Search Results (28)

Objectives: This study aimed to endoscopically assess nasal patency in terms of adenoid obstruction and its mucous coverage, as well as nasal obstruction caused by the inferior nasal turbinate in children with vocal fold nodules. Methods: A retrospective study was conducted involving 54 children admitted to an ENT clinic due to hoarseness caused by vocal fold nodules from 2022 to 2024. The study analyzed medical history, the results of performed flexible nasofiberoscopy and tympanometry. Results: Children with vocal fold nodules snored and slept with open mouths less frequently than the control group of other patients admitted to the ENT outpatient clinic without voice disorders (p = 0.003 and 0.004, respectively). Pathological mucous coverage of the adenoid was observed more often (p = 0.02). The mean adenoid size in the A/C ratio was 52.1% compared to 63.4% in the control group (p = 0.01). Conclusions: Children with vocal fold nodules typically have smaller adenoids, fewer incidents of snoring and open-mouth breathing, but more frequent pathological nasal mucus. It was not possible to prove that the incorrect breathing path through the mouth, causing reduced humidity of the inhaled air, affects the formation of vocal fold nodules. Full article

The critical consequence of climate change resulting from global warming is the increase in temperature. In combined cycle power plants (CCPPs), the Electric Power Output (PE) is affected by changes in both Ambient Temperature (AT) and Sea Surface Temperature (SST), particularly in plants utilizing seawater cooling systems. As AT increases, air density decreases, leading to a reduction in the mass of air absorbed by the gas turbine. This change alters the fuel–air mixture in the combustion chamber, resulting in decreased turbine power. Similarly, as SST increases, cooling efficiency declines, causing a loss of vacuum in the condenser. A lower vacuum reduces the steam expansion ratio, thereby decreasing the Steam Turbine Power Output. In this study, the effects of increases in these two parameters (AT and SST) due to global warming on the PE of CCPPs are investigated using various regression analysis techniques, Artificial Neural Networks (ANNs) and a hybrid model. The target variables are condenser vacuum (V), Steam Turbine Power Output (ST Power Output), and PE. The relationship of V with three input variables—SST, AT, and ST Power Output—was examined. ST Power Output was analyzed with four input variables: V, SST, AT, and relative humidity (RH). PE was analyzed with five input variables: V, SST, AT, RH, and atmospheric pressure (AP) using regression methods on an hourly basis. These models were compared based on the Coefficient of Determination (R²), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Root Mean Square Error (RMSE). The best results for V, ST Power Output, and PE were obtained using the hybrid (LightGBM + DNN) model, with MAE values of 0.00051, 1.0490, and 2.1942, respectively. As a result, a 1 °C increase in AT leads to a decrease of 4.04681 MWh in the total electricity production of the plant. Furthermore, it was determined that a 1 °C increase in SST leads to a vacuum loss of up to 0.001836 bar_a. Due to this vacuum loss, the steam turbine experiences a power loss of 0.6426 MWh. Considering other associated losses (such as generator efficiency loss due to cooling), the decreases in ST Power Output and PE are calculated as 0.7269 MWh and 0.7642 MWh, respectively. Consequently, the combined effect of a 1 °C increase in both AT and SST results in a 4.8110 MWh production loss in the CCPP. As a result of a 1 °C increase in both AT and SST due to global warming, if the lost energy is to be compensated by an average-efficiency natural gas power plant, an imported coal power plant, or a lignite power plant, then an additional 610 tCO₂e, 11,184 tCO₂e, and 19,913 tCO₂e of greenhouse gases, respectively, would be released into the atmosphere. Full article

The turbocharging of hydrogen fuel cell systems (FCSs) has recently become a prominent research area, aiming to improve FCS efficiency to help decarbonise the energy and transport sectors. This work compares the performance of an electrically assisted variable-geometry turbocharger (VGT) with a fixed-geometry turbocharger (FGT) by optimising both the sizing of the components and their operating points, ensuring both designs are compared at their respective peak performance. A MATLAB-Simulink reduced-order model is used first to identify the most efficient components that match the fuel cell air path requirements. Maps representing the compressor and turbines are then evaluated in a 1D flow model to optimise cathode pressure and stoichiometry operating targets for net system efficiency, using an accelerated genetic algorithm (A-GA). Good agreement was observed between the two models’ trends with a less than 10.5% difference between their normalised e-motor power across all operating points. Under optimised conditions, the VGT showed a less than 0.25% increase in fuel cell system efficiency compared to the use of an FGT. However, a sensitivity study demonstrates significantly lower sensitivity when operating at non-ideal flows and pressures for the VGT when compared to the FGT, suggesting that VGTs may provide a higher level of tolerance under variable environmental conditions such as ambient temperature, humidity, and transient loading. Overall, it is concluded that the efficiency benefits of VGT are marginal, and therefore not necessarily significant enough to justify the additional cost and complexity that they introduce. Full article

