Browsing by Author "Li, Yiguang"

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    Abrupt fault detection and isolation for gas turbine components based on a 1D convolutional neural network using time series data
    (AIAA, 2020-08-17) Zhao, Junjie; Li, Yiguang
    The FDI step identifies the presence of a fault, its level, type, and possible location. Gas turbine gas-path fault detection and isolation can improve the availability and economy of gas turbine components. Data-driven FDI methods are studied in this paper. Some notable gas turbine FDI challenges include: insensitivity to operating conditions, robust separation of faults, noisy sensor readings and missing data, reliable fault detection in time-varying conditions, and the influence of performance gradual deterioration. For conventional ML methods, the problem with handling time series data is its volume and the associated computational complexity; therefore, the available information must be appropriately compressed via the transformation of high-dimensional data into a low-dimensional feature space with minimal loss of class separability. In order to improve the detection and isolation sensitivity, this paper develops a method for FDI based on CNNs. Work in this paper includes: (1) Defining the problem and assembling a dataset. (2) Preparing data for training, validation and test: data generation, feature engineering, data pre-processing, data formatting. (3) Building up the model. (4) Training and validating the model (evaluation protocol). (5) Optimizing: a. deciding the model size. b. regularizing the model by getting more training data, reducing the capacity of the network, adding weight regularization or adding dropout. c. tuning hyperparameters. (6) Evaluation.
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    Aircraft engine transient performance modelling with heat soakage effects
    (Cranfield University, 2019-11) Li, Zhuojun; Li, Yiguang
    Transient performance design and assessment is a very crucial step of aircraft engine development, especially for acceleration and deceleration process. Normally, the assessment of transient performance stability would be done during the detained design stage while component design parameters are available. As a result, design iterations might be necessary and costly if the transient performance assessment is not satisfactory. To make engine design more cost and time efficiently, it has become more and more important to assess the transient performance stability at conceptual and preliminary design stage with the inclusion of key impact factors such as fuel control schedule, rotor dynamics, volume dynamics and heat soakage. However, due to the lack of detailed engine structural and geometrical information at the initial design stage, such transient performance simulation and assessment may have to ignore heat soakage effects. Therefore, in this paper, a novel generically simplified heat soakage and tip clearance model for three major gas path components of gas turbine engines including compressors, turbines and combustors and has been developed to support more realistic transient performance simulation of gas turbine engines at conceptual and preliminary design stage. Such heat soakage model including heat transfer and tip clearance only requires thermodynamic design parameters as input, which is normally available during such design stages. This generic heat soakage method has been applied to two engine models to test its effectiveness through an in-house developed performance code. The case study of heat-soakage effects could demonstrate that results are promising and the simplified heat soakage model is satisfactory.
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    Application of CFD zooming for preliminary design of a low emissions combustor.
