Search Results (152)

In 2019, more than 16% of the globe’s total production of electricity was provided by hydroelectric power plants. The core of a typical hydroelectric power plant is the turbine. Turbines are subjected to high levels of pressure, vibration, high temperatures, and air gaps as water passes through them. Turbine blades weighing several tons break due to this surge, a tragic accident because of the massive damage they cause. This research aims to develop predictive models to accurately predict the status of hydroelectric power plants based on real stored data for all factors affecting the status of these plants. The importance of having a typical predictive model for the future status of these plants lies in avoiding turbine blade breakage and catastrophic accidents in power plants and the resulting damages, increasing the life of these plants, avoiding sudden shutdowns, and ensuring stability in the generation of electrical energy. In this study, artificial neural network algorithms (RNN and LSTM) are used to predict the condition of the hydropower station, identify the fault before it occurs, and avoid it. After testing, the LSTM algorithm achieved the greatest results with regard to the highest accuracy and least error. According to the findings, the LSTM model attained an accuracy of 99.55%, a mean square error (MSE) of 0.0072, and a mean absolute error (MAE) of 0.0053. Full article

The increasing environmental challenges posed by the widespread use of fossil fuels and the fluctuating nature of renewable energy have driven the need for more efficient and sustainable energy solutions. Current research is actively exploring hybrid energy systems as a means to address these issues. One such area of focus is the integration of Organic Rankine Cycles (ORCs) with gas and steam turbines, utilizing both natural gas (NG) and solar parabolic trough collectors (PTCs) as energy sources. This study examines the performance of a hybrid system implemented in Kirkuk, Iraq, a region known for its substantial solar radiation. Previous research has shown that hybrid systems can effectively enhance energy conversion efficiency and reduce environmental impacts, but there is still a need to assess the specific benefits of such systems in different geographical and operational contexts. The analysis reveals a thermal efficiency of 59.32% and an exergy efficiency of 57.28%. The exergoeconomic analysis highlights the optimal energy cost at USD 71.93/MWh when the compressor pressure ratio is set to 8 bar. The environmental assessment demonstrates a significant reduction in CO2/emissions, with a carbon footprint of 316.3 kg CO2/MWh at higher compressor pressure ratios. These results suggest that integrating solar energy with natural gas can substantially improve electricity generation while being both cost-effective and environmentally sustainable. Full article

This paper proposes an innovative transient stability index (TSI) designed to enhance the real-time assessment of power system stability. The TSI integrates a corrected kinetic energy approach with a modified equal area criterion, offering a novel methodology for evaluating transient stability margins in power systems. Unlike traditional methods, the proposed TSI operates without relying on post-fault data, making it particularly suitable for online applications. A structure-preserving model is utilized to represent the power network, accounting for key factors such as controller behavior during transient events. Additionally, a new statistical classification method is introduced to efficiently determine the individual contribution of generators to the overall system stability. The effectiveness of the proposed approach is validated through comprehensive case studies on IEEE 9-bus and IEEE 39-bus systems. The simulation results confirm that the proposed method provides accurate, real-time insights into the transient stability margins of power systems, demonstrating its practical advantages in both analysis and operation. Full article

Hydrogen is a promising fuel because it has good capabilities to operate gas turbines. Due to its ignition speed, which exceeds the ignition of traditional fuel, it achieves a higher thermal efficiency while the resulting emissions are low. So, it was used as a clean and sustainable energy source. This paper reviews the most important research that was concerned with studying the characteristics of hydrogen combustion within incinerators and power generation equipment, where hydrogen was used as a fuel mixed with traditional fuel in the combustion chambers of gas turbines. It also includes an evaluation of the combustion processes and flame formation resulting from the enrichment of gaseous fuels with hydrogen and partial oxidation. A large amount of theoretical and experimental work in this field has been reviewed. This review summarizes the predictive and experimental results of various research interests in the field of hydrogen combustion and also production. Full article

