Numerical Approach for Real Gas Simulations: Part II — Flow Simulation for Supercritical CO2 Centrifugal Compressor

This paper is presented in two parts. Part I (Tabular fluid properties for real gas analysis) describes an approach to creating a tabular representation of the equation of state that is applicable to any fluid. This approach is applied to generating an accurate and robust tabular representation of the RefProp CO2 properties. Part II (this paper) presents numerical simulations of a low flow coefficient supercritical CO2 centrifugal compressor developed for a closed loop power cycle. The real gas tables presented in part I are used in these simulations. Three operating conditions are simulated near the CO2 critical point: normal day (85 bar, 35C), hot day (105 bar, 50 C) and cold day (70 bar, 20C) conditions. The compressor is a single stage overhung design with shrouded impeller, 155 mm impeller tip diameter and a vaneless diffuser. An axial variable inlet guide vane (IGV) is used to control the incoming swirl into the impeller. An in-house three-dimensional computational fluid dynamics (CFD) solver named TACOMA is used with real gas tables for the steady flow simulations. The equilibrium thermodynamic modeling is used in this study. The real gas effects are important in the desired impeller operating range. It is observed that both the operating range (minimum and maximum volumetric flow rate) and the pressure ratio across the impeller are dependent on the inlet conditions. The compressor has nearly 25% higher operating range on a hot day as compared to the normal day conditions. A condensation region is observed near the impeller leading edge which grows as the compressor operating point moves towards choke. The impeller chokes near the mid-chord due to lower speed of sound in the liquid-vapor region resulting in a sharp drop near the choke side of the speedline. This behavior is explained by analyzing the 3D flow field within the impeller and thermodynamic quantities along the streamline. The 3D flow analysis for the flow near the critical point provides useful insight for the designers to modify the current compressor design for higher efficiency.

Optimization of Statistical Methodologies for Anomaly Detection in Gas Turbine Dynamic Time Series

Statistical parametric methodologies are widely employed in the analysis of time series of gas turbine sensor readings. These methodologies identify outliers as a consequence of excessive deviation from a statistically-based model, derived from available observations. Among parametric techniques, the k-σ methodology demonstrates its effectiveness in the analysis of stationary time series. Furthermore, the simplicity and the clarity of this approach justify its direct application to industry. On the other hand, the k-σ methodology usually proves to be unable to adapt to dynamic time series, since it identifies observations in a transient as outliers. As this limitation is caused by the nature of the methodology itself, two improved approaches are considered in this paper in addition to the standard k-σ methodology. The two proposed methodologies maintain the same rejection rule of the standard k-σ methodology, but differ in the portions of the time series from which statistical parameters (mean and standard deviation) are inferred. The first approach performs statistical inference by considering all observations prior to the current one, which are assumed reliable, plus a forward window containing a specified number of future observations. The second approach proposed in this paper is based on a moving window scheme. Simulated data are used to tune the parameters of the proposed improved methodologies and to prove their effectiveness in adapting to dynamic time series. The moving window approach is found to be the best on simulated data in terms of True Positive Rate (TPR), False Negative Rate (FNR) and False Positive Rate (FPR). Therefore, the performance of the moving window approach is further assessed towards both different simulated scenarios and field data taken on a gas turbine.

Partial Admission, Axial Impulse Type Turbine Design and Partial Admission Radial Turbine Test for SCO2 Cycle

Power generation cycle — typically Brayton cycle — to use CO2 at supercritical state as working fluid have been researched many years because this cycle increase thermal efficiency of cycle and decrease turbomachinery size. But small turbomachinery make it difficult to develop proto type Supercritical Carbon dioxide (S-CO2) cycle equipment of lab scale size. KIER (Korea Institute of Energy Research) have been researched S-CO2 cycle since 2013. This paper is about 60kWe scale and sub-kWe class turbo generator development for applying to this S-CO2 cycle at the lab scale. A design concept of this turbo-generator is to use commercially available components so as to reduce development time and increase reliability. Major problem of SCO2 turbine is small volume flow rate and huge axial force. High density S-CO2 was referred as advantage of S-CO2 cycle because it make small turbomachinery possible. But this advantage was not valid in lab-scale cycles under 100kW because small amount volume flow rate means high rotating speed and too small diameter of turbine to manufacture it. Also, high inlet and outlet pressure make huge axial force. To solve these problem, KIER have attempt various turbines. In this paper, these attempts and results are presented and discussed.

