Investigation of three-shaft high-bypass-ratio engine performance and emission prediction using alternative fuels
Protecting the environment has become the main challenge in recent years specifically in aviation industries as they lead to the vulnerable energy crisis and simultaneously pose environmental concerns. With the stringent policies and legislations applied, many potential technological advancement pro...
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Main Author: | |
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Format: | Monograph |
Language: | English |
Published: |
2019
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Subjects: | |
Online Access: | http://irep.iium.edu.my/73833/1/RIGS%20FINAL%20REPORT.pdf http://irep.iium.edu.my/73833/ |
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Summary: | Protecting the environment has become the main challenge in recent years specifically in aviation industries as they lead to the vulnerable energy crisis and simultaneously pose environmental concerns. With the stringent policies and legislations applied, many potential technological advancement programs are well planned and found out drop-in alternative fuels can potentially help to meet the target. In response, the purpose of this research aims to numerically evaluate the feasibility of the alternative fuels in terms of performance for a conventional aero-gas turbine engine. The investigated contents encompass the evaluation of engine performance analysis and emission prediction analysis. This research served as an extension of the PhD work of the principle investigator. Engine performance analysis utilizes a Cranfield Univeristy in-house latest code version of PYTHIA for modeling a three-shaft high-bypass-ratio engine which is similar to RB211 variant at various off-design conditions. Focusing on NOx formation, the emission analysis was also carried out using a Cranfield University in-house HEPHAESTUS emission model prediction. Alternative fuels are expected to show much better engine performance with further reductions in NOx emission. Finally, the research brings together all the analyses and makes trade-offs assessment between the performance and emission by applying a Design of Experiment (DoE) method, to identify the factors main effects, their interactions and the best trade-off solutions. |
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