Hakan Aygün

Exergetic modeling with machine learning approaches for turbojet engine and its core components

Muhammed Cemal Guc, Hakan Aygün, Mehmet Kirmizi

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Investigation of effects of component and fuel parameters on performance of jet engine and main units

Mehmet Kirmizi, Hakan Aygün

The studies addressing the fuel efficiency of jet engines are of critical significance in terms of mitigating the environmental impact of aviation. In this context, examining aviation engines at the component level reveals the fuel consumption of engine behavior more clearly. In …

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Prediction of aircraft engine parameters from real sensor values using machine learning throughout flight envelope

Hakan Aygün, Suat Toraman, Ömer Osman Dursun

In recent years, the prediction of aircraft engine parameters using machine learning methods has become increasingly common and widely preferred. The forecasting of aircraft engine parameters based on actual flight data is of great importance in terms of maintenance facilitation and safety. …

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Component-based exergy modeling of three spool turboprop engine depending on the flight conditions

Onur Yüksel, Hakan Aygün

Aero gas turbine engines, given their key role in aviation, have parameters that depend on flight conditions, and those parameters are extensively modeled using several approaches. Recently, energy and exergy metrics have revealed the engine’s characteristics. In this study, flight-condition- based efficiency …

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Performance searching of an experimental micro turbojet engine via modeling-based optimization approaches

Ulaş Kılıç, Hakan Aygün, Mehmet Kirmizi, Kadir Dönmez et autres

Abstract In aviation studies, optimizing jet engine performance is becoming increasingly prominent through experimental analysis. The importance of this study lies in obtaining experimental data from a micro turbojet engine by measuring several engine sensors. The main goal is to optimize engine …

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An RL-Guided Hybrid Forecasting Framework for Aircraft Engine RUL and Performance Emission Prediction

Ukbe Üsame UÇAR, Hakan Aygün

In this paper, a new hybrid prediction method is proposed for estimating remaining useful life, emissions, and performance parameters using experimental data obtained from a micro-turbojet engine. Experiments were conducted under various rotational speed conditions, yielding a total of 342 measurement points. …

A Next-Generation Hybrid Approach for Data-Driven Fuel-Efficient Flight Control of Commercial Aircraft

Ukbe Üsame UÇAR, Zülfü KUZU, Hakan Aygün

In this study, a novel hybrid optimization approach is proposed to minimize the fuel consumption of commercial aircraft by taking flight-related and meteorological constraints into account during the cruise phase. The new method, the Decision Tree–Robust Multiple Regression–Harris Hawks Optimization Algorithm (DRHA), …

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Forecasting efficiency parameters of an experimental turbojet engine by a hybrid deep learning approach

Hakan Aygün, Ömer Osman Dursun, Kadir Dönmez, Oguzhan Sahin et autres

Abstract Forecasting several parameters using machine learning algorithms for micro turbojet engines (MTEs) is of high importance for characterizing engine behavior at different run regimes, thereby facilitating research and design processes. In this study, the MTE is experimentally operated under different operating …

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Component-based exergy modeling of three spool turboprop engine depending on the flight conditions

Onur Yüksel, Hakan Aygün

Modeling of energy and emission metrics of a turboshaft engine with hybrid algorithm involving machine learning and metaheuristic approaches

Ukbe Üsame UÇAR, Hakan Aygün

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Analysis of energy and emission metrics for an experimental turbojet engine by regression approach

Hamza Ezgin, Mehmet Kirmizi, Ümit Çelik, Hakan Aygün

The common usage of micro turbojet engines has sparked attention on these systems due to their unique advantages, which enable insight into the characteristics of different scaled turbojet engines. In this study, 930 data points regarding an experimental turbojet engine are obtained …

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Prediction of noise of commercial aircraft based on itself specifications by using machine learning methods

Suat Toraman, Ömer Osman Dursun, Hakan Aygün

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