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

Zuokun Yang¹, Jun Li^1,2,*, Xin Lai^1,2, Lisheng Liu^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.075980 - 29 January 2026

Abstract Peridynamics (PD) demonstrates unique advantages in addressing fracture problems, however, its nonlocality and meshfree discretization result in high computational and storage costs. Moreover, in its engineering applications, the computational scale of classical GPU parallel schemes is often limited by the finite graphics memory of GPU devices. In the present study, we develop an efficient particle information management strategy based on the cell-linked list method and on this basis propose a subdomain-based GPU parallel scheme, which exhibits outstanding acceleration performance in specific compute kernels while significantly reducing graphics memory usage. Compared to the classical parallel scheme,… More >

Abdulaziz Almalaq¹, Ambe Harrison^2,*, Ibrahim Alsaleh¹, Abdullah Alassaf¹, Mashari Alangari¹

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074815 - 29 January 2026

Abstract We present a computer-modeling framework for photovoltaic (PV) source emulation that preserves the exact single-diode physics while enabling iteration-free, real-time evaluation. We derive two closed-form explicit solvers based on the Lambert W function: a voltage-driven V-Lambert solver for high-fidelity I–V computation and a resistance-driven R-Lambert solver designed for seamless integration in a closed-loop PV emulator. Unlike Taylor-linearized explicit models, our proposed formulation retains the exponential nonlinearity of the PV equations. It employs a numerically stable analytical evaluation that eliminates the need for lookup tables and root-finding, all while maintaining limited computational costs and a small… More >

Hyeon-Sik Choi¹, Min Kyu Kim¹, Jiuk Shin², Thomas H.-K. Kang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.074029 - 29 January 2026

Abstract Unbonded post-tensioned (PT) concrete systems are widely used in safety-critical structures, yet modeling practices for prestress implementation and tendon-concrete interaction remain inconsistent. This study investigates the effects of sheath (duct) implementation and confinement assumptions through nonlinear finite element analysis. Four modeling cases were defined, consisting of an explicit sheath without tendon-concrete confinement (S) and three no-sheath variants with different confinement levels (X, N, A). One-way beams and two-way panels were analyzed, and panel blast responses were validated against experimental results. In both beams and panels, average initial stress levels were similar across models, through local More >

Zia Ur Rahman¹, Nigar Ali^1,2, Dragan Pamucar³, Imtiaz Ahmad^1,2, Haci Mehmet Baskonus^2,*, Naseer Ul Haq¹, Zeeshan Ali⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.070268 - 29 January 2026

Abstract Hepatitis B Virus (HBV) infection and heavy alcohol consumption are the two primary pathogenic causes of liver cirrhosis. In this paper, we proposed a deterministic mathematical model and a logistic equation to investigate the dynamics of liver cirrhosis progression as well as to explain the implications of variations in alcohol consumption on chronic hepatitis B patients, respectively. The intricate interactions between liver cirrhosis, recovery, and treatment dynamics are captured by the model. This study aims to show that alcohol consumption by Hepatitis B-infected individuals accelerates liver cirrhosis progression while treatment of acutely infected individuals reduces… More >

Nur Afikah Juhari, Khairul Nizam Tahar^*

Revue Internationale de Géomatique, Vol.35, pp. 1-11, 2026, DOI:10.32604/rig.2026.070991 - 19 January 2026

Abstract The use of Unmanned Aerial Vehicles (UAVs) in photogrammetry has grown rapidly due to enhanced flight stability, high-resolution imaging, and advanced Structure from Motion (SfM) algorithms. This study investigates the potential of UAVs as a cost-effective alternative to Terrestrial Laser Scanners (TLS) for 3D building reconstruction. A 3D model of Bangunan Sarjana was generated in Agisoft Metashape Professional v.2.0.2 using 492 aerial images captured at flying altitudes of 40, 50, and 60 m. Ground control points were established using GNSS (RTK-VRS), and Total Station measurements were employed for accuracy validation. The results indicate that the 60 More >

Rayeesa Mehmood^*, Sergei Koltcov, Anton Surkov, Vera Ignatenko

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072735 - 12 January 2026

Abstract Activation pruning reduces neural network complexity by eliminating low-importance neuron activations, yet identifying the critical pruning threshold—beyond which accuracy rapidly deteriorates—remains computationally expensive and typically requires exhaustive search. We introduce a thermodynamics-inspired framework that treats activation distributions as energy-filtered physical systems and employs the free energy of activations as a principled evaluation metric. Phase-transition–like phenomena in the free-energy profile—such as extrema, inflection points, and curvature changes—yield reliable estimates of the critical pruning threshold, providing a theoretically grounded means of predicting sharp accuracy degradation. To further enhance efficiency, we propose a renormalized free energy technique that More >

Ishaani Priyadarshini^*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072343 - 12 January 2026

Abstract Early and accurate detection of bone cancer and marrow cell abnormalities is critical for timely intervention and improved patient outcomes. This paper proposes a novel hybrid deep learning framework that integrates a Convolutional Neural Network (CNN) with a Bidirectional Long Short-Term Memory (BiLSTM) architecture, optimized using the Firefly Optimization algorithm (FO). The proposed CNN-BiLSTM-FO model is tailored for structured biomedical data, capturing both local patterns and sequential dependencies in diagnostic features, while the Firefly Algorithm fine-tunes key hyperparameters to maximize predictive performance. The approach is evaluated on two benchmark biomedical datasets: one comprising diagnostic data… More >

Sarah M. Alhammad¹, Diaa Salama AbdElminaam^2,3,*, Asmaa Rizk Ibrahim⁴, Ahmed Taha²

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.069263 - 12 January 2026

Abstract Accurate parameter extraction of photovoltaic (PV) models plays a critical role in enabling precise performance prediction, optimal system sizing, and effective operational control under diverse environmental conditions. While a wide range of metaheuristic optimisation techniques have been applied to this problem, many existing methods are hindered by slow convergence rates, susceptibility to premature stagnation, and reduced accuracy when applied to complex multi-diode PV configurations. These limitations can lead to suboptimal modelling, reducing the efficiency of PV system design and operation. In this work, we propose an enhanced hybrid optimisation approach, the modified Spider Wasp Optimization… More >

Kai Gui^1,#, Tianyi Yang^1,#, Chengying Xiong¹, Yue Wang¹, Zhiqiang He¹, Wuxian Li^2,3,*, Min Tang^1,*

Oncology Research, Vol.34, No.1, 2026, DOI:10.32604/or.2025.070143 - 30 December 2025

Abstract Objectives: The mechanism by which specific tumor subsets in colorectal cancer (CRC) use alternative metabolic pathways, particularly those modulated by hypoxia and fructose, to alter the tumor microenvironment (TME) remains unclear. This study aimed to identify these malignant subpopulations and characterize their intercellular signaling networks and spatial organization through an integrative multi-omics approach. Methods: Leveraging bulk datasets, single-cell RNA sequencing, and integrative spatial transcriptomics, we developed a prognostic model based on hypoxia-and fructose metabolism-related genes (HFGs) to delineate tumor cell subpopulations and their intercellular signaling networks. Results: We identified a specific subset of stanniocalcin-2 positive (STC2+)… More > Graphic Abstract