Compressor Map Research Articles

Performance improvement of a centrifugal compressor for cogeneration

This work presents the performance improvement of a centrifugal compressor designed for cogeneration applications. The study involves modifications to geometric parameters, including impeller and diffuser configurations, to enhance pressure ratio, temperature ratio, and overall efficiency using computational fluid dynamics to verify the improvement of those parameters. The study has examined the compressor’s behaviour under surge, design, and choke conditions, showcasing improved homogeneity, reduced low-velocity zones, and an extended operating range. The compressor maps are presented to graphically observe the impact of each proposed modification, facilitating the analysis of each of these and evaluating the performance under various operating conditions. The final compressor configuration exhibits notable improvements in key performance metrics, with pressure ratio, temperature ratio, and efficiency showing increases of 1.753%, 1.640%, and 1.760%, respectively.

ANALYSIS OF MICRO GAS TURBINE PERFORMANCE USING MODELLING APPROACH

Micro-gas turbine (MGT) is compact and self-sufficient distributed power generation units that exhibit reliability and has the capability to mitigate carbon monoxide (CO) emissions while conserving energy together with biomass used as a fuel sources. It is expected that they will have a noteworthy impact on securing the provision of upcoming energy resources for isolated areas, disaster condition and off-grid zone regardless of their connection to the power grid. However, the MGT performance using the various fuel still questionable. Databases and procedure of the MGT performance analysis should be established well to understand the overall MGT performance. In this study, MGT performance is determined by utilising the computer aided design (CAD) and solver software such as SOLIDWORKS and ANSYS-FLUENT. CAD drawing is used to design the combustion chamber and simulation performance is visualised in specific inside the combustion chamber (CC) of the MGT. The solver software was employed for the purpose of conducting computational fluid dynamics (CFD) analyses. The optimal configuration contained a flame holder with a diameter of 50 millimetres, a chamber height of 60 centimetres, four holes with diameters of 6, 8, and 10 millimetres, and a dead zone separating the combustion and dilution zones. The air inlet boundary conditions were established by utilising the specifications and compressor maps of the Garrett GT25 turbocharger in the simulation. The simulation employed the standard k-ε model of viscous model and energy equation to establish an optimal maximum airflow rate of 0.15 kg/s at a pressure of 1.4 bar, resulting in a compressor efficiency of approximately 70%. Three different fuels, diesel-air, wood-volatiles-air, and coal-hv-volatile, were used to determine the MGT's optimal performance. Successful investigation of this study opts to significant contribution to understand the MGT performance thus, give the awareness to choose as one of the alternative power generations which can be used in the future.

An improved model for primary prediction of performance map for turbocharger radial turbine

In the contemporary landscape, possessing an intricate understanding of the performance characteristics of turbocharger radial turbine proves invaluable during engine development phases, to improve predictive capabilities of calculation codes and enhance the critical process of matching engines with turbochargers. This research deals with offering two precise yet straightforward analytical functions intended to generate comprehensive performance maps of turbocharger turbines. This is achieved through a refined adjustment of a preexisting analytical function, after introducing an inventive multiplication factor that aligns numerical calculations with experimental data to predict the turbine’s expansion ratio. Besides, a second analytical function forecasts the turbine’s thermo-mechanical efficiency by establishing a power balance equation between the turbine and supplied compressor map. The outcome of the developed model is compared with existing method on two distinct turbochargers, encompassing various rotational speeds. Additionally, a sensitive analysis aiming to detect the most important factors affecting our developed model while exploring it possible validity range for different thermodynamic parameters. The results indicate that the two functions yield reliable estimations of turbine performance, with maximum; root mean square error, R2, and mean absolute percentage error indices find around 9.47%, 0.993, and 9.03% for the turbine expansion ratio, and about 4.42%, 0.612, and 19.78% for efficiency prediction. This novel model enhances simulation accuracy while preserving user-friendliness and robustness based on the prerequisite of limited geometric and thermodynamic parameters at the turbocharger boundaries. Finally, the main advantages of the proposed model is its adaptability for the implementation in calculation codes, turbomachinery optimization strategies and assessments of the design and performance, addressing scenarios where the original turbine maps are rarely provided by turbocharger manufacturers.

