for Propeller Optimization Based on Differential Evolution. Computation 2024, 12, 52.
Abstract
This article describes the choice of an optimization algorithm for solving problems and the optimal design of an unmanned aerial vehicle propeller. To solve the problem using evolutionary algorithms, it was transformed into an unconstrained optimization problem using a penalty function. The airfoil contours were constructed using a Bezier curve. Design variables were divided into two types: those that describe in general terms the propeller geometry or operation, such as propeller diameter, number of blades, and rev/min; and those that vary with propeller radius, such as chord length, effective airfoil angle, and airfoil geometry. The objective function is the calculation of the propeller power required to achieve a given thrust. The differential evolution algorithm was used to solve this problem.
Computer Science and Mathematics, Data Structures, Algorithms and Complexity
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