Gas turbines are widely used in power generation due to their efficiency, flexibility, and low environmental impact. Modeling, especially in thermodynamics, is crucial for the designer and operator of a gas turbine. An advanced and rigorous thermodynamic model is essential to accurately predict the performance of a gas turbine under on-design operating conditions, off-design or failure. Such models not only improve understanding of internal processes but also optimize performance and reliability in a wide variety of operational scenarios. This article presents the development of a thermodynamic model simulating the off-design performance of a gas turbine. The mathematical relationships established in this model allow for quick calculations while requiring a limited amount of data. Only nominal data are required, and some additional data are needed to calibrate the model on the turbine under study. A key feature of this model is the development of an innovative relationship that allows direct calculation of the mass flow of air entering the turbine and, thus, the performances of the turbine according to atmospheric conditions (such as pressure, temperature, and relative humidity) and the position of the compressor inlet guide vanes (IGV). The results of the simulations, obtained using code implemented in MATLAB (R2014a), demonstrate the efficiency of the model compared to experimental data. Indeed, the model relationships exhibit high determination coefficients (R² > 0.95) and low root mean square errors (RMSE). Specifically, the simulation results for the air mass flow rate demonstrate a very high determination coefficient (R² = 0.9796) and a low root mean square error (RMSE = 0.0213). Full article

In cold and humid climate conditions, the surface of wind turbine blades is prone to icing. Effective de-icing methods have attracted widespread attention from scholars around the world. In this study, an external hot-air de-icing test system was designed and constructed. A test program for FRP plate surface de-icing was formulated. The main parameters of the experiment included hot-air temperature (25~55 °C), hot-air speed (7~13 m/s), the jet distance between the outlet of the hot-air pipe and the ice surface (100~400 mm), the pipe inner diameter of the de-icing device air outlet (50 mm, 63 mm, 90 mm), and different jet times. Critical data on the de-icing mass, energy consumption, and energy efficiency were obtained. The experimental results showed that the external hot-air method could be used for FRP plate surface de-icing. Under the conditions of this experiment, the lowest de-icing energy consumption and the highest de-icing energy efficiency of 21.1 kJ/g and 4.95% were achieved when the hot-air temperature was 55 °C and hot-air speed was 13 m/s. Full article

The quality of air intake significantly impacts the overall performance of gas turbines. A new high-precision testing method for the air intake quality assurance system of gas turbines has been proposed, and the influence of typical intake conditions on the system was studied through this testing method. The research results indicate a positive correlation between filtration efficiency and particle size. Atmospheric temperature, particle concentration, filter differential pressure, and atmospheric humidity all affect filtration efficiency, with their influence decreasing in that order. Additionally, this paper presents a performance prediction model based on the LSTM neural network. The calculation results show that the errors of the filter pressure loss and filtration efficiency model test set are both less than 3%, reflecting the characteristics of pressure loss and efficiency well. The research results have significant engineering application value and provide experimental basis for establishing technical standards and high-precision detection systems for air quality assurance in gas turbines. Full article

Wind energy is an eco-friendly, renewable, domestic, and infinite resource. These factors render the construction of wind turbines appealing to nations, prompting numerous governments to implement incentives to augment their installed capacity of wind turbines. Alongside augmenting the installed capacity of wind turbines, identifying suitable locations for their installation is crucial for optimizing turbine performance. This study aims to evaluate potential sites for wind power plant installation via a GIS, a mapping technique. The Analytic Hierarchy Process (AHP) was employed to assess the locations, including both quantitative and qualitative aspects that significantly impact the wind farm suitability map. Utilizing the GIS methodology, all datasets were examined through height and raster transformations of land surface temperature, plant density index, air pressure, humidity, wind speed, air temperature, land cover, solar radiation, aspect, slope, and topographical characteristics, resulting in the creation of a wind farm map. The correlation between the five-year meteorological data and environmental parameters (wind direction, daily wind speed, daily maximum and minimum air temperatures, daily relative humidity, daily average air temperature, solar radiation duration, daily cloud cover, air humidity, and air pressure) influencing the wind power plant in Iğdır province, including Iğdır Airport, Karakoyunlu, Aralık, and Tuzluca districts, was analyzed. If wind energy towers are installed at 1 km intervals across an area of roughly 858,180 hectares in Igdir province, an estimated 858,180 GWh of wind energy can be generated. The GIS-derived wind power plant map indicates that the installation sites for wind power plants are located in regions susceptible to wind erosion. Full article