Optimization of Supercritical CO2 Brayton Cycle for Simple Cycle Gas Turbines Exhaust Heat Recovery Using Genetic Algorithm

For the application of waste heat recovery (WHR), supercritical CO2 (S-CO2) Brayton power cycles offer significant suitable advantages such as compactness, low capital cost and applicable to a broad range of heat source temperatures. The current study is focused on thermodynamic modelling and optimization of Recuperated (RC) and Recuperated Recompression (RRC) S-CO2 Brayton cycles for exhaust heat recovery from a next generation heavy duty simple cycle gas turbine using a genetic algorithm. The Genetic Algorithm (GA) is mainly based on bio-inspired operators such as crossover, mutation and selection. This non-gradient based algorithm yields a simultaneous optimization of key S-CO2 Brayton cycle decision variables such as turbine inlet temperature, pinch point temperature difference, compressor pressure ratio. It also outputs optimized mass flow rate of CO2 for the fixed mass flow rate and temperature of the exhaust gas. The main goal of the optimization is to maximize power out of the exhaust stream which makes it single objective optimization. The optimization is based on thermodynamic analysis with suitable practical assumptions which can be varied according to the need of user. Further the optimal cycle design points are presented for both RC and RRC configurations and comparison of net power output is established for waste heat recovery.

Three-Dimensional Aerodynamic Analysis of a Darrieus Wind Turbine Blade Using Computational Fluid Dynamics and Lifting Line Theory

Due to the rapid progress in high-performance computing and the availability of increasingly large computational resources, Navier-Stokes computational fluid dynamics (CFD) now offers a cost-effective, versatile and accurate means to improve the understanding of the unsteady aerodynamics of Darrieus wind turbines and deliver more efficient designs. In particular, the possibility of determining a fully resolved flow field past the blades by means of CFD offers the opportunity to both further understand the physics underlying the turbine fluid dynamics and to use this knowledge to validate lower-order models, which can have a wider diffusion in the wind energy sector, particularly for industrial use, in the light of their lower computational burden. In this context, highly spatially and temporally refined time-dependent three-dimensional Navier-Stokes simulations were carried out using more than 16,000 processor cores per simulation on an IBM BG/Q cluster in order to investigate thoroughly the three-dimensional unsteady aerodynamics of a single blade in Darrieus-like motion. Particular attention was payed to tip losses, dynamic stall, and blade/wake interaction. CFD results are compared with those obtained with an open-source code based on the Lifting Line Free Vortex Wake Model (LLFVW). At present, this approach is the most refined method among the “lower-fidelity” models and, as the wake is explicitly resolved in contrast to BEM-based methods, LLFVW analyses provide three-dimensional flow solutions. Extended comparisons between the two approaches are presented and a critical analysis is carried out to identify the benefits and drawbacks of the two approaches.

Real Time Conditioning Monitoring for Failure Prediction

Nowadays, the growth in the diameter of the rotors and the power capacity of the machinery require the application of constant monitoring to predict failures and reduce maintenance activities. These activities prevent emergency stops and failures that require the replacement of components; however, these operations involve a high cost. The system presented in this paper integrates a fast data processing method that can analyze monitoring signals in real-time. The overall system includes a set of sensors for the measurement of acceleration, angular velocity, temperature, voltage, electrical current, and oil quality. The system presented is able to produce a frequency spectrum with a length of 8192 points. The FFT module was implemented in a FPGA (Field Programmable Gate Array) and it generates in real time, the frequency spectrum. This system adjusts the dominant frequencies to the wind turbine velocity.

Aeroelastic Analysis of NREL Wind Turbine

The current development of wind turbines is moving toward larger and more flexible units, which can make them prone to fatigue damage induced by aeroelastic vibrations. The estimation of the total life of the composite components in a wind turbine requires the knowledge of both low and high cycle fatigue (LCF and HCF) data. The first aim of this study is to produce a validated numerical model, which can be used for aeroelastic analysis of wind turbines and is capable of estimating the LCF and HCF loads on the blade. The second aim of this work is to use the validated numerical model to assess the effects of extreme environmental conditions (such as high wind speeds) and rotor over-speed on low and high cycle fatigue. Numerical modelling of this project is carried out using the Computational Fluid Dynamics (CFD) & aeroelasticity code AU3D, which is written at Imperial College and developed over many years with the support from Rolls-Royce. This code has been validated extensively for unsteady aerodynamic and aeroelastic analysis of high-speed flows in gas turbines, yet, has not been used for low-speed flows around wind turbine blades. Therefore, in the first place the capability of this code for predicting steady and unsteady flows over wind turbines is studied. The test case used for this purpose is the Phase VI wind turbine from the National Renewable Energy Laboratory (NREL), which has extensive steady, unsteady and mechanical measured data. From the aerodynamic viewpoint of this study, AU3D results correlated well with the measured data for both steady and unsteady flow variables, which indicated that the code is capable of calculating the correct flow at low speeds for wind turbines. The aeroelastic results showed that increase in crosswind and shaft speed would result in an increase of unsteady loading on the blade which could decrease the lifespan of a wind turbine due to HCF. Shaft overspeed leads to significant increase in steady loading which affects the LCF behaviour. Moreover, the introduction of crosswind could result in significant dynamic vibration due to forced response at resonance.

