NARX models for simulation of the start-up operation of a single-shaft gas turbine

In this study, nonlinear autoregressive exogenous (NARX) models of a heavy-duty single-shaft gas turbine (GT) are developed and validated. The GT is a power plant gas turbine (General Electric PG 9351FA) located in Italy. The data used for model development are three time series data sets of two different maneuvers taken experimentally during the start-up procedure. The resulting NARX models are applied to three other experimental data sets and comparisons are made among four significant outputs of the models and the corresponding measured data. The results show that NARX models are capable of satisfactory prediction of the GT behavior and can capture system dynamics during start-up operation

EFFECTS OF MONITORING SIGNAL HYSTERESIS ON SPEED REGULATION FOR THE AERO-DERIVATIVE GAS TURBINE

Sensor aging and sensor failure are the common phenomena due to the high temperature and pressure environment for gas turbines, which can lead to hysteresis of monitoring signals. In this paper, a kind of aero-derivative gas turbine is taken as the research object. The hysteresis effects of single monitoring signal and coupling of multiple monitoring signals on speed control are mainly studied, and the analysis is carried out from the perspective of adjustment time, overshoot, fuel quantity and fuel quantity regulation output. The analysis results show that the pressure signal hysteresis will lead to speed suspension. The speed signal hysteresis will change the speed regulation into a multi-step mode. When the monitoring signal hysteresis is coupled, the effect of pressure signal hysteresis is greater than that of speed signal hysteresis. The results of this paper can provide a reference for the optimal design of speed control of aero-derivative gas turbine

A scientometric analysis and critical review of gas turbine aero-engines control: From Whittle engine to more-electric propulsion

The gas turbine aero-engine control systems over the past eight decades have been thoroughly investigated. This review purposes are to present a comprehensive reference for aero-engine control design and development based on a systematic scientometric analysis and to categorize different methods, algorithms, and approaches taken into account to improve the performance and operability of aircraft engines from the first days to present to enable this challenging technology to be adopted by aero-engine manufacturers. Initially, the benefits of the control systems are restated in terms of improved engine efficiency, reduced carbon dioxide emissions, and improved fuel economy. This is followed by a historical coverage of the proposed concepts dating back to 1936. A comprehensive scientometric analysis is then presented to introduce the main milestones in aero-engines control. Possible control strategies and concepts are classified into four distinct phases, including Single input- single output control algorithms, MIN-MAX or Cascade control algorithms, advanced control algorithms, More-electric and electronic control algorithms and critically reviewed. The advantages and disadvantages of milestones are discussed to cover all practical aspects of the review to enable the researchers to identify the current challenges in aircraft engine control systems

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

With the privatization and intense competition that characterize the volatile energy sector, the gas turbine industry currently faces new challenges of increasing operational flexibility, reducing operating costs, improving reliability and availability while mitigating the environmental impact. In this complex, changing sector, the gas turbine community could address a set of these challenges by further development of high fidelity, more accurate and computationally efficient engine health assessment, diagnostic and prognostic systems. Recent studies have shown that engine gas-path performance monitoring still remains the cornerstone for making informed decisions in operation and maintenance of gas turbines. This paper offers a systematic review of recently developed engine performance monitoring, diagnostic and prognostic techniques. The inception of performance monitoring and its evolution over time, techniques used to establish a high-quality dataset using engine model performance adaptation, and effects of computationally intelligent techniques on promoting the implementation of engine fault diagnosis are reviewed. Moreover, recent developments in prognostics techniques designed to enhance the maintenance decision-making scheme and main causes of gas turbine performance deterioration are discussed to facilitate the fault identification module. The article aims to organize, evaluate and identify patterns and trends in the literature as well as recognize research gaps and recommend new research areas in the field of gas turbine performance-based monitoring. The presented insightful concepts provide experts, students or novice researchers and decision-makers working in the area of gas turbine engines with the state of the art for performance-based condition monitoring

Thematic clusters in the field of gas turbine thermal management: a co-word analysis during a century