The combustion of fuels has been studied by many researchers as it is used in a wide range of engineering applications. The chemical equilibrium approach served as the foundation for the investigation of combustion reactions. This article presents a software application designed to facilitate the calculation of combustion processes by calculating the combustion of 16 fuels among the common alkanes (C_nH_2n+2) and alcohols (C_nH_2n+1OH). The Ozan Combustion Calculator (OCC) offers a user-friendly and efficient graphical user interface (GUI) that allows users to easily input data and obtain results. The program was developed using MATLAB 2021a and LaTeX software, ensuring its reliability and accuracy. To perform these calculations, the program utilizes calculations of the thermophysical properties of fuels and water obtained from tables. The program consists of five modules, each serving a specific purpose. These modules calculate various parameters, such as the Adiabatic Flame Temperature, Exergy of Combustion with Dry Air, Exergy of Combustion with Moist Air, Energy of Combustion with Dry Air, and Energy of Combustion with Moist Air. Additionally, the program can be used to investigate the impact of relative humidity on the adiabatic flame temperature and exergy destruction. The results obtained from the calculations reveal that the adiabatic flame temperature exhibits a linear decrease as the relative humidity increases. On the other hand, exergy destruction demonstrates a quadratic increase with higher relative humidity values. The program derives mathematical relationships for the adiabatic flame temperature and exergy destruction with respect to relative humidity values, with a high regression coefficient ($r^2=0.999$). The versatility of OCC makes it suitable for various applications. It can be utilized in university settings for both undergraduate- and graduate-level courses, providing students with a practical tool for studying combustion processes. Additionally, it finds applications in industrial settings for the design and optimization of combustors, gas turbines, and burners. The user-friendly interface and accurate calculations make OCC a valuable resource in the field of combustion engineering. Full article

Confronted with the climate crisis, the world is making tremendous efforts in energy transition, such as expanding renewable energy that does not emit carbon. The importance of virtual power plant (VPP) operation technology has emerged to secure grid flexibility in response to the expanding renewable energy implemented due to these efforts. Accordingly, VPPs, which include photovoltaics, wind turbines, heating, ventilation, and air conditioning (HVAC), load, and EV, have been constructed. HVAC, one of the component resources, is a system that controls and regulates temperature, humidity, and airflow. Since it responds sensitively to the building’s heat capacity and changes in the external environment, it requires continuous and stable control. In this paper, we used data-based modeling to implement the HVAC required for the optimal operation of VPP. Since accurately creating an equation-based HVAC model was difficult considering building information modeling and external environment variables, we used historical HVAC operation data to perform data-based modeling. The model was implemented using nonlinear regression and machine learning, such as a support vector machine and artificial neural network. Then, the data-based HVAC and the actual HVAC operation results were comparatively analyzed based on a case study, and the model’s goodness-of-fit was evaluated based on performance metrics. Model performance indicators confirmed that the ANN-based HVAC model was most similar to the actual HVAC system. Full article

The present research work shows how a functional subsonic moist-air wind tunnel has been designed. Although this type of wind tunnel has never been developed to date, it is particularly interesting to develop a satisfactory design of feasibility under moist air conditions. Low-speed vertical-axis wind turbines employ different kinds of rotors, such as Savonius, Darrieus, and H-rotor. All these wind turbines present clear advantages, e.g., the horizontal-axis wind turbines are omnidirectional. This means they can work under different wind directions, need lower maintenance, and begin working under low wind speeds of 3 m/s. Recently, a new application of wind concentrators enabled the vertical-axis wind turbines to improve their performance coefficient based on new concepts like moist air phase change, which are being analysed to improve energy conversion. Thus, expectations were raised to design a suitable wind tunnel that accounts for the relative humidity of moist air. An initial prototype showed that the behaviour of open wind tunnels where the relative humidity of moist air was controlled by an adiabatic evaporative process was satisfactory. However, for such wind tunnels, certain improvements like computer control systems would need to be developed. Full article

The enhancement of gas turbine (GT) efficiency through inlet air cooling, known as TIAC, in chillers using the heat of exhaust gas is one of the most attractive tendencies in energetics, particularly in thermal engineering. In reality, any combustion engine with cyclic air cooling using waste heat recovery chillers might be considered as a power plant with in-cycle trigeneration focused on enhancing a basic engine efficiency, which results in additional power output or fuel savings, reducing carbon emissions in all cases. The higher the fuel efficiency of the engine, the more efficient its functioning as a source of emissions. The sustainable operation of a GT at stabilized low intake air temperature is impossible without using rational design to determine the cooling capacity of the chiller and TIAC system as a whole to match current duties without overestimation. The most widespread absorption lithium-bromide chillers (ACh) are unable to reduce the GT intake air temperature below 15 °C in a simple cycle because the temperature of their chilled water is approximately 7 °C. Deeper cooling air would be possible by applying a boiling refrigerant as a coolant in ejector chiller (ECh) as the cheapest and simplest in design. However, the coefficients of performance (COP) of EChs are considerably lower than those of AChs: about 0.3 compared to 0.7 of AChs. Therefore, EChs are applied for subsequent cooling of air to less than 15 °C, whereas the efficient ACh is used for ambient air precooling to 15 °C. The application of an absorption–ejector chiller (AECh) enables deeper inlet air cooling and greater effects accordingly. However, the peculiarities of the subtropical climate, characterized by high temperature and humidity and thermal loads, require extended analyses to reveal the character of thermal load and to modify the methodology of designing TIAC systems. The advanced design methodology that can reveal and thereby forecast the peculiarities of the TIAC system’s thermal loading was developed to match those peculiarities and gain maximum effect without oversizing. Full article

