Application of the multi-objective Alliance algorithm to a benchmark aerodynamic optimization problem

This paper introduces a new version of the multiobjective Alliance Algorithm (MOAA) applied to the optimization of the NACA 0012 airfoil section, for minimization of drag and maximization of lift coefficients, based on eight section shape parameters. Two software packages are used: XFoil which evaluates each new candidate airfoil section in terms of its aerodynamic efficiency, and a Free-Form Deformation tool to manage the section geometry modifications. Two versions of the problem are formulated with different design variable bounds. The performance of this approach is compared, using two indicators and a statistical test, with that obtained using NSGA-II and multi-objective Tabu Search (MOTS) to guide the optimization. The results show that the MOAA outperforms MOTS and obtains comparable results with NSGA-II on the first problem, while in the other case NSGA-II is not able to find feasible solutions and the MOAA is able to outperform MOTS. © 2013 IEEE.

Testing of the multi-objective alliance algorithm on benchmark functions

A new version of the Multi-objective Alliance Algorithm (MOAA) is described. The MOAA's performance is compared with that of NSGA-II using the epsilon and hypervolume indicators to evaluate the results. The benchmark functions chosen for the comparison are from the ZDT and DTLZ families and the main classical multi-objective (MO) problems. The results show that the new MOAA version is able to outperform NSGA-II on almost all the problems.

A self-adaptive genetic algorithm applied to multi-objective optimization of an airfoil

Genetic algorithms (GAs) have been used to tackle non-linear multi-objective optimization (MOO) problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the numbers of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimizing GA (MOGA) that uses self-adaptive mutation and crossover, and which is applied to optimization of an airfoil, for minimization of drag and maximization of lift coefficients. The MOGA is integrated with a Free-Form Deformation tool to manage the section geometry, and XFoil which evaluates each airfoil in terms of its aerodynamic efficiency. The performance is compared with those of the heuristic MOO algorithms, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this GA achieves better convergence.

Plasmonic silver nanoparticles for improved organic solar cells

In the present work we compare the performance of organic solar cells, based on the bulk heterojunction system of P3HT:PCBM when adequate silver nanoparticles (NPs) are incorporated in two distinct places among the device structure. Introduction of NPs on top of the transparent anode revealed better overall performance with an increased efficiency of 17%. Alternatively, placing the NPs on top of the active photovoltaic layer resulted to 25% higher photo-current generation albeit with inferior electrical characteristics (i.e series and shunt resistance). Our findings suggest that enhanced scattering to non-specular directions from NPs site is maximized when penetrating light meets the particles after the polymer blend, but even this mechanism is not sufficient enough to explain the enhanced short circuit current observed. A second mechanism should be feasible; that is plasmon enhancement which is more efficient in the case where NPs are in direct contact with the polymer blend. J-V characteristics measured in the dark showed that NPs placed on top of the ITO film act as enhanced hole conducting sites, as evident by the lower series resistance values in these cells, suggesting this mechanism as more significant in this case. © 2012 Elsevier B.V. All rights reserved.

Weighted least squares with expectation-maximization algorithm for burst detection in U.K. water distribution systems

Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.

Performance of hybrid buffer Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) layers doped with plasmonic silver nanoparticles

We compare the performance of a typical hole transport layer for organic photovoltaics (OPVs), Poly(3,4-ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) thin film with a series of PEDOT:PSS layers doped with silver (Ag) nanoparticles (NPs) of various size distributions. These hybrid layers have attracted great attention as buffer layers in plasmonic OPVs, although there is no report up to date on their isolated performance. In the present study we prepared a series of PEDOT:PSS layers sandwiched between indium tin oxide (ITO) and gold (Au) electrodes. Ag NPs were deposited on top of the ITO by electron beam evaporation followed by spin coating of PEDOT:PSS. Electrical characterization performed in the dark showed linear resistive behavior for all the samples; lower resistance was observed for the hybrid ones. It was found that the resistivity of the samples decreases with increasing the particle's size. A substantial increase of the electric field between the ITO and the Au electrodes was seen through the formation of current paths through the Ag NPs. A striking observation is the slight increase in the slope of the current density versus voltage curves when measured under illumination for the case of the plasmonic layers, indicating that changes in the electric field in the vicinity of the NP due to plasmonic excitation is a non-vanishing factor. © 2014 Published by Elsevier B.V. All rights reserved.