IMProVe 2011 - Proceedings

Design Methods and Applications
campaign has been carried out to acquire vibration data over helicopters. The paper
describes the implementation of a simulator which provides also the reproduction of
vibration felt in flight by pilot. The attention is focused on the conceptual and preliminary
design, CAD modelling, FEM analysis, manufacturing and testing of the device conceived
to reproduce vibrations over the pilot’s seat. Only the first frequency of the rotor is
reproduced since it is the most important excitations and it is variable, depending on the
flight phase. The shaker has been built and installed on a simulator. The final result shows
that such a simulator can improve the realism involving not only the senses of sight and
hearing, but also providing a more “physical” feedback due to vibrations perception.
Keywords: Simulation, Computer Aided Design, Design Methodology, Vibrations, Finite
Element Analysis.
Corresponding Author: Alessandro Ceruti
Tel.:+39 051 2093452
Fax.:+39 051 2093412
e-mail: alessandro.ceruti@unibo.it
Address: University of Bologna, Department of Mechanical, Nuclear, Aeronautical Engineering and
Metallurgy.
Optimization by Particle Swarm Algorithms
of an UAV performed by Hot Wire Cutting Techniques
June 15 th – 17 th , 2011, Venice, Italy
A. Ceruti (a), G. Caligiana (a), F. Persiani (a)
(a) University of Bologna, DIEM Department
Abstract:
This paper describes an original application of unconventional optimization techniques by
Particle Swarm Algorithms. An Unmanned Aerial Vehicle performed by Hot Wire Cutting is
designed for a typical civil mission defining geometry and aerodynamics with a Particle
Swarm Algorithm. The tailless configuration of the vehicle requires an accurate design to
gain the satisfaction of all the requirements and to obtain a low cost solution. Only an
unconventional technique can be applied because of the high non linearity of the problem
and the high number of parameters to be defined. A first preliminary series of tests have
been carried out to define the best values for inertia and acceleration coefficients of the
Particle Swarm algorithm; in the following the algorithm results have been compared with
those obtained by other two techniques like Genetic Algorithms and Monte Carlo
Simulations. The result of this study shows how the Rapid Prototyping techniques can be
applied to the performing of small lots of UAV: the required optimal design is gained
applying the Particle Swarm Algorithm. The conclusion of this work confirms the suitability
of non conventional optimization methods to non linear problems: Genetic Algorithms
and Particle Swarm optimization provide similar results in term of fitness maximization,
while Monte Carlo algorithm presents a lower efficiency. The Particle Swarm and Monte
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IMProVe 2011 - Proceedings