Heavy Duty Gas Turbine Research Articles

Utilizing artificial intelligence to develop an advanced compressor airfoil family for industrial, aero-derivative, and heavy-duty gas turbines

This paper describes the procedure for developing a new airfoil family. This airfoil family applies to heavy-duty, industrial, and aero-derivative gas turbine compressors ranging from subsonic to transonic flow regimes. The airfoil family is generated by filling a database with optimized airfoil geometries. This database is structured in six dimensions, called design space parameters, including inlet Mach number, inlet flow angle, outlet flow angle, axial velocity density ratio, maximum thickness to chord ratio, and solidity. This six-dimensional space includes all compressor blades used in stationary gas turbine compressors. Each set of these design space parameters is related to an optimal geometry produced by the optimization system. The optimization system includes a parametrized airfoil generator, an accurate, fast blade-to-blade flow solver, and an evolutionary optimization algorithm. Airfoils of different stationary gas turbine compressor types are investigated to cover the required design space. Four hundred thirty airfoils, denoted as reference airfoils, are used to define design space borders. Comparing the newly optimized airfoils with reference airfoils revealed superior performance throughout the entire design space. They incorporate these optimized airfoils into a surrogate model, resulting in a fast, optimized airfoil generator (airfoil family). The transonic rotor of the existing multistage compressor has been redesigned according to the developed airfoil family. 3D computational fluid dynamics showed a 2% efficiency improvement for optimized blade row over the original design. Integrating this airfoil family and a streamline curvature code as part of a compressor design system is the main application of this advanced airfoil family.

Experimental Investigation of the Transonic Shock Oscillation Characteristics in a Heavy-Duty Gas Turbine Compressor Cascade

Experimental Investigation of the Transonic Shock Oscillation Characteristics in a Heavy-Duty Gas Turbine Compressor Cascade

A New Compressor Failure Prognostic Method Using Nonlinear Observers and a Bayesian Algorithm for Heavy-Duty Gas Turbines

Failure prognostic predicts the remaining useful life (RUL) of machine/components, which will allow timely maintenance and repair leading to continuous reliable and safe operating conditions. In this article, a novel hybrid RUL prediction approach is proposed for heavy-duty gas turbines. Two common failures, namely the fouling in the gas turbine compressor and filter defect, are investigated. First, a discrete wavelet transform (DWT) is applied to real-time measurements to reduce the effect of noise. A parallel structure consisting of a Laguerre filter and neuro-fuzzy is then constructed to identify nonlinear failure dynamics and generate residuals. These residuals are then utilized to estimate the failure severity. Following that, Bayesian theory is employed to predict the RUL. A novel feature of the approach is that the Laguerre filter is designed by using orthogonal basis functions (OBFs), which deliver precise estimates. Another benefit is that the proposed parallel configuration accurately identifies failure dynamics and boosts the RUL prediction performance. Experimental test studies on heavy-duty gas turbines indicate the high efficiency of the proposed RUL estimation in comparison to other failure prognostic strategies.

Multi-objective performance optimization of target surface of bionic blue whale-skin impinged by array jet

Jet impingement cooling technology is usually applied to combustor liner with large heat load. With the continuous improvement of high capacity and low emission of heavy-duty gas turbines,the research on low resistance and high cooling efficiency cooling technology is particularly important. To meet these urgent needs, based on the blue whale skin structure, a new array impingement target surface cooling structure was proposed from the perspective of bionics. The flow and heat transfer characteristics of the array impingement bionic target surface cooling structure were numerically simulated under high Reynolds number (Re) and high Heat flux density (q) conditions. The influence of groove depth (H, 1 to 3 mm), radius ratio (R/H, 1 to 3) and spacing ratio (P/H, 10 to 20) on the cooling performance of impingement target surface was analyzed. Multi-objective performance optimization of the bionic structure was carried out by using the second-order response surface approximation model (RSM) and the second-generation non-inferior sequencing genetic algorithm (NSGA-II), and the performance of the optimized structure was tested. The results show that the above optimization method is accurate and effective, and the optimal bionic structure is H = 1.212 mm, R/H = 1.132, P/H = 12.078. Compared with the plane target surface, the average Nusselt number (Nuave), flow friction factor (f), and comprehensive thermal coefficient (F) of the optimal bionic groove structure increased by 14.5%, 1.1% and 14.1%，respectively. The structure and multi-objective optimization method proposed in this paper can provide a certain reference for the design of new efficient cooling structure of heavy-duty gas turbines combustor liner.

