Tianfeng Li^*, Yonghua Fan

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-1, 2025, DOI:10.32604/icces.2025.011408

Abstract A fixed-time anti-saturation backstepping guidance law (FTABGL) is designed for interceptor under acceleration input constraints. Firstly, an adaptive fixed-time anti-saturation compensator (AFAC) is proposed to ensure the stability of saturated system and drive it to faster leave the saturated region. Compared with conventional anti-saturation compensators, the auxiliary variable of AFAC is able to realize faster response speed and higher convergent precision when saturation disappears, which avoids the impact on convergent characteristics of original tracking error. In addition, the novel adaptive law in AFAC can further shorten the duration of saturation and improve the convergent speed… More >

Tianyuan Qi¹, Junpeng Zhao^1,2,*, Chunjie Wang^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 127-151, 2025, DOI:10.32604/cmes.2025.070769 - 30 October 2025

Abstract A major bottleneck in large-scale eigenfrequency topology optimization is the repeated solution of the generalized eigenvalue problem. This work presents an efficient graphics processing unit (GPU) solver for three-dimensional (3D) topology optimization that maximizes the fundamental eigenfrequency. The Successive Iteration of Analysis and Design (SIAD) framework is employed to avoid solving a full eigenproblem at every iteration. The sequential approximation of the eigenpairs is solved by the GPU-accelerated multigrid-preconditioned conjugate gradient (MGPCG) method to efficiently improve the eigenvectors along with the topological evolution. The cluster-mean approach is adopted to address the non-differentiability issue caused by… More > Graphic Abstract

Yingying Guo¹, Ziyu Cui², Jibing Shen¹, Pei Li^3,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4519-4550, 2025, DOI:10.32604/cmc.2025.071504 - 23 October 2025

Abstract Accurate simulation of acoustic wave propagation in complex structures is of great importance in engineering design, noise control, and related research areas. Although traditional numerical simulation methods can provide precise results, they often face high computational costs when applied to complex models or problems involving parameter uncertainties, particularly in the presence of multiple coupled parameters or intricate geometries. To address these challenges, this study proposes an efficient algorithm for simulating the acoustic field of structures with adhered sound-absorbing materials while accounting for ground reflection effects. The proposed method integrates Catmull-Clark subdivision surfaces with the boundary… More >

Wenda Ma, Qizhi Tang^*, Huang Lei, Longfei Chang, Chen Wang

Structural Durability & Health Monitoring, Vol.19, No.5, pp. 1265-1286, 2025, DOI:10.32604/sdhm.2025.065294 - 05 September 2025

Abstract Lost acceleration response reconstruction is crucial for assessing structural conditions in structural health monitoring (SHM). However, traditional methods struggle to address the reconstruction of acceleration responses with complex features, resulting in a lower reconstruction accuracy. This paper addresses this challenge by leveraging the advanced feature extraction and learning capabilities of fully convolutional networks (FCN) to achieve precise reconstruction of acceleration responses. In the designed network architecture, the incorporation of skip connections preserves low-level details of the network, greatly facilitating the flow of information and improving training efficiency and accuracy. Dropout techniques are employed to reduce… More >

Jianying Li^1,2,*, Donglai Li^1,2, Tiefeng Li^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.3, pp. 445-470, 2025, DOI:10.32604/fdmp.2025.062337 - 01 April 2025

Abstract Hydrodynamic cavitation, as an efficient technique applied in many physical and chemical treatment methods, has been widely used by various industries and in several technological fields. Relevant generators, designed with specific structures and parameters, can produce cavitation effects, thereby enabling effective treatment and reasonable transformation of substances. This paper reviews the design principles, performance, and practical applications associated with different types of cavitation generators, aiming to provide theoretical support for the optimization of these systems. It systematically analyzes the underpinning mechanisms and the various factors influencing the cavitation phenomena, also conducting a comparative analysis of More > Graphic Abstract

Fengju Zhang¹, Kai Zhu^2,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2353-2372, 2025, DOI:10.32604/cmc.2024.058944 - 17 February 2025

Abstract The Internet of Vehicles (IoV) has become an important direction in the field of intelligent transportation, in which vehicle positioning is a crucial part. SLAM (Simultaneous Localization and Mapping) technology plays a crucial role in vehicle localization and navigation. Traditional Simultaneous Localization and Mapping (SLAM) systems are designed for use in static environments, and they can result in poor performance in terms of accuracy and robustness when used in dynamic environments where objects are in constant movement. To address this issue, a new real-time visual SLAM system called MG-SLAM has been developed. Based on ORB-SLAM2,… More >

Xianxian Yin¹, Shimin Yin¹, Yiming Bu², Xiukun Wei^3,*

Structural Durability & Health Monitoring, Vol.18, No.5, pp. 623-640, 2024, DOI:10.32604/sdhm.2024.050195 - 19 July 2024

Abstract As an important component of load transfer, various fatigue damages occur in the track as the rail service life and train traffic increase gradually, such as rail corrugation, rail joint damage, uneven thermite welds, rail squats fastener defects, etc. Real-time recognition of track defects plays a vital role in ensuring the safe and stable operation of rail transit. In this paper, an intelligent and innovative method is proposed to detect the track defects by using axle-box vibration acceleration and deep learning network, and the coexistence of the above-mentioned typical track defects in the track system… More >

Zhenjiang Dong¹, Xin Ge¹, Yuehua Huang¹, Jiankuo Dong¹, Jiang Xu^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4021-4044, 2024, DOI:10.32604/cmc.2024.049233 - 20 June 2024

Abstract This paper presents a comprehensive exploration into the integration of Internet of Things (IoT), big data analysis, cloud computing, and Artificial Intelligence (AI), which has led to an unprecedented era of connectivity. We delve into the emerging trend of machine learning on embedded devices, enabling tasks in resource-limited environments. However, the widespread adoption of machine learning raises significant privacy concerns, necessitating the development of privacy-preserving techniques. One such technique, secure multi-party computation (MPC), allows collaborative computations without exposing private inputs. Despite its potential, complex protocols and communication interactions hinder performance, especially on resource-constrained devices. Efforts… More >

Zhonglu Lin^1,2, Dongfang Liang², Yu Zhang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.3, pp. 1-9, 2023, DOI:10.32604/icces.2023.010442

Abstract Fish schools are capable of simultaneous linear acceleration. To reveal the underlying hydrodynamic mechanism, we numerically investigate how Reynolds number Re = 1000−2000, Strouhal number St = 0.2−0.7 and wavelength λ = 0.5−2 affects the mean net thrust of two side-by-side NACA0012 hydrofoils undulating in anti-phase. In total, 550 cases are simulated using immersed boundary method. The thrust is strengthened by wavelength and Strouhal number, yet only slightly by the Reynolds number. We apply the symbolic regression algorithm to formulate this relationship as a high-level summary. More >

Dongping Tian^1,*, Bingchun Li¹, Jing Liu¹, Chen Liu¹, Ling Yuan¹, Zhongzhi Shi²

Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2783-2807, 2023, DOI:10.32604/iasc.2023.039531 - 11 September 2023

Abstract Particle swarm optimization (PSO) is a stochastic computation technique that has become an increasingly important branch of swarm intelligence optimization. However, like other evolutionary algorithms, PSO also suffers from premature convergence and entrapment into local optima in dealing with complex multimodal problems. Thus this paper puts forward an adaptive multi-updating strategy based particle swarm optimization (abbreviated as AMS-PSO). To start with, the chaotic sequence is employed to generate high-quality initial particles to accelerate the convergence rate of the AMS-PSO. Subsequently, according to the current iteration, different update schemes are used to regulate the particle search… More >