Jiao Chen¹, Xiao Wang^1,*, Zhiqin He¹, Yi Chen², Chao Ma¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5423-5450, 2025, DOI:10.32604/cmc.2025.067952 - 23 October 2025

Abstract This research proposes an innovative solution to the inherent challenges faced by landslide displacement prediction models based on data-driven methods, such as the need for extensive historical datasets for training, the reliance on manual feature selection, and the difficulty in effectively utilizing landslide historical data. We have developed a dual-channel deep learning prediction model that integrates multimodal decomposition and an attention mechanism to overcome these challenges and improve prediction performance. The proposed methodology follows a three-stage framework: (1) Empirical Mode Decomposition (EMD) effectively segregates cumulative displacement and feature factors; (2) We have developed a Double… More >

Mohammed Albekairi¹, Radhia Khdhir^2,*, Amina Magdich³, Somia Asklany^4,*, Ghulam Abbas⁵, Amr Yousef ^6,7

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3607-3644, 2025, DOI:10.32604/cmes.2025.069681 - 30 September 2025

Abstract License plate recognition in haze-affected images is challenging due to feature distortions such as blurring and elongation, which lead to pixel displacements. This article introduces a Displacement Region Recognition Method (DR2M) to address such a problem. This method operates on displaced features compared to the training input observed throughout definite time frames. The technique focuses on detecting features that remain relatively stable under haze, using a frame-based analysis to isolate edges minimally affected by visual noise. The edge detection failures are identified using a bilateral neural network through displaced feature training. The training converges bilaterally… More >

Xiaolin Wang, Richeng Liu^*, Kai Qiu, Zhongzhong Liu, Shisen Zhao, Shuchen Li

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 289-307, 2025, DOI:10.32604/cmes.2025.066716 - 31 July 2025

Abstract Gas-liquid two-phase flow in fractal porous media is pivotal for engineering applications, yet it remains challenging to be accurately characterized due to complex microstructure-flow interactions. This study establishes a pore-scale numerical framework integrating Monte Carlo-generated fractal porous media with Volume of Fluid (VOF) simulations to unravel the coupling among pore distribution characterized by fractal dimension (D_f), flow dynamics, and displacement efficiency. A pore-scale model based on the computed tomography (CT) microstructure of Berea sandstone is established, and the simulation results are compared with experimental data. Good agreement is found in phase distribution, breakthrough behavior, and flow… More >

Qiaowei Ye¹, Ying Peng², Zihang Wang², Chao Deng², Xiang Xu², Yuan Ren^2,*

Structural Durability & Health Monitoring, Vol.19, No.4, pp. 851-868, 2025, DOI:10.32604/sdhm.2025.060906 - 30 June 2025

Abstract The girder end restraint devices such as bearings and dampers on long span suspension bridge will deteriorate over time. However, it is difficult to achieve the quantitative assessment of the performance of the restraint device through existing detection methods in actual inspections, making it difficult to obtain the impact of changes in the performance of the restraint device on the bridge structure. In this paper, a random vehicle load model is firstly established based on the WIM data of Jiangyin Bridge, and the displacement of girder end under the actual traffic flow is simulated by… More >

Baoyu Chen^1,2, Meina Li³, Jicheng Zhang¹, Wenguo Ma^1,*, Yueqi Wang¹, Tianchen Pan¹, Xuan Liu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.6, pp. 1459-1471, 2025, DOI:10.32604/fdmp.2025.060255 - 30 June 2025

Abstract The relative permeability of oil and water is a key factor in assessing the production performance of a reservoir. This study analyzed the impact of injecting a viscosity reducer solution into low-viscosity crude oil to enhance fluid flow within a low-permeability reservoir. At 72°C, the oil-water dispersion solution achieved a viscosity reduction rate (f) of 92.42%, formulated with a viscosity reducer agent concentration (C_VR) of 0.1% and an oil-water ratio of 5:5. The interfacial tension between the viscosity reducer solution and the crude oil remained stable at approximately 1.0 mN/m across different concentrations, with the minimum More >

I Made Putrama^1,2,*, Péter Martinek¹

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5699-5727, 2025, DOI:10.32604/cmc.2025.063465 - 19 May 2025

Abstract Imbalanced multiclass datasets pose challenges for machine learning algorithms. They often contain minority classes that are important for accurate predictions. However, when the data is sparsely distributed and overlaps with data points from other classes, it introduces noise. As a result, existing resampling methods may fail to preserve the original data patterns, further disrupting data quality and reducing model performance. This paper introduces Neighbor Displacement-based Enhanced Synthetic Oversampling (NDESO), a hybrid method that integrates a data displacement strategy with a resampling technique to achieve data balance. It begins by computing the average distance of noisy… 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 >

Yao Jin¹, Yuan Ren¹, Chong-Yuan Guo², Chong Li³, Zhao-Yuan Guo^1,4, Xiang Xu^1,*

Structural Durability & Health Monitoring, Vol.19, No.2, pp. 307-325, 2025, DOI:10.32604/sdhm.2024.055265 - 15 January 2025

Abstract To improve the accuracy of thermal response estimation and overcome the limitations of the linear regression model and Artificial Neural Network (ANN) model, this study introduces a deep learning estimation method specifically based on the Long Short-Term Memory (LSTM) network, to predict temperature-induced girder end displacements of the Dasha Waterway Bridge, a suspension bridge in China. First, to enhance data quality and select target sensors, preprocessing based on the sigma rule and nearest neighbor interpolation is applied to the raw data. Furthermore, to eliminate the high-frequency components from the displacement signal, the wavelet transform is… More >

Zhao-Jun Zhang¹, Jing-Shui Zhen¹, Bo-Cheng Li¹, De-Cheng Cai¹, Yang-Yang Du¹, Wen-Wei Wang^2,*

Structural Durability & Health Monitoring, Vol.19, No.2, pp. 327-346, 2025, DOI:10.32604/sdhm.2024.054671 - 15 January 2025

Abstract To mitigate the challenges in managing the damage level of reinforced concrete (RC) pier columns subjected to cyclic reverse loading, this study conducted a series of cyclic reverse tests on RC pier columns. By analyzing the outcomes of destructive testing on various specimens and fine-tuning the results with the aid of the IMK (Ibarra Medina Krawinkler) recovery model, the energy dissipation capacity coefficient of the pier columns were able to be determined. Furthermore, utilizing the calibrated damage model parameters, the damage index for each specimen were calculated. Based on the obtained damage levels, three distinct More >

Yangjian Si^1,2, Yujie Wei^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011974

Abstract Edge cracking represents one of the most prominent damage modes in engineering practice and hence receives immense attention from academic societies. When branched cracks or multiple cracks are present at the edge, their propagation may be affected by the interaction between the cracks. In this talk, we may cover the elasticity of a cracked half-plane with two typical scenarios: a double branched crack with two rays emanating from one point on the edge and two edge cracks spaced by a certain distance (Kalthoff–Winkler cracks). By adopting the combination of the Schwartz-Christoffel conformal mapping and the… More >