LEADER 04168nam 22007095 450 001 9910720076103321 005 20251008145136.0 010 $a9783031276354$b(electronic bk.) 010 $z9783031276347 024 7 $a10.1007/978-3-031-27635-4 035 $a(MiAaPQ)EBC7243114 035 $a(Au-PeEL)EBL7243114 035 $a(DE-He213)978-3-031-27635-4 035 $a(OCoLC)1378390160 035 $a(PPN)269655689 035 $a(CKB)26540756300041 035 $a(EXLCZ)9926540756300041 100 $a20230429d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEvolutionary Methods Based Modeling and Analysis of Solar Thermal Systems $eA Case Studies Approach /$fedited by Biplab Das, Jagadish 205 $a1st ed. 2023. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2023. 215 $a1 online resource (143 pages) 225 1 $aMechanical Engineering Series,$x2192-063X 311 08$aPrint version: Das, Biplab Evolutionary Methods Based Modeling and Analysis of Solar Thermal Systems Cham : Springer International Publishing AG,c2023 9783031276347 320 $aIncludes bibliographical references and index. 327 $aIntroduction -- 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. 330 $aThis book presents insights into the thermal performance of solar thermal collectors using both computational and experimental modeling. It consists of various computational and experimental case studies conducted by the authors on the solar thermal collector system. The authors begin by developing thermal modeling using a case study that shows the effect of different governing parameters. A few more experimental cases studies follow that highlight the energy, exergy, and environmental performance of the solar thermal collector system and to examine the performance of a modified solar collector system, illustrating performance improvement techniques. Finally, application of different evolutionary optimization techniques such as soft computing and evolutionary methods, like fuzzy techniques, MCDM methods like fuzzy logic based expert system (FLDS), Artificial Neural Network (ANN), Grey relational analysis (GRA), Entropy-Jaya algorithm, Entropy-VIKOR etc. are employed. Covers improvement of solar thermal systems and advances in solar air collector systems, modeling, and optimization; Includes modeling and parametric optimization issues for the practitioners of solar thermal industries; Provides a new method for modeling and optimizing solar air collectors using actual case studies from the field. 410 0$aMechanical Engineering Series,$x2192-063X 606 $aSolar energy 606 $aRenewable energy sources 606 $aElectric power-plants 606 $aBuilding information modeling 606 $aMathematical models 606 $aSolar Thermal Energy 606 $aRenewable Energy 606 $aPower Stations 606 $aBuilding Information Modeling 606 $aMathematical Modeling and Industrial Mathematics 615 0$aSolar energy. 615 0$aRenewable energy sources. 615 0$aElectric power-plants. 615 0$aBuilding information modeling. 615 0$aMathematical models. 615 14$aSolar Thermal Energy. 615 24$aRenewable Energy. 615 24$aPower Stations. 615 24$aBuilding Information Modeling. 615 24$aMathematical Modeling and Industrial Mathematics. 676 $a621.472 702 $aDas$b Biplab 702 $aJagadish 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 912 $a9910720076103321 996 $aEvolutionary Methods Based Modeling and Analysis of Solar Thermal Systems$93417235 997 $aUNINA