The research aims to visualize and analyze the co-word network and thematic clusters of the intellectual structure in gas turbine thermal management during 1919-2020. The study is applied research in terms of the purpose, which is conducted with a descriptive approach, scientometrics indicators, techniques of co-word, and social network analysis. Data analysis and visualization of the co-word network were represented by VoS­Viewer, SPSS, UCINet, and python Software. The top scientific products in the last century were related to engineering subject area and published by the USA country. Seven main clusters were identified for the index keywords, and 20 main clusters were recognized for the author keywords in Scopus regarding the network structure and thematic clusters based on the co-occurrences. Moreover, 38 clusters were identified based on the hierarchical clusters. The clusters, namely heat flux calculations and radiation effects, thermal performance optimization, and operational considerations, have central and major positions in this field and have more potential to maintain and develop themselves in the future. The future of Research and Development (R&D) activities in the area will be focused on novel cycles, heat map development, and Techno-Economic and Risk Analysis (TERA) by utilizing systematic approaches for the identification of heat sinks and sources, fluid modeling, and environmental considerations. In addition, the emerging contributors in the field will be advanced manufacturing and material considerations

Fault diagnostics for advanced cycle marine gas turbine using genetic algorithm

The major challenges faced by the gas turbine industry, for both the users and the manufacturers, is the reduction in life cycle costs , as well as the safe and efficient running of gas turbines. In view of the above, it would be advantageous to have a diagnostics system capable of reliably detecting component faults (even though limited to gas path components) in a quantitative marmer. V This thesis presents the development an integrated fault diagnostics model for identifying shifts in component performance and sensor faults using advanced concepts in genetic algorithm. The diagnostics model operates in three distinct stages. The rst stage uses response surfaces for computing objective functions to increase the exploration potential of the search space while easing the computational burden. The second stage uses the heuristics modification of genetics algorithm parameters through a master-slave type configuration. The third stage uses the elitist model concept in genetic algorithm to preserve the accuracy of the solution in the face of randomness. The above fault diagnostics model has been integrated with a nested neural network to form a hybrid diagnostics model. The nested neural network is employed as a pre- processor or lter to reduce the number of fault classes to be explored by the genetic algorithm based diagnostics model. The hybrid model improves the accuracy, reliability and consistency of the results obtained. In addition signicant improvements in the total run time have also been observed. The advanced cycle Intercooled Recuperated WR2l engine has been used as the test engine for implementing the diagnostics model.SOE Prize winne

TERA for Rotating Equipment Selection

This thesis looks at creating a multidisciplinary simulation tool for rotating plant equipment selection, specifically gas turbines, for the liquefaction of natural gas (LNG). This is a collaborative project between Shell Global Solutions and Cranfield University in the UK. The TERA LNG tool uses a Techno-economic, Environmental and Risk Analysis (TERA) approach in order to satisfy the multidisciplinary nature of the investigation. The benefits of the tool are to act as an aid to selection, operations and maintenance planning and it also acts as a sensitivity tool for assessing the impact of changes in performance, environmental and financial parameters to the overall economic impact of technology selection. The aim is to not only select technology on the basis of techno-economics but also on the basis of risk analysis. The LNG TERA tool is composed of a number of modules starting with the performance simulation which calculates the thermodynamic conditions in the core of the engine. Next, life estimates of the hot gas path components are made using a mixture of parametric and probabilistic lifing models for the turbine first stage blades, coatings, and combustor liner. This allows for a risk analysis to be conducted before maintenance and economics issues are dealt with. In parallel, emissions estimations are made based on empirical correlations. The modelling exemplifies a methodology which is uniquely applied to this application and there are no studies previous to this which look at so many aspects before making conclusions on plant machinery selection. Comparisons have been done between industrial frame engines based on the General Electric Frame 9E (130 MW) and Frame 7EA (87 MW) engines as well as more complex cycles involving aero-derivation and inter-cooling such as the LM 6000 (42 MW) and LMS 100 (100 MW). Work has also been carried out to integrate the tool to Shell based systems in order to utilise the database of information on failure and maintenance of machinery as well as its performance. The results of the integrated TERA show a clear favour for the aero-derivative engines and the main benefit is the fuel saving, though the life of the hot gas path components is deteriorated much faster. The risk results show that the industrial frame engines have a wider variation in expected life compared to aero-derivatives, though the industrial frames have longer component lives. In the context of maintenance and economics, the aero-derivative engines are better suited to LNG applications. The modular change out design of the aero- derivatives also meant that time to repair was lower, thus reducing lost production. Application of the LNG TERA tool was extended to power generation whereby a series of 6 engines were simulated. The changes required to the modelling were minimal and it shows the flexibility of the TERA philosophy. This study was carried out assuming a given ratio of load split between the engines and hence is sensitive to the way an operator demands power of the engine as opposed to LNG application where the operator tries to drive the engine as hard as possible to get the most production out of the train. The study was limited in the modes of failure which were investigated, a major further work would be to extend the methodology to more components and incorporate fatigue failure. Further, the blade creep and probabilistic coating models were very sensitive to changes in their respective control parameters such as coating thickness allowances and firing temperature. The contribution to the project from the MBA is the statistical techniques used to conduct the risk analysis and data handling as well as financial management techniques such as the Net Present Value (NPV) methodology for project evaluations

