Chao Zhang¹, Shang-Xi Lai¹, Hua-Ping Wang^1,2,*

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 25-54, 2025, DOI:10.32604/sdhm.2024.053662 - 15 November 2024

Abstract Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure. Therefore, it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring (SHM) system, so as to provide a scientific basis for structural damage identification and dynamic model modification. In view of this, this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters. The paper primarily introduces data-driven modal parameter recognition methods… More >

Daixuan Zhou¹, Yujin Liu¹, Xu Wang², Fuxing Wang¹, Yan Jia^2,*

Energy Engineering, Vol.121, No.12, pp. 3573-3616, 2024, DOI:10.32604/ee.2024.055853 - 22 November 2024

Abstract With the increasing proportion of renewable energy in China’s energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. More > Graphic Abstract

Ziran Li¹, Weihao Zhang², Lei Qi^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.013344

Abstract In the future, the wide speed and altitude range aviation engine will have features such as "wide range of high-bypass-ratio adjustment" and "wide range of high-pressure-ratio adjustment". Therefore, its turbine will work in a very wide range of operating conditions, with a large flow regulation range. Under conditions of high-rate flow regulation, existing flow control technologies can significantly reduce turbine efficiency. To support the performance and technical specifications of future engines, their low-pressure turbines need to maintain high operational efficiency within a flow regulation range and power output range that exceed those of current aircraft engines.
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Jie Wang^1,*, Jingyu Gu¹, Shuai Li¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012184

Abstract The interaction between the particle and the bubble under the ultrasonic wave excitation plays a pivotal role in various applications such as targeted therapy, ultrasonic cleaning, ultrasonography, and microbubble motors. When the particle is in close proximity or even attached to the bubble, a strong fluid-structure interaction occurs, significantly influencing the particle propulsion. The attachment of the bubble to the particle results in distinct bubble pulsation patterns and particle acceleration mechanisms from the non-contact state. Thus, we propose a fluid-structure interaction model based on the boundary integral method (BIM) to comprehensively consider the distance between More >

Ruiqi Pan¹, Wei Xiong², Liang Hao^1,*, Yan Li^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011651

Abstract As metal additive manufacturing (MAM) becomes more widely used in engineering, an increasing number of novel lattice structures are being developed. However, most recently developed lattice structures do not match the requirement of MAM efficiently. Based on the Design for Additive Manufacturing (DfAM), comparing the mainstream implicit and explicit modelling methods, it is proposed to introduce a Subdivisional (Sub-D) modelling method to model lattice structures with better modelling versatility, 3D printability, and mechanical properties. To this end, a novel negative Poisson's ratio (NPR) structure is developed as an example to demonstrate the efficient and wide… More >

Xionglve Li, Chengyu Wang, Yifan Yang, Changsheng Hou, Bingnan Hou, Zhiping Cai^*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 53-78, 2024, DOI:10.32604/cmc.2024.055186 - 15 October 2024

Abstract The global Internet is a complex network of interconnected autonomous systems (ASes). Understanding Internet inter-domain path information is crucial for understanding, managing, and improving the Internet. The path information can also help protect user privacy and security. However, due to the complicated and heterogeneous structure of the Internet, path information is not publicly available. Obtaining path information is challenging due to the limited measurement probes and collectors. Therefore, inferring Internet inter-domain paths from the limited data is a supplementary approach to measure Internet inter-domain paths. The purpose of this survey is to provide an overview… More >

Xuefeng Zhu^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012543

Abstract Isogeometric Analysis (IGA) was introduced by Thomas Hughes et al. with the aim of integrating CAD and FEA. IGA methods can be categorized into two groups: Conforming IGA, such as T-spline based IGA, and non-conforming IGA, such as immersed or embedded IGA. Embedded or immersed IGA methods do not require the construction of analysis-aware geometry, unlike conforming IGA methods such as T-spline based IGA. However, the Galerkin method does not directly apply to these methods, making it challenging for immersed IGA methods to impose strong Dirichlet boundary conditions directly. Nitsche's method is a popular approach… More >

Oluwaseun Peter Ige^1,2, Keng Hoon Gan^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1847-1865, 2024, DOI:10.32604/cmes.2024.053373 - 27 September 2024

Abstract Feature selection is a crucial technique in text classification for improving the efficiency and effectiveness of classifiers or machine learning techniques by reducing the dataset’s dimensionality. This involves eliminating irrelevant, redundant, and noisy features to streamline the classification process. Various methods, from single feature selection techniques to ensemble filter-wrapper methods, have been used in the literature. Metaheuristic algorithms have become popular due to their ability to handle optimization complexity and the continuous influx of text documents. Feature selection is inherently multi-objective, balancing the enhancement of feature relevance, accuracy, and the reduction of redundant features. This… More >

Xianghua Liu¹, Hai Song¹, Lu Zhao¹, Yan Zheng¹, Neng Yang², Dongling Qiu^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2377-2392, 2024, DOI:10.32604/fdmp.2024.051418 - 23 September 2024

Abstract The segmented water control technology for bottom water reservoirs can effectively delay the entry of bottom water and adjust the production profile. To clarify the impact of different methods on horizontal well production with different reservoir conditions and to provide theoretical support for the scientific selection of methods for bottom water reservoirs, a numerical simulation method is presented in this study, which is able to deal with wellbore reservoir coupling under screen tube, perforation, and ICD (Inflow Control Device) completion. Assuming the geological characteristics of the bottom-water conglomerate reservoir in the Triassic Formation of the… More >

Mahmoud E. Farfoura^1,*, Ahmad Alkhatib¹, Deema Mohammed Alsekait^2,*, Mohammad Alshinwan^3,7, Sahar A. El-Rahman⁴, Didi Rosiyadi⁵, Diaa Salama AbdElminaam^6,7

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4833-4857, 2024, DOI:10.32604/cmc.2024.054849 - 12 September 2024

Abstract The article describes a new method for malware classification, based on a Machine Learning (ML) model architecture specifically designed for malware detection, enabling real-time and accurate malware identification. Using an innovative feature dimensionality reduction technique called the Interpolation-based Feature Dimensionality Reduction Technique (IFDRT), the authors have significantly reduced the feature space while retaining critical information necessary for malware classification. This technique optimizes the model’s performance and reduces computational requirements. The proposed method is demonstrated by applying it to the BODMAS malware dataset, which contains 57,293 malware samples and 77,142 benign samples, each with a 2381-feature… More >