Adaptive Polynomial Chaos for Gas Turbine Compression Systems Performance Analysis

Constrained orthogonal polynomials have been recently introduced in the study of the Hohenberg–Kohn functional to provide basis functions satisfying particle number conservation for an expansion of the particle density. More generally, we define block orthogonal (BO) polynomials which are orthogonal, with respect to a first Euclidean inner product, to a given i-dimensional subspace of polynomials associated with the constraints. In addition, they are mutually orthogonal with respect to a second Euclidean inner product. We recast the determination of these polynomials into a general problem of finding particular orthogonal bases in an Euclidean vector space endowed with distinct inner products. An explicit two step Gram–Schmidt orthogonalization (G-SO) process to determine these bases is given. By definition, the standard block orthogonal (SBO) polynomials are associated with a choice of equal to the subspace of polynomials of degree less than i. We investigate their properties, emphasizing similarities to and differences from the standard orthogonal polynomials. Applications to classical orthogonal polynomials will be given in forthcoming papers.

Combustion instability due to thermo-acoustic interactions in high-speed propulsion devices such as gas turbines and rocket engines result from pressure waves with very large amplitudes propagating back and forth in the combustion chamber. Exposure to the pressure fluctuations over a long period of time can lead to a cataclysmic failure of engines. The underlying physics governing the generation of the thermo-acoustic instability is a complex interaction among heat release, turbulence, and acoustic waves. Currently, it is very difficult to accurately predict the expected level of oscillations in a combustor. Hence development of strategies and engineering solutions to mitigate thermo-acoustic instability is an active area of research in both academia and industry. In this work, we carry out numerical modeling of thermo-acoustic instability in a self-excited, laboratory scale, model rocket combustor developed at Purdue University. Two different turbulent combustion models to account for turbulence-chemistry interactions are considered in this study, the flamelet model and the transported probability density function (PDF) method. <br>In the flamelet modeling approach, detailed chemical kinetics can be easily incorporated at a relatively low cost in comparison to other turbulent combustion models and it also accounts for turbulence-chemistry interactions. The flamelet model study is divided into two parts. In first part, we examine the effect of different numerical approaches for implementing the flamelet model. In advanced modeling and simulations of turbulent combustion, the accuracy of model predictions is affected by physical model errors as well as errors that arise from the numerical implementation of models in simulation codes. Here we are mainly concerned with the effect of numerical implementation on model predictions of turbulent combustion. Particularly, we employ the flamelet/progress variable (FPV) model and examine the effect of various numerical approaches for the flamelet table integration, with presumed shapes of PDF, on the FPV modeling results. Three different presumed-PDF table integration approaches are examined in detail by employing different numerical integration strategies. The effect of the different presumed-PDF table integration approaches is examined on predictions of two real flames, a laboratory-scale turbulent free jet flame, Sandia Flame D and the self-excited resonance model rocket combustor. Significant difference is observed in the predictions both of the flames. The results in this study further support the claims made in previous studies that it is imperative to preserve the laminar flamelet structure during integration while using the flamelet model to achieve better predictions in simulations. In the second part of the flamelet modeling study, computational investigations of the coupling between the transient flame dynamics such as the ignition delay and local extinction and the thermo-acoustic instability developed in a self-excited resonance combustor to gain deep insights into the mechanisms of thermo-acoustic instability. A modeling framework that employs different flamelet models (the steady flamelet model and the flamelet/progress variable approach) is developed to enable the examination of the effect of the transient flame dynamics caused by the strong coupling of the turbulent mixing and finite-rate chemical kinetics on the occurrence of thermo-acoustic instability. The models are validated by using the available experimental data for the pressure signal. Parametric studies are performed to examine the effect of the occurrence of the transient flame dynamics, the effect of artificial amplification of the Damkohler number, and the effect of neglecting mixture fraction fluctuations on the predictions of the thermo-acoustic instability. The parametric studies reveal that the occurrence of transient flame dynamics has a strong influence on the onset of the thermo-acoustic instability. Further analysis is then conducted to localize the effect of a particular flame dynamic event, the ignition delay, on the thermo-acoustic instability. The reverse effect of the occurrence of the thermo-acoustic instability on the transient flame dynamics in the combustor is also investigated by examining the temporal evolution of the local flame events in conjunction with the pressure wave propagation. The above observed two-way coupling between the transient flame dynamics (the ignition delay) and the thermo-acoustic instability provides a plausible mechanism of the self-excited and sustained thermo-acoustic instability observed in the combustor.<br>The second turbulent combustion model considered in this study is the transported PDF method. The transported PDF method is one of the most attractive models because it treats the highly-nonlinear chemical reaction source term without a closure requirement and it is a generalized model for a wide range of turbulent combustion problems.Traditionally, the transported PDF method has been used to model low-Mach number, incompressible flows where the pressure is assumed to be thermodynamically constant. Since there is significant pressure fluctuations in the model rocket combustor, the flow is highly compressible and it is necessary to account for this compressibility in the transported PDF method. In the past there has been very little work to model compressible reactive flows using the transported PDF and no effort has been made to model thermo-acoustic instability using the transported PDF method. There is a pressing need to further examine and develop the transported PDF method for compressible reactive flows to broaden our understanding of physical phenomenon like thermo-acoustic instability, interaction between combustion and strong shock and expansion waves, coupling between acoustic and heat release which are observed in high-speed turbulent combustion problems. To address this, a modeling framework for compressible turbulent reactive flows by the using the transported PDF method is developed. This framework is validated in a series of test cases ranging from pure mixing to a supersonic turbulent jet flame. The framework is then used to study the thermo-acoustic interactions in the self-excited model rocket combustor.

