Turbine Mass Flow Rate Research Articles

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.

Off-design operation of supercritical CO2 Brayton cycle arranged with single and multiple turbomachinery shafts for lead-cooled fast reactor

The lead-cooled fast reactor (LFR) engenders novel requisites for the energy conversion system when applied to maritime ships and distributed energy supply systems. The supercritical carbon dioxide (sCO2) Brayton cycle, with the advantages of high efficiency, space-saving, simplicity, and flexibility, is a promising candidate for LFR. Here, we present the first study on the off-design operation of the sCO2 cycle for LFR, with the turbine and compressor arranged on a single shaft (coaxial-shaft) or two shafts (split-shaft). The off-design performances of the system are investigated using four rotational speed (RS) control-based hybrid control strategies. We showed that the split-shaft system controlled by separate turbine speed and compressor speed has a wider operating space of power load than the coaxial-shaft system. Among the four investigated control strategies, the RS-inventory hybrid control can achieve the best thermal efficiency during load variation by operating at the turbine speed and mass flow rate corresponding to the optimal turbine isentropic efficiency. The maximum operating space of power load (0%–100 %) can be achieved by the RS-turbine inlet pressure hybrid control and the RS-bypass hybrid control. Our study can provide guidance for the flexible and safe part-load operation for small-scale modular Gen-IV nuclear reactors.

Optimum design of bivariate operation strategy for a supercritical/ transcritical CO2 hybrid waste heat recovery system driven by gas turbine exhaust

Gas turbines are always operated under part-load conditions to participate in the frequency regulation of power grids; therefore, the exhaust gas has fluctuating temperature and mass flow rate parameters. For better utilization of the waste heat in gas turbine exhaust under part-load conditions, a supercritical/transcritical carbon dioxide (CO2) hybrid waste heat recovery system with different operation strategies was studied. The turbine inlet pressure and mass flow rate were considered as the dominant factors affecting the system part-load performance, which formed a bivariate operation strategy. A solution procedure was proposed to optimize the bivariate operation strategy for a hybrid waste heat recovery system. The results indicate that the mass flow rate of the transcritical CO2 cycle has a greater effect on its net power than the turbine inlet pressure whereas these two regulation variables should be controlled cooperatively. The net power of the hybrid waste heat recovery system increased with an increase in the inlet valve opening of the supercritical CO2 turbine under a specific gas turbine load. Generally, the optimal bivariate operation strategy has the advantage of enhancing the part-load performance of a hybrid waste heat recovery system driven by gas turbine exhaust.

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.

Power prediction of waste heat recovery system for a cement plant using back propagation neural network and its thermodynamic modeling

This work targets on the prediction of power produced by a waste heat recovery (WHR) system for a cement plant using the back-propagation neural network (BPNN) and comparing its results with the actual cycle. A regression-based predictive model is developed to compare it with an actual WHR cycle that is analyzed thermodynamically. The predictive model is trained using the following parameters as input features: turbine inlet steam, pressure, temperature, and mass flow rate of both stages (i.e., high-pressure (HP) and low-pressure (LP) stages). The mean square error for the validation dataset is found to be 0.283 with 10 neurons in the hidden layer. Moreover, the significance of each parameter on the predicted power investigated shows that the HP stage parameters tend to have more impact on the power generated. The other half of the study comprises energy analysis of the power plant and a detailed parametric analysis to review the impact of each parameter on the power produced and thermal efficiency. The calculated thermal efficiency and generated power of the system are found to be 19.75% and 10.06 MW, respectively. Lastly, from the comparative study of the predictive model and the actual WHR simulated cycle, it is concluded that data science can be used as an alternative to thermodynamic modeling to avoid hefty calculations.