Predicting compressor mass flow rate using various machine learning approaches

Abstract A major focus of the present study is to construct high-fidelity models for predicting corrected mass flow rates based on the collected compressor map data. Both traditional machine learning research and modern deep learning techniques have been employed to obtain well-fitted regression models of compressor mass flow rate. As traditional machine learning methods, Multiple Linear Regression and Random Forest, are conducted on compressor maps for prediction of corrected mass flow rate. The time series-based deep learning models are able to capture the overall trend of a given input for specific map data. Therefore, a time series-based deep learning technique, namely Gated Recurrent Unit has been employed to improve regression results. Besides, the prediction capabilities of the models, results also show that the proposed models can be used for the development of dynamic aero-thermal mathematical models of gas turbine engines and mass flow rate models created for dynamic compressors in other disciplines.

Research on speculation method for compressor map of PG9351FA gas turbine

A compressor map is usually represented by a limited number of feature points to speculate the entire operating range. Also, accurate compressor map models can be obtained quickly by using the appropriate methods. In this paper, 9351FA gas turbine is used as the research object, and a set of targeted compressor map speculation scheme is proposed. At 15 data points, high-precision compressor maps are obtained based on BP neural network, and this method is suitable for a large number of data points. At 6 data points, compressor maps are obtained based on the parameter estimation method, and this method is suitable for a small number of data points. The mean square deviation of the compressor map obtained by the neural network is about 0.002, while the minimum mean square deviation of the results of the parameter estimation method is 0.026 and the maximum mean square deviation is 0.088. Since the corrected speed line of 106.4 is almost vertical, the maximum error mean squared deviation and the maximum standard deviation occur on this line. Both methods are suitable for different sample sizes, and the speculated compressor maps are more reliable. The combination of the two methods can provide a set of reference methods for compressor map speculation.

Model-based performance study of an industrial single spool gas turbine 9EA-GT by changing the inlet guide vane angle and modifying the compressor map

Model-based performance study of an industrial single spool gas turbine 9EA-GT by changing the inlet guide vane angle and modifying the compressor map

Performance map of the hydraulic air compressor (HAC) installed at Dynamic Earth, Sudbury

After a 6-month construction phase, the approximately 30m high hydraulic air compressor (HAC) demonstrator facility installed at the Dynamic Earth science centre in Sudbury was officially opened on June 21, 2017. For the first time in the open literature, this paper presents experimental results from a large scale hydraulic air compressor, which proves their performance as an energy efficiency technology for industrial air compression. The temperature rise of air compressed in the HAC downcomer has been repeatedly measured at around 0.010K, experimentally confirming the process to be nearly isothermal. The ratio of mass flow air at intake to mass flow of air at output peaked at 94% for the conditions tested. The theoretical peak efficiency of compression for HAC Demonstrator geometry (predicted to be nearly 73%) was only attained when an in-line air–water mixing system replaced a century-old air–water mixing head design.

A novel marine turbocharger compressor volume flow rate model based on stagnation enthalpy theory

The compressor volume flow rate model determines the mass flowing into the diesel engine in simulation. It is a key component model that affects the accuracy of the overall performance of the diesel engine. At present, there is a lack of an accurate and easy-to-use compressor volume flow rate model. To solve this, the stagnation enthalpy-based compressor volume flow rate model (SP model) is proposed. The SP model is compared with an improved version of the famous empirical JENSEN model, M-JENSEN (MJ), and physics-based KS model. The proposed SP model only requires the stagnation pressure to be determined. The empirical M-JENSEN model needs a compressor map to optimize its six parameters. The physics-based KS model requires specific work to be determined. The SP model needs the least measured data and is easy to be identified. Models’ accuracy comparison on ABB A270 shows that the proposed SP model can generate the compressor map with RMSE of about 1.1m3/s and mean relative error (MRE) of about 6.9%. The rated volume flow rate of ABB A270 is about 20m3/s. While the RMSE and MRE of MJ model are about 0.6m3/s and 3.1% respectively. And they are about 3.0m3/s and 17.4% for KS model. When the model’s accuracy is compared to MAN TCA88, SP model shows slightly better performance than its performance on ABB A270. The rated volume flow rate of MAN TCA88 is about 60m3/s. The values of RMSE of SP model, MJ model, and KS model are 3.2m3/s, 2.2m3/s, 10.3m3/s respectively. Their MREs are 6.73%, 4.45%, and 17.8% respectively. In terms of these results, it can be concluded that our proposed SP model needs the least data, easy to code, and has excellent performance. It is one of the best compressor mass flow rate models so far in real-time diesel simulation.

