Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application

Increasing the cycle efficiency of Organic Rankine Cycles is an important R&D area. In this study, an effort has been made to optimize various parameters related to the axial flow turbine to maximize an ORC's efficiency. First, a numerical model for a small-scale single-stage axial flow tur...

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Autores principales:	Yohan Engineer, Ahmed Rezk, Abul Kalam Hossain
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Energy Conversion Optimization ORC system Turbine Performance Turbine Design Heat QC251-338.5
Acceso en línea:	https://doaj.org/article/d68eb29fa1714890a1f78ac56260e286
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spelling	oai:doaj.org-article:d68eb29fa1714890a1f78ac56260e2862021-11-28T04:38:29ZEnergy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application2666-202710.1016/j.ijft.2021.100119https://doaj.org/article/d68eb29fa1714890a1f78ac56260e2862021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2666202721000574https://doaj.org/toc/2666-2027Increasing the cycle efficiency of Organic Rankine Cycles is an important R&D area. In this study, an effort has been made to optimize various parameters related to the axial flow turbine to maximize an ORC's efficiency. First, a numerical model for a small-scale single-stage axial flow turbine was developed and coupled with a 1D model of an existing ORC system. Then, a parametric study was undertaken for the system working under various turbine inlet conditions, such as turbine pressure ratios and working fluids. An optimization study was undertaken for the turbine flow profile using a low computational intensity Artificial Neural Network coupled with Genetic Algorithm optimization. Investigating the turbine losses revealed that the Mach Number is the most influential factor, which depends on the molar mass of the working fluid. Our study revealed that increasing the degree of superheat by up to 200% enhanced the turbine and overall cycle efficiency by 11% and 5%, respectively. Increasing the turbine total-to-static pressure ratio from 3 to 10 improved the turbine and cycle efficiency by up to 41% and 15%, respectively. Optimizing the turbine's flow profile enhanced the overall loss coefficient by 13.7%, the turbine's total-to-static efficiency by 5.2%, and the overall cycle efficiency from 8.78% to 9.02%.Yohan EngineerAhmed RezkAbul Kalam HossainElsevierarticleEnergy ConversionOptimizationORC systemTurbine PerformanceTurbine DesignHeatQC251-338.5ENInternational Journal of Thermofluids, Vol 12, Iss , Pp 100119- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Energy Conversion Optimization ORC system Turbine Performance Turbine Design Heat QC251-338.5
spellingShingle	Energy Conversion Optimization ORC system Turbine Performance Turbine Design Heat QC251-338.5 Yohan Engineer Ahmed Rezk Abul Kalam Hossain Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application
description	Increasing the cycle efficiency of Organic Rankine Cycles is an important R&D area. In this study, an effort has been made to optimize various parameters related to the axial flow turbine to maximize an ORC's efficiency. First, a numerical model for a small-scale single-stage axial flow turbine was developed and coupled with a 1D model of an existing ORC system. Then, a parametric study was undertaken for the system working under various turbine inlet conditions, such as turbine pressure ratios and working fluids. An optimization study was undertaken for the turbine flow profile using a low computational intensity Artificial Neural Network coupled with Genetic Algorithm optimization. Investigating the turbine losses revealed that the Mach Number is the most influential factor, which depends on the molar mass of the working fluid. Our study revealed that increasing the degree of superheat by up to 200% enhanced the turbine and overall cycle efficiency by 11% and 5%, respectively. Increasing the turbine total-to-static pressure ratio from 3 to 10 improved the turbine and cycle efficiency by up to 41% and 15%, respectively. Optimizing the turbine's flow profile enhanced the overall loss coefficient by 13.7%, the turbine's total-to-static efficiency by 5.2%, and the overall cycle efficiency from 8.78% to 9.02%.
format	article
author	Yohan Engineer Ahmed Rezk Abul Kalam Hossain
author_facet	Yohan Engineer Ahmed Rezk Abul Kalam Hossain
author_sort	Yohan Engineer
title	Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application
title_short	Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application
title_full	Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application
title_fullStr	Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application
title_full_unstemmed	Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application
title_sort	energy analysis and optimization of a small-scale axial flow turbine for organic rankine cycle application
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/d68eb29fa1714890a1f78ac56260e286
work_keys_str_mv	AT yohanengineer energyanalysisandoptimizationofasmallscaleaxialflowturbinefororganicrankinecycleapplication AT ahmedrezk energyanalysisandoptimizationofasmallscaleaxialflowturbinefororganicrankinecycleapplication AT abulkalamhossain energyanalysisandoptimizationofasmallscaleaxialflowturbinefororganicrankinecycleapplication
_version_	1718408286586273792

Energy analysis and optimization of a small-scale axial flow turbine for Organic Rankine Cycle application

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