Hui Sun^1,2, Jianwei Zhang^1,2, Wenbo Shi^1,2, Zhenhao Liu^1,2, Jianxin Xu^1,2,*, Hua Wang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.5, 2026, DOI:10.32604/fdmp.2026.080128 - 27 May 2026

Abstract Uniformity in solid-liquid mixing is a critical aspect for mass and heat transfer efficiency in multiphase reactors. This highlights the necessity for rigorous quantitative approaches capable of resolving spatial heterogeneity across multiple scales. In this work, a coupled discrete element method-volume of fluid (DEM-VOF) framework is employed to simulate the suspension dynamics of 20,000 particles, each 2 mm in diameter, within a liquid medium. To achieve a quantitative and multiscale characterization of three-dimensional particle distributions, Ripley’s L function, rooted in spatial statistics, is introduced and systematically applied. Its validity and robustness are further corroborated through… More >

Md Al Rifat Anan¹, Donghyeon Ryu², Yu-Lin Shen^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080371 - 27 May 2026

Abstract The development of surface wrinkles on thin films bonded to compliant substrates is recognized as a form of mechanical instability. While this wrinkling behavior is widely studied when the thin film is under direct compression, much less attention has been devoted to the prediction of wrinkle formation caused by tension and cyclic compression-tension deformations. This work focuses on compression vs. tension-induced wrinkles using a relatively stiff polymeric film on an elastomeric substrate as the model system. Experimental observations show that parallel wrinkles formed during unidirectional compression gradually disappear under reverse loading. When the thin film… More >

S. M. Anas^1,*, Rayeh Nasr Al-Dala’ien^2,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.081439 - 08 May 2026

Abstract This article has no abstract. More >

Sojin Shin¹, Guk Heon Kim², Seung Hwan Kim³, Jaemin Kim^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.079127 - 30 March 2026

Abstract This study develops a surrogate super-resolution (SR) framework that accelerates finite element method (FEM)-based computational fluid dynamics (CFD) using deep learning. High-resolution (HR) FEM-based CFD remains computationally prohibitive for time-sensitive applications, including patient-specific aneurysm hemodynamics where rapid turnaround is valuable. The proposed pipeline learns to reconstruct HR velocity-magnitude fields from low-resolution (LR) FEM solutions generated under the same governing equations and boundary conditions. It consists of three modules: (i) offline pre-training of a residual network on representative vascular geometries; (ii) lightweight fine-tuning to adapt the pretrained model to geometric variability, including patient-specific aneurysm morphologies; and… More >

Yuxin Tian¹, Wangxin Yu¹, Wanqing Yuan¹, Qingquan Liu^1,*, Xiaoliang Wang^1,2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.3, 2026, DOI:10.32604/cmes.2026.078776 - 30 March 2026

Abstract Granular flow, such as hopper discharge and debris flows, involves complex multi-scale, multi-phase, and multi-physics coupling, posing significant challenges for numerical simulation. Over the past two decades, methods like the Discrete Element Method (DEM), Smoothed Particle Hydrodynamics (SPH), and Depth-Averaging Method (DAM), have been developed to address these problems. However, their applicability across different scales remains unclear due to differences in physical assumptions and numerical algorithms. Therefore, a comprehensive evaluation is critically needed. This study selects three typical methods (DEM, SPH, and DAM) to examine their convergence behavior, boundary condition implementation, and limitations in physical More >

Evgenii V. Fomin^1,2, Ilya A. Bryukhanov¹, Natalya A. Grachyova², Alexander E. Mayer^2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2026.071952 - 10 February 2026

Abstract It is well known that aluminum and copper exhibit structural phase transformations in quasi-static and dynamic measurements, including shock wave loading. However, the dependence of phase transformations in a wide range of crystallographic directions of shock loading has not been revealed. In this work, we calculated the shock Hugoniot for aluminum and copper in different crystallographic directions ([100], [110], [111], [112], [102], [114], [123], [134], [221] and [401]) of shock compression using molecular dynamics (MD) simulations. The results showed a high pressure (>160 GPa for Cu and >40 GPa for Al) of the FCC-to-BCC transition.… 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

Miah A. Robinson, Abdulghani M. Abdulghani, Mokhles M. Abdulghani, Khalid H. Abed^*

Journal on Artificial Intelligence, Vol.7, pp. 615-632, 2025, DOI:10.32604/jai.2025.073535 - 01 December 2025

Abstract Ensuring the safety of Artificial Intelligence (AI) is essential for providing dependable services, especially in various sectors such as the military, education, healthcare, and automotive industries. A highly effective method to boost the precision and performance of an AI agent involves multi-configuration training, followed by thorough evaluation in a specific setting to gauge performance outcomes. This research thoroughly investigates the design of three AI agents, each configured with a different number of hidden units. The first agent is equipped with 128 hidden units, the second with 256, and the third with 512, all utilizing the… More >

Xiao Li^*, Junxiang Liu, Weinan Fan, Shiying Xu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.1, pp. 1-2, 2025, DOI:10.32604/icces.2025.012284

Abstract Flooding is one of the most common types of natural hazards leading to wide-spread disturbances and damages to human communities and natural environment across the world. Flood forecasting is an effective means to provide timely hazard information to relevant government decision-makers and practitioners as well as those residents at risk, which plays an important role in flood risk reduction. A complete flood forecasting system normally includes at least two components, that is precipitation predictions and a hydrological or hydraulic model for flooding processes simulation. However, the current flood forecasting especially for urban floods face obvious… More >

Dan Xu^1,2, Chuanfu Luo^1,2,3,*

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 2807-2818, 2025, DOI:10.32604/cmc.2025.069471 - 23 September 2025

Abstract The crystallization behavior of polymers is significantly influenced by molecular chain length and the dispersion of varying chain lengths. The complexity of studying crystallization arises from the dispersity of polymer materials and the typically slow cooling rates. Recent advancements in fast cooling techniques have rendered the investigation of polymer crystallization at varying cooling rates an attractive area of research; however, a systematic quantitative framework for this process is still lacking. We employ a coarse-grained model for polyvinyl alcohol (CG-PVA) in molecular dynamics simulations to study the crystallization of linear polymers with varying chain lengths under… More >