Chunyan Li¹, Luo Li¹, Yushuang Li², Yong Jia¹, Wenyan Li^3,*

Energy Engineering, Vol.122, No.10, pp. 4313-4330, 2025, DOI:10.32604/ee.2025.070187 - 30 September 2025

Abstract To accelerate the large-scale integration of renewable energy and support the strategic goals of “carbon peaking and carbon neutrality,” High Voltage Direct Current (HVDC) transmission technology has made significant breakthroughs. Among the various approaches, a hybrid DC transmission system that combines a line-commutated converter (LCC) and a voltage source converter (VSC) retains the inherent fault self-clearing capability of the LCC topology while mitigating the risk of commutation failure when connected to a weak grid. In this paper, based on the harmonic generation mechanisms of hybrid DC transmission systems, an improved 3-pulse harmonic source model of… More >

Jichao Li, Xuexin Zhu, Cong Zhang, Shiwang Dang, Guang Chen^*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.9, pp. 2305-2329, 2025, DOI:10.32604/fdmp.2025.067087 - 30 September 2025

Abstract The rapid advancement of technology and the increasing speed of vehicles have led to a substantial rise in energy consumption and growing concern over environmental pollution. Beyond the promotion of new energy vehicles, reducing aerodynamic drag remains a critical strategy for improving energy efficiency and lowering emissions. This study investigates the influence of key geometric parameters on the aerodynamic drag of vehicles. A parametric vehicle model was developed, and computational fluid dynamics (CFD) simulations were conducted to analyse variations in the drag coefficient () and pressure distribution across different design configurations. The results reveal that More >

Sen Yang¹, Jie Zhong¹, Boyu Gan¹, Yi Sun¹, Changming Bu¹, Mingtao Zhang¹, Jiehong Li^1,*, Yang Yu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 2943-2967, 2025, DOI:10.32604/cmes.2025.067282 - 30 September 2025

Abstract Foam concrete is widely used in engineering due to its lightweight and high porosity. Its compressive strength, a key performance indicator, is influenced by multiple factors, showing nonlinear variation. As compressive strength tests for foam concrete take a long time, a fast and accurate prediction method is needed. In recent years, machine learning has become a powerful tool for predicting the compressive strength of cement-based materials. However, existing studies often use a limited number of input parameters, and the prediction accuracy of machine learning models under the influence of multiple parameters and nonlinearity remains unclear.… More >

Yuming Luo¹, Wei Zhang², Anqi Zhao², Ling Gou¹, Li Chen¹, Yaling Yang¹, Xiaoping Wang¹, Shichang Liu¹, Huiqing Qi³, Shilai Hu^2,*

Energy Engineering, Vol.122, No.8, pp. 3201-3221, 2025, DOI:10.32604/ee.2025.066507 - 24 July 2025

Abstract This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety. Previous research primarily focused on integrating reservoir, wellbore, and surface facility constraints, often resulting in broad constraint ranges and slow model convergence. To solve this problem, the present study introduces additional constraints on maximum withdrawal rates by combining binomial deliverability equations with material balance equations for closed gas reservoirs, while considering extreme peak-shaving demands. This approach effectively narrows the constraint range. Subsequently, a collaborative optimization model with… More >

Van-Ha Hoang¹, Jong Weon Lee¹, Chun-Su Park^2,*

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4097-4116, 2025, DOI:10.32604/cmc.2025.063468 - 19 May 2025

Abstract Fire can cause significant damage to the environment, economy, and human lives. If fire can be detected early, the damage can be minimized. Advances in technology, particularly in computer vision powered by deep learning, have enabled automated fire detection in images and videos. Several deep learning models have been developed for object detection, including applications in fire and smoke detection. This study focuses on optimizing the training hyperparameters of YOLOv8 and YOLOv10 models using Bayesian Tuning (BT). Experimental results on the large-scale D-Fire dataset demonstrate that this approach enhances detection performance. Specifically, the proposed approach… More >

Zihang Wang¹, Ying Peng¹, Xiong Lan², Xiaoyu Bai³, Chao Deng¹, Yuan Ren^1,*

Structural Durability & Health Monitoring, Vol.19, No.3, pp. 643-664, 2025, DOI:10.32604/sdhm.2025.060302 - 03 April 2025

Abstract To investigate the influence of different longitudinal constraint systems on the longitudinal displacement at the girder ends of a three-tower suspension bridge, this study takes the Cangrong Xunjiang Bridge as an engineering case for finite element analysis. This bridge employs an unprecedented tower-girder constraint method, with all vertical supports placed at the transition piers at both ends. This paper aims to study the characteristics of longitudinal displacement control at the girder ends under this novel structure, relying on finite element (FE) analysis. Initially, based on the Weigh In Motion (WIM) data, a random vehicle load… More >

Ho-Yin Wong¹, Guan-Yan Yang^1,*, Kuo-Hui Yeh², Farn Wang¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-4, 2024, DOI:10.32604/icces.2024.013279

Abstract 1 Introduction
This paper explores various strategies to enhance neural network performance, including adjustments to network architecture, selection of activation functions and optimizers, and regularization techniques. Hyperparameter optimization is a widely recognized approach for improving model performance [2], with methods such as grid search, genetic algorithms, and particle swarm optimization (PSO) [3] previously utilized to identify optimal solutions for neural networks. However, these techniques can be complex and challenging for beginners. Consequently, this research advocates for the use of SSO, a straightforward and effective method initially applied to the LeNet model in 2023 [4]. SSO optimizes… More >

Junshan Hu^1,2,*, Shiqing Mi¹, Jinrong Fang¹, Wei Tian¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.011840

Abstract This research aims to investigate efficient repair techniques of cracked Ti-alloy aircraft structures with adhesively bonded carbon fiber-reinforced polymer composite patches. The repaired specimens in the configuration of a Ti-alloy butt joint with one-side bonded composite patch were prepared under multiple repair factors including patch thickness, patch length, adhesive thickness, cure pressure, patch layup and surface treatment. The repair efficiency was evaluated by loading behavior, bonded interface microstructure and failure mode. The three-dimensional (3D) finite element (FE) model has been established. Based on 3D Hashin failure criteria, the damage initiation and evolution in CFRP were… More >

Aijia Ding, Tingzhang Liu^*

Energy Engineering, Vol.121, No.12, pp. 3735-3759, 2024, DOI:10.32604/ee.2024.054687 - 22 November 2024

Abstract The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources. This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative (FOPID) controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration. To improve load frequency control, the proposed controllers are applied to a two-area interconnected microgrid system incorporating diverse energy sources, such as wind turbines, photovoltaic cells, diesel generators, and various storage technologies. A novel meta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers. The efficacy… More >

Yaren Aydın¹, Gebrail Bekdaş^1,*, Sinan Melih Nigdeli¹, Zong Woo Geem^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2471-2499, 2024, DOI:10.32604/cmes.2024.056693 - 31 October 2024

Abstract Dynamic impacts such as wind and earthquakes cause loss of life and economic damage. To ensure safety against these effects, various measures have been taken from past to present and solutions have been developed using different technologies. Tall buildings are more susceptible to vibrations such as wind and earthquakes. Therefore, vibration control has become an important issue in civil engineering. This study optimizes tuned mass damper inerter (TMDI) using far-fault ground motion records. This study derives the optimum parameters of TMDI using the Adaptive Harmony Search algorithm. Structure displacement and total acceleration against earthquake load More >