Thi Kim Chi Duong¹, Bich-Ngoc. Mach², Hoa-Cuc. Nguyen², Thi Nhu Quynh Trinh², Thanh Q. Nguyen^3,4,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070185 - 08 January 2026

Abstract This study explores theoretical insights and experimental results on monitoring load-carrying capacity degradation in bridge spans through frequency analysis. Experiments were conducted on real bridge structures, including the Binh Thuan Bridge, focusing on analyzing the power spectral density (PSD) of vibration signals under random traffic loads. Detailed digital models of various bridge spans with different structural designs and construction periods were developed to ensure diversity. The study utilized PSD to analyze the vibration signals from the bridge spans under various loading conditions, identifying the vibration frequencies and the corresponding response regions. The research correlated the… More >

D. A. Adu-Boadu^a, M. Paal^a, M. B. Mensah^b, I. Nkrumah^a,*, R. Y. Tamakloe^a, F. K. Ampong^a, R. K. Nkum^a, F. Boakye^a

Chalcogenide Letters, Vol.22, No.7, pp. 603-614, 2025, DOI:10.15251/CL.2025.227.603

Abstract Cd_1-xPb_xSe (0≤ x ≤ 1) thin films with values of x = 0, 0.2, 0.4, 0.5 and 1, have been deposited by chemical bath technique for photovoltaic application. The deposition temperature, time and pH of the reactive solutions were 80℃, 150 min and 11 respectively. The XRD results confirmed the polycrystalline nature of all the films. It also showed that all the films exist in face centered cubic structures. There were no pure phases of CdSe and PbSe identified in the XRD results of the ternary compounds. The average grain sizes determined for each sample were… More >

Chao Gui^1,2, Wanying Chang³, Yaping Liu^1,*, Leren Tao³, Daoming Shen¹, Mengyi Ge¹

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1621-1637, 2025, DOI:10.32604/fhmt.2025.072268 - 31 October 2025

Abstract Freeze-drying of structurally heterogeneous biomaterials such as porcine aorta presents considerable modeling challenges due to their inherent multilayer composition and moving sublimation interfaces. Conventional models often overlook structural anisotropy and dynamic boundary progression, while experimental determination of key parameters under cryogenic conditions remains difficult. To address these, this study develops a heat and mass transfer model incorporating a dynamic node strategy for the sublimation interface, which effectively handles continuous computational domain deformation. Additionally, specialized fixed nodes were incorporated to adapt to the multilayer structure and its spatially varying thermophysical properties. A novel non-contact gravimetric system More > Graphic Abstract

Xin Liu¹, Zheng Zhang^2,*, Yu Zhao³, Yi Yang², Zhenning Qiao², Zhibo Xu², Xianzhi Yu²

Energy Engineering, Vol.122, No.11, pp. 4679-4702, 2025, DOI:10.32604/ee.2025.068371 - 27 October 2025

Abstract With the growing demand for offshore energy, deepwater drilling has become a vital technology in petroleum engineering. However, conventional drilling systems often face limitations such as delayed bottomhole pressure response and low control precision, particularly under narrow pressure window and complex formation conditions. To address these challenges, Dual-layer Pipe dual-gradient drilling (DGD) technology has been introduced, utilizing a dual-pipe structure and downhole lift pumps to extend the pressure control range. Despite these advantages, current DGD systems lack fast and precise bottomhole pressure control due to their reliance on indirect flow-based methods. This study proposes a… More >

Tao Chen¹, Xiaoxi Mi^2,*, Shibo Zhou^3,*, Shijun Tong¹, Yunxuan Zhou¹, Yulin Zhang¹, Yuan Yuan⁴

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4571-4586, 2025, DOI:10.32604/cmc.2025.070649 - 23 October 2025

Abstract Magnesium (Mg) alloys face a critical challenge in balancing performance optimization and unintended density increases caused by high-density secondary phases. To address this, machine learning was employed to predict the density and volume of Mg-containing binary phases, aiming to guide lightweight alloy design. Using 211 experimentally observed data points, five machine learning (ML) algorithms—Random Forest (RF), Support Vector Machine (SVM), Artificial Neural Network (ANN), K-Nearest Neighbors (KNN), and Bayesian Ridge (Bayes)—were trained and tested. Quantitative results showed that RF achieved exceptional performance in volume prediction, with a testing coefficient of determination (R²) exceeding 0.96 and More > Graphic Abstract

