Browsing by Author "Li, Yi-Guang"
Now showing 1 - 19 of 19
Results Per Page
Sort Options
Item Open Access An adaptive model-based framework for prognostics of gas path faults in aircraft gas turbine engines(Prognostics and Health Management Society, 2019-03-25) Alozie, Ogechukwu; Li, Yi-Guang; Wu, Xin; Shong, Xingchao; Ren, WenchengThis paper presents an adaptive framework for prognostics in civil aero gas turbine engines, which incorporates both performance and degradation models, to predict the remaining useful life of the engine components that fail predominantly by gradual deterioration over time. Sparse information about the engine configuration is used to adapt a performance model which serves as a baseline for implementing optimum sensor selection, operating data correction, fault isolation, noise reduction and component health diagnostics using nonlinear Gas Path Analysis (GPA). Degradation models which describe the progression of faults until failure are then applied to the diagnosed component health indices from previous run-to-failure cases. These models constitute a training library from which fitness evaluation to the current test case is done. The final remaining useful life (RUL) prediction is obtained as a weighted sum of individually-evaluated RULs for each training case. This approach is validated using dataset generated by the Commercial Modular Aero-Propulsion System Simulation (CMAPSS) software, which comprises both training and testing instances of run-to-failure sensor data for a turbofan engine, some of which are obtained at different operating conditions and for multiple fault modes. The results demonstrate the capability of improved prognostics of faults in aircraft engine turbomachinery using models of system behaviour, with continuous health monitoring dataItem Open Access Aero gas turbine flight performance estimation using engine gas path measurements(AIAA, 2015-01-05) Li, Yi-GuangMature gas turbine performance simulation technology has been developed in the past decades and, therefore, gas turbine performance at different ambient and operating conditions can be well predicted if good thermodynamic performance software and necessary engine performance information are available. However, the performance of gas turbine engines of the same fleet may be slightly different from engine to engine due to manufacturing and assembly tolerance and may change over time due to engine degradation. Therefore, it is necessary to monitor and track important performance parameters of gas turbine engines, particularly those that cannot be directly measured, to ensure safe operation of the engines. For that reason, a novel gas turbine performance estimation method using engine gas path measurements has been developed to predict and track engine performance parameters at different ambient, flight, degraded, and part-load operating conditions. The method is based on the influence coefficient matrix of thermodynamic performance parameters of gas turbine engines and the Newton Contrary to the conventional gas turbine off-design performance predictions where component characteristic maps are essential, it has the advantage that no component characteristic maps are required for the predictions and, therefore, it is relatively simple thermodynamically, fast in calculation, and desirable in engineering applications. It is able to make important invisible performance parameters visible to gas turbine users, which is a useful complement to current engine condition monitoring techniques. The developed method was applied to the performance prediction of a model gas turbine engine similar to EJ200 low-bypass turbofan engine running at different altitudes, Mach numbers, and part load, with and without degradation, by using simulated gas path measurements to test the effectiveness of the method. The results show that the method is able to predict the engine performance with good accuracy without the consideration of measurement noise and with slightly lower accuracy when measurement noise is included. It takes about 30 s for a typical prediction point, which is suitable for offline performance tracking and condition monitoring. Theoretically, the method can be applied to the performance estimation of any types of gas turbine engines.