Article
Thermodynamics
Khaled A. Naeim, Ahmed A. Hegazi, Mohamed M. Awad, Salah H. El-Emam
Summary: The enthalpy-entropy approach was used to model the gas turbine cycle and study the effects of ambient conditions on the output parameters. The results showed that changes in temperature, humidity, and pressure had impacts on the power, efficiency, and fuel consumption of the turbine.
CASE STUDIES IN THERMAL ENGINEERING
(2022)
Article
Thermodynamics
Samira Pourhedayat, Eric Hu, Lei Chen
Summary: This paper presents an improved validated semi-analytical gas turbine (GT) model that can simulate GT performance under various intake air conditions. The improved model overcomes three limitations of previous models by not assuming constant volumetric flow rate of intake air, constant output temperature of the combustion chamber (CC), and by evaluating the performance of the GT power plant directly from compressor intake air conditions. Deviations between model results and experimental data are less than 3%. Additionally, sensitivity analysis of both ambient conditions and GT characteristics is conducted as a sample application of the new model.
Article
Nanoscience & Nanotechnology
Kai Han, Jianjun Luo, Jian Chen, Baodong Chen, Liang Xu, Yawei Feng, Wei Tang, Zhong Lin Wang
Summary: A self-powered ammonia synthesis system using the Tesla turbine TENG was designed, showing a yield of 2.14 μg/h (0.126 μmol/h) under ambient conditions. The high-energy plasma generated by the system can react with water molecules to directly produce ammonia, indicating great potential for large-scale synthesis.
MICROSYSTEMS & NANOENGINEERING
(2021)
Article
Mechanics
Xiangheng Feng, Jiangyuan Fang, Yonggang Lin, Bowen Chen, Danyang Li, Hongwei Liu, Yajing Gu
Summary: In this study, a fully coupled and highly elaborated model based on computational fluid dynamics with the dynamic fluid body interaction method was established. The blade pitch motion was regulated through a user-defined function. Dynamic simulations of the full-configuration floating wind turbine system were performed in power production, shutdown, and startup cases. The results showed that the blade pitch motion decreased the aerodynamic loads and amplified the platform response amplitude, while extreme motion responses and mooring line tension oscillations were observed in shutdown and startup cases.
Article
Green & Sustainable Science & Technology
Haoran Meng, Hao Su, Jia Guo, Timing Qu, Liping Lei
Summary: Wind tunnel experiments were conducted to investigate the power and thrust characteristics of a wind turbine model under various surge and sway motions. Results showed that while these motions minimally affected the mean power output and rotor thrust, the rotor thrust fluctuations during surging were significantly higher than during swaying motions, and increased with surge frequency and amplitude. Additionally, the rotor thrust showed periodic fluctuations corresponding to the surge and sway motions, with peak power spectral density at the motion frequency and odd multiples.
Article
Thermodynamics
Koichi Yonezawa, Genki Nakai, Masahiro Takayasu, Kazuyasu Sugiyama, Katsuhiko Sugita, Shuichi Umezawa, Shuichi Ohmori
Summary: This study examined the influence of blade corrosion on aerodynamic characteristics of gas turbine blades using numerical simulations. The results showed that the change in throat area of the first-stage nozzle significantly affected aerodynamic characteristics, with expansion ratio playing a more significant role. Numerical results under actual operating conditions revealed a 3% difference in expansion ratio between new and old blades in the examined gas turbine.
Article
Automation & Control Systems
Sibel Arslan, Kemal Koca
Summary: This paper presents the accuracy of four different automatic programming (AP) methods in predicting the aerodynamic coefficients and power efficiency of the AH 93-W-145 wind turbine blade at different Reynolds numbers and angles of attack. The results show that while all four methods tested in the study accurately predict the aerodynamic coefficients, the Multi Gene GP (MGGP) method achieves the highest accuracy.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Mechanics
Lin Huang, Zhengping Zou, Chao Fu, Yumin Liu, Fei Shao
Summary: The mixing of turbine blade tip leakage and mainstream flows leads to significant aerodynamic loss. Understanding this mixing is crucial for improving turbine performance. In this study, a detached eddy simulation is used to simulate the flow in a typical high-pressure turbine rotor. The mixing in the blade tip region is assessed using the dilution index algorithm. The influence of various parameters on mixing is identified and analyzed, and the mixing mechanism is revealed. It is found that the diffusion coefficient and the unsteady tip leakage flow stick vortices play key roles in mixing. The mixing is enhanced by the Kelvin-Helmholtz instability-induced vortices. Additionally, the tip region is divided into near and far fields, with the entrainment zone in the far field showing high degrees of mixing while the leakage jet in the near field shows minimal mixing.