Effects of turbocharger rotational inertia on engine and turbine performance in a turbocharged gasoline direct injection engine under transient and steady conditions

The effects of turbocharger (T/C) rotational inertia on engine and turbine performance under transient and steady engine conditions were analyzed in a 2.0 L 4-cylinder turbocharged-gasoline direct injection (T-GDI) engine. The test T/Cs consisted of heavy and light compressor wheels (C/W) and turbine wheels (T/W). The study was conducted in two research stages. First, transient engine load tests were conducted to evaluate the effect of T/C rotational inertia on transient response of the T/C, combustion performance, and fuel consumption. Seconds, steady engine load tests were conducted to find out if a light inertia T/C can run at higher efficiency under the same exhaust pulsating flow conditions within one engine cycle. In order to evaluate the engine on-board turbine instantaneous performances in the units of crank angle degree (CAD), T/C rotation speed and pressure data were measured in the experiment. The instantaneous exhaust gas mass flow rate and the temperature of upstream and downstream of the turbine were extracted by 1-D simulation. Turbine efficiency and mass flow rate parameters were calculated by combining these data. In the results, there existed positive effects of light inertia T/C on response and specific fuel consumption under transient conditions. It was also found that the light inertia T/C could show higher T/C speed fluctuation under the same exhaust pulsating flow conditions. Consequently, blade speed ratio (BSR) and turbine efficiency of light inertia T/C were partially higher than that of conventional one. However, it was not led to higher engine efficiency.

Improvement of instantaneous turbine efficiency through late intake valve phase (LIVP) in a turbocharged-gasoline direct injection (T-GDI) engine

The effects of a late intake valve phase (LIVP) strategy on crank-angle resolved real-time turbocharger efficiency were analyzed. The research is composed of experiments and simulations. In the experiments, an engine test was conducted with a downsized 2.0 L 4-cylinder turbocharged-gasoline direct injection (T-GDI) engine. In order to evaluate the effects of LIVP on the instantaneous turbocharger efficiency, the intake valve phase was retarded from its reference phase to 30 crank angle degrees (CADs) by steps of 10 CADs, while maintaining the fixed position of the other engine control parameters. Pressure in the intake and exhaust systems and turbocharger rotational speed were also measured in the experiments. In the simulation, a 1-D simulation model was built to simulate the same conditions as in the experiments. Instantaneous turbine mass flow rate as well as, temperature upstream and downstream of the turbine were extracted from the model in the units of CAD. This was done because it is inherently impossible to measure these data in the units of CAD with the existing real-world mass flow meter and thermocouples. The instantaneous blade speed ratio (BSR), turbine efficiency, and mass flow parameter were calculated by combining the results of the experiment and the 1-D simulation. In the results, the instantaneous turbine efficiency was divided into two phases and analyzed. First, in the filling phase, the effects of exhaust blow-down pulse arrival on the instantaneous turbine efficiency were analyzed. Second, in the emptying phase, the effects of exhaust gas scavenged from the cylinder on the instantaneous turbine efficiency were analyzed. The instantaneous turbine efficiency showed strong unsteady characteristics and deviated from the quasi-steady performance line. This was due to large fluctuations in the turbine inlet conditions. With the application of the LIVP strategy, the instantaneous turbine efficiency was increased. This was because of a decrease in the amount the waste-gate opened while meeting the same engine load lead to more exhaust gas energy entering the turbine, and the turbine’s operating conditions were changed to more efficient conditions. Finally, correlation of the engine thermal efficiency rising according to the instantaneous turbine efficiency rising was confirmed.

On dynamic modeling of industrial gas turbines based on low calorific value (LCV) gaseous fuels