    (2018-10) Sun, Xiaoxiao; Sethi, Vishal; Li, Yiguang
    The design of low emissions combustors is particularly challenging as there is a requirement to deliver designs that meet a large number of performance, emissions and operability (often conflicting) objectives. There is an increasing need for combustor preliminary design and performance tools which can be used in the early phases of the design process for rapid design space exploration thereby reducing the risk and cost in the long term. Although both reduced order models and higher fidelity tools have been widely used for preliminary design independently, significant benefit can be derived from using a multi-fidelity modelling approach to address the limitation of reduced order model (accuracy) and high fidelity CFD (time and cost). To the author’s best knowledge there is no information in the public domain related to the coupling of reduced order models with higher fidelity 3D CFD multi-fidelity modelling tools for low emissions gas turbine combustion systems. Such a tool has a potential to offer a good compromise between modelling accuracy and computational expense. In this PhD research, a novel multi-fidelity zooming combustor preliminary design method is proposed. The method uses design outcomes of an existing reduced order model based design tool to construct CFD models for a series of RANS simulations. A case study for the design of a Lean Direct Injection Partially Premixed combustor was conducted to identify the limitations of an existing reduced order modelling approach. Dedicated CFD simulations were performed to demonstrate that improved methods/models/correlations can be derived from these higher fidelity simulations to refine the existing reduced order model. The main research contributions are summarised below: External aerodynamics – Performance is sensitive to inlet velocity profiles, the effect of which cannot be reflected in ROMs, realistic compressor outlet profiles is needed instead of generic turbulent pipe flow profiles. – Performance maps were generated from CFD which include more degrees of freedom and suggest a different ‘optimum locus’ than 1D correlations. Fuel injector initial conditions – The Sauter Mean Diameter calculated from correlations in the ROM is not suitable to be used as injection initial condition. Detailed correlations on jet breakup were used to generate representative droplet size and velocity for different nozzle designs and conditions. – Swirler flow split correlations does not account for flow turning in the venturi and the pre-mixer, coarse mesh CFD was sufficient to generate more accurate flow splits among different stages. Reacting flow – The initial 10 fuel nozzle ports design from the ROM was not sufficient for good mixing quality at the main stage, which resulted in higher flame temperature. The number was increased to 16, which provides more uniform flame distribution at the circumferential direction. – Three of the four methods used to generate the time delay provides consistent results. The time delay was used as an input of the ROM thermoacoustic analysis model. – The reactor layout can be better customised for emissions prediction with extra zones within the pilot injector and the dilution zone to account for reaction and recirculation. – Combustor cooling design was refined without modifying the variables of ROM, in which circumferential distribution was not captured. Simplified re-fining method was developed at less computational expense compared to complete Conjugate Heat Transfer simulations with the radiation model. Based on these findings, the reduced order design tool could be refined once the data from all parametric study cases are extracted and incorporated in the model, which is recommended as the future development of the work. The CFD model constructed could also be used to initiate higher fidelity Large Eddy Simulation.
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    Convolutional neural network denoising autoencoders for intelligent aircraft engine gas path health signal noise filtering
    (American Society of Mechanical Engineers, 2022-10-31) Zhao, Junjie; Li, Yiguang; Sampath, Suresh
    Removing noise from health signals is critical in gas path diagnostics of aircraft engines. An efficient noise filtering/denoising method should remove noise without using future data points, preserve important changes, and promote accurate diagnostics without time delay. Machine Learning (ML)-based methods are promising for high fidelity, accuracy, and computational efficiency under the motivation of Intelligent Engines. However, previous ML-based denoising methods are rarely applied in actual engineering practice because they cannot accommodate time series and cannot effectively capture important changes or are limited by the time delay problem. This paper proposes a Convolutional Neural Network Denoising Autoencoder (CNN-DAE) method to build a denoising autoencoder structure. In this structure, a convolutional operation is used to accommodate time series, and causal convolution is introduced to solve the problem of using future data points. The proposed denoising method is evaluated against NASA's Propulsion Diagnostic Method Evaluation Strategy (ProDiMES) software. It has been proved that the proposed method can accommodate time series, remove noise for improved denoising accuracy and preserve the important changes for enhanced diagnostic information. NASA's blind test case results show that Kappa Coefficient of a common diagnostic method using the processed data is 0.731 and is at least 0.046 higher than the other diagnostic methods in the open literature. Processing health signals using the proposed method would significantly promote accurate diagnostics without time delay. The proposed method could support intelligent condition monitoring systems by exploiting historical information for improved denoising and diagnostic performance.
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    Creep-life usage analysis and tracking for industrial gas turbines
    (AIAA, 2017-07-14) Saturday, Egbigenibo Genuine; Li, Yiguang; Newby, Michael A.