A theoretical study on the interplay of thermoacoustic modes with Helmholtz dampers in a longitudinal combustor

Thermoacoustic instabilities often present in gas turbine combustors, especially in land-based heavy-duty gas turbines. Normally, thermoacoustic modes can be classified into two sets: acoustic mode and intrinsic mode (ITA mode). Low order network models are usually used to study thermoacoustic instabilities and passive control methods such as liners and Helmholtz dampers are often used to suppress these instabilities. The addition of Helmholtz dampers could suppress the original thermoacoustic modes. Meanwhile, it could also introduce a new mode, the eigenfrequency of which is related to the parameters of the Helmholtz damper, including its resonant frequency and neck mean flow Mach number. The damping effects depend on the system parameters and could be different on the two categories of original thermoacoustic modes. Based on a rational design, both original modes can be controlled by one damper. The new mode introduced by the damper could interplay with original modes to form new exceptional points with certain parameters. In that case, the eigenfrequency and mode shape of original modes could be vastly influenced. The theoretical results will be verified by numerical simulations.

Optimization Design of Aspect Ratio and Solidity of a Heavy-Duty Gas Turbine Transonic Compressor Rotor

To investigate the influence of blade aspect ratio and solidity on the performance of heavy-duty gas turbine transonic compressors, a multi-objective optimization design platform was built by adopting the blade parameterization method based on the superposition of thickness distribution on the suction surface, the Kriging surrogate model, and the NSGA-II optimization method. The spanwise distribution of solidity and number of blades were the optimization variables. The multi-objective optimization was carried out with isentropic efficiency and stall margin as the objective parameters for the inlet stage transonic rotor of an F-class heavy-duty gas turbine compressor. The results show that the isentropic efficiency and stall margin at design condition with a constant mass flow rate can be improved by 0.96% and 18.7%, respectively, and the total pressure ratio can also increase. The analysis shows that, for regions where the shock wave–boundary layer interaction is obvious, increasing the solidity can reduce the shock wave loss, the shock wave–boundary layer interaction loss, and the end wall loss, and reducing the aspect ratio can reduce the blade boundary layer loss. The spanwise distributions of solidity and aspect ratio determine the stall margin by affecting the radial matching of the load of each blade section. Tip solidity near the tip region needs to be determined according to the pressure field established by the bulk of the flow.

Development Trend of Cooling Technology for Turbine Blades at Super-High Temperature of above 2000 K

Aeroengines and heavy-duty gas turbines are the core power equipment in the field of national defense and energy. Their research and development (R&D) level and manufacturing level represent the status of a country’s heavy industry in the world. The common cooling technologies of turbine blades including impingement cooling, film cooling, effusion cooling, layer cooling, pin fin cooling, and rough ribs were introduced in this paper. With the continuous improvement of the efficiency and performance of aeroengines and gas turbines, the turbine inlet temperature increases gradually every year; turbine blades will be exposed to higher gas temperatures in the future as gas temperatures break 2000 K. In order to ensure the safe operation of turbine blades under severe super-high temperature working conditions, cooling technology must be developed emphatically. This paper first reviews the research status of turbine blade cooling technology and points out future research focuses. The development trends of next-generation turbine blade cooling technology for above 2000 K temperature are summarized from several aspects: the innovative excavation of high-efficiency composite cooling configuration, multi-objective cooperative cooling structure and optimization design based on 3D printing, composite cooling structure design and optimization based on an artificial intelligence algorithm, tapping the cooling potential of new cooling media and heat pipes, integrated thermal protection with new thermal insulators, and the application of low-resistance and high-efficiency surface dimple cooling. The summary of this paper can provide a reference for the researchers of turbine blade cooling technology.

An adaptive synergetic controller applied to heavy-duty gas turbine unit

The accurate control of a gas turbine usually requires precise information of its nonlinear model, as well as all states and the parameters. To access the information of the model, an accurate estimation and compensation of the variables of the gas turbine in the controller architecture are vital. In this study, an adaptive model-based controller using the synergetic approach is utilized to control the generated power and exhaust temperature for a heavy-duty gas turbine power generator unit. For this purpose, first, the problem of the controllability of the nonlinear gas turbine is studied. Then, performance of the proposed controller is compared with a classical PI and well-known nonlinear control methods. Next, a sensitivity analysis regarding the parameters of the gas turbine model is performed, and its critical parameter is identified. These variables are estimated based on an extended Kalman filter and then compensated in the adaptive synergetic controller algorithm. The results demonstrate the effectiveness of the synergetic approach when the components of the gas turbine states and its critical parameter are compensated within the proposed control architecture.

