Optimización multi-objetivo frente a varias direcciones del viento incidente del testero de un tren de alta velocida

Crespo Martínez, Antonio

García García, Javier

Muñoz Paniagua, Jorge

Servicio de Coordinación de Bibliotecas de la Universidad Politécnica de Madrid

11th World Congress on Computational Mechanics (WCCM XI)
5th European Conference on Computational Mechanics (ECCM V)
6th European Conference on Computational Fluid Dynamics (ECFD VI)
July 20–25, 2014, Barcelona, Spain
SURROGATE-BASED OPTIMIZATION OF THE NOSE
SHAPE OF A TRAIN SUBJECTED TO CROSS-WIND
J. Munoz-Paniagua∗1, J. Garc´ıa and A. Crespo
1 Research Group of Applied Fluid Mechanics, Universidad Polite´cnica de Madrid
C/Jose´ Gutie´rrez Abascal 2, 28006, Madrid, Spain
e-mail: le.munoz@upm.es
Key words: Surrogate-based Optimization, Genetic Algorithm, Shape Optimization,
High-speed Train, Cross-wind
People have never traveled as much as over the last decade and, in this situation, the
importance of trains has notably grown because of its energy efficiency. More mobility
involves an increase in both the train cruise speed and lightness, and these requirements
directly influence the stability and the ride comfort of the passengers when the train is
subjected to a cross-wind. Thus, cross-wind stability plays a very relevant role among
the aerodynamic objectives to be optimized. Over the past few years, this has led to an
extensive research in the analysis of the flow characteristics in many different scenarios,
[1], [3] or [4]. Once the flow structures are pictured, it is possible to propose a geometric
modification that can improve the aerodynamic performance of trains. Dealing with these
optimization problems has traditionally been done by a trial-and-error procedure, which
is very expensive in terms of computer and designer time. Furthermore, this procedure
strongly depends on the expertise of the engineer. Advanced optimization algorithms try
to use the information extracted from these previous analyses while, at the same time,
present a new strategy to solve the problem based in a more automated fashion. The
application of these methods is very popular in aircraft or vehicle aerodynamics, but is still
in progress in train aerodynamics,[4], [5] and [6]. Therefore, the interest of aerodynamic
shape optimization for high-speed trains and the development and application of advanced
optimization methods for train aerodynamics is evident. Here we propose the use of
genetic algorithms (GA) for the aerodynamic optimization of the nose shape of a high-
speed train subjected to cross-wind.
GA, [2], is a technique that mimics the mechanics of the natural evolution. Once a
population of potential (optimal) solutions is defined, it combines survival-of-the-fittest
concept to eliminate unfit characteristics and, after several iterations (generations), better
results are obtained until a solution closer to the globally optimal solution is reached.
The main drawback when using a GA is their need of a large number of evaluations
of the objective function. Furthermore, each optimal candidate needs to be defined as
J. Munoz-Paniagua, J. Garc´ıa and A. Crespo
a codified structure, and since a set of individuals is required at each generation, an
efficient representation of each possible optimal design (i.e. a high-speed nose shape)
is demanded. Nose shrinking, bluntness and A-pillar roundness features are captured
within the proposed parameterization. To overcome the requirement of a very large
number of evaluations of the objective function, surrogate models are used. The surrogate-
based optimization proposed here considers radial basis functions (RBF) to construct the
surrogate model that will approximate the numerical solver, enabling a faster evaluation
and optimization process.
The metamodel is used not only to help the GA to find the optimal design, but also to
analyze the whole design space and determine the sensitivity of the objective function
to the design variables. In this way, we can identify which are the most relevant design
variables and quantify the effect of these on the objective function. [4] points out that
the optimization of the aerodynamic performance of a train results into a multi-objective
optimization problem since several aerodynamic objectives are known to be in conflict.
Indeed, well rounded fronts of trains, which are beneficial for drag reduction, can deterio-
rate lateral stability. Therefore, it is expected that the importance of the design variables
will change for different yaw angles or cross-wind scenarios, and so the optimal design.
Our paper aims to solve the aerodynamic optimization of a high-speed train for four dif-
ferent yaw-angles and the multi-objective problem of the aerodynamic optimization of a
high-speed train when considering two conflicting yaw-angles. Furthermore, the multi-
objective optimization of minimizing the aerodynamic drag and side force is performed.
In this case, a Pareto front of optimal solutions is obtained. Finally, conclusions about
the influence of the considered design variables on the drag and side force are achieved.
REFERENCES
[1] B. Diedrichs, “Aerodynamic Calculations of Crosswind Stability of a High-speed train
using Control Volumes of Arbitrary Polyhedral Shape”, in BBAA VI International
Colloquium on Bluff Bodies Aerodynamics & Applications, Milano, Italy, 2008.
[2] D. E. Goldberg, “Genetic Algorithms in Search, Optimization and Machine Learn-
ing”, Addison Wesley, 1989.
[3] H. Hemida and S. Krajnovic, “LES study of the influence of the nose shape and yaw
angles on flow structures around trains”, Journal of Wind Engineering and Industrial
Aerodynamics, 98, 34–46, 2010.
[4] S. Krajnovic, “Shape Optimization of High-Speed Trains for Improved Aerodynamic
Performance”, in Proceedings of the Institution of Mechanical Engineers, Part F:
Journal of Rail and Rapid Transit, 223, 439–452, 2009.
[5] J. Munoz-Paniagua, J. Garc´ıa and A. Crespo, “Multi-objective Aerodynamic Opti-
mization of High-speed Trains in Tunnels”, in EUROGEN 2013, Las Palmas de Gran
Canaria, Spain, 2013.
[6] A. Orellano, AeroEfficient - Optimized Train, in modeFRONTIER International
Users Meeting 2010, Trieste, Italy, 2010.
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Surrogate-based optimization of the nose shape of a train subjected to crosswind

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Surrogate-based optimization of the nose shape of a train subjected to crosswind

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