Axial Compressor Map Generation Leveraging Autonomous Self-Training Artificial Intelligence. Phase 2

Abstract This paper discusses a study performed by SoftInWay as part of a Phase II SBIR project funded by NASA. In contrast with the Phase I project (Burlaka and Moroz, 2023, “Axial Compressor Map Generation Leveraging Autonomous Self-Training Artificial Intelligence,” ASME J. Eng. Gas Turbines Power, 145(1), p. 011001) where three discrete compressors were considered, the Phase II study was focused on addressing the problem of axial compressor long development time and cost with the use of AI models capable of predicting the geometry and performance of various multistage axial compressors with multiple variable vanes. The applicability of the AI models to various compressors enables the opportunity to avoid iterations between engine cycle analysis and compressor design. In this paper, automated compressor design and performance generation workflows are described. The approach for autonomous selection of the architectures and hyperparameters of Machine Learning (ML) models is explained. The uncertainty quantification techniques are considered. The developed ML-powered methods for compressor geometry prediction are discussed. The ML models' accuracy values and representations of typical geometry and performance predictions are given. The utilization of the ML models in engine cycle analysis is discussed.

Equivalent diffusion ratio distribution in the UGT15000 low pressure compressor

With spatial and temporal periodicity approach the results of steady state CFD simulation of compressible air flow in each blade-to-blade row of low pressure compressor (LPC) of the UGT15000 gas turbine engine (Ukrainian SSR constr. and prod.) are presented. Near the nominal rotation speed compressor map and adiabatic efficiency of each stage and the flow angles at leading and trailing blade edges are predicted and calculated. At the average radius stage flow and stage load coefficients are determined. It has been established that the reason of the low efficiency of the last stage is associated with the low stage reaction (≈0.5) leading to high airflow swirling at outlet. For LPC optimization a calculation of the radial distributions of the equivalent diffuser coefficient was performed. It is shown that the greatest total pressure losses are in the stator rows of stages 9, 8, 5 and in the rotor rows of stage 9. High losses are also shown on the upper half of the 4th, 3rd, 2nd stator blades and the lower half of the 1st rotor blades. The identified potential for increasing the efficiency of the LPC is up to 2% without significant construction changes.

Modeling of Proton Exchange Membrane Fuel Cell Stack and Start Strategy Optimization with a Multi-Objective Genetic Algorithm

This paper proposes a non-dominated ranking genetic algorithm (NSGA-II) method for fast optimizing the loading strategy at the start of a proton exchange membrane fuel cell (PEMFC) stack to optimize the dynamic response capability, power density and system efficiency. First, a Simulink model of the PEMFC stack including anode module, cathode module, water transfer module and output voltage module is established as the base model for optimization, and the accuracy of the stack model is verified through experiments. The power consumption of the air compressor is the main parasitic power considered, and it is modelled using the air compressor map by taking a table look-up method directly. The three performance indicators of dynamic response capability, power density and system efficiency are then optimized simultaneously based on NSGA-II. The results show that the optimized start-up loading strategy results in a PEMFC stack that outperforms the base model in all three indicators, demonstrating the success of the method in solving time-consuming multiple optimization problems. This study presents an effective and rapid approach for the multi-objective optimization of PEMFC stack, which is of guidance for engineering practice.

A Surge/Stall-Capable Dynamic Performance Simulation Methodology for a Turbojet Engine

Abstract A lumped-parameter dynamic performance model for a single-spool turbojet engine is presented in this paper. This model can handle pre and poststall transients under forward and reverse-flow conditions. The inter-component volume technique is employed instead of the standard matching technique to be able to handle high-frequency transients and reverse-flow conditions. Inspired by Greitzer's lumped-parameter surge model, momentum (duct) and volume elements are placed within the flow path to handle surge dynamics. Compressor and turbine maps are extended to low-flow and reverse-flow regions using a combination of the guidelines presented by Kurzke, the cubic axisymmetric characteristics of Moore and Greitzer, and a quadratic function guess for in-stall characteristics. Combustor efficiency, stability limits, and delay are taken from the literature. Poststall behavior of the model is validated using the data available in the literature for a Rolls-Royce Viper engine. A good match is observed with a correct prediction of poststall behaviors, which transition from surge after locked stall to multiple surge cycles around 80% speed and multiple surge cycles to surge after flameout around 95% speed. The effects of different modeling choices and modeling parameters on the obtained results are discussed. The produced model can be calibrated for a specific engine with surge tests, and it can be used for hard-to-test scenarios like surge after shaft breakage. Different surge/stall-causing events, such as fuel spiking, in-bleeding, and shaft breakage, are simulated to see the capabilities of the model.

