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Jagadish / Das

Evolutionary Methods Based Modeling and Analysis of Solar Thermal Systems

A Case Studies Approach

Medium: Buch
ISBN: 978-3-031-27637-8
Verlag: Springer International Publishing
Erscheinungstermin: 01.05.2024
Lieferfrist: bis zu 10 Tage
This book presents insights into the thermal performance of solar thermal collectors using both computational and experimental modeling. It consists of various computational and experimental case studies conducted by the authors on the solar thermal collector system. The authors begin by developing thermal modeling using a case study that shows the effect of different governing parameters. A few more experimental cases studies follow that highlight the energy, exergy, and environmental performance of the solar thermal collector system and to examine the performance of a modified solar collector system, illustrating performance improvement techniques.

Finally, application of different evolutionary optimization techniques such as soft computing and evolutionary methods, like fuzzy techniques, MCDM methods like fuzzy logic based expert system (FLDS), Artificial Neural Network (ANN), Grey relational analysis (GRA), Entropy-Jaya algorithm, Entropy-VIKOR etc. are employed.

Produkteigenschaften


  • Artikelnummer: 9783031276378
  • Medium: Buch
  • ISBN: 978-3-031-27637-8
  • Verlag: Springer International Publishing
  • Erscheinungstermin: 01.05.2024
  • Sprache(n): Englisch
  • Auflage: 2023
  • Serie: Mechanical Engineering Series
  • Produktform: Kartoniert, Paperback
  • Gewicht: 236 g
  • Seiten: 128
  • Format (B x H x T): 155 x 235 x 9 mm
  • Ausgabetyp: Kein, Unbekannt

Autoren/Hrsg.

Herausgeber

Jagadish

Das, Biplab

Introduction.- Modeling and optimization of energetic and exergetic performance of solar air collector.- Expert system based thermal performance analysis of corrugated absorber plate based solar air collector.- Investigation of thermal performance of SAC variables using fuzzy logic-based expert system.- Sustainability assessment of solar air collector using deep learning.