Article
Engineering, Environmental
Herman Heng, Fanran Meng, Jon McKechnie
Summary: This study predicts the future wind turbine blade waste arising in Canada and assesses five alternative strategies for managing this waste stream, finding that waste generation is concentrated in provinces with greater wind power deployment. The environmental impacts of waste management strategies depend on background energy systems, with cement kiln coprocessing achieving net zero emission and mechanical recycling reducing primary energy demand and greenhouse gas emissions, but requiring regulatory support for financial viability.
Article
Thermodynamics
Guangya Zhu, Tin-Tai Chow, Chun-Kwong Lee
Summary: The integration of biogas-fueled Maisotsenko combustion turbine cycle (MCTC) system offers significant advantages in improving system efficiency and cycle efficiency, with lower sensitivity to the methane content in biogas.
APPLIED THERMAL ENGINEERING
(2021)
Article
Thermodynamics
Minho Bang, Seungyeong Choi, Seok Min Choi, Dong-Ho Rhee, Hee Koo Moon, Hyung Hee Cho
Summary: This study investigates the cooling effectiveness and flow characteristics of a turbine blade tip using a special slot cooling scheme. The slot cooling exhibits significantly enhanced cooling performance compared to cooling holes, providing better thermal durability and reliability for the blade tip.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER
(2023)
Article
Engineering, Mechanical
M. Najmi, S. M. H. Mirbagheri
Summary: The failure of CM88Y nickel-based superalloy blades in a 25 MW gas turbine was investigated. Visual inspection and microscopy were used to examine the blades for damage. The metallurgical degradation and coating damages of the service-exposed blades were studied, along with the effect of service exposure on micro-hardness. The study found that the blades suffered from coating damages and degraded microstructure, leading to their rejection.
ENGINEERING FAILURE ANALYSIS
(2023)
Article
Thermodynamics
Zhongyi Wang, Yue Yin, Yanhua Wang, Tao Sun, Yigang Luan
Summary: This article explores the similarity characteristics of cooling performance in gas turbine blades and the effects of geometric scaling factor. Numerical simulation and data fitting were used to find that the heat transfer performance and resistance performance increase exponentially with the increase of the scaling factor. Regression equations were established for accurate prediction in engineering applications.
APPLIED THERMAL ENGINEERING
(2022)
Article
Energy & Fuels
Alaa Ahmad Sammour, Oleg V. Komarov, Mohammed A. Qasim, Samair Almalghouj, Ali Mazen Al Dakkak, Yang Du
Summary: This paper investigates the impact of intake ambient conditions on a combined cycle power plant in Syria. The study reveals that an increase in ambient temperature leads to a decrease in thermal efficiency and net power output, as well as an increase in fuel consumption and heat rate.
ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
(2023)
Article
Engineering, Multidisciplinary
Kun Feng, Yuan Xiao, Zhouzheng Li, Zhinong Jiang, Fengshou Gu
Summary: In this article, we propose a method that utilizes advanced signal processing and machine learning techniques to solve the problems of early warning of blade failure and difficulty in locating the failure. The method accurately calculates the blade passing frequency from gas turbine broadband casing vibration using Sparse Harmonic Product Spectrum (SHPS). It also separates the blade-related vibration from casing vibration in strong noise using Vold-Kalman filter and adaptive parameter optimization process (AVKF). Based on the blade-related vibration, a gas turbine blade condition model is built in an unsupervised learning manner, which can detect potential blade failures earlier and more accurately compared to conventional threshold methods. Furthermore, three coefficients are constructed to identify the blade fault location in a multi-stage system based on the vibration characteristics.
