Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network

An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included

Sampling-related frames in finite U-invariant subspaces

Recently, a sampling theory for infinite dimensional U-invariant subspaces of a separable Hilbert space H where U denotes a unitary operator on H has been obtained. Thus, uniform average sampling for shift-invariant subspaces of L-2(R) becomes a particular example. As in the general case it is possible to have finite dimensional U-invariant subspaces, the main aim of this paper is to derive a sampling theory for finite dimensional U-invariant subspaces of a separable Hilbert space H. Since the used samples are frame coefficients in a suitable euclidean space C-N, the problem reduces to obtain dual frames with a U-invariance property

Distance-based kernels for real-valued data

We consider distance-based similarity measures for real-valued vectors of interest in kernel-based machine learning algorithms. In particular, a truncated Euclidean similarity measure and a self-normalized similarity measure related to the Canberra distance. It is proved that they are positive semi-definite (p.s.d.), thus facilitating their use in kernel-based methods, like the Support Vector Machine, a very popular machine learning tool. These kernels may be better suited than standard kernels (like the RBF) in certain situations, that are described in the paper. Some rather general results concerning positivity properties are presented in detail as well as some interesting ways of proving the p.s.d. property.Peer ReviewedPostprint (author's final draft

Photochemical hazes in sub-Neptunian atmospheres with focus on GJ 1214 b

We study the properties of photochemical hazes in super-Earths/mini-Neptunes atmospheres with particular focus on GJ1214b. We evaluate photochemical haze properties at different metallicities between solar and 10000$\times$solar. Within the four orders of magnitude change in metallicity, we find that the haze precursor mass fluxes change only by a factor of $\sim$3. This small diversity occurs with a non-monotonic manner among the different metallicity cases, reflecting the interaction of the main atmospheric gases with the radiation field. Comparison with relative haze yields at different metallicities from laboratory experiments reveals a qualitative similarity with our theoretical calculations and highlights the contributions of different gas precursors. Our haze simulations demonstrate that higher metallicity results into smaller average particle sizes. Metallicities at and above 100$\times$solar with haze formation yields of $\sim$10$\%$ provide enough haze opacity to satisfy transit observation at visible wavelengths and obscure sufficiently the H$_2$O molecular absorption features between 1.1 $\mu$m and 1.7 $\mu$m. However, only the highest metallicity case considered (10000$\times$solar) brings the simulated spectra into closer agreement with transit depths at 3.6 $\mu$m and 4.5 $\mu$m indicating a high contribution of CO/CO$_2$ in GJ1214b's atmosphere. We also evaluate the impact of aggregate growth in our simulations, in contrast to spherical growth, and find that the two growth modes provide similar transit signatures (for D$_f$=2), but with different particle size distributions. Finally, we conclude that the simulated haze particles should have major implications for the atmospheric thermal structure and for the properties of condensation clouds

Criterio de detección de outliers en modelos probabilísticos tipo Pareto

Partiendo de una población tipo Pareto con origen de rentas H conocido, se encuentra un criterio para detección de outliers. Se estudia a continuación el caso de origen de rentas desconocido, dándose al final un criterio para la detección de varias observaciones outliers. Se incluye el correspondiente programa de ordenador.Starting from a Pareto type population with known minimum income H in this paper a criterium for detecti^n of outliers is derived. The unknowm minimum income case is also studied, showing a criterium for detection of some outliers observations. The corresponding computing program is inciuded

Aerodynamic Optimization of a High-speed Train using Genetic Algorithms

Genetic algorithms (GA) have been used for the minimization of the aerodynamic drag of a train subject to front wind. The significant importance of the external aerodynamic drag on the total resistance a train experiments as the cruise speed is increased highlights the interest of this study. A complete description of the methodology required for this optimization method is introduced here, where the parameterization of the geometry to be optimized and the metamodel used to speed up the optimization process are detailed. A reduction of about a 25% of the initial aerodynamic drag is obtained in this study, what confirms GA as a proper method for this optimization problem. The evolution of the nose shape is consistent with the literature. The advantage of using metamodels is stressed thanks to the information of the whole design space extracted from it. The influence of each design variable on the objective function is analyzed by means of an ANOVA test

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

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