Turbine Performance Research Articles

Thermodynamic analysis of an advanced adiabatic compressed air energy storage system integrated with a high-temperature thermal energy storage and an Organic Rankine Cycle

Advanced adiabatic compressed air energy storage (AA-CAES) system has drawn great attention owing to its large-scale energy storage capacity, long lifespan, and environmental friendliness. However, the performance of the air turbine during the discharging process is limited by the low temperature of the compression heat. Thus, this study proposes an integrated AA-CAES system incorporating high-temperature thermal energy storage and an Organic Rankine Cycle (ORC). The high-temperature thermal energy storage is introduced to heat the discharging compressed air to enhance the air turbine performance, and the Organic Rankine Cycle is integrated to utilize the waste heat. Notably, two preheaters are deployed in a special tandem to recover the heat from the air exiting the turbine and the water exiting the hot water tank, respectively. This paper develops a thermodynamic model to simulate the proposed system, assessing the effects of heat storage temperature, ambient temperature, and inlet conditions of the air turbine on performance metrics, including exergy efficiency and exergy destruction. The simulation results indicate that, compared to thermal oil and Hitec salt, employing solar salt as the heat storage medium for the solar thermal collection and storage unit yields the best performance. The energy storage efficiency, roundtrip efficiency, exergy efficiency, exergy conversion coefficient, and energy storage density of this system are 115.6 %, 65.7 %, 78 %, 79.4 %, and 5.51 kWh/m3, respectively. Exergy analysis reveals that the exergy efficiency of interheaters (IH) is the lowest at 76.7 %, while air turbines (ATBs) exhibit the highest exergy efficiency at 91.2 %. Moreover, due to the irreversible processes of compression, expansion, and throttling, ATBS, compressors, and throttle valves collectively contribute to an exergy destruction rate as high as 79.2 %. The parameter analysis demonstrates that low ambient temperature, high inlet temperature, and high inlet pressure of the air turbine enhance energy storage performance.

Exploring explainable ensemble machine learning methods for long-term performance prediction of industrial gas turbines: A comparative analysis

In today's modern life, where electricity demand is one of the fundamental necessities, gas turbines play a pivotal role in meeting this demand. As such, it is imperative to address the challenges faced in the field. Current models often rely on simplifying assumptions, neglecting the intricate relationships between variables. This limitation leads to reduced accuracy and reliability, ultimately affecting the overall efficiency of gas turbine systems. Furthermore, the complexity of gas turbine behavior, coupled with the scarcity of comprehensive datasets, exacerbates the problem.To address these challenges, this research aimed to develop an advanced model capable of accurately forecasting real gas turbine behavior. The proposed approach leveraged ensemble decision trees, robust preprocessing techniques, and rigorous evaluation using an extensive dataset spanning from 2011 to 2015. The training and validation phases were conducted on data from 2011 to 2014, with the 2015 dataset reserved for evaluation.The results demonstrated that the bagging structure outperformed the boosted structure, exhibiting lower complexity and higher reliability. Remarkably, the bagging approach with only 30 estimators achieved a superior root mean square error of 1.4176, outperforming the boosted trees with 200 learners. The model effectively captured the overall gas turbine performance, though it encountered limitations in certain specific operating ranges.To further investigate the model's behavior, an evaluation was conducted to assess the effects of the input variables on the output power. While the interpretability of the results posed some challenges, the overall findings were deemed acceptable and provide valuable insights for optimizing gas turbine performance. The significance of this research lies in its potential to inform decision-making and enhance the efficiency of gas turbine systems, ultimately contributing to the reliable and sustainable supply of electricity.

Design and analysis of a single-stage supersonic turbine with partial admission

Supersonic impulse turbines are commonly used to harvest waste heat from systems based on organic Rankine cycles, automotive applications, and gas-generator liquid rocket engines. This research aims to design and analyze a single-stage supersonic turbine with a rated power of approximately 440 KW. We present a comprehensive preliminary design roadmap followed by design parameters optimization. The preliminary sizing is carried out using one-dimensional flow analysis, while the blade geometrical design is performed using the two-dimensional method of characteristics. The turbine performance is then analyzed through numerical simulations on three-dimensional models. Comprehensive parametric analyses are conducted to examine the turbine performance sensitivity to changes in partial admission (PA), mean radius, and turbine blade height using three-dimensional sliding mesh techniques (SMT). The current analysis simulates the full turbine to capture PA effects, rather than focusing on a single periodic sector as is common in turbomachinery simulation practices. Different PA scenarios are investigated, emphasizing a single rotor passage over a complete rotor cycle in a partially admitted turbine, and examining its charging and discharging mechanisms. Flow tracking over such a blade shows that the turbine rotor exhibits compressor-like behavior over most of the unadmitted zone, contributing to efficiency drops and severe transients.