Global energy demand is expected to increase in the following two decades. Operational flexibility of power generation systems is a key aspect when assessing potential solutions seeking to help meeting this expected increase in global energy demand. In low calorific value (LCV) gaseous fuels-fired power plants, it is paramount to consider the effects of the employed LCV/lean-gases-based fuels on the associated gas turbine systems and surrounding equipment. Moreover, because of the industrial processes usually occurring upstream these power plants, the fuel supply conditions change significantly during their normal operation. Gas turbines based on LCV gaseous fuels thus present a quite distinct engine behavior, and their modeling is therefore challenging. The dynamic modeling of such engines is the main focus of this work. Accordingly, the gas turbine dynamic model developed here is initially discussed, along with topics, such as gas turbine mass flow rates, cooling systems effectiveness and gas turbine component characteristics, relevant to the dynamic modeling of LCV fuels-based power plants. The use of the developed model for the simulation of an actual combined cycle power plant with cogeneration based on a LCV fuel is next highlighted. The main results show that overall acceptable agreements between computed parameters and actual power plant operating data are obtained. The corresponding average discrepancies range from 1 to 6%. In spite of the large number of factors directly influencing the numerical results obtained from the real-time simulations carried out, the power plant operating data trends are in general well reproduced by the computed results. The obtained results highlight in particular both the model applicability to operating scenarios presenting significant gradients in gas turbine characteristic parameters, and the need of including in the modeling key processes present in power plants actual operation.

Design and off-design optimisation of an organic Rankine cycle (ORC) system with an integrated radial turbine model

This paper investigates the design and thermodynamic optimisation of both sub- and transcritical organic Rankine cycle (ORC) power systems featuring radial turbines via performance calculations using mean-line models. The emphasis is on rapid performance predictions for a given turbine geometry, as well as geometric optimisation for a given heat source. From three specified quantities, which are the turbine inlet temperature, inlet pressure and mass flow rate, the other flow properties (e.g., outlet pressure and temperature) are computed, together with derived quantities which are required for cycle- or system-level assessments, such as the isentropic efficiency of the turbine. Experimental investigations from the open literature suitable for validation purposes are summarised and analysed with respect to their strengths and weaknesses. Similar computational fluid dynamic (CFD) simulations are also used to complement the available experimental data. The main contributions of this paper are that it provides a comprehensive overview of radial turbine performance modelling, and that it proposes a detailed framework that can be used for the improved development of efficient thermodynamic power systems based on a unified mean-line model that is validated against experimental data and supported by CFD results. Specifically, predictions from the mean-line model show good accuracy over a wide range of operating conditions for different turbine designs and fluids with compressibility factors from 0.6 to 1.0. Finally, in order to demonstrate its efficacy, the integrated radial turbine and ORC system design framework is used in a case study of a nominally 400-kW power system with propane as the working fluid in low-grade waste-heat application, where the turbine inlet temperature is fixed at 150 °C and the condenser temperature is fixed at 15 °C. The novelty of this work arises from the optimisation of the turbine nozzle vane position at off-design conditions. This feature, along with multi-stage radial turbine designs are shown to allow high-performance operation over a wide range of off-design conditions. Specifically, good efficiencies are demonstrated over a wide range of heat-source fluid flow rates when employing an adjustable nozzle geometry, as is the ability of radial turbines to achieve efficiencies that are not constrained by the pressure ratio across them by replacing single-stage designs with multi-stage designs.

Effect of nozzle angle, turbine inlets and mass flow rate on the performance of a bladeless turbine

A comprehensive experimental study on the effects of different operating parameters on the efficiency of tesla turbine is reported. A bladeless turbine with nine discs and up to four turbine inlets was used, with water as the working fluid. The parameters investigated are the nozzle angle, number of turbine inlets and mass flow rates. Contrary to earlier studies, an effort was made to determine the performance under varying loading conditions, and hence identify the complete performance characteristics. The study revealed that efficiency of the turbine increases at lower nozzle angles and higher number of turbine inlets. It was observed that the nozzle angle becomes a significant parameter when the number of turbine inlets is increased. Efficiencies up to 78% were achieved when the working fluid entered the turbine through two nozzles at an angle of 7°. It was also noted that the turbine is most efficient at the designed mass flow rate, and the efficiency reduces appreciably if lower mass flow rates are fed to the turbine. The results obtained are an important contribution to the available knowledge and can be used as design references for further studies.

