Dong Pan¹, Xu Gui¹, Jiayin Xu¹, Yuming Shen¹, Haoran Xu², Yinghao Ma^2,*

Energy Engineering, Vol., , DOI:10.32604/ee.2024.046464

Abstract With the increasing urgency of the carbon emission reduction task, the generation expansion planning process needs to add carbon emission risk constraints, in addition to considering the level of power adequacy. However, methods for quantifying and assessing carbon emissions and operational risks are lacking. It results in excessive carbon emissions and frequent load-shedding on some days, although meeting annual carbon emission reduction targets. First, in response to the above problems, carbon emission and power balance risk assessment indicators and assessment methods, were proposed to quantify electricity abundance and carbon emission risk level of power planning scenarios, considering power supply regulation… More >

Wenlu Ji^*, Teng Tu, Nan Ma

Energy Engineering, Vol., , DOI:10.32604/ee.2024.046112

Abstract To improve the resilience of a distribution system against extreme weather, a fuel-based distributed generator (DG) allocation model is proposed in this study. In this model, the DGs are placed at the planning stage. When an extreme event occurs, the controllable generators form temporary microgrids (MGs) to restore the load maximally. Simultaneously, a demand response program (DRP) mitigates the imbalance between the power supply and demand during extreme events. To cope with the fault uncertainty, a robust optimization (RO) method is applied to reduce the long-term investment and short-term operation costs. The optimization is formulated as a tri-level defender-attacker-defender (DAD)… More >

Shichao Cao^*, Yonggang Dong, Xiaoying Liu

Energy Engineering, Vol., , DOI:10.32604/ee.2023.043004

Abstract The synchronous virtual machine uses inverter power to imitate the performance of the conventional synchronous machine. It also has the same inertia, damping, frequency, voltage regulation, and other external performance as the generator. It is the key technology to realize new energy grid connections’ stable and reliable operation. This project studies a dynamic simulation model of an extensive new energy power system based on the virtual synchronous motor. A new energy storage method is proposed. The mathematical energy storage model is established by combining the fixed rotor model of a synchronous virtual machine with the charge-discharge power, state of charge,… More >

Abhishek Singhal^*, Devendra Kumar Sharma

Computer Systems Science and Engineering, Vol., , DOI:10.32604/csse.2023.046730

Abstract This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions, employing a deep learning classification algorithm for speech signal analysis. In this study, speech samples are categorized for both training and testing purposes based on their geographical origin. Category 1 comprises speech samples from speakers outside of India, whereas Category 2 comprises live-recorded speech samples from Indian speakers. Testing speech samples are likewise classified into four distinct sets, taking into consideration both geographical origin and the language spoken by the speakers. Significantly, the results indicate a noticeable difference in gender identification accuracy among… More >

Wuyang Fan, Shisheng Zhong^*

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.046951

Abstract The dynamic balance assessment during the assembly of the coordinator gyroscope significantly impacts the guidance accuracy of precision-guided equipment. In dynamic balance debugging, reliance on rudimentary counterweight empirical formulas persists, resulting in suboptimal debugging accuracy and an increased repetition rate. To mitigate this challenge, we present a multi-head residual graph attention network (ResGAT) model, designed to predict dynamic balance counterweights with high precision. In this research, we employ graph neural networks for interaction feature extraction from assembly graph data. An SDAE-GPC model is designed for the assembly condition classification to derive graph data inputs for the ResGAT regression model, which… More >

Yan Wang^*, Siwen Li, Na Wei

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.046454

Abstract A novel approach for analyzing coupled vibrations between vehicles and bridges is presented, taking into account spatiotemporal effects and mechanical phenomena resulting from vehicle braking. Efficient modeling and solution of bridge vibrations induced by vehicle deceleration are realized using this method. The method’s validity and reliability are substantiated through numerical examples. A simply supported beam bridge with a corrugated steel web is taken as an example and the effects of parameters such as the initial vehicle speed, braking acceleration, braking location, and road surface roughness on the mid-span displacement and impact factor of the bridge are analyzed. The results show… More >

Oulfa Harrat^1,*, Yazid Hadidane¹, S. M. Anas^2,*, Nadhim Hamah Sor^3,4, Ahmed Farouk Deifalla⁵, Paul O. Awoyera⁶, Nadia Gouider¹

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.044950

Abstract Given their numerous functional and architectural benefits, such as improved bearing capacity and increased resistance to elastic instability modes, cold-formed steel (CFS) built-up sections have become increasingly developed and used in recent years, particularly in the construction industry. This paper presents an analytical and numerical study of assembled CFS two single channel-shaped columns with different slenderness and configurations (back-to-back, face-to-face, and box). These columns were joined by double-row rivets for the back-to-back and box configurations, whereas they were welded together for the face-to-face design. The built-up columns were filled with ordinary concrete of good strength. Finite element models were applied,… More > Graphic Abstract

Xianfeng Cao¹, Meihua Yao², Yahui Zhang^3,*, Xiaofeng Hu⁴, Chuanxun Wu³

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.030773

Abstract As the take-off of China’s macro economy, as well as the rapid development of infrastructure construction, real estate industry, and highway logistics transportation industry, the demand for heavy vehicles is increasing rapidly, the competition is becoming increasingly fierce, and the digital transformation of the production line is imminent. As one of the most important components of heavy vehicles, the transmission front and middle case assembly lines have a high degree of automation, which can be used as a pilot for the digital transformation of production. To ensure the visualization of digital twins (DT), consistent control logic, and real-time data interaction,… More > Graphic Abstract

Saima Rashid^1,2,*, Fahd Jarad^3,4

CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.028773

Abstract Because of the features involved with their varied kernels, differential operators relying on convolution formulations have been acknowledged as effective mathematical resources for modeling real-world issues. In this paper, we constructed a stochastic fractional framework of measles spreading mechanisms with dual medication immunization considering the exponential decay and Mittag-Leffler kernels. In this approach, the overall population was separated into five cohorts. Furthermore, the descriptive behavior of the system was investigated, including prerequisites for the positivity of solutions, invariant domain of the solution, presence and stability of equilibrium points, and sensitivity analysis. We included a stochastic element in every cohort and… More >

Yanjun Yu¹, Lei Yu^1,*, Huiqi Wang², Haodong Zheng¹, Yi Deng¹

CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2024.047641

Abstract Bone age assessment (BAA) helps doctors determine how a child’s bones grow and develop in clinical medicine. Traditional BAA methods rely on clinician expertise, leading to time-consuming predictions and inaccurate results. Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations. This operation is costly and subjective. To address these problems, we propose a multi-scale attentional densely connected network (MSADCN) in this paper. MSADCN constructs a multi-scale dense connectivity mechanism, which can avoid overfitting, obtain the local features effectively and prevent gradient vanishing even in limited training data. First, MSADCN designs… More >