Article
Energy & Fuels
Keonwoo Park, Ilkyeong Moon
Summary: As the competitive advantages and demand for electric vehicles increase, efficient charging scheduling research is being actively conducted. Previous studies focused on centralized execution methods, but a decentralized method is more suitable for a realistic smart grid charging environment. Therefore, we propose a multi-agent deep reinforcement learning approach that can derive charging schedules for each electric vehicle and shows desirable performance in minimizing operating costs.
Article
Computer Science, Interdisciplinary Applications
Athanasios Aris Panagopoulos, Filippos Christianos, Michail Katsigiannis, Konstantinos Mykoniatis, Georgios Chalkiadakis, Marco Pritoni, Therese Peffer, Orestis P. Panagopoulos, Emmanouil S. Rigas, David E. Culler, Nicholas R. Jennings, Timothy Lipman
Summary: This study proposes an intelligent PEV charging scheduling system that takes into account time-varying tariffs, peak demand charges, and export tariffs, while considering the energy consumption of buildings and intermittent energy resource generation. The approach, based on adaptive model predictive control and a depth-first-search-based charging planning algorithm, demonstrates a cost reduction of approximately 5% and 35% in the United States and the United Kingdom domestic settings, respectively, compared to standard PEV charging practices.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Computer Science, Information Systems
Xi Chen, Haihui Wang, Fan Wu, Yujie Wu, Marta C. Gonzalez, Junshan Zhang
Summary: This article presents a model of the electric vehicle (EV) charging network as a cyber-physical system that is coupled with transportation networks and smart grids. An EV charging station recommendation algorithm is proposed to create synergy between transportation networks and smart grids and utilize EV charging activities as a load-balancing tool to transfer energy between unbalanced distribution grids.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Automation & Control Systems
Yanyu Zhang, Xinpeng Rao, Chunyang Liu, Xibeng Zhang, Yi Zhou
Summary: The rapid growth in electric vehicle (EV) numbers has increased residents' demand for electricity, which may overload distribution networks without proper power consumption planning. To address the coordinated charging of EVs with photovoltaic (PV) energy connected to the power grid, a collaborative charging control strategy based on a double deep q-network with Prioritized experience replay (DDQN-PER) is proposed. The approach incorporates a Long-Short-Term Memory (LSTM) neural network to handle uncertainties caused by power requirements, PV power, and real-time electricity prices. Simulation case studies using real data demonstrate that the proposed algorithm reduces charging costs by 30% and increases PV power utilization by 10% compared to the DDQN algorithm.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Energy & Fuels
Mike F. Voss, Steven P. Haveman, Gerrit Maarten Bonnema
Summary: Current EV charging systems have limited smart functionality, with most research focusing on grid load-balancing. This article introduces a VeCS model to support the early design of a smart charging system, with a focus on adaptive charging speeds and charging point management. Simulation algorithms are developed to assess system performance based on operational costs, CO2 emissions, and employee satisfaction.
Article
Computer Science, Information Systems
Shiyao Zhang, James J. Q. Yu
Summary: This article proposes a multistage system framework for an integrated EV dynamic wireless charging system in a smart city. It develops an optimal placement strategy for power tracks based on city traffic information and EV energy demand, and formulates a dynamic V2G scheduling scheme to coordinate the schedules of EVs with V2G ancillary services.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Mathematics
Xinxin Wang, Qian Xu, Xiaopan Shen
Summary: This paper proposes a strategy to predict the probability of queues forming for electric vehicles arriving at charging stations under intelligent network connection. It develops a real-time dynamic charging selection strategy and a distribution path optimization model based on intelligent network connection and queuing theory, which can reduce the distribution cost of electric vehicles.
Article
Environmental Sciences
Shafiqur Rehman, Abdul Baseer Mohammed, Luai Alhems, Fahad Alsulaiman
Summary: The current global greenhouse gas (GHG) emissions will lead to a 1.5-degree Celsius increase in the average global temperature by 2050, which will have negative impacts on organisms, ecosystems, and human well-being. Many countries have committed to reducing their emissions by 50% by 2030 and achieving net zero targets by 2050. The optimum solution to address this issue is to generate electricity from sustainable sources and use it to charge electric vehicle (EV) batteries, particularly in large open car parking areas near retail stores, academic institutes, industrial areas, and offices. This study focuses on implementing solar energy systems in the open parking areas of a specific academic campus to meet the daily load demand and charge EV batteries.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Energy & Fuels
Monica Hernandez Cedillo, Hongjian Sun, Jing Jiang, Yue Cao
Summary: This paper proposes a dynamic optimal operation of a solar-powered EV charging station, aiming to integrate more electric vehicles and renewable energy sources through pricing and control strategies. Simulations demonstrate that participating in energy markets can bring additional revenue streams to charging stations.