    Creep-life usage analysis and tracking of first-stage turbine rotor blades of an aeroderivative industrial gas-turbine engine are investigated in this study. An engine performance model is created, and blade thermal and stress models are developed for the calculation of the blade material temperatures and stresses at different sections of the blade. A creep-life model is developed based on the Larson–Miller parameter method by taking inputs from the thermal and stress models. An integrated creep-life estimation system is developed by bringing together the engine performance model, the blade thermal and stress models, the creep-life model, and a data acquisition and preprocessing model. Relative creep-life consumption analysis using new concepts developed in this research is introduced for the analysis of creep-life consumption of the gas-turbine engine operating for a period of time; these concepts include equivalent creep life and equivalent creep factor. The developed algorithms have been applied to the creep-life tracking of an aeroderivative gas-turbine engine using its field test data. The results show that it is able to provide a quick evaluation and tracking of engine creep-life consumption and provide very useful information for gas-turbine operators to support their operation optimization and creep-life consumption monitoring.
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    Diagnostics of power setting sensor fault of gas turbine engines using genetic algorithm
    (Cambridge University Press, 2017-07-03) Li, Yiguang
    Gas path diagnostics is one of the most effective condition monitoring techniques in supporting condition-based maintenance of gas turbines and improving availability and reducing maintenance costs of the engines. The techniques can be applied to the health monitoring of different gas path components and also gas path measurement sensors. One of the most important measurement sensors is that for the engine control, also called the power setting sensor, which is used by the engine control system to control the operation of gas turbine engines. In most of the published research so far, it is rarely mentioned that faults in such sensors have been tackled in either engine control or condition monitoring. The reality is that if such a sensor degrades and has a noticeable bias, it will result in a shift in engine operating condition and misleading diagnostic results. In this paper, the phenomenon of a power-setting sensor fault has been discussed and a gas path diagnostic method based on a Genetic Algorithm (GA) has been proposed for the detection of power-setting sensor fault with and without the existence of engine component degradation and other gas path sensor faults. The developed method has been applied to the diagnostic analysis of a model aero turbofan engine in several case studies. The results show that the GA-based diagnostic method is able to detect and quantify the power-setting sensor fault effectively with the existence of single engine component degradation and single gas path sensor fault. An exceptional situation is that the power-setting sensor fault may not be distinguished from a component fault if both faults have the same fault signature. In addition, the measurement noise has small impact on prediction accuracy. As the GA-based method is computationally slow, it is only recommended for off-line applications. The introduced GA-based diagnostic method is generic so it can be applied to different gas turbine engines. This paper will be presented at the ISABE 2017 Conference, 5-8 September 2017, Manchester, UK.
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    Gas path diagnostics for compressors
    (Cranfield University, 2012-05) Salamat, Reza; Li, Yiguang
    The use and application of compressors cannot be overemphasized in the aeronautical and oil & gas industries. Yet research works in sufficient depth has not been conducted previously to analyze their actual behaviour under degraded or even new conditions in operation. For the purpose of degradation modeling and simulation, a compressor model was set up using thermodynamic equations and affinity laws representing the characteristics of a clean compressor. HYSYS was used for degradation modeling analysis by implanting known linear and nonlinear degradation trends for an operating point and taking the compressor measurement changes. It was then assumed the degradation levels are unknown and these were established by applying the compressor health indices to the new compressor map. A diagnostic method for compressors was developed where the prediction in degradation levels were compared for diagnostic purposes. By applying a unique “successive iteration method” to a real gas site compressor data at various speeds, a compressor performance adaptation technique has been developed in this thesis which maps out the actual performance of the compressor shows the errors in performance prediction has been reduced from 5-15% to a minimum. This performance adaptation method allows the compressor performance map to be adapted against field data of a compressor for a range of speeds. All data were corrected to a common datum and GPA Indices were utilised for the evaluation of confidence in the established method. By observing the centrifugal compressor performance data from 2006 to 2010, the actual compressor degradation was quantified and modeled by trending techniques for diagnostic and prognostic purposes so that the operator can plan ahead for maintenance by knowing an estimate for the actual health of the compressor at any time. The major conclusions are that the performance adaptation developed for the site compressor and the diagnostic technique by data trending has been successful. And estimation of degradation in health indicators (throughput, pressure ratio and efficiency drops) by scaling the measurable parameters is a useful tool for diagnostic purposes.
