Uporaba algoritmov MCDM pri izbiri fazno spremenljivih snovi v prenosnikih toplote sistemov za shranjevanje toplote
| Autor: | Paul Gregory Felix, Velavan Rajagopal, Kannan Kumaresan |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
business.industry Mechanical Engineering večkriterijsko odločanje multiple criteria decision making thermal energy storage udc:536.24 eritritol latent heat latentna toplota fazno spremenljive snovi Multiple-criteria decision analysis Thermal energy storage shranjevanje toplote Phase change Mechanics of Materials Heat exchanger kuhanje na pari phase change material Process engineering business Selection (genetic algorithm) |
| Zdroj: | Strojniški vestnik, vol. 67, no. 11, pp. 611-622, 2021. |
| ISSN: | 0039-2480 |
| DOI: | 10.5545/sv-jme.2021.7356 |
| Popis: | Latent heat thermal energy storage heat exchangers store heat energy by virtue of the phase transition that occurs in the thermal storage media. Since phase change materials (PCMs) are utilized as the media, there is a critical necessity for the appropriate selection of the PCM utilized. Since multiple thermo-physical properties and multiple PCMs are required to be evaluated for the selection, there arises a need for multiple criteria decision making (MCDM) algorithms to be adopted for the selection. But owing to the different weight estimation techniques employed and the voluminous quantity of selection algorithms available, there arises a need for a comparative methodology to be adopted. This study was intended to select an optimal PCM for a sustainable steam cooking application coupled with a thermal energy storage system. In this research study, six PCMs were chosen as the alternatives and five thermo-physical properties were chosen as the criteria for the evaluation. 11 different algorithms were augmented with 3 different weight estimation techniques and therefore a total of 33 algorithms were employed in this study. All of the algorithms have chosen Erythritol as the optimal PCM for the application. The outcomes of the MCDM algorithms have been validated through an intricate Pearson’s correlation coefficient study. |
| Databáze: | OpenAIRE |
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