Article
Engineering, Electrical & Electronic
Luis E. Guillen Montenegro, Hugo N. Villegas Pico
Summary: This study focuses on the impacts of fast-charging processes of all-electric vehicles (EVs) on electric grids. Detailed and reduced-order simulation models are proposed to determine the power requirements for ac heating and fast-charging of EVs. The reduced-order model shows close agreement with real-time simulation and laboratory experimentation.
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION
(2023)
Article
Green & Sustainable Science & Technology
Ibrahim Sengor, Sitki Guner, Ozan Erdinc
Summary: The study proposes a real-time optimization-based energy management model for an EV parking lot using linear programming, aiming to maximize load factor and provide operational flexibility. By considering historical data to generate arrival/departure times and energy states, a more realistic approach is ensured. The validity of the optimization model is proven through a series of case studies, resulting in credible outcomes and valuable insights.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Engineering, Electrical & Electronic
Waleed Ejaz, Muhammad Naeem, Shree Krishna Sharma, Asad Masood Khattak, Muhammad Rashid Ramzan, Amjad Ali, Alagan Anpalagan
Summary: Internet of vehicles (IoV) is a new paradigm for exchanging and analyzing information between vehicles and people, infrastructure, and other vehicles. This paper proposes an IoV-based framework for deployment and scheduling of mobile charging infrastructure, aiming to minimize overall cost and optimize charging for electric vehicles.
IEEE SENSORS JOURNAL
(2021)
Article
Engineering, Electrical & Electronic
Jiayan Liu, Gang Lin, Christian Rehtanz, Sunhua Huang, Yang Zhou, Yong Li
Summary: A data-driven intelligent EV charging scheduling algorithm is proposed in this paper, which considers the charging costs, battery degradation, and users' dissatisfaction comprehensively. By forecasting the charging demand and establishing an optimization model based on time-of-use electricity price and charging facility limitation, the proposed algorithm achieves better effectiveness and performance compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Energy & Fuels
M. Secchi, G. Barchi, D. Macii, D. Petri
Summary: In this paper, an optimization algorithm is proposed to reduce the fluctuations in power supply and demand caused by the increasing penetration of EVs and PV generators. This algorithm achieves this by exploiting available PV power, shifting EV charging, and using vehicle-to-grid (V2G). The results of grid-level simulations show that this approach can decrease the net-load variance by up to 60% if no forecasting errors occur.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Green & Sustainable Science & Technology
Noman Shabbir, Lauri Kuett, Kamran Daniel, Victor Astapov, Hadi Ashraf Raja, Muhammad Naveed Iqbal, Oleksandr Husev
Summary: This study aims to provide input for the optimization design and management of PV and BESS systems for residential users with electric vehicles. Using measurement-based data from a rural low-voltage distribution network, the study investigates the capacity and use cases of BESS under different household and PV-EV penetration levels, and performs an economic analysis.
Article
Materials Science, Multidisciplinary
Ning Zhang, Zhiwei Lian, Weichen Zhang, Bo He, Xuewen Hu, Tao Zhu, Bo Jiang
Summary: The corrosion resistance and influence mechanism of P in low-Ni Cu-P-Cr-Ni weathering steels were analyzed. The results showed that the addition of P improved the corrosion current density and promoted the rapid formation of a rust layer. Cu and Cr enrichment further protected the steel matrix. After long-term wet/dry cyclic corrosion tests, the P content did not significantly affect the corrosion resistance of weathering steels. Therefore, the P content can be reduced to reduce cold brittleness.
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
(2023)
Review
Materials Science, Multidisciplinary
Xiaorui Wang, Tao Zhu, Jingke Zhang, Haoxu Ding, Shoune Xiao, Liantao Lu, Bing Yang, Guangwu Yang, Yanwen Liu
Summary: This review focuses on the research progress of millimeter- and micron-scale small specimen test techniques (SSTTs) for metallic materials over the past decade. The mainstream small specimens are divided into similarity, penetration, and semi-penetration methods, and representative tests such as small tensile test, small punch test, and indentation test are analyzed in detail. The correlations between SSTTs and conventional tests are discussed, along with the requirements for material testing. In addition, the characteristics and modification strategies of SSTTs are described, and their applications in forging, stamping, welding, and additive manufacturing are explored.