–Raphson mathematical algorithm.Item Open Access Aeroengine transient performance simulation integrated with generic heat soakage and tip clearance model(Cambridge University Press, 2022-03-11) Li, Zhuojun; Li, Yi-Guang; Sampath, SureshThe simulations and assessment of transient performance of gas turbine engines during the conceptual and preliminary design stage may be conducted ignoring heat soakage and tip clearance variations due to lack of detailed geometrical and structural information. As a result, problems with transient performance stability may not be revealed correctly, and corresponding design iterations would be necessary and costly when those problems are revealed at a detailed design stage. To make an engine design more cost and time effective, it has become important to require better transient performance simulations during the conceptual and preliminary design stage considering all key impact factors such as fuel control schedule, rotor dynamics, inter-component volume effect as well as heat soakage and tip clearance variation effects. In this research, a novel transient performance simulation approach with generically simplified heat soakage and tip clearance models for major gas path components of gas turbine engines including compressors, turbines and combustors has been developed to support more realistic transient performance simulations of gas turbine engines at conceptual and preliminary design stages. Such heat soakage and tip clearance models only require thermodynamic design parameters as input, which is normally available during such design stages. The models have been implemented into in-house transient performance simulation software and applied to a model twin-spool turbojet engine to test their effectiveness. Comparisons between transient performance simulated with and without the heat soakage and tip clearance effects demonstrate that the results are promising. Although the introduced heat soakage and tip clearance models may not be as accurate as that using detailed component geometrical information, it is able to include the major heat soakage and tip clearance effects and make the transient performance simulations and analysis more realistic during conceptual and preliminary engine design stage.Item Open Access Assessment of degradation equivalent operating time for aircraft gas turbine engines(Cambridge University Press, 2020-01-09) Alozie, Ogechukwu; Li, Yi-Guang; Diakostefanis, Michail; Wu, Xin; Shong, Xingchao; Ren, WenchengThis paper presents a novel method for quantifying the effect of ambient, environmental and operating conditions on the progression of degradation in aircraft gas turbines based on the measured engine and environmental parameters. The proposed equivalent operating time (EOT) model considers the degradation modes of fouling, erosion, and blade-tip wear due to creep strain, and expresses the actual degradation rate over the engine clock time relative to a pre-defined reference condition. In this work, the effects of changing environmental and engine operating conditions on the EOT for the core engine booster compressor and the high-pressure turbine were assessed by performance simulation with an engine model. The application to a single and multiple flight scenarios showed that, compared to the actual engine clock time, the EOT provides a clear description of component degradation, prediction of remaining useful life, and sufficient margin for maintenance action to be planned and performed before functional failure.Item Open Access Development and application of a preliminary design methodology for modern low emissions aero combustors(SAGE, 2020-04-23) Liu, Yize; Sun, Xiaoxiao; Sethi, Vishal; Li, Yi-Guang; Nalianda, Devaiah; Abbott, David; Gauthier, Pierre Q.; Xiao, Bairong; Wang, LuIn this article, a preliminary design framework containing a detailed design methodology is developed for modern low emissions aero combustors. The inter-related design elements involving flow distribution, combustor sizing, heat transfer and cooling, emission and performance are coupled in the design process. The physics-based and numerical methods are provided in detail, in addition to empirical or semi-empirical methods. Feasibility assessment on the developed work is presented via case studies. The proposed combustor sizing methodology produces feasible combustor dimensions against the public-domain low emissions combustors. The results produced by the physics-based method show a reasonable agreement with experimental data to represent NOx emissions at key engine power conditions. The developed emission prediction method shows the potential to assess current and future technologies. A two-dimensional global prediction on liner wall temperature distribution for different cooling systems is reasonably captured by the developed finite difference method. It can be of use in the rapid identification of design solutions and initiating the optimisation of the design variables. The altitude relight efficiency predicted shows that the method could be used to provide an indicative assessment of combustor altitude relight capability at the preliminary design phase. The methodology is applied and shows that it enables the automatic design process for the development of a conceptual lean staged low emissions combustor. The design evaluation is then performed. A sensitivity analysis is carried out to