This paper introduces a novel real-time ANFIS controller, specifically designed for thermal synchronous generators, to mitigate the risks associated with cyber-physical attacks on power systems. The controller integrates the dynamic model of the turbine’s thermomechanical components, such as the boiler and heat transfer processes, within the synchronous generator. In contrast to previous studies, this model is designed for practical implementation and addresses often-overlooked areas, including the interaction between electrical and thermomechanical components, real-time control responses to cyber-physical attacks, and the incorporation of economic considerations alongside technical performance. This study takes a comprehensive approach to filling these gaps. Under normal conditions, the proposed controller significantly improves the management of industrial turbines and governors, optimizing existing control systems with a particular focus on minimizing generation costs. However, its primary innovation is its ability to respond dynamically to local and inter-area power oscillations triggered by cyber-physical attacks. In such events, the controller efficiently manages the turbines and governors of synchronous generators, ensuring the stability and reliability of power systems. This approach introduces a cutting-edge thermo-electrical control strategy that integrates both electrical and thermomechanical dynamics of thermal synchronous generators. The novelty lies in its real-time control capability to counteract the effects of cyber-physical attacks, as well as its simultaneous consideration of economic optimization and technical performance for power system stability. Unlike traditional methods, this work offers an adaptive control system using ANFIS (Adaptive NeuroFuzzy Inference System), ensuring robust performance under dynamic conditions, including interarea oscillations and voltage deviations. To validate its effectiveness, the controller undergoes extensive simulation testing in MATLAB/Simulink, with performance comparisons against previous state-of-the-art methods. Benchmarking is also conducted using IEEE standard test systems, including the IEEE 9-bus and IEEE 39-bus networks, to highlight its superiority in protecting power systems. Full article

Friction and high temperatures greatly affect the hardness and processing efficiency of superalloys. Therefore, it is important to provide a coating on their surfaces with a hard layer. In this study, pack boronizing was applied on Inconel 601 to improve its microstructure and tribological properties. In this regard, tribological tests were performed under MQL, nano-MQL1 (MQL + CuO), and nano-MQL2 (MQL + TiO₂) environments. The research results showed that the lowest wear depth, friction force, coefficient of friction (CoF), and volume loss values were obtained in pack-boronized Inconel 601 in a nano-MQL2 environment. In the nano-MQL2 environment, the wear depth decreased by 17.81% (from 57.922 µm to 47.605 µm) with package-boronized Inconel 601 compared to as-received Inconel 601 at a 45 N load. Pack-boronized Inconel 601 experienced an average reduction of 30.23%, 41.60%, and 52.32% in friction force when switching from dry to MQL, nano-MQL1, and nano-MQL2 environments, respectively. It was also observed that the coefficient of friction (CoF) and volume loss values decreased with pack boronizing in an MQL/nano-MQL environment. In a nano-MQL2 environment at 15 N load, volume losses for as-received and boron-coated Inconel 601 were determined as 0.288 mm³ and 0.249 mm³, respectively (13.54% decrease). The findings of this study demonstrate that pack boronizing and MQL and nano-MQL techniques enhance the tribological characteristics of Inconel 601 alloys. Full article

Ensuring the secure and cost-effective operation of smart power microgrids has become a significant concern for managers and operators due to the escalating damage caused by natural phenomena and cyber-attacks. This paper presents a novel framework focused on the dynamic reconfiguration of multi-microgrids to enhance system’s security index, including stability, reliability, and operation costs. The framework incorporates distributed generation (DG) to address cyber-attacks that can lead to line outages or generation failures within the network. Additionally, this work considers the uncertainties and accessibility factors of power networks through a modified point prediction method, which was previously overlooked. To achieve the secure and cost-effective operation of smart power multi-microgrids, an optimization framework is developed as a multi-objective problem, where the states of switches and DG serve as independent parameters, while the dependent parameters consist of the operation cost and techno-security indexes. The multi-objective problem employs deep learning (DL) techniques, specifically based on long short-term memory (LSTM) and prediction intervals, to effectively detect false data injection attacks (FDIAs) on advanced metering infrastructures (AMIs). By incorporating a modified point prediction method, LSTM-based deep learning, and consideration of technical indexes and FDIA cyber-attacks, this framework aims to advance the security and reliability of smart power multi-microgrids. The effectiveness of this method was validated on a network of 118 buses. The results of the proposed approach demonstrate remarkable improvements over PSO, MOGA, ICA, and HHO algorithms in both technical and economic indicators. Full article

In this study, by using the texts describing the hazards and precautions taken during text mining, the necessary processes were carried out to first estimate the probability value and severity value of the risk and then calculate the risk values by Natural Language Processing analysis. In order to be used within the scope of the study, two data sets were generated from the data in the risk assessment report prepared by applying the L-type matrix risk assessment in marble quarries between 2015 and 2021. Stochastic Gradient Descent (SGD) was used for classification and prediction by analyzing text data. One data set was used to analyze the probability value of the risk and the other was used to analyze the severity value of the risk. In light of the results, when a text containing hazard and precaution information was entered, a system was developed that analyzed this text, estimated the probability and severity values, and calculated the risk assessment score. The application of the SGD algorithm to learning models developed on text data yielded an accuracy rate of 91.2% in the risk probability data set and 97.5% in the risk severity data set. The results indicated that the models were capable of conducting automatic risk assessment on text data and of effectively predicting the requisite probability and severity values. Due to the high accuracy rates obtained during the study, this risk assessment software was recommended for use in marble quarries. Full article

