Yang Liu¹, Lifu Ding^2,*, Zhenfan Yu¹, Tannan Xiao², Qiuyu Lu¹, Ying Chen², Weihua Wang¹

Energy Engineering, Vol.122, No.11, pp. 4365-4384, 2025, DOI:10.32604/ee.2025.068712 - 27 October 2025

Abstract Wake effects in large-scale wind farms significantly reduce energy capture efficiency. Active Wake Control (AWC), particularly through intentional yaw misalignment of upstream turbines, has emerged as a promising strategy to mitigate these losses by redirecting wakes away from downstream turbines. However, the effectiveness of yaw-based AWC is highly dependent on the accuracy of the underlying wake prediction models, which often require site-specific adjustments to reflect local atmospheric conditions and turbine characteristics. This paper presents an integrated, data-driven framework to maximize wind farm power output. The methodology consists of three key stages. First, a practical simulation-assisted… More >

Ahmad S. Azzahrani^*

Energy Engineering, Vol.122, No.11, pp. 4703-4713, 2025, DOI:10.32604/ee.2025.067398 - 27 October 2025

Abstract The Light Detection and Ranging (LiDAR) data analysis method has emerged as a powerful and versatile tool for characterizing atmospheric conditions and modeling light propagation through various media. In the context of renewable energy, particularly wind energy, LiDAR is increasingly utilized to analyze wind flow, turbine wake effects, and turbulence in complex terrains. This study focuses on advancing LiDAR data interpretation through the development and application of the LiDAR Statistical Barnes Objective Analysis (LiSBOA) method. LiSBOA enhances the capacity of scanning LiDAR systems by enabling more precise optimization of scan configurations and improving the retrieval… More >

Yinyu Tang^1,2,3,*, Mingzhi Yang^1,2,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011292

Abstract Energy efficiency and environmental sustainability in rail transit are key engineering goals. In urban trains, pressure drag plays a more significant role than in high-speed EMUs, primarily due to the blunt shape of the train’s head. The constraints imposed by underground construction and engineering protocols prevent the optimization strategies used in high-speed EMUs from being applied to urban trains. Therefore, aerodynamic drag reduction in blunt-tail urban trains, through active wake flow control, holds promise for improving train aerodynamics.
This study investigates drag reduction on the tail car of blunt urban trains using a hybrid numerical and… More >

Yinguo Yang¹, Lifu Ding^2,*, Yang Liu¹, Bingchen Wang², Weihua Wang¹, Ying Chen²

Energy Engineering, Vol.122, No.7, pp. 2571-2587, 2025, DOI:10.32604/ee.2025.065716 - 27 June 2025

Abstract This paper addresses the complexity of wake control in large-scale wind farms by proposing a partitioning control algorithm utilizing the FLORIDyn (FLOW Redirection and Induction Dynamics) dynamic wake model. First, the impact of wakes on turbine effective wind speed is analyzed, leading to a quantitative method for assessing wake interactions. Based on these interactions, a partitioning method divides the wind farm into smaller, computationally manageable zones. Subsequently, a heuristic control algorithm is developed for yaw optimization within each partition, reducing the overall computational burden associated with multi-turbine optimization. The algorithm’s effectiveness is evaluated through case More >

Zhi Yang^1,2, Xiaohui Zhang^1,2,*, Xinting Tong³, Yutang Zhao⁴, Teng Xia^1,2, Hua Wang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.5, pp. 1133-1150, 2025, DOI:10.32604/fdmp.2025.061737 - 30 May 2025

Abstract In bottom-blown copper smelting processes, oxygen-enriched air is typically injected into the melt through a lance, generating bubbles that ascend and agitate the melt, enhancing mass, momentum, and heat transfer within the furnace. The melt’s viscosity, which varies across reaction stages, and the operating conditions influence bubble size and dynamics. This study investigates the interplay between melt viscosity and bubble diameter on bubble motion using numerical simulations and experiments. In particular, the volume of fluid (VOF) method and Ω-identification technique were employed to analyze bubble velocity, deformation, trajectories, and wake characteristics. The results showed that More >

