Xiaoguang Wang^1,2, Dehua Liu^1,2,*, Zhenping Liu³, Zhen Luo³, Guihua Yang^1,2, Zongfa Li^1,2, Lijuan Huang^1,2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.7, 2026, DOI:10.32604/fdmp.2026.079864 - 31 July 2026

Abstract Low-permeability conglomerate reservoirs are characterized by complex pore structures and poor sweep efficiency, making the optimization of carbon dioxide-water alternating gas (CO₂-WAG) injection critical for enhanced oil recovery. To evaluate the displacement performance of CO₂-WAG and determine the lower limit of effectively swept pore throats, this study presents long-core flooding experiments conducted on cores from the KS Formation of the B Oilfield in the Junggar Basin under reservoir conditions (20.1 MPa and 58°C). Continuous CO₂ flooding and CO₂-WAG schemes with varying cycle numbers and gas-water ratios (GWRs) were systematically compared. In situ online nuclear magnetic resonance (NMR) monitoring… More >

Lijun Yang¹, Qiuwei Yang^2,*

CMC-Computers, Materials & Continua, Vol.88, No.3, 2026, DOI:10.32604/cmc.2026.083976 - 23 July 2026

Abstract This study proposes a Multi-Stage Sparrow Search Algorithm (MS-SSA) for precise structural damage identification. Initially, the structural static displacement sensitivity formulation is derived via the Sherman-Morrison-Woodbury formula, and an objective function is constructed by integrating the sensitivity equations with the L2-norm penalty. Subsequently, MS-SSA is implemented to sequentially achieve preliminary damage localization and accurate quantification. In the localization phase, a constrained narrow-bound search space is predefined to identify potential damage regions. Leveraging this feedback, the sensitivity equations are condensed, and the search boundaries are adaptively refined for the quantification phase, where SSA is reapplied to… More >

Dejun Wu^1,2,*, Chunlei Yu¹, Xuan Lu¹, Deshuo Tao¹, Xiaoning Li¹, Hao Song³

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.6, 2026, DOI:10.32604/fdmp.2026.084484 - 30 June 2026

Abstract To address the short peak-production period and limited incremental recovery commonly encountered during chemical flooding of high water-cut reservoirs, this study investigates the dynamic evolution of displacement fronts and their controlling factors through laboratory experiments and numerical simulation. Two-dimensional plate flooding experiments were first conducted to characterize the evolution of the oil bank in homogeneous and heterogeneous reservoirs, revealing a four-stage process of formation, enrichment, mobilization, and residual depletion. Based on water-cut behavior, the flooding process was further classified into early-response, peak-response, and late-response stages. A three-dimensional heterogeneous reservoir model was subsequently developed to quantify… More >

Gebrail Bekdaş^*, Sinan Melih Nigdeli, Omer Elselumi

Structural Durability & Health Monitoring, Vol.20, No.4, 2026, DOI:10.32604/sdhm.2026.078870 - 30 June 2026

Abstract This study presents a comparison study between a Tuned Mass Damper (TMD) and Multiple Tuned Mass Dampers (MTMD). The main novelty of this study lies in the unified optimization-based comparison of optimized and fixed-mass MTMD configurations, highlighting the trade-off between seismic performance and practical applicability compared to a single large TMD installed at the top of the building. The Jaya algorithm is used to determine the optimum solution of mass damper parameters. Three cases are examined. The first case is the building with the TMD system. The second case is the building with the MTMD… More >

Lishuai Zhu¹, Guangcai Zhang^1,*, Qun Xie^1,*, Zhen Peng², Li Ai³, Ruijun Liang¹, Taochun Yang¹

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.074620 - 31 March 2026

Abstract Structural displacement monitoring faces significant challenges under complex environmental conditions due to the loss or degradation of target features, making it difficult for traditional methods to ensure high accuracy and robustness. Therefore, this study proposes a structural displacement identification and quantification method that integrates YOLOv8n with an improved edge-orientation gradient-based template matching algorithm. By combining deep learning techniques with traditional template matching methods, the accuracy and robustness of monitoring are enhanced under adverse conditions such as noise and extremely low illumination. Specifically, in the edge-orientation gradient matching stage, the Canny-Devernay sub-pixel edge detection technique and… More >

Jing Li¹, Bo Ning^1,*, Bo Li², Xuemei Jin¹, Dezhi Qiu¹, Fenlan Ou¹

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.074335 - 06 February 2026

Abstract As a controllable power generation method requiring no energy storage, Ocean Thermal Energy Conversion (OTEC) technology demonstrates characteristics of abundant reserves, low pollution, and round-the-clock stable operation. The free-standing cold-water pipe (CWP) in the system withstands various complex loads during operation, posing potential failure risks. To reveal the deformation and stress mechanisms of OTEC CWPs, this study first analyzes wave particle velocity and acceleration to determine wave loads at different water depths. Based on the Euler-Bernoulli beam model, a quasi-static load calculation model for OTEC CWPs was established. The governing equations were discretized using the… More >

Huixin Wei, Baopeng Liao^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012367

Abstract Friction behavior at soft-hard material interfaces plays a pivotal role in applications spanning biomedical devices, robotics, and tactile systems. While theoretical frameworks and experimental characterization methods have advanced, it is still difficult to unravel interfacial mechanisms. In this study, a theoretical model is firstly developed to predict static-to-sliding transitions by analyzing geometric evolution and stick-slip dynamics at soft material interfaces. The model quantitatively determines the threshold force for slip initiation, offering predictive insights into The sliding behavior of the interface. Second, an innovative tribometry platform is introduced, combining synchronized optical visualization, mechanical loading, and automated More >

Tianen Liu^1,2, Kun Dai^1,2, Shiju Ren^1,2, Chuanxiang Zhang^1,2, Xiaoling Tang^3,*, Jinghong Hu^3,*, Yidong Cai³, Jun Lu³

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.12, pp. 2981-2995, 2025, DOI:10.32604/fdmp.2025.073859 - 31 December 2025

Abstract Many mature onshore oilfields have entered a high-water-cut stage, with reservoir recovery approaching economic limits. Converting these depleted or nearly depleted reservoirs into underground gas storage (UGS) facilities offers an efficient way to leverage their substantial storage potential. During cyclic gas injection and withdrawal, however, the reservoir experiences complex three-phase flow and repeated stress fluctuations, which can induce rock fatigue, inelastic deformation, and ultimately sand production. This study uses controlled physical experiments to simulate sand production in reservoir rocks subjected to alternating gas injection and production under three-phase conditions. After preparing oil-water-saturated cores through waterflooding,… More > Graphic Abstract

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 >