Xiuli Wang¹, Xinshen You^1,2, Wei Xu³, Weibin Zhang², Kehui Zhang¹, Yuanyuan Zhao^4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.081863 - 27 May 2026

Abstract Gas binding fault (GBF) represents a critical operating condition in centrifugal pumps, characterized by severe performance degradation due to gas–liquid interactions within the flow passages. To elucidate the underlying mechanisms, this study employs a coupled Lattice Boltzmann Method and Large Eddy Simulation (LBM–LES) framework to analyze the hydro–mechanical-electrical behavior of a centrifugal pump under varying inlet gas volume fractions (IGVF, β). It is shown that, at low gas content (β ≈ 3%), dispersed bubbles primarily accumulate along the blade suction surface and near the impeller outlet. As β increases to 6%, gas structures migrate toward… More >

Ting He^*, Dong Chen, Liqiong Chen, Kun Huang, Haoyu Jia

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.080326 - 27 May 2026

Abstract The global transition toward sustainable energy systems underscores the strategic importance of methane (CH₄)–carbon dioxide (CO₂) mixtures in cryogenic applications. In Liquefied Natural Gas (LNG) processing and Carbon Capture, Utilization, and Storage (CCUS) networks, such mixtures are routinely exposed to low-temperature environments where phase stability becomes critical. Under these conditions, the unintended formation of solid CO₂ (dry ice) within pipelines poses significant engineering challenges, including flow blockage and potential equipment damage. Ensuring flow assurance therefore demands a rigorous understanding of the coupling between thermodynamic phase transitions and complex hydrodynamic behavior. This paper presents a comprehensive review of More >

Xiang Li^1,2, Jie Zhang^1,2,*, Yuxin Cheng^1,2, Jiaohao Xie^1,2, Zhaoqi Xiong^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.079253 - 27 May 2026

Abstract Current prediction methods for wellbore temperature and pressure in gas storage injection–production wells are commonly based on the simplifying assumption of pure methane, thereby neglecting the multi-component nature of real natural gas and limiting predictive accuracy. To overcome this shortcoming, this study develops a comprehensive model for the coupled temperature and pressure fields in wellbores transporting multi-component natural gas mixtures. The proposed framework explicitly accounts for compositional effects by integrating key thermophysical properties, including density, viscosity, compressibility factor, and Joule–Thomson coefficient, into the governing flow equations, thereby enhancing the fidelity of the ensuing injection and More >

Penghui Zhang^1,2, Nan Lin^2,*, Yang Wang^1,*, Ming Sun², Sixi Zha¹, Zongjie Zhou¹, Chenglin Li³

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.078553 - 27 May 2026

Abstract Erosion-corrosion in refining and chemical plant pipelines remains a persistent integrity concern, particularly in straight sections located downstream of elbows, which are rarely prioritized in inspection programs that typically focus on elbows and tees despite their well-known vulnerability. In these downstream regions, developing flow structures can sustain wall impingement and liquid film formation, leading to progressive material loss that is often underestimated in practice. This work examines a representative industrial pipeline through a combined approach based on computational fluid dynamics (CFD) simulations and controlled experimental validation to resolve the hydrodynamic behavior in the straight pipe… More >

H. Kamlesh¹, E. P. Siva^1,*, P. Bathmanaban², O. D. Makinde³, Dharmendra Tripathi⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.081147 - 27 May 2026

Abstract The current study comprehensively investigates Williamson nanofluid flow and transport in an asymmetric porous tapered channel under varying slip conditions, using both analytical and supervised machine learning approaches. This mathematical model integrates thermophoresis, Brownian motion, the Soret and Dufour effects, thermal radiation, and a transverse magnetic field to accurately describe thermosoluble transport phenomena relevant to biomedical contexts. The non-Newtonian Williamson formulation is used to explain how fluids, such as blood, dilute when sheared. Darcy resistance is used to describe porous structures in tissue scaffolds, capillary networks, and dialysis membranes. A perturbation method is used to… More >