Study on the Effect of Turbine Inlet Temperature and Backpressure Conditions on Reduced Turbine Flow Rate Performance Characteristics and Correction Method for Automotive Turbocharger

In actual vehicle operation, the turbocharger turbine operates at various temperatures, inlet, and backpressure conditions, unlike compressors. The flow rate characteristics of the turbine are generally evaluated under certain conditions using an assembled turbocharger with a compressor and a turbine and a hot gas bench from the turbocharger manufacturer. Flow rate characteristics are also presented as the reduced mass flow rate to correct the flow rate characteristics according to the turbine inlet temperature and pressure. Therefore, the turbine mass flow rate seen in many engine development cases and studies—including the analysis of the turbine performance and characteristics, engine model configuration, and matching of the engine and turbocharger—is calculated according to the reduced turbine mass flow rate performance and turbine inlet temperature and pressure obtained through hot gas bench experiments under certain conditions. However, the performance of the reduced turbine mass flow rate is influenced by the compressor power conditions, and additional correction of the reduced turbine mass flow rate is required when the turbine inlet temperature and turbine backpressure differ from the reference test conditions, such as the hot gas bench test conditions. In this study, the effect of the turbine inlet temperature and turbine backpressure on the performance of the reduced turbine mass flow rate were examined based on the power balance relationship between the compressor and turbine of an automotive turbocharger. The principle of its correction is also presented.

Off-design performance of the supercritical carbon dioxide recompression Brayton cycle with NDDCT cooling for concentrating solar power

The aim of this study is to investigate the off-design performance of an air-cooled supercritical carbon dioxide recompression Brayton cycle for concentrating solar thermal power generation. Off-design component models were developed in a system modelling framework. The components were designed for 25 MWe net power generation at ambient temperature 30 °C, with design point cycle thermal efficiency of 46.2%. The off-design performance was investigated for a range of heat source temperatures, ambient temperatures and cycle mass flow rates. Key elements of the off-design control scheme used are independent compressor shaft speeds, fixed low side pressure (assuming inventory control), and fixed turbine speed (for synchronous operation). The cycle can maintain nominal net power generation at 50 °C ambient temperature with increased cycle mass flow rate and turbine inlet temperature. At design point turbine inlet temperature and mass flow rate, net power generation decreases by approximately 10% for each 10 °C increase above the design point ambient temperature. The high design point ambient temperature limits the beneficial effect low ambient temperature. The effect of decreasing the design point ambient temperature was investigated. While this allows higher peak cycle efficiency, it also leads to much greater deterioration of cycle efficiency with increasing ambient temperature.

Mass flow extrapolation model for automotive turbine and confrontation to experiments

The turbochargers performance maps given by the manufacturer present a narrow range for the turbine mass flow rate which requires extrapolation models. This paper presents a new partly empirical model for radial turbine mass flow rate performance map extrapolation. An experimental measurement of a complete mass flow map is presented. An existing model is used to show the need for a better fitting because the results do not correspond to the values in all the experimental range. The proposed model is done in two steps. The first step is the calculation of the isentropic expansion across an ideal nozzle with four fitting coefficients to take into consideration the effect of the rotational speed, the two stages expansion across a turbine, the friction and the choking. The second step is the calculation of a reversed flow to represent the effect of the centrifugal forces pushing the fluid to the outer radius direction: in this part there are three constants and one variable, the blade speed. No fitting coefficients are used in this part. The final model is the difference between the two parts. The results present a good correlation of the experiment inside and outside the manufacturer’s data map range.