Due to the growing concern on the issues of global warming, climate change, and energy shortage, more rigorous requirements are imposed on the energy conversion process of combustion. Due to the relative safety and convenience in transportation and storage, liquid fuels are commonly used in many practical combustion systems such as diesel engines, gas turbines and industrial furnaces. In these combustion devices, turbulent spray flows are involved. The character of spray dispersion, evaporation, mixing and combustion of fuel droplets strongly determines the performance of these systems with respect to the combustion efficiency, stability, and emissions. Therefore, an improved understanding of turbulent spray combustion and the development of predictive models are needed for a better design of more efficient combustion systems. The present work focuses on the development of a computational methodology based on the transported joint probability density function (PDF) method for the modeling and simulation of two-phase turbulent spray flows without and with chemical reactions. In the non-reacting situation, the dependent variables of the joint PDF include the gas velocity and the mixture fraction. For the simulation of reacting spray flows, a three-variate joint PDF transport equation is derived and modeled in order to account for the pre-vaporization effects and partially premixed regime in turbulent spray flames. The dependent variables include the gas phase mixture fraction, the reaction progress variable and gas enthalpy. Detailed combustion chemistry is considered through an extended spray flamelet model by including a reaction progress variable in addition to the classical formulation. The dilute spray is simulated using a Lagrangian discrete parcel method for the description of droplet motion, heating and evaporation. The infinite conductivity model with consideration of non-equilibrium effects based on the Langmuir-Knudsen law is considered. The spray evolution and flame structures in the frame of the polydisperse reacting spray flows are investigated. Numerical results are compared with experimental data provided by Prof. Masri at the University of Sydney, Australia, and the test cases include three different turbulent non-reacting acetone spray flows in air and turbulent spray flames with the liquid fuel ethanol. For the acetone spray flows, computational results generally show good agreement with experimental data in terms of the droplet size and mean velocity distribution, as well as the liquid volume flux. The results show that the inflow liquid mass loading hardly affects the droplet diameter distribution, whereas the inlet turbulence level has a pronounced effect. The tendency of droplet accumulation near the jet centerline is found with a somewhat overprediction of liquid volume flux at downstream locations. A more sophisticated turbulence model is expected to eliminate this discrepancy. Moreover, the local joint PDF of the gas velocity and the mixture fraction is analyzed. A linear correlation of the gas velocity and the mixture fraction exists close to the nozzle exit outside the main spray jet, and no regions are found where statistical independence prevails. For the simulation of spray flames, computations with the newly developed spray flamelet/progress variable approach and with the previous standard spray flamelet formulation are carried out and compared with the experiments by Prof. Masri at the University of Sydney. A good agreement between the computations with the new formulation and the experiments for gas temperature and droplet size and velocity is achieved. The major spray and combustion properties are correctly captured using this new formulation, which is compared with an unphysically attached flame near the nozzle exit predicted by the previous model. A partially premixed combustion prevails in this piloted turbulent spray flame. Due to the prevaporization of the ethanol droplets near the nozzle exit, a lean premixed gas mixture is found at the inner side of spray jet. Moving downstream, the lean-sided diffusion flame is promoted towards the inner fuel-rich side by heating up the inner premixed core that is controlled by the droplet evaporation. Additionally, it is observed that in the far-field region, the diffusion flame becomes the dominant combustion mode. In summary, an efficient computational model based on the transported joint PDF method is developed to two-phase turbulent spray flows. The combined transported joint PDF and a newly proposed spray flamelet/progress variable approach shows an improved performance in the prediction of complex turbulent spray flames, and new insights on the local flame structure influenced by evaporating sprays are obtained.