Kiran Deep Singh¹, Prabh Deep Singh², Narinder Kaur³, Jawad Khan^4,*, Dildar Hussain⁵, Yeong Hyeon Gu^5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080915 - 27 May 2026

Abstract In smart healthcare systems, Image data of critical patients is essential in controlling and diagnosing the disease development. To acquire the medical images, traditional methods encountered the difficulty of generating cost-effective data. This research work introduces a novel and innovative approach to collect high-quality image data from individuals with atypical clinical presentations. Initially, a new Internet of Medical Things (IoMT) image collection architecture is introduced. This design uses edge intelligence and motion-static synergy to make it easier to record both coarse-grained and fine-grained patient images. This study introduces an image acquisition technique that leverages edge… More >

Roshana Mukhtar¹, Chuan-Yu Chang², Muhammad Asif Zahoor Raja^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079390 - 27 May 2026

Abstract Parkinson’s disease (PD) is a complex neurodegenerative disease associated with the accumulation of α-synuclein, which is linked to the dysfunctional ubiquitin–proteasome system. Fractional calculus has emerged as a powerful tool for modeling complex disease dynamics due to its promising features that inherently capture memory and hereditary effects. This paper presents a fractional-order Proteasome-Fibril interaction model (F-PFIM) for the dynamics of PD, represented by three fractional differential classes, showing concentrations of fibrils (F), proteasomes (P), and proteasome fibril complex (C). The three classes of the F-PFIM collectively make a controlling system that works for the clearance… More > Graphic Abstract

Yousra Abudaqqa^*, Zulaiha Ali Othman, Azuraliza Abu Bakar

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.079034 - 27 May 2026

Abstract Signal categorization is a critical component of the Dendritic Cell Algorithm (DCA), as it directly influences its anomaly detection capability. Conventional DCA implementations typically rely on heuristic or optimization-based approaches, such as Grouping Particle Swarm Optimization (GPSO), Grouping Genetic Algorithms (GGA), Principal Component Analysis (PCA), and Support Vector Machines (SVM), to determine mappings between input features and the three immunological signal categories: Pathogen-Associated Molecular Patterns (PAMP), Danger Signals (DS), and Safe Signals (SS). These approaches depend heavily on domain expertise and predefined rules, making the resulting signal mappings static and often dataset specific. Consequently, the… More >

Kalim Sattar¹, Malik Muhammad Saad Missen², Syeda Zoupash Zahra^1,3, Najia Saher⁴, Rab Nawaz Bashir^3,5,6,*, Oumaima Saidani⁷, Shahid Kamal⁵, Muhammad I. Khan⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.078569 - 27 May 2026

Abstract Tropical Cyclone (TC) genesis forecasting is an important aspect of early warning systems, as it allows the adoption of early warnings and mitigation plans. However, existing methods often rely on binary classification or fail to capture the complex spatio-temporal dependencies that govern TC formation. To address this limitation, this study introduces STAG-Net, a novel Spatio-Temporal Attention-Gated Network designed to directly predict the geographical coordinates of TC genesis. The model uses multivariate variables of meteorological factors such as u-wind, v-wind, relative humidity, temperature, and large-scale dynamic features using a Convolutional Neural Network (CNN), Gated Recurrent Units… More >

Jiaoyan Li¹, James D. Lee^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.077471 - 27 May 2026

Abstract The key points of micromorphic theory, including the balance laws and entropy principle, are briefly introduced. Maxwell’s equations and the Lorentz Transformation of E and B fields in both relativistic and non-relativistic electromagnetic theory are discussed. The link between the thermomechanical part and the electromagnetic part of the micromorphic electromagnetic theory is established through the body force, body moment, and energy source. The constitutive theory for thermo-visco-elastic-plastic-electromagnetic (TVEP-EM) materials is formulated. Then the constitutive relations are reduced to the materially linear constitutive equations. Onsager’s postulate is utilized for the derivation of viscosity. Return-Mapping-Algorithm is invoked for plasticity.… More >