Numerical simulations of the cutting process play a key role in manufacturing and cost optimization. Inherent in finite element analysis (FEA) simulations is the correct description of material behavior during machining. For this purpose, various material models are used to describe the behavior of the material in the range of high deformation, high temperature values, and high strain rates. Very often the Johnson–Cook (JC) material model is used for this purpose; however, the correct determination of the material constants of this model is a key aspect. Therefore, this paper presents a procedure for determining the material constants of the JC model using an analytical method based on normalized tensile and compression testing of the material for different strain rates over a wide temperature range. After determining the material constants, the authors conducted numerical simulations of the orthogonal turning of Ti6Al4V titanium alloy using the obtained constants. Validation of the obtained results with those obtained in experimental studies was also carried out. The outcomes demonstrated that the difference between FEM simulation and experimental tests did not exceed 0.02 mm (14%) in the case of chip thickness,. Much smaller differences were obtained for the temperature in the cutting zone, where the maximum difference was about 45 °C (4%). Comparing the components of the cutting force, we found that, in the case of the main cutting force, in most cases, the differences did not exceed 70 N (8%). After the verification of the obtained results, it was also found that the determined material constants of the Johnson–Cook model can be successfully used in FEM modeling of the cutting process of Ti6Al4V titanium alloy for the adopted range of values of technological parameters. Full article

This study investigates the efficiency of a hybrid coagulation–flocculation process for the treatment of industrial wastewater from the steel industry. The novel method combines a natural coagulant, processed Rosehip Seed Powder (RSP), with a chemical coagulant, aluminum chloride (AlCl₃), across varying concentrations and pH levels. The study simulated the pH 8 conditions of iron and steel industrial wastewater and examined the removal of heavy metals, total suspended solids (TSS), chemical oxygen demand (COD), and ammonia–nitrogen (NH₃-N). At pH 8, the optimal coagulant dosage was determined to be 0.75:0.75 (g/g) of RSP/AlCl₃ powder, resulting in high removal efficiencies across several parameters: 88.29% for COD, 91.85% for color, 99% for TSS, 93.11% for NH₃-N, 94.3% for Mn, 98.5% for Fe, 96.7% for Zn, and 99.3% for Ni. The pH optimization demonstrated high removal efficiencies without pH adjudication. The removal of heavy metals at pH 8 demonstrated high efficiencies, with Mn, Fe, Zn, and Al achieving 99.00%, 90.6%, 95.73%, and 92.3%, respectively. These results suggest that no pH adjustment is required when using RSP/AlCl₃ for the treatment of iron and steel industry wastewater through the coagulation method. Full article

Modern heritage, especially post-war housing estates, is facing the problems of appreciation and preservation. These buildings are interpreted in different ways by decision-makers because of questions relating to their identification. Accordingly, this research aims to better understand the heritage attributes and significance of post-war housing estates, in particular in the Yenişehir settlement—a neighborhood in Karabük, Türkiye. Within the framework of cultural significance and heritage values (values of DOCOMOMO), an assessment was conducted by using expert interviews for data collection. The AHP (analytical hierarchy process) method, one of the decision support systems, was used to contribute to the subjective decision process. The experts determined significance levels for the studied buildings based on whether they needed to be preserved. Comparisons with the AHP created essential data that showed different views, especially regarding intangible values. Through the process, the attributes and values of buildings were made visible. According to experts, the significance of the buildings has changed. This study consists of 5 stages: authenticity analysis of the buildings in the area, classification of the buildings, application of the AHP on buildings of greater significance, determining of cultural significance ranking, and making suggestions according to the ranking. Full article