assess the design uncertainties. The optimisation of the air distribution and cooling geometrical parameters addresses the trade-off between the NOx emissions and liner wall cooling, which demonstrates that the developed work has potential to identify and solve the design challenges at the early stages of the design process.Item Open Access A dynamic performance diagnostic method applied to hydrogen powered aero engines operating under transient conditions(Elsevier, 2022-04-26) Chen, Yu-Zhi; Tsoutsanis, Elias; Xiang, Hen-Chao; Li, Yi-Guang; Zhao, Jun-JieAt present, aero engine fault diagnosis is mainly based on the steady-state condition at the cruise phase, and the gas path parameters in the entire flight process are not effectively used. At the same time, high quality steady-state monitoring measurements are not always available and as a result the accuracy of diagnosis might be affected. There is a recognized need for real-time performance diagnosis of aero engines operating under transient conditions, which can improve their condition-based maintenance. Recent studies have demonstrated the capability of the sequential model-based diagnostic method to predict accurately and efficiently the degradation of industrial gas turbines under steady-state conditions. Nevertheless, incorporating real-time data for fault detection of aero engines that operate in dynamic conditions is a more challenging task. The primary objective of this study is to investigate the performance of the sequential diagnostic method when it is applied to aero engines that operate under transient conditions while there is a variation in the bypass ratio and the heat soakage effects are taken into consideration. This study provides a novel approach for quantifying component degradation, such as fouling and erosion, by using an adapted version of the sequential diagnostic method. The research presented here confirms that the proposed method could be applied to aero engine fault diagnosis under both steady-state and dynamic conditions in real-time. In addition, the economic impact of engine degradation on fuel cost and payload revenue is evaluated when the engine under investigation is using hydrogen. The proposed method demonstrated promising diagnostic results where the maximum prediction errors for steady state and transient conditions are less than 0.006% and 0.016%, respectively. The comparison of the proposed method to a benchmark diagnostic method revealed a 15% improvement in accuracy which can have great benefit when considering that the cost attributed to degradation can reach up to $702,585 for 6000 flight cycles of a hydrogen powered aircraft fleet. This study provides an opportunity to improve our understanding of aero engine fault diagnosis in order to improve engine reliability, availability, and efficiency by online health monitoring.Item Open Access A hierarchical structure built on physical and data-based information for intelligent aero-engine gas path diagnostics(Elsevier, 2022-12-23) Zhao, Junjie; Li, Yi-Guang; Sampath, SureshFuture trends in engine health management (EHM) systems are information fusion, advanced analytical methods, and the concept of the Intelligent Engines. Machine Learning (ML)-based aero-engine gas path diagnostic methods are promising under the motivation of these trends. However, previous ML-based diagnostic structures are rarely applied in actual engineering practice because they are purely mathematical and lack physical insight or are limited by the error accumulation problem. Developing an accurate, flexible and interpretable intelligent diagnostic method has always posed a challenge, especially when physical knowledge is also available for more diagnostic information. Instead of modifying and applying existing ML methods for classification or regression, this study proposes a novel hierarchical diagnostic method to get insight into the physical systems, build hierarchies automatically, and recommend the classification structures. The proposed hierarchical diagnostic method is evaluated against a NASA model high-bypass two-spool turbofan engine. NASA's blind test case results show that Kappa Coefficient of the proposed hierarchical diagnostic method is 0.693 and is at least 0.008 higher than the other diagnostic methods in the open literature. It has been proved that the proposed method can quantify the dependence relationships between the fault classes for enhanced diagnostic information, recommend the best diagnostic structure for reduced complexity, and solve the error accumulation problem for improved diagnostic accuracy. The proposed method could support intelligent condition monitoring systems by effectively exploiting physical and data-based information for improved model interpretability, model flexibility, diagnostic visibility, diagnostic accuracy, and