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 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%.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences > Aston Institute of Urban Technology and the Environment (ASTUTE)
College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > Aston Institute of Materials Research (AIMR)
College of Engineering & Physical Sciences > Sustainable environment research group
Additional Information: ©2021 Published by Elsevier Ltd.This is an open access article under the CC BY-NC-ND license(
Uncontrolled Keywords: Energy Conversion,ORC system,Optimization,Turbine Design,Turbine Performance,Mechanical Engineering,Fluid Flow and Transfer Processes,Condensed Matter Physics
Publication ISSN: 2666-2027
Last Modified: 19 Jun 2024 07:18
Date Deposited: 07 Oct 2021 11:04
Full Text Link:
Related URLs: https://www.sci ... 666202721000574 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2021-11
Published Online Date: 2021-11-06
Accepted Date: 2021-10-06
Authors: Engineer, Yohan
Rezk, Ahmed (ORCID Profile 0000-0002-1329-4146)
Hossain, A K (ORCID Profile 0000-0002-8713-8058)



Version: Accepted Version

Access Restriction: Restricted to Repository staff only

License: Creative Commons Attribution Non-commercial No Derivatives


Version: Published Version

License: Creative Commons Attribution Non-commercial No Derivatives

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