Model Predictive Control Strategies for Turbine Electrified Energy Management

Abstract The increasing electrification of aircraft propulsion systems is leading to new control architectures being developed to address integration between electric machines and gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures often couple electric machines with the shafts of gas turbine engines and introduce energy storage. Leveraging the electrical power system of hybridized engines, Turbine Electrified Energy Management (TEEM) is a recent control approach that improves transient operability in an effort to enable more efficient and lighter weight turbomachinery. This study seeks to expand TEEM's application beyond traditional proportional-integral (PI) control by presenting linear model predictive control (MPC) schemes to execute the TEEM concept. Through constraint selection and cost function design, transient operability goals for TEEM are considered with no external logic or saturation. Unique to the designs are the use of a washout filter, which simplifies transient detection and motor activation logic. The proposed architectures are implemented with both centralized MPC and distributed MPC approaches, and comparisons are drawn to a benchmark PI controller simulated on a nonlinear turbofan engine model at one ground condition and one cruise condition. Performance is evaluated using compressor maps, stall margin performance, and two novel metrics: transient stack usage and transient excursion integral. Results reveal the linear MPC scheme performs comparably to the baseline controller and can be implemented in at least two distinct configurations with potential for further modifications, thus establishing the groundwork for future investigations.

Adjoint-Based Design Optimization of a Volute for a Radial Compressor

Numerical optimization methods are widely used for designing turbomachinery components due to the cost and time savings they can provide. In the available literature, the shape optimization of radial compressors mainly focuses on improving the impeller alone. However, it is well-established knowledge that the volute plays a key role in the overall performance of the compressor. The aim of the present paper is to perform an adjoint-based optimization of a volute that is designed for the SRV2-O compressor. The CAD model was first created by using the parametrization of 33 design parameters. Then, a butterfly topology was applied to mesh the computational domain with a multi-block structured grid, and an elliptic smoothing procedure was used to improve the quality of the fluid grid. A steady-state RANS CFD solver with a Spalart-Allmaras turbulence model was used to solve the Navier–Stokes equations, and then the flow sensitivities were computed with an adjoint solver. The objective function consists of minimizing the loss coefficient of the volute. The optimization is performed to obtain an improved design with a 14% loss reduction. A detailed flow and design analysis is carried out to highlight the loss reduction mechanisms, followed by the optimizer. Finally, the compressor map of the full stage is compared between the baseline and the optimized volute from the CFD simulations using a mixing plane interface. This research demonstrates the successful use of a gradient-based optimization technique to improve the volute of a radial compressor and opens the door towards simultaneously optimizing the wheel and the volute.

Aero-Engine Preliminary Design Optimization and Operability Studies Supported by a Compressor Mean-Line Design Module

An approach for preliminary aero-engine design, incorporating a mean-line code for the design of axial-flow, multi-stage compressors, is presented. The compressor mean-line code is developed and integrated within a framework for the preliminary design and assessment of aero-engine concepts. It is then combined with modules for compressor map generation, multi-point engine design, steady-state and transient engine off-design performance and aircraft mission analysis. Implementation examples are presented, demonstrating the determination of the optimal combination of compressor and engine design parameters for achieving minimum fuel burn over a specific aircraft mission, while obeying constraints that guarantee operability over the entire flight envelope. Constraints related to compressor stability during transient maneuvers between idle and static take-off conditions and engine temperature limits at maximum take-off are respected by the final design. The results demonstrate the potential for design trade-offs between engine performance at the aircraft mission level and compressor aerodynamic stability.

Off-design performance of micro-scale solar Brayton cycle

A novel methodology to design a micro-scale, solar-only, air-breathing, open Brayton cycle and assess its on- and off-design performance. The methodology is applied to generate and assess six thermodynamic layouts over a range of solar irradiation levels. All plants have the same on-design requirements to create a baseline to compare their off-design performance. PyCycle, a thermodynamic cycle modeling library to model jet engine performance, is revised to transform the jet engine performance modeling to solar thermal plant performance modeling and used to create a volumetric receiver component. A response surface surrogate model of the receiver is created for design optimization to maximize the component-level efficiency. The compressor and turbine maps are scaled for the balance of the plant. Off-design efficiency, mass flow rate, operation range, turbomachinery maps, and maximum power output are presented. Since the methodology can be adapted to all plant sizes, the results are normalized to on-design condition. The outcome of this study demonstrates the impact of the thermodynamic configuration on off-design performance and provides a methodology to design plants that are more robust across a range of solar irradiation levels and can be operated in a more flexible manner. Compared to single shaft configuration, solar radiation operation range is improved by 5%, with 6% less mass flow, and operates more efficiently than the benchmark case over 85% of the operating regime.