Article
Energy & Fuels
Shitong Fang, Houfan Du, Tao Yan, Keyu Chen, Zhiyuan Li, Xiaoqing Ma, Zhihui Lai, Shengxi Zhou
Summary: This paper proposes a new type of nonlinear VIV energy harvester (ANVEH) that compensates for the decrease in peak energy output at low wind speeds by introducing an auxiliary structure. Theoretical and experimental results show that ANVEH performs better than traditional nonlinear VIV energy harvesters under various system parameter variations.
Article
Energy & Fuels
Wei Jiang, Shuo Zhang, Teng Wang, Yufei Zhang, Aimin Sha, Jingjing Xiao, Dongdong Yuan
Summary: A standardized method was developed to evaluate the availability of solar energy resources in road areas, which combined the Analytic Hierarchy Process (AHP) and the Geographic Information System (GIS). By analyzing critical factors and using a multi-indicator evaluation method, the method accurately evaluated the utilization of solar energy resources and guided the optimal location selection for road photovoltaic (PV) projects. The results provided guidance for the application of road PV projects and site selection for route corridors worldwide, promoting the integration of transportation and energy.
Article
Energy & Fuels
Chang Liu, Jacob A. Wrubel, Elliot Padgett, Guido Bender
Summary: The study investigates the effects of coating defects on the performance of the anode porous transport layer (PTL) in water electrolyzers. The results show that an increasing fraction of uncoated regions on the PTL leads to decreased cell performance, with continuous uncoated regions having a more severe impact compared to multiple thin uncoated strips.
Article
Energy & Fuels
Marcos Tostado-Veliz, Xiaolong Jin, Rohit Bhakar, Francisco Jurado
Summary: In this paper, a coordinated charging price mechanism for clusters of parking lots is proposed. The research shows that enabling vehicle-to-grid characteristics can bring significant economic benefits for users and the cluster coordinator, and vehicle-to-grid impacts noticeably on the risk-averse character of the uncertainty-aware strategies. The developed pricing mechanism can reduce the cost for users, avoiding to directly translate the energy cost to charging points.
Article
Energy & Fuels
Duan Kang
Summary: Building an energy superpower is a key strategy for China and a long-term goal for other countries. This study proposes an evaluation system and index for measuring energy superpower, and finds that China has significantly improved its ranking over the past 21 years, surpassing other countries.
Article
Energy & Fuels
Fucheng Deng, Yifei Wang, Xiaosen Li, Gang Li, Yi Wang, Bin Huang
Summary: This study investigated the synergistic blockage mechanism of sand and hydrate in gravel filling layer and the evolution of permeability in the layer. Experimental models and modified permeability models were established to analyze the effects of sand particles and hydrate formation on permeability. The study provided valuable insights for the safe and efficient exploitation of hydrate reservoirs.
Article
Energy & Fuels
Hao Wang, Xiwen Chen, Natan Vital, Edward Duffy, Abolfazl Razi
Summary: This study proposes a HVAC energy optimization model based on deep reinforcement learning algorithm. It achieves 37% energy savings and ensures thermal comfort for open office buildings. The model has a low complexity, uses a few controllable factors, and has a short training time with good generalizability.
Article
Energy & Fuels
Moyue Cong, Yongzhuo Gao, Weidong Wang, Long He, Xiwang Mao, Yi Long, Wei Dong
Summary: This study introduces a multi-strategy ultra-wideband energy harvesting device that achieves high power output without the need for external power input. By utilizing asymmetry, stagger array, magnetic coupling, and nonlinearity strategies, the device maintains a stable output voltage and high power density output at non-resonant frequencies. Temperature and humidity monitoring are performed using Bluetooth sensors to adaptively assess the device.