Development of Reliable NARX Models of Gas Turbine Cold, Warm and Hot Start-Up

This paper documents the set-up and validation of nonlinear autoregressive exogenous (NARX) models of a heavy-duty single-shaft gas turbine. The considered gas turbine is a General Electric PG 9351FA located in Italy. The data used for model training are time series data sets of several different maneuvers taken experimentally during the start-up procedure and refer to cold, warm and hot start-up. The trained NARX models are used to predict other experimental data sets and comparisons are made among the outputs of the models and the corresponding measured data. Therefore, this paper addresses the challenge of setting up robust and reliable NARX models, by means of a sound selection of training data sets and a sensitivity analysis on the number of neurons. Moreover, a new performance function for the training process is defined to weigh more the most rapid transients. The final aim of this paper is the set-up of a powerful, easy-to-build and very accurate simulation tool which can be used for both control logic tuning and gas turbine diagnostics, characterized by good generalization capability.

Comparison of Supercritical CO2 Power Cycles to Steam Rankine Cycles in Coal-Fired Applications

Increasing the efficiency of coal-fired power plants is vital to reducing electricity costs and emissions. Power cycles employing supercritical carbon dioxide (sCO2) as the working fluid have the potential to increase power cycle efficiency by 3–5% points over state-of-the-art oxy-combustion steam-Rankine cycles operating under comparable conditions. To date, the majority of studies have focused on the integration and optimization of sCO2 power cycles in waste heat, solar, or nuclear applications. The goal of this study is to demonstrate the potential of sCO2 power cycles, and quantify the power cycle efficiency gains that can be achieved versus the state-of-the-art steam-Rankine cycles employed in oxy-fired coal power plants. Turbine inlet conditions were varied among the sCO2 test cases and compared with existing Department of Energy (DOE)/National Energy Technology6 Laboratory (NETL) steam base cases. Two separate sCO2 test cases were considered and the associated flow sheets developed. The turbine inlet conditions for this study were chosen to match conditions in a coal-fired ultra-supercritical steam plant (Tinlet = 593°C, Pinlet = 24.1 MPa) and an advanced ultra-supercritical steam plant (Tinlet = 730°C, Pinlet = 27.6 MPa). A plant size of 550 MWe, was selected to match available information on existing DOE/NETL bases cases. The effects of cycle architecture, combustion-air preheater temperature, and cooling source type were considered subject to comparable heat source and reference conditions taken from the steam Rankine reference cases. Combinations and variants of sCO2 power cycles — including cascade and recompression and variants with multiple reheat and compression steps — were considered with varying heat-rejection subsystems — air-cooled, direct cooling tower, and indirect-loop cooling tower. Where appropriate, combustion air preheater inlet temperature was also varied. Through use of a multivariate nonlinear optimization design process that considers both performance and economic impacts, curves of minimum cost versus efficiency were generated for each sCO2 test case and combination of architecture and operational choices. These curves indicate both peak theoretical efficiency and suggest practical limits based on incremental cost versus performance. For a given test case, results for individual architectural and operational options give insight to cost and performance improvements from step-changes in system complexity and design, allowing down selection of candidate architectures. Optimized designs for each test case were then selected based on practical efficiency limits within the remaining candidate architectures and compared to the relevant baseline steam plant. sCO2 cycle flowsheets are presented for each optimized design.

Heat Exchanger Options for Dry Air Cooling for the sCO2 Brayton Cycle

The capability to utilize dry air cooling by which heat is directly rejected to the air atmosphere heat sink is one of the benefits of the supercritical carbon dioxide (sCO2) energy conversion cycle. For the selection and analysis of the heat exchanger options for dry air cooling applications for the sCO2 cycle, two leading forced air flow design approaches have been identified and analyzed for this application; an air cooler consisting of modular finned tube air coolers; and an air cooler consisting of modular compact diffusion-bonded heat exchangers. The commercially available modular finned tube air cooler is found to be more cost effective and is selected as the reference for dry air cooling.