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    Gas turbine and sensor fault diagnosis with nested artificial neural networks
    (ASME, 2004) Xiradakis, N; Li, Yiguang
    Accurate gas turbine diagnosis relies on accurate measurements from sensors. Unfortunately, sensors are prone to degradation or failure during gas turbine operations. In this paper a stack of decentralised artificial neural networks are introduced and investigated as an approach to approximate the measurement of a failed sensor once it is detected. Such a system is embedded into a nested neural network system for gas turbine diagnosis. The whole neural network diagnostic system consists of a number of feedforward neural networks for engine component diagnosis, sensor fault detection and isolation; and a stack of decentralised neural networks for sensor fault recovery. The application of the decentralised neural networks for the recovery of any failed sensor has the advantage that the configuration of the nested neural network system for engine component diagnosis is relatively simple as the system does not take into account sensor failure. When a sensor fails, the biased measurement of the failed sensor is replaced with a recovered measurement approximated with the measurements of other healthy sensors. The developed approach has been applied to an engine similar to the industrial 2-shaft engine, GE LM2500+, whose performance and training samples are simulated with an aero-thermodynamic modelling tool — Cranfield University’s TURBOMATCH computer program. Analysis shows that the use of the stack of decentralised neural networks for sensor fault recovery can effectively recover the measurement of a failed sensor. Comparison between the performance of the diagnostic system with and without the decentralised neural networks shows that the sensor recovery can improve the performance of the neural network engine diagnostic system significantly when a sensor fault is present. Copyright © 2004 by ASME
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    Gas turbine diagnosis using a fault isolation enhanced GPA
    (ASME, 2004-07) Li, Yiguang
    Gas Path Analysis (GPA) and its different derivatives have been developed for more than thirty years and used widely and successfully by many gas turbine manufacturers and operators. In gas turbine gas path component diagnosis, it has been recognized for a long time that GPA would be more successful if degraded components could be located. Unfortunately, only the deviation of measurable parameters is monitored in operation and information about the degraded components is normally not available. In this research, a two-step diagnostic approach is introduced, where a pattern matching method is used first and further developed to isolate degraded components; then Gas Path Analysis is applied to assess the quantity of degradation. A gas turbine performance simulation program, Cranfield University TURBOMATCH, has been modified to simulate the diagnostic process. A model gas turbine engine similar to Rolls-Royce aero AVON is used to test the effectiveness of the approach. It is found that the developed fault isolation method can isolate degraded components accurately and enhance the effectiveness of the quantitative assessment of the degradation with Gas Path Analysis (GPA) in gas turbine diagnostics. Copyright © 2004 by ASME
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    Hot section components life usage analyses for industrial gas turbines
    (Cranfield University, 2015-11) Saturday, Egbigenibo Genuine; Li, Yiguang
    Industrial gas turbines generally operate at a bit stable power levels and the hot section critical components, especially high pressure turbine blades are prone to failure due to creep. In some cases, plants are frequently shut down, thus, in addition to creep low cycle fatigue failure equally sets in. Avoiding failure calls for proper monitoring of how the lives of these components are being consumed. Efforts are thus being made to estimate the life of the critical components of the gas turbine, but, the accuracy of the life prediction methods employed has been an issue. In view of the above observations, in this research, a platform has been developed to simultaneously examine engine life consumption due to creep, fatigue and creep-fatigue interaction exploiting relative life analysis where the engine life calculated is compared to a reference life in each failure mode. The results obtained are life analysis factors which indicate how well the engine is being operated. The Larson-Miller Parameter method is used for the creep life consumption analysis, the modified universal slopes method is applied in the low cycle fatigue life estimation while Taira's linear accumulation method is adopted for creep-fatigue interaction life calculation. Fatigue cycles counting model is developed to estimate the fatigue cycles accumulated in any period of engine operation. Blade thermal and stress models are developed together with a data acquisition and pre-processing module to make the life calculations possible. The developed models and the life analysis algorithms are implemented in PYTHIA, Cranfield University's in-house gas turbine performance and diagnostics software to ensure that reliable simulation results are obtained for life analysis. The developed life analysis techniques are applied to several months of real engine operation data, using LM2500+ engine operated by Manx Utilities at the Isle of Man to test the applicability and the feasibility of the methods. The developed algorithms provide quick evaluation and tracking of engine life. The lifing algorithms developed in this research could be applied to different engines. The relative influences of different factors affecting engine life consumption were investigated by considering each effect on engine life consumtion at different engine operation conditions and it was observed that shaft power level has significant impact on engine life consumption while compressor degradation has more impact on engine life consumption than high pressure turbine degradation. The lifing methodologies developed in this work will help engine operators in their engine conditions monitoring and condition-based maintenance.
