Bo Su¹, Mwansa Chambalile¹, Shihao He¹, Wan Sun², Enyuan Zhang¹, Tong Guo³, Jianming Hao⁴, Md. Mahbub Alam^5,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.076681 - 06 February 2026

Abstract Predicting the precise impacts of climate change on extreme winds remains challenging, yet strong storms are widely expected to occur more frequently in a warming climate. Wind barriers are commonly used on bridges to reduce aerodynamic loads on trains through blocking effects. This study develops a novel wind barrier based on Tesla valves, which not only blocks incoming flow but also dissipates mechanical energy through fluid collision. To demonstrate this energy-dissipation capability, a Tesla plate is placed in a circular duct to examine its influence on pressure drop. Experimental tests and numerical simulations comparing a… More >

Xianke He¹, Yuansheng Li¹, Hengjie Liao¹, Zhehao Jiang¹, Meixue Shi¹, Zhe Hu^2,3, Yaowei Huang^2,3, Keliu Wu^2,3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.074990 - 06 February 2026

Abstract Weak water-drive offshore reservoirs with complex pore architecture and strong permeability heterogeneity present major challenges, including rapid depletion of formation energy, low waterflood efficiency, and significant lateral and vertical variability in crude oil properties, all of which contribute to limited recovery. To support more effective field development, alternative strategies and a deeper understanding of pore-scale flow behavior are urgently needed. In this work, CT imaging and digital image processing were used to construct a digital rock model representative of the target reservoir. A pore-scale flow model was then developed, and the Volume of Fluid (VOF)… More > Graphic Abstract

Zhirong Jin^1,*, Xiaorui Hou¹, Yanrong Ge¹, Tiankui Guo², Ming Chen², Shuyi Li², Tianyu Niu²

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070750 - 27 January 2026

Abstract Hydraulic fracturing serves as a critical technology for reservoir stimulation in deep coalbed methane (CBM) development, where the mechanical properties of gangue layers exert a significant control on fracture propagation behavior. To address the unclear mechanisms governing fracture penetration across coal-gangue interfaces, this study employs the Continuum-Discontinuum Element Method (CDEM) to simulate and analyze the vertical propagation of hydraulic fractures initiating within coal seams, based on geomechanical parameters derived from the deep Benxi Formation coal seams in the southeastern Ordos Basin. The investigation systematically examines the influence of geological and operational parameters on cross-interfacial fracture… More >

Abla Guechi¹, Djohra Dekhil², Abdelhak Nouri^2,*

Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076586 - 26 January 2026

Abstract This work uses numerical modeling in SCAPS-1D to examine the efficiency analysis of a solar cell based on SnS. The power conversion efficiency (PCE) is limited to 24.5% because of incomplete photon absorption in the absorber layer (SnS) and carrier recombination. To increase the absorption window, facilitate charge mobility, and suppress bulk recombination at the rear contact, the absorbent film was divided up into three sublayers with graded band gaps of 1.1 eV, 1.2 eV, and 1.3 eV. Furthermore, the sublayers’ linear gradient doping improved charge collection while simultaneously lowering recombination at the interface. A… More >

Juhwan Kim¹, Gwanghyun Jo², Dongsik Jo^1,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072664 - 12 January 2026

Abstract In recent years, three-dimensional reconstruction technologies that employ multiple cameras have continued to evolve significantly, enabling remote collaboration among users in extended Reality (XR) environments. In addition, methods for deploying multiple cameras for motion capture of users (e.g., performers) are widely used in computer graphics. As the need to minimize and optimize the number of cameras grows to reduce costs, various technologies and research approaches focused on Optimal Camera Placement (OCP) are continually being proposed. However, as most existing studies assume homogeneous camera setups, there is a growing demand for studies on heterogeneous camera setups.… More >

Xun Chen¹, Jinbao Lin^1,2,*, Zai Wang¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072495 - 12 January 2026

Abstract This work investigates the effects of deformation mechanisms on the mechanical properties and anisotropy of rolled AZ31B magnesium alloy under uniaxial tension, combining experimental characterization with Visco-Plastic Self Consistent (VPSC) modeling. The research focuses particularly on anisotropic mechanical responses along transverse direction (TD) and rolling direction (RD). Experimental measurements and computational simulations consistently demonstrate that prismatic <a> slip activation significantly reduces the strain hardening rate during the initial stage of tensile deformation. By suppressing the activation of specific deformation mechanisms along RD and TD, the tensile mechanical behavior of the magnesium alloy was further investigated. More >

Tahir Mahmood^1,*, Muhammad Waseem Ashraf^1,*, Shahzadi Tayyaba², Muhammad Munir³, Babiker M. A. Abdel-Banat³, Hassan Ali Dinar³

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072436 - 12 January 2026

Abstract Artificial intelligence (AI) based models have been used to predict the structural, optical, mechanical, and electrochemical properties of zinc oxide/graphene oxide nanocomposites. Machine learning (ML) models such as Artificial Neural Networks (ANN), Support Vector Regression (SVR), Multilayer Perceptron (MLP), and hybrid, along with fuzzy logic tools, were applied to predict the different properties like wavelength at maximum intensity (444 nm), crystallite size (17.50 nm), and optical bandgap (2.85 eV). While some other properties, such as energy density, power density, and charge transfer resistance, were also predicted with the help of datasets of 1000 (80:20). In… More >

Jinfeng Ji¹, Geunseok Yang^2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071733 - 12 January 2026

Abstract Automated Program Repair (APR) techniques have shown significant potential in mitigating the cost and complexity associated with debugging by automatically generating corrective patches for software defects. Despite considerable progress in APR methodologies, existing approaches frequently lack contextual awareness of runtime behaviors and structural intricacies inherent in buggy source code. In this paper, we propose a novel APR approach that integrates attention mechanisms within an autoencoder-based framework, explicitly utilizing structural code affinity and execution context correlation derived from stack trace analysis. Our approach begins with an innovative preprocessing pipeline, where code segments and stack traces are… More >

Karim Boudjebbour^1,2, Abdelkader Belkhir¹, Hamza Kheddar^2,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.071532 - 12 January 2026

Abstract Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties. Although several community detection methods have been proposed, many are unsuitable for social networks due to significant limitations. Specifically, most approaches depend mainly on user–user structural links while overlooking service-centric, semantic, and multi-attribute drivers of community formation, and they also lack flexible filtering mechanisms for large-scale, service-oriented settings. Our proposed approach, called community discovery-based service (CDBS), leverages user profiles and their interactions with consulted web services. The method introduces a novel similarity measure, global similarity interaction profile (GSIP), which… More >

Supriya Wadekar^1,*, Shailendra Mittal¹, Ganesh Wakte², Rajshree Shinde²

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.071761 - 27 December 2025

Abstract Rapid evolutions of the Internet of Electric Vehicles (IoEVs) are reshaping and modernizing transport systems, yet challenges remain in energy efficiency, better battery aging, and grid stability. Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand, thus increasing energy costs and battery aging. This study proposes a smart charging station with an AI-powered Battery Management System (BMS), developed and simulated in MATLAB/Simulink, to increase optimality in energy flow, battery health, and impractical scheduling within the IoEV environment. The system operates through… More >