Uncertainty Quantification of Compressor Map Using the Monte Carlo Approach Accelerated by an Adjoint-Based Nonlinear Method

Precise and inexpensive uncertainty quantification (UQ) is crucial for robust optimization of compressor blades and to control manufacturing tolerances. This study looks into the suitability of MC−adj−nonlinear, a nonlinear adjoint-based approach, to precisely and rapidly assess the performance discrepancies of a transonic compressor blade section, arising from geometric alterations, and building upon previous research. In order to assess the practicality and illustrate the benefits of the adjoint-based nonlinear approach, its proficiency and precision are gauged against two other methodologies, the adjoint-based linear approach (MC−adj−linear) and the high-fidelity nonlinear Computational Fluid Dynamics (MC−CFD) method. The MC−adj−nonlinear methodology exhibits impressive generalization capabilities. The MC−adj−nonlinear method offers a great balance between precision and time efficiency, since it is more precise than the MC−adj−linear method in both design and near-stall conditions, yet requires approximately a thirtieth of the time of the MC−CFD method. Finally, the MC−adj−nonlinear method was utilized to conduct fast UQ analyses of the section at four distinct speeds to quantify the performance uncertainty for the compressor map. It is found that aerodynamic performance is more sensitive to geometric deviations at high speeds than at low speeds. The impact of the geometric deviations is generally detrimental to the mean efficiency.

Starting and windmilling simulations using compressor and turbine maps

Starting and windmilling simulations with a normal gas turbine performance program require extended compressor and turbine maps which include sub-idle corrected speeds down to say 5–10% of the design value. During such simulations certain specific phenomena which are insignificant in the normal operating range between idle and full power must be considered. For example, while starting a low bypass ratio mixed flow turbofan, flow reversal in the bypass duct can occur. This paper illustrates a general understanding of what happens from when the starter is activated to when stabilized idle operation is reached. Operating lines in the compressor and turbine maps are predicted depending on starter torque, starter power, burner light-up and starter cut-off speed. It is explained why knowing combustor efficiency precisely is not required for that. Simulating engine starting and windmilling is not a magical art. The laws of physics still apply at these somewhat exotic operating conditions.

Simulating Combined Cycle and Gas Turbine Power Plant under Design Condition using Open-Source Software DWSIM

Nowadays, clean and high-power generation is essential matters worldwide. To be improved and optimized, power plants require accurate models that can be introduced to process simulators. There is various commercial software for industrial simulation which is not accessible to everyone. The open-source DWSIM process simulator is the first chemical engineering code that offers many tools for the better study of industrial plants. In this paper, we employ DWSIM software to simulate a combined cycle gas turbine (CCGT) power plant under design conditions for three cases. The generic models are predicted for multistage compressors and compressor maps. In the first case, two models developed in ASPEN HYSYS and GateCycle will be considered. The achieved results by DWSIM are acceptably comparable for thermal efficiency and power generation. The DWSIM result is 3.5% lower than the ASPEN HYSYS for thermal efficiency, and the power generation is completely the same. In the second case, rigorous simulation was carried out using actual field data from the local CCGT power plant. The DWSIM outcomes are very close to the practical data. The power generation of GT and CC is very close; the variety is nearly 0.45%. In the third case, the simulation of CCGT with a cogeneration system is precisely accomplished, and the outcomes of DWSIM are shown in excellent agreement. The DWSIM prediction shows lower values by 0.26%, 4.79%, and 0.72% for the HP turbine, LP turbine, and plant net power, respectively.

Assessment of the impact of the number and the arrangement of cylinders of the KAMAZ disel engines on their fuel efficiency

Most of the natural aspirated truck diesel engines had an eight-cylinder V-twin (V8) configuration. Modern turbocharged diesel engines have a six-cylinder in-line configuration (L6), although some V8 diesel engines continue to be produced. A comparison was made of the performance of the KAMAZ-740 (V8) diesel engine with two turbochargers and KAMAZ-910 (L6) diesel engines with one turbocharger, having almost the same displacement with the same pattern of torque along the full load characteristic. The AVL BOOST software and experimental compressor and turbine maps were used. The factors influencing fuel efficiency were analyzed: indicated efficiency, friction and gas exchange losses, turbocharger efficiency. The L6 diesel engine had a uniform pressure pulsation in the exhaust manifold and at the turbine inlet. In the V8 diesel engine, the pulsations were uneven and had higher amplitude, which led to higher gas exchange losses and a decrease in turbine efficiency. The L6 diesel engine had a higher indicated efficiency but also higher friction losses. On average, the brake specific fuel consumption of the L6 diesel engine was by 5.5 % lower than that of the V8 diesel engine. Keywords V8 and P6 diesel engines; modeling in AVL BOOST; pressure pulsations in the exhaust system; turbocharger efficiency; friction and gas exchange losses