Large Eddy Simulations of a Francis Turbine Operating at Ultra-Low Load to Overload Conditions

Due to the increasing global power demand, hydropower plants face the challenge of operating at flow rates far from their best efficiency point to comply with the electrical grid. Consequently, turbine units experience unstable high swirling flows under different load conditions, reducing the life of system components. Understanding the mechanisms behind the onset and sustenance of these instabilities in the swirling flow leaving the turbine runner is crucial for improving turbine performance. To achieve this, large-eddy simulations (LES) were conducted to characterize the unsteady flow inside an industrial-sized Francis turbine. The turbine was studied under a wide range of flow rates, 100, 80, 60, 40, and 120% of the design flow rate. A high swirl velocity was introduced as the flow rate deviated from 100% load, causing significant changes in the flow structure. An organized structure of vortex filaments in a helical pattern is seen inside the draft tube at 80 and 60% load, and the 40% load case showed an unorganized collection of small-scale vortices. A straight vortex cavity is seen in the draft tube center at 120% excess load. At the best design point, the magnitude of the swirl velocity was 0.1 times the tip speed. However, as the flow rate dropped to 40% of the design flow rate, the magnitude increased to 0.4 times the tip speed near the wall. In addition, the 40% load case had the highest magnitude of pressure fluctuations, over 25 times the peak design case near the runner. This showed a very unsteady flow field could damage the system or cause unstable operation at ultra-low partial loads. Generated power dropped dramatically as the flow rate decreased, and more noise was present in the power signal.

A novel wide flow matching approach of hydrogen-powered F-class gas turbine based on multistage installation angle

To achieve excellent power performance of F-class gas turbine when using pure H2 or H2-rich fuel, this work develops a novel and flexible flow matching approach by modifying the turbine multistage installation angle, with obvious features of easy implementation and low cost. An accurate thermodynamic model of heavy-duty gas turbine considering turbine-stage cooling is established and verified by the actual operation data from Ban-Shan power plant, and to investigate variable condition property and emission characteristic of gas turbine with natural gas and H2-rich fuel. Faced with the inefficiency and narrow working area caused by the flow mismatch between 18-stage compressor and 3-stage turbine when natural gas is switched to H2-rich fuel, the scheme of modifying the installation angles of multistage rotary blade and static blade is proposed. By calculating the pressure and temperature at each turbine stage, the gas turbine power, efficiency, Mach number and NOx emission with different H2 concentration are predicted. Results show that, as the H2 concentration increases, the fuel volume flow required to reach the same turbine inlet temperature increases.When H2-rich fuel increases the turbine inlet volume flow by 3.23 %, the cooling effect significantly decreases, and the turbine outlet temperature rises by about 13.60 K, which deviates from the appropriate operating point. The most serious is the phenomenon of over Mach number and airflow blocking at the outlet of the 2-stage and 3-stage turbine static blades. The installation angle variation increases with the increase of H2, and the higher the stage, the bigger the angle change. The gas turbine can be realized the wide flow matching feature corresponding to the installation angle variation of 0.19°/-0.41°, 0.38°/-0.48°, and 0.53°/-0.94°, respectively for all stages static/rotary blades. After re-matching, the maximum fluctuation of rated power and efficiency are 1.5 % and 1.7 %, and the NOx emission will reach the maximum value of 14.3 ppm with 70 % H2. Research work will provide a novel and feasible retrofit scheme for the heavy-duty gas turbine using clean and low-carbon fuel to widen flow matching scenario.