In this study, the thermodynamic behavior of a combined cycle power plant with integrated solar-driven inlet air cooling was simulated for Tehran, Phoenix, and Houston during warm-hot seasons. A considerable reduction in the output power was realized during hot ambient conditions due to the lower density of the air and lower mass flow rate to the turbines. The output power decreases from 306.6 to 260.8 MW as ambient temperature increases from 15 to 45 °C. This research focuses on utilizing solar cooling systems to achieve low inlet air temperature to generate high-electricity yields. Four different types of solar collectors and two different absorption chiller units were selected and simulated for each city to achieve the required goal. It was identified that integrating a solar inlet air cooling (SIAC) system can avert the reduction in output power with no impact on efficiency. The humid climatic condition in Houston and the low electricity cost in Tehran posed some challenges in designing a feasible SIAC system. However, by optimizing the solar collectors and cooling capacities, an optimal solution for utilizing inlet air cooling in humid climates is presented. In terms of overall impact, the evacuated flat plate collector (EFPC) coupled with a double-effect absorption chiller displayed the best economic performance among the four variants under study. In Phoenix, this combination can maintain output power during hot days with a DPR of 2.96 years. Full article

A large number of application cases show that air filter media are easy to fail under extreme conditions of high humidity, haze, rain and snow, thus seriously affecting the energy efficiency of gas turbines. To study the impact of humidity on the dust-holding performance of filter media, three typical filter media applied for gas turbines with a similar efficiency are selected, and their dust-holding performance is investigated at a humidity of 30%, 60% and 75%, respectively. The results showed that the dust-holding pressure drop curves of three filter media were divided into two phases. With the increase of humidity, the increasing pressure drop rate of three filter media decreased. The pressure drop synthetic fiber, glass fiber composite filter media and the synthetic fiber composite filter media with a sandwich structure were more significantly affected by humidity during the filter cake filtration phase. Under the same conditions, filter media with a sandwich structure had the highest dust-holding capacity, while the electrospun fiber composite filter material had the lowest one. The dustcake formed on the surface of the filter media that consist of a pure synthetic fiber or a small amount of plant fiber is significantly affected by humidity. Full article

In this work, a new hydroelectric basin modelling approach is described and applied to the Pontecosi basin, Italy. Several types of data sources were used to learn the model: a number of weather stations, satellite observations, the reanalysis dataset, and basin data. With the goal of predicting the water level of the basin, the model was composed by three cascade modules. Firstly, different spatial interpolation methods, such as Kriging, Radial Basis Function, and Natural Neighbours, were compared and applied to interpolate the weather stations data nearby the basin area to infer the main environmental variables (air temperature, air humidity, precipitation, and wind speed) in the basin area. Then, using these variables as inputs, a neural network was trained to predict the mean soil moisture concentration over the area, also to improve the low availability due to satellite orbits. Finally, a non-linear auto regressive exogenous input (NARX) model was trained to simulate the basin level with different prediction horizons, using the data from the previous modules and past basin data (water level, discharge flow rate, and turbine flow rate). Accurate predictions of the basin water level were achieved within 1 to 6 h ahead, with mean absolute errors (MAE) between 2 cm and 10 cm, respectively. Full article

This research investigates the most modern approaches to water treatment and recovery in power plants because of the scarcity of water sources and the significance of those sources in enhancing the performance of power-generating cycles. Gas turbines, which use mixes of air and water as the working fluid, provide superior efficiency, high specific power outputs, and reduced investment costs compared to combined cycles. Several different cycles for humidified gas turbines, including cycles of direct water injection, cycles of steam injection, and evaporative cycles that include humidity control towers, have been proposed. Despite this, only a few of these cycles have been put into practice, and even fewer are available for purchase on the market. This work aims to analyze the research and development literature on humidification-based gas turbines and highlight the cycles that have the most significant promise for the long run. In addition, work on development that still has to be carried out in order to deploy humidification-based gas turbine cycles is advised. This article may also be used as an overview of the research and development work that has taken place on humidification-based gas turbines over the course of the last thirty years. Full article