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Research Papers: Gas Turbines: Aircraft Engine

Multi-objective Optimization of Conceptual Rotorcraft Powerplants: Trade-off Between Rotorcraft Fuel Efficiency and Environmental Impact

[+] Author and Article Information
Fakhre Ali

Centre for Propulsion,
School of Aerospace,
Transport and Manufacturing,
Cranfield University,
Bedfordshire MK430AL, UK
e-mail: f.ali@cranfield.ac.uk

Konstantinos Tzanidakis

Center for Propulsion,
School of Aerospace,
Transport and Manufacturing,
Cranfield University,
Bedfordshire MK430AL, UK
e-mail: k.tzanidakis@cranfield.ac.uk

Ioannis Goulos

Center for Propulsion,
School of Aerospace,
Transport and Manufacturing,
Cranfield University,
Bedfordshire MK430AL, UK
e-mail: i.goulos@cranfield.ac.uk

Vassilios Pachidis

Center for Propulsion,
School of Aerospace,
Transport and Manufacturing,
Cranfield University,
Bedfordshire MK430AL, UK
e-mail: v.pachidis@cranfield.ac.uk

Roberto d'Ippolito

NOESIS Solutions,
Gaston Geenslaan, 11,
B4, Leuven 3001, Belgium
e-mail: roberto.dippolito@noesissolutions.com

1Corresponding author.

Contributed by the Aircraft Engine Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received August 22, 2014; final manuscript received October 29, 2014; published online December 17, 2014. Editor: David Wisler.

J. Eng. Gas Turbines Power 137(7), 071201 (Jul 01, 2015) (10 pages) Paper No: GTP-14-1508; doi: 10.1115/1.4029103 History: Received August 22, 2014; Revised October 29, 2014; Online December 17, 2014

This paper aims to present an integrated rotorcraft conceptual design and analysis framework, deployed for the multidisciplinary design and optimization of regenerative powerplant configurations in terms of rotorcraft operational and environmental performance. The proposed framework comprises a wide-range of individual modeling theories applicable to rotorcraft flight dynamics, gas turbine engine performance, and weight estimation as well as a novel physics-based, stirred reactor model for the rapid estimation of gas turbine gaseous emissions. A multi-objective particle swarm optimizer (mPSO) is coupled with the aforementioned integrated rotorcraft multidisciplinary design framework. The combined approach is applied to conduct multidisciplinary design and optimization of a reference twin engine light civil rotorcraft modeled after the Airbus-Helicopters Bo105 helicopter, operating on representative mission scenario. Through the implementation of a multi-objective optimization study, Pareto front models have been acquired, quantifying the optimum interrelationship between the mission fuel consumption and gaseous emissions for the representative rotorcraft and a variety of engine configurations. The acquired optimum engine configurations are subsequently deployed for the design of conceptual rotorcraft regenerative engines, targeting improved mission fuel economy, enhanced payload range capability, as well as improvements in the rotorcraft overall environmental impact. The proposed methodology essentially constitutes an enabler in terms of focusing the multidisciplinary design and optimization of rotorcraft powerplants within realistic, three-dimensional operations and toward the realization of their associated design trade-offs at mission level.

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Figures

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Fig. 1

HECTOR; architecture of integrated rotorcraft multidisciplinary design and optimization framework, deployed for the design analysis and optimization of conceptual rotorcraft powerplant configurations

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Fig. 2

(a) Reference PATM geographical definition; (b) time variations of deployed operational airspeed and altitude

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Fig. 3

(a) Sensitivity analysis for various engine and mission output parameters against engine OPR, (b) sensitivity analysis for various engine and mission output parameters against HEE; conceptual regenerated Bo105 helicopter, PATM

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Fig. 4

(a) RSM for engine SFCDP versus engine LPC PR and HPC PR, (b) RSM for mission NOx versus engine LPC PR and HPC PR; conceptual regenerated Bo105 helicopter, PATM

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Fig. 5

(a) RSM for engine SFCDP versus engine HPC PR and HEE; (b) RSM for mission NOx versus engine HPC PR and HEE; conceptual regenerated Bo105 helicopter, PATM

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Fig. 6

(a) RSM for EW versus engine W· and HEE, (b) Pareto front models corresponding to minimum MFB and minimum mission NOx inventory; conceptual regenerated Bo105 helicopter, PATM

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Fig. 7

(a) Comparison between baseline and three selected Pareto front models; mission level parameters and deltas; Bo105 helicopter, PATM, (b) fuel flow production rate comparison between baseline and three selected Pareto front models, (c) NOx production rate comparison between baseline and three selected Pareto front models; conceptual regenerated Bo105 helicopter, PATM

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