Background: This study aimed to investigate the effect of cytoreductive nephrectomy (CN) on the survival outcomes of nivolumab used as a subsequent therapy after the failure of at least one anti-vascular endothelial growth factor (VEGF) agent in patients with metastatic clear-cell renal-cell carcinoma (ccRCC). Methods: We included 106 de novo metastatic ccRCC patients who received nivolumab after progression on at least one anti-VEGF agent. Multivariate Cox regression analysis was performed to investigate the factors affecting survival in patients receiving nivolumab. Results: Of the 106 de novo metastatic ccRCC patients, 83 (78.3%) underwent CN. There were no statistical differences between the two groups in terms of age, gender, Eastern Cooperative Oncology Group (ECOG) score, tumor size, International Metastatic RCC Database Consortium (IMDC) risk group, number of previous treatment lines, first-line anti-VEGF therapy, or metastasis sites (p = 0.137, p = 0.608, p = 0.100, p = 0.376, p = 0.185, p = 0.776, p = 0.350, and p = 0.608, respectively). The patients who received nivolumab with CN had a longer time to treatment discontinuation (TTD) [14.5 months, 95% confidence interval (CI): 8.6–20.3] than did those without CN 6.7 months (95% CI: 3.9–9.5) (p = 0.001). The median overall survival (OS) was 22.7 months (95% CI: 16.1–29.4). The patients with CN had a median OS of 22.9 months (95% CI: 16.3–29.4), while those without CN had a median OS of 8.1 months (95% CI: 5.6–10.5) (p = 0.104). In the multivariate analysis, CN [hazard ratio (HR): 0.521; 95% CI: 0.297–0.916; p = 0.024] and the IMDC risk score (p = 0.011) were statistically significant factors affecting TTD; however, the IMDC risk score (p = 0.006) was the only significant factor for overall survival. Conclusions: Our study showed that the TTD of nivolumab was longer in metastatic ccRCC patients who underwent cytoreductive nephrectomy. Full article

Titanium-Niobium (TiNb) alloys are commonly employed in a number of implantable devices, yet concerns exist regarding their use in implantology owing to the biomechanical mismatch between the implant and the host tissue. Therefore, to balance the mechanical performance of the load-bearing implant with bone, TiNb alloys with differing porosities were fabricated by powder metallurgy combined with spacer material. Microstructures and phase constituents were characterized with energy dispersive spectroscopy (EDS), scanning electron microscopy (SEM), and X-ray diffraction (XRD). The mechanical properties were tested by uniaxial compression, and the corrosion performance was determined via a potentiodynamic polarization experiment. To evaluate a highly matched potential implant with the host, biocompatibilities such as cell viability and proliferation rate, fibronectin adsorption, plasmid-DNA interaction, and an SEM micrograph showing the cell morphology were examined in detail. The results showed that the alloys displayed open and closed pores with a uniform pore size and distribution, which allowed for cell adherence and other cellular activities. The alloys with low porosity displayed compressive strength between 618 MPa and 1295 MPa, while the alloys with high porosity showed significantly lower strength, ranging from 48 MPa to 331 MPa. The biological evaluation of the alloys demonstrated good cell attachment and proliferation rates. Full article

Safranbolu, located in the Western Black Sea region of northern Turkey, consists of three historical settlements distinguished by monumental buildings and especially traditional houses. For this reason, the city was declared a ‘World Heritage Site’ by UNESCO in 1994. Traditional Safranbolu houses are examples of Turkish houses built with mixed techniques. In research on Turkish residences and traditional Safranbolu houses, the focus has been on the origin of dwelling construction culture, the spatial reading of the parts of the house, the sociocultural life of the owners, and the surveying of traditional construction techniques. In this study, the design principles affecting the spatial arrangement of Safranbolu houses were evaluated from a holistic perspective. Dwellings selected from Safranbolu sites were analyzed at the urban scale according to the environmental design data of the residential area. It can be seen that houses were designed in a certain order according to these factors. In the building scale analyses, the diversity in the domestic space configuration was surveyed by the drawings of immediate environments at the plans and sections of the houses. The study contributes by explaining the relationship between parcel characteristics and house design. Full article

The resurgence of the Taliban in Afghanistan has significantly exacerbated educational challenges for marginalized women and girls, deepening gender disparities and impeding socio-economic development. Addressing these issues, this article introduces the Blockchain and Artificial Intelligence Non-Formal Education System (BANFES), an innovative educational solution specifically designed for Afghan girls deprived of formal schooling. BANFES leverages advanced artificial intelligence technologies, including personalized data analysis, to provide customized learning experiences. Additionally, blockchain technology ensures secure record management and data integrity, facilitating a decentralized educational ecosystem where various nodes offer hybrid learning methodologies without intermediaries. This system not only adapts to individual learning speeds and styles to enhance engagement and outcomes but also employs an independent assessment mechanism to evaluate learners. Such evaluations promote transparency and maintain the quality and reputation of educational contributions within the network. The BANFES initiative also addresses implementation challenges, including local distrust and integration with existing educational structures, providing a robust model to overcome barriers to education. Furthermore, the paper explores the scalability of BANFES, proposing its application as a global strategy for non-formal education systems facing similar geopolitical and infrastructural challenges. By creating a secure, flexible, and learner-focused environment, BANFES aims to empower Afghan women and girls with essential skills for personal and professional growth, thus fostering socioeconomic advancement within their communities and setting a new standard for informal education worldwide. Full article