Unsteady vane-rotor secondary flow interaction of the endwall region in a 1.5-stage variable-geometry turbine

Variable-geometry turbines present significant improvements in both off-design cycle efficiency and enhanced engine responsiveness for future adaptive cycle engines. The adjustable vanes regulate the through-flow capacity by varying the installation angle and thus unavoidably require endwall clearance, resulting in profound implications for vane and downstream blade rows. Unsteady numerical simulations are carried out to investigate the vane-rotor flow interaction under the zero and partial clearance type of the adjustable vane in a 1.5-stage variable-geometry turbine. First, specific vortical structures and loss characteristics of upstream adjustable vane leakage flow at turning angles of −5°, 0°, and +5° are described. Then, the basic mechanisms of vane-rotor secondary flow interaction between acquired upstream leakage flow and downstream blade rows secondary flow is explored by the time-resolved method and quantitative detailed analysis method. The results show that adjustable vane vortex core area is the primary cause of internal loss within the vortex, and the mixing and interaction between the leakage vortex and other vortex systems contribute to secondary loss in the vane. Due to the downstream blade shear action caused by different flow velocity on the suction and pressure surfaces, the vane leakage flow fragments upon entering the R1 blade passage and develops downstream of the endwall region. Compared to the vane with zero clearance case at same turning angle, the intensity of the R1 tip leakage vortex at the design turning angle and open turning angle is reduced by 47.4 % and 23.66 % with the upstream partial clearance, respectively. The unsteady vane-rotor secondary flow interaction under different turning angles has large influence on the flow structure and loss characteristics of the downstream blade rows, and results in significant differences in the variation pattern and trend direction of the turbine performance.

Study on the Influence of Volute Throat Jet on Excitation Vibration Alleviation of Radial Turbine Blade

Abstract Turbine blade fracture, resulting from high-cycle fatigue (HCF), is the most commonly observed failure mode of turbochargers. In a vaneless turbine, the radial turbine blade is susceptible to HCF under excessive aerodynamic excitation due to the flow field distortion caused by the volute tongue. The present study explores a technique to mitigate blade excitation by reducing pressure disturbance in the volute tongue area. The gas with higher pressure in the inlet section of the volute is transferred to the low-static pressure area upstream of the volute tongue through a throat jet hole. The usage of high-pressure gas improved the homogeneity of the flow field near the volute tongue. The study investigates the mitigation of high-pressure gas jet on turbine blade excitation, the impact of jet hole geometry on the suppression effect of the blade vibration, and the effect of high-pressure jet on turbine performance using numerical simulation of unsteady flow fields. The results indicate that the jet flow has a substantial impact on dampening the blade vibrations. The harmonic pressure amplitude at the monitor point located within the high blade vibration amplitude region is reduced by up to 56%. Generalized pressure analysis reveals that the aerodynamic excitation of the turbine blades is significantly reduced. Experimental evidence verifies the effectiveness of the jet hole scheme in reducing blade vibration. Moreover, the jet hole has a negligible effect on turbine efficiency. However, there is a degree of increased stress in the volute tongue with a jet hole which needs to be evaluated in engineering applications.

Investigating the effect of using hydrogen as fuel on gas turbine performance operating under lean conditions at the Hassi R'mel gas site

This study evaluates the feasibility of using pure hydrogen as fuel for the MS5002C gas turbine at the Hassi R'mel gas site in Algeria. THERMOPTIM software was used to analyze key parameters, including compression ratio, excess air (λ), and climatic conditions, identifying an optimal excess air of 4.5. This configuration was validated over a year under local climatic conditions. The results indicate that at a harsh temperature of 50 °C, the hydrogen-fueled gas turbine increased thermal efficiency by 3.66% and power output by 6.18%, while reducing fuel consumption by 62% compared to an optimized natural gas turbine. Hydrogen use eliminated carbon emissions but caused a slight 1.17% increase in NOx emissions. Under reel climatic conditions, hydrogen fuel eliminated carbon footprint and mitigated the adverse effect of harsh climate on turbine performance, with a peak NOx emission of 1.891 ppm in August.

