A Novel Memetic Feature Selection Algorithm

Feature selection is a problem of finding efficient features among all features in which the final feature set can improve accuracy and reduce complexity. In feature selection algorithms search strategies are key aspects. Since feature selection is an NP-Hard problem; therefore heuristic algorithms have been studied to solve this problem. In this paper, we have proposed a method based on memetic algorithm to find an efficient feature subset for a classification problem. It incorporates a filter method in the genetic algorithm to improve classification performance and accelerates the search in identifying core feature subsets. Particularly, the method adds or deletes a feature from a candidate feature subset based on the multivariate feature information. Empirical study on commonly data sets of the university of California, Irvine shows that the proposed method outperforms existing methods

CFD simulations of a vertical axis wind turbine in dynamic stall: URANS vs. Scale-Adaptive Simulation (SAS)

Vertical axis wind turbines (VAWTs) are promising candidates for wind energy harvesting in the urban environment. However, their aerodynamic performance still falls behind of their horizontal axis counterparts. This could be associated to the comparatively small research they have received in the past decades as well as their complex unsteady aerodynamics. Computational Fluid Dynamics (CFD) has been widely used to evaluate and improve the aerodynamic performance of VAWTs. An extensive literature study reveals that the 2D unsteady Reynolds-Averaged Navier-Stokes (URANS) approach has been used in the majority of the CFD studies on VAWTs. The current study intends to evaluate the aerodynamic performance of a VAWT, calculated using 2D URANS, and compare it with that of 2.5D URANS and 2.5D scale-adaptive simulation (SAS). SAS is a hybrid RANS-LES model developed by Menter and Egorov [1]. The four-equation transition SST turbulence model is employed in the URANS simulations as well as in the RANS region of the hybrid RANS-LES simulation. The studied turbine is a one-bladed Darrieus H-type VAWT with a solidity of 0.125 operating at a low tip speed ratio of 2.0, which corresponds to the most complex case for VAWTs where dynamic stall is dominant. The reduced frequency is 0.125 representing the high unsteadiness in the flow. Significant benefits of the one-bladed turbine are: (i) less blade-wake interactions while the essential flow features, such as dynamic stall, are still present, (ii) reduced computational costs due to the smaller number of cells. The turbine characteristics is based on the experiment by Simão Fereira et al. [2]. Validation studies for the one-bladed turbine as well as the other turbines have been performed [3-5]. A comparative analysis of the instantaneous tangential and normal loads on the turbine (see Fig. 1), spatiotemporal distribution of pressure coefficient (see Figs. 2a-c) and skin friction coefficient (see Fig. d-f) on the blade suction side, the evolution of the shed vorticity by the blade, dynamic loads on the blade and the turbine wake are employed to evaluate the performance of URANS modeling in comparison to the SAS model. The instantaneous turbine loads calculated using the 2D and the 2.5D URANS, shown in Fig. 1, are in line with minor differences in the downwind side. Despite the 180 times higher number of cells and 10 times finer time step of the SAS modeling, an overall good agreement exists between the 2D URANS and the SAS results. The predicted thrust coefficients for 2D and 2.5D URANS and SAS are 0.422, 0.424 and 0.430, respectively. Nevertheless, there exist noticeable differences between the URANS and SAS results in the bursting location of the laminar separation bubble (LSB), the evolution of the dynamic stall vortex (DSV), the leading-edge secondary and tertiary vortices and the trailing-edge separation. The findings of the present study help to highlight the deficiencies of URANS modeling of VAWTs in dynamic stall

Adaptive Integral Terminal Sliding Mode Control for the Nonlinear Active Vehicle Suspension System under External Disturbances and Uncertainties

Suspension system is one of the most effective vehicle components that play an essential role in the stability and comfort of the vehicle. The passive suspension can not fully meet a car's stability and comfort requirements. Instead, an active suspension system has been proposed to improve these challenges. Active suspension minimizes the vibrations entering the body using a closed-loop control system. To this end, in this research, an integral terminal sliding mode control (integral TSMC) for an active nonlinear car suspension system under external disturbances and uncertainties is designed. First, the integral TSMC is designed to deal with the uncertainties and the external disturbances in the system when the upper bound is known. Next, an adaptation law is recommended to estimate the upper bound of uncertainties and external disturbances. The results show that the proposed integral TSMC improves the convergence rate and tracking error of the closed-loop system. The stability of the nonlinear control system is investigated and proven using Lyapunov's stability theory. The numerical results indicate a good robust performance and stability for the proposed controller for the nonlinear suspension system with different road profiles in the presence of uncertainties and external disturbances. From the results, it can also be understood that important measures such as ride comfort, road holding, and mechanical structural limitations are met using the proposed approach

Factors Affecting Rangeland Utilization by Ranchers in the Golestan Rangelands, Iran

In Iran, rangelands produce most of the forage resources for livestock. There are various types of traditional grazing systems for the utilization of rangelands, including the consultative, collective and operational multiplayer systems. In the consultative type, certain people are selected by the ranchers and they determine the utilization method and manage grazing. In the collective system, all ranchers use rangeland in common. In the operational multiplayer system, rangelands are used in common but the ranchers share rangelands by rancher-rancher negotiation. This research was undertaken to investigate the human factors as rancher\u27s effect on rangeland utilization in different systems above mentioned

A computational framework for the lifetime prediction of vertical-axis wind turbines:CFD simulations and high-cycle fatigue modeling

A novel computational framework is presented for the lifetime prediction of vertical-axis wind turbines (VAWTs). The framework uses high-fidelity computational fluid dynamics (CFD) simulations for the accurate determination of the aerodynamic loading on the wind turbine, and includes these loading characteristics in a detailed 3D finite element method (FEM) model to predict fatigue cracking in the structure with a fatigue interface damage model. The fatigue interface damage model allows to simulate high-cycle fatigue cracking processes in the wind turbine in an accurate and robust fashion at manageable computational cost. The FEM analyses show that the blade-strut connection is the most critical structural part for the fatigue life of the VAWT, particularly when it is carried out as an adhesive connection (instead of a welded connection). The sensitivity of the fatigue response of the VAWT to specific static and fatigue modeling parameters and to the presence of a structural flaw is analyzed. Depending on the flaw size and flaw location, the fatigue life of the VAWT can decrease by 25%. Additionally, the decrease of the fatigue resistance of the VAWT appears to be mainly characterized by the monotonic reduction of the tensile strength of the adhesive blade-strut connection, rather than by the reduction of its mode I toughness, such that fatigue cracking develops in a brittle fashion under a relatively small crack opening. It is emphasized that the present computational framework is generic; it can also be applied for analyzing the fatigue performance of other rotating machinery subjected to fluid–structure interaction, such as horizontal-axis wind turbines, steam turbine generators and multistage pumps and compressors

Urban physics simulation for climate change adaptation of buildings and urban areas

This chapter discusses the simulation of urban thermal microclimate with a focus on heat waves in urban areas, the simulation of overheating of buildings and the effects of adaptation measures to limit temperatures in buildings and urban areas during heat waves. The spatial scales are the meteorological microscale (neighborhood scale) and the building scale; the methods are computational fluid dynamics and building energy simulation. Adaptation measures investigated at the neighborhood scale are avenue trees, green facades and green roofs; adaptation measures at the building scale are increased thermal resistance, increased thermal mass, increased short-wave reflectivity of facades and roofs, peak ventilation, vegetated roofs and exterior solar shading