Performance deterioration in gas turbine engines (GTEs) depends on various factors in the ambient and the operating conditions. For example, humidity condensation at the inlet duct of a GTE creates water mist, which affects the fouling phenomena in the compressor and varies the performance. In this paper, the effective factors on the short-term performance deterioration of a GTE are identified and studied. GTE performance level is quantified with two physics-based performance indicators, calculated from the recorded operating data from the control system of a GTE over a full time between overhaul (TBO) period. A regularized particle filtering (RPF) framework is developed for filtering the indicator signals, and an adaptive neuro-fuzzy inference system (ANFIS) is then trained with the filtered signals and the effective ambient and the operating conditions, i.e., the power, the air mass flow, and the humidity condensation rate. The trained ANFIS model is then run to simulate the GTE performance deterioration in different conditions for system identification. The extracted behavior of the system clearly shows the dependency of the trend of performance deterioration on the operating conditions, especially the humidity condensation rate. The developed technique and the results can be utilized for GTE performance prediction, as well as for suggesting the optimum humidity supply at the GTE intake to control the performance deterioration rate.

There is a growing need for devices with small weight and large power density as a substitute for today’s accumulators widely used for electrical tools or as thrust application in the aerospace industry e.g. for small unmanned aerial vehicles (UAV). Systems burning liquid or gaseous fuels and working after the principle of the Brayton cycle became more and more interesting as a new field of research (powermems devices). This ongoing miniaturization of power devices such as ultra micro gas turbines requires a reliable and safe combustion of fuels. A new test rig for micro scale combustion chambers has been realized and tested with a new hydrogen prototype burner for a 600 W μ-scale gas turbine. By preheating and pressurizing the flow realistic combustion chamber inlet conditions for the design point and for μ-scale gas turbine part load conditions can be realized. Furthermore the quartz glass prototype burner offers visual access to the flame region during operation at atmospheric condition. Detailed investigations on the burning characteristics for different chamber configurations were carried out for an optimization of the burner concept and gas turbine integration. By changing air mass flow and thermal energy the results allow a mapping of the combustion chamber for setting the control laws of the μ-scale gas turbine. The test results prove a very good flame stability and burning efficiency for the micromix principle covering a wide range of power settings including the design point. Even at extreme part load conditions it was possible to handle all the operating points of the proposed μ-scale gas turbine. Based on the prototype burner results a realistic combustion chamber design for μ-scale gas turbine integration will be presented.

Contracted continuous distributed approximating functions (CCDAFs) have been developed. In particular, it has been shown that, continuous distributed approximating functions (CDAFs) based on standard orthogonal polynomials can be contracted to functions formed as the product of a weight function and the sinc function or a Bessel function of the first kind. The CCDAFs of Hermite type have been applied to derive new expressions for the coordinate representation of the free particle evolution operator and that of the evolution operator of harmonic oscillator. These new expressions of free particle and harmonic propagators have as compact mathematical form as Makri’s effective free propagator [N. Makri, Chem. Phys. Lett. 159, 489 (1989)] and Gaussian decay identical to that of the CDAF class free and harmonic propagators due to Kouri et al. [D. J. Kouri, W. Zhu, X. Ma, B. M. Pettitt, and D. K. Hoffman, J. Phys. Chem. 96, 9622 (1992)] and Marchioro et al. [T. L. Marchioro II, M. Arnold, D. K. Hoffman, W. Zhu, Y. Huang, and D. J. Kouri, Phys. Rev. E50, 2320 (1994)], respectively. The Gaussian decay of a CCDAF Hermite free propagator has been shown to be the result of including momentum eigenstates in the propagator which have momenta larger than the momentum of the wave packet of largest momentum that still can be well approximated by the CCDAF considered.