Deep learning-aided active subspace exploration of free-stream effects for fan-shaped film cooling

Film cooling plays a critical role in protecting engine components from high temperatures that can influence safety and performance of gas turbines. However, the process is fraught with uncertainties due to complex inflow conditions and geometrical configurations. These uncertainties significantly impact cooling effectiveness, underscoring the importance of identifying the dominant factors in a quantified manner. Traditional methods, such as the Monte Carlo approach, encounter the “curse of dimensionality,” making them computationally intensive as the number of variable increases. This study tackles these challenges by employing a deep learning strategy with a convolutional neural network (CNN) model to predict film cooling effectiveness efficiently, reducing computational loads compared to traditional computational fluid dynamics (CFD) simulations. It enables the CNN model to act as a surrogate for the CFD simulation and provides gradient information for subsequent analyses. Additionally, this study employs active subspace (AS) analysis for dimensionality reduction, identifying dominant parameters based on the trained CNN model. This approach not only enhances the speed of simulations but also provides an effective way to analyze dominant parameters and carry out optimizations. Results demonstrate a strong correlation between the CNN predictions and detailed CFD simulations, with all the mean absolute errors below 0.08, validating the model's efficacy in capturing complex cooling dynamics. The dominant analysis based on the AS method gives the blowing ratio as the most important factors, and the subsequent parameter dimension reduction and suggested optimization region are also explored by applying the low-dimensional active variable. The tested optimal factors yield higher spatially averaged cooling effectiveness above 0.35 and show reasonable pattern changes compared to the maximum and minimum results in the sample.

Design and Analysis of a Vertical Axis Ocean Current Turbine Tunnel Using SolidWorks Computational Fluid Dynamics

The development of renewable energy in the marine power generation sector presents a promising approach to producing electrical energy in a sustainable and environmentally friendly manner. Indonesia, with its vast oceanic territory, holds significant potential for harnessing marine energy. However, the relatively slow speed of ocean currents in the region, typically ranging from 0.1 m/s to 1.5 m/s, poses a challenge to the efficiency of marine power generation. To overcome this limitation, this research focuses on the design and analysis of a vertical-axis ocean current turbine tunnel aimed at increasing the speed of ocean currents, thereby enhancing the overall efficiency of energy production. The study combines a thorough literature review with experimental research methods, utilizing SolidWorks Computational Fluid Dynamics (CFD) software to simulate the tunnel's impact on ocean current velocity. The simulations reveal that the tunnel construction significantly boosts current speeds, increasing them from 1.0 m/s to 1.7 m/s, and from 1.5 m/s to 2.6 m/s. This increase in velocity directly translates to higher kinetic energy available for conversion into electrical power by the turbine. Moreover, the study shows that the tunnel construction contributes to a more uniform flow of ocean currents, as evidenced by the Reynolds numbers obtained—100.250 at a current speed of 1.0 m/s and 150.375 at 1.5 m/s. These values, being below 2000, indicate laminar flow conditions within the tunnel, which are beneficial for optimizing turbine performance by reducing turbulence and ensuring a stable energy output. The findings underscore the effectiveness of the tunnel design in improving the efficiency of vertical-axis ocean current turbines, making it a viable solution for enhancing renewable energy production in regions with low ocean current speeds.

Gas Turbine Performance Enhancement and Evaluation for Power Generation in the City of Karbala, Iraq

Gas Turbine Performance Enhancement and Evaluation for Power Generation in the City of Karbala, Iraq

Gas turbine multi-working conditions identification and performance prediction based on deep learning and knowledge

Performance prediction is crucial for monitoring, controlling and optimizing gas turbine (GT) operations. Due to significant performance variation under different working conditions, a single model cannot adequately represent all scenarios. In this paper, we propose a novel multi-working conditions performance prediction framework for GT, leveraging deep learning and professional knowledge. The GT is used in gas-steam combined cycle power plants that utilize low calorific value gases. A unique multi-working condition identification model has been established, enabling accurate identification of the current operating status of GT. Additionally, a dynamic model has been developed to fully utilize the temporally varying data. The entire GT model, spanning from unstart to steady-state, is constructed through model fusion using a mathematical mechanism. Compared to the single working condition model, our approach demonstrates superior performance prediction results on the actual GT operating dataset. The mean square error (MSE), mean absolute error (MAE) and correlation coefficient (CORR) are 0.7501, 0.5872, and 0.9973, respectively. These results highlight a substantial improvement in prediction accuracy and robustness outperforming the single working condition model in same contexts, effectively capturing operational characteristics and offering valuable insights for optimizing GT operations. The findings may also contribute to advancing GT research.

