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Research Papers: Gas Turbines: Aircraft Engine

Optimal Architectures for Dry and Wet Gas-Turbine Engines

[+] Author and Article Information
Rebecca Zarin Pass

Energy Technology Area,
Lawrence Berkeley National Laboratory,
Berkeley, CA 94720
e-mail: rzpass@lbl.gov

Sankaran Ramakrishnan

Institute for Data, Systems and Society,
Massachusetts Institute of Technology,
Cambridge, MA 02139
e-mail: sankara@mit.edu

Chris Edwards

Department of Mechanical Engineering,
Stanford University,
Stanford, CA 94305
e-mail: cfe@stanford.edu

Contributed by the Aircraft Engine Committee of ASME for publication in the JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER. Manuscript received July 21, 2017; final manuscript received November 5, 2017; published online June 15, 2018. Assoc. Editor: Klaus Dobbeling.

J. Eng. Gas Turbines Power 140(9), 091202 (Jun 15, 2018) (12 pages) Paper No: GTP-17-1383; doi: 10.1115/1.4038794 History: Received July 21, 2017; Revised November 05, 2017

We systematically determine the maximally efficient manner of using water and air in a single-cycle steady-flow combustion gas turbine power plant. In doing so, we identify the upper limit to exergy efficiency for dry and wet gas turbine engines through architectures that employ regenerative work, heat, and matter transfers using imperfect practical devices. For existing device technology, the derived optimal architectures can theoretically achieve exergy efficiency above 65% without employing a bottoming cycle. This surpasses known efficiencies for both wet and combined cycles. We also show that when optimally used, nonreactive matter transfers, like water, provide an alternative, but not superior, thermal regeneration strategy to direct heat regeneration.

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Figures

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Fig. 1

Generalized cycle with flexible work, heat, and matter transfers

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Fig. 2

Equilibration surfaces for a methane–air system

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Fig. 3

Optimal work-and-heat regenerative cycle [2]

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Fig. 4

Simple-cycle gas-turbine engine, shown with two stages of compression and expansion

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Fig. 5

Introduction of a feed-forward matter transfer at an arbitrary pressure: (a) simple cycle without feed-forward and (b) simple cycle with feed-forward air

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Fig. 6

Effect of feed-forward transfer on exergy distribution

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Fig. 7

Introduction of a feedback matter transfer at an arbitrary pressure: (a) simple cycle without feedback, (b) simple cycle with feedback, and (c) feedback as a parallel cycle

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Fig. 8

Feedback effects on system performance: (a) effect of feedback pressure on system pressure and (b) effect of feedback pressure on exergy distribution

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Fig. 9

Comparison of reactant stream mixing locations: (a) mixing before compression and (b) compression before mixing

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Fig. 10

Exergy distribution for different water injection locations

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Fig. 11

Full architecture with water injection after intercooling

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Fig. 12

Efficiency-work curves of architectures with optimized parameters over a range of equivalence ratios and water quantities. Water percentages defined as mass of water with respect to mass of air. TIT = 1650 K in all cases.

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Fig. 13

Exergy distribution across different amounts of water injection. ϕ = 0.5, TIT = 1650 K: (a) internal exergy destruction and (b) external exergy destruction.

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Fig. 14

Optimal architecture for various allowable energy transfers

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