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    Modelling the performance of aero-gas turbine engine using algae-based biofuel with emission prediction
    (IOP Publishing: Conference Series / IOP Publishing, 2019-04-30) Azami, Muhammad Hanafi; Zaki, Muhamad; Savill, Mark; Li, Yiguang
    The world oil consumption is at the peak where the fuel price is insubstantial and can increase dramatically due to economic, social, and political factors andunprecedentedstability.Since fuel resourcesare scarce, it is an urgent need to find alternative fuel. Biofuel is one of the favorable choices in the market. Algae-based biofuel is the fourth generation of biofuel where it does not compete with the food production and it has myriad of advantages.These abundant algae are easy to cultivate and researchers found that algae-based biofuel is capable of reducing engine emission. This paper modelled the RB211aero-gas turbine engine by utilizing algae-based biofuel with various blended percentageratios at different flight conditions. Cranfield’s University in-house software, PYTHIA,and HEPHAESTUSare used to model the engine performance and emission prediction respectively.PYTHIA programme uses a modified Newton-Raphson convergence technique in the zero-dimensional steady-state model for both design and off-design conditions. Meanwhile, HEPHAESTUSsoftware uses the Zeldovich 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.Results have shown that thrust force produced is increasing at higher blended percentage ratio of algae biofuel. Through emission analysisprediction, generally,the nitrous oxide emission formation is lower at a higher altitude during the cruising. Results also predicted that higher percentage blended ratio of algae biofuel also reduces the emission formation.
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    Performance adaptation of gas turbines for power generation applications
    (Cranfield University, 2010-06-29) Tsoutsanis, Elias; Li, Yiguang; Pilidis, Pericles; Newby, Michael A.
    One of the greatest challenges that the world is facing is that of providing everyone access to safe and clean energy supplies. Since the liberalization of the electricity market in the UK during the 1990s many combined cycle gas turbine (CCGT) power plants have been developed as these plants are more energy efficient and friendlier to the environment. The core component in a combined cycle plant is the gas turbine. In this project the MEA’s Pulrose Power Station CCGT plant is under investigation. This plant cronsists of two aeroderivative LM2500+ gas turbines of General Electric for producing a total of 84MW power in a combined cycle configuration. Cont/d.