A methodology for the preliminary design and performance prediction of high-pressure ratio radial-inflow turbines

Modern power generation technologies, such as organic Rankine cycle power systems, require turboexpanders operating with high-efficiency and high power density. These features often lead to high-pressure ratios machines, characterised by the presence of choking and supersonic flow conditions. This paper proposes a comprehensive methodology for the preliminary design and performance prediction of radial-inflow turbines operating at high-pressure ratios. A steady-state, mean-line model of a radial-inflow turbine is developed including real-gas effects and a detailed modelling strategy for the treatment of choking flow conditions. In addition, a set of loss models tailored to high-pressure ratio radial-inflow turbines is developed. After a global sensitivity analysis, the model is calibrated by means of a multi-objective optimisation with a Genetic Algorithm and using the data of six high-pressure ratio turbines with total-to-total pressure ratios up to 5.8. The calibration method allows a significant reduction in the overall predicted deviation of the turbine isentropic efficiency and mass flow rate. The design model yields predicted deviations in isentropic efficiency within ± 3 %-points and the off-design model within 5%. The methodology and the results are intended to be used as a benchmark for the future development of radial-inflow turbines in high-pressure ratio applications.

Experimental Study of an Organic Rankine Cycle Using n-Hexane as the Working Fluid and a Radial Turbine Expander

Conversion of low-grade waste heat to electrical energy paves the way to reducing environmental pollution. This work focuses on the experimental study of an organic Rankine cycle (ORC) with an n-hexane working fluid and radial turbine expander. The heat source is varied from 120 to 190 °C with a mass flow rate of 0.10 to 0.50 kg/s and pressure between 12 and 15 bar. The heat-source temperature has a direct impact on turbine performance. Increase in the mass flow rate of the working fluid led to an increase in pressure and temperature at the turbine inlet. The rise in turbine speed enhanced electrical efficiency while cutting down isentropic efficiency. The optimum speed of the turbine increased with increasing in turbine inlet temperature. Superheating leads to an increase in power along with a decrease in isentropic efficiency. The thermal efficiency followed an increasing trend when there was an increase in turbine inlet temperature and mass flow rate and decreased with an increase in turbine speed. The electrical efficiency increased for all three cases. The system was found to have a highest thermal efficiency of 5.57% with a power of 1.75 kW. Based on the experimental results, it can be concluded that an ORC with n-hexane as the working fluid and a radial turbine as the expander can be used in low-temperature waste heat recovery systems to produce power.

Theoretical Investigation For The Effect of Fuel Quality on Gas Turbine Power Plants

Gas turbine engine power generation is declined dramatically because of the reduction in thermodynamic parameters as a work of turbine, compressor ratio, compressor work, and air mass flow rate and fuel consumption. There are two main objectives of this work, the first is related with the effect of fuel kinds and their quality on the operation of fuel flow divider and its performance specifically gear pump displacement and fuel flow rate to the combustion chambers of gas power plant. AL-DORA gas turbine power plant 35MW was chosen to predict these effects on its performance MATLAB Software program is used to perform thermodynamic calculations.Fuel distribution stage before the process of combustion and as a result of the kind and its quality, chemical reaction will occur between the fuel and the parts of the gear system of each pump of the flow divider, which causes the erosion of the internal pump wall and the teeth of the gear system, thus hampering the pump operation in terms of fuel discharge.The discharge of fuel form the eight external gates of flow divider is decreased and varied when going to the combustion chambers, so that, flow divider does not give reliable mass flow rate due to absence of accurate pressure in each of eight exit pipes.The second objective deals with the stage of fuel combustion process inside the combustion chamber. A comparative study based upon performance parameters, such as specific fuel consumption for gas and gasoil and power generation. Fuel poor quality causes incomplete combustion and increased its consumption, so that combustion products are interacted with the surface of the turbine blades, causing the erosion and create surface roughness of the blade and disruption of gas flow. As a result of this situation, turbulence flow of these gases will increase causing the separation of gas boundary layers over the suction surface of the blade. Therefore the amount of extracted gas will decrease causing retreat work done by turbine, as a result decline of power and gas turbine power plant efficiency causing the drop in the level of electric generation. The fuel quality is found to be a strong function of specific fuel consumption and its effects on the power generation and the efficiency of the gas turbine power plants and hence, the cycle performance shifts towards favorable conditions.

