Lijia Li, Shu Liu, Xiaoliang Huang^*, Zhilin Qi

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.073294 - 06 February 2026

Abstract Identifying geohazards such as landslides and methane leakage is crucial during gas extraction from natural gas hydrate (NGH) reservoirs, and understanding reservoir settlement behavior is central to this assessment. Horizontal wells can enlarge the pressure relief zone within the formation, improving single-well productivity, and are therefore considered a promising approach for NGH development. This study examines the settlement response of hydrate-bearing sediments during depressurization using horizontal wells. A fully coupled thermal, hydraulic, mechanical, and chemical (THMC) model with representative reservoir properties (Shenhu region in the South China Sea) is presented accordingly. The simulations show that More >

Md. Ehsanul Haque¹, Md. Nurul Absur², Fahmid Al Farid³, Md Kamrul Siam⁴, Jia Uddin^5,*, Hezerul Abdul Karim^3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071771 - 12 January 2026

Abstract Manual inspection of onba earing casting defects is not realistic and unreliable, particularly in the case of some micro-level anomalies which lead to major defects on a large scale. To address these challenges, we propose BearFusionNet, an attention-based deep learning architecture with multi-stream, which merges both DenseNet201 and MobileNetV2 for feature extraction with a classification head inspired by VGG19. This hybrid design, figuratively beaming from one layer to another, extracts the enormity of representations on different scales, backed by a pre-preprocessing pipeline that brings defect saliency to the fore through contrast adjustment, denoising, and edge… More >

Yingyong Zou^*, Yu Zhang, Long Li, Tao Liu, Xingkui Zhang

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-24, 2026, DOI:10.32604/cmc.2025.068246 - 10 November 2025

Abstract Fault diagnosis of rolling bearings is crucial for ensuring the stable operation of mechanical equipment and production safety in industrial environments. However, due to the nonlinearity and non-stationarity of collected vibration signals, single-modal methods struggle to capture fault features fully. This paper proposes a rolling bearing fault diagnosis method based on multi-modal information fusion. The method first employs the Hippopotamus Optimization Algorithm (HO) to optimize the number of modes in Variational Mode Decomposition (VMD) to achieve optimal modal decomposition performance. It combines Convolutional Neural Networks (CNN) and Gated Recurrent Units (GRU) to extract temporal features… More >

Yingxin Zhang^1,2, Shuai Mo^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.011038

Abstract To accurately describe the dynamic behavior of a gear-rotor-bearing system, it is essential to consider the interplay between thermal effects and dynamics. Therefore, this study develops a real-time coupling model that integrates thermal and dynamic aspects of the gear-rotor-bearing system, which captures the combined effects of various nonlinear factors, including dynamic clearances caused by thermal deformation, thermoelastic coupling stiffness, non-uniform load distribution in bearings, and multi-meshing state of gear. Building on this model, the study introduces a stepwise coupled thermodynamic and dynamic joint solution method, which is used to evaluate the effects of thermal influences More >

Yunjun Lee¹, Sanggyu Cheon², Woo Chul Chung^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 3381-3403, 2025, DOI:10.32604/cmes.2025.073729 - 23 December 2025

Abstract The application of carbon capture systems on ships is technically constrained by limited onboard space and the weight of the conventional absorption tower. The rotating packed bed (RPB) has emerged as a promising alternative due to its small footprint and high mass transfer performance. However, despite its advantages, the structural and vibration stability of RPBs at high rotational speed remains insufficiently studied, and no international design standards currently exist for RPBs. To address this gap, this study performed a comprehensive finite element analysis (FEA) using ANSYS to investigate the structural and dynamic characteristics of an… More >

Qiang Ma^1,2,3,4, Zepeng Li^1,2, Kai Yang^1,2,*, Shaofeng Zhang^1,2, Zhuopei Wei^1,2

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1607-1634, 2025, DOI:10.32604/sdhm.2025.069876 - 17 November 2025

