Impact of Operating Conditions and Design Parameters on Gas Turbine Hot Section Creep Life

Eshati, S.; Ghafir, Mohammad Fahmi Abdul; Laskaridis, Panagiotis; Li, Y. G.

doi:10.1115/gt2010-22334

Cited by 7 publications

(8 citation statements)

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“…Figure 5 shows that the rupture time to creep failure for the LH 2 seems longer than the jet fuel, due to the fuel heating value on the expander after the combustion process is completed. There was a slight decrease in the turbine entry temperature, which would have also contributed to a longer life on the turbine blade, as the stress and thermal load values are lower than when the jet fuel was utilized in the turbofan engine as described by Eshati et al [33]. The assessment shows a 15% improvement in extended blade life, compared with jet fuel.…”

Section: Creep Life Estimationmentioning

confidence: 97%

“…Another assessment that has not been visible is understanding the impact of LH 2 utilization on aero-engine hot section blade life compared with jet fuel. Creep is one of the most common failure mechanisms that reduce component life [32][33][34]. Agbadede et al [35] provided a comparison for hydrogen and natural gas using an industrial gas turbine.…”

Section: System Descriptionmentioning

confidence: 99%

“…The stress model assumes a constant axial velocity along the blade's span, with the centrifugal load acting at the blade center of gravity. As the stress prediction varies along the blade span and chord, the blade is divided into sections, with the centrifugal force (CF) and stress value (σ) at each section given as [33]:…”

Section: Creep Life Assessmentmentioning

confidence: 99%

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Thermodynamic Performance and Creep Life Assessment Comparing Hydrogen- and Jet-Fueled Turbofan Aero Engine

et al. 2021

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There is renewed interest in hydrogen as an alternative fuel for aero engines, due to their perceived environmental and performance benefits compared to jet fuel. This paper presents a cycle, thermal performance, energy and creep life assessment of hydrogen compared with jet fuel, using a turbofan aero engine. The turbofan cycle performance was simulated using a code developed by the authors that allows hydrogen and jet fuel to be selected as fuel input. The exergy assessment uses both conservations of energy and mass and the second law of thermodynamics to understand the impact of the fuels on the exergy destruction, exergy efficiency, waste factor ratio, environmental effect factor and sustainability index for a turbofan aero engine. Finally, the study looks at a top-level creep life assessment on the high-pressure turbine hot section influenced by the fuel heating values. This study shows performance (64% reduced fuel flow rate, better SFC) and more extended blade life (15% increase) benefits using liquefied hydrogen fuel, which corresponds with other literary work on the benefits of LH2 over jet fuel. This paper also highlights some drawbacks of hydrogen fuel based on previous research work, and gives recommendations for future work, aimed at maturing the hydrogen fuel concept in aviation.

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Section: Creep Life Estimationmentioning

confidence: 97%

Section: System Descriptionmentioning

confidence: 99%

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Thermodynamic Performance and Creep Life Assessment Comparing Hydrogen- and Jet-Fueled Turbofan Aero Engine

et al. 2021

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“…Several approaches exist to predict the remaining lifetime, such as neural networks [4][5][6][7], finite element analysis (FEA) [8][9][10], and statistical methods [11]; however, in order to significantly enhance the accuracy of the lifetime prediction, it is necessary to estimate the lifetime in real time (on-line prediction) using actual conditions [12,13]. All of the previously cited approaches require a large amount of computing resources, making them not suitable for an on-line application; another limitation is that none of the cited approaches take into consideration the existing engine-to-engine differences and the performance deterioration.…”

Section: Introductionmentioning

confidence: 99%

A New Approach for Model Developing to Estimate Unmeasured Parameters in an Engine Lifetime Monitoring System

Maravilla¹,

Yepifanov²

2019

Gas Turbines - Control, Diagnostics, Simulation, and Measurements [Working Title]

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Monitoring systems to predict the remaining lifetime of gas turbine engines are a major field of investigation, in particular, the monitoring systems that allow an online prediction. This chapter introduces and analyzes a new approach to develop mathematical models to estimate unmeasured parameters in an engine lifetime monitoring system; these models in contrast to previously developed models allow an on-line monitoring of unmeasured parameters, which are necessary to perform an on-line lifetime prediction. The blade of a high-pressure turbine (HPT) of a twospool free turbine power plant is the test case. Several candidate models are developed for each unmeasured parameter; the best models are selected by their accuracy and robustness using the instrumental and truncation error as criteria. Ten faulty engine conditions are considered to analyze the model robustness. Two methods for model developing are compared; the first method uses physics-based models (proposed in this chapter), and the second method develops the models using the similarity concept (reference methodology). The results of the comparison show that the physics-based models are more robust to engine faults and overall they deliver a significantly more accurate prediction of the engine lifetime.

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“…However, in pursuit of such improved accuracy and reliability, model-based creep life estimation methods have become more and more interdisciplinary and multitasking [4][5][6][7][8]. However, in pursuit of such improved accuracy and reliability, model-based creep life estimation methods have become more and more interdisciplinary and multitasking [4][5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Creep Life Prediction for Aero Gas Turbine Hot Section Component Using Artificial Neural Networks

Ghafir

Li²,

Wang

2013

Journal of Engineering for Gas Turbines and Power

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Accurate and reliable component life prediction is crucial to ensure safety and economics of gas turbine operations. In pursuit of such improved accuracy and reliability, modelbased creep life prediction methods have become more complicated and demand higher computational time. Therefore, there is a need to find an alternative approach that is able to provide a quick solution to creep life prediction for production engines while at the same time maintain the same accuracy and reliability as that of the model-based methods. In this paper, a novel creep life prediction approach using artificial neural networks is introduced as an alternative to the model-based creep life prediction approach to provide a quick and accurate estimation of gas turbine creep life. Multilayer feed forward baekpropagation neural networks have been utilized to form three neural network-based creep life prediction architectures known as the range-based, functional-based, and sensor-based architectures. The new neural network creep life prediction approach has been tested with a model single-spool turboshaft gas turbine engine. The results show that good generalization can be achieved in all three neural network architectures. It was also found that the sensor-based architecture is better than the other two in terms of accuracy, with 98% of the post-test samples possessing prediction errors within ±0.4%.2 Artificial Neural Networks 2.1 Artificial Neural Networks. ANN is a well-established algorithm that involves a large number of processors operating in parallel, designed to mimic the architecture and function of biological neural systems. The most widely used ANN is the multilayer feed forward baekpropagation (MFBP) network [13], as shown in Fig. 1. The terms "feed forward" and "baekpropagation" indicate that the network has two processing elements, which are Journal of Engineering for Gas Turbines and Power

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Impact of Operating Conditions and Design Parameters on Gas Turbine Hot Section Creep Life

Cited by 7 publications

References 0 publications

Thermodynamic Performance and Creep Life Assessment Comparing Hydrogen- and Jet-Fueled Turbofan Aero Engine

Thermodynamic Performance and Creep Life Assessment Comparing Hydrogen- and Jet-Fueled Turbofan Aero Engine

A New Approach for Model Developing to Estimate Unmeasured Parameters in an Engine Lifetime Monitoring System

Creep Life Prediction for Aero Gas Turbine Hot Section Component Using Artificial Neural Networks

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