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    Prediction and analysis of impact of thermal barrier coating oxidation on gas turbine creep life
    (American Society of Mechanical Engineers, 2016-08-02) Ogiriki, E. A.; Li, Yiguang; Nikolaidis, Theoklis
    Thermal barrier coatings (TBCs) have been widely used in the power generation industry to protect turbine blades from damage in hostile operating environment. This allows either a high turbine entry temperature (TET) to be employed or a low percentage of cooling air to be used, both of which will improve the performance and efficiency of gas turbine engines. However, with continuous increases in TET aimed at improving the performance and efficiency of gas turbines, TBCs have become more susceptible to oxidation. Such oxidation has been largely responsible for the premature failure of most TBCs. Nevertheless, existing creep life prediction models that give adequate considerations to the effects of TBC oxidation on creep life are rare. The implication is that the creep life of gas turbines may be estimated more accurately if TBC oxidation is considered. In this paper, a performance-based integrated creep life model has been introduced with the capability of assessing the impact of TBC oxidation on the creep life and performance of gas turbines. The model comprises of a thermal, stress, oxidation, performance, and life estimation models. High pressure turbine (HPT) blades are selected as the life limiting component of gas turbines. Therefore, the integrated model was employed to investigate the effect of several operating conditions on the HPT blades of a model gas turbine engine using a creep factor (CF) approach. The results show that different operating conditions can significantly affect the oxidation rates of TBCs which in turn affect the creep life of HPT blades. For instance, TBC oxidation can speed up the overall life usage of a gas turbine engine from 4.22% to 6.35% within a one-year operation. It is the objective of this research that the developed method may assist gas turbine users in selecting the best mission profile that will minimize maintenance and operating costs while giving the best engine availability.
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    Review of more electric engines for civil aircraft
    (Springer, 2022-05-12) Liu, Yixiong; Mo, Da; Nalianda, Devaiah; Li, Yiguang; Roumeliotis, Ioannis
    More electric engines (MEEs) and more electric aircraft are mainly implemented to address the global warming issue and make engines more fuel efficient. Developing technology has made them applicable. This paper presents a detailed introduction to the MEE for civil aircraft, including its architecture, characteristics and performance, as well as the potential benefits of fuel consumption and emissions reduction. It is obvious that the adoption of electric components, such as active magnet bearings, electric starters and generators and electric fuel pumps, is beneficial. It is especially advantageous when mechanical, hydraulic and pneumatic systems with great weight and complex structures are eliminated. Moreover, the exploration of electric propulsion systems indicates that the potential profits are large and tempting. The challenges and technology bottlenecks for MEEs are also discussed. With the further development of battery and motor technology, the MEE will undoubtedly play a dominant role in the civil aircraft market.
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    Three-Dimensional Flow and Performance Simulation of Multistage Axial Flow Compressors
    (Cranfield University, 2000-03) Li, Yiguang; Elder, R. L.; Tourlidakis, A.
    \Yith the current develop111ent in computer technology and Computational Fluid D)"n<'tlllics techniques, t.he si11utlation within axial flow compressors becomes 1110re and 1110re pract.ical and beneficial to the compressor designs. Due to the insufficient capabilit)" of today's COll1put.ers for three-dimensional unsteady flow 1110delling of 111Ult i~Llg(' axial flow compressors, sophisticated models of steady state flow and perfor111ance 1110delling of the C0111prcssors deserve to be thoroughly investigated. In l1utltistage C0111pressor sinlulations with steady state methods, frame of reference is fixed on blades and the c0111putational domains for rotors and stators haye relati\"e rotation. One of the difficulties in such simulations is how to pass information across the interfaces between blade rows without losing continuity. Two 111ajor stead)" state modelling approaches, a mixing plane approach based on Denton's circu111ferentially non-uniform mixing plane model and a deterministic stress approach based on Adamczyk's average passage model, are investigated and compared with each other through the flow predictions of the third stage of Cranfield Low Speed Research Compressor at peak efficiency operating condition. In the deterministic stress approach, overlapped solution domains are introduced to calculate deterministic stresses in order to "close" the time-averaged governing equation system and the influence of the downstream blade row of the blade row under investigation has to be imposed through the simulation of bodyforce and blade blockage effect of the downstream blade row. An effective method of simulating bodyforce and blade blockage effect has been developed and proven to be simple in programming. ConYentionally, boundary conditions are specified in CFD calculations based on experimental data or other empirical calculations. By taking advantage of the special flow features in rear stages of multistage axial flow compressors where each rear stage behaves like a repeating stage of its neighbouring stages in terms of flow pattern at the inlet and the exit of these stages, a repeating stage model has been developed aiming at significantly simplifying the boundary conditions when simulating rear stages of a multistage axial flow compressor with only mass flow rate and stage exit average static pressure required as global input. A computer simulation system 1'/ STurbo3D has been developed to investigate a11d assess different steady state simulation models within multistage compressor environment. It has been proven that with the mixing plane model M STurbo3D is able to predict flows in multistage low speed axial flow compressors with acceptable accuracy. Application of the repeating stage model to the third stage of LS RC shows that the prediction with this model has equivalent accuracy to the prediction with the conventional boundary setting, and proves that the repeating stage model is an effective alternative to the expensive complete compressor simulation. The deterministic stress model provides more information of rotor-stator interaction and slightly better performance prediction than the mixing plane model, but the benefits of the model is not significant when applied to low speed axial flow compressors.