diagnostic reliability.Item Open Access Integrated gas turbine system diagnostics: components and sensor faults quantification using artificial neural networks(International Society for Air Breathing Engines (ISABE), 2017-09-11) Osigwe, Emmanuel O.; Li, Yi-Guang; Suresh, Sampath; Jombo, GbanaibolouThe role of diagnostic systems in gas turbine operations has changed over the past years from a single support troubleshooting maintenance to a more proactive integrated diagnostic system. This has become so, because detecting and fixing fault(s) on one gas turbine sub-system can trigger false fault(s) indication, on other component(s) of the gas turbine system, due to interrelationships between data obtained to monitor not only the GT single component, but also the integrated components and sensors. Hence, there is need for integration of gas turbine system diagnostics. The purpose of this paper is to present artificial neural network diagnostic system (ANNDS) as an integrated gas turbine system diagnostic tool capable of quantifying gas turbine component and sensor fault. A model based approach which consists of an engine model, and an associated parameter estimation algorithm that predicts the difference between the real engine data and the estimated output data is described in this paper. The ANNDS system was trained to detect, isolate and assess component(s) and sensor fault(s) of a single spool industrial gas turbine GT-PG9171ER. The ANN model was construed with multi-layer feed-forward back propagation network for component fault(s) and auto associative network for sensor fault(s). The diagnostic methodology adopted was a nested network structure, trained to handle specific objective function of detecting, isolating or quantifying faults. The data used for training, and testing purposes were obtained from a non-linear aero-thermodynamic model using PYTHIA; a Cranfield University in-house software. The data set analyzed in this paper represent samples of clean and faulty gas turbine components caused by fouling (0.5% - 6% degradation) and sensor fault(s) due to bias (±1% - ±7%). The results show the capability of ANN to detect, isolate (classification) and quantify multiple faults if properly trained.Item Open Access Investigation of aircraft engine performance utilizing various alternative fuels(IOP, 2019-10-24) Li, Yi-Guang; Khan, S. A.; Ismail, Ahmad FarisThe airlines are subjected to the energy crisis and have raised environmental issues at the same time. Future engine technology advances could decrease the effect on the environment and energy consumption. Alternative fuelspotentially assist in the reduction of engine emissions and hence lower the energy-related issues. This study presents analysis of the efficiency of aircraft engines as a function of thrust force, flow of the and specific fuel consumption (SFC) at distinct mixing ratios (40% and 100%) of African natural gas, Algae, Camelina, Jatropa, Diesel, Hydrogen, Synthetic paraffinic kerosene, UK natural gas at cruising altitude. In – house Cranfield University simulation codes, PYTHIA & TURBOMATCH have been used to investigate and model a three-shaft high bypass engine analogous to RB211 - 524. The engine model has been certified and authenticated in commercial aircraft with open works found in the Bio - Synthetic Paraffinic Kerosene test program.Blended fuel of Kerosene & hydrogen (KE+HY) fuels gives values of 331.6 KN,1.2577KG/S, and 6.9512 kg/kwh for net thrust force,the flow of fuel and specific fuel feastingat mingling ratio of 40 % respectively. However, at mixing ratio of 100% Blended fuel of Kerosene & hydrogen (KE+HY) fuels gives values of 339.01 KN, 0.800KG/S, and 4.333 kg/kwh for net thrust, fuel flow, and specific fuel consumption respectively. It is found that blended fuel of Kerosene &hydrogen (KE+HY) fuels give better engine performances as compared to other alternative fuels. However, Kerosene &diesel (KE+DI) fuels have shown a slight reduction in engine performance.Item Open Access Modelling of a three-shaft high-bypass-ratio engine performance and emission prediction using hydrogen fuel(BEIE&SP, 2019-05-25) Wan Yahya, M. Z.; Azami, M. H.; Savill, Mark; Li, Yi-Guang; Khan, S.A; Warimani, Mahammad SalmanThe price of oil has seen an unprecedented increase and the resulting demand for oil, especially from the transportation industries. The pollution emits from the vehicle has affected human health and environmental problems especially aviation industries because the emission covers much broader spectrums. Drop-in alternative fuels such as liquefied hydrogen fuel are believed to offer better engine performance and reduce the emission. An in-house computer tool, PYTHIA was used to model the performance of RB211 engine at a wide range of flight operations. Liquid hydrogen fuel will increase the thrust and