To obtain a better understanding of the internal combustion processes of gas turbines, CFD computations of a combustion chamber, based on a Rolls-Royce industrial gas turbine, were performed. Minor simplifications are made to generate a 3-D rotational symmetric geometry. Computations are performed at typical gas turbine conditions and natural gas is used as the fuel. An internal Rolls-Royce CFD code is applied to perform the computations. This paper explains the models used for the CFD computations and describes the advantages and limitations on the applied models. The combustion process has been modelled using a two-step global reaction mechanism and Intrinsic Low Dimensional Manifold (ILDM) reduced reaction mechanisms. The global reaction mechanisms are optimised for the considered operating conditions by modification of the reaction rates so that the same burning velocity and the amplitude CO-peak are obtained as predicted by detailed reaction mechanism (GRI 2.11, Bowman 1995). This optimisation is done considering a one-dimensional laminar flame. Although the global reaction mechanism is optimised for one particular operating condition, it appears that it is suitable for use over the entire range of operating conditions. The ILDM reduced reaction mechanisms are derived from GRI 2.11. Two ILDM tables are used to model two operating conditions, as they are specific for the pressure and inlet temperature. The interaction between turbulence and chemistry is modelled using presumed Probability Density Functions (PDF). The flow field in the combustion chamber is studied at isothermal and combusting conditions. It appeared that the flow field for burning and non-burning circumstances is quite different. There is a lack of experimental data so that it is not possible to verify the CFD results in detail. However, there is knowledge about the mechanisms by which the flame is stabilised and emissions are measured in the exhaust. The predicted flame front position agrees with that which is experimentally observed. The predicted increase of CO at low power is at the same order of magnitude as the measured emissions.

This study presents a methodology to improve monitoring of gas turbines (GTs) while not having the specific engine characteristics available by applying a nonparametric statistical modeling based on operational data. The goal is to quantify the relationship between the operational conditions and the GT performance parameters during normal operation. In this study, the Multi-Layer Perceptron (MLP) Neural Network (NN) model is used to develop so called baseline models of the GTs. To verify the generic applicability, two different GTs and several units for each GT type are evaluated. A methodology to both, selecting the appropriate models with regard to input and output parameters as well as validating the selection of the parameters is reported. The key result can be summarized as: MLPs can be used for statistical modeling of GTs with very high accuracy, which permits an accurate prediction of the performance parameters during different operational conditions. It is also shown that under certain conditions, a developed NN model can be transferred to a similar GT. In summary, this study shows that NN can be used to improve on-line monitoring of a GT, making it possible to detect trends in the measured data indicating a change in the health status of the engine, requiring operational data only for model development.

Modern large frame F, G, &amp; J class gas turbine flow path component design requires the complex integration of multiple design disciplines that traditionally reside with distinct specialists. A traditional design system for an actively cooled gas turbine blade includes aerodynamicists, heat transfer engineers, structural engineers and a failure or lifetime prediction engineers passing information through a manual process with a small number of iterations between the disciplines. Design or manufacturing engineers can also be involved ensuring manufacturability and policing best practices in a predominantly deterministic design system. Over the past few decades robust design or probabilistic design philosophies along with cluster computing advancements have accelerated the release of commercial software that allows for the automation of multiple analytical evaluations at off design points. These software codes allow for process automation of several independent codes executed multiple times at various conditions for automated design of experiment (DOE), and reliability analysis using Monte Carlo or other advanced approximate probabilistic methods across the entire design system. In this paper, the authors are presenting a novel approach of using a commercially available process integration tool to fully integrate a series of other commercially available tools for a root cause failure analysis of a F class turbine blade rather than a new make design. The analysis incorporated a computational fluid dynamics model (CFD) to define inlet temperatures and pressure profiles, a fully conjugate thermal analysis interacting with a finite element (FEA) solver linked to a proprietary creep lifetime prediction model. A DOE was executed to define the meaningful parameters and help rule out potential causes of failure such as loss of coating or compromised cooling system as a contributing factor of the failure which greatly reduced the amount of time and money needed for the investigation. A probabilistic failure analysis was then executed and surrogate models created for quick probabilistic assessment for different operating conditions. This allowed for validation against fleet history to explain the single engine failure not previously observed. Setting up the non-deterministic models initially allowed for rapid redesign in less than 1 month time with confidence that the true root cause was identified and mitigated. It further allowed for feedback and calibrations to the traditional design system methodology.

