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dc.contributor.authorATA, Sadık
dc.contributor.authorKAHRAMAN, Ali
dc.contributor.authorŞAHİN, Remzi
dc.date.accessioned2023-02-27T18:26:10Z
dc.date.available2023-02-27T18:26:10Z
dc.date.issued2020
dc.identifier.urihttp://hdl.handle.net/20.500.12498/5874
dc.description.abstractIn this study, parametric optimization and sensitivity analysis of performance parameters were performed for the Organic Rankine Cycle (ORC) system at 120 °C heat source temperature. R1234ze, which is called the new-generation fluid, was used in the ORC design. Performance parameters have been selected considering Energy, Exergy, Economy (Turbine performance) and Environmental (Thermodynamic sustainability indices) factors. Six performance indices used in the orthogonal design with Taguchi-ANOVA. These are; thermal efficiency, turbine power, exergy efficiency, total irreversibility, Volume Flow Ratio (VFR) and Environmental Effect Factor (EEF). Such control factors as ΔTPP,e - ΔTPP,c -Tc,i -Tsup – ƞt – ƞp were selected for the statistical analysis. Sensitivity levels were determined under all performance indices for the designed ORC. It has been determined that indices affect control factors differently. According to the results of the parametric optimization, it was determined that the parameter affecting the ORC performance the most was ΔTPP,e. The effect of ΔTPP,e on ORC performance is stated as 39.72%. EES numerical analysis results were compared with the derived predictive equations using different statistical methods with regression method. When these equations obtained for all objective functions are evaluated, the average MAPE, RRMSE and R2 values were determined as 4.1%, 4.29% and 94.1%, respectively.en_US
dc.language.isoenen_US
dc.publisherCase Studies in Thermal Engineeringen_US
dc.subjectOrganic Rankine Cycle (ORC)en_US
dc.subjectPerformance Predictionen_US
dc.subjectSensitivity Analysisen_US
dc.subjectR1234zeen_US
dc.subjectThermodynamic Optimizationen_US
dc.titlePrediction and sensitivity analysis under different performance indices of R1234ze ORC with Taguchi’s multi-objective optimizationen_US
dc.typeMakaleen_US


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