GT-ACYSS: Gas Turbine Arekret-Cycle Simulation Modelling for Training and Educational Purposes

[+] Author and Article Information
Emmanuel Osigwe

Cranfield University, Bedford, Bedfordshire, United Kingdom

Pericles Pilidis

Cranfield University, Bedford, Bedfordshire, United Kingdom

Theoklis Nikolaidis

Cranfield University, Bedford, Bedfordshire, United Kingdom

Suresh Sampath

Cranfield University, Bedford, Bedfordshire, United Kingdom

1Corresponding author.

ASME doi:10.1115/1.4043681 History: Received January 05, 2019; Revised April 29, 2019


This paper presents the modelling approach of a multi-purpose simulation tool called GT-ACYSS; which can be utilized for simulation of steady-state and pseudo transient performance of closed-cycle gas turbine plants. The tool analyses the design point performance as a function of component design and performance map characteristics predicted based on multi-fluid map scaling technique. The off-design point is analyzed as a function of design point performance, plant control settings and a wide array of other off-design conditions. GT-ACYSS can be useful educational tool since it allows the student to monitor gas path properties throughout the cycle without laborious calculations. It allows the user to have flexibility in selection of four different working fluids, and ability to simulate various single-shaft closed-cycle configurations, as well as the ability to carry out preliminary component sizing of the plant. The modelling approach described in this paper has been verified with case studies and the trends shown appeared to be reasonable when compared with reference data in the open literature, hence, can be utilized to perform independent analyses of any referenced single-shaft closed-cycle gas turbine plants. The results of case studies presented herein demonstrated that the multi-fluid scaling method of components and the algorithm of the steady state analysis were in good agreement for predicting cycle performance parameters (such as efficiency, and output power) with mean deviations from referenced plant data ranging between 0.1% and 1% over wide array of operations.

Copyright (c) 2019 by ASME
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