Gas turbine (GT) engines employed in natural gas compressor stations operate in different modes depending on the power, turbine inlet temperature and shaft speeds. These modes apply different sequencing of bleed valve opening on the air compressor side of the engine. Improper selection of the GT and the driven centrifugal gas compressor operating conditions can lead to larger bleed losses due to wider bleed valve openings. The bleed loss inevitably manifests itself in the form of higher overall heat rate of the GT and greater engine emission. It is therefore imperative to determine and understand the engine and process conditions that drive the GT to operate in these different modes. The ultimate objective is to operate the engine away from the inefficient modes by adjusting the driven gas compressor parameters as well as the overall station operating conditions (i.e. load sharing, control set points, etc.). This paper describes a methodology to couple the operating conditions of the gas compressor to the modes of GT bleed valve opening (and the subsequent air bleed rates) leading to identification of the operating parameters for optimal performance (i.e., best overall efficiency and minimum CO2e emission). A predictive tool is developed to quantify the overall efficiency loss as a result of the different bleed opening modes, and map out the condition on the gas compressor characteristics. One year’s worth of operating data taken from two different compressor stations on TransCanada Pipelines’ Alberta system were used to demonstrate the methodology. The first station employs GE-LM1600 gas turbine driving a Cooper Rolls-RFBB-30 centrifugal compressor. The second station employs GE-LM-2500+ gas turbine driving NP PCL-800/N compressor. The analysis conclusively indicates that there are operating regions on the gas compressor maps where losses due to bleed valves are reduced and hence CO2 emissions are lowered, which presents an opportunity for operation optimization.

Regulated two-stage (RTS) turbocharging system is an effective way to enhance power density and reduce pollutant of internal combustion engine for increasingly stringent demands of fuel consumption and emission regulation. Due to achieving high boost pressure with great system efficiency and controllable characteristic in wide working range, the RTS turbocharging system improves output power at low speed condition and reduces pumping loss at high speed condition. Composing of two turbochargers and control valves, the RTS turbocharging system is matched with engine at a design point and regulated by adjusting control valves to meet the engine requirement of intake pressure and flow at other working conditions. Calibration of the control valves under all operating conditions by plentiful experiments is significant for turbocharging system, particularly that matched with diesel engine for vehicle. Moreover, when an automobile run on the plateau, the intake air flow will decrease and combustion in cylinder will deteriorate obviously. Compared with other turbocharging system, two-stage turbocharging system is more suitable to the offset power loss of engine. Regulating boost system under different operation conditions draws more attention to engine performance recovery so that the workload of calibration raises rapidly in consideration of altitude factor. Though much work has been done in calibration at various altitudes, there are few, if any, discussion on open-closed boundary of control valves to simplify the calibration process. In this paper, it aims to present a regulation boundary model of control valve at different altitudes to guide the calibration and a series of experiments for RTS system can be saved. Firstly, a thermodynamics analysis of the RTS turbocharging system is conducted and typical regulation methods are compared in terms of the adjustment capacity and efficiency characteristics of turbocharging system, which indicates that high-stage turbine bypass is the optimum regulation method. Then, a regulation boundary model for the RTS turbocharging system at different altitudes is deduced, according to the relation of equivalent turbine area and engine operating condition. The regulation boundaries of different altitudes are obtained by iterative computation of the model, and the whole working mode of the RTS system is divided into a fully closed area and a regulated area. Experiments are carried out to verify the regulation boundary model at sea level condition. Brake torque, efficiency of the RTS system and temperature before high-stage turbine are primary parameters for verification in this article. The maximum error shows up with a value of 3.65% brake torque at 2200rpm. While a one-dimensional simulation model is built up to validate the regulation boundary model of the plateau. All the errors are smaller than 3% at various altitudes. It results that model is accurate enough to predict the regulation boundary of the RTS system. By the calculation of regulation boundary model, the brake torque at regulation boundary will decrease if the engine speeds up. It also manifests that fully closed area will argument if the automobile climbs up to high operating altitude, especially under high speed condition.

