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  • Open Access

    PROCEEDINGS

    Full-Field Deformation Measurement Systems with Advanced Region-Based Image Alignment

    Qinghua Wang*, Yi Zhu

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.012693

    Abstract This study presents a robust and automated image registration framework designed to enhance the precision and efficiency of full-field deformation measurement in experimental mechanics applications. Traditional optical techniques, such as the sampling moiré method, rely on manual alignment processes that introduce significant errors and inefficiencies, particularly when analyzing large datasets or operating under dynamic experimental conditions. Addressing these limitations, the proposed method integrates the Maximally Stable Extremal Regions (MSER) algorithm to automate the alignment of grating images with sub-pixel accuracy. The technique is specifically tailored to handle challenges arising from high-noise environments and complex deformation… More >

  • Open Access

    PROCEEDINGS

    Spatio-Temporal Prediction of Curing-Induced Deformation for Composite Structures Using a Hybrid CNN-LSTM and Finite Element Approach

    Xiangru He1, Ying Deng1, Zefu Li1, Jie Zhi1,2, Yonglin Chen1,2, Weidong Yang1,2,3,*, Yan Li1,2,3,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012395

    Abstract Coordinated control of structural accuracy and mechanical properties is the key to composites manufacturing and the prerequisite for aerospace applications. In particular, accurate and efficient prediction of curing-induced deformation (CID) is of vital importance for fiber reinforced polymer composites quality control. In this study, we explored a novel spatio-temporal prediction model, which incorporates the finite element method with a deep learning framework to efficiently forecast the curing-induced deformation evolution of composite structures. Herein, we developed an integrated convolutional neural network (CNN) and long short-term memory (LSTM) network approach to capture both the space-distributed and time-resolved… More >

  • Open Access

    ARTICLE

    Numerical Simulation of Microscopic Seepage Mechanisms in Gas Reservoir Storage Systems

    Yulong Zhao1, Yang Luo1,*, Yuming Luo2, Yulai Pang2, Ruihan Zhang1, Zihan Zhao3

    FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 3073-3090, 2025, DOI:10.32604/fdmp.2025.070685 - 31 December 2025

    Abstract The development of underground gas storage (UGS) systems is vital for maintaining stability between energy supply and demand. This study explores the dynamic response mechanisms of carbonate reservoirs subjected to intense injection–production cycling during UGS operations. By integrating three-dimensional digital core technology with a coupled poro-mechanical model, we simulate the pore-scale behavior of a representative Huangcaoxia UGS carbonate core. The results demonstrate that fluid–solid coupling effects markedly amplify permeability reduction, far exceeding the influence of porosity variations alone. More significantly, gas production leads to a pronounced decline in permeability driven by rising effective stress, arising More >

  • Open Access

    ARTICLE

    Atmospheric Delay Correction Using GNSS and GACOS Data in InSAR Land Subsidence Monitoring over Banting, Selangor

    Mohd Hakimi Abdul Rahman1, Amir Sharifuddin Ab Latip1,*, Zulkiflee Abd Latif1,2, Siti Balqis Mohd Tun1, Nur Azlina Hariffin1, Mohd Fikri Razali3

    Revue Internationale de Géomatique, Vol.34, pp. 959-972, 2025, DOI:10.32604/rig.2025.071109 - 12 December 2025

    Abstract Atmospheric phase delay, primarily caused by water vapor in the troposphere, is a major source of error in InSAR measurements, especially for land subsidence monitoring. This study integrates GNSS and GACOS data to correct tropospheric delay and enhance InSAR accuracy in Banting, Selangor. A total of 27 Sentinel-1A images, 14 GNSS stations, and 27 corresponding GACOS ZTD maps were used to monitor subsidence between 2023 and 2025. The InSAR data were processed using SNAP, StaMPS, and the TRAIN toolbox, incorporating both GNSS- and GACOS-derived ZTD corrections. The results show that applying atmospheric correction improved the… More >

  • Open Access

    ARTICLE

    Influence Mechanism of Liquid Level on Oil Tank Structures and Damage Risk Prevention Based on Shell Theory

    Si-Kai Wang1, Ti-Cai Wang1, Di-Fei Yi2, Jia Rui3, Peng-Fei Cao4, Hua-Ping Wang1,5,*

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1411-1432, 2025, DOI:10.32604/sdhm.2025.070034 - 17 November 2025

    Abstract As a key storage facility, the structural safety of large oil tanks is directly related to the stable operation of the energy system. The static pressure caused by the change of liquid level is one of the main loads in the service process of storage tanks, which determines the structural deformation and damage risk. To explore the structural deformation properties under the change of liquid levels and provide a theoretical basis for the prevention and control of damage risk, this paper systematically analyzes the mechanical response of storage tanks under the pressures induced by different… More > Graphic Abstract