Regulation of the power of a wind turbine of a special design by changing the length of the blades

The object of this research is a model of a wind turbine with retractable blades. This model allows for the adjustment of the turbine’s screw radius by extending or retracting the blades, providing a basis for examining the impact of blade radius on turbine performance. The primary problem addressed by this study is to determine how changes in the screw radius, achieved by altering the blade length, affect the wind turbine’s performance, specifically its electrical output (voltage and current) and rotational speed, under constant wind conditions. The experimental results showed that when the turbine blades are fully extended (R1), the wind turbine generates higher voltage and current compared to when the blades are retracted (R2). This confirms that the turbine’s electrical output is significantly influenced by the screw radius. These results are explained by the aerodynamic principles governing wind turbines. An increased screw radius allows the turbine blades to capture more wind energy, leading to greater force applied to the blades, thus increasing the rotational speed and the amount of electrical energy generated. The linear relationship between the screw radius and the turbine’s performance was as summed to simplify the analysis, though the actual relationship may be more complex. The finding soft its study can be practically applied in the design and operation of wind turbines. Turbines with adjust table blade lengths can optimize performance across varying wind conditions, maximizing efficiency and power output. These results are particularly useful in environments where wind speed is variable, as turbine scan adjust their blade radius to maintain optimal performance. The study assumes consistent wind conditions and uniform air flow for the results to be accurate, so these conditions should be considered when implementing the findings in real-world scenarios

Recent advances in VAWT aerodynamic performance research: Optimal design

Vertical axis wind turbine is a popular research direction in recent years, and its aerodynamic performance directly affects its power generation efficiency. Using CFD method simulation, the aerodynamic characteristics of wind turbine blades can be deeply analyzed. In this paper, the numerical simulation progress of the aerodynamic performance of vertical axis wind turbines with airfoil as the main object in recent years is studied, the influence of different design parameters on the performance of wind turbines is discussed, the characteristics of current research are summarized, and the future research trends are prospected.

A numerical investigation of a new horizontal wind turbine performance for rural use

In this paper, a new configuration of a horizontal axis wind turbine with three blades for domestic electricity production on farms was numerically simulated. Three configurations were tested numerically: a standard single-blade wind turbine (STWT), a single wind turbine (SWT), and a tandem three-blade wind turbine (TWT) for rural use. For the tandem wind turbine, the effects of pitch angle and the distance between the blades were also investigated. The Gambit and Fluent 19.2 codes were, respectively, used to generate different meshes and determine various parameters. The resolution of the averaged Navier–Stokes equations (RANS) using a finite volume method was conducted. The k–[Formula: see text] realizable two-equation model was chosen for turbulence calculation. The obtained results showed that the maximum power coefficient (Cp) was 0.444 for one of the tandem configurations (TWT), compared to the conventional blade (STWT). The maximum Cp obtained in this study is slightly greater than the experimental results found in the literature. It has also been observed that the flow on these new turbines exhibits a complex phenomenon on both surfaces.

Application of roughness models to stationary and rotating minichannel flows

PurposeThe performance of a bladeless Tesla turbine is closely tied to momentum diffusion, kinetic energy transfer and wall shear stress generation on its rotating disks. The surface roughness adds complexity of flow analysis in such a domain. This paper aims to assess the effect of roughness on flow structures and the application of roughness models in flow cross sections with submillimeter height, including both stationary and rotating walls.Design/methodology/approachThis research starts with the examination of flow over a rough flat plate, and then proceeds to study flow within minichannels, evaluating the effect of roughness on flow characteristics. An in-house test stand validates the numerical solutions of minichannel. Finally, flow through the minichannel with corotating walls was analyzed. The k-ω SST turbulent model and Aupoix's roughness method are used for numerical simulations.FindingsThe findings emphasize the necessity of considering the constricted dimensions of the flow cross section, thereby improving the alignment of derived results with theoretical estimations. Moreover, this study explores the effects of roughness on flow characteristics within the minichannel with stationary and rotating walls, offering valuable insights into this intricate phenomenon, and depicts the appropriate performance of chosen roughness model in studied cases.Originality/valueThe originality of this investigation is the assessment and validation of flow characteristics inside minichannel with stationary and corotating walls when the roughness is implemented. This phenomenon, along with the effect of roughness on the transportation of kinetic energy to the rough surface of a minichannel in an in-house test setup, is assessed.