The characteristics and experiences of the gas turbine interactive design system, TDSYS, are described. The design of high performance advanced gas turbines requires complex trade-off analyses for optimization and hence it is necessary to use a highly efficient and accurate computerised integrated design system to complete the laborious design jobs in a short time. TDSYS is an interactive design system which makes extensive use of computer graphics and enables the designers to complete a gas turbine blade design systematically in a very short time. TDSYS has been developed and continuously improved over a period of ten years. The system has been used for the complete and retrofit design of many gas turbines including Mitsubishi MW701 and AGTJ-100A which is a high efficiency reheat gas turbine now being developed under a Japanese national project. In this paper, typical design samples of high temperature turbines are also presented.

This work newly proposes an uncertainty quantification (UQ) method named sparse approximation of moment-based arbitrary polynomial chaos (SAMBA PC) that offers a single solution to many current problems in turbomachinery applications. At the moment, every specific case is characterized by a variety of different input types such as histograms (from experimental data), normal probability density functions (PDFs) (design rules) or fat tailed PDFs (for rare events). Thus, the application of UQ requires the adaptation of ad hoc methods for each individual case. A second problem is that parametric PDFs have to be determined for all inputs. This is difficult if only few samples are available. In gas turbines, however, the collection of statistical information is difficult, expensive, and having scarce information is the norm. A third critical limitation is that if using nonintrusive polynomial chaos (NIPC) methods, the number of required simulations grows exponentially with increasing numbers of input uncertainties: the so-called “curse of dimensionality.” It is shown that the fitting of parametric PDFs to small data sets can lead to large bias and the direct use of the available data is more accurate. This is done by propagating uncertainty through several test functions and the computational fluid dynamics (CFD) simulation of a diffuser, highlighting the impact of different PDF fittings on the output. From the results, it is concluded that the direct propagation of the experimental data set is preferable to the fit of parametric distributions if data is scarce. Thus, the suggested method offers an alternative to the maximum entropy theorem to handle scarce data. SAMBA simplifies the mathematical procedure for many different input types by basing the polynomial expansion on moments. Its moment-based expansion automatically takes care of arbitrary combinations of different input data. It is also numerically efficient compared to other UQ implementations. The relationship between the number of random variables and number of simulation is linear (only 21 simulations for ten input random variables are required). It is shown in this paper that SAMBA's algorithm can propagate a high number of input distributions through a set of nonlinear analytic test functions. Doing this, the code needs a very small number of simulations and preserve a 5% error margin. SAMBA's flexibility to handle different forms of input distributions and a high number of input variables is shown on a low-pressure turbine (LPT) blade-based on H2 profile. The relative importance of manufacturing errors in different location of the blade is analyzed.

Gas turbine (GT) engines employed in natural gas compressor stations operate in different modes depending on the power, turbine inlet temperature, and shaft speeds. These modes apply different sequencing of bleed valve opening on the air compressor side of the engine. Improper selection of the GT and the driven centrifugal gas compressor operating conditions can lead to larger bleed losses due to wider bleed valve openings. The bleed loss inevitably manifests itself in the form of higher overall heat rate of the GT and greater engine emission. It is, therefore, imperative to determine and understand the engine and process conditions that drive the GT to operate in these different modes. The ultimate objective is to operate the engine away from the inefficient modes by adjusting the driven gas compressor parameters as well as the overall station operating conditions (i.e., load sharing, control set points, etc.). This paper describes a methodology to couple the operating conditions of the gas compressor to the modes of GT bleed valve opening (and the subsequent air bleed rates) leading to identification of the operating parameters for optimal performance (i.e., best overall efficiency and minimum CO2e emission). A predictive tool is developed to quantify the overall efficiency loss as a result of the different bleed opening modes and map out the condition on the gas compressor characteristics. One year's worth of operating data taken from two different compressor stations on TransCanada Pipelines' Alberta system were used to demonstrate the methodology. The first station employs a GE-LM1600 gas turbine driving a Cooper Rolls-RFBB-30 centrifugal compressor. The second station employs a GE-LM-2500+ gas turbine driving NP PCL-800/N compressor. The analysis conclusively indicates that there are operating regions on the gas compressor maps where losses due to bleed valves are reduced and, hence, CO2 emissions are lowered, which presents an opportunity for operation optimization.

Performance adaptation of a 100 kW microturbine