JOURNAL OF MATERIALS SCIENCE
(2023)
Article
Optics
Jingsheng Huang, Yulong Cao, Jindong Wang, Ai Liu, Qiang Wu, Zhenghu Chang, Ziwei Li, Yiyang Luo, Lei Gao, Guolu Yin, Tao Zhu
Summary: This article introduces an ultrafast multidimensional time-stretch imaging method, which can obtain multidimensional imaging through one-dimensional scanning. By encoding onto the amplitude and frequency of a spatially dispersed ultrafast chirped beam, the entire row of surface and depth information of the reflective sample is acquired. This method has micron level positioning accuracy in depth and the capability to obtain three-dimensional surface information.
OPTICS AND LASERS IN ENGINEERING
(2023)
Review
Neurosciences
Qingbo Yu, Zhang Jian, Dan Yang, Tao Zhu
Summary: Ischemic stroke is a globally prevalent neurological disorder with a high disability and mortality rate. Tissue plasminogen activator and thrombectomy can restore blood flow and improve outcomes, but are limited by a narrow time window. Biomaterials have emerged as a potential treatment option for ischemic stroke, with the ability to deliver therapeutic drugs and improve brain-targeting property.
FRONTIERS IN CELLULAR NEUROSCIENCE
(2023)
Article
Cardiac & Cardiovascular Systems
Weimin Zhang, Zheng Liu, Tao Zhu, Qiang Huo
Summary: Pentalogy of Cantrell is a rare congenital anomaly involving multiple birth defects, including the sternum, diaphragm, pericardium, abdominal wall, and heart. This paper reports the successful treatment of a 9-month-old girl with Pentalogy of Cantrell, Pentalogy of Fallot, and left ventricular diverticulum. The patient remains alive and healthy 13 years after surgery.
CONGENITAL HEART DISEASE
(2023)
Review
Medicine, General & Internal
Chang Liu, Yu-Tao Xiong, Tao Zhu, Wei Liu, Wei Tang, Wei Zeng
Summary: This review examined the efficacy of tooth extraction interventions in reducing the risk of medication-related osteonecrosis of the jaw (MRONJ) in patients taking antiresorptive drugs. The findings suggest that a drug holiday during dental procedures is unnecessary and may be potentially harmful. However, the evidence quality is low, highlighting the need for further high-quality randomized controlled trials.
JOURNAL OF CLINICAL MEDICINE
(2023)
Article
Energy & Fuels
Danyang Hu, Haorui Tang, Xiyao Zhang, Zhishan Li, Xing Zhu, Tao Zhu
Summary: The incorporation of Ce3+ ions into the PTAA film successfully suppresses the defects in perovskite and improves the performance of perovskite solar cells.
Article
Optics
Yu Long, Qiang Wu, Zhenghu Chang, Ai Liu, Yuanjie Yu, Lei Gao, Tao Zhu
Summary: We characterize the single-shot polarization evolution of dual dissipative solitons in an erbium-doped fiber laser mode-locked with carbon nanotubes using a high-speed wave-resolved measurement technique. The coupling between the orthogonal components of the vector soliton has a great influence on its physical properties, leading to various physical images. We observe typical polarization-locked vector solitons and polarization attractors in the dual soliton pulses, and identify three kinds of two solitons pulses with distinct relative phase evolutions.
OPTICS AND LASER TECHNOLOGY
(2023)
Article
Neurosciences
Mengchan Ou, Yali Chen, Jin Liu, Donghang Zhang, Yaoxin Yang, Jiefei Shen, Changhong Miao, Shao-Jun Tang, Xin Liu, Daniel K. Mulkey, Tao Zhu, Cheng Zhou
Summary: Astrocyte activation in the spinal dorsal horn may contribute to chronic neuropathic pain. The Kir4.1 channel in astrocytes is important for pain regulation, but its regulation and role in behavioral hyperalgesia remain unclear. This study found that Kir4.1 expression was decreased in spinal astrocytes after chronic constriction injury, and conditional knockout of Kir4.1 led to hyperalgesia while overexpression relieved pain. Kir4.1 expression was regulated by MeCP2. Knockdown of Kir4.1 increased astrocyte excitability and altered neuronal firing patterns in the spinal cord. Targeting spinal Kir4.1 could be a therapeutic approach for hyperalgesia in chronic neuropathic pain.