Exergo-environmental and exergo-economic analyses and multi-criteria optimization of a novel solar-driven CCHP based on Kalina cycle

The present research proposes and optimizes the performance of a novel solar-driven combined cooling, heating, and power (CCHP) Kalina system for two seasons—winter and summer—based on exergy, exergo-economic, and exergo-environmental concepts applying a Non-dominated Sort Genetic Algorithm-II (NSGA-II) technique. Three criteria, i.e. daily exergy efficiency, total product cost rate, and total product environmental impact rate associated with the exergy of the system for each season are considered simultaneously for multi-objective optimization. The outcomes reveal that increments in turbine inlet pressure and mass flow rate of the vapour generator lower the environmental impact of system products as well as the total product cost rate in both seasons. The optimum value of daily exergy efficiency, total product environmental impact rate, and total product cost rate indicate improvements by 2.56%, 15.7%, and 15.3% respectively in summer and 36.34%, 7.39%, and 4.93% respectively in winter, relative to the base point.

Exergy analysis and optimization of an integrated micro gas turbine, compressed air energy storage and solar dish collector process

An integrated micro gas turbine, compressed air energy storage and solar dish collector system is proposed and analyzed. The required equations for modeling different components of the system are presented. Performance of the system is analyzed by changing effective parameters including maximum and minimum pressure of the cavern, inlet temperature of the gas turbine and outlet mass flow rate of the cavern. Performance of the system is investigated by energy and exergy analyses methods. The results show that in design condition, the plants charging and discharging times are six and 5 h, respectively. During the operating time, the system consumes 152 kW h and produces 228 kW h. It is also capable of producing four tons of hot water. The highest exergy destruction occurs in dish collector. Optimization results indicate that round trip efficiency increases with the difference between the minimum and maximum pressure of the air cavern. In the optimum operating point, round trip efficiency of the system increases by 4.2% compared to the situation before optimization.

Thermodynamic and economic analysis for the pre-feasibility study of a binary geothermal power plant

Maximum power output and thermal conversion efficiency are the goals of ORC thermodynamic analysis. Co-optimization of energetic performance and system cost is needed for pre-feasibility design analysis. This paper presents a pre-feasibility design investigation for a binary geothermal power plant using a typical geothermal resource in New Zealand. Thermodynamic and economic analyses were conducted for key cycle design options, a range of working fluids and component selection parameters. The net electrical power output (Wnet) and the ratio of Wnet to total Purchased Equipment Cost (PEC) are used as the objective function to select the most thermo-economical designs. Three working fluids n-pentane, R245fa and R134a are investigated. The thermodynamic analysis shows that the net electrical power output (Wnet) of cycle design achieves a maximum level at a certain optimum turbine inlet pressure and mass flow rate of working fluid. The 2-stage designs produce higher Wnet and thermal and exergy efficiencies than the 1-stage designs. Economic comparison indicates that the type of working fluid and cycle configuration have a great effect on economic performance as measured by PEC. The profitability analysis was conducted for the top three options. The results indicate that a standard Rankine cycle with a 2-stage turbine using n-pentane is the most thermo-economical design for the particular brine resource and re-injection conditions.

Modeling of turbine mass flow rate performances using the Taylor expansion

The turbine is a key component of many equipment and systems, such as air cycle refrigeration and gas-turbine engines. Existing turbine mass flow rate models need to be improved to increase the prediction accuracy and extrapolation performance for control and diagnosis-oriented simulation. This work proposes a novel methodology for building a regression model, which makes use of the Taylor series to expand functions to deal with variables with small variation and develops a single partly empirical model to present a component performance map. With the methodology, a general regression model of mass flow rates of inward radial turbines is built. Measured data of a turbocharger turbine and a simple air cycle machine turbine are used for the regression analysis to validate the methodology and model. Model predictions agree with measured data very well, proving that the proposed methodology and the model are highly reliable. Comparison of the proposed model with the best existing model searched shows that the present model reduces the mean absolute percentage error by more than 50%, and has much better extrapolation performance as well.