Optimization of nanoantenna for solar energy harvesting based on particle swarm technique

El-Toukhy, Youssef M.; Heikal, A. M.; Hameed, Mohamed Farhat O.; Abd-Elrazzak, Maher M.; Obayya, S. S. A.

doi:10.1109/ropaces.2016.7465458

Cited by 3 publications

(2 citation statements)

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“…The relatively fast and accurate simulation of nanostructures operating at TeraHertz frequencies has created a space for stochastic optimizers to participate in design process refinement for various engineering electromagnetic (EM) problems where a link between the optimization algorithm and the EM solver is created. Particle swarm optimization (PSO) was previously introduced to the nanoantenna field [28] and has a great potential in the microwave antenna design recently by the authors [29,30]. Kennedy and Eberhart were the first to introduce the PSO concept [21].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Tapered Plasmonic Nanoantennas for Energy Harvesting Applications

El-Toukhy¹,

OthmanHameed²,

Hussein³

et al. 2017

Nanoplasmonics - Fundamentals and Applications

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In this chapter, novel designs of tapered-dipole nanoantennas are investigated for energy harvesting applications. A full systematic analysis for the proposed structure is presented where the harvesting efficiency, return loss, radiation pattern, and near-field enhancement are calculated using a finite-element frequency domain solver. Simulation results show that the proposed nanoantennas can achieve a harvesting efficiency of 60% at a wavelength of 500 nm where the antenna input impedance is matched to that of fabricated rectifying devices. Additionally, the cross-tapered nanoantenna offers a near-field enhancement factor of 252 V/m, which is relatively high compared to previously reported nanoantennas. The spatial and spectral resonance modes are investigated, and the simulation results indicate the ability of the cross geometry to be utilized in color-sorting applications. Moreover, the particle swarm optimization technique is adapted to configure the proposed designs for maximum performance.

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Section: Particle Swarm Optimizationmentioning

confidence: 99%

Tapered Plasmonic Nanoantennas for Energy Harvesting Applications

El-Toukhy¹,

OthmanHameed²,

Hussein³

et al. 2017

Nanoplasmonics - Fundamentals and Applications

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“…Compared with small and medium-sized spacecraft swarms, large-scale swarms are more autonomous, flexible, and scalable. The swarms can form large space structures via specified formation patterns, for example, synthetic aperture [3] , space-based solar energy stations [4] . The technology of pattern control is also widely used in configuration transformation, unknown area coverage, task allocation, and modular spacecraft assembly [1] .…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Collision-free Pattern Control For Large-Scale Spacecraft Swarms Around Circular Orbits

Chen

Wang

Yang

et al. 2022

J. Phys.: Conf. Ser.

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This work considers controlling large-scale spacecraft swarms to achieve complex spatial configuration. A novel distributed guidance algorithm is proposed based on Inhomogeneous Markov Chains, Probabilistic Density Guidance and Voronoi partition (IMC-PDG-Voronoi) algorithms. The physical space is partitioned into multiple bins and the density distribution of the swarm is controlled via a probabilistic approach. Then the modified Voronoi partition method is used to generate a collision-free trajectory for each agent. To apply the probabilistic control algorithm to circular Earth orbit, the periodic solution of the Clohessy-Wiltshire (C-W) equation in configuration space is transformed into a parameter space. Then a convex optimization open-loop controller with minimum fuel consumption in LVLH coordinates is designed to control the swarm to expected positions. Numerical simulations show that the algorithm can effectively guide and control large-scale spacecraft swarms to form complex configurations on circular orbits, with high precision and little cost.

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