Alena Vjuginova^1,*, Leonid Leontyev²

Journal of Renewable Materials, Vol.13, No.9, pp. 1819-1828, 2025, DOI:10.32604/jrm.2025.02025-0061 - 22 September 2025

Abstract In this paper, the stability of the results of ultrasonic wood surface modification after long-term storage, including macroscopic properties and microstructure of specimens, was investigated. Specimens of aspen wood (Populus tremula) were processed by the developed ultrasonic method of wood surface modification in three different treatment modes and the surface hardness of the specimens was evaluated after processing and after storing the specimens for more than 5 years since long-term stability is an important factor for the use of ultrasonically modified sawn timber as construction and finishing materials. The obtained results of surface hardness measurements by… More > Graphic Abstract

Buddhini Chaturika Jayasinghe¹, Neel Chaminda Withanage¹, Prabuddh Kumar Mishra^2,*

Revue Internationale de Géomatique, Vol.34, pp. 707-729, 2025, DOI:10.32604/rig.2025.067395 - 12 September 2025

Abstract Road Traffic Accidents (RTAs) pose significant threats to public safety and urban infrastructure. While numerous studies have addressed this issue in other countries, there remains a notable gap in localized RTA research in Sri Lanka. In this context, the present study investigates the spatial and temporal patterns of RTAs in the Matara urban area in 2023, with the goal of supporting evidence-based policy interventions. A suite of GIS-based spatial analysis techniques including hotspot analysis, kernel density estimation, GiZscore mapping, and spatial autocorrelation (Moran’s I = 0.36, p < 0.01) was applied to examine the distribution and… More >

Sidra Jubair¹, Jie Yang^1,2,*, Bilal Ali³, Walid Emam⁴, Yusra Tashkandy⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 511-534, 2025, DOI:10.32604/cmes.2025.066514 - 31 July 2025

Abstract Effectively handling imbalanced datasets remains a fundamental challenge in computational modeling and machine learning, particularly when class overlap significantly deteriorates classification performance. Traditional oversampling methods often generate synthetic samples without considering density variations, leading to redundant or misleading instances that exacerbate class overlap in high-density regions. To address these limitations, we propose Wasserstein Generative Adversarial Network Variational Density Estimation WGAN-VDE, a computationally efficient density-aware adversarial resampling framework that enhances minority class representation while strategically reducing class overlap. The originality of WGAN-VDE lies in its density-aware sample refinement, ensuring that synthetic samples are positioned in underrepresented More >

Chaoliang Wang^1,*, Qi Fu², Zhaohui Li¹

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3707-3729, 2025, DOI:10.32604/cmc.2025.062795 - 03 July 2025

Abstract Cluster-based models have numerous application scenarios in vehicular ad-hoc networks (VANETs) and can greatly help improve the communication performance of VANETs. However, the frequent movement of vehicles can often lead to changes in the network topology, thereby reducing cluster stability in urban scenarios. To address this issue, we propose a clustering model based on the density peak clustering (DPC) method and sparrow search algorithm (SSA), named SDPC. First, the model constructs a fitness function based on the parameters obtained from the DPC method and deploys the SSA for iterative optimization to select cluster heads (CHs). More >

Mustafa Turkyilmazoglu^1,2,*, Abdulaziz Alotaibi³

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.3, pp. 2847-2865, 2025, DOI:10.32604/cmes.2025.068031 - 30 June 2025

Abstract The variable salinity in stored reservoirs connected by a long channel attracts the attention of scientists worldwide, having applications in environmental and geophysical engineering. This study explores the impact of Navier slip conditions on exchange flows within a long channel connecting two large reservoirs of differing salinity. These horizontal density gradients drive the flow. We modify the recent one-dimensional theory, developed to avoid runaway stratification, to account for the presence of uniform slip walls. By adjusting the parameters of the horizontal density gradient based on the slip factor, we resolve analytically various flow regimes ranging… More >