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    Thrust rebalance to extend engine time on-wing with consideration of engine degradation and creep life consumption
    (American Society of Mechanical Engineers, 2023-10-18) da Mota Chiavegatto, Rafael; Li, Yiguang
    Over 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 due to the expiration of Life Limiting Parts, performance deterioration, etc. This paper presents a novel method of rebalancing the thrust of engines of an aircraft to maximize the time between overhaul 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 GE90 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 overhaul 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 overhaul 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.
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    Transient Performance Simulation of Aircraft Engine Integrated with Fuel and Control Systems
    (Elsevier, 2016-12-10) Wang, Chen; Li, Yiguang; Yang, B. Y.
    A new method for the simulation of gas turbine fuel systems based on an inter-component volume method has been developed. It is able to simulate the performance of each of the hydraulic components of a fuel system using physics-based models, which potentially offers more accurate results compared with those using transfer functions. A transient performance simulation system has been set up for gas turbine engines based on an inter-component volume (ICV) method. A proportional-integral (PI) control strategy is used for the simulation of engine controller. An integrated engine and its control and hydraulic fuel systems has been set up to investigate their coupling effect during engine transient processes. The developed simulation system has been applied to a model aero engine. The results show that the delay of the engine transient response due to the inclusion of the fuel system model is noticeable although relatively small. The developed method is generic and can be applied to any other gas turbines and their control and fuel systems.
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    Transient performance simulation of gas turbine engine integrated with fuel and control systems
    (Cranfield University, 2016-01) Wang, Chen; Li, Yiguang
    Two new methods for the simulation of gas turbine fuel systems, one based on an inter-component volume (ICV) method, and the other based on the iterative Newton Raphson (NR) method, have been developed in this study. They are able to simulate the performance behaviour of each of the hydraulic components such as pumps, valves, metering unit of a fuel system, using physics-based models, which potentially offer more accurate results compared with those using transfer functions. A transient performance simulation system has been set up for gas turbine engines based on an inter-component volume (ICV). A proportional- integral (PI) control strategy is used for the simulation of engine control systems. An integrated engine and its control and hydraulic fuel systems has been set up to investigate their coupling effect during engine transient processes. The developed simulation methods and the systems have been applied to a model turbojet and a model turboshaft gas turbine engine to demonstrate the effectiveness of both two methods. The comparison between the results of engines with and without the ICV method simulated fuel system models shows that the delay of the engine transient response due to the inclusion of the fuel system components and introduced inter-component volumes is noticeable, although relatively small. The comparison of two developed methods applied to engine fuel system simulation demonstrate that both methods introduce delay effect to the engine transient response but the NR method is ahead than the ICV method due to the omission of inter-component volumes on engine fuel system simulation. The developed simulation methods are generic and can be applied to the performance simulation of any other gas turbines and their control and fuel systems. A sensitivity analysis of fuel system key parameters that may affect the engine transient behaviours has also been achieved and represented in this thesis. Three sets of fuel system key parameters have been introduced to investigate their sensitivities, which are, the volumes introduced for ICV method applied to fuel system simulation; the time constants introduced into those first order lags tosimulate the valve movements delay and fuel spray delay effect; and the fuel system key performance and structural parameters.