Liquefied natural gas plant maintenance: a case study of gas turbine centrifugal compressor thrust bearing failure analysis

Maintenance is essential for preserving gas turbine engineering system functionality during equipment life cycle. Heavy-duty gas turbine (HDGT) engineering systems are often quite complex to maintain. Therefore an effective condition based maintenance (CBM) program is vital to reduce downtime, improve equipment reliability and cost optimization. It is estimated that 50 to 75% of gas turbine maintenance cost is related to the replacement and repair of hot section parts. Furthermore, the maintenance intervals of the engine is governed by the hot section material durability, and the replacement of these components is the largest contributor to determining maintenance related equipment availability. This paper investigate multiple thrust bearing failures on gas turbine driven centrifugal compressor application in a liquefied natural gas (LNG) plant. A root cause failure analysis (RCFA) approach was conducted to determine the failure mode and its consequencies. Process instability is believed to be the cause of several thrust bearing failures. Downtime analysis is presented to estimate the the loss of production (LPO).

Research of Heavy-Duty Gas Turbines through Computer Mathematical Statistics and Big Data Analysis

Heavy duty gas turbine is the core power equipment of energy efficient conversion and clean utilization system in the 21st century and even longer. It is important for an efficient, clean and safe energy system. The heavy duty gas turbine is developed and manufactured at a level that represents a country's heavy industry and is by far the most efficient thermoelectric conversion equipment. This paper introduces the development status of the heavy duty gas turbine industry at home and abroad, summarizes the working principle and characteristics of heavy duty gas turbines, and prospects the development trend of heavy duty gas turbines.

Experimental and Numerical Investigation of the Non-Reacting Flow in a High-Fidelity Heavy-Duty Gas Turbine DLN Combustor

A dry, low-NOx (DLN) combustor for a heavy-duty gas turbine using lean premixed technology was studied. A high-fidelity test model was built for the experimental study using particle image velocimetry (PIV). The non-reacting flow in the DLN combustion chamber was investigated experimentally and numerically. The numerical results are in good agreement with the experimental data. The results show that recirculation zones were formed downstream of each swirl nozzle and that the flow pattern in each section was self-similar under different working conditions. For two adjacent swirl nozzles with opposite swirling directions, the entrainment phenomenon was present between their two flows. The two flows gradually mixed with each other and obtained a higher speed. If the two adjacent swirl nozzles had the same swirling direction, then the mixing of the two flows out of the nozzles was not present, resulting in two separate downstream recirculation zones. The interaction of swirling flows out of different nozzles can enhance the turbulent fluctuation inside the combustion chamber. Based on the analysis of the recirculation zones and turbulent kinetic energy (TKE) distribution downstream of each nozzle, it can be found that nozzle coupling results in stronger recirculation and turbulent mixing downstream counterclockwise surrounding nozzles.

A Probabilistic Model for Forging Flaw Crack Nucleation Processes for Heavy Duty Gas Turbine Rotor Operations

Abstract We present a probabilistic model for quantifying the number of load cycles for nucleation of forging flaws—for a 3.5NiCrMoV high strength low alloy rotor steel—into a crack under gas turbine operating conditions. The model correlates low cycle fatigue data, ultrasonic testing indication data, flaw morphology, and type with the nucleation process. This paper is the third of a series of publications presenting this modeling approach progressively. It focuses on the effect of temperature variation on the nucleation life of forging flaws. We quantified the number of cycles to crack nucleation was for specimens that included forging flaws at elevated temperatures. Flaws of different sizes and shapes are effectively described at respective temperature and stress levels by either an ellipsoidal finite element model or an analytical area-based model. A local probabilistic low-cycle fatigue model analyzes the resulting stress distributions accounting for statistical size effects. Via Maximum Likelihood Estimation of these probabilistic low cycle fatigue results, a probabilistic model for crack nucleation of forging flaws is obtained. This proposed probabilistic model is based on experimental data for realistic heavy duty gas turbine rotor temperature and stress conditions. It can be utilized in the energy sector for component life time quantification. Our suggested approach can support component assessment under flexible gas turbines operation conditions driven by increased availability of intermittent renewable energy sources.

Influence of Position of Intake Struts on Unsteady Load and Vibration of First-Stage Rotor

To investigate the influence law and mechanism of the relative circumferential position of intake struts on the unsteady load and vibration of the first stage rotor, the first 1.5-stage of a heavy-duty gas turbine compressor with intake struts was numerically simulated. The analysis of the flow field and vibration of the rotor blade reveals that the circumferential position of intake struts has little effect on aerodynamic performance but obviously changes the unsteady load and vibration level of the rotor blade. When strut and inlet guide vane wakes coincide, they are strengthened, resulting in the overall enhancement of the unsteady load and vibration on the rotor blade. The circumferential position of struts changes the combined effect of strut wakes and the first stage stator potential flow on the rotor blade, which has an obvious influence on the unsteady load and vibration in the middle chord length but has little influence on the unsteady load near the leading and trailing edges. Research results provide reference and guidance for the installation of struts.