Abstract Effective fault identification is crucial for bearings, which are critical components of mechanical systems and play a pivotal role in ensuring overall safety and operational efficiency. Bearings operate under variable service conditions, and their diagnostic environments are complex and dynamic. In the process of bearing diagnosis, fault datasets are relatively scarce compared with datasets representing normal operating conditions. These challenges frequently cause the practicality of fault detection to decline, the extraction of fault features to be incomplete, and the diagnostic accuracy of many existing models to decrease. In this work, a transfer-learning framework, designated DSCNN-HA-TL,… More >

Youlong Lyu^1,2,*, Ying Chu³, Qingpeng Qiu³, Jie Zhang^1,2, Jutao Guo⁴

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3393-3418, 2025, DOI:10.32604/cmc.2025.068157 - 23 September 2025

Abstract In intelligent manufacturing processes such as aerospace production, computer numerical control (CNC) machine tools require real-time optimization of process parameters to meet precision machining demands. These dynamic operating conditions increase the risk of fatigue damage in CNC machine tool bearings, highlighting the urgent demand for rapid and accurate fault diagnosis methods that can maintain production efficiency and extend equipment uptime. However, varying conditions induce feature distribution shifts, and scarce fault samples limit model generalization. Therefore, this paper proposes a causal-Transformer-based meta-learning (CTML) method for bearing fault diagnosis in CNC machine tools, comprising three core modules:… More >

Mianyue Yang^1,*, Huasheng Sun¹, Weigao Sheng²

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2749-2761, 2025, DOI:10.32604/cmc.2025.068009 - 23 September 2025

Abstract The shear pin of the friction pendulum bearing (FPB) can be made of 40Cr steel. In conceptual design, the optimal cut-off point of the shear pin is predetermined, guiding the design of bridges isolated by FPBs to maximize their isolation performance. Current researches on the shear pins are mainly based on linear elastic models, neglecting their plasticity, damage, and fracture mechanical properties. To accurately predict its cutoff behavior, the elastic-plastic degradation model of 40Cr steel is indeed calibrated. For this purpose, the Ramberg-Osgood model, the Bao-Wierzbicki damage initiation criterion, and the linear damage evolution criterion… More >

Haifeng Zhu^1,*, Zhenyu Chen^1,*, Teng Lu¹, Xiaoqin Zhi²

Frontiers in Heat and Mass Transfer, Vol.23, No.4, pp. 1303-1321, 2025, DOI:10.32604/fhmt.2025.065830 - 29 August 2025

Abstract To meet the demand for miniaturized, compact, high-reliability, and long-life cryocoolers in small satellite platforms, the development of a linear Stirling cryocooler has been undertaken. Computational Fluid Dynamics (CFD) numerical simulation software was used to conduct simulation analyses, verifying the impact of porous media channel layout, eccentricity, viscous resistance coefficient of the porous media, and piston position on the designed aerostatic bearing piston employing self-supplied gas bearing technology. The calculation results indicate that both the aerostatic force and leakage increase synchronously with eccentricity, while the two designed gas lift channel layouts are capable of providing… More >

Ronghua Wang¹, Shibao Sun^1,*, Pengcheng Zhao^1,*, Xianglan Yang², Xingjia Wei¹, Changyang Hu¹

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3519-3539, 2025, DOI:10.32604/cmc.2025.066212 - 03 July 2025

Abstract The capacity to diagnose faults in rolling bearings is of significant practical importance to ensure the normal operation of the equipment. Frequency-domain features can effectively enhance the identification of fault modes. However, existing methods often suffer from insufficient frequency-domain representation in practical applications, which greatly affects diagnostic performance. Therefore, this paper proposes a rolling bearing fault diagnosis method based on a Multi-Scale Fusion Network (MSFN) using the Time-Division Fourier Transform (TDFT). The method constructs multi-scale channels to extract time-domain and frequency-domain features of the signal in parallel. A multi-level, multi-scale filter-based approach is designed to More >