PROGRESS IN NEUROBIOLOGY
(2023)
Article
Neurosciences
Xiahui Zhang, Lei Ma, Meifang Liu, Tao Zhu, Zhilin Huang, Youlong Xiong, Ziyi Wang, Jing Shi
Summary: LYDD acupuncture treatment significantly reduces neurological impairment, cerebral infarct area, inflammatory factor levels, cerebral lesions, number of Nissl body and neuronal apoptosis in the MCAO/R model at different time points of reperfusion. RNA-seq analysis identifies differentially expressed genes that may be involved in neurotransmitter transmission, synaptic membrane potential, cell junctions, inflammatory response, immune response, cell cycle, and ECM. LYDD acupuncture treatment inhibits NF-kappa B pathway activity.
Article
Automation & Control Systems
Jianghong Zhou, Yi Qin, Jun Luo, Shilong Wang, Tao Zhu
Summary: Remaining useful life (RUL) prediction plays a crucial role in industrial equipment operation and maintenance. A new dual-thread gated recurrent unit (DTGRU) is proposed to enhance the predictive ability for complex degradation trajectories by mining stationary and nonstationary information. The DTGRU-based RUL prediction approach is validated using gear vibration signals and a degradation-trend-constrained variational autoencoder. Experimental results demonstrate that DTGRU outperforms existing typical prediction methods in terms of fitting precision and RUL prediction performance.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Laiyang Dang, Chaoze Zhang, Jiali Li, Da Wei, Ligang Huang, Tianyi Lan, Jiangshan Wang, Paul Ikechukwu Iroegbu, Leilei Shi, Guolu Yin, Tao Zhu
Summary: This paper reports on the implementation of a novel ultra-high spectral purity distributed Bragg reflector (DBR) all-fiber laser based on weak distributed feedback, where the spectrum can be modulated by precisely controlling the intensity of the distributed feedback signal. An ultra-high spectral purity laser with a spectral signal-to-noise ratio of 64 dB, a side mode suppression ratio (SMSR) of 83 dB, an output Lorentz linewidth of 115 Hz, and a relative intensity noise of less than -122 dB/Hz is successfully obtained.
JOURNAL OF LIGHTWAVE TECHNOLOGY
(2023)
Article
Energy & Fuels
Timothy J. Silverman, Michael G. Deceglie, Ingrid R. Repins, Tao Zhu, Zhaoning Song, Michael J. Heben, Yanfa Yan, Chengbin Fei, Jinsong Huang, Laura T. Schelhas
Summary: Metal halide perovskite photovoltaic modules deployed outdoors exhibit reversible daily efficiency changes of up to 30% between morning and afternoon at their maximum power point. Accurate prediction of energy yield and quantification of reliability require proper handling of these daily performance variations.
IEEE JOURNAL OF PHOTOVOLTAICS
(2023)
Article
Engineering, Mechanical
Jian Li, Bing Yang, Shuancheng Wang, M. N. James, Shoune Xiao, Tao Zhu, Guangwu Yang
Summary: This study measured the crack tip displacement field in U71MnG rail steel using digital image correlation technique. The Christopher-James-Patterson (CJP) model was modified to include the effect of dislocation field on the plastic zone and elastic field. The modified model accurately described the experimental plastic zone and improved the accuracy of stress intensity factors, showing the effectiveness of dislocation correction.
CHINESE JOURNAL OF MECHANICAL ENGINEERING
(2023)
Article
Thermodynamics
Yan-Jun Liu, Jing Wang, Tao Zhu, Yong-Qiang Chen, Rong-Jie Cai, Jun Wang, Qian Liu
Summary: A magnetic-field-enhanced solid-state fan (SSF) is proposed for thermal management of high-power electronics, utilizing a negative corona discharge superimposed by an electromagnetic field. Experimental optimization of magnetic flux density and permanent magnet position in the SSF, along with its application to LED chip cooling, demonstrates enhanced ionic wind velocity and driving force. The magnetic-field-enhanced SSF exhibits a better cooling effect, achieving a maximum junction temperature drop of 11.6 degrees C and higher cooling efficiency. This research introduces a novel approach to improve electronic cooling.
HEAT TRANSFER RESEARCH
(2023)
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