Towards Predictive Maintenance of a Heavy-Duty Gas Turbine A New Hybrid Intelligent Methodology for Performance Simulation

As the increasing demands of global clean power for the main purpose of lowering environmental pollution, heavy-duty gas turbines are playing an increasingly important role in energy fields because of their low emission, high thermal efficiency and flexible start-up capacity. Accurate modeling and simulation of the turbine performance is extremely needed to precisely design a large-watt industrial heavy-duty gas turbine, which is still very challenging due to the high nonlinearity, system complexity, varying conditions, and strong coupling interaction of high-dimension parameters under the harsh operation environment of the turbine. In order to improve the accuracy and efficiency of the performance simulation model for a heavy-duty gas turbine at various operating conditions, this paper presents a new hybrid intelligent methodology to adeptly integrate system thermodynamic balance mechanism with multivariate data by seamlessly combing advanced signal processing, machine learning and artificial neural network modeling techniques. The thermodynamic model of a complicated single-shaft gas turbine is first created based on the balances of both flow and power in various subsystems including inlet, compressor, turbine, combustor and exhaust. The characteristic curves of compressor and turbine are utilized to accurately represent the physical mechanism and effectively simulate the high nonlinear behaviors of subsystems. Wavelet signal processing and machine learning based feature extraction are employed to preprocess the multivariate raw data of the turbine. Multilayer artificial neural network models are explored to efficiently simulate the start-up transient process of the turbine, thus improve the simulation efficiency and accuracy of the complicated system. Multivariate data collected from a real-world industrial heavy-duty gas turbine is employed to illustrate the effectiveness and feasibility of the proposed methodology.

Modeling and Simulation of a Low-Cost Fast Charging Station Based on a Micro Gas Turbine and a Supercapacitor

In recent years, micro turbine technology has become a continuously reliable and viable distributed generation system. The application of distributed energy power generation sources, such as micro gas turbines (MGT), to charge electric vehicles offers numerous technical, economical benefits, and opportunities. MGT are considered as they are smaller than conventional heavy-duty gas turbines. They also are capable of accepting and operating with different fossil fuels in the range of low–high pressure levels as well as co-generation opportunities. The MGT could provide the fast and reliable output power guaranteed and needed for grid stability. This paper provides a mathematical representation, modelling, and simulation of a low-cost fast charging station based on a micro gas turbine and a super capacitor forming altogether a power generation system suitable for use especially as energy source in fast charging stations and dynamic power systems. All the micro gas turbine’s parameters are estimated according to available performance and operational data. The proposed system generates up to 30 kW output power assuming that it operates with natural gas. The developed model of the system is simulated in the environment of MATLAB/Simulink. Each part of the micro turbine generation system is represented by a mathematical model. On the basis of the developed model of the system, the minimum value of the supercapacitor was determined, which ensures the charging schedule of a selected electric vehicle.

Predicting the Impact of Compressor Flexibility Improvements on Heavy-Duty Gas Turbines for Minimum and Base Load Conditions

The increasing importance of renewable energy capacity in the power generation scenario, together with the fluctuating consumer energy demand, forces conventional fossil fuel power generation systems to promptly respond to relevant and rapid load variations and to operate under off-design conditions during a major fraction of their lives. In order to improve existing power plants’ flexibility in facing energy surplus or deficit, retrofittable solutions for gas turbine compressors are proposed. In this paper, two different operation strategies, variable inlet guide vanes (IGVs) and blow-off extraction (BO), are considered for enabling partial load and minimum environmental load operation, and thus to identify implementation opportunities in existing thermal power plants. A typical 15-stage F-class gas turbine compressor is chosen as a test case and some energy demand scenarios are selected to validate the adopted solutions. The results of an extensive 3D, steady, CFD analysis are compared with the measurements coming from an experimental campaign carried out in the framework of the European Turbo-Reflex project. It will be shown how the combined strategies can reduce gas turbine mass flow rate and power plant output, without significantly penalizing efficiency, and how such off-design performance figures can be reliably predicted by employing state-of-the-art CFD models.