    Influence Mechanism of Liquid Level on Oil Tank Structures and Damage Risk Prevention Based on Shell Theory

  • Open Access

    REVIEW

    Review of the Mechanical Performance Prediction of Concrete Based on Artificial Neural Networks

    Yidong Xu1, Weijie Zhuge1,2, Jialei Wang1, Xiaopeng Yu3,*, Kan Wu4

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1507-1527, 2025, DOI:10.32604/sdhm.2025.069021 - 17 November 2025

    Abstract The performance of concrete can be affected by many factors, including the material composition, environmental conditions, and construction methods, and it is challenging to predict the performance evolution accurately. The rise of artificial intelligence provides a way to meet the above challenges. This article elaborates on research overview of artificial neural network (ANN) and its prediction for concrete strength, deformation, and durability. The focus is on the comparative analysis of the prediction accuracy for different types of neural networks. Numerous studies have shown that the prediction accuracy of ANN can meet the standards of the More >

  • Open Access

    ARTICLE

    Monitoring the Oil Tank Deformations for Different Operating Conditions

    Roman Shults1,2,*, Natalia Kulichenko3, Andriy Annenkov3, Oleksandr Adamenko3

    Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1433-1456, 2025, DOI:10.32604/sdhm.2025.068099 - 17 November 2025

    Abstract Oil tanks are essential components of the oil industry, facilitating the safe storage and transportation of crude oil. Safely managing oil tanks is a crucial aspect of environmental protection. Oil tanks are often used under extreme operational conditions, including dynamic loads, temperature variations, etc., which may result in unpredictable deformations that can cause severe damage or tank collapses. Therefore, it is essential to establish a monitoring system to prevent and predict potential deformations. Terrestrial laser scanning (TLS) has played a significant role in oil tank monitoring over the past decades. However, the full extent of… More >

  • Open Access

    PROCEEDINGS

    Multi-Scale Investigation on the Nonlinear Deformation of Flax Fibre Reinforced Composites Based on the Evolution of Microstructures

    Qian Li*, Jiali Zhou, Yan Li*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-1, 2025, DOI:10.32604/icces.2025.012234

    Abstract Plant fibres are emerging as sustainable composite reinforcements. Compared to synthetic fibres, the hierarchical and twisted structure of plant fibres may produce microfibril angle (MFA) reorientation and untwisting time-varying behaviors after loading and consequently decide the mechanical response of plant fibre reinforced composites (PFRCs) in macro-scale. Existing theories, assuming homogeneous fibres, cannot accurately describe the multi-scale coupling nonlinear deformations of PFRCs. Based on this, a multi-scale analysis method on the nonlinear tensile responses of flax fibre reinforced composites (FFRCs) was proposed, focusing on the effect of the evolution of MFA in micro-scale and twist angle… More >

  • Open Access

    PROCEEDINGS

    Light Interacted Soft Units for Mechanical Logics

    Nan Yang*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.4, pp. 1-1, 2025, DOI:10.32604/icces.2025.011055

    Abstract Integrating mechanical computing capabilities into robotic materials or systems enhances their intelligence in stimulus-response processes. However, current mechanical computing systems face limitations such as incomplete functionality, inflexible computational rules, challenges in implementing sequential and random logic operations, and lack of reusability. To address these issues, we propose a straightforward design method based on logical expressions to achieve more complex computational tasks. We developed soft B-shaped mechanical metamaterial units and introduced stress inputs through compression. The outputs are represented by light-shielding effects caused by unit deformation. Using this approach, we successfully implemented logic gates and their… More >

  • Open Access

    PROCEEDINGS

    Resolving Self-Stress Artifacts in Twin Boundary Migration: A Stress Correction Scheme for the CPFE-PF Model of HCP Alloys

    Linfeng Jiang1,*, Guisen Liu1, Yao Shen1, Jian Wang2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.011397

    Abstract The plastic deformation of Mg/Ti alloys arises from the synergistic interplay of dislocation slip and deformation twinning. To model these mechanisms, we previously developed a mesoscale CPFE-PF framework that couples crystal plasticity finite element (CPFE) and phase field (PF) methods, enabling predictions of microstructure evolution and mechanical behavior under complex loading. A central challenge, however, lies in accurately capturing deformation twinning—a process critical for accommodating shear and reorienting crystal domains in low-symmetry metals. Twin propagation and thickening occur via twinning dislocations/disconnections at the atomic scale, while at larger scales they are governed by the migration… More >

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