the specific fuel consumption up to 63.9% reduction at higher speed. Liquid hydrogen fuel resulted in higher burning temperature which encourage the formation of NOx. At the sea level, it was found that EINOx was increased to about 5.5% when 20% blended ratio was used.Item Open Access Modelling the performance and emission prediction of RB211 aero-gas turbine engine fuelled by Jatropha-based biofuel(IOP Publishing: Conference Series / IOP Publishing, 2019-04-30) Azami, Muhammad Hanafi; Noorazman, Zahid; Savill, Mark; Li, Yi-Guang; Hilmi, Mohd RaziFossil fuel is one of the world vital energy resources. The development of transportation technologies increases the demand for petroleum derivative globally. Fossil fuel consumption produces emissions, which potentially harm the environment and human health. Many mitigations have been implemented to address the two main crises; the energy scarcity and environmental calamity. This paper will discuss on one of the potential solutions by analyzing the performance and emission prediction of aero-gas turbine engine fuelled by Jatropha-based biofuel. Performance analysis was made based on the thrust and specific fuel consumptions at different blended ratio percentages for various flight conditions. The three-shaft high-bypass-ratio engine model, which is identical to the Rolls Royce RB211-524 was used to model in an in-house Cranfield's University software, PYTHIA. PYTHIA is integrated with the TURBOMATCH performance evaluation programme by iterating the mass and energy balance for each engine component. The analysis is then continued to predict Nitrogen Oxides emission index (EINOx) at every flight conditions using an in-house Cranfield's University computer tool, HEPHAESTUS. HEPHAESTUS is an emission prediction software by using Zel'Dovich equations (for NOx) and models the emission by implementing a partially-stirred reactor (PSR) model and perfectly stirred reactor (PSRS) models at different zones in the combustor. Validation showed that HEPHAESTUS is able to capture a reasonable prediction as compared to the International Civil Aviation Organization (ICAO) databank. The performance the biofuel has shown an improvement in engine performance at higher percentage blended ratio but also increase the nitrous oxide indices emission slightlyItem Open Access Non-linear model calibration for off-design performance prediction of gas turbines with experimental data(Cambridge University Press, 2017-09-18) Tsoutsanis, Elias; Li, Yi-Guang; Pilidis, Pericles; Newby, Mike A.One of the key challenges of the gas turbine community is to empower the condition based maintenance with simulation, diagnostic and prognostic tools which improve the reliability and availability of the engines. Within this context, the inverse adaptive modelling methods have generated much attention for their capability to tune engine models for matching experimental test data and/or simulation data. In this study, an integrated performance adaptation system for estimating the steady-state off-design performance of gas turbines is presented. In the system, a novel method for compressor map generation and a genetic algorithm-based method for engine off-design performance adaptation are introduced. The methods are integrated into PYTHIA gas turbine simulation software, developed at Cranfield University and tested with experimental data of an aero derivative gas turbine. The results demonstrate the promising capabilities of the proposed system for accurate prediction of the gas turbine performance. This is achieved by matching simultaneously a set of multiple off-design operating points. It is proven that the proposed methods and the system have the capability to progressively update and refine gas turbine performance models with improved accuracy, which is crucial for model-based gas path diagnostics and prognostics.Item Open Access Performance degradation and component deterioration degree estimation for a turboshaft engine [Chinese language](Zhongguo Hangkong Xuehui,Chinese Society of Aeronautics and Astronautics, 2015-11-30) Huang, Kai-Ming; Li, Yi-Guang; Zhang, Wei; Feng, Xing; Cai, Jiang-bingTo monitor the performance and health conditions of a turboshaft engine during an endurance test, an engine mathematical model was set up and adapted to its real performance by adjusting component maps using a multiple-point performance adaption method. Gas path diagnostic analysis of the engine based on a non-linear gas path analysis (GPA) methodology was performed. In combination with field experiences, evaluation of the engine gas path component deterioration during an engine endurance test was carried out. The results indicated that the engine performance deviation and component deterioration varied over time. During initial phase of the test, the performance of the compressor and the