Article
Energy & Fuels
Tianshu Dong, Xiudong Duan, Yuanyuan Huang, Danji Huang, Yingdong Luo, Ziyu Liu, Xiaomeng Ai, Jiakun Fang, Chaolong Song
Summary: Electrochemical water splitting is crucial for hydrogen production, and improving the hydrogen separation rate from the electrode is essential for enhancing water electrolyzer performance. However, issues such as air bubble adhesion to the electrode plate hinder the process. Therefore, a methodology to investigate the two-phase flow within the electrolyzer is in high demand. This study proposes using a microfluidic system as a simulator for the electrolyzer and optimizing the two-phase flow by manipulating the micro-structure of the flow.
Article
Energy & Fuels
Shuo Han, Yifan Yuan, Mengjiao He, Ziwen Zhao, Beibei Xu, Diyi Chen, Jakub Jurasz
Summary: Giving full play to the flexibility of hydropower and integrating more variable renewable energy is of great significance for accelerating the transformation of China's power energy system. This study proposes a novel day-ahead scheduling model that considers the flexibility limited by irregular vibration zones (VZs) and the probability of flexibility shortage in a hydropower-variable renewable energy hybrid generation system. The model is applied to a real hydropower station and effectively improves the flexibility supply capacity of hydropower, especially during heavy load demand in flood season.
Article
Energy & Fuels
Zhen Wang, Kangqi Fan, Shizhong Zhao, Shuxin Wu, Xuan Zhang, Kangjia Zhai, Zhiqi Li, Hua He
Summary: This study developed a high-performance rotary energy harvester (AI-REH) inspired by archery, which efficiently accumulates and releases ultralow-frequency vibration energy. By utilizing a magnetic coupling strategy and an accumulator spring, the AI-REH achieves significantly accelerated rotor speeds and enhanced electric outputs.
Article
Energy & Fuels
Yi Yang, Qianyi Xing, Kang Wang, Caihong Li, Jianzhou Wang, Xiaojia Huang
Summary: In this study, a novel hybrid Quantile Regression (QR) model is proposed for Probabilistic Load Forecasting (PLF). The model integrates causal dilated convolution, residual connection, and Bidirectional Long Short-Term Memory (BiLSTM) for multi-scale feature extraction. In addition, a Combined Probabilistic Load Forecasting System (CPLFS) is proposed to overcome the inherent flaws of relying on a single model. Simulation results show that the hybrid QR outperforms traditional models and CPLFS exceeds the best benchmarks in terms of prediction accuracy and stability.
Article
Energy & Fuels
Wen-Jiang Zou, Young-Bae Kim, Seunghun Jung
Summary: This paper proposes a dynamic prediction model for capacity fade in vanadium redox flow batteries (VRFBs). The model accurately predicts changes in electrolyte volume and capacity fade, enhancing the competitiveness of VRFBs in energy storage applications.
Article
Energy & Fuels
Yuechao Ma, Shengtie Wang, Guangchen Liu, Guizhen Tian, Jianwei Zhang, Ruiming Liu
Summary: This paper focuses on the balance of state of charge (SOC) among multiple battery energy storage units (MBESUs) and bus voltage balance in an islanded bipolar DC microgrid. A SOC automatic balancing strategy is proposed considering the energy flow relationship and utilizing the adaptive virtual resistance algorithm. The simulation results demonstrate the effectiveness of the proposed strategy in achieving SOC balancing and decreasing bus voltage unbalance.
Article
Energy & Fuels
Raad Z. Homod, Basil Sh. Munahi, Hayder Ibrahim Mohammed, Musatafa Abbas Abbood Albadr, Aissa Abderrahmane, Jasim M. Mahdi, Mohamed Bechir Ben Hamida, Bilal Naji Alhasnawi, A. S. Albahri, Hussein Togun, Umar F. Alqsair, Zaher Mundher Yaseen
Summary: In this study, the control problem of the multiple-boiler system (MBS) is formulated as a dynamic Markov decision process and a deep clustering reinforcement learning approach is applied to obtain the optimal control policy. The proposed strategy, based on bang-bang action, shows superior response and achieves more than 32% energy saving compared to conventional fixed parameter controllers under dynamic indoor/outdoor actual conditions.