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Transient Optimization of a Gas Turbine EngineGas turbine engines are the primary power plants for modern commercial aircraft. Transients prompted by significant changes in thrust or power demand are common and unavoidable. Extreme transient scenarios such as those associated with a go-around during a landing attempt are possible and must be accounted for in the design of the engine and its controller. Engine transients tend to cause a reduction in compressor operability margin, which must be addressed by the engine control system and accounted for in the engine design to prevent events such as compressor stall/surge and combustor blow out. Transient operability concerns typically lead to compromises in the engine design that sacrifice efficiency and/or limit responsiveness. Transient operability is typically managed by logic that limits the fuel flow command. If this logic is not optimized, then the potential for valuable performance could be lost. This study presents a strategy for optimizing the transient limit logic and proposes a strategy for updating the control logic over the lifespan of the engine. The results demonstrate significant improvements in transient operability. For example, of the results at sea level static conditions demonstrated a 31% reduction in the usage of the high pressure compressor operability stack during a snap acceleration transient. Furthermore, a reinforcement learning algorithm is demonstrated to modify the transient logic as the engine degrades to minimize response time while respecting a prescribed compressor operability margin limit. A simple demonstration of the reinforcement learning algorithm resulted in a thrust response time reduction of ~11.8%.
Document ID
20220016302
Acquisition Source
Glenn Research Center
Document Type
Conference Paper
Authors
Jonathan L Kratz
(Glenn Research Center Cleveland, Ohio, United States)
Date Acquired
October 28, 2022
Subject Category
Aircraft Propulsion And Power
Meeting Information
Meeting: American Institute of Aeronautics and Astronautics (AIAA) Science & Technology (SciTech) Forum
Location: National Harbor, MD
Country: US
Start Date: January 23, 2023
End Date: January 27, 2023
Sponsors: American Institute of Aeronautics and Astronautics
Funding Number(s)
WBS: 109492.02.03.06.05
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Technical Review
NASA Technical Management
Keywords
transient
optimization
gas turbine engine
turbofan
operability
compressor
genetic algorithm
reinforcement learning
acceleration
deceleration
schedule
limit logic
control
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