compressor turbine deviated most rapidly then stabilized afterwards. As for the power turbine, the health was almost unchanged during the entire endurance test. The validation and experience of the GPA diagnostic technique prove that the technology can be applied into engine performance and health check for the evaluation of health of the turboshaft engine in its future serviceItem Open Access Performance simulation of a parallel dual-pressure once-through steam generator(Elsevier, 2019-02-08) Chen, Yu-Zhi; Li, Yi-Guang; Newby, Mike A.The increasing demand for electricity and concern about global warming mean that electric power generation is required to be more efficient, cleaner, and more cost-effective. Combined-cycle power plants have gradually replaced their simple-cycle counterparts to generate more useful power by adding a bottom cycle to recover more energy from prime mover exhaust gas. There are two types of devices used to produce steam—one is the conventional drum-type heat recovery steam generator, and the other is the once-through steam generator (OTSG). The performance simulation of the former is relatively mature but is more difficult for the later. In this research, a novel simulation method for the thermodynamic performance of a parallel dual-pressure OTSG under both design and off-design operating conditions has been developed. The method has been applied to an OTSG operating in a combined-cycle gas turbine power plant at Manx Utilities, Isle of Man in the UK to demonstrate the effectiveness of the method. Meanwhile, the OTSG performance variation caused by inlet gas energy variation and downstream steam turbine erosion are demonstrated. The simulation results of the OTSG show good agreement with field data. The proposed method may be useful for both researchers and engineers in relevant area.Item Open Access Performance-based fault diagnosis of a gas turbine engine using an integrated support vector machine and artificial neural network method(SAGE, 2018-11-18) Fentaye, Amare; Ul-Haq Gilani, Syed Ihtsham; Baheta, Aklilu Tesfamichael; Li, Yi-GuangAn effective and reliable gas path diagnostic method that could be used to detect, isolate, and identify gas turbine degradations is crucial in a gas turbine condition-based maintenance. In this paper, we proposed a new combined technique of artificial neural network and support vector machine for a two-shaft industrial gas turbine engine gas path diagnostics. To this end, an autoassociative neural network is used as a preprocessor to minimize noise and generate necessary features, a nested support vector machine to classify gas path faults, and a multilayer perceptron to assess the magnitude of the faults. The necessary data to train and test the method are obtained from a performance model of the case engine under steady-state operating conditions. The test results indicate that the proposed method can diagnose both single- and multiple-component faults successfully and shows a clear advantage over some other methods in terms of multiple fault diagnosis. Moreover, 5-8 sets of measurements have been used to assess the prediction accuracy, and only a 2.3% difference was observed. This result indicates that the proposed method can be used for multiple fault diagnosis of gas turbines with limited measurements.Item Open Access Review of modern low emissions combustion technologies for aero gas turbine engines(Elsevier, 2017-09-12) Liu, Yize; Sun, Xiaoxiao; Sethi, Vishal; Nalianda, Devaiah; Li, Yi-Guang; Wang, LuPollutant emissions from aircraft in the vicinity of airports and at altitude are of great public concern due to their impact on environment and human health. The legislations aimed at limiting aircraft emissions have become more stringent over the past few decades. This has resulted in an urgent need to develop low emissions combustors in order to meet legislative requirements and reduce the impact of civil aviation on the environment. This article provides a comprehensive review of low emissions combustion technologies for modern aero gas turbines. The review considers current high Technologies Readiness Level (TRL) technologies including Rich-Burn Quick-quench Lean-burn (RQL), Double Annular Combustor (DAC), Twin Annular Premixing Swirler combustors (TAPS), Lean Direct Injection (LDI). It further reviews some of the advanced technologies at lower TRL. These include NASA multi-point LDI, Lean Premixed Prevaporised (LPP), Axially Staged Combustors (ASC) and Variable Geometry Combustors (VGC). The focus of the review is placed on working principles, a review of the key technologies (includes the key technology features, methods of realising the technology, associated technology advantages and design challenges, progress in development), technology application and emissions mitigation potential. The article concludes