Optimization of aeroengine utilization through improved estimation of remaining useful life (RUL) of on condition (OC) parts

Gas Turbine Operators and Maintainers face the challenge of increasing the operationallife, availability, and reliability of Aero Engine during the operations amid the advancements in the technology for the speed, Power, SFC, and Comfort which led to closing in the safety margins and increasing in the failure rate of Aero Engines, and low serviceability of aero engines due to the rapid increase in demand and expansion of the aircraft fleet by the various airlines for various reasons which led to increase in downtime and lead time of serviceability of Aero Engines. This study focuses on the inherent Aero Engine deterioration caused due to various Gas Turbine Faults or Physical Problems and how Performance, Trend, and Systems Monitoring contain this deterioration and contribute to the optimization of aero engine utilization. The purpose of thispaper is to present the importance of accurate estimation of Remaining Useful Life (RUL) of On Condition (OC) Parts and how it optimizes aero engine life. The benefits associated with the introduction of a novel estimation of RUL of OC Parts are also presented. A Standardized Replacement Model (SRM), which improves the estimation of RUL of OC Parts, is proposed for optimization of Aero Engine Utilization

Transient performance simulation of gas turbine engine integrated with fuel and control systems

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

Optimise repair strategy selection and repair knowledge sharing to support aero engine design.

Recent growth in aviation industry, large civil jet engines OEMs (Original Equipment Manufacturer) and MROs ((Maintenance, Repair and overhaul)) have emphasised on decreased profits, poor technology selections and maintenance focused design. This has generated service based approach in their selling, offering all customers’ requirements, known as servitisation. The servitisation has increased profits but did not solve the challenges of poor technology selection and design. The difficulties involved within servitisation entails rationalised decision making often with high risk and very limited information. This thesis assesses the most suitable Multi-criteria decision making (MCDM) in concurrence with OEMs and MRO focus groups that recognises the industrial requirements and proposed a novel selection method which is an AHP algorithm based on MCDM in efforts to address business KPIs in aero engine servitisation. This AHP algorithm based MCDM develops an optimised repair process/technology selection framework which is called ORSS (Optimised Repair Selection Strategy). The ORSS applies the business KPIs (Quality Cost Delivery) as a selection criteria combined with the repair engineer's requirements and expert's evaluation of processes/technologies based on a component and its damage-mode to provide the optimised repair process/technology selection that also compliments the components lifecycle repair strategy. A structured knowledge sharing framework has also been developed. This consists of the information that the designers can update to help repair teams to become more effective and efficient in repair and services critical information tasks. These frameworks were validated successfully by experts within the design, repair and service teams at Rolls Royce. These frameworks have shown high levels of improvements in repair process selection and the key knowledge sharing for designs.Engineering and Physical Sciences (EPSRC)PhD in Manufacturin