Yuzhe Ma, Jiye Zhang^*, Jiawei Shi

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.12, pp. 2843-2865, 2024, DOI:10.32604/fdmp.2024.055205 - 23 December 2024

Abstract The large number and dense layout of rail fastening can significantly affect the aerodynamic performance of trains. Utilizing the Improved Delayed Detached Eddy Simulation (IDDES) approach based on the SST (Shear Stress Transport) k-ω turbulent model, this study evaluates the effects of the rail fastening system on the aerodynamic force, slipstream and train wake under crosswind conditions. The results indicate that in such conditions, compared to the model without rails, the rail and the fastening system reduce the drag force coefficient of the train by 1.69%, while the lateral force coefficients increase by 1.16% and… More >

Xueguang Meng¹, Zengshuang Chen¹, Yuxin Xie¹, Gang Chen^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.4, pp. 1-5, 2023, DOI:10.32604/icces.2023.09892

Abstract Many species generally choose highly organized movements to gain more performance advantages rather than alone in the animal world, such as V-formation and line formation in birds. Understanding the aerodynamic characteristics and flow variation of multi-flapping wings in formation flight could be applied to the formation design of new bionic flapping-wing aircraft. In this paper, the effects of unequal individual spacing on the aerodynamic performance and flow mechanism of three-dimensional three-flapping wings flying in tandem formation are investigated numerically at a low Reynolds number. The simulations include small and large spacings, as well as cases… More >

Hafza Ayesha Siddiqa¹, Muhammad Irfan¹, Saadullah Farooq Abbasi^2,*, Wei Chen¹

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1759-1778, 2023, DOI:10.32604/cmc.2023.041970 - 29 November 2023

Abstract Automatic sleep staging of neonates is essential for monitoring their brain development and maturity of the nervous system. EEG based neonatal sleep staging provides valuable information about an infant’s growth and health, but is challenging due to the unique characteristics of EEG and lack of standardized protocols. This study aims to develop and compare 18 machine learning models using Automated Machine Learning (autoML) technique for accurate and reliable multi-channel EEG-based neonatal sleep-wake classification. The study investigates autoML feasibility without extensive manual selection of features or hyperparameter tuning. The data is obtained from neonates at post-menstrual… More >

Kun Liu^1,2, Peiran Li³, Yu Zhang^1,*, Jia Ren¹, Xianyu Wang², Uzair Aslam Bhatti¹

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3257-3274, 2023, DOI:10.32604/cmc.2023.039430 - 08 October 2023

Abstract To obtain the optimal Bayesian network (BN) structure, researchers often use the hybrid learning algorithm that combines the constraint-based (CB) method and the score-and-search (SS) method. This hybrid method has the problem that the search efficiency could be improved due to the ample search space. The search process quickly falls into the local optimal solution, unable to obtain the global optimal. Based on this, the Particle Swarm Optimization (PSO) algorithm based on the search space constraint process is proposed. In the first stage, the method uses dynamic adjustment factors to constrain the structure search space… More >

Sun-Woo Yun¹, Na-Eun Park¹, Il-Gu Lee^1,2,*

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2897-2917, 2023, DOI:10.32604/iasc.2023.039940 - 11 September 2023

Abstract As time and space constraints decrease due to the development of wireless communication network technology, the scale and scope of cyberattacks targeting the Internet of Things (IoT) are increasing. However, it is difficult to apply high-performance security modules to the IoT owing to the limited battery, memory capacity, and data transmission performance depending on the size of the device. Conventional research has mainly reduced power consumption by lightening encryption algorithms. However, it is difficult to defend large-scale information systems and networks against advanced and intelligent attacks because of the problem of deteriorating security performance. In… More >