the technology review by providing a technology evaluation matrix based on a number of combustion performance criteria including altitude relight auto-ignition flashback, combustion stability, combustion efficiency, pressure loss, size and weight, liner life and exit temperature distribution.Item Open Access Sliding mode control with system constraints for aircraft engines(Elsevier, 2019-09-19) Yang, Shu-Bo; Wang, Xi; Wang, Hao-Nan; Li, Yi-GuangThis paper proposes a constraint-tolerant design with sliding mode strategy to improve the stability of aircraft engine control. To handle the difficulties associated with the high-frequency switching laws, merely attenuating the chattering is far from satisfactory. System constraints on input, output, and input rate should be addressed in the design process. For a sort of uncertain nonlinear systems subjected to the constraints, sliding mode regulators are designed using Lyapunov analysis. A turbofan engine is adopted for simulation, which shows that the methodology developed in this paper can handle the speed tracking and limit protection problem in a stable fashion, despite the negative influence posed by the system constraints.Item Open Access Techno-economic evaluation and optimization of CCGT power plant: a multi-criteria decision support system(Elsevier, 2021-04-19) Chen, Yu-Zhi; Li, Yi-Guang; Tsoutsanis, Elias; Newby, Mike A.; Zhao, Xu-DongA key objective of the power generation industry is to achieve maximum economic benefit without over-consuming the life of power plants and over-maintaining its assets. From a CCGT power plant operator’s perspective, the stand-alone performance analysis of the plant is not enough to support the decision-making process due to the plethora of possible scenarios characterized by variable ambient conditions, engine health (fouling, erosion), electricity prices, and power demand. This study proposes a novel methodology to support decision-making for a CCGT power plant’s operational optimization. The comprehensive techno-economic performance evaluation is conducted by multidisciplinary optimization and decision-making to enhance information integration for the combined cycle power plant operated by Manx Utilities in the Isle of Man, UK. The decision support system has the capability to recommend the optimal operation schedules to plant operators. It recommends that the more severely degraded engine should run at a relatively lower power setting to decrease creep life consumption. The established power plant optimization framework has the potential to assist power plant operators in deciding the total power output and power split between gas turbines based on optimization results that considers both immediate thermo-economic benefits and life consumption. Finally, the proposed system can facilitate similar power plants to adjust daily operations to achieve thermo-economic and lifing benefitsItem Open Access Thrust rebalance to extend engine time on-wing with consideration of engine degradation and creep life consumption(American Society of Mechanical Engineers (ASME), 2023-09-28) da Mota Chiavegatto, Rafael; Li, Yi-GuangOver the years, airlines have consistently attempted to lower their operational costs and improve aircraft availability by applying various technologies. Engine maintenance expenses are one of the most substantial costs for aircraft operations, accounting for around 30% of overall aircraft operational costs. So, maximizing aircraft time between overhaul is crucial to lowering the costs. The engine time on-wing is often limited by the expiration of Life Limiting Parts, performance deterioration, maintenance schedule, etc. This paper presents a novel method of rebalancing the thrust of engines of an aircraft to maximize the time between overhauls of the aircraft considering the performance degradation and creep life consumption of the engines. The method is applied to a model aircraft fitted with two model engines similar to GT90 115B to test the feasibility of the method with one engine degraded and the other engine undegraded. The obtained results demonstrate that for the aircraft flying between London and Toronto with 5,000 nominal flight cycles given to the engines, the time on-wing of the degraded engine could drop from 5,000 to 2,460 flight days due to its HP turbine degradation (1% efficiency degradation 3% flow capacity degradation), causing the same level of drop of time between overhauls of the aircraft. The time on-wing of the degraded engine could increase from 2,460 flight days without thrust rebalance to 3,410 flight days with thrust rebalance, i. e. around 38.6% potential improvement for the time between overhauls of the aircraft at the expenses of increased creep life consumption rate of the clean engine. The proposed method could be applied to other aircraft and engines.