A New Fault Diagnosis Approach for Heavy-Duty Gas Turbines

Effective fault detection, estimation, and isolation are essential for the safety and reliability of gas turbines. In this article, a hybrid fault detection and isolation (FDI) approach is presented for condition monitoring of heavy-duty gas turbines. First, nonlinear dynamical models are constructed using an orthonormal basis function and an adaptive neuro-fuzzy inference system through experimental data. Following that, a fuzzy inference system is employed to estimate the fault severity. For this aim, fuzzy rules are extracted from the fault patterns by defining appropriate features. Later, various faults are isolated using an ensemble decision tree classifier. The proposed nonlinear modeling compensates for disturbances and uncertainty in the system and leads to adaptive thresholds for fault detection, which reduces the false alarm rate. Moreover, the proposed FDI method brings high accuracy in fault estimation by properly modeling a bounded uncertainty using the adaptive threshold. Experimental data are applied to validate the gas turbine model. Test results indicate that the proposed hybrid FDI method via adaptive threshold overwhelms the other FDI methods, where the misclassified data are 5.6%.

Brush seal design and secondary air system modification of a heavy-duty gas turbine to improve the output power

The overall performance of heavy-duty gas turbines is strongly affected by the mass flow distribution of the secondary air system. Reducing the mass flow of the secondary air is a remarkable method to improve the performance of a gas turbine. The aim of this article is to implement a brush seal as an alternative to labyrinth seal. Based on the experiences gained from the integrity of brush seals into a gas turbine, installing a brush seal would not necessarily improve turbine performance. This is because of SAS mass flow redistribution, which may not lead to overall SAS mass flow reduction. Therefore, some other components in the SAS arrangement should be modified as controlling variables to overcome this problem. The effect of these modifications on the airflow distribution is investigated using an in-house network analysis code. To establish an optimum solution (optimized brush seal geometry and controlling variables), the network analysis code is coupled with an in-house optimization code that benefits from the Genetic Algorithms and Artificial Neural Networks. Some constraints including upstream and downstream cavity purge flow and vane cooling air are considered in the optimization process. The final network results show a 33.27% reduction in overall SAS mass flow. To ensure an improvement in the performance of the new three-stage turbine, a CFD analysis is conducted, which indicates 1.0% more power with respect to the original turbine. In the end, the aerodynamic and mechanical behavior of the brush seal is analyzed using CFD and FEM.

Non-destructive Metallurgical Failure Investigation of Erroneously Heat Treated Hot Gas Path Component Using Replica Technique

Abstract Metallic heat shields, used in combustion chambers of heavy-duty gas turbine engines and made of nickel-based superalloys, were accidentally heat treated during fabrication, using wrong parameters. There were concerns about embrittlement. Nondestructive metallurgical material characterization using the replica technique verified embrittlement by secondary phases. In spite of this, it was recommended to the client to use the affected parts as is, this on the grounds that no grain growth was observed and hardness was not elevated. While the case study presented in this contribution may appear trivial at first sight, it interestingly shows how metallographic examinations may sometimes be performed non-destructively, without sacrificing any engine components. The inclined reader should also note the superb quality of the photomicrographs presented in this contribution. They were taken from replica foils, not actual metallographic sections.

Aerodynamic limits air injection for heavy-duty gas turbine: Compressor aerodynamic limits for power augmentation and ramp-up capabilities

Improved operational flexibility of gas turbines can play a major role in stabilising the electric power grid, by backing up intermittent renewable power. Gas turbines offer on-demand power and fast dispatch of power that is vital when renewable power reduces. This has brought about increasing demand to improve the ramp-up rate of gas turbines. One approach is through the injection of compressed air from energy storage or an auxiliary compressor. This method is the focus of the present work, which shows for the first time, the implications and limits of compressor air injection in a high-fidelity Computational Fluid Dynamics model (CFD). The 3D multi-stage model of the compressor was developed in ANSYS CFX v19.2, while the boundary conditions related to the injection cases have been obtained from a corresponding 0D engine model. The upper limits to air injection determine how much air can be injected into the engine, providing indicative values of power augmentation and ramp-up rate capabilities. These have been previously addressed by the authors using 0D models that do not consider the compressor aerodynamics in great detail. The CFD study has shown that for power augmentation, 16% of compressed air (based on compressor exit) is allowed based on the onset of stall. It also shows that increasing air injection amplifies losses, blockage factor and absolute velocity angle. Also, about 30% of the blade span from the hub is dominated by a rise in the total pressure loss coefficient, except the outlet guide vane for which separation occurs at the tip. For the ramp-up rate analysis, up to 10% air injection is shown to be sustainable. The work shows that the improvements in the 0D analytical engine model are plausible, in addition to demonstrating similar limits at different ambient temperatures.