Genetic algorithms used for the optimization of light-emitting diodes and solar thermal collectors

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Abstract

We present a genetic algorithm (GA) we developed for the optimization of light-emitting diodes (LED) and solar thermal collectors. The surface of a LED can be covered by periodic structures whose geometrical and material parameters must be adjusted in order to maximize the extraction of light. The optimization of these parameters by the GA enabled us to get a light-extraction efficiency η of 11.0% from a GaN LED (for comparison, the flat material has a light-extraction efficiency η of only 3.7%). The solar thermal collector we considered consists of a waffle-shaped Al substrate with NiCrOx and SnO2 conformal coatings. We must in this case maximize the solar absorption α while minimizing the thermal emissivity ? in the infrared. A multi-objective genetic algorithm has to be implemented in this case in order to determine optimal geometrical parameters. The parameters we obtained using the multi-objective GA enable α~97.8% and ε~4.8%, which improves results achieved previously when considering a flat substrate. These two applications demonstrate the interest of genetic algorithms for addressing complex problems in physics.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Number of pages10
Volume9187
ISBN (Print)9781628412147
DOIs
Publication statusPublished - 2014
EventThe Nature of Light: Light in Nature V - San Diego, United States
Duration: 18 Aug 2014 → …

Conference

ConferenceThe Nature of Light: Light in Nature V
CountryUnited States
CitySan Diego
Period18/08/14 → …

Fingerprint

Diode
genetic algorithms
accumulators
Light emitting diodes
light emitting diodes
Genetic algorithms
Genetic Algorithm
optimization
Multi-objective Genetic Algorithm
Optimization
Maximise
Substrate
Emissivity
Periodic Structures
Coating
Periodic structures
Substrates
Infrared
Absorption
emissivity

Keywords

  • Al
  • Cermet
  • Gan
  • Genetic algorithm
  • Light-emitting diode
  • Optimization
  • Solar thermal collector

Cite this

@inproceedings{c017df9f9a3144b185c85440a774f55c,
title = "Genetic algorithms used for the optimization of light-emitting diodes and solar thermal collectors",
abstract = "We present a genetic algorithm (GA) we developed for the optimization of light-emitting diodes (LED) and solar thermal collectors. The surface of a LED can be covered by periodic structures whose geometrical and material parameters must be adjusted in order to maximize the extraction of light. The optimization of these parameters by the GA enabled us to get a light-extraction efficiency η of 11.0{\%} from a GaN LED (for comparison, the flat material has a light-extraction efficiency η of only 3.7{\%}). The solar thermal collector we considered consists of a waffle-shaped Al substrate with NiCrOx and SnO2 conformal coatings. We must in this case maximize the solar absorption α while minimizing the thermal emissivity ? in the infrared. A multi-objective genetic algorithm has to be implemented in this case in order to determine optimal geometrical parameters. The parameters we obtained using the multi-objective GA enable α~97.8{\%} and ε~4.8{\%}, which improves results achieved previously when considering a flat substrate. These two applications demonstrate the interest of genetic algorithms for addressing complex problems in physics.",
keywords = "Al, Cermet, Gan, Genetic algorithm, Light-emitting diode, Optimization, Solar thermal collector",
author = "Alexandre Mayer and Annick Bay and Lucie Gaouyat and Delphine Nicolay and Timoteo Carletti and Olivier Deparis",
year = "2014",
doi = "10.1117/12.2060811",
language = "English",
isbn = "9781628412147",
volume = "9187",
booktitle = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",

}

Mayer, A, Bay, A, Gaouyat, L, Nicolay, D, Carletti, T & Deparis, O 2014, Genetic algorithms used for the optimization of light-emitting diodes and solar thermal collectors. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 9187, 918705, SPIE, The Nature of Light: Light in Nature V, San Diego, United States, 18/08/14. https://doi.org/10.1117/12.2060811

Genetic algorithms used for the optimization of light-emitting diodes and solar thermal collectors. / Mayer, Alexandre; Bay, Annick; Gaouyat, Lucie; Nicolay, Delphine; Carletti, Timoteo; Deparis, Olivier.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9187 SPIE, 2014. 918705.

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

TY - GEN

T1 - Genetic algorithms used for the optimization of light-emitting diodes and solar thermal collectors

AU - Mayer, Alexandre

AU - Bay, Annick

AU - Gaouyat, Lucie

AU - Nicolay, Delphine

AU - Carletti, Timoteo

AU - Deparis, Olivier

PY - 2014

Y1 - 2014

N2 - We present a genetic algorithm (GA) we developed for the optimization of light-emitting diodes (LED) and solar thermal collectors. The surface of a LED can be covered by periodic structures whose geometrical and material parameters must be adjusted in order to maximize the extraction of light. The optimization of these parameters by the GA enabled us to get a light-extraction efficiency η of 11.0% from a GaN LED (for comparison, the flat material has a light-extraction efficiency η of only 3.7%). The solar thermal collector we considered consists of a waffle-shaped Al substrate with NiCrOx and SnO2 conformal coatings. We must in this case maximize the solar absorption α while minimizing the thermal emissivity ? in the infrared. A multi-objective genetic algorithm has to be implemented in this case in order to determine optimal geometrical parameters. The parameters we obtained using the multi-objective GA enable α~97.8% and ε~4.8%, which improves results achieved previously when considering a flat substrate. These two applications demonstrate the interest of genetic algorithms for addressing complex problems in physics.

AB - We present a genetic algorithm (GA) we developed for the optimization of light-emitting diodes (LED) and solar thermal collectors. The surface of a LED can be covered by periodic structures whose geometrical and material parameters must be adjusted in order to maximize the extraction of light. The optimization of these parameters by the GA enabled us to get a light-extraction efficiency η of 11.0% from a GaN LED (for comparison, the flat material has a light-extraction efficiency η of only 3.7%). The solar thermal collector we considered consists of a waffle-shaped Al substrate with NiCrOx and SnO2 conformal coatings. We must in this case maximize the solar absorption α while minimizing the thermal emissivity ? in the infrared. A multi-objective genetic algorithm has to be implemented in this case in order to determine optimal geometrical parameters. The parameters we obtained using the multi-objective GA enable α~97.8% and ε~4.8%, which improves results achieved previously when considering a flat substrate. These two applications demonstrate the interest of genetic algorithms for addressing complex problems in physics.

KW - Al

KW - Cermet

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KW - Light-emitting diode

KW - Optimization

KW - Solar thermal collector

U2 - 10.1117/12.2060811

DO - 10.1117/12.2060811

M3 - Conference contribution

SN - 9781628412147

VL - 9187

BT - Proceedings of SPIE - The International Society for Optical Engineering

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