Structural Design and Research of Offshore Wind Turbine Towers

The structural design and research of offshore wind turbine tower need to involve knowledge and technology in many fields, such as mechanical engineering, material science, fluid mechanics and so on. Through the research and optimization of tower structure, it can promote the development of related industries and improve the technical level and competitiveness of the whole industrial chain. The structural design and research of offshore wind turbine tower has important practical significance and application value. Through in-depth research and optimization of design, the performance and reliability of offshore wind turbines can be improved, and the rapid development of offshore wind power technology can be promoted.

An experimental investigation of the performance of cross-flow turbine: impact of number of blades in runner

ABSTRACT This study examines a cross-flow turbomachine designed for power generation in areas with limited discharge and head availability, focusing on sustainability, affordability, and ease of operation. It investigates how varying the number of blades in the runner affects turbine performance while keeping other design factors constant. Testing runners with 8, 12, 16, 20, and 24 blades under identical conditions reveal consistent RPM variations across different blade numbers for various parameter combinations. The study identifies a 12-blade configuration as optimal for electrification projects at selected sites. Experimental validation using the Taguchi technique confirms the reliability of the findings. Additionally, the research explores the turbine’s performance under different nozzle tip elevations (18 cm, 16 cm, and 14 cm). The highest observed runner speed is 345 RPM for the 12-blade runner at an 8° angle of attack, with similar speeds recorded for the 24-blade runner under similar conditions.

Aerodynamic efficiency assessment of a cross-axis wind turbine integrated with an offshore deflector

The present work examines the performance of an offshore cross-axis wind turbine (CAWT) with a flow deflector by integrating numerical and analytical methods. The deflector's geometry redirects flow in all directions, causing it to exit vertically and collide with the wind turbine's horizontal blades. In contrast, the blades of a vertical axis wind turbine (VAWT) harness the power of horizontal wind flow. The total power absorbed by the horizontal and vertical turbine blades represents the power of CAWT. In this study, the speed of the outflow from the deflector was initially determined through numerical simulation. The numerical simulation output was then utilized as an input for analytical Double Multiple Stream Tube (DMST) and Blade Element Momentum (BEM) methods to evaluate the vertical and horizontal turbine blades, respectively. This approach reduces the overall simulation time and establishes an offline coupling between analytical and numerical approaches. The findings of this research have unveiled a promising future for offshore wind energy generation. Through the implementation of a modeled deflector on a Cross-Axis Wind Turbine (CAWT), the power output reached a remarkable 19 KW with a power coefficient of 0.35 at an 8.4 m/s wind speed. The results indicate that the CAWT with the deflector produced a power output 35 % higher and was 45 % more efficient than a single Vertical-Axis Wind Turbine (VAWT). These outcomes illustrate the potential for greater energy production and efficiency in offshore wind farms.

Dynamic behaviors of multiphase vortex-induced vibration for hydropower energy conversion

To satisfy the growing electricity demand, continuous and stable hydropower conversion is particularly critical in tidal power station operation. In the above industrial application, multiphase vortices will be formed, and they suck air and floating items into the flow tube, thus causing irregular pulsation that affects turbine performance. Due to nonlinear characteristics of gas-liquid coupling transfer, dynamic modeling and transition behavior of the multiphase vortex-induced vibration have improtant difficulties. This paper conducts a fluid-structure mechanic optimization model with the dynamic mesh technology to investigate multiphase vortex-induced vibration (MVIV) dynamic behaviors and reveal the internal relation between displacement responses and multiphase flow states. The fluid-induced vibration sensing platform is developed to validate MVIV transition behaviors, and a wavelet packet signal analyzing approach is adopted to acquire energy-spectrum distribution regularities of the vibration distortion state. Results show that the presented optimization modelling strategy can well obtain the MVIV transition behaviors and energy transfer mechanism. The flow flux can control the Ekman transfer intensity, and vibration energy waves take on various frequency components at the critical penetration state. Moreover, impulse energy components and structure evolution properties of high-frequency bands can be utilized to recognize the MVIV distortion peak. It can supply theoretical guidance and technology support for hydropower conversion.